The authors would like to thank Dr. Harvey Hung for his advice&#160;on the manuscript.

This research project was approved by the Joint Chinese University of Hong Kong-New Territories East Cluster Clinical Research Ethics Committee (CREC Ref. No.: 2015.263).
1. Participants Recruitment and Baseline Assessment
<ol>
	<li>Recruit Parkinson&#39;s disease patients aged less than or equal to 70 from a neurology specialist clinic with the diagnosis made based on the United Kingdom Parkinson&#39;s Disease Society (UKPDS) Brain Bank Diagnostic Criteria12.
	<ol>
		<li>Exclude subjects with psychiatric illnesses, ophthalmological diseases that would impair eye movement, or other neurological disorders. Also, exclude cases using anticholinergics as they are known to affect cognitive performance and eye movement.</li>
	</ol>
	</li>
	<li>Recruit healthy controls on a 1:1 basis matched by sex, age, and education.</li>
	<li>Obtain informed consent from the subject.</li>
	<li>Conduct a clinical diagnostic interview with the subject and, if available, their relatives, to exclude dementia and screen for cognitive impairment with Mini-Mental State Examination (MMSE)13 and Montreal Cognitive Assessment (MoCA)14. Exclude dementia cases from the study or if the subject&#8217;s scores of either MMSE or MoCA is &#60;22/30.</li>
	<li>Assess the visual acuity with a Snellen chart. Exclude the subject if the visual acuity is less than 20/40.</li>
	<li>Assess motor severity and staging of Parkinson&#39;s disease using the Unified Parkinson&#39;s Disease Rating Scale (UPDRS) Part II &#38; III15 and Modified Hoehn and Yahr (H&#38;Y) Staging16, respectively. Also, obtain information about the current medications taken by the subject.</li>
	<li>Assess the depressive mood state by the Beck Depression Inventory-II (BDI-II)17.</li>
</ol>
2. Experimental Setup
<ol>
	<li>Conduct the experiment in a quiet room with an adequate light source.</li>
	<li>Conduct the experiment for Parkinson&#39;s disease subjects when they are on medication with optimal motor function.</li>
	<li>Prepare the setup that consists of a screen-based eye tracker, a computer, a mouse, a standard keyboard, a chin rest, and cognitive assessment tools (Table of Materials).</li>
	<li>Use an eye tracker with a sampling rate of at least 300 Hz.</li>
	<li>Place the chin rest 60 cm in front of the eye tracker screen.</li>
</ol>
3. The Flow of the Cognitive Assessment and the Visual Search Task
<ol>
	<li>Carry out the Chinese Categorical Verbal Fluency Test18. Instruct the subject to name as many animals as possible in a minute. Record the number of answers and perseverative error. Then repeat the same in the category of fruits and vegetables.</li>
	<li>Conduct the registration part (Trial 1, 2 and 3) of the Hong Kong List Learning Test (HKLLT)19 by reading out a pre-defined 16-vocabulary word list and instruct the subject to remember them. Afterwards ask the subject to do free recall of the word list and record the answer (Trial 1).
	<ol>
		<li>Repeat step 3.2 twice for Trial 2 and Trial 3.</li>
	</ol>
	</li>
	<li>Wait 10 min and 30 min after the registration part of the HKLLT for the 10&#160;and 30 min delay recall.</li>
	<li>Before the 10 min delayed recall of the HKLLT, perform the Pattern Recognition Memory (PRM) from Cambridge Neuropsychological Test Automated Battery (CANTAB)20 (Table of Material).
	<ol>
		<li>Using the tablet computer, present 24 visual patterns, one at a time, at the center of the screen. Instruct the subject to remember the pattern.</li>
		<li>After the presentation, in a 2-choice force discrimination paradigm, instruct the subject to choose the pattern that he/she can recognize.</li>
	</ol>
	</li>
	<li>Perform the 10 min delay recall of HKLLT by asking the subject to do free recall of the 16-vocabulary word list.</li>
	<li>Before the 30 min delayed recall of the HKLLT, perform Spatial Span (SSP) from CANTAB20.
	<ol>
		<li>Use the tablet computer to show a pattern of white boxes which change in color, one by one, in variable sequences.</li>
		<li>Afterwards instruct the subject to touch the boxes in the same sequence they were presented and record the spatial span length that the subject could attain as the difficulty (number of boxes change in color) of the task increases.</li>
	</ol>
	</li>
	<li>Carry out the 30 min delay recall by asking the subject to do free recall of the 16-vocabulary word list.
	<ol>
		<li>Conduct the recognition and discrimination part of the HKLLT by reading out another pre-defined 32-vocabulary word list, of which half of the vocabularies are from the original word list in 3.2. Instruct the subject to determine whether each vocabulary read out is from the original word list or not.</li>
	</ol>
	</li>
	<li>Allow the subject to rest quietly if they finish the tasks in 3.4 and 3.6 before the 10- and 30-min delay recall, respectively.</li>
	<li>Perform the Stocking of Cambridge (SOC) from CANTAB20.
	<ol>
		<li>Using the tablet computer, present 20 scenarios of two parallel displays of 3 balls held in 3 vertical stockings, of which the arrangement of the balls in the displays varies in each scenario.</li>
		<li>Instruct the subject to determine, in each scenario, the least number of moves required to rearrange the balls in the lower display in order to copy the pattern shown in the upper display. Record the mean number of choices to correct answer.</li>
	</ol>
	</li>
	<li>Perform the Stroop Test21.
	<ol>
		<li>Give the subject 3 cards consecutively; the first card contains dots printed in different colors, the second card contains Chinese characters printed in different colors while the last card has Chinese characters denoting different colors (e.g., Chinese words of &#34;blue&#34;, &#34;yellow&#34;, &#34;green&#34;, or &#34;red&#34;) but printed in a color not denoted by the name (e.g., the word &#34;red&#34; printed in blue ink).</li>
		<li>Ask the subject to read out the printed color of the dots/Chinese characters as quickly as possible and record the time required for each card (T1, T2, and T3).</li>
		<li>Calculate the interference index with the formula (T3-T1)/T1.</li>
	</ol>
	</li>
