The protocol was conducted at the Laboratory of Brain Imaging at the Nencki Institute of Experimental Biology, Warsaw, Poland and was supported by a grant 2018/29/B/NZ4/02435 from the National Science Centre (Poland) awarded to K.B and J.S.

All procedures were performed following the relevant guidelines and regulations and were approved by the Ethical Committee, WUM (KB/157/2017). Written consent was obtained from all participants, ensuring that they understood the general aim of the experiment and that they understood the inclusion of their data for statistical analysis purposes. All presented visual stimuli are generated using a Java-based desktop application (Viscacha2) created for the purpose of these experiments.&#160;
1. Setup
<ol>
	<li>Secure a quiet, dimmed room. Build a setup consisting of a computer, a keyboard, a flat display, an eye tracker (optional, depending on the research question and aims; see Table of Materials), a desk, a chinrest, and a chair. Arrange it so that the participants can sit with the chin resting on the chinrest, eyes directly in front of the center of the upper half of the display, and hands reaching the arrow keys on the keyboard. The horizontal distance between the display and the eyes should be 85 cm. 
	NOTE: Although the participants are trained and specifically asked to fixate the central fixation cross during the entire procedure, testing with an eye tracker may constitute an additional control for filtering during analyses of those participants who exhibit too many fluctuations with their gaze. Moreover, depending on the aim of the study, eye tracker results may provide interesting insight into the fixation patterns, pupil size, or location of interest of different cohorts of participants.&#160;</li>
	<li>Visit https://github.com/grimwj/Viscacha2 and download the software by clicking the Code button and downloading ZIP. Extract the zip file and save it in the working directory.</li>
	<li>Follow the installation steps described in the README.txt file. In case of testing with an eye tracker, follow the software installation steps for the eye tracker. Mount the eye tracker as per instruction.</li>
	<li>To perform an initial check, run the program by double-clicking the Viscacha2.jar file. After the initial screen is displayed, press ESC on the keyboard to exit the program.</li>
	<li>Navigate through newly created folders &#8211; experiment_data, TestPatient, Shape_Brt. Open the .csv file using a spreadsheet editor (set semicolon as field separator). Verify that the parameters, such as screen dimensions and the distance from the screen, are correct. 
	NOTE: From here, the protocol is based on the assumption that a 1920 x 1080, 31.5 inch display is used and the distance between the patient and the screen is 85 cm. This implies that the screen occupies 44.6&#176; of visual space horizontally. If these parameters cannot be met, one can refer to step 5 for reconfiguring the program.</li>
</ol>
2. Determining the initial difficulty of the test
<ol>
	<li>Open the config.txt file and find a line containing patient_name=TestPatient. Replace the TestPatient with a text identifying the subject being examined.</li>
	<li>In the config.txt file, find the line filename=Shape_Brt.txt. Make sure that this line does not begin with a hash symbol # (uncommented line).&#160;</li>
	<li>Ask the subject to sit in front of the display, with his/her chin rested and eyes directly in front of the center of the upper half of the display. Verify that the distance from the screen is correct. Make sure that the keyboard keys are easily accessible for the subject to use.&#160;</li>
	<li>Navigate to the Viscacha2.jar directory and run the program. Teach the participant to focus the sight on the fixation cross at the center of the screen for the entire duration of the experiment.&#160;&#160;</li>
	<li>On each side of the screen, either a circle or an ellipse will be presented at the same distance from the central fixation cross. The task is to select the circle over an ellipse using the left and right arrow keys on the keyboard. Explain the task to the participant, and when he/she is ready, press the s key to begin the experiment. The experiment continues till the participant presses one of the arrow keys.&#160;</li>
	<li>The program ends&#160;after four reversals have occurred or a maximum number of trials has been reached. A reversal occurs when the subject selects the wrong response after previously selecting the correct one or vice versa. 
