triggering a closed-loop stimulation by neuron spiking activity

Triggering a Closed-Loop Stimulation by Neuron Spiking Activity

To perform a closed-loop experiment, resume the data acquisition in Cheetah and open Matlab. Open ClosedLoop.m and click Run. Alternatively, execute ClosedLoop in the command window. Browse to the recording folder, and select one of the spiking data files to load the spike information defined in the initial recording. Click the appropriate checkboxes under the plotted waveforms to select one or multiple neurons that will trigger stimulation.
Define the minimum number of neurons that will trigger stimulation by entering an integer in the Min Matches text box, and define the time window in which the spikes matching the different waveforms are considered co-active by entering a number into the Window text box. Then, click Send to begin the online triggering of events based on the spiking activity of the selected neurons.

triggering-a-closed-loop-stimulation-by-neuron-spiking-activity

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Neuroscience

Neurophysiology

Stimulation and Modulation Techniques

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All procedures involving animal models have been reviewed by the local institutional animal care committee and the JoVE veterinary review board.
1. Surgery
NOTE: The exact details of the surgery for closed-loop stimulation depend on the type of recording probes used and the brain areas targeted. In most cases, however, a typical surgery will consist of the following steps.
<ol>
	<li>Bring a cage with a rat to the surgery room to be implanted with a silicone probe or electrode array to record neuronal activity.</li>
	<li>Anesthetize the rodent with 2-2.5% isoflurane and fix the head in a stereotaxic frame. Ensure that the animal is unconscious during surgery by observing any motoric reaction to mild tactile stimuli.</li>
	<li>Apply an eye ointment to minimize dryness during the surgery.</li>
	<li>Shave the surgical area and disinfect the skin with 2% chlorhexidine solution and 70% isopropyl alcohol.</li>
	<li>Inject lidocaine (5 mg/kg) under the scalp over the brain area where electrodes will be implanted.</li>
	<li>Make an incision of the scalp over the area of the future implant, and use a scalpel and a cotton swab to clear the periosteum from the exposed skull.</li>
	<li>Drill 4-8 holes in the skull for implantation of anchor screws (~0.5 mm) as structural support for the implant. Attach the screws to the skull by inserting them in the holes and ensure that they are held firmly in place.</li>
	<li>Drill the craniotomy at the specified coordinates and inset the microdrive/probe implant. 
	NOTE: The described protocol for closed-loop stimulation will work for any brain region in which the electrodes are inserted.</li>
	<li>Fix the microdrive/probe and any required electrical interface connector to the skull using dental acrylic. The amount of dental acrylic should be enough to attach the implant firmly, but it should not come in contact with the surrounding soft tissue.</li>
	<li>After surgery, closely monitor the animal until it has regained sufficient consciousness to maintain sternal recumbency. For the subsequent three days, administer subcutaneously an analgesic (e.g., Metacam, 1 mg/kg) and an antibiotic to prevent infection (e.g., enrofloxacin, 10 mg/kg). 
NOTE: Animals are typically left to recover from surgery for one week prior to any testing or recording.</li>
</ol>
2. Software installation
NOTE: This was tested on Windows 10, 64-bit version.
<ol>
	<li>Install data acquisition and processing software.</li>
	<li>Install the data acquisition system Cheetah 6.4 (https://neuralynx.com/software/category/sw-acquisition-control), which includes libraries to interact with the Cheetah Acquisition System.</li>
	<li>Install SpikeSort3D (https://neuralynx.com/software/spikesort-3d) or any other software that uses KlustaKwik27 for spike sorting. The online detection software uses the cluster definitions from the KlustaKwik engine. This software may run on the same computer or on separate computers on the same network.</li>
	<li>Install the NetComDevelopmentPackage (https://github.com/leomol/cheetah-interface/blob/master/NetComDevelopmentPackage_v3.1.0), which can also be downloaded from https://neuralynx.com/software/netcom-development-package.</li>
	<li>Install Matlab (https://www.mathworks.com/downloads/; code was tested on Matlab version R2018a). Make sure that Matlab is enabled in the Windows firewall. Normally, a pop-up will appear during the first connection.</li>
	<li>Log in to a Matlab account. Choose the license. Choose the version. Choose the operating system.</li>
	<li>Download the following library for online event triggering from https://github.com/leomol/cheetah-interface and extract files to the computer&#39;s &#39;Documents/Matlab&#39; folder. A copy of the code is provided in the accompanying Supplemental Materials.</li>
</ol>
3. Initial data acquisition
<ol>
	<li>Start data acquisition using Cheetah software.</li>
	<li>Record a few minutes of spiking data to populate template waveforms.</li>
	<li>Stop the data acquisition and perform spike sorting on the recorded data.</li>
	<li>Open SpikeSort3D, click File | Menu | Load Spike File and select a spike file from the folder with recorded data.</li>
	<li>Click Cluster Menu, then Autocluster using KlustaKwik, leaving the default settings, and click Run.</li>
</ol>
4. Closed-loop experiment
<ol>
	<li>Resume data acquisition in Cheetah.</li>
	<li>Open Matlab.</li>
	<li>Open ClosedLoop.m and click on Run. Alternatively, in the Matlab command window, execute ClosedLoop(). Ensure that ClosedLoop.m is on the Matlab path. If the user wants to employ a custom function to call on every trigger, execute ClosedLoop(&#39;-callback&#39;, customFunction) instead, where customFunction is a handle to that function.</li>
	<li>Load the spike information defined on the initial recording by clicking on Load, browsing the recording folder, and selecting one of the spiking data files (.ntt, .nse).</li>
	<li>Select one or multiple neurons that will trigger stimulation by clicking the checkbox under the plotted waveforms.</li>
	<li>Define the minimum number of neurons that will trigger stimulation by typing an integer in the &#34;min matches&#34; text box. Then, define the time window in which spikes matching different waveforms are considered co-active by typing a number in the &#34;window&#34; text box.</li>
	<li>Click Send to start. This will begin online triggering of events (tones as default) based on the spiking activity of selected neurons.</li>
</ol>

