Name: ssvep-based experimental procedure for brain-robot interaction with humanoid robots
Uploaded: 2015-11-24T15:00:00.000+00:00
Duration: 11 min 1 s
Description: Watch this Scientific Journal Video about SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots at JoVE.com

<p class="jove_content"> Yazarlar bu yazıda bildirilen deneyler yaptığı yardım için Bay Hong Hu şükranlarını ifade etmek istiyorum. Bu çalışma Çin Ulusal Doğa Bilim Vakfı (No 61473207) tarafından kısmen desteklenmiştir. </p>

<p class="jove_title"> 1. EEG Sinyallerini Edinme </p><ol><li> Konuya deneysel prosedür açıklayın ve deneyler katılmaya yazılı bilgilendirilmiş onam edinin. </li><li> Bir mezura kullanarak konu kafa çevresini ölçün ve ölçüm yakın EEG kap boyutunu seçin. Elektrotlar düzenleme &quot;Uluslararası 10-20 Sistemi&quot; <sup>12</sup> dayanmaktadır. </li><li> Nasion ve inion arasındaki mesafeyi ölçün. Kapağı hizalanması için referans olarak mesafe% 10 işaretlemek için bir cilt işaretleyici kalem kullanın ve öznenin kafa derisi üzerinde tepe olarak mesafenin orta noktası işaretleyin. </li><li> FP1 ve FP2 elektrotlar orta noktası% 10 işaretini hizalayarak konuyla ilgili EEG kapağını yerleştirin. Verteksteki kapağın Taşlı pozisyonu elektrot. </li><li> Fz, Cz, Pz ve Oz başın orta hat üzerinde olduğundan emin olun ve orta hat her iki tarafında bulunan elektrot her çifti bir yatay çizgi olduğunu. </li><li>Iletken jel ile REF1 ve REF2 elektrotları sürün. Tıbbi bant kullanarak sağ ve sol mastoide referans elektrotlar yerleştirin. Chinstrap sıkın. </li><li> Elektrot tutucu bir künt uçlu şırınga yerleştirin ve aşağıdaki sırayla her bir elektrodun içine iletken jel enjekte: Birincisi, alnına ve &quot;toprak&quot; elektrot ikinci, O2, O1, Oz, Pz deneyde kullanılan beş elektrotlar ve Taşlı. </li><li> Bir uyarıcı monitörün önünde rahat bir sandalye 60 cm konuyu Seat. Monitörün merkezi ile aynı yatay seviyede onun / onun gözlerini tutmak için konuyu söyleyin. </li><li> EEG veri toplama sistemine elektrot kablolarını bağlayın. 1 kHz örnekleme hızı yapılandırın. </li><li> Özel DPC EEG sinyal kalitesini inceleyin. Belirli bir elektrot ile ilgili bir sorun varsa, yeniden enjekte jel kanalının empedansını ayarlamak için. </li><li> 4,615, 12, 15 ve 20 frekanslarda dört robot görüntüleri titreşmeye adanmış SPC kullanınKullanıcı Arabirimi görsel uyaranlar olarak Hz <strong>Şekil 2&#39;de</strong> görüldüğü gibi. </li></ol><p class="jove_title"> 2. Çevrimdışı Analiz SSVEP Özellikleri </p><ol><li> Her konu için çevrimdışı eğitim deneyleri 32 denemeler yapmak ve bu süreç boyunca EEG sisteminden alınan beyin sinyallerini kaydeder. <br /> NOT: Bu işlem sadece kendi SSVEP özelliği vektörleri kurmak ve sınıflandırıcı eğitmek için deney ilk kez bireyler tarafından yapılır. </li><li> Deneme başladığında, rastgele hedef olarak tek uyaran seçin ve üstündeki sarı ok görüntüler. </li><li> 1 sn sonra 5 saniye boyunca Kullanıcı Arabirimi üzerinde farklı frekanslarda dört görsel uyaranlara titreme. </li><li> Minimumda onun / onun vücut hareketini tutarken seçilen uyaran hedefe odaklanmak konuyu isteyin. </li><li> Her deneme sonra, dinlenmek konu 3 saniye ver, sonra bir sonraki deneme başlatın. </li><li> Tüm çalışmalar bittiğinde, kaydedilen veri okumak. 3 sn veri çığır olmak Özü<html> ara 2 sn ve her denemede hedef olarak bir uyarıcı seçer tetik sonra 5 sn. </li><li> MATLAB komut Offline Veri Analyzer kullanarak veri dönemini güç spektrumu yoğunluğu (PSD) hesaplayın. Aşağıda ayrıntılı olarak tarif işleme algoritması kullanın: <ol><li> Referans veri ile çok kanallı EEG verilerinin kanonik korelasyon analizi (CCA) katsayıları hesaplayın. CCA altta yatan korelasyon <sup>13</sup> bulmak için iki veri seti için kullanılan bir çok değişkenli istatistiksel bir yöntemdir. Çok kanallı EEG verileri <em>X ve</em> referans verileri aynı uzunlukta <em>Y</em> 3s segmenti göz önüne alındığında, <em>X = X <sup>T</sup> W <sub>x ve y</sub> = Y <sup>T</sup></em> arasındaki <em>ρ</em> korelasyon katsayısının üst düzeye çıkarmak için, ağırlık vektörleri, <em>W <sub>x ve y</sub> W</em> bulmak için kullanımı CCA <em><sub>y</sub> W.</em> Belirli uyaran frekanslarda periyodik sinyalleri referans verileri ayarlayın. <br />/ftp_upload/53558/53558eq1.jpg &quot;/&gt; <br /> burada <em>f <sub>1,</sub> f <sub>2, 3</sub> f, <sub>4</sub></em> dört görsel uyaranın özelliği frekansları <em>f.</em> </li><li> Mekansal referans veri doğrusal kombinasyonu ile en belirgin ilişki vardır bir tek boyutu süzülmüş veri <em>x,</em> elde etmek için hesaplanan CCA katsayıları <em>W <sub>x</sub></em> kullanarak çok kanallı EEG verisi <em>X</em> filtre. </li><li> Hızlı Fourier Dönüşümü (FFT) kullanan uzamsal biçimde filtre edilmiş veriler <em>x</em> PSD hesaplayın. <br /><img alt="Denklem 2" src="/files/ftp_upload/53558/53558eq2.jpg" /><br /> <em>N <sub>FFT</sub></em> örnek veri <em>x</em> boyutu ve FFT burada <em>(x, N <sub>FFT)</sub> N <sub>FFT</sub></em> -Point ayrık Fourier dönüşümü <em>x</em> döndürür. </li><li> 3 ve 30 Hz arasındaki ortalama değer bakımından PSD Normale. <br /><img alt="Denklem 3" src="/files/ftp_upload/53558/53558eq3.jpg" /><br /> nerede60; <img alt="Denklem 3 Payda" src="/files/ftp_upload/53558/53558eq3denominator.jpg" /> 3 ve 30Hz arasındaki güç spektrumunun ortalamasını gösterir. </li></ol></li><li> Dört uyaran frekanslar için sınıflandırma parametrelerini ayarlayın. İlk olarak, uyarıcı hedefine karşılık normalize PSD spektrumu gözlemlemek ve el özellik sıklığı gibi güçlü PSD genlikli frekans yapılandırın. İlgili uyaran hedef olarak seçildiğinde tek elde edilir, ve hedef olmayan uyaranlara seçildiğinde diğer elde edilir: özellik frekansına dayanarak, iki takım halinde normalize PSD verileri bölün. Sırasıyla kurulan her ortalama değerini hesaplayın. Hedef ve hedef olmayan <sup>14</sup> setleri sınıflandırmak için iki ortalama değerlerin ortanca tarafından eşiğini belirler. </li></ol><p class="jove_title"> 3. Online İşlem Beyin Sinyalleri </p><ol><li> B <strong>geliştirilmiştir, Şekil 3</strong> de gösterildiği gibi online Sinyal İşlemcisi açonline işlem beyin sinyalleri için DPC üzerinde OpenViBE ortamı ve MATLAB komut, üzerinde ased. </li><li> Çift OpenViBE ayarı penceresini açmak için, <strong>Şekil 3&#39;te</strong> kırmızı döngüsü ile işaretlenmiş Edinme ve Süreç Sinyal kutusunu tıklatın. Konu için sınıflandırma parametrelerini yapılandırın. Çevrimdışı analiz sonuçlarına göre 1 kHz olarak örnekleme oranını ayarlamak, 3 saniye olarak FFT zaman uzunluğunu ayarlayın ve özellik frekanslarını <em>ayarlamak, örneğin</em> 4,667, 24, 15 ve 20 Hz . </li><li> Üç adımda aşağıdaki algoritmayı kullanarak gerçek zamanlı verileri işler Çevrimiçi Sinyal İşlemci, çalıştırmak için başlatır düğmesini tıklatın. </li><li> İlk olarak, algoritma kanalları Oz, O1, O2, Pz ve EEG sisteminin her 0.5s arasında CPZ gelen EEG verilerini satın aldı ve çevrimiçi işlem için son 3s veri kesimini ayıklar. </li><li> İkincisi, algoritma aşama 2.7&#39;de açıklanan algoritmalar kullanarak 3-sn veri segmenti işler ve sınıfla için gerçek zamanlı PSD hesaplaryon. </li><li> Üçüncü olarak, algoritma dört özellik frekanslarda PSD genliklerine göre beyin desenleri sınıflandırır. Tek özellik frekans genlik verilen eşiğin üstünde olduğunda, SSVEP hedef olarak karşılık gelen frekansta titreşen uyaran sınıflandırır. </li></ol><p class="jove_title"> 4. İnsansı Robot Bağlanması </p><ol><li> İnsansı robot Göğüs düğmesine basın ve başlatmak için bekleyin. <br /> NOT: Bu işlem yaklaşık 1 dakika sürer ve Göğüs düğmesi beyaz olurken robot &quot;OGNAK GNOUK&quot; diyor tamamlandı. </li><li> DPC <sup>15</sup> olan Wireless Fidelity (WiFi) bağlantısı kurun. </li><li> Robot Denetleyicisi DPC Visual C ++ komut programlanmış a açın. Kumanda robot komutları içine çevirir, Virtual Reality-Periferik Ağı (VRPN) arabirimi üzerinden online Sinyal İşlemcisi sınıflandırma sonuçlarını alır ve humanoi karşılık gelen davranışları kontrolkablosuz bağlantı üzerinden d robotu. </li><li> Olabilir robot davranışlarının üç set tanımlayan kendi WiFi bağlantı göre robotun IP adresini girerek Robot Kontrolörü yapılandırma kolaylıkla üç farklı görevleri gerçekleştirmek için açık ve (bu davranışların icra parametreleri <em>ayarlayarak, örneğin.,</em> Yürüme hızı veya mesafe) görev gereksinim uyacak şekilde. <br /> NOT: Bu davranışların daha fazla detay adımlarla 5.2.1, 5.3.1, 5.4.1 ve tarif edilmektedir. </li><li> Robot Denetleyicisi çalıştırmak için Visual Studio platformunun Oluştur düğmesini tıklatın. </li><li> SPC üzerinde Choregraphe programını açın. Düğmesini tıklatın Bağlantı Widget açılır &quot;bağlan&quot;. IP adresine göre kontrol edilecek robot seçin ve çift ona bağlanmak için simgesini tıklatın. </li><li> Choregraphe Menü çubuğundaki görünüm menüsünden video monitörü açın ve robotun kameradan canlı video geribildirim görüntülemek için kullanıcı arabirimi önüne monitörü taşıyın. </li></ol> &lt;p class = &quot;jove_title&quot;&gt; 5. Kapalı çevrim kontrol Deneyleri yapılması </p><ol><li> Beyin-robot etkileşimi performansını değerlendirmek için farklı ortamlar içinde üç özel kapalı çevrim kontrol görevleri gerçekleştirmek için konuyu isteyin. <br /> NOT: günlük hayatlarında engelli ve yaşlı yardımcı yararlı çünkü robotik uygulamalarda önemli olan bu görevler, farklı robot davranışları etkinleştirmeniz gerekir. </li><li> <strong>Şekil 4&#39;te</strong> gösterildiği gibi, engellerin üzerinden yürümek ve ışığı açmak için bir ışık anahtarı itmek için beyin sinyalleri aracılığıyla insansı robot kontrolü TelePresence ilk kapalı çevrim kontrol görevi yürütün. <ol><li> İlk görevi başarmak üzere dört SSVEP uyaranlarla kodlanmış robot davranışlarını kontrol etmek için: 0.15 m sabit mesafe ile ileri adım 0.3 rad sabit radyan ile sola dönülerek, sağ 0.3 rad sabit radyan ile dönerek, ve onun sağ elini kullanarak anahtarı iterek. <br /> NOT: ayarlayation işlem aşamasında 4,4 tarif edilmektedir. </li><li> Görev hedefi konusunu ve dört davranışları bilgilendirin kontrol edilecek. </li><li> Adımlar 4,5-4,7 olarak Robot denetleyicisi çalıştırın ve deney başlar. Çevreyi algılama ve canlı video yorumlarına dayanarak kararlar ve ilgili uyaranlara bakarak robot davranışları etkinleştirmek için konuyu özgürlük verin. <br /> . NOT: Acil <em>durumlarda,</em> örn, robot bir engel ile çarpışmak üzere olmadıkça hiçbir talimat veya yardım konusuna önem verilmelidir. </li></ol></li><li> Yoldan geçenleri Ne zaman karşı karşıya <strong>Şekil 5&#39;te</strong> gösterildiği gibi, çıkış işareti aşağıdaki merdiven doğru yürümeye beyin sinyalleri aracılığıyla insansı robot kontrolü TelePresence ikinci görevi yürütün., Say &quot;pardon&quot; ve beklemek robotu kontrol etmek konuyu sormak geçenler yol vermek için. <ol><li> Continuousl ileri yürüyüş: dört SSVEP uyaranlara tarafından kodlanan robot davranışlarını kontrol0,05 m / s bir hızda y 0.1 rad / sn bir hızda hemen sürekli dönerek ve yürüyüş davranışları durdurma 0.1 rad / sn bir hızda sürekli sola dönerek. </li><li> Duruş bağlı kontrol fonksiyonu <sup>16</sup> Robot Kontrol Anahtarı. <br /> NOT: robot yürürken bu fonksiyon yürüyüş davranışları durdurma emri olarak dördüncü uyaran kullanır; Robot yürürken değilken, bu &quot;pardon&quot; demek robotu kontrol etmek dördüncü uyarıcı kullanır. Fonksiyon robotun yürüme durumunu tespit ederek C ++ komut uygulanmaktadır. </li><li> Görev hedefi konusunu ve beş davranışları bilgilendirin kontrol edilecek. </li><li> Aşama 5.2.3 de açıklandığı gibi, Robot Kontrolörü çalıştırın ve deney başlar. </li></ol></li><li> <strong>Şekil 6&#39;da</strong> gösterildiği gibi, onu almaya ve deneğin elinin teslim etmek, bir balon hedefe doğru yürümeye insansı robot kontrolü TelePresence için üçüncü görevi Davranış. <ol><li> Dört SSVEP uyaranlara tarafından kodlanan robot davranışlarını kontrol: 0,15 m sabit mesafe ile öne çıkarak, 0.3 rad sabit radyan sol 0,3 rad sabit radyan ile doğru dönerek, ve nesneleri toplayıp dönülerek. </li><li> Zaten kaldırdı edildiğinde nesneyi koyarak emri olarak dördüncü uyaran yeniden Robot denetleyicisi duruş bağlı kontrol fonksiyonunu etkinleştirin. </li><li> Görev hedefi konusunu ve beş davranışları bilgilendirin kontrol edilecek. </li><li> Aşama 5.2.3 de açıklandığı gibi, Robot Kontrolörü çalıştırın ve deney başlar. </li></ol></li></ol>

