This work was supported by NSERC Discovery grants to AL and AG.

All procedures described here were performed under an Animal Research Protocol approved by the University of Lethbridge Animal Welfare Committee.
1. Surgery
NOTE: The surgery procedures used to implant probes for neurophysiological recordings have been presented in other publications24,25,26. 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 to the surgery room a cage with a rat 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 stimuli25.</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 future implant, and use a scalpel and cotton swab to clear the periosteum from the exposed skull25.</li>
	<li>Drill 4-8 holes in the skull for implantation of anchor screws (~0.5 mm) as structural support for the implant25. 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 firmly attach the implant, but it should not come in contact with the surrounding soft tissue25.</li>
	<li>After surgery, closely monitor the animal until it has regained sufficient consciousness to maintain sternal recumbency25. For the subsequent 3 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.
	<ol>
		<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 it may run on separate computers that are on the same network.</li>
		<li>Install the NetComDevelopmentPackage (https://github.com/leomol/cheetah-interface/blob/master/NetComDevelopmentPackage_v3.1.0), which can be also downloaded from https://neuralynx.com/software/netcom-development-package.</li>
	</ol>
	</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 come up during the first connection.
	<ol>
		<li>Log in to a Matlab account. Choose the licence. Choose the version. Choose the operating system.</li>
	</ol>
	</li>
	<li>Download the following library for online event triggering from: https://github.com/leomol/cheetah-interface and extract files to the computer&#8217;s &#8216;Documents/Matlab&#8217; 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.
	<ol>
		<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 and then Autocluster using KlustaKwik, leaving the default settings and click Run.</li>
	</ol>
	</li>
</ol>
4. Closed-loop experiment
<ol>
	<li>Resume data acquisition in Cheetah.</li>
	<li>Open Matlab.
	<ol>
		<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(&#8216;-callback&#8217;, 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 to 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 &#8220;min matches&#8221; text box; and define the time window in which spikes matching different waveforms are considered co-active by typing a number in the &#8220;window&#8221; text box.</li>
		<li>Click Send to start. This will begin online triggering of events (tones as default) based on spiking activity of selected neurons.</li>
	</ol>
	</li>
</ol>

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Authors do not have any conflict of interests related to this work.

The protocol described here, shows how to use a standard neurophysiological recording system to perform closed-loop stimulation. This protocol allows neuroscientists with limited expertise in computer science to rapidly implement a variety of closed-loop experiments with little cost. Such experiments are often necessary to study causal interactions in the brain.
After preparing an animal and installing the software (Steps 1 &amp; 2), the closed-loop experiment consists of two separate stages. First, initial data acquisition (Step 3) to collect data to define templates corresponding to activity of single neurons (i.e., spike sorting; Step 3.5). Secondly, the closed-loop stimulation, where newly recorded spikes will be automatically assigned to predefined clusters in real time and trigger stimulation if spikes form specified neurons are detected (Step 4). The presented Matlab scripts (see Supplemental Materials) demonstrate the triggering of different stimuli based on the activity of a single neuron, and on the activity of multiple selected neurons. The latter is a particularly important option, because neurons are believed to process information as an assembly (e.g., packets35,36). Triggering stimuli based on neuronal population patterns may thus be a key tool for answering a wide range of research questions. The data flow during closed-loop control is illustrated in Figure 3.
In this protocol demonstration, a 3 kHz tone stimuli was used. This pure tone can be replaced by an arbitrary sound waveform by changing the variable &ldquo;tone0&rdquo;. Also, note that instead of a speaker, many other devices could be connected to the computer&rsquo;s audio output to trigger a stimulation. For example, the audio output was used to drive a vibration motor to deliver low frequency (20 Hz) tactile stimuli22. Alternatively, the Matlab code could be used to send a TTL signal to a device connected to a computer serial port. This can be accomplished by replacing the &lsquo;sound()&rsquo; command with the following code: obj=serial('COM1'); fopen(obj); obj.RequestToSend = 'on'. A sample implementation of this method is provided in the Supplemental Materials (see pulse.m). Similarly, Matlab could be used to send signals to external devices through a USB port. Thus, the code presented here allows users to send closed-loop triggers in a variety of ways to multiple devices.
Tests showed that the time delay between a neuronal spike and the trigger signal is about 13 ms (min 9 ms; max 15 ms). The distribution of time delays is illustrated in Figure 4A. For this latency tests, an Arduino was used to send an artificial spike to the acquisition system (via the head-stage). The delay was recorded as the time between the spike and the trigger signal from the acquisition PC running the closed-loop Matlab script. The schematic of the Arduino setup to generate spikes is shown in Figure 4B.
The approach presented here is implemented in software, and thus may not be able to deliver stimuli with temporal accuracy of systems with dedicated hardware. For example, TDT (Tucker-Davis Technologies) offers systems for spike triggered stimulation which can deliver stimuli within milliseconds. However, the advantage of the Matlab solution presented here is its low cost for users who own Cheetah recording hardware, its flexibility in defining the activity patterns to trigger stimuli, and its flexibility in defining neuronal templates. Moreover, single millisecond precision is not required in many experiments, so the implementation ease of this approach could offer a major advantage.