	<li>Proceed to the visual search task after completing the cognitive tests. 
	NOTE: Do not carry out any verbal cognitive task after the registration part of HKLLT until the end of the whole HKLLT (3.7) to prevent interference effect on verbal memory performance.</li>
</ol>
4. Visual Search Task
<ol>
	<li>Position the subject on a chair and place their chin on the chin rest with their forehead against a bar to minimize head movement. Align the subject&#39;s eyes to approximately the center of the computer screen. Begin by clicking the Start Recording button in the computer program.</li>
	<li>Calibration
	<ol>
		<li>Calibrate the eye tracker with the in-built calibration program by clicking the Start button in the calibration interface.</li>
		<li>Ask the subject to gaze at a red dot moving across the screen with 9 fixation points, while keeping the head still.</li>
		<li>Check for the quality of the calibration by viewing the calibration plot (Figure 1). Make sure that the length of the green lines, which represent the error vectors, fall within the grey circles for an acceptable quality of the calibration. Redo the calibration if there is any missing point or the green lines fall outside the grey circles. Click Accept to proceed to the visual search task.</li>
	</ol>
	</li>
	<li>Instruction
	<ol>
		<li>Provide verbal instruction to the subject and start with 5 practice runs to familiarize the subject with the task.</li>
		<li>Instruct the subject to fixate their gaze on the central fixation cross at the beginning of each trial. Then, press Enter on the keyboard to begin a trial, at which the computer screen will display a single number and 79 distracter alphabets scattered randomly (Figure 2).</li>
		<li>Instruct the subject to look as quickly as possible for the number and then simultaneously click on the mouse and state the number aloud as soon as the number is located.</li>
		<li>Cross check if the number stated is correct or not.</li>
		<li>Administer a total of 40 trials after the 5 practice runs.</li>
	</ol>
	</li>
	<li>Design of the trial images in the visual search task 
	NOTE: The program code, written in PHP, for this section can be found in Supplement File 1.
	<ol>
		<li>Use the numbers 4, 6, 7 and 9 exclusively (Supplementary File 1 - Line 5). 
		NOTE:&#160;The pilot study11 showed that these numbers are most easily discriminated from the alphabets.</li>
		<li>Ensure that the location of the target number is randomized from trial to trial with the rule that it could not be in the same visual quadrant for more than three successive trials (Supplementary File 1 - Line 48-52).</li>
		<li>Do not use ambiguous alphabets such as &#34;I&#34;&#160;and &#34;O&#34;&#160;(Supplementary File 1 - Line 76-78).</li>
		<li>Set the size of the fixation cross, alphabets, and numbers at 0.85&#176; visual angle (equivalent to around 0.9 cm on a 23 inches computer screen). 
		NOTE: Numbers and alphabets are used because these are easily recognizable visual stimuli yet require foveation for identification.</li>
		<li>Allow a time lapse of 1.5 s after the investigator has pressed Enter in 4.3.2 and before the display of the central fixation cross is switched to a trial image to begin a trial (Supplementary File 2 - Line 71; 156-158).</li>
		<li>Ensure that the screen will go blank with the fixation cross reappearing as the mouse is clicked or after 10 s have elapsed since the beginning of a trial, whichever that is earlier (Supplementary File 2 - Line 72; 162-180).</li>
		<li>As the task is finished, generate a .csv file that contains the timestamps of the beginning and the end of each trial (Supplementary File 2 &#8211; line 48-59; 199-208). Use this file in the data analysis in section 5.</li>
	</ol>
	</li>
</ol>
5. Eye Tracking Data Processing and Analysis
<ol>
	<li>In the Replay section of the computer program, check the Samples Percentage of the eyes during the visual search task (Figure 3). Discard the subject&#8217;s data if more than 20% missing data are observed. 
	NOTE: Samples Percentage denotes the percentage of time the eyes are successfully located by the eye tracker during the visual search task.</li>
	<li>Click on the Play button for the recording to check the quality of the data by eyeballing the visualized scan path video generated (Figure 4). Discard the whole subject&#39;s data if it is grossly erroneous (Figure 5).</li>
	<li>Discard any trial(s) in which the subject pressed the mouse accidentally and prematurely.</li>
	<li>In the Data Export section of the program, select GazePointX (ADCSpx) and GazePointY (ADCSpx) and the subject of interest (Figure 6). Click Export Data to export each subject&#8217;s data and save as a .csv file. The file contains the x and y coordinates of the subject&#39;s eyes position on the computer screen, in pixels, at every time point.</li>
	<li>Use the Visual Search Analyzer and in the interface (Figure 7), select the data exported in 5.4 as the input of Eye Data and the .csv file generated in 4.4.7 as the input of Action data. Select ST DBScan as the classification algorithm and click on Run. Then, click on Summary to generate a spreadsheet file containing the mean saccade amplitude and the mean fixation duration of the subject.</li>
	<li>Design of the visual search analyzer 
	NOTE: The coding for the design of the analyzer could be found at https://github.com/lab-viso-limited/visual-search-analyzer. Its program code can be found in Supplementary File 3.
	<ol>
		<li>Program the analyzer such that it extracts and analyzes only the data from the beginning to the end of the trial (i.e., from the display of the number and alphabets until the mouse is clicked or 10 s have elapsed), using the .csv file generated in 4.4.7 (Supplementary File 3 - Line 6-173).</li>
		<li>Program the analyzer such that it fills in the data loss due to eye-blinking by averaging the x and y coordinates of the gaze point immediately before and after the blinking (Supplementary File 3 - Line 176-260).</li>
		<li>Program the analyzer such that it classifies the raw data into either saccade or fixation by using the algorithm developed based on ST-DBSCAN22 (Program code in Supplementary File 4).&#160;</li>
	</ol>
	</li>
</ol>