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<p class='jove_content'>The authors have nothing to disclose.</p>

<p class="jove_content"> Bu yazıda birden fazla yazılım programlarını entegre ederek insansı robotlar beyin-robot etkileşimi sistemi kurmak için bir SSVEP tabanlı deneysel prosedür sunar. İnsan niyet gerçek zamanlı EEG sinyallerini yorumlayarak algılanan olduğundan, deney yapmadan önce elektrot bağlantıları ve EEG sinyal kalitesini doğrulamak için kritik öneme sahiptir. Tüm elektrotlar elde edilen sinyaller kötü nitelikleri ise, ilk zemin ve referans elektrotlar bağlantısını kontrol etmek gereklidir. Elektrotların parçaları ile ilgili sorunlar varsa, bu kanalların empedansı ayarlamak için iletken jel yeniden enjekte edilir. </p><p class="jove_content"> EEG sinyalleri elde edilirken bir başka ortak sorunu eserler girişim ve <sup>17</sup> gürültüsü. EEG sinyal gürültü oranı (SNR), parazit ve gürültü SSVEP yanıtları PSD kolayca belirsiz değişiklikler küçük bir sinyal olduğu gibi. Bu pow uzak EEG sisteminin sinyal amplifikatörü tutmak önemlidirer temini ve diğer gürültü kaynakları. Deney sırasında, göz kırpma ve vücut hareketleri giren fazladan unsurların düşürüleceği minimumda tutulmalıdır. Ayrıca bu tür girişimlere karşı sağlamlığını artırmak için, bizim yöntem çok kanallı EEG verileri yorumlamak için bir CCA tabanlı tekniği kullanır. Sonuçlar, bu tekniğin sesler ve eserler içeren EEG sinyallerinden özellikleri ayıklanması etkili olduğunu göstermektedir. </p><p class="jove_content"> Insansı robotlar kapalı döngü kontrolü yeni bir görev başlamak için, elle yeni görev gereksinim uyacak şekilde her robot davranışlarının tanımı ve parametre yapılandırmanız gerekir. Bu akım, BRI sisteminde mevcut kontrol komutlarının sınırlı sayıda kaynaklanmaktadır ve bu nedenle beyin kalıpların daha fazla türde harekete geçirilmesi ile geliştirilebilir. <em>Hwang</em> ve ark. <sup>18</sup> daha fazla görsel uyaranlar üretilmesi için bir çift frekanslı uyarım yöntemi önerilmiştir. <em>Wang</em> ve <em>arkadaşları.</em> <sup>19,</sup> Allison <em>ve ark.,</em> <sup>20,</sup> Pan <em>ve ark.,</em> <sup>21,</sup> ve Li &lt;em&gt; ve ark., <sup>22</sup> ERP ve MI dahil olmak üzere diğer beyin desenleri ile SSVEP tabanlı bir model birleştirmek için çeşitli yöntemler hibrit önerdi. Aynı zamanda makine öğrenmesi veya sınırlı beyin kalıplarını <sup>23</sup> kullanılarak insansı robot tam vücut hareketini kontrol etmek için hiyerarşik mimarisine dayanan anahtarlama teknikleri benimsemeye mümkündür. </p><p class="jove_content"> LCD monitör <sup>24 ve</sup> SSVEPs <sup>25</sup> harmonik bileşenleri arasındaki etkisi mevcut yanıp sönen frekansları göz önüne alındığında, biz 1&#39;den 60 Hz ve dört frekansları kullanarak bulundu <em>yani.,</em> 4,615, 12, 15 ve 20 tüm olası yanıp sönen frekansları taranmış onlar bizim konularda en yüksek ortalama doğruluk oranı elde olarak Hz iyi seçimdir muhtemeldir. Bu nedenle, biz mümkün en nesneleri, sola dönülerek, ileri yürürken sağa dönerek ve yürüyüş durdurma / anahtarını iterek / toplayıp dahil insansı robot davranışlarını, kontrol arayüzünde dört uyaranlara kullanılırBu yazıda sunulan görevleri yerine getirmek için bir insansı robot kontrol etmek ough. </p><p class="jove_content"> Böyle OpenViBE, Choregraph, Merkezi yazılım ve C kullanıcı geliştirilen programların ++ ve MATLAB gibi çoklu yazılım programları, entegre tarafından geliştirilen olarak BRI sisteminin avantajları güvenilirlik ve esneklik vardır. Bu standart yazılımı kullanarak farklı deneysel prosedürler tasarımı için verimli ve güvenilir olduğunu. Sistemimiz insansı robot ile beyin-robot etkileşimi için yeni algoritmalar ve teknikler araştırmak için güçlü bir araçtır. Kolayca hasta ve yaşlı, ve sahne sağlıksız ve tehlikeli işler yardımcı BRI uygulamaları keşfetmek için yükseltilebilir. </p>