The goal of this protocol is to demonstrate how to implement closed-loop stimulation in neurophysiological experiments. The typical setup for closed-loop experiments in neuroscience involves triggering stimuli based on the online readout of neuronal activity. This, in turn, causes modifications in the brain activity, thus closing the feedback loop1,2. Such closed-loop experiments provide multiple benefits over standard open-loop setups, especially when combined with optogenetics, which allows researchers to target a specific subset of neurons. For example, Siegle and Wilson used closed-loop manipulations to study the role of theta oscillations in information processing3. They demonstrated that stimulating hippocampal neurons on the falling phase of theta oscillations had different effects on behavior than applying the same stimulation on the rising phase. Closed-loop experiments are also becoming increasingly important in preclinical studies. For instance, multiple epilepsy studies have shown that neuronal stimulation triggered on seizure onset is an effective approach to reduce the severity of seizures4,5,6. Moreover, systems for automated seizure detection and the contingent delivery of therapy7,8 showed significant benefits in epilepsy patients9,10,11,12. Another application area with rapid advancement of closed-loop methodologies is the control of neuroprosthetics with cortical brain&#8211;machine interfaces. This is because providing instantaneous feedback to users of prosthetic devices significantly improves accuracy and capability13.
In recent years, several labs have developed custom systems for the simultaneous electrical recording of neuronal activity and delivery of stimuli in a closed-loop system14,15,16,17,18. Although many of those setups have impressive characteristics, it is not always easy to implement them in other labs. This is because the systems often demand experienced technicians to assemble the required electronics and other necessary hardware and software components.
Therefore, in order to facilitate the adoption of closed-loop experiments in neuroscience research, this paper provides a protocol and Matlab code to convert an open-loop electrophysiological recording setup19,20,21,22 into a closed-loop system2,6,23. This protocol is designed to work with the Digital Lynx recording hardware, a popular laboratory system for neuronal population recordings. A typical experiment consists of the following: 1) Recording 5-20 minutes of spiking data; 2) Spike sorting to create neuronal templates; 3) Using these templates to perform online detection of neural activity patterns; and 4) Triggering stimulation or experimental events when user-specified patterns are detected.

<table><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&amp;nbsp;</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 &amp;amp; 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&amp;nbsp;</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>

using neuron spiking activity to trigger closed-loop stimuli in neurophysiological experiments

Closed-loop neurophysiological systems use patterns of neuronal activity to trigger stimuli, which in turn affect brain activity. Such closed-loop systems are already found in clinical applications, and are important tools for basic brain research. A particularly interesting recent development is the integration of closed-loop approaches with optogenetics, such that specific patterns of neuronal activity can trigger optical stimulation of selected neuronal groups. However, setting up an electrophysiological system for closed-loop experiments can be difficult. Here, a ready-to-apply Matlab code is provided for triggering stimuli based on the activity of single or multiple neurons. This sample code can be easily modified based on individual needs. For instance, it shows how to trigger sound stimuli and how to change it to trigger an external device connected to a PC serial port. The presented protocol is designed to work with a popular neuronal recording system for animal studies (Neuralynx). The implementation of closed-loop stimulation is demonstrated in an awake rat.

