The authors acknowledge the financial support of the Social Sciences and Humanities Research Council of Canada (SSHERC), Natural Sciences and Engineering Research Council of Canada (NSERC), Fonds de Recherche Nature et Technologies du Qu&#233;bec (FQRNT) and Fonds de Recherche sur la Soci&#233;t&#233; et Culture du Qu&#233;bec (FQRSC).

<ol>
	<li>Fredricks, J. A., Blumenfeld, P. C., Paris, A. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=School+engagement:+Potential+of+the+concept,+state+of+the+evidence.">School engagement: Potential of the concept, state of the evidence.</a> Rev. Educ. Res. 74 (1), 59-109 (2004).</li><li>Clark, R. C., Mayer, R. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> E-learning and the Science of Instruction. , (2011).</li><li>Zhang, D., Zhou, L., Briggs, R. O., Nunamaker, J. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Instructional+video+in+e-learning:+Assessing+the+impact+of+interactive+video+on+learning+effectiveness.">Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness.</a> Inform. Manage. 43 (1), 15-27 (2006).</li><li>Freeman, F. G., Mikulka, P. J., Prinzel, L. J., Scerbo, M. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+an+adaptive+automation+system+using+three+EEG+indices+with+a+visual+tracking+task.">Evaluation of an adaptive automation system using three EEG indices with a visual tracking task.</a> Biol. Psychol. 50, 61-76 (1999).</li><li>Glimcher, P., Rustichini, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuroeconomics:+The+consilience+of+brain+and+decision.">Neuroeconomics: The consilience of brain and decision.</a> Science. 306 (5695), 447-452 (2004).</li><li>Lieberman, M. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Social+Cognitive+neuroscience:+A+review+of+core+processes.">Social Cognitive neuroscience: A review of core processes.</a> Annu. Rev. Physiol. 58, 259-289 (2007).</li><li>Pope, A. T., Bogart, E. H., Bartolome, D. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biocybernetic+system+evaluates+indices+of+operator+engagement+in+automated+task.">Biocybernetic system evaluates indices of operator engagement in automated task.</a> Biol. Psychol. 40 (1-2), 187-195 (1995).</li><li>Mandryk, R., Inkpen, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physiological+indicators+for+the+evaluation+of+co-located+collaborative+play.">Physiological indicators for the evaluation of co-located collaborative play.</a> , (2004).</li><li>Allaire-Duquette, G., Charland, P., Riopel, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=At+the+very+root+of+the+development+of+interest:+Using+human+body+contexts+to+improve+women&#8217;s+emotional+engagement+in+introductory+physics.">At the very root of the development of interest: Using human body contexts to improve women&#8217;s emotional engagement in introductory physics.</a> Eur. J. Phy. Ed. 5 (2), 31-48 (2014).</li><li>Bradley, M. M., Lang, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+emotion:+The+self-assessment+manikin+and+the+semantic+differential.">Measuring emotion: The self-assessment manikin and the semantic differential.</a> J. Behav. Ther. Exp. Psy. 25 (1), 49-59 (1994).</li><li>Lang, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+emotion+probe:+Studies+of+motivation+and+attention.">The emotion probe: Studies of motivation and attention.</a> Am. Psychol. 50 (5), 372-385 (1995).</li><li>Ekman, P., Felt Friesen, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=false,+and+miserable+smiles.">false, and miserable smiles.</a> J. Nonverbal Behav. 6 (4), 238-252 (1982).</li><li>Van Kuilenburg, H., Den Uyl, M. J., Isra&#235;l, M. L., Ivan, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+face+and+gesture+analysis.">Advances in face and gesture analysis.</a> , 371-372 (2008).</li><li>Cacioppo, J., Tassinary, L. G., Berntson, G. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Handbook of Psychophysiology. , (2007).</li><li>Lubar, J. F., Swartwood, M. O., Swartwood, J. N., O&#8217;Donnell, P. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+the+effectiveness+of+EEG+neurofeedback+training+for+ADHD+in+a+clinical+setting+as+measured+by+changes+in+T.O.V.A.+scores,+behavioral+ratings,+and+WISC+R+performance.">Evaluation of the effectiveness of EEG neurofeedback training for ADHD in a clinical setting as measured by changes in T.O.V.A. scores, behavioral ratings, and WISC R performance.</a> Biofeedback Self-reg. 20 (1), (1995).</li><li>Mikulka, P. J., Freeman, F. G., Scerbo, M. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+a+biocybernetic+system+on+the+vigilance+decrement.">Effects of a biocybernetic system on the vigilance decrement.</a> Hum. factors. 44 (4), 654-664 (2002).</li><li>Freeman, F. G., Mikulka, P. J., Scerbo, M. W., Scott, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+evaluation+of+an+adaptive+automation+system+using+a+cognitive+vigilance+task.">An evaluation of an adaptive automation system using a cognitive vigilance task.</a> Biol. Psychol. 67 (3), 283-297 (2004).</li><li>Chaouachi, M., Chalfoun, P., Jraidi, I., Frasson, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Affect+and+mental+engagement:+Toward+adaptability+for+intelligent+systems.">Affect and mental engagement: Toward adaptability for intelligent systems.</a> Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference (FLAIRS 2010), Association for the Advancement of Artificial Intelligence. , 355-360 (2010).</li><li>Courtemanche, F., Ortiz de Guinea, A., Titah, R., Fredette, M., Labont&#233;-LeMoyne, &. #. 2. 0. 1. ;. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Precision+is+in+the+eye+of+the+beholder:+Application+of+eye+fixation-related+potentials+to+information+systems+research.">Precision is in the eye of the beholder: Application of eye fixation-related potentials to information systems research.</a> J. Assoc. Inf. Syst. 15 (10), 651-678 (2014).</li><li>Courtemanche, F., Ortiz de Guinea, A., Titah, R., Fredette, M., Labont&#233;-Lemoyne, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Applying+eye+fixation-related+potentials+to+information+systems+research:+Demonstration+of+the+method+during+natural+IS+use+and+guidelines+for+research.">Applying eye fixation-related potentials to information systems research: Demonstration of the method during natural IS use and guidelines for research.</a> J. Assoc. Inf. Syst. 15 (10), (2014).</li><li>Courtemanche, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Un outil d&#8217;&#233;valuation neurocognitive des interactions humain-machine Doctoral thesis. , (2014).</li><li>Charland, P., L&#233;ger, P. M., Mercier, J., Skelling-Desmeules, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessing+multiple+dimensions+of+learner+engagement+during+science+problem+solving+using+psychophysiological+and+behavioral+measures.">Assessing multiple dimensions of learner engagement during science problem solving using psychophysiological and behavioral measures.</a> , (2014).</li><li>Venables, P. H., Christie, M. J., Martin, I., Venables, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electrodermal+activity.">Electrodermal activity.</a> Techniques in Psychophysiology. , 3-67 (1980).</li><li>Boucsein, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Electrodermal Activity. , (2012).</li><li>Sarlo, M., Palomba, D., Buodo, G. M., Minghetti, R., Stegagno, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Blood+pressure+changes+highlight+gender+differences+in+emotional+reactivity+to+arousing+pictures.">Blood pressure changes highlight gender differences in emotional reactivity to arousing pictures.</a> Biol. Psychol. 70 (3), 188-196 (2005).</li><li>Martens, R. L., Gulikers, J., Bastiaens, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+impact+of+intrinsic+motivation+on+e-learning+in+authentic+computer+tasks.">The impact of intrinsic motivation on e-learning in authentic computer tasks.</a> J. Comput. Assist. Lear. 20 (5), 368-376 (2004).</li></ol>

The authors have nothing to disclose.