<p class="jove_content"> Beyin-Robot Etkileşimi insan ve beyin sinyalleri yoluyla robotik cihaz arasında bir yenilikçi iletişim yolu sağlar (BRI), günlük yaşamlarında <sup>1,2</sup> engelli yardımcı prospektif olduğunu. Çeşitli yöntemler oluşturmak için vb elektrokortikografi (ECOG), elektroansefalografi (EEG), fonksiyonel manyetik rezonans görüntüleme (fMRI) gibi, ya invaziv veya non-invaziv en sık kullanılan non-invaziv bir yöntem beyin sinyallerini elde edebiliyoruz BRI sistem kafa derisi üzerine yerleştirilen elektrotlar EEG sinyallerini elde etmektir. Bu yöntem, pahalı olmayan bir kullanımı kolaydır, ve kabul edilebilir bir zamansal çözünürlüğü <sup>3</sup> içerir. Onlar insanların günlük geçmesi aynı fiziksel ve zihinsel görevlerin bazıları taklit oluşturulan olarak robotik cihazlar çeşitli arasında, insansı robotlar ileri seviyededir. Insansı robot ile BRI hasta ve yaşlı yardımcı, hem de sağlıksız ve tehlikeli görevlerini yerine getirirken önemli bir rol oynayacaktır. Ama kontroltam vücut hareketi ile insansı robot gibi kişisel yardım <sup>4, 5</sup> gibi karmaşık görevleri yerine getirmek için geliştirilmiştir olarak BRI sistemi aracılığıyla bir insansı robot, son derece zordur. </p><p class="jove_content"> Kararlı Hal Görsel Uyarılmış Potansiyel (SSVEP) Belli bir frekansta <sup>6</sup> görsel uyaranın modülasyonu ile uyarılmış beyin sinyalinin bir türüdür. Bu titreşen uyaran temel ve harmonik frekanslarda sinüzoidlerde içerir ve belirgin kafa derisi <sup>7</sup> oksipital bölgede görsel korteks boyunca görünür. SSVEP sinyallerini seçilmesinin sebebi SSVEP merkezli BRI sistem nispeten yüksek bilgi aktarım hızı verir ve daha az eğitim <sup>8</sup> gerektirir. Bu tür olaya ilişkin potansiyeller (OİP) <sup>9</sup> veya motor görüntüleri (MI) <sup>10</sup> potansiyelleri olarak beyin dalgalarını diğer türleri, aynı zamanda bu deneysel prosedür içine gömülü olabilir. </p><p class="jove_content"> İnsansı beyin-robot etkileşimini Bizim prosedürrobotlar Cerebot dayanmaktadır - bir zihin kontrollü insansı robot platformu - EEG veri toplama sistemi ve bir insansı robot <sup>11</sup> oluşmaktadır. EEG sistemi, ön işlem ve elektrotların çeşitli edindiği ekran biyo-potansiyel sinyallerini kayıt yapabiliyor. Birden fazla analog I / O ve dijital I / Os sağlar ve 16-bit çözünürlük ile 30 kHz örnekleme hızında anda 128 sinyal kanala kadar kayıt yeteneğine sahiptir. C ++ ve MATLAB Onun yazılım geliştirme kitleri kullanıcıların deneysel prosedürler tasarlamak için kolaydır. Insansı robot serbestlik 25 derece vardır ve 2 kameralar, mikrofonlar 4, 2 sonar rangefinders, 2 IR vericiler ve alıcılar, 1 eylemsizlik kurulu, 9 dokunsal sensörleri ve 8 basınç sensörleri de dahil olmak üzere çoklu sensör ile donatılmıştır. Bu oluşturma ve düzenleme hareketleri ve interaktif robot davranışları Choregraphe ve C ++ SDK sağlar. </p><p class="jove_content"> Bu yöntemin genel amacı bir SSVEP tabanlı deneysel proce kurmakdure insansı robotlar <sup>11</sup> ile beyin robot etkileşim çalışması sağlamak için, örneğin OpenViBE, Choregraph, Merkezi yazılımı gibi birden fazla yazılım programlarının yanı sıra C ++ ve MATLAB yazılı kullanıcı geliştirdiği programlar entegre ederek. <strong>1</strong> sistem yapısını <strong>göstermektedir.</strong> Özel uyaran sunum bilgisayar (SPC) görsel uyaranlara, talimatlar ve çevre yorumlarından konuyu sunmak için Kullanıcı Arayüzü görüntüler. Özel bilgi işlem bilgisayar (DPC) çevrimdışı eğitim sürecinde Veri Kaydedici ve Offline Veri Analyzer çalışır ve Online Sinyal İşlemci ve insansı robot online kontrolü için Robot Kontrol çalışır. Diğer SSVEP tabanlı kontrol sistemleri ile karşılaştırıldığında, bizim sistem yeniden ve böyle OpenViBE, Choregraph, Merkezi yazılımı gibi standartlaştırılmış yazılım paketleri, bir dizi entegre tarafından geliştirilen olarak yükseltilmiş ve olması daha esnek, daha güvenilir ve özellikle daha uygundur Modüller C ++ ile yazılmışve MATLAB. </p><p class="jove_content"> Aşağıdaki prosedür gözden ve Tianjin tıbbi üniversite genel hastane etik kurulu tarafından onaylandı ve tüm denekler yazılı onayını vermiş oldu. </p>

<table><tbody><tr><td>Cerebus EEG Data Acquisition System</td><td>Blackrock Microsystems</td><td>4176-9967</td><td></td></tr><tr><td>NAO humanoid robot</td><td>Aldebaran Robotics</td><td>H25</td><td></td></tr><tr><td>EEG cap</td><td>Neuroscan</td><td>8732</td><td></td></tr><tr><td>Ten20 Conductive gel</td><td>Weaver and company</td><td>10-20-8</td><td></td></tr></tbody></table>

ssvep-based experimental procedure for brain-robot interaction with humanoid robots

<p class='jove_content'>Brain-Robot Interaction (BRI), which provides an innovative communication pathway between human and a robotic device via brain signals, is prospective in helping the disabled in their daily lives. The overall goal of our method is to establish an SSVEP-based experimental procedure by integrating multiple software programs, such as OpenViBE, Choregraph, and Central software as well as user developed programs written in C++ and MATLAB, to enable the study of brain-robot interaction with humanoid robots.</p>
<p class='jove_content'>This is achieved by first placing EEG electrodes on a human subject to measure the brain responses through an EEG data acquisition system. A user interface is used to elicit SSVEP responses and to display video feedback in the closed-loop control experiments. The second step is to record the EEG signals of first-time subjects, to analyze their SSVEP features offline, and to train the classifier for each subject. Next, the Online Signal Processor and the Robot Controller are configured for the online control of a humanoid robot. As the final step, the subject completes three specific closed-loop control experiments within different environments to evaluate the brain-robot interaction performance.</p>
<p class='jove_content'>The advantage of this approach is its reliability and flexibility because it is developed by integrating multiple software programs. The results show that using this approach, the subject is capable of interacting with the humanoid robot via brain signals. This allows the mind-controlled humanoid robot to perform typical tasks that are popular in robotic research and are helpful in assisting the disabled.</p>

<p class="jove_content" fo:keep-together.within-page="1"> Burada sunulan sonuçlar, erkek konusu düzeltilmiş-to normal olan elde edilen bir versiyonu. <strong>Şekil 7,</strong> uzamsal olarak CCA katsayıları kullanılarak verilerin filtre edilmesi, çok kanallı bir veri Epoch <strong>(Şekil 7A)</strong> ekstre dahil olmak üzere işleme EEG veri prosedürü gösterir <strong>(Şekil</strong> 7B) ve normalize PSD <strong>(Şekil 7C)</strong> hesaplanması. </p><p class="jove_content" fo:keep-together.within-page="1"> <strong>Şekil 8</strong> normalize PSD konu farklı frekanslarda titreşen hedeflere baktı ki tek denemeler kullanılarak elde gösterir. Belirgin tepe titrek uyaran temel veya harmonik frekans belirir. BRI sistemi farklı robot davranışlarının kontrolü için komutlar içine SSVEP yanıtları bu kalıpları eşler. </p><p class="jove_content" fo:keep-together.within-page="1"> <strong>4-6</strong> üç kapalı döngü devam uyarıcısı gösteriyor <strong>Rakamlar</strong>rol görevleri beyin robot etkileşimi performansını değerlendirmek için seslendirdi. Bu görevler robotik araştırmalarda popüler ve günlük hayatlarında engelli ve yaşlı yardımcı yardımcı olur. <strong>4</strong> engellerin üzerinden yürüyüş ve beyin dalgalarını aracılığıyla ışığı açmak için bir anahtar itme telepresence kontrol deneyini <strong>göstermektedir. Şekil 5</strong> telepresence kontrolünü gösterir çıkış işareti aşağıdaki merdiven durumda doğru yürüyen deney. <strong>Şekil 6</strong> bir balon alıp deneğin elinin onu teslim telepresence kontrol deneyini gösterir. </p><p class="jove_content" fo:keep-together.within-page="1"><img alt="figür 1" src="/files/ftp_upload/53558/53558fig1.jpg" /><br /> <strong>Şekil bir İnsansı Robot ile Beyin Robot Etkileşimi 1. Sistem Yapısı.</strong> Beyin sinyalleri EEG veri toplama sistemi ile ölçülür. Kullanıcı arayüzü SSVEP yanıtları ve görüntüler video görüşlerinizi canlı ortaya çıkarır<html> kapalı döngü kontrol deneyleri. İlk kez denekler için, Veri Kaydedici ve Çevrimdışı Data Analyzer kendi SSVEP çevrimdışı özellikleri analiz etmek ve her konu için sınıflandırıcı eğitmek için çevrimdışı eğitim sürecinde kullanılmaktadır. Sonra Çevrimiçi Sinyal İşlemci ve Robot Kontrol insansı robot online kontrolü için yapılandırılır. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53558/53558fig1large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> </p><p class="jove_content" fo:keep-together.within-page="1"><img alt="Şekil 2," src="/files/ftp_upload/53558/53558fig2.jpg" /><br /> <strong>SSVEP merkezli BRI Sistemi Şekil 2. Kullanıcı Arayüzü.</strong> Kullanıcı Arabirimi görüntüler orta penceresinde video geribildirim yaşamak ve dört frekanslarda insansı robot davranışları temsil eden çevre üzerinde dört görüntü titriyor. Sağ panelde 3D gösterimi insansı robot mevcut duruş gösterir.<html> /www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53558/53558fig2large.jpg &quot;target =&quot; _ blank &quot;&gt; bu rakamın büyük halini görmek için lütfen buraya tıklayınız. </p><p class="jove_content" fo:keep-together.within-page="1"><img alt="Şekil 3," src="/files/ftp_upload/53558/53558fig3.jpg" /><br /> <strong>Şekil 3. Çevrimiçi Sinyal İşlemci OpenViBE programlama ortamında uyguladı.</strong> Kırmızı döngüsü ile işaretlenmiş Edinme ve Proses Sinyalleri kutu MATLAB komut yazılı işleme algoritması çağırır. Menü panelindeki başlar düğmesi programı başlar. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53558/53558fig3large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> </p><p class="jove_content" fo:keep-together.within-page="1"><img alt="Şekil 4," src="/files/ftp_upload/53558/53558fig4.jpg" /><br /> <strong>Engeller sayesinde yürüyüş ve Işık Anahtarı Pushing 4. Telepresence Kontrol Experiment Şekil.</strong>es / ftp_upload / 53558 / 53558fig4large.jpg &quot;target =&quot; _ blank &quot;&gt; bu rakamın büyük halini görmek için lütfen buraya tıklayınız. </p><p class="jove_content" fo:keep-together.within-page="1"><img alt="Şekil 5," src="/files/ftp_upload/53558/53558fig5.jpg" /><br /> <strong>Şekil Çık Sign ardından Merdiven Doğru Yürüyüş 5. Telepresence Kontrol Deneyi.</strong> <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53558/53558fig5large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> </p><p class="jove_content" fo:keep-together.within-page="1"><img alt="Şekil 6," src="/files/ftp_upload/53558/53558fig6.jpg" /><br /> <strong>Şekil 6. Konu ile Balona teslim ve Telepresence Kontrol Deneyi.</strong> <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53558/53558fig6large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> </p><p class="jove_content" fo:keep-together.within-page="1"><img alt="Şekil 7," src= &quot;/ files / ftp_upload / 53558 / 53558fig7.jpg&quot; /&gt; <br /> <strong>İşleme Kanallı EEG Verilerinin Şekil 7. Prosedür (A)</strong> Konu 4,615 Hz uyarıcı bakıyordu olduğu deneme çıkarılan Kanallı veri <strong>çağı.; (B)</strong> CCA katsayıları kullanılarak Mekansal süzülmüş veri; <strong>(C)</strong> uzamsal filtrelenmiş verilerin normalize PSD. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53558/53558fig7large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> </p><p class="jove_content" fo:keep-together.within-page="1"><img alt="Şekil 8" src="/files/ftp_upload/53558/53558fig8.jpg" /><br /> <strong>Konu Farklı Frekanslarda Uyaranlar Titreşen bakıyorum mı hangisi Tek Denemeler Elde Şekil 8. Normalize PSD.</strong> <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53558/53558fig8large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> </p>

Watch this Scientific Journal Video about SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots at JoVE.com

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

<p class='jove_content'>The overall goal of this method is to establish an SSVEP-based experimental procedure by integrating multiple software programs to enable the study of brain-robot interaction with humanoid robots, which is prospective in assisting the sick and elderly as well as performing unsanitary or dangerous jobs.</p>

İnsansı Robotlar ile Beyin Robot Etkileşimi Deneysel Prosedür SSVEP tabanlı

Brain-Robot Interaction (BRI), which provides an innovative communication pathway between human and a robotic device via brain signals, is prospective in ...

ssvep-based-experimental-procedure-for-brain-robot-interaction-with

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Introduction to Control Systems

SCIENTISTS IN ACTION

13.1K Görüntüleme.  Tianjin University. The overall goal of this method is to establish an SSVEP-based experimental procedure by integrating multiple software programs to enable the study of brain-robot interaction with humanoid robots, which is prospective in assisting the sick and elderly as well as performing unsanitary or dangerous jobs.