Fisher-Brown Norway rats born and raised on-site were habituated to handling for two weeks prior to the experiment. A recording drive was surgically implanted, similar to methods described previously28,29,30,31,32,33,34. The neuronal signals were recorded at 32 kHz with a digital acquisition system. Neuronal signals were first amplified with a unity gain wireless head-stage, then amplified with a gain of 1000, and band pass filtered between 600 and 6,000 Hz. Neuronal spikes exceeding a manually set amplitude threshold (typically 48-60 &#181;V) were automatically saved, and then sorted into distinct clusters. Thus, each cluster presumably corresponds to spikes from a different neuron27. For this protocol demonstration, the rat was resting on a flowerpot, which was a familiar resting place during breaks in behavioral experiments (Figure 1).
A representative screenshot from the recording computer is shown in Figure 2. It shows the simultaneous running of the recording software (left) and the Matlab program, which displays spike waveforms acquired in real time. This Matlab script is included in the Supplemental Materials. When spikes from predefined triggering clusters are detected, the waveforms are displayed with a bold dashed line in the Matlab figure window (Figure 2), and it triggers a tone, providing a closed-loop system. This closed-loop experimental setup allows, for example, to study neuroplasticity, where one can test if pairing neuronal activity with an external stimuli (tone) can affect the receptive fields of those neurons.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59812/59812fig01.jpg" /> 
Figure 1: Photograph of a rat with the wireless head-stage (board with pre-amplifiers and a blue LED) attached to an implanted silicone probe. The probe is positioned under the dental acrylic (pink material) and is not visible. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59812/59812fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59812/59812fig02.jpg" /> 
Figure 2: Screenshot of the recording and closed-loop software. Leftward panels are windows that are part of the Cheetah recording system used for visualizing and controlling the data acquisition. The window on the right side of the screen shows a Matlab session running the described software. The middle window shows the waveform of an online detected spike matching a pre-defined template. Spikes belonging to that cluster were used to trigger sound in the presented video. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59812/59812fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59812/59812fig03.jpg" /> 
Figure 3: Schematic pipeline for the data flow. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59812/59812fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/59812/59812fig04.jpg" /> 
Figure 4: Test of stimulus latency. (A) Histogram of delays between time of generating an artificial spike and time of triggered signal. (B) Schematic of a microprocessor board setup to generate artificial spike waveforms. The black and orange connections output an RC like waveform (ranging from 0 to 810 mV) and it is connected to the head-stage via a &#8220;signal-mouse&#8221; interface that reduces the voltage to 810 &#181;V. Components plugged in the same column of the breadboard are connected (resistors: 110 Ohm; 220 Ohm; 1000 Ohm; capacitor: 10 &#181;F). The Arduino was connected to a PC via USB/UART, which triggered Arduino spikes and received back signals from both the Arduino circuit and the acquisition software API. The Arduino was instructed to generate 1000 spikes. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59812/59812fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental File 1: Matlab Scripts. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59812/supplemental.zip" target="_blank">Please click here to view this file (Right click to download).</a>

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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

This protocol demonstrates how to use an electrophysiological system for closed-loop stimulation triggered by neuronal activity patterns. Sample Matlab code that can be easily modified for different stimulation devices is also provided.

Closed-loop neurophysiological systems use patterns of neuronal activity to trigger stimuli, which in turn affect brain activity. Such closed-loop systems ...

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7.0K Views.  University of Lethbridge. This protocol demonstrates how to use an electrophysiological system for closed-loop stimulation triggered by neuronal activity patterns. Sample Matlab code that can be easily modified for different stimulation devices is also provided.

Video: Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

The non-stationary nature and variability of neuronal signals is a fundamental problem in brain-machine interfacing. We developed a brain-machine interface to assess the robustness of different control-laws applied to a closed-loop image stabilization task. Taking advantage of the well-characterized fly visuomotor pathway we record the electrical activity from an identified, motion-sensitive neuron, H1, to control the yaw rotation of a two-wheeled robot. The robot is equipped with 2 high-speed video cameras providing visual motion input to a fly placed in front of 2 CRT computer monitors. The activity of the H1 neuron indicates the direction and relative speed of the robot's rotation. The neural activity is filtered and fed back into the steering system of the robot by means of proportional and proportional/adaptive control. Our goal is to test and optimize the performance of various control laws under closed-loop conditions for a broader application also in other brain machine interfaces.

We use a closed-loop fly-machine interface to investigate general principles in neuronal control.

The non-stationary nature and variability of neuronal signals is a fundamental problem in brain-machine interfacing. We developed a brain-machine ...

