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 e...

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.

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		<col />
		<col />
		<col />
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	<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>
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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...

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

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

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 ...

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 ...

Organotypic Retinal Explant Cultures from Macaque Monkey

Hereditary retinal degeneration (RD) is characterized by progressive photoreceptor cell death. Overactivation of the cyclic guanosine monophosphate (cGMP)-dependent protein kinase (PKG) pathway in photoreceptor cells causes photoreceptor cell death, especially in models harboring phosphodiesterase 6b (PDE6b) mutations. Previous studies on RD have used mainly murine models such as rd1 or rd10 mice. Given the genetic and physiological differences between mice and humans, it is important to understand to which extent the retinas of primates and rodents are comparable. Macaques share a high level of genetic similarity with humans. Therefore, wild-type macaques (aged 1-3 years) were selected for the in vitro culture of retinal explants that included the retina-retinal pigment epithelium (RPE)-choroid complex. These explants were treated with different concentrations of the PDE6 inhibitor zaprinast to induce the cGMP-PKG signaling pathway and simulate RD pathogenesis. cGMP accumulation and cell death in primate retinal explants were subsequently verified using immunofluorescence and the TUNEL assay. The primate retinal model established in this study may serve for relevant and effective studies into the mechanisms of cGMP-PKG-dependent RD, as well as for the development of future treatment approaches.

Retinal explants obtained from wild-type macaques were cultured in vitro. Retinal degeneration and the cGMP-PKG signaling pathway was induced using the PDE6 inhibitor zaprinast. cGMP accumulation in the explants at different zaprinast concentrations was verified using immunofluorescence.

Hereditary retinal degeneration (RD) is characterized by progressive photoreceptor cell death. Overactivation of the cyclic guanosine monophosphate ...

An In Situ Immunostaining Protocol for Parkinson's Disease Study

Histological Examination of Mitochondrial Morphology in a Parkinson's Disease Model

Mitochondria play a central role in the energy metabolism of cells, and their function is especially important for neurons due to their high energy demand. Therefore, mitochondrial dysfunction is a pathological hallmark of various neurological disorders, including Parkinson's disease. The shape and organization of the mitochondrial network is highly plastic, which allows the cell to respond to environmental cues and needs, and the structure of mitochondria is also tightly linked to their health. Here, we present a protocol to study mitochondrial morphology in situ based on immunostaining of the mitochondrial protein VDAC1 and subsequent image analysis. This tool could be particularly useful for the study of neurodegenerative disorders because it can detect subtle differences in mitochondrial counts and shape induced by aggregates of &#945;-synuclein, an aggregation-prone protein heavily involved in the pathology of Parkinson's disease. This method allows one to report that substantia nigra pars compacta dopaminergic neurons harboring pS129 lesions show mitochondrial fragmentation (as suggested by their reduced Aspect Ratio, AR) compared to their healthy neighboring neurons in a pre-formed fibril intracranial injection Parkinson model.

Author Spotlight: Establishing a New Fluorescence-Based Protocol for In Vivo Mitochondrial Morphology Analysis in Parkinson's Disease

This study presents a method to analyze the morphology of mitochondria based on immunostaining and image analysis in mouse brain tissue in situ. It also describes how this allows one to detect changes in mitochondrial morphology induced by protein aggregation in Parkinson's disease models.

Mitochondria play a central role in the energy metabolism of cells, and their function is especially important for neurons due to their high energy ...

Python-Based Tool for Quantitative Optokinetic Reflex Assessment in Animals

PyOKR: A Semi-Automated Method for Quantifying Optokinetic Reflex Tracking Ability

The study of behavioral responses to visual stimuli is a key component of understanding visual system function. One notable response is the optokinetic reflex (OKR), a highly conserved innate behavior necessary for image stabilization on the retina. The OKR provides a robust readout of image tracking ability and has been extensively studied to understand visual system circuitry and function in animals from different genetic backgrounds. The OKR consists of two phases: a slow tracking phase as the eye follows a stimulus to the edge of the visual plane and a compensatory fast phase saccade that resets the position of the eye in the orbit. Previous methods of tracking gain quantification, although reliable, are labor intensive and can be subjective or arbitrarily derived. To obtain more rapid and reproducible quantification of eye tracking ability, we have developed a novel&#160;semi-automated analysis program, PyOKR, that allows for quantification of two-dimensional eye tracking motion in response to any directional stimulus, in addition to being adaptable to any type of video-oculography equipment. This method provides automated filtering, selection of slow tracking phases, modeling of vertical and horizontal eye vectors, quantification of eye movement gains relative to stimulus speed, and organization of resultant data into a usable spreadsheet for statistical and graphical comparisons. This quantitative and streamlined analysis pipeline, readily accessible via PyPI import, provides a fast and direct measurement of OKR responses, thereby facilitating the study of visual behavioral responses.

Author Spotlight: A Streamlined and Accessible Analysis Method to Quantify Optokinetic Reflex Tracking Responses

We describe here PyOKR, a semi-automated quantitative analysis method that directly measures eye movements resulting from visual responses to two-dimensional image motion. A Python-based user interface and analysis algorithm allows for higher throughput and more accurate quantitative measurements of eye-tracking parameters than previous methods.

The study of behavioral responses to visual stimuli is a key component of understanding visual system function. One notable response is the optokinetic ...

Visualizing Retinal Synaptic Structures in 3D with Volume Electron Microscopy

Preparation of Retinal Samples for Volume Electron Microscopy

Volume electron microscopy (Volume EM) has emerged as a powerful tool for visualizing the 3D structure of cells and tissues with nanometer-level precision. Within the retina, various types of neurons establish synaptic connections in the inner and outer plexiform layers. While conventional EM techniques have yielded valuable insights into retinal subcellular organelles, their limitation lies in providing 2D image data, which can hinder accurate measurements. For instance, quantifying the size of three distinct synaptic vesicle pools, crucial for synaptic transmission, is challenging in 2D. Volume EM offers a solution by providing large-scale, high-resolution 3D data. It is worth noting that sample preparation is a critical step in Volume EM, significantly impacting image clarity and contrast. In this context, we outline a sample preparation protocol for the 3D reconstruction of photoreceptor axon terminals in the retina. This protocol includes three key steps: retina dissection and fixation, sample embedding processes, and selection of the area of interest.

Author Spotlight: Retinal Neuroscience Studies with Volume Electron Microscopy

This protocol describes the detailed steps for preparing retinal samples for volume electron microscopy, focusing on the structural features of retinal photoreceptor terminals.

Volume electron microscopy (Volume EM) has emerged as a powerful tool for visualizing the 3D structure of cells and tissues with nanometer-level ...

Optimized Protocol for Retinal Organoid Sample Preparation for TEM

Preparing Retinal Organoid Samples for Transmission Electron Microscopy

Retinal organoids (ROs) are a three-dimensional culture system mimicking human retinal features that have differentiated from induced pluripotent stem cells (iPSCs) under specific conditions. Synapse development and maturation in ROs have been studied immunocytochemically and functionally. However, the direct evidence of the synaptic contact ultrastructure is limited, containing both special ribbon synapses and conventional chemical synapses. Transmission electron microscopy (TEM) is characterized by high resolution and a respectable history elucidating retinal development and synapse maturation in humans and various species. It is a powerful tool to explore synaptic structure in ROs and is widely used in the research field of ROs. Therefore, to better explore the structure of RO synaptic contacts at the nanoscale and obtain high-quality microscopic evidence, we developed a simple and repeatable method of RO TEM sample preparation. This paper describes the protocol, reagents used, and detailed steps, including RO fixation preparation, post fixation, embedding, and visualization.

Author Spotlight: Analyzing the Synaptic Ultrastructure in Mature Retinal Organoids Using TEM

This protocol provides an optimized and elaborate preparation procedure for retinal organoid samples for transmission electron microscopy. It is suitable for applications that involve the analysis of synapses in mature retinal organoids.

Retinal organoids (ROs) are a three-dimensional culture system mimicking human retinal features that have differentiated from induced pluripotent stem ...