Video: SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Eusociality and Division of Labor

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Simulating Eusocial and Solitary Behavior
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">Note: In this simulation, you will portray either a eusocial or solitary animal. The goal of this simulation is to maximize your fitness by reproducing as many offspring as possible during the allotted five minutes. To do this, you must forage for resources and reproduce within the constraints of your assigned role.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Assuming a class size of 10, 4 individuals should form the solitary, or the carpenter bee group, and the remaining 6 students should form the eusocial, or the honeybee group. Note: The eusocial honeybee group will include one queen, one drone, and four workers. The queen and the drone will reproduce and protect the resources, while the workers will forage and steal resources. The solitary carpenter bee students must perform all of the tasks in this activity, with the exception of reproduction, by themselves.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Store your resources for reproduction in the nest bowl provided by your instructor. These resources are represented by assorted beans that can be collected by foraging in the environment buckets or by stealing from other nests.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">The blue cups are male and the red cups are female, and they will be used to produce offspring. This is done by combining all four bean types in one red or blue cup to symbolize the resources needed to reproduce, and then stacking one completed cup inside a cup of the opposite color that also contains one of each bean type, to simulate a mating that produces two-cup offspring, one from each parent.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">To reproduce, the solitary students will need to seek out another solitary student with an opposite-colored cup. Conversely, the eusocial queen and drone always reproduce with each other. HYPOTHESES: The hypotheses for this lab activity are based on the possible benefits of eusocial groups over solitary individuals. The alternate hypothesis could be that one group, either eusocial or solitary, will have an advantage over the other, given the ecological constraints, and this will be reflected in the number of offspring per capita. The null hypothesis might be that there will be advantage conferred by either of the strategies.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">If you are a worker in the honeybee group or a solitary student in the carpenter bee group, walk to the other side of the room to search through the rice on the foraging side of the room for one bean and bring the bean back to your bowl on the nest side of the room. Note: Even though this activity has a 5-minute time limit, running is not permitted. 
</div></li><li data-sub-note-item="1-7"><div class="lab-step">If a solitary student is not present at a neighboring bowl, you can try to steal one bean at a time, using a cup to scoop up the bean without touching the bean or the bowl with anything but the cup. You must immediately stop trying to steal if the solitary student makes it back to their bowl before you finish stealing. Note: Neighbors cannot steal from eusocial nests because the queen and drone do not leave their nest.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">You can create offspring at any time during the activity. Remember to label each cup that is contributed to an offspring with your name to keep track of your reproduction.  Note: Eusocial groups produce two offspring for their group every time they reproduce, while solitary students produce only one offspring per reproductive coupling.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">If you were a solitary carpenter bee, record the number of offspring you produced in the appropriate row of the table. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/36/Table_1_Eusociality_and_division_of_labor.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="2-2"><div class="lab-step">If you were a part of the eusocial honeybee group, record the number of offspring produced by your queen and drone.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">To calculate the fitness for a solitary carpenter bee student, simply count the number of offspring that the student produced.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">To calculate the fitness for a eusocial honeybee student, divide the number of offspring produced by the queen and drone by the number of members in the group, in this case 6, to get a per-student fitness value.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">When each student has calculated their respective fitness value, calculate the average number of offspring produced for each social category and plot these as a bar graph. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/36/Table_2_Eusociality_and_division_of_labor.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Table 2</a>
</div></li><li data-sub-note-item="2-6"><div class="lab-step">Next, use Hamilton&#39;s equation to analyze the data. To do this, set r equal to the degree of relatedness, B to the class average eusocial fitness, and C to the class average solitary fitness.  r * B > C
</div></li><li data-sub-note-item="2-7"><div class="lab-step">Use these results to determine if altruistic behavior should persist in your eusocial honeybee group. Discuss the variables in Hamilton&#39;s equation that may contribute to this observation. Consider circumstances under which you would expect to see different results. 
</div></li></ul></li></ol>

Ösosyallik ve İş Bölümü

Simulating Eusocial and Solitary Behavior
ExpandNote: In this simulation, you will portray either a eusocial or solitary animal. The goal of this ...

JoVE Lab Manual

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Extinction

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Diversity and Extinction during the Paleogene Epoch
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">Begin this procedure by reading the extinction reading supplement that has been printed out for you. <br /><strong>NOTE:</strong> Alternatively, you may download the reading supplement at the link below.&nbsp; <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/24/Lab_20_Reading Supplement.docx" style="display:block;margin:20px;" target="_blank">Click here to download the extinction reading supplement</a>
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Using the information contained in the extinction reading supplements pertaining to the taxa of interest and the Chicxulub impact event, make predictions for each taxon listed in Table 1. Consider whether diversity in each taxon increased, decreased, or stayed the same immediately following the Cretaceous-Paleogene boundary and later on in the Paleogene epoch. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/24/Table_1_Extinction.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Then, fill out the reasons for each of your predictions in the Contributing Factors column. HYPOTHESES: The experimental hypothesis is that many of the different taxa will show changes in diversity after the Cretaceous-Paleogene event, and again at the end of the Paleogene, with some increasing in diversity, while others decrease. The null hypothesis is that there will be no changes in diversity between taxa following the Cretaceous-Paleogene event, or at the end of the Paleogene.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Gather diversity data by going to the Paleobiology Database: <a href="http://www.paleobiodb.org" target="_blank">www.paleobiodb.org</a>.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">In the center of the screen, click the yellow box labeled Download Data. Under the italicized heading, &#8220;What do you want to download?&#8221;, select Diversity over time on the left side and Comma-separated values on the right side.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Scroll down to the heading &#8220;Select by taxonomy&#8221;.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">In the first box labeled 'Taxon or taxa to include', type in the name of the taxon that data is being gathered on.  NOTE: Ensure the spelling is correct.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Now, go to the dropdown menu right below that box labeled &#8220;Taxonomic resolution&#8221;, and select genera.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Under the next heading, Select by time, type Maastrichtian into the first box and Chattian in the box directly below. Make sure the dropdown menu labeled Time rule is set to major and the Temporal resolution is set to stage.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Select &#8220;Assume extant taxa range through to present&#8221;. Scroll back up to the middle of the page and click download. A save window will open.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Save the .csv file to a safe and accessible place and rename it to make it easy to identify.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Open the file and scroll down to the main dataset under Records.  NOTE: The data are arranged in reverse time order by geological stage. The second column, interval_name, gives the accepted name of the stage in question. The next two columns give the appropriate dates of the stage in millions of years before the present. The final column, number of occurrences, gives a total count of the genera extant during that geological stage as determined from occurrence of fossils.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">To more easily work with this data, copy and paste each column into a new sheet. Be sure to label this sheet with the taxon in question, the data and time the data were obtained, and the data source.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Repeat this process for each of the taxa in Table 1 (steps 4 &#8211; 12). NOTE: Data from multiple taxa can be kept on the same sheet, so long as they are kept distinct and labeled appropriately.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">To create line plots for each of the taxa showing the change in diversity over time, select the max_ma column and the number of occurrences column simultaneously.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">In Excel, select Insert from the top toolbar and find the section labeled Charts. Select the bottom center icon, Insert Scatter Chart.
</div></li><li data-sub-note-item="1-17"><div class="lab-step">Then, select the Scatter with Straight Lines and Markers and a graph should appear. NOTE: Since the axis of this graph is in units of millions of years ago, the axis is in the reverse direction of time when put in numerical order.
</div></li><li data-sub-note-item="1-18"><div class="lab-step">To fix this, click on the green plus sign in the top-right corner of the graph and hover over Axes. This should reveal a small black arrow. Click the arrow to open up a small menu and select More Options.
</div></li><li data-sub-note-item="1-19"><div class="lab-step">This will open the Axis Options menu. Under Axis Options, click the box next to Values in reverse order. NOTE: It is also possible to change the axis scales from this menu, which can be used to eliminate the excess time that is not being analyzed in this lab. Keep any changes consistent between different graphs.
</div></li><li data-sub-note-item="1-20"><div class="lab-step">Double-click on the title at the top of the graph and change it to the taxon being represented.
</div></li><li data-sub-note-item="1-21"><div class="lab-step">Make a separate graph for each of the taxa in Table 1. Keep them organized and in one location. A separate sheet for graphs is recommended.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">For each graph, identify the location of the Cretaceous-Paleogene boundary and draw a vertical line through the graph at this point.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Using the information from the graphs, fill out Table 2. In some cases, it may be helpful to go back to the original dataset and compare actual values, particularly when they are small. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/24/Table_2_Extinction.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Table 2</a>
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Compare these values to the predictions made in Table 1 and discuss if the original contributing factors are still likely candidates.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Using the dataset, calculate the percentage of total taxa that went extinct over the Cretaceous-Paleogene boundary using this equation.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">There is an event in the middle of the Paleogene known as the Paleocene-Eocene Thermal Maximum about 55.5 million years ago. This represents a high point in temperature during the Paleogene epoch at approximately 8 &#176;C higher than today&#39;s average temperature. Does this point seem to have an effect on diversity for any of the taxa? If yes, then which ones?
</div></li></ul></li></ol>

Extinction: Diversity and Extinction during the Paleogene Epoch - Procedure

Diversity and Extinction during the Paleogene Epoch
ExpandBegin this procedure by reading the extinction reading supplement that has been printed out for ...