Using Affordable LED Arrays for Photo-Stimulation of Neurons

Standard slice electrophysiology has allowed researchers to probe individual components of neural circuitry by recording electrical responses of single cells in response to electrical or pharmacological manipulations1,2. With the invention of methods to optically control genetically targeted neurons (optogenetics), researchers now have an unprecedented level of control over specific groups of neurons in the standard slice preparation. In particular, photosensitive channelrhodopsin-2 (ChR2) allows researchers to activate neurons with light3,4. By combining careful calibration of LED-based photostimulation of ChR2 with standard slice electrophysiology, we are able to probe with greater detail the role of adult-born interneurons in the olfactory bulb, the first central relay of the olfactory system. Using viral expression of ChR2-YFP specifically in adult-born neurons, we can selectively control young adult-born neurons in a milieu of older and mature neurons. Our optical control uses a simple and inexpensive LED system, and we show how this system can be calibrated to understand how much light is needed to evoke spiking activity in single neurons. Hence, brief flashes of blue light can remotely control the firing pattern of ChR2-transduced newborn cells.

Adult-born neurons expressing ChR2 can be manipulated in slice electrophysiological preparations in order to examine their contribution towards the function of olfactory neural circuits.

Standard slice electrophysiology has allowed researchers to probe individual components of neural circuitry by recording electrical responses of single ...

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Signaling of information in the vertebrate central nervous system is often carried by populations of neurons rather than individual neurons. Also propagation of suprathreshold spiking activity involves populations of neurons. Empirical studies addressing cortical function directly thus require recordings from populations of neurons with high resolution. Here we describe an optical method and a deconvolution algorithm to record neural activity from up to 100 neurons with single-cell and single-spike resolution. This method relies on detection of the transient increases in intracellular somatic calcium concentration associated with suprathreshold electrical spikes (action potentials) in cortical neurons. High temporal resolution of the optical recordings is achieved by a fast random-access scanning technique using acousto-optical deflectors (AODs)1. Two-photon excitation of the calcium-sensitive dye results in high spatial resolution in opaque brain tissue2. Reconstruction of spikes from the fluorescence calcium recordings is achieved by a maximum-likelihood method. Simultaneous electrophysiological and optical recordings indicate that our method reliably detects spikes (&gt;97% spike detection efficiency), has a low rate of false positive spike detection (&lt; 0.003 spikes/sec), and a high temporal precision (about 3 msec) 3. This optical method of spike detection can be used to record neural activity in vitro and in anesthetized animals in vivo3,4.

Understanding the function of the vertebrate central nervous system requires recordings from many neurons because cortical function arises on the level of populations of neurons. Here we describe an optical method to record suprathreshold neural activity with single-cell and single-spike resolution, dithered random-access scanning. This method records somatic fluorescence calcium signals from up to 100 neurons with high temporal resolution. A maximum-likelihood algorithm deconvolves the underlying suprathreshold neural activity from the somatic fluorescence calcium signals. This method reliably detects spikes with high detection efficiency and a low rate of false positives and can be used to study neural populations in vitro and in vivo.

Signaling of information in the vertebrate central nervous system is often carried by populations of neurons rather than individual neurons. Also ...

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Current neurophysiological research has the aim to develop methodologies to investigate the signal route from neuron to neuron, namely in the transitions from spikes to Local Field Potentials (LFPs) and from LFPs to spikes.
LFPs have a complex dependence on spike activity and their relation is still poorly understood1. The elucidation of these signal relations would be helpful both for clinical diagnostics (e.g. stimulation paradigms for Deep Brain Stimulation) and for a deeper comprehension of neural coding strategies in normal and pathological conditions (e.g. epilepsy, Parkinson disease, chronic pain). To this aim, one has to solve technical issues related to stimulation devices, stimulation paradigms and computational analyses. Therefore, a custom-made stimulation device was developed in order to deliver stimuli well regulated in space and time that does not incur in mechanical resonance. Subsequently, as an exemplification, a set of reliable LFP-spike relationships was extracted.
The performance of the device was investigated by extracellular recordings, jointly spikes and LFP responses to the applied stimuli, from the rat Primary Somatosensory cortex. Then, by means of a multi-objective optimization strategy, a predictive model for spike occurrence based on LFPs was estimated.
The application of this paradigm shows that the device is adequately suited to deliver high frequency tactile stimulation, outperforming common piezoelectric actuators. As a proof of the efficacy of the device, the following results were presented: 1) the timing and reliability of LFP responses well match the spike responses, 2) LFPs are sensitive to the stimulation history and capture not only the average response but also the trial-to-trial fluctuations in the spike activity and, finally, 3) by using the LFP signal it is possible to estimate a range of predictive models that capture different aspects of the spike activity.

