This work was supported in part by a CAREER award from the National Science Foundation (BES-0447713) and from a grant from Essilor, International.

An overview of the key elements needed to conduct an oculomotor experiment is shown in figure 1. Each block in the flow chart will be discussed in detail below.

1. 	INSTRUMENTATION SET-UP:
<ol>
<li>Any type of eye movement monitor can be used for this system. We will demonstrate an infrared limbus tracking and a video monitoring system.</li>
<li>For tandem tracking movements such as saccadic or smooth pursuit, a single computer can be used for the visual display. To study opposing eye movements such as vergence or the interaction of vergence with tandem version movements (ie, vergent with saccadic stimuli) a haploscope is needed with two computer monitors for visual display, see figure 2.</li>
</ol>
2. 	CALIBRATION:
<ol>
<li>Calibration is needed to convert one set of metrics into another. Eye movements are typically indicated in degrees (&deg;) of rotation shown in figure 3. However, computer monitors use pixel values compared to vision researchers who often denote the visual stimuli in degrees. Hence, a conversion is needed to convert the pixel values to degrees. One can use trigonometry to calculate where to place the physical targets to calibrate the visual displays. For example, if the stimulus on the computer screen aligns with a 2&deg; physical target (see figure 2) then that pixel value corresponds to a 2&deg; stimulus.</li>
<li>To calibrate the system, the operator needs to open Pixel2Deg.vei within the VisualEyes directory. First, define the monitor to calibrate using the stretch mode field. Enter number 1 for the left eye monitor and number 2 for the right eye monitor. Then, run the program and move the green line stimulus until the green line is superimposed on top of the physical target. Enter the known position of the physical target in degrees and press the save button. Then, click on the green line. The degree and pixel value will be shown on the display in the bottom left corner. The operator should collect a minimum of three calibration points.</li>
<li>After saving all the calibration points, open the D2P output file in the VisualEyes directory to obtain the calibration points. Plot the calibration points to attain a linear regression equation. Use the equation to calculate the initial and final position of the visual stimulus the operator desires to program in pixel values. An example of the left eye and right eye calibration curve obtained using five calibration points for a vergence stimulus is shown in figure 4.</li>
<li>Repeat steps 2.2 and 2.3 for the other monitor if the stimulus requires an additional monitor.</li>
</ol>
3. 	VISUALEYES SOFTWARE:
<ol>
<li>Define A Stimulus: The operator needs to define the initial and final position of left and right eye stimulus prior to the experiment. First, open a new text file and on the first row, define the initial time and position values of the stimulus. Four parameters need to be defined 1) time (seconds), 2) the horizontal position (pixel), 3) the vertical position (pixel), and 4) the rotation (&deg;) separated by a tab. Likewise, define the four parameters of the final time and position of the stimulus. Save the stimulus in the VisualEyes directory as a stimulus_name.vei (VEI=VisualEyes Input) file and repeat this step for the other eye stimulus.
<ol>
<li>The movement of the stimulus can be generalized into two types of movement: an abrupt step or a continuous ramp. A step allows the stimulus to abruptly move or jump from the initial position to the final position. The operator should note that the change in time is 0.001 seconds for a step stimulus. In the next row, define how long you want the stimulus to reside in the initial position as well as the final position. Stimuli are defined using four fields within one row. An example of a saccadic step, smooth pursuit ramp, vergent step and vergent ramp are shown in Table 1.</li>
<li>For stimuli, you can have a single stimulus such as a step or a sequence of visual tasks such as a multiple steps.</li>
</ol>
</li>
<li>Save Stimulus into Stimuli Library: There are several default settings in the dc1.txt (left eye stimulus / monitor) and dc2.txt (right eye stimulus / monitor) files within the VisualEyes directory. The first line is the percentage of the screen within the horizontal direction. The second line is the percentage of the screen within the vertical direction. The third is the background image and the fourth is the foreground or target image. The fifth line indicates the computer to work in independent mode. The 6th signifies which monitor (1 is right eye and 2 is left eye). The 7th line is the aspect ratio of the monitors. The rest of the lines are the different type of stimuli the operator can use within an experimental session. 
<ol>
<li>Open the dc1.txt and dc2.txt from the VisualEyes directory. These two files contain the library stimuli for left eye and right eye respectively. On the last row, write the file name of the stimulus that has been generated from step 3.1. The profile number refers to the mth row corresponding to the stimulus file name. For example, in figure 1, the profile number of the stimulus is 8.</li>
</ol>
</li>
<li>One can repeat steps 3.1 to 3.2 to create as many stimuli that are needed for an experiment.</li>