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Baytril</td>
			<td>Bayer, Mississauga, CA</td>
			<td>DIN 02169428</td>
			<td>antibiotic; 50 mg/mL</td>
		</tr>
		<tr>
			<td>Cheetah 6.4</td>
			<td>NeuraLynx, Tucson, AZ</td>
			<td>6.4.0.beta</td>
			<td>Software interfaces for data acquisition</td>
		</tr>
		<tr>
			<td>Digital Lynx 4SX</td>
			<td>NeuraLynx, Tucson, AZ</td>
			<td>4SX</td>
			<td>recording equipment</td>
		</tr>
		<tr>
			<td>Headstage transmitter</td>
			<td>TBSI</td>
			<td>B10-3163-GK</td>
			<td>transmits the neural signal to the receiver</td>
		</tr>
		<tr>
			<td>Isoflurane</td>
			<td>Fresenius Kabi, Toronto, CA</td>
			<td>DIN 02237518</td>
			<td>inhalation anesthetic</td>
		</tr>
		<tr>
			<td>Jet Denture Powder &#38; Liqud</td>
			<td>Lang Dental, Wheeling, US</td>
			<td>1230</td>
			<td>dental acrylic</td>
		</tr>
		<tr>
			<td>Lacri-Lube</td>
			<td>Allergan, Markham, CA</td>
			<td>DIN 00210889</td>
			<td>eye ointment</td>
		</tr>
		<tr>
			<td>Lido-2</td>
			<td>Rafter 8, Calgary</td>
			<td>DIN 00654639</td>
			<td>local anesthetic; 20 mg/mL</td>
		</tr>
		<tr>
			<td>Matlab</td>
			<td>Mathworks</td>
			<td>R2018b</td>
			<td>software for signal processing and triggering external events</td>
		</tr>
		<tr>
			<td>Metacam</td>
			<td>Boehringer, Ingelheim, DE</td>
			<td>DIN 02240463</td>
			<td>analgesic; 5 mg/mL</td>
		</tr>
		<tr>
			<td>Netcom</td>
			<td>NeuraLynx</td>
			<td>v1</td>
			<td>Application Programming Interface (API) that communicates with Cheetah</td>
		</tr>
		<tr>
			<td>Silicone probe</td>
			<td>Cambridge Neurotech</td>
			<td>ASSY-156-DBC2</td>
			<td>implanted device</td>
		</tr>
		<tr>
			<td>SpikeSort 3D</td>
			<td>NeuraLynx, Tucson, AZ</td>
			<td>SS3D</td>
			<td>spike waveform-to-cell classification tools</td>
		</tr>
		<tr>
			<td>Wireless Radio Receiver</td>
			<td>TBSI</td>
			<td>911-1062-00</td>
			<td>transmits the neural signal to the Digital Lynx</td>
		</tr>
	</tbody>
</table>