Group Behavior

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">The Hawk-Dove Game
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">NOTE: In this activity, you will play the hawk and dove game with a single partner and then with multiple partners to observe hypothetical costs and benefits of the antagonist or cooperative behavior respectively. 
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Before the activity starts, review the cost-benefit table so that you understand how to score the game. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/33/Table_1_Group_behavior.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="1-3"><div class="lab-step">HYPOTHESES: The experimental hypothesis for this exercise could be that the dove strategy will become more frequent between repeated partners, and the hawk strategy will become more frequent when interactions are with a variety of partners. The null hypothesis could be that there will be no change in strategy over time with repeat or different partner combinations. NOTE: Benefit can be determined by looking at the left column and choosing the row that corresponds to the card you played. The box that corresponds to the choice of your partner can be found in the top row. For the purposes of this game, B equals four and C equals three. So depending on the cards played, player one here, which is you, would gain a score of two, four, zero or one half. 
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Collect a set of two game cards. 
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Take out the cards labeled hawk and dove and place them face down on the table or conceal them in your hands. 
</div></li><li data-sub-note-item="1-6"><div class="lab-step">When the instructor gives the signal show either of the two cards to the student sitting across from you. Try to strategize how to receive the highest benefit from every interaction on your own but do not communicate with your partner. 
</div></li><li data-sub-note-item="1-7"><div class="lab-step">In the Single Partner Recording Table (Table 2) provided by your instructor, note the cards played as well as the benefit you received for that round.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Repeat showing cards to the same partner and determining benefit on your instructor&#39;s signal for a total of 15 rounds.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">At the end of those rounds, the student with the highest total benefit value was determined to be the &#8220;winner&#8221;, or the most fit.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">As a class, determine the percentages of hawks and doves played as well as the average benefit received for each round, using this formula: Class average benefit=(sum total benefit)/(number of players)
</div></li><li data-sub-note-item="1-11"><div class="lab-step">For the second game, and then for each round of play, one row of students should rotate to their right, leaving all players with a new partner.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Continue playing for 15 rounds or until students end up back in their starting positions, recording the data in the Multiple Partner Recording Table (Table 3) given to you by your instructor.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">For each round, determine the percentages of hawks and doves played that round, as well as the average benefit received.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Cheating and Cooperation Exercise
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">NOTE: In this activity, you will exchange benefits, represented by colored or similar items, with your classmates. In this simulation, a cheater is defined as a person who gives fewer benefits than they receive. During this activity, you will observe the frequency of cheating behavior over time. 
</div></li><li data-sub-note-item="2-2"><div class="lab-step">HYPOTHESES: The experimental hypothesis is that cheaters will receive fewer benefits over time and cooperators will continue to provide equal benefits to one another. The null hypothesis is that the frequency of cheaters and cooperators does not change over time. 
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Each person should collect beads of one color to represent a tangible benefit, as well as one paper bag and a three-ring binder.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Get into a group of three so that all members have objects of the same color.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Now find another group with a different color to pair with. In each round, partners will exchange benefits without knowing what they are receiving from their partner and without discussion within their group.  NOTE: Benefits of a different color from your starting color are worth twice as much.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">Turn face to face with a member from the other group while still being able to conceal the objects in your possession.  TIP:<strong> </strong>Setting up a screen using a notebook or sitting behind a desk can be helpful here.
</div></li><li data-sub-note-item="2-7"><div class="lab-step">When given a signal from the instructor, place zero to two benefits into the paper bag and pass it to your partner.
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Simultaneously, receive the bag from your partner and then remove the benefits from the bag.
</div></li><li data-sub-note-item="2-9"><div class="lab-step">Make a note of how many benefits you gave away and how many you received in the Cheating and Cooperation Table (Table 4) provided by your instructor.
</div></li><li data-sub-note-item="2-10"><div class="lab-step">Turn to a new member from the other group and repeat the exchange.
</div></li><li data-sub-note-item="2-11"><div class="lab-step">Rotate through all of the members of the other group for as many rounds as the instructor determines - which will not be revealed until the game ends so as not to alter player behavior.
</div></li><li data-sub-note-item="2-12"><div class="lab-step">Once the game has ended, note for each round in the cheating and cooperation table whether you gave more than your partner, received more from them or if you gave the same amount.
</div></li><li data-sub-note-item="2-13"><div class="lab-step">Now total up all of the benefits in your possession, with benefits you&#39;ve received from the other group being worth twice as much.
</div></li><li data-sub-note-item="2-14"><div class="lab-step">For each round, the whole class should total up the number of cheaters - with cheaters defined as those who gave less than they received.
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">For both the single partner hawk-dove game and the multiple partners hawk-dove game, use the whole class data to plot the percentages as two separate lines - one for the percentage of hawks, and one for the percentage of doves, for each of the 15 rounds.
</div></li><li data-sub-note-item="3-2"><div class="lab-step">Take note of whether the cards played changed as more rounds were played.
</div></li><li data-sub-note-item="3-3"><div class="lab-step">Manipulate the values for B and C to see if you can find the point at which values of B and C would render the hawk strategy no longer effective (this would be the point when there is no benefit to choosing the hawk strategy over always choosing the dove strategy).
</div></li><li data-sub-note-item="3-4"><div class="lab-step">As a class, use the data from the cheating and cooperation activity to make a graph showing the percentage of rounds each individual player cheated versus the amount of benefits they ended with.
</div></li><li data-sub-note-item="3-5"><div class="lab-step">Consider whether it is better to be a cheater or a cooperator in this scenario and discuss as a class what makes this scenario different from the hawk-dove game.
</div></li><li data-sub-note-item="3-6"><div class="lab-step">Now, use the class data to graph the percentage of cheaters against the number of rounds, and look for any trends over time.
</div></li><li data-sub-note-item="3-7"><div class="lab-step">Consider which type of strategy would most likely evolve in a setting where partners interact repeatedly.
</div></li><li data-sub-note-item="3-8"><div class="lab-step">Then, note which tactic might be beneficial for a species that relies on cooperation. 
</div></li><li data-sub-note-item="3-9"><div class="lab-step">Discuss as a class what would likely happen if you increased or decreased the relative value of the benefits you receive.
</div></li></ul></li></ol>

Group Behavior: Hawk-Dove Game and Trading Exercise - Procedure

Grup Davranışı

The Hawk-Dove Game
ExpandNOTE: In this activity, you will play the hawk and dove game with a single partner and then with multiple partners to observe ...

Optimal Foraging

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Simulating Foraging with Artificial Habitats and Prey
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">NOTE: The foragers will hunt for prey represented by pinto beans in four buckets of rice with varying prey densities. Without knowing what these densities are, foragers must obtain as many prey items as possible in as little time as possible. 
</div></li><li data-sub-note-item="1-2"><div class="lab-step">HYPOTHESES: In this experiment, the experimental hypothesis could be that foragers will catch the most prey in the higher prey density bucket and also spend the most time foraging there.  The null hypothesis would then be that foragers will catch an equal number of prey in each bucket and that foragers will spend an equal amount of time foraging in each patch. 
</div></li><li data-sub-note-item="1-3"><div class="lab-step">To begin the foraging activity, record the names and role of each participant at the top of the student data collection sheet.  NOTE: Before starting the experiment, the forager is allowed to become familiar with the foraging process &#8211; the following steps are a practice round. 
</div></li><li data-sub-note-item="1-4"><div class="lab-step">The forager should kneel or sit in front of the average density bucket. 
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Once the timer says start, the forager may begin looking for the pinto beans representing the prey. The forager can spend as much time as they like foraging in this bucket. 
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Once a prey item is located, the forager must signal that one has been found and place the prey in the cup next to the bucket.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Once they believe they have acquired most of the prey in the patch, they should tell the timer to stop the time and the practice round is over. 
</div></li><li data-sub-note-item="1-8"><div class="lab-step">To begin the simulation proper, the forager should sit or kneel in front of bucket A. 
</div></li><li data-sub-note-item="1-9"><div class="lab-step">The timer must be ready to start the stopwatch. 
</div></li><li data-sub-note-item="1-10"><div class="lab-step">The recorder should be ready to record the time each prey item is located, in addition to the time that the forager arrived at and left each bucket. 
</div></li><li data-sub-note-item="1-11"><div class="lab-step">When all parties are ready, the timer should start the stopwatch and say &#8220;start&#8221;,  and the forager should begin foraging. NOTE: The stopwatch will run through the rest of the round for buckets B and C.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">As the forager signals finding pinto beans and places them in the cup next to the bucket, the timer should tell the recorder the time.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">The recorder should then write the time in the student data collection sheet.  <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/34/Table_1_Optimal_foraging.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Once the forager has decided to move on to the next bucket, they should tell the timer &#8220;done&#8221;, and begin moving to the next patch. 
</div></li><li data-sub-note-item="1-15"><div class="lab-step">The recorder should record the time the forager left and the time they arrived at bucket B in the student data collection sheet.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">Repeat the same procedure for buckets B and C. Once the forager has completed the activity, it is time for the next forager to begin using the same procedure. 
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">Before performing any data analysis, review the data collection sheet and compile your individual data for captured prey, foraging time, and travel time for each bucket in your student calculations table. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/34/Table_2_Optimal_foraging.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Table 2</a>
</div></li><li data-sub-note-item="2-2"><div class="lab-step">After this, calculate your individual capture rate for each bucket by dividing the number of prey captured by the sum of the foraging time and travel time and record these values in your table. Individual capture rate =  Number of prey captured / (foraging time + travel time)
</div></li><li data-sub-note-item="2-3"><div class="lab-step">To calculate your Giving-Up-Time or a GUT for each bucket, subtract the time that the last prey item was acquired from the time you left the bucket.  GUT = time forager left bucket  -  time last prey item acquired
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Next, calculate the mean GUT for your foraging group and record the values in your table.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Finally, calculate your scaled GUT for each bucket by dividing the bucket GUT by your group&#39;s mean GUT. Scaled GUT =  Bucket GUT / Group mean GUT NOTE: The scaled GUT will allow class data to be pooled later on without differences in individual foragers skewing the data. 
</div></li><li data-sub-note-item="2-6"><div class="lab-step">The instructor should now compile the data into the classroom spreadsheet.  <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/34/Table_3_Optimal_foraging.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Table 3</a>
</div></li><li data-sub-note-item="2-7"><div class="lab-step">Plot a bar graph of the average number of prey collected in each bucket. On the x-axis, A should represent the low prey density bucket, B should represent the medium prey density bucket, and C the high prey density bucket. Plot the y-axis as the number of prey items caught. 
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Next, plot the graph of the class average scaled GUT, where the x-axis represents the buckets with varying levels of prey density and the y-axis shows the values for the average scaled GUT. 
</div></li><li data-sub-note-item="2-9"><div class="lab-step">Plot a third graph of the average time spent foraging in each bucket. 
</div></li><li data-sub-note-item="2-10"><div class="lab-step">Now review the Marginal Value Theorem (MVT) from the concepts video and examine the three graphs that you generated from your class data. Take note of whether the graphs conform to the predictions of MVT. 
</div></li></ul></li></ol>

Optimal Foraging: Foraging with Artificial Habitats and Prey - Procedure

Optimal Yiyecek Arama

Simulating Foraging with Artificial Habitats and Prey
ExpandNOTE: The foragers will hunt for prey represented by pinto beans in four buckets of rice with ...