<li>Write Script for the Experimental Protocol: Open a text file to type the experimental protocol commands. This file is called the script file which signifies that the VisualEyes System will read and execute each command from the script found in this file. The ability to create a script file for an experimental protocol allows the user to conduct repeated experimental sessions using the same protocol. Furthermore, numerous scripts can be written to vary the type and sequence of experimental commands. This file can be saved into the VisualEyes directory as a script_name.ves file. (VES = VisualEyes Script)
<ol>
<li>The VisualEyes functions have input and output arguments. Table 2 shows all the functions in the VisualEyes software.
<ol>
<li>ExpTrial: This function is used to call the stimulus that has been saved in the stimulus library from step 3.2. The length of the data is the time it will allow the function to execute the stimulus. The tempfile.lwf allows the VisualEyes software to temporarily store the incoming data and output it into an output buffer. When the tempfile.lwf is not defined, during the execution of this function, it will not store any incoming data for digitization.</li>
<li>LogFile: This function outputs strings or the input buffer defined from ExpTrial into the out.txt file in the VisualEyes directory. When the experiment is complete, the operator must change the name of the out.txt file to another name. Otherwise, the data will be overwritten during the next experiment.</li>
<li>TriggerWait: This function waits for the subject to push a trigger button to start the ExpTrial and digitize the data. This is a channel in on the digital acquisition card that is waiting for the signal to change from a digital high (5 V) to low (0 V).</li>
<li>RandomDelay: This function generates a random delay to prevent prediction or anticipation of the next stimulus.</li>
<li>WaveMSD: This function calculates the mean and standard deviation of the data.</li>
</ol>
</li>
</ol>
</li>
</ol>
4. 	PLACE THE EYE MOVEMENT MONITOR &amp; RUN EXPERIMENT:
<ol>
<li>Different eye movement monitors such as the corneal reflection video imaging system, limbus tracking system or sclera search coil may be used to collect and record eye movements.</li>
<li>Before a subject can participate, the experiment must be explained and the subject must read and sign an informed consent form approved by the Institutional Review Board.</li>
<li>The operator must adjust the eye movement monitor on the subject. First, the subject is asked to fixate on a target. The operator adjusts the eye movement monitor to capture the anatomical attributes of the eye such as the limbus (boundary between the iris and sclera) or the pupil and corneal reflection depending on the eye movement monitor used.</li>
<li>Once the eye movement monitor is properly adjusted on the subject, the operator should validate that the eye movement monitor is capturing the eye movements by asking the subject to make vergent or saccadic movements.</li>
<li>Open the program ReadScript.vei in the VisualEyes directory. On the upper right corner, type in the file name of the experimental protocol script file created from step 3.4. Then, run the ReadScript.vei program by pushing the red arrow on top left corner.</li>
<li>Give the subject the trigger button and explain that when the subject pushes the button, the data collection will begin. Another Acquire.vei file will automatically appear on the screen which will plot the incoming data. Data are sampled at 500Hz.</li>
<li>When the experiment is complete, the ReadScript.vei will automatically stop. At this time, go into the VisualEyes directory and find the Out1.txt file. Rename the file otherwise the next time the operator runs the experiment, the data file will be overwritten.</li>
</ol>
5. 	OFF-LINE DATA ANALYSIS:
<ol>
<li>The operator can analyze the data by using different software packages (ie MatLab or Excel). Latency, peak velocity, or amplitude may be of interest depending on the study.
<ol>
<li>An example of a Matlab analysis code is provided in the VisualEyes directory to plot saccades, vergence steps and vergence ramps. Examples of the ensemble saccade, vergence step and vergence ramp position traces with the corresponding velocity responses are shown in figure 5.</li>
</ol>
</li>
</ol>
6. Representative Results: 
Examples of the ensemble of eye movements recorded using the VisualEyes System is shown in Figure 5. Typical 10&deg; saccadic movements are shown in plot 4A. Antisaccades are saccadic responses when the subject is told to make a saccade in the opposite direction of the visual stimulus and are shown in plot 4B. This is a more cognitively demanding task; hence one can observe that the latency or the time to begin the movement is longer for antisaccades (plot 4B) compared to saccades towards a visual stimulus also called prosaccades (plot 4A). Vergence responses to 4&deg; steps are shown in plot 4C and vergence responses to 5 &deg;/s ramps stimuli are shown in plot 4D. Each trace is an individual eye movement where the upper row is position denoted in degrees as a function of time. Eye movements are calibrated in the units of degrees, meter angles, or prism diopters. Our research uses degree of rotation. The bottom row is the velocity plotted in &deg;/ s as a function of time and is the speed of the movement. The scale for each ensemble data differs depending on the movement.
<img src="/files/ftp_upload/2530/2530fig1.jpg" alt="Figure 1" /> 