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Q., Kabir, A., Dogu, O., Patel, A., Khondker, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prevalence+of+blepharospasm+and+apraxia+of+eyelid+opening+in+patients+with+parkinsonism,+cervical+dystonia+and+essential+tremor.">Prevalence of blepharospasm and apraxia of eyelid opening in patients with parkinsonism, cervical dystonia and essential tremor.</a> European Neurology. 68 (5), 318-321 (2012).</li></ol>

The authors have nothing to disclose.

The protocol presented above was designed as the first part of a longitudinal study in exploring the potential clinical utility of eye movement parameters as surrogate markers for cognitive functions in Parkinson&#39;s disease. While there are studies that examine more classical eye tracking paradigms such as self-paced saccade, reflexive saccade, and anti-saccade25,26,27, a visual search task was used in this study to measure eye movement parameters. As discussed, the design of this visual search task is of paramount importance as it must minimize the known confounding effect of a cognitive ability on the performance of the eye tracking task, as it may affect the eye movement parameters recorded. An example of which would be the effect of frontal executive functions on the saccadic latency28. The critical issue in the design would be the random scattering of the number and alphabets and varying quadrants of the number&#39;s location, making it more difficult to use cognitive strategies to enhance the performance of the task. Together with an average of roughly 650 saccades measured in 40 trials per subject, the average saccade amplitude calculated represents more of a physiological ability of the eye to generate saccade. In accordance with previous literature, it was found that the saccade amplitude is smaller in Parkinson&#39;s disease patients29,30. The choice of parameters extracted from the eye tracking task also needs to be taken care of with respect to the issue of the potential confounding effect by cognition. For example, parameters such as the speed of finding the number, error rate, and accuracy, which are a direct measurement of attention and processing speed, were not used.
Another critical step for this study is to ascertain the validity of the algorithm that was used in the classification of eye movement parameter. There exist numerous ways of classifying eye tracking data into saccade and fixation: velocity-based, dispersion-based algorithm and so on31. Each of these algorithms has its own pros and cons and there is no gold standard for doing so such that one has to also take into consideration the specifications of the eye tracker used and the design of eye tracking task to determine the best way of classifying the data. For this study, an in-house, density-based clustering algorithm, developed based on ST-DBSCAN22, was used. The research team has cross-validated the validity of this classification algorithm against manual classification in a pilot study before applying the algorithm to the data of this study. The computer program incorporating the algorithm would automatically splice out and classify the data within the trials, from the moment the trial starts (with the alphabets and number appearing on the screen) to the end (that the subject clicks on the mouse or 10 s has lapsed) so that no non-trial data recorded (e.g., during the display of the fixation cross) will be analyzed to contaminate the results.
The use of domain-specific cognitive tests in this study allow correlations of the eye movement parameters with individual cognitive function performance. As discussed, this has significance over using general overall cognitive measures as the neural circuitry and biochemical basis for each cognitive function are different. The contemporary knowledge on the neural mechanisms of eye movement control and individual cognitive functions allow us to make inference and interpretation of the results found. For example, the significant negative correlations of fixation duration with temporal-, parietal-, and cholinergic-based cognitive functions are of particular interest as impairment of these functions may predict the development of dementia3. Detailed discussions of the scientific basis that explain the correlations can be found in the original paper published23.
The battery of cognitive examination and the visual search task were highly tolerable to the subjects of this study. Requiring roughly 1.5 h to complete the entire battery, none of the subjects were unable to finish because of fatigue or physical discomfort. The visual search task consisted of 40 trials and took only around 5-10 min to complete. The noninvasive, simple and quick nature of the task makes it suitable as a screening tool if supported by more robust data. This paradigm could also be applied transdiagnostically in other neurocognitive disorders to answer similar research questions. One major practical limitation encountered in this protocol is the incompatibility of the eye tracker in subjects wearing certain progressive lens, as presbyopia is not an uncommon condition in the elderly. Eyelid apraxia and blepharospasm are also seen in Parkinson&#39;s disease32 and sufferers of these conditions may not be able to complete the task.
As an explorative and cross-sectional study, the design of the study does not allow us to infer any definite neuroanatomical and biochemical basis that explains the results found. The interpretations of the results were mostly based on independent knowledge on the physiologies of cognitive functions and eye movement control and, therefore, remained as postulations. The longitudinal data on how these parameters may change over time during the neurodegenerative process is unknown. Yet, it is worthwhile to have a follow-up study to investigate the predictive values of the baseline eye movement parameters on cognitive impairment development. Future studies should incorporate neuroimaging to address the neurostructural underpinnings for more solid support of any postulation, without which further development of eye tracking as a proxy marker of cognitive function will not be possible.

Parkinson&#8217;s disease is classically a motor disorder; yet, the disease is also associated with cognitive deficits, and progression into dementia is common1. The pathophysiology of cognitive impairment in Parkinson&#39;s disease is not well understood. It is thought to be related to alpha-synuclein deposition in the cortical area based on Braak&#39;s staging2. It was also proposed that a dual syndrome of degeneration of the dopaminergic and the cholinergic system leads to different cognitive deficits with prognostic implication3. More research is needed to further elucidate the exact mechanisms involved in cognitive impairment in Parkinson&#39;s disease. On the clinical aspect, the presence of cognitive impairment has a significant impact on prognosis4,5. Assessment of cognitive function in clinical practice is, therefore, essential. However, a lengthy cognitive assessment is limited by patients&#8217; mental and motor conditions. Therefore, a noninvasive and simple measurement that can reflect the disease&#39;s burden on cognitive function is needed.
The eye movement abnormalities are widely described detectable signs of Parkinson&#39;s disease from its early stages6, yet the pathophysiology is even less well-characterized than that of cognitive impairment. The generation of eye movement is through a transformation of the visual sensory input, subserved by an intertwined cortical and subcortical network, into signals to the oculomotor nuclei in the brainstem for effect7. Involvement of Parkinson&#39;s disease pathologies in these networks may lead to observable eye movement abnormalities. There is, perhaps overlapping of neuroanatomical structures that govern the control of eye movement and cognitive function. Furthermore, there have been studies examining the relationship between saccadic eye movement and cognitive function in other neurodegenerative disorders8. On such grounds, it is worthwhile to explore the use of eye movement parameters as a proxy marker of cognitive functions in Parkinson&#39;s disease. One cross-sectional study9 showed that reduced saccadic amplitude and longer fixation duration was associated with the severity of global cognitive impairment in Parkinson&#39;s disease. However, there is a lack of data on the correlation between eye movement parameters and specific cognitive domains. The significance and need of measurement of specific cognitive domains, rather than a general cognitive state, is that individual cognitive domain informs differential prognostic information in Parkinson&#39;s disease3 and they are subserved by different neural networks. The aim of this study is to explore the specific relationship between eye movement metrics and different cognitive functions. This is the first step to establish a foundation on which the development of biomarkers of cognitive decline in Parkinson&#39;s disease using eye tracking technology could be built.
The experimental paradigm presented is composed of 2 major parts: the cognitive assessment and the eye tracking task. The cognitive assessment battery encompassed a range of cognitive functions, including attention and working memory, executive function, language, verbal memory and visuospatial function. The choice of these 5 cognitive domains is based on the Movement Disorder Society Task Force Guidelines for the mild cognitive impairment in Parkinson&#39;s disease10, and a set of locally available cognitive tests were selected to build the assessment battery. In a previous similar eye tracking study on Parkinson&#39;s disease cognition mentioned9, the author extracted the eye movement parameters while the subjects were engaged in visual cognitive tasks, where the parameters may potentially be influenced by the subject&#39;s cognitive ability. As this study aimed to assess the correlation between the eye movement parameters and different cognitive domains, the potential confounding effect of cognitive abilities on the eye parameters must be addressed. In this regards, a visual search task, adapted from another eye tracking study on Alzheimer&#8217;s disease11, was employed to capture the eye movement parameters of the subjects. During the task, subjects had to search for a single number on a computer screen among multiple alphabet distracters. This task would elicit the alternate use of saccadic eye movement and visual fixation, the abnormalities of which are described widely in Parkinson&#39;s disease. The identification and differentiation of number and alphabet is an overlearned task where the demand for cognitive functions is only minimal and would, therefore, be suitable to answer the research question of this study. A computer program was developed based on the specifications and design as stated by R&#246;sler et al.11. in their original study to be run within the in-built software of our eye tracker. An in-house algorithm for classification and analysis of the eye tracking data was also developed for this study.