من حيث الخطوات الحاسمة في البروتوكول، ينبغي أولا أن أشير إلى أن نوعية البيانات هي دائما التركيز الرئيسي لتقنيات جمع العصبية. في هذه المنهجية، يجب أن مساعدي البحوث تولي اهتماما خاصا لتعليمات الموضوعات للحد من حركات الرأس التي من شأنها أن تتداخل مع مراقبة التكافؤ (فقدان الصحيحة زاوية مواجهة للكاميرا) أو توليد التحف تخطيط العضل في EEG. من ناحية أخرى، لا بد من الحفاظ على التوازن بين أصالة حل مشكلة حقيقية والمداخلات لمزيد من جمع البيانات مريح. ومن المهم أيضا أن نلاحظ أن جمع البيانات EEG يخضع لتقلبات الكهرومغناطيسية في البيئة. مرافق EEG التقليدية في محاولة لعزل أجهزتها من التقلبات الكهرومغناطيسية مع أقفاص فاراداي. ومع ذلك، لأن بعض المعدات المستخدمة في هذه المنهجية من شأنه أن يولد التقلبات الكهرومغناطيسية (أساسا جهاز تتبع العين) داخل قفص فاراداي، الغير أن النهج تكون غير فعالة. نتغلب على القضايا الكهرومغناطيسية عن طريق إيلاء اهتمام خاص لأسس والتدريع جميع الأجهزة الكهربائية. أما بالنسبة للتعديلات واستكشاف الأخطاء وإصلاحها مع هذه التقنية، واعتمدت استراتيجية التزامن الأولي على قدرة برنامج المزامنة على وجه التحديد &quot;بداية&quot; جمع البيانات على أجهزة الكمبيوتر وبرامج متعددة معا. لأن لوحظت تأخيرات حرجة وغير متناسقة بين أجهزة الكمبيوتر والبرامج، وأصبحت بعد جمع-المزامنة اللازمة. ونتيجة لذلك، تم إضافة جهاز syncbox إلى الهندسة المعمارية. وsyncbox يرسل علامة TTL لكافة أجهزة الكمبيوتر والبرامج التي تقوم بجمع البيانات. يصبح التزامن مسألة احتساب التأخير بين علامات syncbox الأولى. واحد الحد من هذه التقنية التي تحتاج إلى أن المذكور هو دقة تحليل الإشارات، التي تقتصر تلاه مؤشر الاشتباك المعرفي. بسببالافتراضات الأساسية من الاتحاد الفرنسي للتنس، يتم إنشاء هذا المؤشر على أساس الحقبة 1 ثانية: السيناريو الاشتباك المعرفي يولد قيمة كل ثانية. في هذا النموذج، الذي يركز على حل مشكلة أصيلة، وهذا إطار زمني مقبول، ولكن دراسات أكثر دقة الاشتباك قد تواجه بعض القيود مع هذا الإطار الزمني للتحليل. فيما يتعلق بأساليب القائمة / بديل، لا بد من الإشارة إلى أن التكافؤ العاطفي ويمكن أيضا أن تستمد مع ضغط حجم الدم 18، 25 أجهزة الاستشعار. ويمكن أيضا أن تكون متكاملة هذه التقنية في البحوث المستقبلية لتقييم دقتها مقارنة مع إشارة التكافؤ من برنامج التعرف على الوجه العاطفة. يجب علينا أيضا أن نذكر أن مؤشر المشاركة المعرفية المستخدمة في هذه الدراسة هو واحد المعروفة التي تم استخدامها في الأبحاث المنشورة السابق. بعض الشركات المصنعة للأجهزة EEG خفيفة تدعي توفير قدر مماثل، ولكن من الصعب تقييم جودة البيانات الخام والمصنعة منذالخوارزميات هي غير منشورة. أخيرا، تقدم هذه التقنية العديد من التطبيقات الممكنة في مختلف المجالات. بالطبع، وسوف تكون ذات قيمة في مجال التعليم. من بين الاحتمالات الأخرى، يمكن لهذه التقنية تقييم المشاركة أن تكون أداة قوية لإعلام مصممي ملاعب. على سبيل المثال، كما مارتنز، Gulikers وBastiaens 26 لاحظ، &quot;في كثير من الأحيان، يميل المطورون لإضافة الملتيميديا ​​إضافات، والمحاكاة، وهلم جرا، وذلك أساسا بسبب التكنولوجيا تجعل من الممكن، على الرغم من أنها لا تستند إلى تحليل دقيق التعليمي والتصميم &quot;. وهكذا، البيانات العصبية يمكن أن يفيد مصممي إذا الإضافة محددة هي قيمة، إذا كان المحتوى معقد جدا، إذا استراتيجيات التعلم المقترحة تتسم بالكفاءة، وما إلى ذلك وبالإضافة إلى ذلك، وتقييم في الوقت الحقيقي من المشاركة المتعلم يفتح الاحتمالات عن التكيف التعلم الإلكتروني أو تقييم الإلكترونية البيئات. يمكننا أن نتوقع من المتعلم، وهو يرتدي خوذة EEG خفيفة الوزن، وتحذيره من قبل النظام عرجن له / مستوى خطبتها آخذ في الانخفاض، وعلى سبيل المثال، أدى إلى وقفة أو تتفاعل وفقا لذلك. سيكون من الممكن أيضا لتطوير مهام التقييم على التكيف، استنادا إلى مؤشرات الاشتباك. ويجري حاليا إجراء قدر لا بأس به من بحث والتطوير في مجال مبتكرة من واجهات الدماغ والحاسوب (BCI).