Figure 1. Flow chart of key elements to conduct an oculomotor experiment. Examples of steps needed to generate a stimulus using the VisualEyes software and conduct an experiment for offline data analysis are shown. Part A shows the Pixel2Deg.vei window. Part B demonstrates the four parameters needed to define a stimulus. Part C is the stimuli library where the black text lines within the stimulus library are example stimuli files and the red text defines each line. Part D is an example of an experimental script protocol.
<img src="/files/ftp_upload/2530/2530fig2.jpg" alt="Figure 2" /> 
Figure 2. VisualEyes System Haploscope Experimental Set-Up. Three CRT monitors are used: 1) A control panel is needed to view stimuli and responses 2) a CRT monitor for the right eye (RE) visual stimuli and 3) a CRT monitor the left eye (LE) visual stimuli. A half-silvered mirror is placed 30 cm away from the two visual stimuli CRT monitors. This is to insure that the stimuli on the CRT monitors are projected onto the half silvered mirror (50% transmission and 50% reflectance mirror). The mirror allows the subject to view stimuli from the computer screens superimposed onto targets located at measured distances from the subject which is needed for calibration. With a haploscope, the accommodation demand to both eyes is held constant. The distance between the subject's eyes and the mirror is 10 cm. The system can be adjusted to accommodate different inter-pupillary distances (IPD) but for this demonstration we will assume the IPD to be 6 cm.
<img src="/files/ftp_upload/2530/2530fig3.jpg" alt="Figure 3" /> 
Figure 3. Calculations of Saccadic (left) and Vergent (right) movement from targets A to B are shown. IPD is the inter-pupillary distance.
<img src="/files/ftp_upload/2530/2530fig4.jpg" alt="Figure 4" /> 
Figure 4. Calibration curve of the left eye (top plot) and right eye (bottom plot) stimulus. A similar procedure would be conducted for saccadic or smooth pursuit stimuli.
<img src="/files/ftp_upload/2530/2530fig5.jpg" alt="Figure 5" /> 
Figure 5. Examples of saccades (A) antisaccades (B), vergence steps (C) and vergence ramps (D) using the VisualEyes system and analyzed using a custom MATLAB program. Ensemble position traces (&deg; as a function of time in sec) are plotted in the upper row where each colored line represents a different eye movement. The corresponding velocity traces (&deg;/s as a function of time in sec).
<table border="1">
<tbody>
 <tr>
 <td>Stimulus Type</td>
 <td colspan="4">Stimulus_Name_Left Eye.vei</td>
 <td colspan="4">Stimulus_Name_Right_Eye.vei</td>
 </tr>
 <tr>
 <td>&nbsp;</td>
 <td>Time (s)</td>
 <td>x-position (pixel)</td>
 <td>y-position (pixel)</td>
 <td>Rotation (&deg;)</td>
 <td>Time (s)</td>
 <td>x-position (pixel)</td>
 <td>y-position (pixel)</td>
 <td>Rotation (&deg;)</td>
 </tr>
 <tr>
 <td rowspan="2">Smooth Pursuit Ramp</td>
 <td>0</td>
 <td>100</td>
 <td>0</td>
 <td>0</td>
 <td>0</td>
 <td>100</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td>10</td>
 <td>200</td>
 <td>0</td>
 <td>0</td>
 <td>10</td>
 <td>200</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td width="53" rowspan="4">Saccade Step</td>
 <td>0</td>
 <td>100</td>
 <td>0</td>
 <td>0</td>
 <td>0</td>
 <td>100</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td>0.5</td>
 <td>100</td>
 <td>0</td>
 <td>0</td>
 <td>0.5</td>
 <td>100</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td>0.501</td>
 <td>200</td>
 <td>0</td>
 <td>0</td>
 <td>0.501</td>
 <td>200</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td>3</td>
 <td>200</td>
 <td>0</td>
 <td>0</td>
 <td>3</td>
 <td>200</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td rowspan="2">Vergence Ramp</td>
 <td>0</td>
 <td>452</td>
 <td>0</td>
 <td>0</td>
 <td>0</td>
 <td>973</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td>10</td>
 <td>370</td>
 <td>0</td>
 <td>0</td>
 <td>10</td>
 <td>1044</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td rowspan="4">Vergence Step</td>
 <td>0</td>
 <td>452</td>
 <td>0</td>
 <td>0</td>
 <td>0</td>
 <td>973</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td>0.5</td>
 <td>452</td>
 <td>0</td>
 <td>0</td>
 <td>0.5</td>
 <td>973</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td>0.501</td>
 <td>416</td>
 <td>0</td>
 <td>0</td>
 <td>0.501</td>
 <td>1002</td>
 <td>0</td>
 <td>0</td>
 </tr>
 <tr>
 <td>3</td>
 <td>416</td>
 <td>0</td>
 <td>0</td>
 <td>3</td>
 <td>1002</td>
 <td>0</td>
 <td>0</td>
 </tr>
 </tbody>
</table>
Table 1. An Example of Smooth Pursuit Ramp, Saccadic Step, Vergence Ramp and Vergence Step Stimuli
<table border="1">
<tbody>
 <tr>
 <td>Function</td>
 <td>Syntax</td>
 </tr>
 <tr>
 <td>ExpTrial</td>
 <td>Output Buffer # = ExpTrial ("Length of Data: LE Profile: RE Profile"); 
 Example: 2=ExpTrial("13:3:3");</td>
 </tr>
 <tr>
 <td>&nbsp;</td>
 <td>Output Buffer # = Exo Trial ("Length of Data: LE Profile: RE Profile: tempfile. lwf") ; 
 Example: 2=ExpTrial("13:3:3:templfile.lwf");</td>
 </tr>
 <tr>
 <td>LogFile</td>
 <td>Output Buffer # = LogFile("TEXT"); 
 Example: 0=LogFile("Experiment 1");</td>
 </tr>
 <tr>
 <td>&nbsp;</td>
 <td>0=LogFile( Input Buffer #); 
 Example: 0=LogFile(2);</td>
 </tr>
 <tr>
 <td>TriggerWait</td>
 <td>0=TriggerWait(Buffer Number); 
 Example: 0=TriggerWait(0);</td>
 </tr>
 <tr>
 <td>RandomDelay</td>
 <td>0=RandomDelay("t2:t1"); 
 Example: 0=RandomDelay("2000:500");</td>
 </tr>
 <tr>
 <td>WaveMSD</td>
 <td>Output Buffer #= WaveMSD(Input Buffer #);</td>
 </tr>
 </tbody>
</table>
Table 2. Functions Used to Write the Experimental Protocol in the VisualEyes Program