Sexual Selection and Mate Choice

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Sexual Selection Class Simulation
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">Note: In this activity, you and your classmates will portray a sexually reproducing population consisting of an equal number of male and female animals. You will simulate several different mating scenarios to determine how relative quality, attractiveness, sex, and parental commitment affect mate choice and reproductive success. The goal of this activity is to maximize your progeny. 
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Hypotheses: There are several overall hypotheses for female and male behavior for this activity. The main experimental hypothesis for female behavior is that females will mate with males of high quality more frequently than those of low quality, yielding a higher reproductive success. The null hypothesis is that females will not demonstrate preference towards high- or low-quality males in any of the four rounds of mating. For males, one experimental hypothesis is that males with a higher visible score will have greater reproductive success. Another could be that males will be more selective for females in scenarios in which they join females to care for offspring as opposed to scenarios in which they exhibit no parental commitment. The null hypothesis for male behavior might be that males will not demonstrate preference towards high- or low-quality females in any of the four rounds of mating. 
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Activity Overview: To begin, each student will be assigned a sex as well as a relative quality and attractiveness score. Remember - the goal is to maximize your reproductive success in each round. You do this by mating with partners of the highest possible quality which is rated on a scale of one to three with three being the highest possible score. Attractiveness scores, which follow the previously described scoring paradigm, correlate with quality but do not exactly predict the score. Though useful, they are not a perfect way to choose the best mate.  If you are assigned a male ID holder, you will have 16 gametes. However, if you are assigned a female ID holder, you will only have four. A successful mating occurs when one sperm and one egg are paper-clipped together and deposited at the fertilization area. 
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Note - Rules of the activity: 
<ul>
	<li>Assigned male and female identities for these experiments are not representative of students&#39; personal gender identities. </li>
	<li>Running is not permitted. </li>
	<li>Talking is not permitted.</li>
	<li>Hidden values cannot be shared but individuals can attempt to hide their visible scores. </li>
	<li>Respect the space around each individual and remain an arm&#39;s length away. </li>
	<li>Offspring will only be counted towards an individual score if both gametes are paper-clipped together and dropped off in the designated fertilization area before the end of the two-minute round. </li>
</ul>
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Round 1 &#8211; Hidden Quality Score
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">To begin the first simulation, take the clip-on ID holder you were randomly assigned and make sure it contains four gametes if you are assigned female or sixteen gametes if male. Males should also have a strip of white paper and two paperclips. 
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Next, males should paperclip the white strip of paper over their quality score to hide it, but keep the attractiveness score visible. 
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Record your ID number for round one in table two.  <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/35/Table_2_sexual_selection.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Table 2</a>
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Next, clip on the ID holder and move to the designated mating area. 
</div></li><li data-sub-note-item="2-5"><div class="lab-step">When the instructor says begin, you may commence the mating simulation. You will have exactly two minutes to produce as many offspring as possible. Males may freely give their sperm to females, and females may choose to use these sperm immediately after which they would walk to the fertilization area and paperclip it to one of their eggs, or they may choose to wait until they receive other sperm to do so. 
</div></li><li data-sub-note-item="2-6"><div class="lab-step">Once the gametes have been deposited in the fertilization area, females may resume mating. 
</div></li><li data-sub-note-item="2-7"><div class="lab-step">When the two minutes have elapsed, all matings must stop and any gametes not in the fertilization area at this time will not be counted. 
</div></li><li data-sub-note-item="2-8"><div class="lab-step">The instructor should now tally all of the matings and record the numbers of the individuals who produced each offspring.
</div></li><li data-sub-note-item="2-9"><div class="lab-step">Now, find all the gametes that came with your ID holder and repackage them for the next round. 
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">Round 2 &#8211; Hidden Attractiveness Score
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">For the second round, obtain a new randomly assigned ID holder and again ensure it contains the proper number of gametes. 
</div></li><li data-sub-note-item="3-2"><div class="lab-step">Next, males should use the paperclip and strip of white paper to hide their attractiveness score (instead of the quality score, which was covered in round one).
</div></li><li data-sub-note-item="3-3"><div class="lab-step">Record the ID number of your clip in table two under round two.  Note: The mating simulation process for round two will be the same as round one.
</div></li><li data-sub-note-item="3-4"><div class="lab-step">Move to the designated mating area and with for the instructor to signal the start of the round. As before, males may freely give away their sperm while females will choose to use it now or wait for different sperm. When a female decides to fertilize an egg, she will walk to the fertilization area and paperclip the gametes together. 
</div></li><li data-sub-note-item="3-5"><div class="lab-step">Proceed with the simulation for two minutes, and at the signal from the instructor all mating activity should stop. 
</div></li><li data-sub-note-item="3-6"><div class="lab-step">The instructor should now tally all of the matings from this second round.
</div></li><li data-sub-note-item="3-7"><div class="lab-step">Now, find and return the gametes to your ID holder, and then return the holder to the instructor.
</div></li></ul></li><li data-note-item="4" data-parent-collapse="">Round 3 &#8211; Visible Quality and Attractiveness Scores
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="4-1"><div class="lab-step">For the third simulation, you should again obtain a new clip-on ID holder and check that it contains the appropriate number of gametes. Record the ID number of your clip in table two.
</div></li><li data-sub-note-item="4-2"><div class="lab-step">For this round, leave both attractiveness and quality scores visible on male IDs. Note: The mating simulation process for round three will be the same as the previous two rounds.
</div></li><li data-sub-note-item="4-3"><div class="lab-step">Move to the mating area and wait for the signal to begin the simulation.
</div></li><li data-sub-note-item="4-4"><div class="lab-step">Once the instructor starts the timer and gives the signal, commence mating. As before, males are allowed to freely give away their sperm to females and females may use the sperm immediately or wait for different sperm. Again, fertilized eggs only count if placed in the fertilization area. 
</div></li><li data-sub-note-item="4-5"><div class="lab-step">After the two-minute time limit, the instructor should tally all matings. 
</div></li><li data-sub-note-item="4-6"><div class="lab-step">Now, find and return the gametes to your ID holder, and then return the holder to the instructor.
</div></li></ul></li><li data-note-item="5" data-parent-collapse="">Round 4 &#8211; Increased Male Parental Care
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="5-1"><div class="lab-step">In the final round, males will again leave their attractiveness and quality scores visible. 
</div></li><li data-sub-note-item="5-2"><div class="lab-step">Obtain an ID holder and ensure it contains the appropriate number of gametes. 
</div></li><li data-sub-note-item="5-3"><div class="lab-step">Clip on the ID holder and move to the mating area. Note: As before, males may freely give away their sperm to females. However, in this round, once a female chooses to mate with a male, both the male and female will walk to the fertilization area to paperclip their gametes together. After placing the paper-clipped gametes on the table, both male and female actors may return to the mating area. 
</div></li><li data-sub-note-item="5-4"><div class="lab-step">The instructor should signal the start of the round and begin the timer &#8211; at this point participants can begin the simulation.
</div></li><li data-sub-note-item="5-5"><div class="lab-step">Once the two-minute time limit is up, all matings must stop. 
</div></li><li data-sub-note-item="5-6"><div class="lab-step">The instructor should tally all mating events.
</div></li><li data-sub-note-item="5-7"><div class="lab-step">Find and return the gametes to your ID holder. Give your ID holder to the instructor and notify them if any gametes or supplies are missing. 
</div></li></ul></li><li data-note-item="6" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="6-1"><div class="lab-step">To analyze the data generated during the mating activities, first split up into groups of four. 
</div></li><li data-sub-note-item="6-2"><div class="lab-step">Collect the class data from the instructor for ONE of the four rounds of mating. Note: In this activity, there were several types of females and males distinguished by different letters. These letter types correspond to specific combinations of quality and attractiveness scores. In the compiled data, the average number of matings and reproductive success has already been sorted by letter type for you by the instructor. 
</div></li><li data-sub-note-item="6-3"><div class="lab-step">Use these data to generate four graphs for the round you were assigned. First plot two graphs for the average number of matings against female and male type. 
</div></li><li data-sub-note-item="6-4"><div class="lab-step">Then plot the reproductive success for males and females against male or female type, giving a total of four graphs.
</div></li><li data-sub-note-item="6-5"><div class="lab-step">Once these graphs are complete, each group should present their data to the class, making sure to state the original hypothesis for your assigned round and whether or not the hypothesis was upheld.
</div></li><li data-sub-note-item="6-6"><div class="lab-step">After each group presents, discuss the overall results of the four rounds together. 
</div></li><li data-sub-note-item="6-7"><div class="lab-step">Note the affect that hiding the quality score had on the overall quality of mates chosen.
</div></li><li data-sub-note-item="6-8"><div class="lab-step">Note how hiding or revealing the attractiveness score affected the results.
</div></li><li data-sub-note-item="6-9"><div class="lab-step">Discuss the effect of male parental investment on the number and overall quality of mating pairs.
</div></li></ul></li></ol>

Cinsel Seçilim ve Eş Seçimi

Sexual Selection Class Simulation
ExpandNote: In this activity, you and your classmates will portray a sexually reproducing population consisting of an ...

Evolutionary Relationships

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Forming an Evolutionary Hypothesis
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">NOTE: A cladogram is an important tool for forming an evolutionary hypothesis. A cladogram is a tree-shaped chart used to depict the hypothetical genealogical relationships between species. The tips or leaves of the chart represent specific species and the branches of the tree are different lengths. The different lengths represent the degree of change between each of the species. The common ancestor of all of the species that a specific line branches from is located at a node, where the branches intersect. Species that share a node are called a sister group.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">To begin, look at the provided blank cladogram and make a hypothesis about where the assigned animals should be placed on the tree. If a blank cladogram has not been provided please <a target="_blank" href="/files/ftp_upload/10562/Blank_Cladogram.png">download one here</a>.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Next, observe the image of the fossilized animal.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Using the morphology, or physical characteristics, of the fossil, make a hypothesis about where on your cladogram it should be placed. Add a new line or mark to indicate your proposed position for the fossil.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Comparing Gene Sequences Using BLAST
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">NOTE: Historically, cladograms have been constructed through the comparison of morphology. Now, genetic sequences can also be compared between species of interest to construct cladograms. DNA sequences are not usually preserved in fossils, so for this lab you will use the BLAST database to compare the DNA sequences of living species that are closely related to the fossil to thousands of other living species.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Before beginning this lab, your instructor will have downloaded the three preserved gene sequences to a folder on your desktop.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Navigate to the BLAST homepage, which the instructor should have left open in your browser, and click on Saved Strategies from the menu at the top of the page.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Click Open on the Evolutionary_Relationships_Gene1.txt file.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Then, click View to go to the Standard Nucleotide BLAST search page. You should be able to see the DNA sequence in the Query Sequence box at the top-right of the screen.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">Scroll to the bottom of the screen and click the BLAST button. Note: It will take a few moments to process and analyze the data. 
</div></li><li data-sub-note-item="2-7"><div class="lab-step">When the data has been processed, a graphic summary will appear.  NOTE: Your query sequence is represented by the blue line at the top of the box. Each of the lines below the blue line represents another sequence in the BLAST database that matches your query. The length and location of these bars represent where and how much of the sequence match up to the query. The color of the bar represents its score, or how identical the sequence is to the query. Below the graphic summary is the Sequences producing significant alignments list, which contains descriptions of the DNA sequences retrieved from the database that most closely align with the query sentence. These are listed in descending order, from the most similar at the top to the least similar at the bottom. On the right, there are several statistics on how closely related each database sequence is to the experimental sequence. The higher the Max, Total, Query Coverage, and Identity scores are, the more similar the query and retrieved sequences are to each other. Similarly, the lower the E value number, the less likely the sequences match was found by random chance and more significantly the alignment is accurate. An E value of 0 indicates a highly significant match.
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Click on the name of the description of the most similar alignment listed. This will take you further down the page to the exact DNA sequence alignment between the retrieved sequence and the query sequence.
</div></li><li data-sub-note-item="2-9"><div class="lab-step">Click on the Sequence ID number. This will open a new tab with more specific information on the retrieved gene sequence.
</div></li><li data-sub-note-item="2-10"><div class="lab-step">Identify and record the scientific and common names of the organism, which should be listed next to Source.
</div></li><li data-sub-note-item="2-11"><div class="lab-step">Identify and record the protein that the gene codes for, which should be listed next to Definition.
</div></li><li data-sub-note-item="2-12"><div class="lab-step">Close the tab and hit Back to return to the Sequences producing significant alignments list.
</div></li><li data-sub-note-item="2-13"><div class="lab-step">Then, repeat steps 7 &#8211; 9 for the next most similar sequences.
</div></li><li data-sub-note-item="2-14"><div class="lab-step">After collecting several species names, return to the Sequences producing significant alignments list and click Select: All to check all of the boxes next to the names of each listed alignment sequence.
</div></li><li data-sub-note-item="2-15"><div class="lab-step">Click on Distance of tree results to create a phylogram based on the similarity of all of the BLAST result gene sequences to the query gene sequence.  Note: Your query fossil relative sequence will be highlighted in yellow.
</div></li><li data-sub-note-item="2-16"><div class="lab-step">Record your sequence&#8217;s location in relation to the other taxon groups shown in the tree.
</div></li><li data-sub-note-item="2-17"><div class="lab-step">Finally, return to the Saved Strategies tab and upload the next saved gene sequence.
</div></li><li data-sub-note-item="2-18"><div class="lab-step">Query the remaining two fossil relative DNA sequences as previously demonstrated (steps 1 &#8211; 16).
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">Data Analysis
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">Based on your gene sequence results, come up with a second hypothesis about where your fossil specimen fit in the original cladogram.
</div></li><li data-sub-note-item="3-2"><div class="lab-step">Compare this placement with your first hypothesis.
</div></li><li data-sub-note-item="3-3"><div class="lab-step">Compare your tree with your classmates&#8217;. If any of your classmates put the fossil on a different branch, ask them how they came to that decision.
</div></li></ul></li></ol>

Evolutionary Relationships: Using BLAST to Test Evolutionary Hypotheses - Procedure

Evrimsel İlişkiler

Forming an Evolutionary Hypothesis
ExpandNOTE: A cladogram is an important tool for forming an evolutionary hypothesis. A cladogram is a tree-shaped chart ...