	NOTE: This is a staircase-type procedure. The difficulty of each trial increases after each correct response and decreases after a wrong response. Figure 1 displays how the staircase level changes over trials for one representative participant.&#160;&#160;&#160;</li>
	<li>Note the four reversals after which the task is finished and the detection threshold has been established. Open the corresponding .csv file containing results. Locate the THRESHOLD columns near the end of the file. Use the value in this column to calculate the initial difficulty for subsequent tasks.&#160; 
	NOTE: The test can also be presented in a constant paradigm, where the level of the difficulty is fixed and does not change, by removing the hash symbol from the Experiment_Type=Constant line in the init.txt files and by adding a hash symbol before the line Experiment_Type=Staircase.&#160;</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66272/66272fig1.jpg" /> 
Figure 1: Change in the staircase level over the duration of the Shape_Brt experiment (subsequent trials). The red plot depicts the staircase level, which translates to the aspect ratio of the S- (ellipse). After 4 reversals have occurred (blue bars), the subject&#8217;s detection threshold has been established, and the task is finished. <a href="https://www.jove.com/files/ftp_upload/66272/66272fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="8">
	<li>Use the newly obtained threshold as the baseline for the next stimuli presentation (steps 2.3&#8211;2.5). To replace the new threshold in all the stimuli definition files, use the Python script inside the replacer folder and follow the instructions on the screen.&#160;&#160;</li>
</ol>
3. Stimuli procedure
NOTE: A total of 10 experiments will be conducted: 5 with white dots on a black background and 5 with black dots on a white background.
<ol>
	<li>Coherence task
	<ol>
		<li>When the subject is ready, open the config.txt file and comment (i.e., insert the hash symbol) the line filename=Shape_Brt.txt and uncomment the line below, including the shape_dotsB_C.txt task. In this task, the circle and the ellipse consist of dots moving randomly with a velocity of 10&#176;/s. The background is built of dots moving coherently upward with the same velocity as in the circle and ellipse. 
		NOTE: It is possible to define a different movement direction of the background dots by editing the Direction parameter inside the definition file for each task.&#160;&#160;</li>
		<li>Run Viscacha2.jar. Explain the task to the subject in simple words, for example, Please always point to the circle. When the participant is ready, press the s key to begin the experiment. Wait until the experiment is completed.&#160;</li>
		<li>Open the config.txt file, comment the line filename=shape_dotsB_C.txt, and uncomment the line below including the shape_dotsW_C.txt task. Repeat step 3.1.2.&#160;</li>
	</ol>
	</li>
	<li>Direction task&#160;
	<ol>
		<li>&#160;When the subject is ready, open the config.txt file and comment on the previously selected filename. Uncomment the line containing filename=shape_dotsB_D.txt task. In this task, the circle and the ellipse consist of dots moving coherently upward with a velocity of 10&#176;/s. The background consists of dots moving coherently leftward with the same velocity as in the circle and ellipse.&#160;</li>
		<li>Run Viscacha2.jar. Explain the task to the subject. When the participant is ready, press the s key to begin the experiment. Wait until the experiment is completed.&#160;</li>
		<li>Open the config.txt file, comment the line filename=shape_dotsB_D.txt, and uncomment the line below, including the shape_dotsW_D.txt task. Repeat step 3.2.2.&#160;</li>
	</ol>
	</li>
	<li>Velocity task&#160;
	<ol>
		<li>&#160;When the subject is ready, open the config.txt file and comment the previously selected filename. Uncomment the line containing filename=shape_dotsB_V10_20.txt task. This task involves three conditions. The circle and ellipse and the background consist of dots moving coherently upward, and dots within the circle and the ellipse always move slower than the background dots: i) 10&#176;/s versus 20&#176;/s; ii) 5&#176;/s versus 10&#176;/s; and iii) 1&#176;/s versus 2&#176;/s.</li>
		<li>Run Viscacha2.jar. Explain the task to the subject. When the participant is ready, press the s key to begin the experiment. Wait until the experiment is completed.&#160;</li>
		<li>Open the config.txt file and comment on the line shape_dotsB_V10_20.txt and uncomment the line below, including the shape_dotsW_V10_20.txt task. Repeat step 3.2.2.&#160;</li>
		<li>Repeat steps 3.3.1 - 3.3.3 2x, for tasks shape_dotsB_V5_10.txt and shape_dotsW_V5_10.txt, as well as for shape_dotsB_V1_2.txt and shape_dotsW_V1_2.txt.&#160;