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No conflicts of interest declared.

Critical Steps:
Eye movement monitors must be properly adjusted on the subject. For example, eye movement recording monitors work within a range and must be adjusted to the subject. If the subject's eye movement goes beyond the range, then the system becomes saturated. Upon saturation, the eye movement signal is not valid. Calibration is also critical in eye movement recording. All eye movement monitors measure an analog signal that is digitized and needs to be converted to units commonly used...

A correction was made to <a href="http://www.jove.com/details.php?id=2530">VisualEyes: A Modular Software System for Oculomotor Experimentation</a>. There was an error in the authors, Eun H. Kim and Tara L. Alvarez, names. The author's names have been corrected to: Eun H. Kim and Tara L. Alvarez instead of: Eun Kim and Tara Alvarez

Erratum: VisualEyes: A Modular Software System for Oculomotor Experimentation

visualeyes: a modular software system for oculomotor experimentation

Eye movement studies have provided a strong foundation forming an understanding of how the brain acquires visual information in both the normal and dysfunctional brain.1 However, development of a platform to stimulate and store eye movements can require substantial programming, time and costs. Many systems do not offer the flexibility to program numerous stimuli for a variety of experimental needs. However, the VisualEyes System has a flexible architecture, allowing the operator to choose any background and foreground stimulus, program one or two screens for tandem or opposing eye movements and stimulate the left and right eye independently. This system can significantly reduce the programming development time needed to conduct an oculomotor study. The VisualEyes System will be discussed in three parts: 1) the oculomotor recording device to acquire eye movement responses, 2) the VisualEyes software written in LabView, to generate an array of stimuli and store responses as text files and 3) offline data analysis. Eye movements can be recorded by several types of instrumentation such as: a limbus tracking system, a sclera search coil, or a video image system. Typical eye movement stimuli such as saccadic steps, vergent ramps and vergent steps with the corresponding responses will be shown. In this video report, we demonstrate the flexibility of a system to create numerous visual stimuli and record eye movements that can be utilized by basic scientists and clinicians to study healthy as well as clinical populations.