مشاركة يلعب دورا حاسما في التعلم. لكلارك وماير 2 &quot;عن التعلم يتطلب الاشتباك،&quot; بغض النظر عن وسائل الاعلام التسليم. واقترح تشانغ وآخرون. 3 كما أن زيادة مشاركة الطلاب يمكن أن تحسن نتائج التعلم، مثل حل المشكلات ومهارات التفكير النقدي. تحديد الاشتباك لا يزال يشكل تحديا. في مراجعة أدبهم، Fredricks، بلومنفلد وباريس 1 تعريف المشاركة بطبيعتها المتعددة الجوانب والمتمثلة: &quot;يستمد مشاركة السلوكي على فكرة المشاركة؛ ويشمل المشاركة في الأنشطة الأكاديمية والاجتماعية واللامنهجية. (...) المشاركة العاطفي يشمل ردود الفعل الإيجابية والسلبية للمعلمين وزملاء الدراسة، والأكاديميين، والمدرسة، ويفترض لخلق علاقات مع كائن والنفوذ استعداد للقيام بهذا العمل. أخيرا، وتوجه الاشتباك المعرفي على فكرة الاستثمار العقلي؛ أنه يشتمل على التفكير والاستعداد لبذل جهد غير المصنفةاقتضت أن يفهم الأفكار المعقدة والصعبة مهارات سيد &quot;. ادعى Fredricks، بلومنفلد وباريس 1 كما أن التركيز على السلوك، والعاطفة، والإدراك، ضمن مفهوم الخطبة، قد توفر خصائص أغنى من التعلم. وأشار هؤلاء المؤلفين إلى أن الجسم القوي للبحوث ويتناول كل مكون من الانخراط بشكل منفصل، ولكن لم يتم دراسة هذه العناصر جنبا إلى جنب. لاحظوا أيضا أن قلة المعلومات المتوفرة حول التفاعلات بين الأبعاد وأن المزيد من الدراسات يمكن أن تسهم في تخطيط تدخلات التدريس دقيقا. وكخطوة في هذا الاتجاه، توضح هذه الورقة منهجية البحث التي تم تطويرها لجمع وتحليل البيانات الكمية والنوعية، بشكل متزامن، على المشاركة السلوكي والعاطفي والإدراكي خلال مهام التعلم. يصل العلوم العصبية في التعليم BehavIOR، والانخراط في السلوك بالتالي، منذ فترة طويلة محور الدراسات في مجال التعليم: تصميمات البحوث التي تركز أساسا على التغيرات في المعرفة والسلوك التي تحدث على مدى فترات طويلة من الزمن، وبين ما قبل وما بعد الاختبارات، وعلى فترات لساعات أو أسابيع أو شهور أو سنوات. التمييز بين المشاركة السلوكي والعاطفي، والمعرفي لا يزال يشكل تحديا لأن أبعاد الماضيين ليست ملاحظتها بشكل منتظم من الخارج. يجب إما أن يستدل على الإدراك والعواطف من الملاحظات أو تقييمها مع تدابير تقرير المصير. من جهة نظر خارجية، فإنه لا يزال من الصعب تحديد ما إذا كان الطلاب يحاولون الحصول على العمل المنجز في أسرع وقت ممكن أو باستخدام استراتيجيات التعلم على مستوى عميق لإتقان محتوى معين. في واقع الأمر، لم تتمكن من العثور على أي دراسات منشورة باستخدام تدابير موضوعية مباشرة الاشتباك المعرفي Fredricks، بلومنفلد وباريس 1. التطورات التكنولوجية الحديثة فيخلقت مجال علوم الأعصاب إمكانيات جديدة للبحث في مجال التعليم. طرق جديدة لجمع البيانات وتحليل الخوارزميات المتقدمة في مجال بيئة العمل العصبية تبدو واعدة جدا للدراسات النوعية والكمية خلال مهام التعلم. تخصصات أخرى، مثل الاقتصاد، وعلم النفس، والتسويق، والهندسة البشرية، وقد تم استخدام القياسات الفسيولوجية العصبية لتقييم المشاركة المعرفية لبعض الوقت 4-8. تدابير العصبية، إلى جانب خوارزميات تحليل كفاءة، تسمح واحد لدراسة الظاهرة من دون إزعاج ذلك. بحكم طبيعتها، واستبيانات التقرير الذاتي تنسحب فيه الطلاب من التعلم. تسمح تدابير العصبية تصميمات البحوث التي يتعين الاضطلاع بها في بيئات التعلم أكثر واقعية. وتشمل هذه الأدوات المعدات لمراقبة معدل ضربات القلب ومعدل التنفس وضغط الدم ودرجة حرارة الجسم، وقطره تلميذ، والنشاط الكهربي، كهربية (EEG)، وما إلى ذلك. <stرونغ&gt; جمع البيانات المتزامنة على السلوكية والعاطفية والمعرفية المشاركة كنتائج التمثيلية التالية لاستخدام هذا البروتوكول، وهذه الورقة النتائج الجزئية للدراسة التي كان المتعلمين على حل، على شاشة الكمبيوتر، وعشرة المشاكل في الفيزياء الميكانيكية. وقد وضعت هذه المشاكل في العمل السابق 9. وقد تم جمع البيانات العصبية في حين أن المتعلمين تم حل المشاكل والاسترخاء خلال 45 ق استراحة، مع عيونهم مغلقة، بعد كل مشكلة. كما ذكر أعلاه، تتكون بيانات التعاقد السلوكي للتفاعلات البرمجيات (حركات الماوس والنقرات)، نظرات العين، والأداء وأجوبة على الأسئلة التي تنتجها المتعلم التفاعل مع النظام أثناء إنجاز المهمة 1. تم استخدام نظام تتبع العين لجمع التفاعلات البرامج والبيانات نظرات العين. وقد تم جمع بيانات الأداء (الوقت من أجل حل المشكلة، صحة الإجابات) على<html> استبيان الموقع الذي تم استخدامه لتقديم هذه المهمة. وقد استخدم هذا الموقع أيضا لجمع بيانات تقرير المصير التي تم جمعها مع استبيان مقتبس من برادلي وانج 10. مشاركة العاطفي يشمل توصيف المشاعر. وفقا لانج 11، وتتميز العواطف من حيث التكافؤ (سارة / غير سارة) والاستثارة (الهدوء / أثار). والبيانات التي تم جمعها المشاركة العاطفية وفقا لذلك، وذلك باستخدام التلقائي برنامج التعرف على العاطفة الوجه يحدد مقدار التكافؤ العاطفي والنشاط الكهربي التشفير / الاستشعار عن الإثارة 12،13. النشاط الكهربي (EDA) يشير إلى المقاومة الكهربائية المسجلة بين قطبين عندما يتم تمرير تيار كهربائي ضعيف جدا بثبات بينهما. أظهر Cacioppo، Tassinary وبرنتسون 14 أن المقاومة سجلت تختلف وفقا لالإثارة في هذا الموضوع. وبالتالي، بيانات النفسية لمثل التكافؤ أو الإثارة، وتعتبر كما يرتبط إلى التواصل العاطفي. الطبقة = &quot;jove_content&quot;&gt; وأخيرا، يتم جمع البيانات من خلال المشاركة المعرفية كهربية (EEG). تدابير EEG، على فروة الرأس، وتزامن النشاط الكهربائي من مجموعات من الخلايا العصبية في الدماغ. الإشارات الكهربائية المسجلة من فروة الرأس وغالبا ما تكون متذبذبة وتتألف من مكونات تردد. من جانب الاتفاقية، يتم تجميع هذه الترددات في تسلسل، والمعروفة باسم العصابات. على سبيل المثال، ألفا وبيتا وثيتا العصابات هي محور هذه الدراسة. وفقا للدراسات العلمية العصبية 14، هذه العصابات تعكس مختلف قدرات المعالجة المعرفية في مناطق معينة من الدماغ. وبالتالي، فإن تحليل كثافة القدرة الطيفية (PSD) من ترددات محددة، جنبا إلى جنب مع العديد من الدراسات 7،15 على اليقظة والانتباه، ويسمح للباحثين لقياس الاشتباك المعرفي خلال مهمة. كما لوحظ ميكولكا وآخرون 16، وقد أظهرت الأبحاث وجود علاقة مباشرة بين النشاط بيتا واليقظة المعرفية وعلاقة غير مباشرة بين ألفا ود النشاط ثيتا واليقظة. وبالتالي، وضعت البابا، بوجارت وBartoleme 7 مؤشر الاشتباك الذي يحسب PSD من ثلاثة نطاقات: بيتا / (ألفا + ثيتا). تم التحقق من صحة هذه النسبة في دراسات أخرى على المشاركة 16،17،18. لتوصيف الاشتباك المعرفي على مر الزمن، وتحويل فورييه السريع (الاتحاد الفرنسي للتنس) بتحويل إشارة EEG من كل موقع نشط (F3، F4، O1، O2) في طيف الطاقة. يتم احتساب مؤشر المشاركة EEG في وقت T من المتوسط ​​من كل نسبة المشاركة في 20 ثانية انزلاق النافذة السابقة الوقت T. ويتكرر هذا الإجراء كل ثانية، ويستخدم نافذة انزلاق جديد لتحديث الفهرس. بما أن الهدف من هذه المنهجية هو تقديم تحليل غني للأبعاد المتعددة للمشاركة، مزامنة البيانات أمر بالغ الأهمية. كما يجيه وآخرون 19 تذكير القراء ومصنعي المعدات نوصي بشدة باستخدام جهاز كمبيوتر واحد فقط لكل أداة قياس لضمان دقتها المحدد جنيهفيل. وهكذا، عندما يتم توظيف أجهزة كمبيوتر متعددة، والتزامن بين أجهزة الكمبيوتر تسجيل يصبح خطوة حاسمة. لا يمكن لجميع أن تبدأ التسجيلات في نفس الوقت بالضبط، ولكل تيار البيانات لديها إطاره وقت محدد (على سبيل المثال، ثانية 0 العين تتبع ≠ 0 ثانية من EEG أو البيانات الفسيولوجية). وهذا أمر مهم للغاية: عدم الاتساق بين البيانات والجداول يعني أخطاء في تقدير حجم كل البعد الاشتباك. هناك طرق مختلفة لمزامنة التسجيلات الفسيولوجية والسلوكية المتزامنة. ويمكن تقسيم هذه الطرق إلى نهجين رئيسيين؛ المباشرة وغير المباشرة 20. ويستند بروتوكول المعروضة في المقطع التالي على نهج غير مباشر حيث يتم استخدام جهاز خارجي، وهو syncbox، لإرسال الترانزستور الترانزستور المنطق (TTL) إشارات لجميع أجهزة التسجيل (كما هو موضح في الشكل رقم 1). حيث أن كل قطعة من المعدات لديه وقت البدء مختلفة، تسجل علامات TTL في ملفات السجل مع قريب<html> تأخير. ثم يتم استخدام علامات لإعادة تنظيم الإشارات وبالتالي ضمان التزامن الصحيح بعد كل تسجيل. ويستخدم برنامج برامج التحليل السلوكي الذي يسمح التكامل ملف خارجي لإعادة مزامنة-الجدول الزمني للكل دفق البيانات وإجراء تحليل كمي ونوعي لكل البعد الاشتباك. <img alt="الشكل 1" src="/files/ftp_upload/52627/52627fig1.jpg" /> الشكل 1. العمارة في نظام جمع البيانات، ومختبر البيئة التي السلوكي (العين تتبع)، العاطفي (EDA والعاطفة الوجه) والمعرفية البيانات (EEG) إشراك يتم جمع يحتوي على العديد من أجهزة الكمبيوتر. هذا يثير تحديا التزامن للبيانات التي يتم الرجوع إليها في الساعات الكمبيوتر الخاصة بهم. لتكون قادرة على تحليل جميع البيانات في نفس الوقت إشارة، وإعداد مختبر ينطوي على syncbox التي ترسل إشارات TTL لجميع البيانات والجداول.NK &quot;&gt; اضغط هنا لمشاهدة نسخة أكبر من هذا الرقم. لتقييم دقة منهجية من حيث التزامن، تم إدخال 45 ثانية توقف قبل كل المشاكل الفيزياء الميكانيكية. خلال هذه الوقفات، كانت موضوعات للاسترخاء وإغلاق أعينهم. كما رأينا في دراسات أخرى 4،9،16،17،18، ينبغي لهذه الوقفات لحث اختلافات كبيرة في إشارة جمع: اثنان النقاط تلميذ العين في (المشاركة السلوكي) على الفور تختفي تتبع العين وانخفاض فوري في الاشتباك المعرفي (EEG إشارة) لوحظ. وتستخدم هذه المكونات المحددة للإشارة إلى تقييم صحة العامة للمزامنة. نشر مؤخرا من الأوراق التي تعتمد كليا أو جزئيا على هذا الإجراء تزامن، في مجالات نظم المعلومات 19، والتفاعلات بين الإنسان والآلة والتعليم 21 9، 22، يقدم دليلا على فعاليتها.