		<ol>
			<li>To avoid manually changing the filename for each task after the task is done, use a sweep_file option. In the config.txt file, set the sweep_files field to 0 to end the procedure after each task procedure is over.&#160;&#160;</li>
			<li>Use this setting for the Shape_Brt.txt task to define the initial baseline threshold value. Once the baseline is set, for running multiple tasks in succession, set the sweep file to an integer between 1 and 9. The integer here determines the number of changes between consecutive tasks (e.g., if set to 1 and shape_dotsB_D.txt is uncommented, the program will run this task and the next one. If set to 9, all tasks will be run). Internally, this will result in regenerating a new config file after each experiment is completed, with a previously selected filename commented and the subsequent filename selected for the upcoming experiment.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
4. Goggles limiting vision
<ol>
	<li>To transiently remove the peripheral visual field, use swimming goggles (Figure 2), where transparent lenses are replaced with white opaque ones. The lenses had an aperture of 1.4 mm that limited the visual field to the central 10&#176;. To make the goggles suitable for every subject and to account as best as possible for the natural individual interocular distance, make 14 pairs of goggles with holes spacing from 58 mm to 72 mm (with a step of 1 mm between each pair of goggles).</li>
</ol>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/66272/66272fig2.jpg" /> 
Figure 2: Narrowing goggles. The central holes have a diameter of 1.4 mm. We had 14 pairs of goggles with distances between holes of 58 mm to 72 mm. <a href="https://www.jove.com/files/ftp_upload/66272/66272fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="2">
	<li>Use a ruler to define the distance between the participant&#8217;s eyes. Place the ruler just above the eyes, in line with the eyebrows, with the value 0 on top of one eye. Calculate how far in mm, is the second pupil by checking the value on top of the second eye. During the procedure, ask the participant to maintain the gaze as stable as possible.</li>
	<li>After the more suitable pair has been chosen, give a break of 15 min. During this time, ask the participants to move freely in the room, use their telephone, or read to let the eyes become accustomed to the new visual condition.&#160;</li>
	<li>Start the procedure again from step 3.&#160;&#160;</li>
</ol>
5. Reconfiguration
<ol>
	<li>Screen size and distance calibration
	<ol>
		<li>If a different display is being used, insert the screen dimensions (resolution and diagonal) into the config file (resolution_v for vertical resolution, resolution_h for horizontal resolution, diagonal_inch for the screen diagonal in inches).&#160;</li>
		<li>Run Viscacha2.jar. Once the initial screen displays, press ESC to terminate. Open the .csv file containing the results.&#160;</li>
		<li>Find the line containing Distance mm text and write down the value.&#160;</li>
		<li>Readjust the experimental setup so that the subject can be seated at the newly calculated distance. Calculate the distance so that the screen width occupies 44.6&#176; of visual space horizontally. This is defined by the full_angle_h parameter, which can also be changed in the config.txt file. 
		NOTE: Calibration can be also performed for screen height using the full_angle_v parameter. Please note that only one of these parameters can be set, the other one has to be commented with a # prefix.&#160;&#160;</li>
	</ol>
	</li>
	<li>Stimuli definition&#160;
	<ol>
		<li>Define the stimuli parameters in separate files (e.g., shape_dotsB_C.txt). Some values, such as dimensions of the S- (Ellipse_X, Ellipse_Y) are given in pixels. To calculate from pixels to visual degrees, multiply the value by the Pixel to angle multiplier extracted from the csv file containing results.&#160; 
		NOTE:&#160; Stimuli parameters, such as the coherence of the dots are predefined and adjustable for each layer (background, shape S+, shape S-, noise). In the coherence task, for example, the circle and the ellipse consist of dots moving randomly with a velocity of 10&#176;/s (coherence = 0.0). The background is built of dots moving coherently upward with the same velocity as in the circle and ellipse (coherence = 1.0). Viscacha2 does not have an official user manual as of yet. For further information regarding the stimuli definition refer to the stimuli_description.ods file in the Viscacha2 repository.</li>
	</ol>
	</li>
</ol>