Watch this Scientific Journal Video about VisualEyes: A Modular Software System for Oculomotor Experimentation at JoVE.com

VisualEyes: A Modular Software System for Oculomotor Experimentation

Neural control and cognitive processes can be studied through eye movements. The VisualEyes software allows an operator to program stimuli on two computer screens independently using a simple, custom scripting language. The system can stimulate tandem eye movements (saccades and smooth pursuit) or opposing eye movements (vergence) or any combination.

Eye movement studies have provided a strong foundation forming an understanding of how the brain acquires visual information in both the normal and ...

visualeyes-a-modular-software-system-for-oculomotor-experimentation

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Neuroscience

12.6K Views.  New Jersey Institute of Technology. Neural control and cognitive processes can be studied through eye movements. The VisualEyes software allows an operator to program stimuli on two computer screens independently using a simple, custom scripting language. The system can stimulate tandem eye movements (saccades and smooth pursuit) or opposing eye movements (vergence) or any combination.

Video: VisualEyes: A Modular Software System for Oculomotor Experimentation

Physiological Experimentation with the Crayfish Hindgut: A Student Laboratory Exercise

The purpose of the report is to describe dissection techniques for preparing the crayfish hindgut and to demonstrate how to make physiological recordings with a force transducer to monitor the strength of contraction. In addition, we demonstrate how to visually monitor peristaltic activity, which can be used as a bioassay for various peptides, biogenic amines and neurotransmitters. This preparation is amenable to student laboratories in physiology and for demonstrating pharmacological concepts to students. This preparation has been in use for over 100 years, and it still offers much as a model for investigating the generation and regulation of peristaltic rhythms and for describing the mechanisms underlying their modulation. The pharmacological assays and receptor sub-typing that were started over 50 years ago on the hindgut still contribute to research today. This robust preparation is well suited to training students in physiology and pharmacology.

In this report we demonstrate techniques that can be used to investigate the biology of the crayfish hindgut. We show how to dissect a crayfish abdomen and study the associated anatomy, physiology and modulation of activity. The peristaltic activity and strength of contractions are measured using a force transducer.

The purpose of the report is to describe dissection techniques for preparing the crayfish hindgut and to demonstrate how to make physiological recordings ...

VisioTracker, an Innovative Automated Approach to Oculomotor Analysis

Investigations into the visual system development and function necessitate quantifiable behavioral models of visual performance that are easy to elicit, robust, and simple to manipulate. A suitable model has been found in the optokinetic response (OKR), a reflexive behavior present in all vertebrates due to its high selection value. The OKR involves slow stimulus-following movements of eyes alternated with rapid resetting saccades. The measurement of this behavior is easily carried out in zebrafish larvae, due to its early and stable onset (fully developed after 96 hours post fertilization (hpf)), and benefitting from the thorough knowledge about zebrafish genetics, for decades one of the favored model organisms in this field. Meanwhile the analysis of similar mechanisms in adult fish has gained importance, particularly for pharmacological and toxicological applications.
Here we describe VisioTracker, a fully automated, high-throughput system for quantitative analysis of visual performance. The system is based on research carried out in the group of Prof. Stephan Neuhauss and was re-designed by TSE Systems. It consists of an immobilizing device for small fish monitored by a high-quality video camera equipped with a high-resolution zoom lens. The fish container is surrounded by a drum screen, upon which computer-generated stimulus patterns can be projected. Eye movements are recorded and automatically analyzed by the VisioTracker software package in real time.
Data analysis enables immediate recognition of parameters such as slow and fast phase duration, movement cycle frequency, slow-phase gain, visual acuity, and contrast sensitivity.
Typical results allow for example the rapid identification of visual system mutants that show no apparent alteration in wild type morphology, or the determination of quantitative effects of pharmacological or toxic and mutagenic agents on visual system performance.

The VisioTracker is an automated system for the quantitative analysis of visual performance of larval and small adult fish based on the recording of eye movements. It features full control over visual stimulus properties and real-time analysis, enabling high-throughput research in fields such as visual system development and function, pharmacology, neural circuit studies and sensorimotor integration.