<table border="0" cellpadding="0" cellspacing="0" style="width:1008px;" width="1007">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Computer&#160;</td>
			<td style="width:121px;">Intel</td>
			<td style="width:505px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:215px;">Computerized cognitive assessment tool</td>
			<td style="width:121px;">CANTAB</td>
			<td style="width:505px;">CANTAB Research Suite</td>
			<td>Contains Pattern Recognition Memory, Spatial Span, and Stockings of Cambridge</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Eye Movement Analyzer</td>
			<td style="width:121px;">Lab Viso Limited</td>
			<td style="width:505px;"></td>
			<td>https://github.com/lab-viso-limited/visual-search-analyzer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Eye tracker</td>
			<td style="width:121px;">Tobii</td>
			<td style="width:505px;">Tx300</td>
			<td>23 inch computer screen with resolution of 1920x1080, Sampling rate at 300Hz</td>
		</tr>
		<tr height="105">
			<td height="105" style="height:105px;width:215px;">Hong Kong List Leanrning Test</td>
			<td style="width:121px;">Department of Psychology, The Chinese University of Hong Kong</td>
			<td style="width:505px;">The Hong Kong List Learning Test (HKLLT) 2nd Edition</td>
			<td></td>
		</tr>
		<tr height="84">
			<td height="84" style="height:84px;width:215px;">Stroop test</td>
			<td style="width:121px;">Laboratory of Neuropsychology, The University of Hong Kong</td>
			<td style="width:505px;">Neuropsychological Measures: Normative Data for Chinese, Second Edition (Revised)</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Tobii Studio</td>
			<td style="width:121px;">Tobii</td>
			<td style="width:505px;">Tobii Studio version 3.2.2</td>
			<td>Computer programme for running the visual search task</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Visual Search Task</td>
			<td style="width:121px;">Lab Viso Limited</td>
			<td style="width:505px;"></td>
			<td>https://www.labviso.com/#products</td>
		</tr>
	</tbody>
</table>

characterizing the relationship between eye movement parameters and cognitive functions in non-demented parkinson's disease patients with eye tracking

Cognitive impairment is a common phenomenon in Parkinson&#8217;s disease that has implications on the prognosis. A simple, noninvasive and objective proxy measurement of cognitive function in Parkinson&#8217;s disease will be helpful in detecting early cognitive decline. As a physiological metric, eye movement parameter is not confounded by the subject&#39;s attributes and intelligence and can function as a proxy marker if it correlates with cognitive functions. To this end, this study explored the relationship between the eye movement parameters and performance in cognitive tests in multiple domains. In the experiment, a visual search task with eye tracking was set up, where subjects were asked to look for a number embedded in an array of alphabets scattered randomly on a computer screen. The differentiation between the number and the alphabet is an overlearned task such that the confounding effect of cognitive ability on the eye movement parameters is minimized. The average saccadic amplitude and fixation duration were captured and calculated during the visual search task. The cognitive assessment battery covered domains of frontal-executive functions, attention, verbal and visual memory. It was found that prolonged fixation duration was associated with poorer performance in verbal fluency, visual and verbal memory, allowing further exploration on the use of eye movement parameters as proxy markers for cognitive function in Parkinson&#8217;s disease patients. The experimental paradigm has been found to be highly tolerable in our group of Parkinson&#39;s disease patients and could be applied transdiagnostically to other disease entities for similar research questions.

The full result of this study is available in the original paper published23. Parkinson&#8217;s disease subjects (n = 67) were recruited and completed the assessment. However, 5 cases failed to complete the visual search task as they wore progressive lens incompatible with the eye tracker and their data was discarded. The mean age of the subjects was 58.9 years (SD = 7.5 years) with a male to female ratio of 1.7:1. 62 healthy age-, sex-, and education-matched controls were recruited for comparison.
Cognitive and eye movement parameters 
Consistent with other previous studies24, the Parkinson&#8217;s disease group showed poorer performance in multiple cognitive tasks as compared to the control group (Table 1). Using the in-house algorithm for classification of the visual search task data, fixations and saccades are identified and extracted for calculation and analysis. It was found that the disease group had a smaller mean saccadic amplitude (16.36&#176; &#177; 2.36) as compared to controls (17.27&#176; &#177; 2.49; p = 0.037). The mean fixation duration was not significantly different between the groups (216.58 ms &#177; 31.64 vs, 211.59 ms &#177; 24.90; p = 0.331) (Table 2).
Correlation between eye movement parameters and cognitive function 
After adjusting for covariates, there were negative correlations found between the mean fixation duration and the performance in verbal recognition memory score (Recognition and Discrimination scores; F = 5.843, t = -2.417, p = 0.017 and F = 12.771, t = -3.574, p&#160; = 0.001, respectively), pattern recognition memory (F = 5.505, t = -2.346, p = 0.021) and categorical verbal fluency test in the categories of fruit (F = 5.647, t = -2.376, p = 0.009) and vegetable (F = 9.744, t = -3.122, p = 0.002). (Table 3). However, there was no significant interaction found in these correlations between the disease and control group, suggesting that the correlations are not specific to the disease group. It is speculated that as the control of visual fixation and the correlated cognitive functions commonly involve temporal and parietal regions of the brain with a predominantly cholinergic basis, pathological changes to these neuroanatomical and biochemical mechanisms may explain the findings.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/60052/60052fig1.jpg" /> 
Figure 1: A calibration plot of the eye tracker. The plot shows the result of the calibration. The length of each green line indicates the difference between the gaze point calculated by the eye tracker and the actual dot position. As all the green lines fall within the grey circles and there is no missing point, the quality of this calibration is acceptable. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/60052fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/60052/60052fig2.jpg" /> 
Figure 2: An example of a trial of the visual search task. Display of a non-linear array of 80 stimulus items, of which there is 1 number among 79 distracter alphabets. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/60052fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/60052/60052fig3.jpg" /> 
Figure 3: The interface to check the overall sampling percentage. In the Replay section of the computer program, the Samples Percentage, which denotes the percentage of time that the eyes are successfully located by the eye tracker during the visual search task, could be checked for each subject. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/60052fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/60052/60052fig4.jpg" /> 
Figure 4: An example of a visualized scan path from the visual search task. The scan path during this trial was visualized, with the red straight lines representing the saccadic eye movement and the red dots for visual fixations. Note that the end of each visual fixation is followed by a saccade and vice versa in a normal scan path. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/60052fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/60052/60052fig5.jpg" /> 
Figure 5: An example of a grossly erroneous visualized scan path. This example of a grossly erroneous scan path is taken from a subject wearing a pair of incompatible progressive lens. In contrast to the normal scan path in Figure 4, the red lines (saccade) run in zigzag and fall out of the computer screen. The fixation points are not on either the alphabets or the number. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/60052fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/60052/60052fig6.jpg" /> 
Figure 6: The data export interface in the computer program. This shows the interface where the subject and the kind of the eye tracking data captured can be selected for data export. In our experimental paradigm, the x and y coordinate, in pixels, of the eyes position on the screen at every time point will be used for data analysis. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/60052fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/60052/60052fig7.jpg" /> 
Figure 7: The interface of the Visual Search Analyzer. This shows the interface of the in-house analysis program for eye tracking data. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/60052fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td></td>
			<td>Control group</td>
			<td>Parkinson&#39;s group</td>
			<td>p-value</td>
		</tr>
		<tr>
			<td colspan="4">Global Cognitive scales</td>
		</tr>
		<tr>
			<td>MMSE</td>
			<td>28.53 (1.63)</td>
			<td>28 (1.84)</td>
			<td>0.09</td>
		</tr>
		<tr>
			<td>MoCA</td>
			<td>27.10 (2.25)</td>
			<td>26 (2.34)</td>
			<td>0.009*</td>
		</tr>
		<tr>
			<td colspan="4">Specific Cognitive tests &#8211; Frontal executive &#38; Frontal-temporal</td>
		</tr>
		<tr>
			<td>Stocking of Cambridgea</td>
			<td>1.16 (0.14)</td>
			<td>1.24 (0.19)</td>
			<td>0.018*</td>
		</tr>
		<tr>
			<td>Stroop testb</td>
			<td>1.24 (1.77)</td>
			<td>1.36 (1.65)</td>
			<td>0.697</td>
		</tr>
		<tr>
			<td>Verbal fluency - animalb</td>
			<td>0.92 (1.47)</td>
			<td>0.26 (1.31)</td>
			<td>0.01*</td>
		</tr>
		<tr>
			<td>Verbal fluency - fruitb</td>
			<td>-0.71 (0.74)</td>
			<td>-1.01 (0.79)</td>
			<td>0.028*</td>
		</tr>
		<tr>
			<td>Verbal fluency - vegetableb</td>
			<td>-0.66 (1.04)</td>
			<td>-1.11 (0.90)</td>
			<td>0.011*</td>
		</tr>
		<tr>
			<td colspan="4">Specific Cognitive tests &#8211; Verbal Memory (Hong Kong List Learning Test)</td>
		</tr>
		<tr>
			<td>Total learningb</td>
			<td>0.03 (0.90)</td>
			<td>-0.30 (0.87)</td>
			<td>0.037*</td>
		</tr>
		<tr>
			<td>10 minutes delay free recallb</td>
			<td>-0.17 (0.90)</td>
			<td>-0.44 (1.10)</td>
			<td>0.131</td>
		</tr>
		<tr>
			<td>30 minutes delay free recallb</td>
			<td>-0.19 (0.90)</td>
			<td>-0.39 (1.04)</td>
			<td>0.206</td>
		</tr>
		<tr>
			<td>Recognition scoreb</td>
			<td>0.10 (1.00)</td>
			<td>0.15 (0.73)</td>
			<td>0.722</td>
		</tr>
		<tr>
			<td>Discrimination scoreb</td>
			<td>-0.05 (1.02)</td>
			<td>-0.13 (0.97)</td>
			<td>0.636</td>
		</tr>
		<tr>
			<td colspan="4">Specific Cognitive tests &#8211; Visual spatial memory</td>
		</tr>
		<tr>
			<td>Pattern recognition memoryc</td>
			<td>91.33 (9.40)</td>
			<td>87.77 (10.20)</td>
			<td>0.045*</td>
		</tr>
		<tr>
			<td colspan="4">Specific Cognitive tests &#8211; Attention/Working memory</td>
		</tr>
		<tr>
			<td>Spatial spand</td>
			<td>6.15 (1.10)</td>
			<td>5.65 (1.17)</td>
			<td>0.016*</td>
		</tr>
	</tbody>
</table>
Table 1: Comparison of cognitive scores between two groups using independent sample t-test. MMSE, Mini-Mental State Examination; MoCA, Montreal Cognitive Assessment; *&#8211; p&#60;0.05 a &#8211; mean choices to correct; b &#8211; scores transformed into z-score; c &#8211; percentage correct; d &#8211; span length. This table has been reproduced from23.
<table border="1" fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td></td>
			<td>Control group</td>
			<td>Parkinson&#39;s disease group</td>
			<td>p-value</td>
		</tr>
		<tr>
			<td>Mean fixation duration, in miliseconds (SD) [Range]</td>
			<td>211.59 (24.90) [165.77 - 264.63]</td>
			<td>216.58 (31.64) [145.43-312.68]</td>
			<td>0.331</td>
		</tr>
		<tr>
			<td>Mean saccadic amplitude, in degrees (SD) [Range]</td>
			<td>17.27 (2.49) [13.34 - 22.99]</td>
			<td>16.36 (2.36) [11.66-23.20]</td>
			<td>0.037*</td>
		</tr>
	</tbody>
</table>
Table 2: Comparison of eye tracking parameters between two groups using independent sample t-test. * - p &#60; 0.05. This table has been modified from23.
<table border="1" fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Source</td>
			<td>Dependent Variable</td>
			<td>df</td>
			<td>F</td>
			<td>B</td>
			<td>Beta</td>
			<td>Std. Error</td>
			<td>t</td>
			<td>p-value</td>
		</tr>
		<tr>
			<td>Mean fixation duration</td>
			<td>Verbal fluency - fuit</td>
			<td>1</td>
			<td>5.647</td>
			<td>-0.006</td>
			<td>-0.227</td>
			<td>0.002</td>
			<td>-2.376</td>
			<td>0.009*</td>
		</tr>
		<tr>
			<td></td>
			<td>Verbal fluency - vegetable</td>
			<td>1</td>
			<td>9.744</td>
			<td>-0.009</td>
			<td>-0.288</td>
			<td>0.003</td>
			<td>-3.122</td>
			<td>0.002*</td>
		</tr>
		<tr>
			<td></td>
			<td>Recognition score</td>
			<td>1</td>
			<td>5.843</td>
			<td>-0.007</td>
			<td>-0.215</td>
			<td>0.003</td>
			<td>-2.417</td>
			<td>0.017*</td>
		</tr>
		<tr>
			<td></td>
			<td>Discrimination score</td>
			<td>1</td>
			<td>12.771</td>
			<td>-0.011</td>
			<td>-0.314</td>
			<td>0.003</td>
			<td>-3.574</td>
			<td>0.001*</td>
		</tr>
		<tr>
			<td></td>
			<td>Pattern recognition memory</td>
			<td>1</td>
			<td>5.505</td>
			<td>-0.071</td>
			<td>-0.215</td>
			<td>0.03</td>
			<td>-2.346</td>
			<td>0.021*</td>
		</tr>
	</tbody>
</table>
Table 3: Correlations between cognitive scores and eye-tracking parameters using General Linear Model: Significant findings only. * - p &#60; 0.05. This table has been reproduced from23.
<img alt="Supplemental File 1" src="/files/ftp_upload/60052/60052supfig1.jpg" /> 
Supplemental File 1: Codes related to the trial image design. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/Supplementary_File_1.pdf" target="_blank">Please click here to download this file.</a>
<img alt="Supplemental File 2" src="/files/ftp_upload/60052/60052supfig2.jpg" /> 
Supplemental File 2: Codes related to the actual run of the visual search task. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/Supplementary_File_2.pdf" target="_blank">Please click here to download this file.</a>
<img alt="Supplemental File 3" src="/files/ftp_upload/60052/60052supfig3.jpg" /> 
Supplemental File 3: Codes related to the software (e.g., analyzer program). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/Supplementary_File_3.pdf" target="_blank">Please click here to download this file.</a>
<img alt="Supplemental File 4" src="/files/ftp_upload/60052/60052supfig4.jpg" /> 
Supplemental File 4: Codes related to the ST-DBSCAN algorithm used for classifying eye movement metrics. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60052/Supplementary_File_4.pdf" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking at JoVE

Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Here, we present a protocol to study the relationship between the eye movement parameters and cognitive functions in non-demented Parkinson&#39;s disease patients. The experiment used an eye tracker to measure the saccadic amplitude and fixation duration in a visual search task. The correlation with performance in multi-domain cognitive tasks was subsequently measured.

Cognitive impairment is a common phenomenon in Parkinson&#8217;s disease that has implications on the prognosis. A simple, noninvasive and objective proxy ...

characterizing-relationship-between-eye-movement-parameters-cognitive

Nanyang Technological University

Research

JoVE Journal

Neuroscience

7.7K Views.  The Chinese University of Hong Kong. Here, we present a protocol to study the relationship between the eye movement parameters and cognitive functions in non-demented Parkinson's disease patients. The experiment used an eye tracker to measure the saccadic amplitude and fixation duration in a visual search task. The correlation with performance in multi-domain cognitive tasks was subsequently measured.

Video: Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Experimental Models for Study of Retinal Pigment Epithelial Physiology and Pathophysiology

We have developed a cell culture procedure that can produce large quantities of confluent monolayers of primary human fetal retinal pigment epithelium (hfRPE) cultures with morphological, physiological and genetic characteristics of native human RPE. These hfRPE cell cultures exhibit heavy pigmentation, and electron microscopy show extensive apical membrane microvilli. The junctional complexes were identified with immunofluorescence labeling of various tight junction proteins. Epithelial polarity and function of these easily reproducible primary cultures closely resemble previously studied mammalian models of native RPE, including human. These results were extended by the development of therapeutic interventions in several animal models of human eye disease. We have focused on strategies for the removal of abnormal fluid accumulation in the retina or subretinal space. The extracellular subretinal space separates the photoreceptor outer segments and the apical membrane of the RPE and is critical for maintenance of retinal attachments and a whole host of RPE/retina interactions.

We provide a reproducible method for culturing confluent monolayers of human fetal retinal pigment epithelial cells (hfRPE) cells that exhibit morphology, physiology, polarity, and protein and gene expression patterns of adult native tissue. This work has been extended to an animal model of several eye diseases.

We have developed a cell culture procedure that can produce large quantities of confluent monolayers of primary human fetal retinal pigment epithelium ...

Eye Movement Monitoring of Memory

Explicit (often verbal) reports are typically used to investigate memory (e.g. "Tell me what you remember about the person you saw at the bank yesterday."), however such reports can often be unreliable or sensitive to response bias 1, and may be unobtainable in some participant populations. Furthermore, explicit reports only reveal when information has reached consciousness and cannot comment on when memories were accessed during processing, regardless of whether the information is subsequently accessed in a conscious manner. Eye movement monitoring (eye tracking) provides a tool by which memory can be probed without asking participants to comment on the contents of their memories, and access of such memories can be revealed on-line 2,3. Video-based eye trackers (either head-mounted or remote) use a system of cameras and infrared markers to examine the pupil and corneal reflection in each eye as the participant views a display monitor. For head-mounted eye trackers, infrared markers are also used to determine head position to allow for head movement and more precise localization of eye position. Here, we demonstrate the use of a head-mounted eye tracking system to investigate memory performance in neurologically-intact and neurologically-impaired adults. Eye movement monitoring procedures begin with the placement of the eye tracker on the participant, and setup of the head and eye cameras. Calibration and validation procedures are conducted to ensure accuracy of eye position recording. Real-time recordings of X,Y-coordinate positions on the display monitor are then converted and used to describe periods of time in which the eye is static (i.e. fixations) versus in motion (i.e., saccades). Fixations and saccades are time-locked with respect to the onset/offset of a visual display or another external event (e.g. button press). Experimental manipulations are constructed to examine how and when patterns of fixations and saccades are altered through different types of prior experience. The influence of memory is revealed in the extent to which scanning patterns to new images differ from scanning patterns to images that have been previously studied 2, 4-5. Memory can also be interrogated for its specificity; for instance, eye movement patterns that differ between an identical and an altered version of a previously studied image reveal the storage of the altered detail in memory 2-3, 6-8. These indices of memory can be compared across participant populations, thereby providing a powerful tool by which to examine the organization of memory in healthy individuals, and the specific changes that occur to memory with neurological insult or decline 2-3, 8-10.