Assessing Vision via Shape Recognition in Random Dot Kinematograms

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The authors have nothing to disclose.

Here, a novel method is described for measuring visual motion acuity using a set of stimuli based on random dot kinematograms. The result is given as a minimal perceived difference between a circle and an ellipse, and it allows one to see when the subject stopped distinguishing shapes from each other. The smaller the difference achieved, the better acuity: it means that the subject can still detect where the circle is, even though it is almost identical to the ellipse. The motion-acuity test presented here brings the res...

<a href="https://app.jove.com/t/6597">This corrects</a> the article <a href="https://dx.doi.org/10.3791/66272">10.3791/66272</a>

An erratum was issued for: <a href="https://www.jove.com/t/66272">Motion-Acuity Test for Visual Field Acuity Measurement with Motion-Defined Shapes</a>. The Authors section was updated.

Erratum: Motion-Acuity Test for Visual Field Acuity Measurement with Motion-Defined Shapes

Most of the available visual tests are directed to examine the features processed by central vision, relying on the input deriving from the central retina1. The central retina has the densest cone-photoreceptor population for maximal visual acuity and lacks rod photoreceptors, which dominate the peripheral retina2. The presence of densely packed photoreceptors is also reflected in an increased density of ganglion cells, which means a greater number of axons are directed to the optic nerve and, eventually, to the visual cortex. Outside the fovea towards the periphery, rods outnumber the cone photoreceptor3. With the rods&#39; wider bodies and the sparser mosaic of photoreceptors, the peripheral retina is primarily responsive to night vision and motion awareness4.
Classically, it was believed that visual processing, depending on stimulation of the central part of the visual field, is devoted to the fine analysis of stationary objects, and its peripheral part is specialized in detecting motion and bringing objects to the central, foveal vision, where it is further analyzed5,6. However, now we have emerging evidence showing that on the cortical level, the fine analysis of the stationary pathway is not fully separated from the motion-sensitive one6,7,8. Testing form and motion perception simultaneously is classically performed using moving gratings9 and glass patterns10 and also concentric rings motion11. Our goal is to introduce a test that is close to the normal life of visually disabled people, which can lower their frustrations and give hope by explicitly showing them that some features of their visual processing might still be preserved and even strengthened. The proposed motion-acuity test based on random dot kinematograms (RDKs) combines motion and shape perception analysis and simultaneously tests the functioning of the motion and shape perception. Within the motion-acuity test, there are many possibilities of psychophysical features to test, such as different velocities, directions, and contrasts of the RDKs. By changing the parameters, we can manipulate the strength of stimulation, either specific for the central processing or peripheral. For example, detecting fast-moving objects is a well-described feature specific to peripheral visual processing12, whereas the processing of the darks on the bright background is preferentially processed by central vision13. This test was initially performed on patients with retinal degeneration of photoreceptors, either specifically located within the central or peripheral retina14. Retinitis pigmentosa (RP) is manifested with peripheral damage and prevails in ~1/5000 patients worldwide15. Stargardt disease (STGD), with a prevalence of ~1/10000, is the most common cause of juvenile macular degeneration (MD)16. Damage to the photoreceptors at the central retina, as in macular degeneration or as in retinitis pigmentosa at the peripheral retina, results in corresponding visual field losses. Those visual field losses are reflected in the impairments of the features specific to the given visual system regions17. Importantly, the regions of the visual system that receive inputs from unaffected parts of the retina are also affected. It was previously shown in animal models of macular degeneration18 that after binocular central retinal damage, not only is acuity aggravated, but motion perception, a feature characteristic of peripheral processing, is reinforced. The motion-acuity testing described here provides an important insight for planning visual rehabilitation procedures. A complete view of the interplay between central and peripheral parts of the visual field has a crucial role in understanding how lost functions might be taken over by the spare parts of the visual system and how this process can be supported by visual training rehabilitation procedures. Inline, the knowledge of how regional retinal degeneration affects visual processing, especially beyond its damaged parts, still remains incomplete. Optical tests are based on the measurements of the stationary shape features. For instance, the visual acuity measurements rely on stationary stimuli, either letters (Snellen charts), grating charts, or vernier acuity charts.
For the purpose of widening the insight into the dynamics between central and peripheral vision in healthy eyes and eyes that have impaired central/peripheral visual functions, a motion-based acuity test measuring the shape and motion perception simultaneously was introduced. The motion-acuity test is based on the detection of centrally located shapes in negative or positive contrast (dark or light dots), an ellipse and circle with matching surfaces, built from random dot kinematograms (RDK) and separated from the same RDK background by velocity, coherence, or direction. Acuity is measured as the minimal difference perceived between circle and ellipse dimensions, and the results are given in visual degrees at which the subject stops to perceive the difference. Additionally, to check if the luminance contrast influences the measured motion acuity, stimuli can be presented in negative (black dots on white background) or in positive contrast (white dots on black background). All the available information about positive contrast (ON type) and negative contrast (OFF type) processing in the visual system comes from the stationary stimulation of the central visual field19,20. But how peripheral processing of motion signals depends on contrast remains fairly unknown14,21. It was only established that sensitivity to high velocities is specific for peripheral processing, whereas central motion processing engages slow velocities at higher spatial frequencies presented in positive contrast (ON type)12. The positive and negative contrast versions of the motion-acuity stimuli, as well as the ability to modify the velocity of dots, as well as the coherence or direction, is crucial for a more detailed description of the full visual field. Additionally, a mechanical narrowing of the visual field to central 10 degrees is proposed using goggles with lenses replaced with opaque ones with centrally located holes. This easily replicable narrowing system, suitable for fMRI and TMS protocols, allows further investigations of the functions of the peripheral visual input and how visual peripheries influence centrally measured acuity. A similar system was initially validated in previous studies14, in which it was found that motion acuity tests in negative contrast and in fast motion, strongly activating visual peripheries, are the most difficult for all participants. For patients with Stargardt disease, they were unmanageable. Importantly, attenuation of visual periphery stimulation, by diminishing the velocity of RDKs, improves acuity thresholds in all tested subjects. In conclusion, we propose the task with motion-acuity measurement based on simple shape discrimination. Therefore, the results are straightforward and easy to understand also for patients and their caregivers. The motion-acuity test presented here is also addressed for users outside academia. The task is easy to explain to a broad range of ages and patient groups.