<table><tbody><tr><td>EGI GSN-32&amp;nbsp;</td><td>EGI</td><td></td><td>Dense array EEG</td></tr><tr><td>Netstation v.5.0</td><td>EGI</td><td></td><td>EEG data collection software: EEG is collected with 32-electrode dense array electroencephalography (dEEG) geodesic sensor net using Netstation acquisition software and EGI amplifiers (Electrical Geodesics, Inc). The vertex (recording site Cz) is the reference electrode for recording. Impedance is kept below 50 k&amp;Omega; with a sampling rate of 250 Hz.&amp;nbsp;</td></tr><tr><td>Facereader v.4</td><td>Noldus</td><td></td><td>Facial emotion recognition software</td></tr><tr><td>Syncbox</td><td>Noldus</td><td></td><td>Syncbox start the co-registration of EEG and gaze data by sending a Transistor-Transistor Logic (TTL) signal to the EGI amplifier and a keystroke signal to the Tobii Studio v 3.2.</td></tr><tr><td>Logitech C600&amp;nbsp; Webcam</td><td></td><td>960-000396</td><td>Webcam used to gather video data sent to mediarecorder and that will be analyzed in Facereader</td></tr><tr><td>The Observer XT</td><td>Noldus</td><td></td><td>Integration and synchronization software: The Noldus Observer XT (Noldus Information Technology) is used to synchronize all behavioral, emotional and cognitive engagement data.&amp;nbsp;</td></tr><tr><td>On-Screen LED illumination</td><td>Noldus</td><td></td><td>Neon positioned on computer screen in order to correctly light the face of subjects</td></tr><tr><td>MediaRecorder</td><td>Noldus</td><td></td><td>Video data collection software</td></tr><tr><td>Tobii 60X</td><td>Tobii</td><td></td><td>Collect eye-movement patterns :&amp;nbsp; used to record subjects&amp;rsquo; eye movement patterns at 60Hz during the experiment.&amp;nbsp;</td></tr><tr><td>Tobii Studio v.3.2</td><td>Tobii</td><td></td><td>Eye-tracking data collection and analysis software</td></tr><tr><td>Analyzer 2</td><td>Brainvision</td><td></td><td>EEG signal processing software</td></tr><tr><td>Acqknowledge v.4.0</td><td>Biopac</td><td>ACK100M</td><td>Physiological signal acquisition and processing software</td></tr><tr><td>Control III germicide solution</td><td>Maril Products.</td><td>10002REVA-20002-1</td><td>Disinfectant solution used with EEG helmets : recommended by EGI</td></tr><tr><td>Unipark</td><td>QuestBack AG</td><td></td><td>Online survey environment</td></tr></tbody></table>

assessing the multiple dimensions of engagement to characterize learning: a neurophysiological perspective

In a recent theoretical synthesis on the concept of engagement, Fredricks, Blumenfeld and Paris1 defined engagement by its multiple dimensions: behavioral, emotional and cognitive. They observed that individual types of engagement had not been studied in conjunction, and little information was available about interactions or synergy between the dimensions; consequently, more studies would contribute to creating finely tuned teaching interventions. Benefiting from the recent technological advances in neurosciences, this paper presents a recently developed methodology to gather and synchronize data on multidimensional engagement during learning tasks. The technique involves the collection of (a) electroencephalography, (b) electrodermal, (c) eye-tracking, and (d) facial emotion recognition data on four different computers. This led to synchronization issues for data collected from multiple sources. Post synchronization in specialized integration software gives researchers a better understanding of the dynamics between the multiple dimensions of engagement. For curriculum developers, these data could provide informed guidelines for achieving better instruction/learning efficiency. This technique also opens up possibilities in the field of brain-computer interactions, where adaptive learning or assessment environments could be developed.