Eye movement monitoring (or eye tracking) reveals where in space the eyes linger, when and for how long. Here, we demonstrate how eye tracking can be used to investigate the integrity of memory in multiple participant populations, without requiring verbal, or otherwise explicit, reports.

Explicit (often verbal) reports are typically used to investigate memory (e.g. "Tell me what you remember about the person you saw at the bank ...

A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

We have developed a fully automated system for operant behavior testing and neuronal activity recording by which multiple cognitive brain functions can be investigated in a single task sequence. The unique feature of this system is a custom-made, acoustically transparent chamber that eliminates many of the issues associated with auditory cue control in most commercially available chambers. The ease with which operant devices can be added or replaced makes this system quite versatile, allowing for the implementation of a variety of auditory, visual, and olfactory behavioral tasks. Automation of the system allows fine temporal (10 ms) control and precise time-stamping of each event in a predesigned behavioral sequence. When combined with a multi-channel electrophysiology recording system, multiple cognitive brain functions, such as motivation, attention, decision-making, patience, and rewards, can be examined sequentially or independently.

In this report, we present a fully automated and highly versatile system capable of simultaneously testing multi-cognitive behaviors and recording neuronal activities for rodents.

We have developed a fully automated system for operant behavior testing and neuronal activity recording by which multiple cognitive brain functions can be ...

Tactile Conditioning And Movement Analysis Of Antennal Sampling Strategies In Honey Bees (Apis mellifera L.)

Honey bees (Apis mellifera L.) are eusocial insects and well known for their complex division of labor and associative learning capability1, 2. The worker bees spend the first half of their life inside the dark hive, where they are nursing the larvae or building the regular hexagonal combs for food (e.g. pollen or nectar) and brood3. The antennae are extraordinary multisensory feelers and play a pivotal role in various tactile mediated tasks4, including hive building5 and pattern recognition6. Later in life, each single bee leaves the hive to forage for food. Then a bee has to learn to discriminate profitable food sources, memorize their location, and communicate it to its nest mates7. Bees use different floral signals like colors or odors7, 8, but also tactile cues from the petal surface9 to form multisensory memories of the food source. Under laboratory conditions, bees can be trained in an appetitive learning paradigm to discriminate tactile object features, such as edges or grooves with their antennae10, 11, 12, 13. This learning paradigm is closely related to the classical olfactory conditioning of the proboscis extension response (PER) in harnessed bees14. The advantage of the tactile learning paradigm in the laboratory is the possibility of combining behavioral experiments on learning with various physiological measurements, including the analysis of the antennal movement pattern.

Tactile Conditioning And Movement Analysis Of Antennal Sampling Strategies In Honey Bees Apis mellifera L.

In this protocol we show how to condition harnessed honey bees to tactile stimuli and introduce a 2D motion capture technique for analyzing the kinematics of fine-scale antennal sampling pattern.

Honey bees (Apis mellifera L.) are eusocial insects and well known for their complex division of labor and associative learning capability1, 2. The worker ...

The Corneal Micropocket Assay: A Model of Angiogenesis in the Mouse Eye

The mouse corneal micropocket assay is a robust and quantitative in vivo assay for evaluating angiogenesis. By using standardized slow-release pellets containing specific growth factors that trigger blood vessel growth throughout the naturally avascular cornea, angiogenesis can be measured and quantified. In this assay the angiogenic response is generated over the course of several days, depending on the type and dose of growth factor used. The induction of neovascularization is commonly triggered by either basic fibroblast growth factor (bFGF) or vascular endothelial growth factor (VEGF). By combining these growth factors with sucralfate and hydron (poly-HEMA (poly(2-hydroxyethyl methacrylate))) and casting the mixture into pellets, they can be surgically implanted in the mouse eye. These uniform pellets slowly-release the growth factors over five or six days (bFGF or VEGF respectively) enabling sufficient angiogenic response required for vessel area quantification using a slit lamp. This assay can be used for different applications, including the evaluation of angiogenic modulator drugs or treatments as well as comparison between different genetic backgrounds affecting angiogenesis. A skilled investigator after practicing this assay can implant a pellet in less than 5 min per eye.

The protocol describes the corneal micropocket assay as developed in mice.

The mouse corneal micropocket assay is a robust and quantitative in vivo assay for evaluating angiogenesis. By using standardized slow-release pellets ...

Semi-Quantitative Determination of Dopaminergic Neuron Density in the Substantia Nigra of Rodent Models using Automated Image Analysis

Estimation of the number of dopaminergic neurons in the substantia nigra is a key method in pre-clinical Parkinson's disease research. Currently, unbiased stereological counting is the standard for quantification of these cells, but it remains a laborious and time-consuming process, which may not be feasible for all projects. Here, we describe the use of an image analysis platform, which can accurately estimate the quantity of labeled cells in a pre-defined region of interest. We describe a step-by-step protocol for this method of analysis in rat brain and demonstrate it can identify a significant reduction in tyrosine hydroxylase positive neurons due to expression of mutant &#945;-synuclein in the substantia nigra. We validated this methodology by comparing with results obtained by unbiased stereology. Taken together, this method provides a time-efficient and accurate process for detecting changes in dopaminergic neuron number, and thus is suitable for efficient determination of the effect of interventions on cell survival.

Here we present an automated method for semi-quantitative determination of dopaminergic neuron number in the rat substantia nigra pars compacta.

Estimation of the number of dopaminergic neurons in the substantia nigra is a key method in pre-clinical Parkinson's disease research. Currently, unbiased ...