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motion-acuity test for visual field acuity measurement with motion-defined shapes

The standard visual acuity measurements rely on stationary stimuli, either letters (Snellen charts), vertical lines (vernier acuity) or grating charts, processed by those regions of the visual system most sensitive to the stationary stimulation, receiving visual input from the central part of the visual field. Here, an acuity measurement is proposed based on discrimination of simple shapes, that are defined by motion of the dots in the random dot kinematograms (RDK) processed by visual regions sensitive to motion stimulation and receiving input also from the peripheral visual field. In the motion-acuity test, participants are asked to distinguish between a circle and an ellipse, with matching surfaces, built from RDKs, and separated from the background RDK either by coherence, direction, or velocity of dots. The acuity measurement is based on ellipse detection, which with every correct response becomes more circular until reaching the acuity threshold. The motion-acuity test can be presented in negative contrast (black dots on white background) or in positive contrast (white dots on black background). The motion defined shapes are located centrally within 8 visual degrees and are surrounded by RDK background. To test the influence of visual peripheries on centrally measured acuity, a mechanical narrowing of the visual field to 10 degrees is proposed, using opaque goggles with centrally located holes. This easy and replicable narrowing system is suitable for MRI protocols, allowing further investigations of the functions of the peripheral visual input. Here, a simple measurement of shape and motion perception simultaneously is proposed. This straightforward test assesses vision impairments depending on the central and peripheral visual field inputs. The proposed&#160;motion-acuity test advances the capability of standard tests to reveal spare or even strengthened vision functions in patients with injured visual system, that until now remained undetected.

The motion acuity task generates, for each participant, one result file for each stimuli procedure. An exemplary log file for a test participant has been included in the repository inside the doc folder. From row 1 to row 31, various settings are reported, such as the name of the patient and the configuration settings. The task block starts from row 34 and reports important information necessary for further analysis: event time, event type, trial, duration, selection, correct, success, experimenter, external stimuli, rev...

Watch this Scientific Journal Video about Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing at JoVE.com

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

A novel motion-based acuity test that allows the assessment of central and peripheral visual processing in low-vision and healthy individuals, along with goggles limiting peripheral vision compatible with MRI protocols, are described here. This method offers a comprehensive vision assessment for functional impairments and dysfunctions of the visual system.

Motion-Acuity Test for Visual Field Acuity Measurement with Motion-Defined Shapes

The standard visual acuity measurements rely on stationary stimuli, either letters (Snellen charts), vertical lines (vernier acuity) or grating charts, ...

motion-acuity-test-for-visual-field-acuity-measurement-with-motion

Research

JoVE Journal

Neuroscience

470 Views.  Polish Academy of Sciences. A novel motion-based acuity test that allows the assessment of central and peripheral visual processing in low-vision and healthy individuals, along with goggles limiting peripheral vision compatible with MRI protocols, are described here. This method offers a comprehensive vision assessment for functional impairments and dysfunctions of the visual system.

Video: Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Double Fluorescence in situ Hybridization in Fresh Brain Sections

Here we describe a modified version of a double fluorescence in situ hybridization (dFISH) method optimized for detecting two mRNAs of interest in fresh frozen brain sections. Our group has successfully used this approach to study gene co-regulation. More specifically, we have used this dFISH method to explore the anatomical organization, neurochemical properties, and the impact of sensory experience in central sensory circuits, at single cell resolution. This protocol has been validated in brain tissue from mice, rats and songbirds but is expected to be easily adaptable to other vertebrate species, as well as to an array of non-neural tissues. In this film we provide a detailed demonstration of the main steps of this procedure.

Double Fluorescence in situ Hybridization in Fresh Brain Sections

This protocol involves a non-radioactive in-situ hybridization procedure that enables the simultaneous identification of two transcript species, at a single cell resolution, in thin sections of the vertebrate brain.

Here we describe a modified version of a double fluorescence in situ hybridization (dFISH) method optimized for detecting two mRNAs of interest in fresh ...

One Dimensional Turing-Like Handshake Test for Motor Intelligence

In the Turing test, a computer model is deemed to "think intelligently" if it can generate answers that are not distinguishable from those of a human. However, this test is limited to the linguistic aspects of machine intelligence. A salient function of the brain is the control of movement, and the movement of the human hand is a sophisticated demonstration of this function. Therefore, we propose a Turing-like handshake test, for machine motor intelligence. We administer the test through a telerobotic system in which the interrogator is engaged in a task of holding a robotic stylus and interacting with another party (human or artificial). Instead of asking the interrogator whether the other party is a person or a computer program, we employ a two-alternative forced choice method and ask which of two systems is more human-like. We extract a quantitative grade for each model according to its resemblance to the human handshake motion and name it "Model Human-Likeness Grade" (MHLG). We present three methods to estimate the MHLG. (i) By calculating the proportion of subjects' answers that the model is more human-like than the human; (ii) By comparing two weighted sums of human and model handshakes we fit a psychometric curve and extract the point of subjective equality (PSE); (iii) By comparing a given model with a weighted sum of human and random signal, we fit a psychometric curve to the answers of the interrogator and extract the PSE for the weight of the human in the weighted sum. Altogether, we provide a protocol to test computational models of the human handshake. We believe that building a model is a necessary step in understanding any phenomenon and, in this case, in understanding the neural mechanisms responsible for the generation of the human handshake.