<html> أرقام 2 و 3 عرض لقطات من نتائج التكامل وتزامن البيانات الاشتباك السلوكية والعاطفية والمعرفية السلوكية في تطبيق برامج التحليل. في كلا الرقمين، ينظم القسم الأيسر الموضوعات البحثية ونظام الترميز. في الجزء الأوسط، وشريط فيديو (مع النقط الحمراء) يبين العين البصر موضوع خلال هذه المهمة. ويمكن الاستدلال على المشاركة السلوكي هذا الموضوع بناء على ما هو / هي تبحث في أثناء المهمة والإجراءات ما تؤخذ. في الجزء السفلي، علامة الوقت التمرير بشكل متزامن في ثلاثة مسارات البيانات: جمعية الإمارات للغوص (الشهوة) والوجه التكافؤ الانفعال العاطفي للمشاركة ومؤشر المشاركة EEG للمشاركة المعرفي. عندما يتم جمع البيانات من جميع المواد، ويوفر البرنامج أيضا إحصاءات وصفية الأساسية التي يمكن في نهاية المطاف أن تستخدم لإجراء تحليل intersubject في غيرها من برامج التحليل الإحصائي. والأنف والحنجرة &quot;FO: المحافظة على together.within صفحة =&quot; دائما &quot;&gt; <img alt="الرقم 2" src="/files/ftp_upload/52627/52627fig2.jpg" /> الشكل 2. متعددة الأبعاد الاشتباك البيانات في بداية مهمة حل مشكلة. لقطة للموضوع في بداية مرحلة حل المشكلة. المتعلم هو قراءة مقدمة المشكلة: نظرات العين على السطر الثالث. في هذا الوقت (ويمثل الخط الأحمر مؤشر الوقت)، والإثارة هذا الموضوع قد مرت للتو ذروة تحسبا لمشكلة يجب حلها ولكن لا تزال مرتفعة مقارنة مع خط الأساس، التكافؤ العاطفي يبدو محايدا، ويبدو أن الاشتباك المعرفي EEG في الأقصى . <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52627/52627fig2large.jpg" target="_blank">الرجاء انقر هنا لمشاهدة نسخة أكبر من هذا الرقم.</a> <img alt="الشكل (3)" src="/files/ftp_upload/52627/52627fig3.jpg" /> الشكل 3. متعددة الأبعاد الاشتباك البيانات الدرجي وقفة في العمل. بيانات من وقفة أمام مهمة حل المشكلة. هذا التوقف هو مفيد لإنشاء خط الأساس هذا الموضوع تماما قبل أن المهمة. هنا، لأن عيني الشخص مغلقة، البيانات التكافؤ غير متوفرة. المشاركة المعرفي (إشارة EEG) يرتفع قليلا عن الحد الأدنى لها. موضوع ببطء إعادة الانخراط مع المهمة، وتوقع نهاية وقفة. الاستثارة (إشارة EDA) في تناقص مستمر. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52627/52627fig3large.jpg" target="_blank">الرجاء انقر هنا لمشاهدة نسخة أكبر من هذا الرقم.</a>

Watch this Scientific Journal Video about Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective at JoVE.com

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

This paper aims to describe the techniques involved in the collection and synchronization of the multiple dimensions (behavioral, affective and cognitive) of learners&#8217; engagement during a task.

تقييم أبعاد متعددة الاشتباك لوصف التعلم: A العصبية وجهة نظر

In a recent theoretical synthesis on the concept of engagement, Fredricks, Blumenfeld and Paris1 defined engagement by its multiple dimensions: ...

assessing-multiple-dimensions-engagement-to-characterize-learning

Nanyang Technological University

Research

JoVE Journal

Behavior

12.4K Views.  Université du Québec à Montréal. This paper aims to describe the techniques involved in the collection and synchronization of the multiple dimensions (behavioral, affective and cognitive) of learners’ engagement during a task. 

Video: Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

Study Motor Skill Learning by Single-pellet Reaching Tasks in Mice

Reaching for and retrieving objects require precise and coordinated motor movements in the forelimb. When mice are repeatedly trained to grasp and retrieve food rewards positioned at a specific location, their motor performance (defined as accuracy and speed) improves progressively over time, and plateaus after persistent training. Once such reaching skill is mastered, its further maintenance does not require constant practice. Here we introduce a single-pellet reaching task to study the acquisition and maintenance of skilled forelimb movements in mice. In this video, we first describe the behaviors of mice that are commonly encountered in this learning and memory paradigm, and then discuss how to categorize these behaviors and quantify the observed results. Combined with mouse genetics, this paradigm can be utilized as a behavioral platform to explore the anatomical underpinnings, physiological properties, and molecular mechanisms of learning and memory.

Persistent practice improves the precision of coordinated movements.&#160;Here we introduce a single-pellet reaching task, which is designed to assess the learning and memory of forelimb skill in mice.&#160;

الدراسة موتور مهارة التعلم عن طريق واحدة بيليه المهام الوصول في الفئران

Reaching for and retrieving objects require precise and coordinated motor movements in the forelimb. When mice are repeatedly trained to grasp and ...