Source: Molina, L. et al. <a href="https://app.jove.com/v/59812">Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments.</a> J. Vis. Exp. (2019).
This video demonstrates the operation of closed-loop stimulation in a rat with a surgically implanted device to record neural activity. Neuronal signals are first recorded and analyzed. Template waveforms are then uploaded, and parameters are defined to trigger closed-loop stimulation.

All procedures involving animal models have been reviewed by the local institutional animal care committee and the JoVE veterinary review board.
1. ...

Take a rat with a surgically implanted device to record neural activity.
Download all the required software.
Record the initial spiking data and select template waveforms.
Resume data recording for the closed-loop stimulation experiment.
Closed-loop stimulation is a system in which sensors continuously record neural signals.
Upon detecting specific neural activity, a predefined stimulation is generated as feedback.
The sensors then record the neural response to this stimulation, continuing the loop.
Run the required program.
Load template waveforms from the initial recordings and select the desired number of templates required to trigger the stimulation.
Define a minimal number of neurons needed to initiate the stimulation.
Set parameters for the time period during which spike signals detected from different neurons will be considered co-active.
Begin the closed-loop experiment with predefined stimulation.

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Experimental neuroscience is witnessing an increased interest in the development and application of novel and often complex, closed-loop protocols, where the stimulus applied depends in real-time on the response of the system. Recent applications range from the implementation of virtual reality systems for studying motor responses both in mice1 and in zebrafish2, to control of seizures following cortical stroke using optogenetics3. A key advantage of closed-loop techniques resides in the capability of probing higher dimensional properties that are not directly accessible or that depend on multiple variables, such as neuronal excitability4 and reliability, while at the same time maximizing the experimental throughput. In this contribution and in the context of cellular electrophysiology, we describe how to apply a variety of closed-loop protocols to the study of the response properties of pyramidal cortical neurons, recorded intracellularly with the patch clamp technique in acute brain slices from the somatosensory cortex of juvenile rats. As no commercially available or open source software provides all the features required for efficiently performing the experiments described here, a new software toolbox called LCG5 was developed, whose modular structure maximizes reuse of computer code and facilitates the implementation of novel experimental paradigms. Stimulation waveforms are specified using a compact meta-description and full experimental protocols are described in text-based configuration files. Additionally, LCG has a command-line interface that is suited for repetition of trials and automation of experimental protocols.

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Deep brain stimulation involves the administration of electrical stimulation to targeted brain regions for therapeutic benefit. In the context of major depressive disorder (MDD), most studies to date have administered continuous or open-loop stimulation with promising but mixed results. One factor contributing to these mixed results may stem from when the stimulation is applied. Stimulation administration specific to high-symptom states in a personalized and responsive manner may be more effective at reducing symptoms compared to continuous stimulation and may avoid diminished therapeutic effects related to habituation. Additionally, a lower total duration of stimulation per day is advantageous for reducing device energy consumption. This protocol describes an experimental workflow using a chronically implanted neurostimulation device to achieve closed-loop stimulation for individuals with treatment-refractory MDD. This paradigm hinges on determining a patient-specific neural biomarker that is related to states of high symptoms and programming the device detectors, such that stimulation is triggered by this read-out of symptom state. The described procedures include how to obtain neural recordings concurrent with patient symptom reports, how to use these data in a state-space model approach to differentiate low- and high-symptom states and corresponding neural features, and how to subsequently program and tune the device to deliver closed-loop stimulation therapy.

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Triggering a Closed-Loop Stimulation by Neuron Spiking Activity

ТРАНСКРИПТ

Triggering a Closed-Loop Stimulation by Neuron Spiking Activity