We present a Turing-like Handshake test administered through a telerobotic system in which the interrogator is holding a robotic stylus and interacting with another party (human or artificial). We use a forced choice method, and extract a measure for the similarity of the artificial model to a human handshake.

In the Turing test, a computer model is deemed to "think intelligently" if it can generate answers that are not distinguishable from those of a human.  ...

Cut-loading: A Useful Tool for Examining the Extent of Gap Junction Tracer Coupling Between Retinal Neurons

In addition to chemical synaptic transmission, neurons that are connected by gap junctions can also communicate rapidly via electrical synaptic transmission. Increasing evidence indicates that gap junctions not only permit electrical current flow and synchronous activity between interconnected or coupled cells, but that the strength or effectiveness of electrical communication between coupled cells can be modulated to a great extent1,2. In addition, the large internal diameter (~1.2 nm) of many gap junction channels permits not only electric current flow, but also the diffusion of intracellular signaling molecules and small metabolites between interconnected cells, so that gap junctions may also mediate metabolic and chemical communication. The strength of gap junctional communication between neurons and its modulation by neurotransmitters and other factors can be studied by simultaneously electrically recording from coupled cells and by determining the extent of diffusion of tracer molecules, which are gap junction permeable, but not membrane permeable, following iontophoretic injection into single cells. However, these procedures can be extremely difficult to perform on neurons with small somata in intact neural tissue.
Numerous studies on electrical synapses and the modulation of electrical communication have been conducted in the vertebrate retina, since each of the five retinal neuron types is electrically connected by gap junctions3,4. Increasing evidence has shown that the circadian (24-hour) clock in the retina and changes in light stimulation regulate gap junction coupling3-8. For example, recent work has demonstrated that the retinal circadian clock decreases gap junction coupling between rod and cone photoreceptor cells during the day by increasing dopamine D2 receptor activation, and dramatically increases rod-cone coupling at night by reducing D2 receptor activation7,8. However, not only are these studies extremely difficult to perform on neurons with small somata in intact neural retinal tissue, but it can be difficult to adequately control the illumination conditions during the electrophysiological study of single retinal neurons to avoid light-induced changes in gap junction conductance.
Here, we present a straightforward method of determining the extent of gap junction tracer coupling between retinal neurons under different illumination conditions and at different times of the day and night. This cut-loading technique is a modification of scrape loading9-12, which is based on dye loading and diffusion through open gap junction channels. Scrape loading works well in cultured cells, but not in thick slices such as intact retinas. The cut-loading technique has been used to study photoreceptor coupling in intact fish and mammalian retinas7, 8,13, and can be used to study coupling between other retinal neurons, as described here.

An easy and convenient method to determine the extent of gap junction tracer coupling between retinal neurons is described. This technique enables one to investigate the function of the electrical synapses between neurons in the intact retina under different illumination conditions and at different times of the day and night.

In addition to chemical synaptic transmission, neurons that are connected by gap junctions can also communicate rapidly via electrical synaptic ...

Transretinal ERG Recordings from Mouse Retina: Rod and Cone Photoresponses

There are two distinct classes of image-forming photoreceptors in the vertebrate retina: rods and cones. Rods are able to detect single photons of light whereas cones operate continuously under rapidly changing bright light conditions. Absorption of light by rod- and cone-specific visual pigments in the outer segments of photoreceptors triggers a phototransduction cascade that eventually leads to closure of cyclic nucleotide-gated channels on the plasma membrane and cell hyperpolarization. This light-induced change in membrane current and potential can be registered as a photoresponse, by either classical suction electrode recording technique1,2 or by transretinal electroretinogram recordings (ERG) from isolated retinas with pharmacologically blocked postsynaptic response components3-5. The latter method allows drug-accessible long-lasting recordings from mouse photoreceptors and is particularly useful for obtaining stable photoresponses from the scarce and fragile mouse cones. In the case of cones, such experiments can be performed both in dark-adapted conditions and following intense illumination that bleaches essentially all visual pigment, to monitor the process of cone photosensitivity recovery during dark adaptation6,7. In this video, we will show how to perform rod- and M/L-cone-driven transretinal recordings from dark-adapted mouse retina. Rod recordings will be carried out using retina of wild type (C57Bl/6) mice. For simplicity, cone recordings will be obtained from genetically modified rod transducin &alpha;-subunit knockout (T&alpha;-/-) mice which lack rod signaling8.