Evrim

Energy Dynamics

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Caterpillar Energy Dynamics
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">NOTE: In this lab you will grow caterpillars in conditions with and without food to examine the transfer of biomass in a typical trophic system.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Weigh and record the wet mass of enough leaves of cabbage to line the bottom of a plastic tub.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Then, collect two batches of five caterpillars from their cabbage habitat, and weigh and record the wet mass of each batch separately in individual weigh boats. Make sure to tare the balance before each measurement. HYPOTHESES: The experimental hypothesis is that only a fraction of energy will be transferred between the trophic levels of the cabbage and the caterpillars and a significant amount will be lost as waste and heat energy. The null hypothesis is that there will be no significant difference between the energy input from the cabbage, and the obtained energy stored as biomass in the caterpillars.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Place the weighed cabbage and five caterpillars in a plastic tub lined with damp paper towels, leaving the lid slightly cracked open for ventilation, but not wide enough for the animals to escape.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Place the other five caterpillars in a second clean container prepared the same way, but with no cabbage.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">After three days, transfer the caterpillars to new weigh boats, and weigh and record the final wet mass of both groups of caterpillars and the cabbage.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Then place the caterpillar waste, or frass, and cabbage into two separate dishes, and put both dishes into a 37 &#176;C incubator to dry for 48 hours.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Euthanize the weighed caterpillars by putting them into a minus 20 &#176;C freezer for 24 hours.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Then, transfer the dishes to a 37 &#176;C incubator for 48 hours.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">After drying, weigh and record the dry mass of the uneaten cabbage, the two groups of caterpillars, and the frass, and use these data to calculate the percent biomass of the caterpillars.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Finally, discard all of the dried organisms and plates into the hazardous waste bin, and wipe down your workspace with 70% ethanol.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">Take a look at the data you collected. Ensure the initial wet mass, the final wet mass, and the final dry mass columns are accurately filled out in your table. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/13/Table_1_Energy_Dynamics.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="2-2"><div class="lab-step">NOTE: Remember an object&#39;s biomass is equal to its dry mass. Therefore, percent biomass for each group is the final dry mass divided by the final wet mass times 100. For example, obtain the percent biomass of the cabbage by dividing the final dry mass by the final wet mass and multiplying by 100. This means that approximately 15% of the cabbage&#39;s total weight is biomass.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">After this, estimate the initial biomass of the cabbage and caterpillars by multiplying the percent biomass by the initial wet mass, and put the values in this new table. NOTE: Remember, biomass equals dry mass. Therefore, the final dry mass is equal to the final biomass of each group.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">To calculate the approximate initial and final energy in the form of kilocalories within the cabbage, caterpillars, and frass, multiply the biomass values recorded in your table by the conversions, and record the calculated values in the table. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/13/Table_2_Energy_Dynamics.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 2</a>
</div></li><li data-sub-note-item="2-5"><div class="lab-step">After this, subtract the initial energy from the final energy to obtain the change in energy for each group.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">NOTE: The negative sign denotes loss in energy, and positive indicates gain.
</div></li><li data-sub-note-item="2-7"><div class="lab-step">Using your data table, calculate the energy in kilocalories that the fed caterpillars lost to respiration. The formula is the energy gained from cabbage, which is the positive of the energy lost by cabbage, minus the biomass gained from cabbage, minus the energy lost via frass. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/13/Table_3_Energy_Dynamics.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 3</a>
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Then, repeat the same calculation for the unfed group of caterpillars. Make another column in the table and note this down.
</div></li><li data-sub-note-item="2-9"><div class="lab-step">Finally, add up all of the energy gained via biomass and cabbage consumption, and the energy lost via frass and respiration for each group of caterpillars. NOTE: For both groups of caterpillars the net energy is zero, meaning that this experiment obeyed the first law of thermodynamics.
</div></li></ul></li></ol>

Studying Energy Dynamics and Productivity - Procedure

Enerji Dinamiği

Caterpillar Energy Dynamics
ExpandNOTE: In this lab you will grow caterpillars in conditions with and without food to examine the transfer of biomass in a ...

Animal Behavior

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Making Choice Chambers
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">Before beginning the experiments, use one of the Sharpies from the lab table to trace a line around the circumference of the bottom of both bottles. One line should be 1 cm from the base of the bottle and the other should be 1.5 cm from the base of the bottle.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Use a razor blade to make a small cut in each bottle at the mark. 
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Then, insert the scissors and carefully cut along the line until the bottoms of the bottles are removed completely.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Fit one bottle bottom into the other.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Tape the bottles together to make a secure chamber.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Use the razor blade and scissors to poke a hole into the center of the chamber. 
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Take a piece of tape and fold the edge onto itself to make a tab and place the tape over the hole.  Note: The tab helps with easy removal and reattachment of the tape to the chamber.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Use the Sharpie to label one side of the chamber A and the other side B.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Upon receiving the colony of <em>Drosophila</em>, perform a count to make sure there are 40 living individuals in the vial.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Geotaxis
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">To perform a geotaxis assay, first attach a clean, empty bottle cap to each end of the choice chamber and turn the fly vial upside down onto its lid.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Open the tape flap in the center of the choice chamber.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Insert the funnel into the hole and tap all of the flies into the chamber. HYPOTHESES: The alternate hypothesis is that more flies will be moving against gravity, or up, regardless of the orientation of the choice chamber. Alternatively, if the flies are positively geotactic, then more flies will move down, or with gravity. The null hypothesis is that the flies will have no preference with regard to gravity and will move randomly within the chamber. 
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Once the <em>Drosophila</em> are in the chamber, close the tape flap, rotate the chamber so that it stands vertically with side A on the bottom, and start the timer.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Immediately, count the number of <em>Drosophila</em> that are moving up and the number that are moving down. Record these data for time point 0 in the table. 
</div></li><li data-sub-note-item="2-6"><div class="lab-step">After 30 seconds, rotate the chamber so that side B is on the bottom and count the number of <em>Drosophila</em> that are moving up or down. Record these data for time point 30 in the table.
</div></li><li data-sub-note-item="2-7"><div class="lab-step">After 60 seconds, rotate the chamber so that side A is on the bottom again and record the number of moving flies for time point 60.  <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/15/Table_1_Animal_behavior.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Hold the chamber over the fly vial and carefully open the cap to return all of the <em>Drosophila</em> back to their empty vial. 
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">Phototaxis
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">To perform a phototaxis analysis, first cover side A of the choice chamber with tin foil, taking care that the foil reaches to the exact center between the two sides. 
</div></li><li data-sub-note-item="3-2"><div class="lab-step">Ensure the caps are secured on both ends of the chamber.  HYPOTHESES: In this exercise, the alternative hypothesis is that more flies will be found in the light side of the choice chamber, if the flues are attracted to light, or on the dark side if they are repelled by light. The null hypothesis is that <em>Drosophila</em> will have no preference with regard to either stimulus. Therefore, equal numbers of flies will be found on either side of the choice chamber.
</div></li><li data-sub-note-item="3-3"><div class="lab-step">Open the tape flap in the center of the choice chamber, insert the funnel into the hole, and tap all 40 flies into the chamber as previously described.
</div></li><li data-sub-note-item="3-4"><div class="lab-step">Set the timer to sound an alarm at 10 minutes.
</div></li><li data-sub-note-item="3-5"><div class="lab-step">When the alarm sounds, stop the timer, and count the number of flies in the open side B of the chamber.
</div></li><li data-sub-note-item="3-6"><div class="lab-step">Subtract that number from the total number of flies added to the choice chamber to calculate the number of flies in the covered side A.
</div></li><li data-sub-note-item="3-7"><div class="lab-step">Record these data in the table for time point 10.  <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/15/Table_2_Animal_behavior.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 2</a>
</div></li><li data-sub-note-item="3-8"><div class="lab-step">Carefully, return all of the flies back to their empty vial.
</div></li></ul></li><li data-note-item="4" data-parent-collapse="">Chemotaxis
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="4-1"><div class="lab-step">HYPOTHESES: In this exercise, the alternative hypothesis is that more flies will be found on the side of the chamber with the apple cider vinegar if the flies are attracted to the odor. Or, if the flies are repelled by the vinegar, then more of them will be found on the side of the chamber presenting the odorless water. The null hypothesis is that <em>Drosophila</em> will have no preference with regard to either stimulus and will move randomly in the chamber.  Use an individual disposable plastic pipette to dispense two drops of the apple cider vinegar onto one cotton ball for side A of the chamber. 
</div></li><li data-sub-note-item="4-2"><div class="lab-step">Use an individual disposable plastic pipette to dispense two drops of the distilled water onto a cotton ball for side B of the chamber. 
</div></li><li data-sub-note-item="4-3"><div class="lab-step">Fold two pieces of tape over themselves to create individual pieces of double-sided tape and use the tape to attach each cotton ball to the inside of the single bottle cap.
</div></li><li data-sub-note-item="4-4"><div class="lab-step">Screw the bottle caps with the cotton balls onto their corresponding sides of the chamber.
</div></li><li data-sub-note-item="4-5"><div class="lab-step">Transfer all of the flies into the chamber and set the timer to sound an alarm after 10 minutes. 
</div></li><li data-sub-note-item="4-6"><div class="lab-step">When the alarm sounds, stop the timer and record the number of flies in each side of the chamber. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/15/Table_3_Animal_behavior.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 3</a>
</div></li><li data-sub-note-item="4-7"><div class="lab-step">At the end of the final experiment, funnel the flies into a morgue tube containing 70% ethanol. 
</div></li><li data-sub-note-item="4-8"><div class="lab-step">Dismantle the choice chambers for recycling.  NOTE: Since all of the chemicals used in these experiments are lab safe, the liquids can be disposed of down the sink, the chambers rinsed, and the solids can be thrown away in the trash. 
</div></li></ul></li><li data-note-item="5" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="5-1"><div class="lab-step">Gather all of the data collected for the geotaxis, phototaxis, and chemotaxis experiments.
</div></li><li data-sub-note-item="5-2"><div class="lab-step">Plot these values as bar graphs for different conditions and different time points.
</div></li><li data-sub-note-item="5-3"><div class="lab-step">Use these data to draw inferences about the behavior of <em>drosophila melanogaster</em>. 
</div></li></ul></li></ol>

Animal Behavior: Studying Taxis Behavior of Drosophila - Procedure

Hayvan Davranışı

Making Choice Chambers
ExpandBefore beginning the experiments, use one of the Sharpies from the lab table to trace a line around the circumference of the ...

Artificial Selection

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Observing Artificial Selection in Plants 
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">To begin the experiment, collect five two-week old grown plants from the generation one population that appear healthy. Note: Plants should appear green, not wilted, and not have damaged leaves. Experimental Hypothesis: The experimental hypothesis for this lab might be that the number of lead trichomes varies naturally, but the average number will increase over generations if only plants with the highest number of trichomes are interbred or decrease if those with the least are interbred. Null Hypothesis: The null hypothesis might be that the average number of trichomes will not change over subsequent generations after artificial selection.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Label each plant with a letter from A to E and with both partners&#8217; names.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Record any natural differences you see between your plant samples. Note: All of the plants are the same age, so any observed variation is due to expressed phenotype, not development.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Use a hand lens to count the number of trichomes found on the petiole of the lowest leaf, not including the round, first-grown cotyledons for each plant. Note: It can be helpful to shine a light onto the plant and to hold it against a dark background, such as a lab bench, during the trichome analysis. 
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Both partners will conduct counts on each plant independently and compare answers. If the counts are different, enlist a third counter or take the average of the two results.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">After this, determine the median number of trichomes for the entire class.  <a target="__blank" style="display:block;padding:20px;" href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/2/Lab_2_Table_A.xlsx">Click Here to download Table A</a>
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Determine the top and bottom 10% of the plants from the class trichome count. These groups will make up the two artificially selected lines: high hairiness and low hairiness, respectively.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">If more than 10% of the plants have no trichomes, select 10% of those plants randomly for the low hairiness plant line.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Separate the two groups of selected plants and label them clearly.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Move the plants to a well-lit area and keep them well watered until they develop flowers. Note: Flowers typically develop around 14 days.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">When the flowers are fully developed, use a pollination wand or paintbrush to rub the stigma and anther of one plant&#8217;s flowers for a few seconds.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Using the same wand or brush, rub the inside of each flower of every other plant in the same selection line.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">Using a different wand or brush, repeat steps 11 through 12 on the other line. Note: Take care not to cross the lines. Spread the pollen only among the appropriately selected plants.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Return the generation one plants to the growing areas. When the plants reach approximately 1 month old, they should produce mature seed pods.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">Allow the plants to dry out once the seed pods turn yellow.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">Break the seed pods open and collect the seeds.
</div></li><li data-sub-note-item="1-17"><div class="lab-step">Obtain new pots for the generation two seeds.
</div></li><li data-sub-note-item="1-18"><div class="lab-step">Fill the pots with moist potting soil about halfway and add a fertilizer pellet to each pot.
</div></li><li data-sub-note-item="1-19"><div class="lab-step">Fill the pots with more soil to fill just below the lip.
</div></li><li data-sub-note-item="1-20"><div class="lab-step">Make a shallow depression in the soil of each pot with a probe.
</div></li><li data-sub-note-item="1-21"><div class="lab-step">Touch a clean toothpick to a gluestick and use the toothpick to transplant the seeds into the soil one by one.
</div></li><li data-sub-note-item="1-22"><div class="lab-step">Cover the seeds with a thin layer of soil.
</div></li><li data-sub-note-item="1-23"><div class="lab-step">Label the pots with their hairiness line and place them in the designated growing area.
</div></li><li data-sub-note-item="1-24"><div class="lab-step">Use a plastic dropper to water the plants as needed to ensure they do not dry out.
</div></li><li data-sub-note-item="1-25"><div class="lab-step">When the plants are two weeks old, collect five plants from each line and label them A to E.
</div></li><li data-sub-note-item="1-26"><div class="lab-step">Then, count the trichomes on these plants as previously described (steps 4- 5).
<a target="__blank" style="display:block;padding:20px;" href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/2/Lab_2_Table_B.xlsx">Click Here to download Table B</a>
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Data Analysis
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">Create a frequency graph based on the generation one class data with the trichome count on the x axis and the number of plants on the y axis. Label the mean. 
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Then, create frequency graphs for both of the selected hairiness lines.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Compare the frequency graphs for generation one and both hairiness lines.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Take note of phenotypic shifts observed in the selected hairiness lines.
</div></li></ul></li></ol>

Artificial Selection: Visualization in Plants and Data Analysis - Procedure

Yapay Seçilim

Observing Artificial Selection in Plants 
ExpandTo begin the experiment, collect five two-week old grown plants from the generation one population that ...

Natural Selection

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Simulating Natural Selection
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">To begin, cut the white, black, and gray pipe cleaners into quarters, which should produce a total of 100 pieces that are 3 inches long.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Then, cut the green pipe cleaners in the quantities and lengths specified in the video, taking care to minimize waste. This approximates a normal distribution of lengths and should result in an additional 100 pieces total. NOTE: One 12-inch pipe cleaner should yield multiple lengths, for example, a 5-inch piece and a 7-inch piece. Use this advantage to reduce waste.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Now, cut one sheet of black and one sheet of white construction paper into approximately 3-inch strips measured along the long edge of the paper.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Tape these strips down to cover the base of a dissecting tray to create an alternating pattern of black and white strips. NOTE: In the first simulation, you will use the white, gray, and black pipe cleaner segments against a black and white background to simulate different selection pressures due to predation on a population. You will select your prey using two different strategies, eyes-open and eyes-closed. For each of these strategies, you will perform four rounds consisting of 25 selections, alternating between two partners. After each round you will restore the population back to its original size using the proportions of phenotypes present after selection.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">To begin the first scenario, count out 12 white, 12 black, and 26 gray pipe cleaner segments with your partner. Hypotheses: Here the experimental hypothesis might be that different predation strategies, such as having the eyes open or closed, will result in distinct selection pressures on the populations. Further, different phenotypes may be positively selected in the alternate scenarios. The null hypothesis might be that different predation strategies will have no effect on the populations or phenotypes.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Mix the pipe cleaner segments together as best as possible. Then, sprinkle them into the papered tray. NOTE: Ideally, the pipe cleaners will be spread out. However, this may not occur due to their self-adhering nature.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Once the segments are in the tray, separate them as best as possible without moving them too far from where they landed. As few segments as possible should be touching.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Have the first partner close their eyes. When given an audible signal by the second partner, the first should open their eyes and grab the first pipe cleaner they see from the tray as quickly as possible.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Set the removed pipe cleaner to the side.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Alternating partners, repeat this process a total of 25 times (steps 8 &#8211; 9).
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Count the remaining pipe cleaners by color and record this in the data collection table for Scenario 1. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/23/Lab_23_Tables_1_and_2.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Tables 1 and 2</a>
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Then, restore the population to 50 by adding one pipe cleaner of the same color for each of the remaining pipe cleaners. Hold these to the side until they are all gathered.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">Then, sprinkle the pipe cleaners into the tray as previously described (steps 6-7). Repeat this process for three more rounds consisting of 25 selections each and record the counts for each of the rounds in the data collection table for Scenario 1.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Remove all pipe cleaners from the tray after the fourth round.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">For Scenario 2, again count out 12 white, 12 black, and 26 gray pipe cleaner segments and sprinkle them randomly into the tray.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">Follow the same protocol as in Scenario 1. However, when given the signal, the grabbing partner should keep their eyes closed. To aid in accuracy, it may help to position the hand near to the tray before grabbing.
</div></li><li data-sub-note-item="1-17"><div class="lab-step">Repeat this process 25 times, switching partner roles, and record the remaining pipe cleaner amounts in the data collection table for Scenario 2.
</div></li><li data-sub-note-item="1-18"><div class="lab-step">Then, restore the population to 50 based on that count. Do this for all four rounds. NOTE: In the second simulation, you will be using the eyes-open and eyes-closed predation strategies as previously described to select pipe cleaners of various lengths.
</div></li><li data-sub-note-item="1-19"><div class="lab-step">For Scenario 3, gather all 100 of the pipe cleaners that have been cut to varying lengths to represent different phenotypes.
</div></li><li data-sub-note-item="1-20"><div class="lab-step">One partner should hold all the pipe cleaners upright and loosely in one hand resting on the tabletop, such that the bottom end of each pipe cleaner rests against the tabletop.
</div></li><li data-sub-note-item="1-21"><div class="lab-step">Now, the partner that is not holding the pipe cleaners should close their eyes. When given an audible signal, the partner should open their eyes and grab the first pipe cleaner they see from their partner&#39;s hand.
</div></li><li data-sub-note-item="1-22"><div class="lab-step">Repeat this process 50 times (step 21). However, the partners should not switch roles during the round this time. The partner holding the pipe cleaners should always be the one giving the signal and never grabbing from the bunch.
</div></li><li data-sub-note-item="1-23"><div class="lab-step">After the first round consisting of 50 selections, count the remaining pipe cleaners by length. Then, record this information in the data collection table for scenario three. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/23/Lab_23_Tables_3_and_4.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Tables 3 and 4</a>
</div></li><li data-sub-note-item="1-24"><div class="lab-step">Add one pipe cleaner of the same length as each of the remaining ones to restore the population to 100. This will likely require more pipe cleaners than were originally cut. Try to use scraps from the class to reduce waste.
</div></li><li data-sub-note-item="1-25"><div class="lab-step">Repeat this for three more rounds, alternating which partner holds or grabs each round.
</div></li><li data-sub-note-item="1-26"><div class="lab-step">To perform Scenario 4, gather the varied-length pipe cleaners in their original proportions.
</div></li><li data-sub-note-item="1-27"><div class="lab-step">Now repeat the grabbing process, as described in Scenario 3. However, only remove 30 pipe cleaners instead of 50.
</div></li><li data-sub-note-item="1-28"><div class="lab-step">Divide the count at the end of each round by two for each phenotype 4 inches or below, rounding fractions down.
</div></li><li data-sub-note-item="1-29"><div class="lab-step">Then, record these values in the data recording table for Scenario 4.
</div></li><li data-sub-note-item="1-30"><div class="lab-step">Use the relative proportions of the phenotypes in the final population to restore the population to 100. When restoring the population to 100, it may be necessary to calculate relative proportions of phenotypes.
</div></li><li data-sub-note-item="1-31"><div class="lab-step">Repeat this for three more rounds, again alternating holding and grabbing the pipe cleaners.
</div></li><li data-sub-note-item="1-32"><div class="lab-step">For each scenario calculate the survival for each phenotype, that is the proportion of the phenotype surviving.
</div></li><li data-sub-note-item="1-33"><div class="lab-step">Then, calculate the relative fitness, or w, between each round. As reproductive rate does not vary in this simulation, this should always be considered equal, or 1.
</div></li><li data-sub-note-item="1-34"><div class="lab-step">Also, calculate the selection coefficients for each phenotype.
</div></li><li data-sub-note-item="1-35"><div class="lab-step">Now, use the relative frequencies of each phenotype to create histograms with appropriately labeled axes for each scenario showing the population before any selection took place and then alongside these in a different color after four rounds of selection.
</div></li><li data-sub-note-item="1-36"><div class="lab-step">Identify the type of selection taking place in each scenario and label the graphs. 
</div></li><li data-sub-note-item="1-37"><div class="lab-step">Develop a hypothesis to explain your observations. 
</div></li></ul></li></ol>

Natural Selection: Calculating Fitness and Selection - Procedure

Doğal Seleksiyon

Simulating Natural Selection
ExpandTo begin, cut the white, black, and gray pipe cleaners into quarters, which should produce a total of 100 pieces that ...