Investigations into the visual system development and function necessitate quantifiable behavioral models of visual performance that are easy to elicit, ...

A Lightweight, Headphones-based System for Manipulating Auditory Feedback in Songbirds

Experimental manipulations of sensory feedback during complex behavior have provided valuable insights into the computations underlying motor control and sensorimotor plasticity1. Consistent sensory perturbations result in compensatory changes in motor output, reflecting changes in feedforward motor control that reduce the experienced feedback error. By quantifying how different sensory feedback errors affect human behavior, prior studies have explored how visual signals are used to recalibrate arm movements2,3 and auditory feedback is used to modify speech production4-7. The strength of this approach rests on the ability to mimic naturalistic errors in behavior, allowing the experimenter to observe how experienced errors in production are used to recalibrate motor output.
Songbirds provide an excellent animal model for investigating the neural basis of sensorimotor control and plasticity8,9. The songbird brain provides a well-defined circuit in which the areas necessary for song learning are spatially separated from those required for song production, and neural recording and lesion studies have made significant advances in understanding how different brain areas contribute to vocal behavior9-12. However, the lack of a naturalistic error-correction paradigm - in which a known acoustic parameter is perturbed by the experimenter and then corrected by the songbird - has made it difficult to understand the computations underlying vocal learning or how different elements of the neural circuit contribute to the correction of vocal errors13.
The technique described here gives the experimenter precise control over auditory feedback errors in singing birds, allowing the introduction of arbitrary sensory errors that can be used to drive vocal learning. Online sound-processing equipment is used to introduce a known perturbation to the acoustics of song, and a miniaturized headphones apparatus is used to replace a songbird's natural auditory feedback with the perturbed signal in real time. We have used this paradigm to perturb the fundamental frequency (pitch) of auditory feedback in adult songbirds, providing the first demonstration that adult birds maintain vocal performance using error correction14. The present protocol can be used to implement a wide range of sensory feedback perturbations (including but not limited to pitch shifts) to investigate the computational and neurophysiological basis of vocal learning.

We describe the design and assembly of miniaturized headphones suitable for replacing a songbird&#x2019;s natural auditory feedback with a manipulated acoustic signal. Online sound processing hardware is used to manipulate song output, introduce real-time errors in auditory feedback via the headphones, and drive vocal motor learning.

Experimental manipulations of sensory feedback during complex behavior have provided valuable insights into the computations underlying motor control and ...

A High Content Imaging Assay for Identification of Botulinum Neurotoxin Inhibitors

Synaptosomal-associated protein-25 (SNAP-25) is a component of the soluble NSF attachment protein receptor (SNARE) complex that is essential for synaptic neurotransmitter release. Botulinum neurotoxin serotype A (BoNT/A) is a zinc metalloprotease that blocks exocytosis of neurotransmitter by cleaving the SNAP-25 component of the SNARE complex. Currently there are no licensed medicines to treat BoNT/A poisoning after internalization of the toxin by motor neurons. The development of effective therapeutic measures to counter BoNT/A intoxication has been limited, due in part to the lack of robust high-throughput assays for screening small molecule libraries. Here we describe a high content imaging (HCI) assay with utility for identification of BoNT/A inhibitors. Initial optimization efforts focused on improving the reproducibility of inter-plate results across multiple, independent experiments. Automation of immunostaining, image acquisition, and image analysis were found to increase assay consistency and minimize variability while enabling the multiparameter evaluation of experimental compounds in a murine motor neuron system.

Botulinum neurotoxin is one of the most potent toxins among Category-A biothreat agents, yet a post-exposure therapeutic is not available. The high content imaging approach is a powerful methodology for identifying novel inhibitors as it enables multiparameter screening using biologically relevant motor neurons, the primary target of this toxin.

Synaptosomal-associated protein-25 (SNAP-25) is a component of the soluble NSF attachment protein receptor (SNARE) complex that is essential for synaptic ...

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

The brain operates through the coordinated activation and the dynamic communication of neuronal assemblies. A major open question is how a vast repertoire of dynamical motifs, which underlie most diverse brain functions, can emerge out of a fixed topological and modular organization of brain circuits. Compared to in vivo studies of neuronal circuits which present intrinsic experimental difficulties, in vitro preparations offer a much larger possibility to manipulate and probe the structural, dynamical and chemical properties of experimental neuronal systems. This work describes an in vitro experimental methodology which allows growing of modular networks composed by spatially distinct, functionally interconnected neuronal assemblies. The protocol allows controlling the two-dimensional (2D) architecture of the neuronal network at different levels of topological complexity.
A desired network patterning can be achieved both on regular cover slips and substrate embedded micro electrode arrays. Micromachined structures are embossed on a silicon wafer and used to create biocompatible polymeric stencils, which incorporate the negative features of the desired network architecture. The stencils are placed on the culturing substrates during the surface coating procedure with a molecular layer for promoting cellular adhesion. After removal of the stencils, neurons are plated and they spontaneously redirected to the coated areas. By decreasing the inter-compartment distance, it is possible to obtain either isolated or interconnected neuronal circuits. To promote cell survival, cells are co-cultured with a supporting neuronal network which is located at the periphery of the culture dish. Electrophysiological and optical recordings of the activity of modular networks obtained respectively by using substrate embedded micro electrode arrays and calcium imaging are presented. While each module shows spontaneous global synchronizations, the occurrence of inter-module synchronization is regulated by the density of connection among the circuits.

This manuscript describes a protocol to grow in vitro modular networks consisting of spatially confined, functionally inter-connected neuronal circuits. A polymeric mask is used to pattern a protein layer to promote cellular adhesion over the culturing substrate. Plated neurons grow on coated areas establishing spontaneous connections and exhibiting electrophysiological activity.

The brain operates through the coordinated activation and the dynamic communication of neuronal assemblies. A major open question is how a vast repertoire ...

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Measuring neural activity and connectivity associated with cognitive functions at high spatial and temporal resolutions is an important goal in cognitive neuroscience. Intracranial electroencephalography (EEG) can directly record electrical neural activity and has the unique potential to accomplish this goal. Traditionally, averaging analysis has been applied to analyze intracranial EEG data; however, several new techniques are available for depicting neural activity and intra- and inter-regional connectivity. Here, we introduce two analytical protocols we recently applied to analyze intracranial EEG data using the Statistical Parametric Mapping (SPM) software: time-frequency SPM analysis for neural activity and dynamic causal modeling of induced responses for intra- and inter-regional connectivity. We report our analysis of intracranial EEG data during the observation of faces as representative results. The results revealed that the inferior occipital gyrus (IOG) showed gamma-band activity at very early stages (110 ms) in response to faces, and both the IOG and amygdala showed rapid intra- and inter-regional connectivity using various types of oscillations. These analytical protocols have the potential to identify the neural mechanisms underlying cognitive functions with high spatial and temporal profiles.

We present two analytical protocols that can be used to analyze intracranial electroencephalography data using the Statistical Parametric Mapping (SPM) software: time-frequency statistical parametric mapping analysis for neural activity, and dynamic causal modeling of induced responses for intra- and inter-regional connectivity.

Measuring neural activity and connectivity associated with cognitive functions at high spatial and temporal resolutions is an important goal in cognitive ...

Ex Vivo Oculomotor Slice Culture from Embryonic GFP-Expressing Mice for Time-Lapse Imaging of Oculomotor Nerve Outgrowth

Accurate eye movements are crucial for vision, but the development of the ocular motor system, especially the molecular pathways controlling axon guidance, has not been fully elucidated. This is partly due to technical limitations of traditional axon guidance assays. To identify additional axon guidance cues influencing the oculomotor nerve, an ex vivo slice assay to image the oculomotor nerve in real-time as it grows towards the eye was developed. E10.5 IslMN-GFP embryos are used to generate ex vivo slices by embedding them in agarose, slicing on a vibratome, then growing them in a microscope stage-top incubator with time-lapse photomicroscopy for 24-72 h. Control slices recapitulate the in vivo timing of outgrowth of axons from the nucleus to the orbit. Small molecule inhibitors or recombinant proteins can be added to the culture media to assess the role of different axon guidance pathways. This method has the advantages of maintaining more of the local microenvironment through which axons traverse, not axotomizing the growing axons, and assessing the axons at multiple points along their trajectory. It can also identify effects on specific subsets of axons. For example, inhibition of CXCR4 causes axons still within the midbrain to grow dorsally rather than ventrally, but axons that have already exited ventrally are not affected.

An ex vivo slice assay allows oculomotor nerve outgrowth to be imaged in real time. Slices are generated by embedding E10.5 IslMN:GFP embryos in agarose, slicing on a vibratome, and growing in a stage-top incubator. The role of axon guidance pathways is assessed by adding inhibitors to the culture media.

Accurate eye movements are crucial for vision, but the development of the ocular motor system, especially the molecular pathways controlling axon ...

Isolation and Culture of Oculomotor, Trochlear, and Spinal Motor Neurons from Prenatal Islmn:GFP Transgenic Mice

Oculomotor neurons (CN3s) and trochlear neurons (CN4s) exhibit remarkable resistance to degenerative motor neuron diseases such as amyotrophic lateral sclerosis (ALS) when compared to spinal motor neurons (SMNs). The ability to isolate and culture primary mouse CN3s, CN4s, and SMNs would provide an approach to study mechanisms underlying this selective vulnerability. To date, most protocols use heterogeneous cell cultures, which can confound the interpretation of experimental outcomes. To minimize the problems associated with mixed-cell populations, pure cultures are indispensable. Here, the first protocol describes in detail how to efficiently purify and cultivate CN3s/CN4s alongside SMNs counterparts from the same embryos using embryonic day 11.5 (E11.5) IslMN:GFP transgenic mouse embryos. The protocol provides details on the tissue dissection and dissociation, FACS-based cell isolation, and in vitro cultivation of cells from CN3/CN4 and SMN nuclei. This protocol adds a novel in vitro CN3/CN4 culture system to existing protocols and simultaneously provides a pure species- and age-matched SMN culture for comparison. Analyses focusing on the morphological, cellular, molecular, and electrophysiological characteristics of motor neurons are feasible in this culture system. This protocol will enable research into the mechanisms that define motor neuron development, selective vulnerability, and disease.

Isolation and Culture of Oculomotor, Trochlear, and Spinal Motor Neurons from Prenatal Islmn:GFP Transgenic Mice

This work presents a protocol to yield homogeneous cell cultures of primary oculomotor, trochlear, and spinal motor neurons. These cultures can be used for comparative analyses of the morphological, cellular, molecular, and electrophysiological characteristics of ocular and spinal motor neurons.

Oculomotor neurons (CN3s) and trochlear neurons (CN4s) exhibit remarkable resistance to degenerative motor neuron diseases such as amyotrophic lateral ...

Extracellular Electrophysiology in Modular Neuronal Cell Culture

A Cost-Effective, Versatile Probe Implant System for Electrophysiology in Mice

The DREAM Implant: A Lightweight, Modular, and Cost-Effective Implant System for Chronic Electrophysiology in Head-Fixed and Freely Behaving Mice

Chronic electrophysiological recordings in rodents have significantly improved our understanding of neuronal dynamics and their behavioral relevance. However, current methods for chronically implanting probes present steep trade-offs between cost, ease of use, size, adaptability, and long-term stability.
This protocol introduces a novel chronic probe implant system for mice called the DREAM (Dynamic, Recoverable, Economical, Adaptable, and Modular), designed to overcome the trade-offs associated with currently available options. The system provides a lightweight, modular and cost-effective solution with standardized hardware elements that can be combined and implanted in straightforward steps and explanted safely for recovery and multiple reuse of probes, significantly reducing experimental costs.
The DREAM implant system integrates three hardware modules: (1) a microdrive that can carry all standard silicon probes, allowing experimenters to adjust recording depth across a travel distance of up to 7 mm; (2) a three-dimensional (3D)-printable, open-source design for a wearable Faraday cage covered in copper mesh for electrical shielding, impact protection, and connector placement, and (3) a miniaturized head-fixation system for improved animal welfare and ease of use. The corresponding surgery protocol was optimized for speed (total duration: 2 h), probe safety, and animal welfare.
The implants had minimal impact on animals&#39; behavioral repertoire, were easily applicable in freely moving and head-fixed contexts, and delivered clearly identifiable spike waveforms and healthy neuronal responses for weeks of post-implant data collection. Infections and other surgery complications were extremely rare.
As such, the DREAM implant system is a versatile, cost-effective solution for chronic electrophysiology in mice, enhancing animal well-being, and enabling more ethologically sound experiments. Its design simplifies experimental procedures across various research needs, increasing accessibility of chronic electrophysiology in rodents to a wide range of research labs.

Here, we introduce a lightweight, cost-effective probe implant system for chronic electrophysiology in rodents optimized for ease of use, probe recovery, experimental versatility, and compatibility with behavior.

Chronic electrophysiological recordings in rodents have significantly improved our understanding of neuronal dynamics and their behavioral relevance. ...