We describe a relatively simple method of transretinal electroretinogram (ERG) recordings for obtaining rod and cone photoresponses from intact mouse retina. This approach takes advantage of the block of synaptic transmission from photoreceptors to isolate their light responses and record them using field electrodes placed across the isolated flat-mounted retina.

There are two distinct classes of image-forming photoreceptors in the vertebrate retina: rods and cones. Rods are able to detect single photons of light ...

Single Cell Measurement of Dopamine Release with Simultaneous Voltage-clamp and Amperometry

After its release into the synaptic cleft, dopamine exerts its biological properties via its pre- and post-synaptic targets1. The dopamine signal is terminated by diffusion2-3, extracellular enzymes4, and membrane transporters5. The dopamine transporter, located in the peri-synaptic cleft of dopamine neurons clears the released amines through an inward dopamine flux (uptake). The dopamine transporter can also work in reverse direction to release amines from inside to outside in a process called outward transport or efflux of dopamine5. More than 20 years ago Sulzer et al. reported the dopamine transporter can operate in two modes of activity: forward (uptake) and reverse (efflux)5. The neurotransmitter released via efflux through the transporter can move a large amount of dopamine to the extracellular space, and has been shown to play a major regulatory role in extracellular dopamine homeostasis6. Here we describe how simultaneous patch clamp and amperometry recording can be used to measure released dopamine via the efflux mechanism with millisecond time resolution when the membrane potential is controlled. For this, whole-cell current and oxidative (amperometric) signals are measured simultaneously using an Axopatch 200B amplifier (Molecular Devices, with a low-pass Bessel filter set at 1,000 Hz for whole-cell current recording). For amperometry recording a carbon fiber electrode is connected to a second amplifier (Axopatch 200B) and is placed adjacent to the plasma membrane and held at +700 mV. The whole-cell and oxidative (amperometric) currents can be recorded and the current-voltage relationship can be generated using a voltage step protocol. Unlike the usual amperometric calibration, which requires conversion to concentration, the current is reported directly without considering the effective volume7. Thus, the resulting data represent a lower limit to dopamine efflux because some transmitter is lost to the bulk solution.

The amperometric technique measures dopamine release from a single cell by detecting the oxidative current produced by spontaneous dopamine oxidization. Simultaneous voltage clamp and amperometry methodology reveal the mechanistic relationship between the overall "activity" of dopamine transporter and the regulatory role of this activity on the reverse transport of dopamine.

After its release into the synaptic cleft, dopamine exerts its biological properties via its pre- and post-synaptic targets1. The dopamine signal is ...

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish

Zebrafish are a proven model for vision research, however many of the earlier methods generally focused on larval fish or demonstrated a simple response. More recently adult visual behavior in zebrafish has become of interest, but methods to measure specific responses are new coming. To address this gap, we set out to develop a methodology to repeatedly and accurately utilize the optokinetic response (OKR) to measure visual acuity in adult zebrafish. Here we show that the adult zebrafish's visual acuity can be measured, including both binocular and monocular acuities. Because the fish is not harmed during the procedure, the visual acuity can be measured and compared over short or long periods of time. The visual acuity measurements described here can also be done quickly allowing for high throughput and for additional visual procedures if desired. This type of analysis is conducive to drug intervention studies or investigations of disease progression.

Zebrafish have been a valuable tool for many research areas. Here we demonstrate a method to elicit a visual response and calculate a functional visual acuity in the adult zebrafish.

Zebrafish are a proven model for vision research, however many of the  earlier methods generally focused on larval fish or demonstrated a simple  ...

A Simple Behavioral Assay for Testing Visual Function in Xenopus laevis

Measurement of the visual function in the tadpoles of the frog, Xenopus laevis, allows screening for blindness in live animals. The optokinetic response is a vision-based, reflexive behavior that has been observed in all vertebrates tested. Tadpole eyes are small so the tail flip response was used as alternative measure, which requires a trained technician to record the subtle response. We developed an alternative behavior assay based on the fact that tadpoles prefer to swim on the white side of a tank when placed in a tank with both black and white sides. The assay presented here is an inexpensive, simple alternative that creates a response that is easily measured. The setup consists of a tripod, webcam and nested testing tanks, readily available in most Xenopus laboratories. This article includes a movie showing the behavior of tadpoles, before and after severing the optic nerve. In order to test the function of one eye, we also include representative results of a tadpole in which each eye underwent retinal axotomy on consecutive days. Future studies could develop an automated version of this assay for testing the vision of many tadpoles at once.

A Simple Behavioral Assay for Testing Visual Function in Xenopus laevis

Xenopus laevis tadpoles prefer swimming on the white side of a black/white tank. This behavior is guided by their vision. Based on this behavior, we present a simple assay to test the visual function of tadpoles.

Measurement of the visual function in the tadpoles of the frog, Xenopus laevis, allows screening for blindness in live animals. The optokinetic response ...