Perspectives on Neuroscience

As usual, the main cause for progress in natural sciences are methodological developments. Of course, conceptual developments follow and go in parallel, but I think the, the tremendous expansion of the field of neurosciences was triggered by a number of methodological breakthroughs at the lowest level. These were the progresses in the domain of molecular biology, genetic engineering, which provided model systems for the study of development for the study of certain diseases.These techniques also provided extremely valuable tools for the biochemical and molecular identification of neurons. We learned about a degree of diversification of morphologically seemingly identical neurons that are endowed with different molecular machineries. All this we owe to the development of molecular biology.A second important factor I think was the development of non-invasive imaging technologies. cause this allowed us to transfer a large number of concepts that have been developed in animal experimentation to investigations in human subjects. So this is the functional magnetic resonance imaging pository emission tomography.Also the introduction of the magneto ence holography, which allowed for much better spatial resolution for the analysis of electric activity in the brain led to a substantial expansion in the field. Then I think a non negligible factor was the availability, increasing availability of of massive computer power because as neurobiology started to apply multi-site recording techniques, which I consider essential for the analysis of neuron network properties, the data became increasingly complex and it became increasingly impossible to just evaluate the data by looking at them as in the classical times when I started in the field, there were no computers. We had to do cross correlation analysis by cutting long strips of paper and moving them over the floor.So the availability of of computing power has greatly advanced at least systems physiology. I think it had a major impact on these developments. And then last but not least, the availability of these computer facilities allowed us also to treat properties of neuronal networks at a theoretical level.The dynamics exhibited by neuronal networks are so complex that only modeling studies and theoretical approaches put us in a position to formulate educated hypothesis. Also, for the search of neuronal codes, we cannot proceed without these search tools. So I think altogether these methodological developments were responsible for the great expansion of the neurosciences, which I think is unprecedented in any Scientific discipline.As far as my own Research is concerned, there are two parts in my biography. Initially I studied developmental processes in the brain. I was particularly interested in developmental processes that are shaped by experience postnatally.And the rationale for this approach was that I felt that the organization of the mature brain is so complex that we better study the developmental principles and try to make sense out of them and try to extrapolate what these developmental processes will eventually lead to. But then an accidental finding that actually happened in this very laboratory where we are sitting changed my life because I discovered inadvertently that neurons in the primary visual cortex of kittens that were awake actually sitting on the table behind me watching a drifting grating, got entrained into highly synchronous oscillatory activity that I could not attribute neither to degrading to the stimulus nor to the main switch in Germany are 50 cycles because it was an oscillation in the 40 hertz range. And so for the first time I saw that spatially distributed neurons could coordinate their activity with very high precision in the millisecond range over fairly large distances.And this triggered the idea that maybe time is used as a coding space for the coordination of distributed neuronal responses. And I found this option so interesting that I decided to neglect the so much beloved field of developmental neurobiology and invest most of our efforts into the further analysis of this phenomenon. And this is now nearly 15 years ago or more.And since then we spent most of our time with multi-site recordings and the search for spatial temporal patents in distributed neural networks because it is our firm belief that information is not only encoded in the discharge rate of neurons as is classically assumed and confirmed, but that additional information is encoded in the precise temporary relations among the individual discharges of neurons whereby zero phase lake correlations. So precise coincidence is probably only the tip of the iceberg. But an important tip because synchronous activity is particularly interesting in neuronal networks because it propagates very easily synchronizing responses is a means to enhance the saliency of neuronal responses with great temporal position.It can be done on a spike by spike basis. And the initial hypothesis was that this synchronization is used at peripheral stages of sensory processing in order to establish relations between features that are processed by spatially distributed neurons. Since then, many more labs have engaged in search for the synchronization phenomena.It started I think in Europe with colleagues like RI who applied EEG techniques to assess synchronous oscillatory activity in the brain and relate these activities to cognitive functions. And since then the the role of oscillations and synchrony has been discussed in a very controversial way. Initial doubts that this phenomenon might exist, it all have now been countered I think, and we are now all engaged in the search for functional consequences.And there is a whole plethora of hypothesis of what that could mean. Does the accumulation Of this vast amount of data that we are confronted with nowadays and that we have very great difficulties to cope with reflect true progress. It certainly does reflect progress because we get to know more and more facts and details about the organization of neurons, neuron networks and the brain as a whole.And this is a necessary consequence of the classical analytical approaches that are applied in the natural sciences. One isolates a subsystem and then describes it in ever greater detail. But this is only one half of the scientific endeavor.What we also need is the inductive strategy. This the synthesis of all those data. And what we are now confronted with is that we have a huge amount of words.We have a tremendous vocabulary that is difficult to remember, but we are lacking the syntax to put those words together into meaningful sentences in many domains. This is the case in particular in systems neuroscience. Therefore we need, I think more theory because conditions have become so complex that near verbal descriptions are probably no longer sufficient to grasp or to accomplish this, this synthetic process.We need formal descriptions, we need analysis tools that allow us to generate models and this requires very powerful computations. And then we need of course synthetic thinkers. That's probably the the most important ingredient in the moment.People who can bundle a large amount of details into meaningful hypothesis or concepts. Now one can of course foster this process by providing the appropriate environment and worldwide one sees efforts to provide such environments by generating institutions that are usually called Institute for Computational Neuroscience or Institute for Theoretical Neuroscience. For the time being, many of these places are still existing in two great in isolation and are not sufficiently linked to experimental institutions.Ideally one would have, one would like to see a very close cooperation between theoreticians and experimentalists, as has been so fruitful in physics where theoretical physicists and experimental physicists very closely collaborate freely, exchange data ideas and do this without jealousy, which is still not the case in our field. But I think biology is now approaching a threshold where it is mature enough to support theoretical approaches in a meaningful way. And here in Frankfurt, we have founded the Frankfurt Institute of Advanced Studies exactly for that purpose because I experienced that physicists and mathematicians, theoreticians in general when embedded in the experimental institute, they tend to to be marginalized.They don't have enough colleagues to talk to because biologists usually are not trained in their language. And so the idea was let's create an institute in which several model systems, biological model systems that have in common to be multi-component systems that are tightly coupled like the moon system or the brain are studied by theoreticians, hoping that these theoreticians might discover common principles in these complex self-organizing systems and that they can share analytical tools, can share tools for model building. And I think it worked out because within about a year this institute grew from zero to 120 scientists.And the special structure of this institute, which is not surprising to colleagues in America, but this is quite exceptional in Europe, is that this institute is funded exclusively by donors private funds. It is not a university institute, it is linked to the university in Frankfurt, but it is finance in a different way for the simple reason that it was impossible to install such an interdisciplinary enterprise within the conventional faculties because what happens there is truly I the disciplinary, it crosses faculties and they seem to be realizable only by having a erect and an own building and gather people who come from very different disciplines under the same roof. Even though those Terms have been taken from physical systems initially, they still grasp some of the characteristics of of of the brain because the brain clearly is a self-organizing system.There's no conductor in the brain to coordinate all the distributed processes. The brain develops in a self organizing way through interaction between genes and environment. There is no instructor, there is no blueprint, a priori.And finally the term applies very well to what we observe in complex systems all the time, namely that complex systems tend to exhibit properties that cannot be described or inferred from the properties of the components. And the brain is a particularly nice example for this fact, which we know from all complex systems there's nothing special about the brain. Something that is special about the brain is that we have on the one side material processes, neuron interactions that can be described from a third person perspective as any other process in our environment.And that emergence from these neuronal interactions are mental phenomena, psychological phenomena such as emotions, thoughts, decisions. So there are realities which I would like to address as social realities which emerge or come into being by the interaction between brains that communicate with each other, mirror each other, ascribe properties to each other, could replace brains by persons, doesn't really matter because what makes the person is finally the brain in its in its bodily setting and due to these interactions phenomena emerge that are to be taken as real phenomena, they are realities, but they have to be described in a different language as the phenomena that bring them forth that are at their origin, namely neuronal interactions. And therefore I think that this is a classical case of emergence where something new is generated by a complex system, nobody would ever be able to infer from the knowledge, complete knowledge of neurons, and even from complete knowledge of neuron networks, that they are capable of developing value systems when they interact With each other.I think the main Problem in our efforts to repair brains, apart from the fact that neurons do not easily regenerate in the central nervous system, they don't like to extend processes once they are severed for reasons that we do not know. Maybe there was no Evo evolutionary pressure on the development of such mechanisms because brain damage that really leads to cell death in in a large scale was usually not compatible with survival. The great problem in restoring neuron networks that have been damaged is that it is difficult to recapitulate the developmental process.The mature brain is characterized by an extremely sophisticated circuitry that has developed step by step in a complex self-organizing process, guided by the dialogue between the genes and the increasingly more differentiated cellular environment that changes throughout development. And this process is a essentially bottom up process. Peripheral structures mature first, then they go through critical periods and the connectivity becomes fixed so that the, the higher stages can rely upon what has already been built and then they organize themselves as a function of what's already there.And this process goes on in human beings until age 20 and then the circuitry crystallizes and then we have to live with the brains that we have got at that point of time. There's further modification by learning and neuroplasticity, but this is limited. Now if one were to replace neurons at higher levels of processing, for example, by injection of stem cells or so these neurons we know already, they can differentiate, they the precursors can become neurons, but the problem is will they find the partners with which they have to interact?Will the information still be there That was available during development that guided the axon growth, that guided the formation of specific connections. And we know that to, to a large extent, this information is no longer available because the genes that one needs in order to express the necessary marker molecules, they get switched off once development comes to an end. And what is probably necessary is that one not only supplies cells that can differentiate into neurons and of course also ggl cells, but that one also switches on or helps the organism to switch on the genes that have been active during the developmental process that lead to the expression of all the molecular machinery that is required to tell the cells with whom they should connect, where they should connect.And what of course cannot be reinstalled easily is all the idiosyncratic wiring and the adjustment of synaptic game that is due to learning processes. The newly integrated neurons will of course have no souvenir, no recollection of the experience that has been imprinted into the morphology and the structure and the function of neurons that have disappeared. So there are certain limits to the ability to restore.And as we realize in the moment, there are certain places in the brain where this seems to pose less of a problem because nature has foreseen lifelong regeneration of neurons and apparently kept the machinery alive that is needed in order to promote this ongoing regeneration and insertion of neurons as in hippocampus and in the olfactory bulb. But the other structures where this is probably causing great problems, the first replacements that have been attempted and have had certain success even though it was not satisfactory yet, where the modulatory systems where topological specificity is not that much a problem. These systems are functioning more like endocrine or paracrine systems that liberate certain transmitters that are required in order to keep a certain tous of excitability.These systems are more easily replaceable because specificity is less of a problem, but the future will show how far we get there. Certainly very promising approaches in reinstalling oxon outgrowth in several spinal cords by inhibiting factors that inhibit outgrowth in the adult and by activating mechanisms that come to action during development and promote outgrowth. There are encouraging successes in this field, but one should also consider very seriously the option of neuronal prosthetics to record neuronal activity from places where it is still available and then through mechanical devices and computer interfaces activate actors that can translate this activity into action for the motor system.Or conversely, on the sensory side, cochlear implants already work admirably well. There are now attempts to develop retinal implants in order to reinstall rudimentary visual functions in people who have retinal degeneration. There's also a very promising option to insert light gated iron channels into retinal cells so that cells that are normally not light sensitive, which are the ganglion cells for example, or the bipolar cells become light sensitive so that one could in principle reins store some function that is lost when photoreceptors degenerate by simply transferring light sensitivity to second or third order neurons.This is already possible in animal experimentation. It might be another promising avenue to pursue. I think Europe has a very strong tradition in the development of concepts end of 19th century helm those seminal figures who have provided the grounds for later experimental neurobiology to some extent.They also are the grand grandfathers of a substantial number of systems physiologists who have been active in Europe. I think there is a good tradition in systems neuroscience in Europe has always been in the times when, when linear systems theory was still at its peak cybernetics, as it was called Europe, had a few very strong exponents such as rehad for example. Then the, there was something like, not iconic turn, but the molecular turn in Europe as well as anywhere else, molecular biology took over and replaced many of the systems oriented approaches.Partly because initially it had been cheaper than to work with whole animals, partly because non-invasive technology was not available and one couldn't do certain things in animals, which can now be done in human subjects. But I think there's a strong renaissance in systems physiology even though in Europe we have to fight a hard battle against animal protectionists concerning primary research, this is a real critical issue. The labs that can, they still get the license to work with primates become less and less and those who still have the license.This is the case with us where we have, we are exposed very much to public critique, but still systems neuroscience is having a renaissance. And I think there are good reasons for that because we will need it more and more in order to make sense out of the plethora of data that are collected by the properties of neurons and small circuits. And these data can only be integrated if we have concepts derived from systems neuroscience on the nature of the neuronal code, on the cooperation of areas in the brain, on global coordination of processes, on distributed processing.All those questions are heatedly debated in the moment and we just need more experiments along those lines. And I think Europe is not in a bad position to do this. Israel as well, one should not forget the contribution, also conceptual contribution of our colleagues in Israel, which is substantial.