Immunostaining of Whole-Mount Retinas with the CLARITY Tissue Clearing Method

The tissue hydrogel delipidation method (CLARITY), originally developed by the Deisseroth laboratory, has been modified and widely used for immunostaining and imaging of thick brain samples. However, this advanced technology has not yet been used for whole-mount retinas. Although the retina is partially transparent, its thickness of approximately 200 &#181;m (in mice) still limits the penetration of antibodies into the deep tissue as well as reducing light penetration for high-resolution imaging. Here, we adapted the CLARITY method for whole-mount mouse retinas by polymerizing them with an acrylamide monomer to form a nanoporous hydrogel and then clearing them in sodium dodecyl sulfate to minimize protein loss and avoid tissue damage. CLARITY-processed retinas were immunostained with antibodies for retinal neurons, glial cells, and synaptic proteins, mounted in a refractive index matching solution, and imaged. Our data demonstrate that CLARITY&#160;can improve the quality of standard immunohistochemical staining and imaging for retinal neurons and glial cells in whole-mount preparation. For instance, 3D resolution of fine axon-like and dendritic structures of dopaminergic amacrine cells were much improved by CLARITY. Compared to non-processed whole-mount retinas, CLARITY can reveal immunostaining for synaptic proteins such as postsynaptic density protein 95. Our results show that CLARITY renders the retina more optically transparent after the removal of lipids and preserves fine structures of retinal neurons and their proteins, which can be routinely used for obtaining high-resolution imaging of retinal neurons and their subcellular structures in whole-mount preparation.

Here we present a protocol to adapt the CLARITY method of the brain tissues for whole-mount retinas to improve the quality of standard immunohistochemical staining and high-resolution imaging of retinal neurons and their subcellular structures.

The tissue hydrogel delipidation method (CLARITY), originally developed by the Deisseroth laboratory, has been modified and widely used for immunostaining ...

Optimizing the Setup and Conditions for Ex Vivo Electroretinogram to Study Retina Function in Small and Large Eyes

Measurements of retinal neuronal light responses are critical to investigating the physiology of the healthy retina, determining pathological changes in retinal diseases, and testing therapeutic interventions. The ex vivo electroretinogram (ERG) allows the quantification of contributions from individual cell types in the isolated retina by addition of specific pharmacological agents and evaluation of tissue-intrinsic changes independently of systemic influences. Retinal light responses can be measured using a specialized ex vivo ERG specimen holder and recording setup, modified from existing patch clamp or microelectrode array equipment. Particularly, the study of ON-bipolar cells, but also of photoreceptors, has been hampered by the slow but progressive decline of light responses in the ex vivo ERG over time. Increased perfusion speed and adjustment of the perfusate temperature improve ex vivo retinal function and maximize response amplitude and stability. The ex vivo ERG uniquely allows the study of individual retinal neuronal cell types. In addition, improvements to maximize response amplitudes and stability allow the investigation of light responses in retina samples from large animals, as well as human donor eyes, making the ex vivo ERG a valuable addition to the repertoire of techniques used to investigate retinal function.

Optimizing the Setup and Conditions for Ex Vivo Electroretinogram to Study Retina Function in Small and Large Eyes

Modification of existing multielectrode array or patch clamp equipment makes the ex vivo electroretinogram more widely accessible. Improved methods to record and maintain ex vivo light responses facilitate the study of photoreceptor and ON-bipolar cell function in the healthy retina, animal models of eye diseases, and human donor retinas.

Measurements of retinal neuronal light responses are critical to investigating the physiology of the healthy retina, determining pathological changes in ...

In Vivo Methods to Assess Retinal Ganglion Cell and Optic Nerve Function and Structure in Large Animals

The optic nerve collects axons signals from the retinal ganglion cells and transmits visual signal to the brain. Large animal models of optic nerve injury are essential for translating novel therapeutic strategies from rodent models to clinical application due to their closer similarities to humans in size and anatomy. Here we describe some in vivo methods to evaluate the function and structure of the retinal ganglion cells (RGCs) and optic nerve (ON) in large animals, including visual evoked potential (VEP), pattern electroretinogram (PERG) and optical coherence tomography (OCT). Both goat and non-human primate were employed in this study. By presenting these in vivo methods step by step, we hope to increase experimental reproducibility among different labs and facilitate the usage of large animal models of optic neuropathies.

In Vivo Methods to Assess Retinal Ganglion Cell and Optic Nerve Function and Structure in Large Animals

Here we demostrate several in vivo tests (flash visual evoked potential, pattern electroretinogram and optic coherence tomography) in goat and rhesus macaque to understand the structure and function of the optic nerve and its neurons.

The optic nerve collects axons signals from the retinal ganglion cells and transmits visual signal to the brain. Large animal models of optic nerve injury ...

The 6-hydroxydopamine Rat Model of Parkinson's Disease

Motor symptoms of Parkinson's disease (PD)-bradykinesia, akinesia, and tremor at rest-are consequences of the neurodegeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc) and dopaminergic striatal deficit. Animal models have been widely used to simulate human pathology in the laboratory. Rodents are the most used animal models for PD due to their ease of handling and maintenance. Moreover, the anatomy and molecular, cellular, and pharmacological mechanisms of PD are similar in rodents and humans. The infusion of the neurotoxin, 6-hydroxydopamine (6-OHDA), into a medial forebrain bundle (MFB) of rats reproduces the severe destruction of dopaminergic neurons and simulates PD symptoms. This protocol demonstrates how to perform the unilateral microinjection of 6-OHDA in the MFB in a rat model of PD and shows the motor deficits induced by 6-OHDA and predicted dopaminergic lesions through the stepping test. The 6-OHDA causes significant impairment in the number of steps performed with the contralateral forelimb.

The 6-hydroxydopamine (6-OHDA) model has been used for decades to advance the understanding of Parkinson's Disease. In this protocol, we demonstrate how to perform unilateral nigrostriatal lesions in the rat by injecting 6-OHDA in the medial forebrain bundle, assess motor deficits, and predict lesions using the stepping test.

Motor symptoms of Parkinson's disease (PD)-bradykinesia, akinesia, and tremor at rest-are consequences of the neurodegeneration of dopaminergic neurons in ...

Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Summary

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Chapters in this video

Experimental Models for Study of Retinal Pigment Epithelial Physiology and Pathophysiology

Eye Movement Monitoring of Memory

A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

Tactile Conditioning And Movement Analysis Of Antennal Sampling Strategies In Honey Bees (Apis mellifera L.)

The Corneal Micropocket Assay: A Model of Angiogenesis in the Mouse Eye

Semi-Quantitative Determination of Dopaminergic Neuron Density in the Substantia Nigra of Rodent Models using Automated Image Analysis

Immunostaining of Whole-Mount Retinas with the CLARITY Tissue Clearing Method

Optimizing the Setup and Conditions for Ex Vivo Electroretinogram to Study Retina Function in Small and Large Eyes

In Vivo Methods to Assess Retinal Ganglion Cell and Optic Nerve Function and Structure in Large Animals

The 6-hydroxydopamine Rat Model of Parkinson's Disease