Simultaneous ex vivo Functional Testing of Two Retinas by in vivo Electroretinogram System

An In vivo electroretinogram (ERG) signal is composed of several overlapping components originating from different retinal cell types, as well as noise from extra-retinal sources. Ex vivo ERG provides an efficient method to dissect the function of retinal cells directly from an intact isolated retina of animals or donor eyes. In addition, ex vivo ERG can be used to test the efficacy and safety of potential therapeutic agents on retina tissue from animals or humans. We show here how commercially available in vivo ERG systems can be used to conduct ex vivo ERG recordings from isolated mouse retinas. We combine the light stimulation, electronic and heating units of a standard in vivo system with custom-designed specimen holder, gravity-controlled perfusion system and electromagnetic noise shielding to record low-noise ex vivo ERG signals simultaneously from two retinas with the acquisition software included in commercial in vivo systems. Further, we demonstrate how to use this method in combination with pharmacological treatments that remove specific ERG components in order to dissect the function of certain retinal cell types.

Simultaneous ex vivo Functional Testing of Two Retinas by in vivo Electroretinogram System

Ex vivo ERG can be used to record electrical activity of retinal cells directly from isolated intact retinas of animals or humans. We demonstrate here how common in vivo ERG systems can be adapted for ex vivo ERG recordings in order to dissect the electrical activity of retinal cells.

An In vivo electroretinogram (ERG) signal is composed of several overlapping components originating from different retinal cell types, as well as noise ...

Partial Optic Nerve Transection in Rats: A Model Established with a New Operative Approach to Assess Secondary Degeneration of Retinal Ganglion Cells

Previous studies have shown that the secondary degeneration of retinal ganglion cells (RGCs) occurs commonly in glaucoma. Partial optic nerve transection is considered a useful and reproducible model. Compared with other optic nerve injury models used commonly for assessing secondary degeneration, e.g. complete optic nerve transection and optic nerve crush models, the partial optic nerve transection model is superior as it distinguishes primary from secondary degeneration in situ. Therefore, it serves as an excellent tool for evaluating secondary degeneration. This study describes a novel operative approach of partial optic nerve transection by directly accessing the area of the retrobulbar optic nerve through the orbital lateral wall of the eyeball. Moreover, we present a newly designed, low cost surgical instrument to assist with transection. As demonstrated by the representative results in distinguishing the boundary of primary and secondary injury areas, the new approach and instrument ensures high efficiency and stability of the model by providing adequate space for surgical operation. This in turn makes it easy to separate the meningeal sheath and ophthalmic vessels from the optic nerve before transection. An additional benefit is that this space-saving operative approach improves the investigators&#39; ability to administer drugs, carriers, or selective RGC tracers to the stump of the partially transected optic nerve, allowing the exploration of mechanisms behind secondary injury in RGCs, in a new way.

Secondary degeneration of retinal ganglion cells (RGCs) occurs commonly in glaucoma. This study describes an innovative operative approach for partial optic nerve transection. The use of this space-saving operative approach extends the model's application range, and allows exploration of secondary injury mechanisms in RGCs in a new way.

Previous studies have shown that the secondary degeneration of retinal ganglion cells (RGCs) occurs commonly in glaucoma. Partial optic nerve transection ...

Evaluation of Hemisphere Lateralization with Bilateral Local Field Potential Recording in Secondary Motor Cortex of Mice

This article demonstrates complete, detailed procedures for both in vivo bilateral recording and analysis of local field potential (LFP) in the cortical areas of mice, which are useful for evaluating possible laterality deficits, as well as for assessing brain connectivity and coupling of neural network activities in rodents. The pathological mechanisms underlying Alzheimer&#39;s disease (AD), a common neurodegenerative disease, remain largely unknown. Altered brain laterality has been demonstrated in aging people, but whether or not abnormal lateralization is one of the early signs of AD has not been determined. To investigate this, we recorded bilateral LFPs in 3-5-month-old AD model mice, APP/PS1, together with littermate wild type (WT) controls. The LFPs of the left and right secondary motor cortex (M2), specifically in the gamma band, were more synchronized in APP/PS1 mice than in WT controls, suggesting a declined hemispheric asymmetry of bilateral M2 in this AD mouse model. Notably, the recording and data analysis processes are flexible and easy to carry out, and can also be applied to other brain pathways when conducting experiments that focus on neuronal circuits.

We present in vivo electrophysiological recording of the local field potential (LFP) in bilateral secondary motor cortex (M2) of mice, which can be applied to evaluate hemisphere lateralization. The study revealed altered levels of synchronization between the left and right M2 in APP/PS1 mice compared to WT controls.

This article demonstrates complete, detailed procedures for both in vivo bilateral recording and analysis of local field potential (LFP) in the cortical ...