To elucidate the complex transition from Local Field Potentials (LFPs) to spikes a suitable stimulator for light mechanical peripheral stimuli was built. As an application, the spiking activities recorded from somatosensory cortex were analyzed by a multi-objective optimization strategy. The results demonstrated that the proposed stimulator was able to deliver tactile stimuli with millisecond and millimeter precisions.

Current neurophysiological research has the aim to develop methodologies to investigate the signal route from neuron to neuron, namely in the transitions ...

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

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.

Closed-loop protocols are becoming increasingly widespread in modern day electrophysiology. We present a simple, versatile and inexpensive way to perform complex electrophysiological protocols in cortical pyramidal neurons in vitro, using a desktop computer and a digital acquisition board.

Experimental neuroscience is witnessing an increased interest in the development and application of novel and often complex, closed-loop protocols, where ...

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Information coding in the Central Nervous System (CNS) remains unexplored. There is mounting evidence that, even at a very low level, the representation of a given stimulus might be dependent on context and history. If this is actually the case, bi-directional interactions between the brain (or if need be a reduced model of it) and sensory-motor system can shed a light on how encoding and decoding of information is performed. Here an experimental system is introduced and described in which the activity of a neuronal element (i.e., a network of neurons extracted from embryonic mammalian hippocampi) is given context and used to control the movement of an artificial agent, while environmental information is fed back to the culture as a sequence of electrical stimuli. This architecture allows a quick selection of diverse encoding, decoding, and learning algorithms to test different hypotheses on the computational properties of neuronal networks.

In this paper, an experimental framework to perform closed-loop experiments is presented, in which information processing (i.e., coding and decoding) and learning of neuronal assemblies are studied during the continuous interaction with a robotic body.

Information coding in the Central Nervous System (CNS) remains unexplored. There is mounting evidence that, even at a very low level, the representation ...

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo

The way neurons process information depends both on their intrinsic membrane properties and on the dynamics of the afferent synaptic network. In particular, endogenously-generated network activity, which strongly varies as a function of the state of vigilance, significantly modulates neuronal computation. To investigate how different spontaneous cerebral dynamics impact single neurons&#39; integrative properties, we developed a new experimental strategy in the rat consisting in suppressing in vivo all cerebral activity by means of a systemic injection of a high dose of sodium pentobarbital. Cortical activities, continuously monitored by combined electrocorticogram (ECoG) and intracellular recordings are progressively slowed down, leading to a steady isoelectric profile. This extreme brain state, putting the rat into a deep comatose, was carefully monitored by measuring the physiological constants of the animal throughout the experiments. Intracellular recordings allowed us to characterize and compare the integrative properties of the same neuron embedded into physiologically relevant cortical dynamics, such as those encountered in the sleep-wake cycle, and when the brain was fully silent.

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo

This procedure performs long-lasting in vivo intracellular recordings from single neurons during physiologically relevant cerebral states and after complete abolition of ongoing electrical activities, resulting in an isoelectric brain state. The physiological constants of the animal are carefully monitored during the transition to the artificial comatose condition.

The way neurons process information depends both on their intrinsic membrane properties and on the dynamics of the afferent synaptic network. In ...

Extracellular Recording of Neuronal Activity Combined with Microiontophoretic Application of Neuroactive Substances in Awake Mice

Differences in the activity of neurotransmitters and neuromodulators, and consequently different neural responses, can be found between anesthetized and awake animals. Therefore, methods allowing the manipulation of synaptic systems in awake animals are required in order to determine the contribution of synaptic inputs to neuronal processing unaffected by anesthetics. Here, we present methodology for the construction of electrodes to simultaneously record extracellular neural activity and release multiple neuroactive substances at the vicinity of the recording sites in awake mice. By combining these procedures, we performed microiontophoretic injections of gabazine to selectively block GABAA receptors in neurons of the inferior colliculus of head-restrained mice. Gabazine successfully modified neural response properties such as the frequency response area and stimulus-specific adaptation. Thus, we demonstrate that our methods are suitable for recording single-unit activity and for dissecting the role of specific neurotransmitter receptors in auditory processing.
The main limitation of the described procedure is the relatively short recording time (~3 hr), which is determined by the level of habituation of the animal to the recording sessions. On the other hand, multiple recording sessions can be performed in the same animal. The advantage of this technique over other experimental procedures used to manipulate the level of neurotransmission or neuromodulation (such as systemic injections or the use of optogenetic models), is that the drug effect is confined to the local synaptic inputs to the target neuron. In addition, the custom-manufacture of electrodes allows adjustment of specific parameters according to the neural structure and type of neuron of interest (such as the tip resistance for improving the signal-to-noise ratio of the recordings).