وجهات النظر بشأن العلوم العصبية

Biology

Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning

Shuttle-box avoidance learning is a well-established method in behavioral neuroscience and experimental setups were traditionally custom-made; the necessary equipment is now available by several commercial companies. This protocol provides a detailed description of a two-way shuttle-box avoidance learning paradigm in rodents (here Mongolian gerbils; Meriones unguiculatus) in combination with site-specific electrical intracortical microstimulation (ICMS) and simultaneous chronical electrophysiological in vivo recordings. The detailed protocol is applicable to study multiple aspects of learning behavior and perception in different rodent species.
Site-specific ICMS of auditory cortical circuits as conditioned stimuli here is used as a tool to test the perceptual relevance of specific afferent, efferent and intracortical connections. Distinct activation patterns can be evoked by using different stimulation electrode arrays for local, layer-dependent ICMS or distant ICMS sites. Utilizing behavioral signal detection analysis it can be determined which stimulation strategy is most effective for eliciting a behaviorally detectable and salient signal. Further, parallel multichannel-recordings using different electrode designs (surface electrodes, depth electrodes, etc.) allow for investigating neuronal observables over the time course of such learning processes. It will be discussed how changes of the behavioral design can increase the cognitive complexity (e.g. detection, discrimination, reversal learning).

Shuttle-box avoidance learning is well-established in behavioral neuroscience. This protocol describes how shuttle-box learning in rodents can be combined with site-specific electrical intracortical microstimulation (ICMS) and simultaneous chronical in vivo recordings as a tool to study multiple aspects of learning and perception.

جنبا إلى جنب المكوك بوكس ​​التدريب مع الكهربية اللحاء تسجيل وتحفيز كأداة لدراسة الإدراك والتعلم

Shuttle-box avoidance learning is a well-established method in behavioral neuroscience and experimental setups were traditionally custom-made; the ...

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Statistical learning, a fundamental skill to extract regularities in the environment, is often considered a core supporting mechanism of the first language development. While many studies of statistical learning are conducted within a single domain or modality, recent evidence suggests that this skill may differ based on the context in which the stimuli are presented. In addition, few studies investigate learning as it unfolds in real-time, rather focusing on the outcome of learning. In this protocol, we describe an approach for identifying the cognitive and neural basis of statistical learning, within an individual, across domains (linguistic vs. non-linguistic) and sensory modalities (visual and auditory). The tasks are designed to cast as little cognitive demand as possible on participants, making it ideal for young school-aged children and special populations. The web-based nature of the behavioral tasks offers a unique opportunity for us to reach more representative populations nationwide, to estimate effect sizes with greater precision, and to contribute to open and reproducible research. The neural measures provided by the functional magnetic resonance imaging (fMRI) task can inform researchers about the neural mechanisms engaged during statistical learning, and how these may differ across individuals on the basis of domain or modality. Finally, both tasks allow for the measurement of real-time learning, as changes in reaction time to a target stimulus is tracked across the exposure period. The main limitation of using this protocol relates to the hour-long duration of the experiment. Children might need to complete all four statistical learning tasks in multiple sittings. Therefore, the web-based platform is designed with this limitation in mind so that tasks may be disseminated individually. This methodology will allow users to investigate how the process of statistical learning unfolds across and within domains and modalities in children from different developmental backgrounds.

Presented here is a protocol introducing a set of child-friendly statistical learning tasks geared towards examining children&#8217;s learning of temporal statistical patterns across domains and sensory modalities. The developed tasks collect behavioral data using the web-based platform and task-based functional magnetic resonance imaging (fMRI) data for examining neural engagement during statistical learning.

قياس التعلم الإحصائي عبر الطرائق والمجالات في الأطفال في سن المدرسة عبر منصة عبر الإنترنت وتقنيات التصوير العصبي

Statistical learning, a fundamental skill to extract regularities in the environment, is often considered a core supporting mechanism of the first ...

Neuroscience

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

fNIRS hyperscanning is widely used to detect the neurobiological underpinnings of social interaction. With this technique, researchers qualify the concurrent brain activity of two or more interactive individuals with a novel index called inter-brain synchrony (IBS) (i.e., phase and/or amplitude alignment of the neuronal or hemodynamic signals across time). A protocol for conducting fNIRS hyperscanning experiments on collaborative learning dyads in a naturalistic learning environment is presented here. Further, a pipeline of analyzing IBS of oxygenated hemoglobin (Oxy-Hb) signal is explained. Specifically, the experimental design, the process of NIRS data recording, data analysis methods, and future directions are all discussed. Overall, implementing a standardized fNIRS hyperscanning pipeline is a fundamental part of second-person neuroscience. Also, this is in line with the call for open-science to aid the reproducibility of research.

The protocol for conducting fNIRS hyperscanning experiments on collaborative learning dyads in a naturalistic learning environment is outlined. Further, a pipeline to analyze the Inter-Brain Synchrony (IBS) of oxygenated hemoglobin (Oxy-Hb) signals is presented.

بين الدماغ Synchrony في التعلم التعاوني المفتوح : دراسة fNIRS - Hyperscanning

fNIRS hyperscanning is widely used to detect the neurobiological underpinnings of social interaction. With this technique, researchers qualify the ...

Assessing Corticospinal Excitability During Goal-Directed Reaching Behavior

Reaching is a widely studied behavior in motor physiology and neuroscience research. While reaching has been examined using a variety of behavioral manipulations, there remain significant gaps in the understanding of the neural processes involved in reach planning, execution, and control. The novel approach described here combines a two-dimensional reaching task with transcranial magnetic stimulation (TMS) and concurrent electromyography (EMG) recording from multiple muscles. This method allows for the noninvasive detection of corticospinal activity at precise time points during the unfolding of reaching movements. The example task code includes a delayed response reaching task with two possible targets displayed &#177; 45&#176; off the midline. Single pulse TMS is delivered on the majority of task trials, either at the onset of the preparatory cue (baseline) or 100 ms prior to the imperative cue (delay). This sample design is suitable for investigating changes in corticospinal excitability during reach preparation. The sample code also includes a visuomotor perturbation (i.e., cursor rotation of &#177; 20&#176;) to investigate the effects of adaptation on corticospinal excitability during reach preparation. The task parameters and TMS delivery can be adjusted to address specific hypotheses about the state of the motor system during reaching behavior. In the initial implementation, motor evoked potentials (MEPs) were successfully elicited on 83% of TMS trials, and reach trajectories were recorded on all trials.

Reaching is a fundamental skill that allows humans to interact with the environment. Several studies have aimed to characterize reaching behavior using a variety of methodologies. This paper offers an open-source application of transcranial magnetic stimulation to assess the state of corticospinal excitability in humans during reaching task performance.

تقييم استثارة القشرية الشوكية أثناء سلوك الوصول الموجه نحو الهدف

Reaching is a widely studied behavior in motor physiology and neuroscience research. While reaching has been examined using a variety of behavioral ...

An Introduction to Neurophysiology

Neurophysiology is broadly defined as the study of nervous system function. In this field, scientists investigate the central and peripheral nervous systems at the level of whole organs, cellular networks, single cells, or even subcellular compartments. A unifying feature of this wide-ranging discipline is an interest in the mechanisms that lead to the generation and propagation of electrical impulses within and between neurons. This subject is important not only for our understanding of the fascinating processes driving human thought, but also for our ability to diagnose and treat disorders related to nervous system malfunction. This video will provide an introduction to the field of neurophysiology, beginning with a brief history of neurophysiological research that showcases landmark studies like Galvani&#8217;s observations of twitching frog legs and Eccles&#8217;s discovery of the chemical synapse. Next, key questions asked by neurophysiologists are introduced, followed by an overview of some prominent experimental tools used to answer those questions. The methods presented range from techniques used to investigate single cells, like patch clamping, to those that can measure activity across large regions of the brain, like electroencephalography (EEG). Finally, applications of neurophysiological research are discussed, including the development of brain-machine interfaces that allow for device control using thought.

Introduction to Neurophysiology: Methods &amp; Applications

 Neurophysiology is broadly defined as the study of nervous system function. In this field, scientists investigate the central and peripheral nervous ...

Education

JoVE Science Education

Advanced Biology

An Introduction to Learning and Memory

Learning is the process of acquiring new information and memory is the retention or storage of that information. Different types of learning, such as non-associative and associative learning, and different types of memory, such as long-term and short-term memory, have been associated with human behaviors. Studying these components in detail helps behavioral scientists understand the neural mechanisms behind these two complex phenomena.
JoVE's overview on learning and memory introduces common terminologies and a brief outline of concepts in this field. Then, key questions asked by behavioral scientists and prominent tools such as fear conditioning and fMRI are discussed. Finally, actual experiments dealing with aging, eradication of traumatic memories, and improvising learning are reviewed.

Learning and Memory: Types; Behavioral Tests &amp; Techniques

Learning is the process of acquiring new information and memory is the retention or storage of that information. Different types of learning, such as ...

Psychology

Behavioral Science

Perspectives on Neuropsychology

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212; University of Southern California
Neuropsychology is a complex field, as it investigates how mental processes are executed in the brain&#8212;events that integrate concepts from biochemistry, biology, psychology, and neuroscience. Although the multidisciplinary nature of neuropsychology prepares young learners for a variety of careers, it also poses a challenge in that it forces students to study concepts outside of their comfort zone. For example, a psychology major may have difficulty grasping neuroanatomy&#8212;a challenging topic in itself&#8212;given that the brain is a complicated, three-dimensional organ that is typically represented two-dimensionally in textbooks.
This JoVE collection in Neuropsychology introduces major concepts and methods in the field, and showcases how advances in imaging technology have allowed us to look inside the brain and visualize its structure and function. Importantly, these videos are also meant to reassure students that you don&#8217;t need to be an expert in all aspects of neuropsychology to understand how the brain shapes our experiences, behaviors, and social interactions in everyday life. For instance, the video "Decision-making and the Iowa Gambling Task" explores how damage to a specific region of the brain can affect an individual&#8217;s proclivity for risky decisions, like stealing.
These JoVE videos in Neuropsychology provide the perfect introduction to this complex topic, and also explore some of the potential, exciting future directions in this field. With further advances in technology, one day researchers might even be able to visualize dynamic changes in a person&#8217;s brain outside of a laboratory setting&#8212;for example, when they are sitting in a classroom listening to a lecture on neuropsychology.

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212; University of Southern California
Neuropsychology is a complex field, as it ...

Neuropsychology

Perspectives on Cognitive Psychology

Source: Laboratory of Jonathan Flombaum&#8212;Johns Hopkins University

As an Assistant Professor of Psychology and Cognitive Science at Johns Hopkins University, I teach Introduction to Cognitive Psychology. This large class primarily consists of freshman and sophomores majoring in related fields, like Psychology, Neuroscience, or Cognitive Science. One of the challenges I face in the classroom is teaching students to appreciate how data are obtained in the process of performing experiments. Students have difficulty in appreciating the chronology of experiments as they unfold in time.
This JoVE collection in Cognitive Psychology makes the experimental timeline absolutely clear and encourages students to understand the trajectory and not just jump to conclusions. The videos also present experiments as paradigms&#8212;to illustrate how researchers can implement tasks in different ways&#8212;depending on the questions at hand. Most of these questions translate to the real world and the limits of our cognition. For example, the video Measuring Verbal Working Memory Span demonstrates our limited memory capacity, which explains the difficulty in remembering long shopping lists.
These JoVE videos in Cognitive Psychology provide a perfect place for instructors to start if they are interested in demonstrating tasks in class. Better yet, the videos can be used to get students involved&#8212;to execute the procedures and to even be the participants. Thus, the collection perfectly introduces lab components to a Psychology class.

Source: Laboratory of Jonathan Flombaum&#8212;Johns Hopkins University

As an Assistant Professor of Psychology and Cognitive Science at Johns Hopkins ...

تقييم أبعاد متعددة الاشتباك لوصف التعلم: A العصبية وجهة نظر

Summary

Explore More Videos

Chapters in this video

الدراسة موتور مهارة التعلم عن طريق واحدة بيليه المهام الوصول في الفئران

وجهات النظر بشأن العلوم العصبية

جنبا إلى جنب المكوك بوكس التدريب مع الكهربية اللحاء تسجيل وتحفيز كأداة لدراسة الإدراك والتعلم

قياس التعلم الإحصائي عبر الطرائق والمجالات في الأطفال في سن المدرسة عبر منصة عبر الإنترنت وتقنيات التصوير العصبي

بين الدماغ Synchrony في التعلم التعاوني المفتوح : دراسة fNIRS - Hyperscanning

تقييم استثارة القشرية الشوكية أثناء سلوك الوصول الموجه نحو الهدف

An Introduction to Neurophysiology

An Introduction to Learning and Memory

Perspectives on Neuropsychology

Perspectives on Cognitive Psychology

تقييم أبعاد متعددة الاشتباك لوصف التعلم: A العصبية وجهة نظر

Summary

Explore More Videos

Chapters in this video

الدراسة موتور مهارة التعلم عن طريق واحدة بيليه المهام الوصول في الفئران

وجهات النظر بشأن العلوم العصبية

جنبا إلى جنب المكوك بوكس ​​التدريب مع الكهربية اللحاء تسجيل وتحفيز كأداة لدراسة الإدراك والتعلم

قياس التعلم الإحصائي عبر الطرائق والمجالات في الأطفال في سن المدرسة عبر منصة عبر الإنترنت وتقنيات التصوير العصبي

بين الدماغ Synchrony في التعلم التعاوني المفتوح : دراسة fNIRS - Hyperscanning

تقييم استثارة القشرية الشوكية أثناء سلوك الوصول الموجه نحو الهدف

An Introduction to Neurophysiology

An Introduction to Learning and Memory

Perspectives on Neuropsychology

Perspectives on Cognitive Psychology

جنبا إلى جنب المكوك بوكس التدريب مع الكهربية اللحاء تسجيل وتحفيز كأداة لدراسة الإدراك والتعلم