We present methods for the construction of electrodes to simultaneously record extracellular neural activity and release multiple neuroactive substances at the vicinity of the recording sites in awake mice. This technique allows the detailed analysis of putative local synaptic inputs to the neuron of interest.

Differences in the activity of neurotransmitters and neuromodulators, and consequently different neural responses, can be found between anesthetized and ...

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Micro-electrode arrays (MEAs) can be used to investigate drug toxicity, design paradigms for next-generation personalized medicine, and study network dynamics in neuronal cultures. In contrast with more traditional methods, such as patch-clamping, which can only record activity from a single cell, MEAs can record simultaneously from multiple sites in a network, without requiring the arduous task of placing each electrode individually. Moreover, numerous control and stimulation configurations can be easily applied within the same experimental setup, allowing for a broad range of dynamics to be explored. One of the key dynamics of interest in these in vitro studies has been the extent to which cultured networks display properties indicative of learning. Mouse neuronal cells cultured on MEAs display an increase in response following training induced by electrical stimulation. This protocol demonstrates how to culture neuronal cells on MEAs; successfully record from over 95% of the plated dishes; establish a protocol to train the networks to respond to patterns of stimulation; and sort, plot, and interpret the results from such experiments. The use of a proprietary system for stimulating and recording neuronal cultures is demonstrated. Software packages are also used to sort neuronal units. A custom-designed graphical user interface is used to visualize post-stimulus time histograms, inter-burst intervals, and burst duration, as well as to compare the cellular response to stimulation before and after a training protocol. Finally, representative results and future directions of this research effort are discussed.

Mouse neuronal cells cultured on multi-electrode arrays display an increase in response following electrical stimulation. This protocol demonstrates how to culture neurons, how to record activity, and how to establish a protocol to train the networks to respond to patterns of stimulation.

Micro-electrode arrays (MEAs) can be used to investigate drug toxicity, design paradigms for next-generation personalized medicine, and study network ...

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms

Fluorescent genetically encoded calcium indicators have contributed greatly to our understanding of neural dynamics from the level of individual neurons to entire brain circuits. However, neural responses may vary due to prior experience, internal states, or stochastic factors, thus generating the need for methods that can assess neural function across many individuals at once. Whereas most recording techniques examine a single animal at a time, we describe the use of wide-field microscopy to scale up neuronal recordings to dozens of Caenorhabditis elegans or other sub-millimeter-scale organisms at once. Open-source hardware and software allow great flexibility in programming fully automated experiments that control the intensity and timing of various stimulus types, including chemical, optical, mechanical, thermal, and electromagnetic stimuli. In particular, microfluidic flow devices provide precise, repeatable, and quantitative control of chemosensory stimuli with sub-second time resolution. The NeuroTracker semi-automated data analysis pipeline then extracts individual and population-wide neural responses to uncover functional changes in neural excitability and dynamics. This paper presents examples of measuring neuronal adaptation, temporal inhibition, and stimulus crosstalk. These techniques increase the precision and repeatability of stimulation, allow the exploration of population variability, and are generalizable to other dynamic fluorescent signals in small biosystems from cells and organoids to whole organisms and plants.

We present a method for the flexible chemical and multimodal stimulation and recording of simultaneous neural activity from many Caenorhabditis elegans worms. This method uses microfluidics, open-source hardware and software, and supervised automated data analysis to enable the measurement of neuronal phenomena such as adaptation, temporal inhibition, and stimulus crosstalk.

Fluorescent genetically encoded calcium indicators have contributed greatly to our understanding of neural dynamics from the level of individual neurons ...

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

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An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Using Affordable LED Arrays for Photo-Stimulation of Neurons

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo

Extracellular Recording of Neuronal Activity Combined with Microiontophoretic Application of Neuroactive Substances in Awake Mice

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms