Name: open-source real-time closed-loop electrical threshold tracking for translational pain research
Uploaded: 2023-04-21T14:30:00
Duration: 10 min 28 s
Description: Watch this Scientific Journal Video about Open-Source Real-Time Closed-Loop Electrical Threshold Tracking for Translational Pain Research at JoVE.com

We would like to thank our funders for their support: Academy of Medical Sciences (J.P.D., A.E.P.), Versus Arthritis (J.P.D., A.E.P.), Jean Golding Institute Seedcorn Grant (J.P.D., A.E.P., G.W., A.C.S., M.M.P.), and Biotechnology and Biological Sciences Research Council collaborative training partnership doctoral studentship with Eli Lilly (G.W.T.N.). We would like to extend our thanks to all the contributors to the development of APTrack. We would also like to thank our volunteers who participated in the microneurography experiments and our Patient and Public Involvement and Engagement collaborators for their invaluable contributions.

<ol>
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E., Patapoutian, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nociceptors:+The+sensors+of+the+pain+pathway.">Nociceptors: The sensors of the pain pathway.</a> Journal of Clinical Investigation. 120 (11), 3760-3772 (2010).</li><li>Serra, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microneurographic+identification+of+spontaneous+activity+in+C-nociceptors+in+neuropathic+pain+states+in+humans+and+rats.">Microneurographic identification of spontaneous activity in C-nociceptors in neuropathic pain states in humans and rats.</a> Pain. 153 (1), 42-55 (2012).</li><li>Serra, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hyperexcitable+C+nociceptors+in+fibromyalgia.">Hyperexcitable C nociceptors in fibromyalgia.</a> Annals of Neurology. 75 (2), 196-208 (2014).</li><li>Namer, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Specific+changes+in+conduction+velocity+recovery+cycles+of+single+nociceptors+in+a+patient+with+erythromelalgia+with+the+I848T+gain-of-function+mutation+of+Nav1.7.">Specific changes in conduction velocity recovery cycles of single nociceptors in a patient with erythromelalgia with the I848T gain-of-function mutation of Nav1.7.</a> Pain. 156 (9), 1637-1646 (2015).</li><li>Kleggetveit, I. 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N., Ringkamp, M., Guan, Y., Campbell, J. N., John, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bonica+Award+Lecture:+Peripheral+neuronal+hyperexcitability:+The+&amp;#34;low-hanging&amp;#34;+target+for+safe+therapeutic+strategies+in+neuropathic+pain.">Bonica Award Lecture: Peripheral neuronal hyperexcitability: The &amp;#34;low-hanging&amp;#34; target for safe therapeutic strategies in neuropathic pain.</a> Pain. 161, S14-S26 (2020).</li><li>Middleton, S. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Studying+human+nociceptors:+From+fundamentals+to+clinic.">Studying human nociceptors: From fundamentals to clinic.</a> Brain. 144 (5), 1312-1335 (2021).</li><li>Marshall, A., Alam, U., Themistocleous, A., Calcutt, N., Marshall, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Novel+and+emerging+electrophysiological+biomarkers+of+diabetic+neuropathy+and+painful+diabetic+neuropathy.">Novel and emerging electrophysiological biomarkers of diabetic neuropathy and painful diabetic neuropathy.</a> Clinical Therapeutics. 43 (9), 1441-1456 (2021).</li><li>Themistocleous, A. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Axonal+excitability+does+not+differ+between+painful+and+painless+diabetic+or+chemotherapy-induced+distal+symmetrical+polyneuropathy+in+a+multicenter+observational+study.">Axonal excitability does not differ between painful and painless diabetic or chemotherapy-induced distal symmetrical polyneuropathy in a multicenter observational study.</a> Annals of Neurology. 91 (4), 506-520 (2022).</li><li>Bostock, H., Cikurel, K., Burke, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Threshold+tracking+techniques+in+the+study+of+human+peripheral+nerve.">Threshold tracking techniques in the study of human peripheral nerve.</a> Muscle Nerve. 21 (2), 137-158 (1998).</li><li>Kiernan, M. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+axonal+excitability:+Consensus+guidelines.">Measurement of axonal excitability: Consensus guidelines.</a> Clinical Neurophysiology. 131 (1), 308-323 (2020).</li><li>Sauer, S. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Can+receptor+potentials+be+detected+with+threshold+tracking+in+rat+cutaneous+nociceptive+terminals.">Can receptor potentials be detected with threshold tracking in rat cutaneous nociceptive terminals.</a> Journal of Neurophysiology. 94 (1), 219-225 (2005).</li><li>Vallbo, A. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microneurography:+How+it+started+and+how+it+works.">Microneurography: How it started and how it works.</a> Journal of Neurophysiology. 120 (3), 1415-1427 (2018).</li><li>Torebjork, H., Hallin, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+method+for+classification+of+C-unit+activity+in+intact+human+skin+nerves.">A new method for classification of C-unit activity in intact human skin nerves.</a> Advances in Pain Research and Therapy. 1, 29-34 (1976).</li><li>Brown, G. L., Holmes, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effects+of+activity+on+mammalian+nerve+fibres+of+low+conduction+velocity.">The effects of activity on mammalian nerve fibres of low conduction velocity.</a> Proceedings of the Royal Society of London. Series B: Biological Sciences. 144 (918), 1-14 (1956).</li><li>Obreja, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patterns+of+activity-dependent+conduction+velocity+changes+differentiate+classes+of+unmyelinated+mechano-insensitive+afferents+including+cold+nociceptors,+in+pig+and+in+human.">Patterns of activity-dependent conduction velocity changes differentiate classes of unmyelinated mechano-insensitive afferents including cold nociceptors, in pig and in human.</a> Pain. 148 (1), 59-69 (2010).</li><li>Serra, J., Campero, M., Ochoa, J., Bostock, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Activity-dependent+slowing+of+conduction+differentiates+functional+subtypes+of+C+fibres+innervating+human+skin.">Activity-dependent slowing of conduction differentiates functional subtypes of C fibres innervating human skin.</a> Journal of Physiology. 515, 799-811 (1999).</li><li>Weidner, C., Schmidt, R., Schmelz, M., Torebjork, H. E., Handwerker, H. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Action+potential+conduction+in+the+terminal+arborisation+of+nociceptive+C-fibre+afferents.">Action potential conduction in the terminal arborisation of nociceptive C-fibre afferents.</a> Journal of Physiology. 547, 931-940 (2003).</li><li>Siegle, J. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Open+Ephys:+An+open-source,+plugin-based+platform+for+multichannel+electrophysiology.">Open Ephys: An open-source, plugin-based platform for multichannel electrophysiology.</a> Journal of Neural Engineering. 14 (4), 045003 (2017).</li><li>Sanders, J. I., Kepecs, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+low-cost+programmable+pulse+generator+for+physiology+and+behavior.">A low-cost programmable pulse generator for physiology and behavior.</a> Frontiers in Neuroengineering. 7, 43 (2014).</li><li>Zimmermann, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenotyping+sensory+nerve+endings+in+vitro+in+the+mouse.">Phenotyping sensory nerve endings in vitro in the mouse.</a> Nature Protocols. 4 (2), 174-196 (2009).</li><li>Dunham, J. P., Sales, A. C., Pickering, A. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrasound-guided,+open-source+microneurography:+Approaches+to+improve+recordings+from+peripheral+nerves+in+man.">Ultrasound-guided, open-source microneurography: Approaches to improve recordings from peripheral nerves in man.</a> Clinical Neurophysiology. 129 (11), 2475-2481 (2018).</li><li>Levitt, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transformed+up-down+methods+in+psychoacoustics.">Transformed up-down methods in psychoacoustics.</a> Journal of the Acoustical Society of America. 49 (2), 467 (1971).</li><li>Turnquist, B., RichardWebster, B., Namer, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+detection+of+latency+tracks+in+microneurography+recordings+using+track+correlation.">Automated detection of latency tracks in microneurography recordings using track correlation.</a> Journal of Neuroscience Methods. 262, 133-141 (2016).</li><li>Kiernan, M. C., Burke, D., Andersen, K. V., Bostock, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+measures+of+axonal+excitability:+A+new+approach+in+clinical+testing.">Multiple measures of axonal excitability: A new approach in clinical testing.</a> Muscle Nerve. 23 (3), 399-409 (2000).</li></ol>

G.W.T.N. is a BBSRC Collaborative Training Partnership Doctoral Studentship with the University of Bristol and Eli Lilly and Company (BB/T508342/1). A.P.N. is a current employee of Eli Lilly and Company and may own stock in this company.

APTrack is a software plugin for use with the Open Ephys platform. We have chosen this platform as it is open-source, flexible, and cheap to implement. Not including the cost of the constant current stimulator, all the equipment required to start using the plugin could be purchased for around $5,000 USD at the time of writing. We hope this will enable researchers to implement APTrack in their peripheral nerve electrophysiology studies more easily. Furthermore, researchers can freely modify the software to fit their experimental needs. Importantly, this tool has allowed the electrical threshold tracking of single C-fiber nociceptors, for the first time, in humans.
The higher the signal-to-noise ratio, the better the algorithms can identify action potentials. The signal-to-noise ratio during microneurography was sufficient in the majority of our recordings, but users must be alert to the risk of signal degradation over time. This is particularly important for longer experimental protocols, because if the tracked action potential&#39;s amplitude drops below the detection threshold, the stimulation amplitude will be increased mistakenly; this can be mitigated by experimenters monitoring the plugin and then adjusting the settings if required. The signal-to-noise ratio is improved with bandpass filtering, but larger transients may still be misidentified as action potentials should they arrive during the search box time window. The risk of misidentifying transient noise as an action potential can be reduced by narrowing the time window during which the plugin searches for action potentials and by optimizing the threshold settings. However, there are still situations one may encounter that impede the plugin&#39;s performance. Spontaneous activity may cause difficulties if larger-amplitude action potentials fall within the algorithm&#39;s search box window, as they will be misidentified as the target action potential. Additionally, spontaneous activity in the neuron of interest may mean that the electrical stimulation falls during its refractory period, causing failure to generate an action potential. Difficulties using the software can also arise when primary afferent neurons exhibit flip-flop, whereby alternate terminal branches of a single neuron are stimulated, thus causing the evoked action potential to have two (or more) baseline latencies that are mutually exclusive20. During recordings from neurons exhibiting flip-flop with high signal-to-noise ratios, we successfully performed latency and electrical threshold tracking by increasing the search box width to encapsulate all the potential conduction velocities that the neuron exhibited. However, the electrical threshold may vary depending on the terminal branch of the neuron that is being excited, which is likely in part due to differences in the distance from the site of the electrical stimulation to the alternate nociceptor terminals. Additional work on the action potential identification process to include, for example, template matching is feasible and could be integrated into this software. The GUI plugins for band-stop or adaptive noise filtration could also be used upstream of APTrack in the signal chain should they be developed.
We consider the electrical threshold determined to be the current required to elicit an action potential 50% of the time, over a user-defined number of electrical stimuli, typically 2-10. The morphology of electrical stimulation is 0.5 ms and positive, square wave pulses. This is not the same as determining the rheobase, a commonly used measure of neuronal excitability. The plugin could be adapted to determine the rheobase. However, we pursued a simpler measure, as dynamic changes in excitability, such as those hypothesized to occur during heating, would have been more difficult to quantify with rheobase changes than our electrical threshold estimate.
This software can be used in both human and rodent experiments. This is made possible by flexible support for the electrical stimulation systems. The software will work with any stimulator that accepts an analog command voltage or can be manually interfaced with a stepper motor. For microneurography, we used it with a CE-marked constant current stimulator that was designed for use in human research and had its stimulation controlled by a dial. Stimulators that accept analog voltage commands can be noisy as they do not disconnect the circuit between stimuli, meaning any 50/60 Hz hum or noise on the analog input will be transmitted to the recording. A stimulator that requires an additional TLL trigger signal to connect the circuit, permitting a stimulus at a current analogous to the analog voltage input to be generated, is ideal for use with the plugin. This prevents the noise from being transmitted to the recording between stimuli.
The software uses a simple up-down method to estimate the electrical threshold. This has been used in psychophysics tests for many decades25. In line with the up-down method, the electrical threshold tracking algorithm for modulating the stimulation amplitude only considers the previous stimulation&#39;s amplitude and response when calculating the next stimulation&#39;s amplitude. This means that the stimulation amplitude will oscillate around the true electrical threshold, thus producing a 50% firing rate, assuming the threshold is stable. The minimum size of an increment or decrement is 0.01 V; this is equivalent to 0.01 mA assuming the stimulator has a 1 V:1 mA input-to-output ratio and sufficient resolution to achieve step changes this small. The plugin will update the live estimate of the target action potential&#39;s electrical threshold every time it reaches a 50% firing rate over a user-defined number of previous stimuli (2-10). Post hoc, we recommend using a rolling average of the stimulation amplitude over the last 2-10 stimuli to estimate the electrical threshold, and it should be noted that this estimate will only be accurate when the firing rate is relatively stable at 50%. In both the live and post hoc&#160;estimates of the electrical threshold, there is a balance of resolution, reliability, and time to consider. Using smaller increment and decrement steps will increase the accuracy of the electrical threshold estimate but will increase the time taken to find the new electrical threshold initially and following perturbation. Calculating the electrical threshold over a greater number of previous stimuli will provide better reliability but will increase the time required to reach an accurate estimate.
APTrack was designed for use in peripheral nerve recordings, specifically to track the electrical thresholds of C-fibers during experimental and pathological perturbations over periods where the action potential latency may vary depending on the underlying neuronal activity. This method will enable the examination of not only axonal excitability but also of nociceptor generator potentials in healthy volunteers and patients. We anticipate that other fields of electrophysiology may adopt and adapt this tool for use in any experiment that requires the electrical threshold tracking of a stimulus-locked activity. For example, this could as easily be adapted for optogenetic stimulation with light pulses driven from APTrack. The plugin is open-source and available to researchers under a GPLv3 license. It is built on the Open Ephys platform, which is an adaptable, low-cost, open-source data acquisition system. The plugin provides additional hooks for downstream plugins to extract the action potential information and provide additional user interfaces or adaptative paradigms. The plugin provides a simple user interface for the visualization and latency tracking of action potentials in real time. It can also play back previous data and visualize them using the temporal raster plot. Furthermore, it can also perform latency tracking during the playback of previous data. While there are other software packages available for real-time latency tracking, they are not open-source and cannot perform electrical threshold tracking26,27. APTrack has an advantage over traditional methods of identifying constant latency action potentials from voltage traces as it uses a temporal raster plot for the data visualization. Furthermore, our experiences of using it in experiments with low signal-to-noise ratios have indicated that the temporal raster plot visualization method allows the identification of constant latency action potentials that may have been otherwise missed.
Whole-nerve threshold tracking is a widely used method for assessing axonal excitability13. Single-neuron electrical threshold tracking in rodent C-fibers has been used previously to quantify nociceptor excitability14, and its utility in humans is recognized10,11; however, until now, this was not possible. We provide a novel, open-source tool to directly measure single nociceptor excitability in both rodent and human peripheral nerve electrophysiological studies. APTrack enables the real-time, open-source, electrical threshold tracking of single-neuron action potentials in humans, for the first time. We anticipate that it will facilitate translational studies of nociceptors between rodents and humans.

Nociceptors are primary afferent neurons in the peripheral nervous system that are activated by overtly or potentially tissue-damaging events and play a critical protective role in acute pain1. Electrophysiological recordings from C-fiber and A&#948;-fiber nociceptors in animal models, healthy human volunteers, and patients have revealed sensitization and abnormal spontaneous activity in a diverse range of pain conditions2,3,4,5,6,7. Understanding the mechanisms that underlie these changes in nociceptor excitability in patients could enable targeted therapeutic interventions8. However, there are few tools to assess nociceptor excitability directly, particularly in patients9, but the potential for the utility of such tools is well recognized10,11.
Whole-nerve electrical threshold tracking can be used to examine axonal excitability in humans12. However, as large, myelinated, peripheral neurons contribute disproportionally to the amplitude of the sensory compound action potential, whole-nerve electrical threshold tracking does not allow the assessment of C-fiber function11,13. Indeed, in a previous study, whole-nerve electrical threshold tracking in chronic neuropathic pain cohorts with diabetic neuropathy and chemotherapy-induced polyneuropathy showed no differences in axonal excitability11.
In a previous study, electrical threshold tracking at the single-neuron level was used to examine the excitability of C-fiber nociceptors during teased-fiber recordings in an ex vivo rat skin-nerve preparation14. The authors demonstrated that an increased potassium concentration, acidic conditions, and bradykinin all increased C-fiber nociceptor excitability, as reflected by a reduced electrical threshold for action potential generation. Furthermore, heating the receptive field of the heat-sensitive nociceptors reduced their electrical threshold, whereas heat-insensitive nociceptors exhibited an increase in their electrical threshold14. This provides important proof that single-neuron electrical threshold tracking is possible and can be of utility, but there are currently no software and/or hardware solutions available to enable such investigations, particularly for human studies.
In humans, microneurography is the only available method to directly assess the electrophysiological properties of C-fibers15. This approach has been used to demonstrate nociceptor dysfunction in patients with chronic pain2,3,4,5,6,7. Microneurography can detect single-neuron action potentials; however, due to the low signal-to-noise ratios, researchers use the marking technique to characterize C-fiber activity16. In the marking technique, suprathreshold electrical stimulation is applied to C-fiber receptive fields in the skin. This electrical stimulation generates an action potential that occurs at a constant latency, which is determined by the C-fiber&#39;s conduction velocity. C-fibers exhibit activity-dependent slowing, whereby their conduction velocity reduces and, therefore, their conduction latency increases during periods of action potential discharge17. Under basal conditions, C-fibers do not normally generate action potentials in the absence of noxious stimuli, and, therefore, their conduction latency in response to low-frequency electrical stimulation is constant. Mechanical, thermal, or pharmacological stimuli, which evoke firing, induce activity-dependent slowing, which increases the latency of the action potentials evoked by concomitant low-frequency electrical stimulation. This allows the objective identification of responses to the applied non-electrical stimuli in the context of a low signal-to-noise ratio. Therefore, activity-dependent slowing can be used to functionally characterize C-fibers16. Indeed, different functional classes of C-fibers exhibit distinctive patterns of activity-dependent slowing in electrical stimulation paradigms that involve varying the stimulation frequency18,19. This variability in the latency of C-fiber action potentials presents a challenge for algorithms designed to monitor them.
Ongoing activity in a nociceptor leads to increased variability in its latency during low-frequency electrical stimulation, and this is again due to activity-dependent slowing. This increased variability, or jitter, is a quantifiable proxy measure of excitability2. Further causes of variability in action potential latency include flip-flop, where alternate terminal branches of a single neuron are stimulated, which causes the evoked action potential to have two (or more) baseline latencies that are mutually exclusive20. Finally, changes in the temperature of a peripheral neuron&#39;s terminal branches also cause action potential latency changes in a thermodynamic manner, with warming increasing the conduction velocity and cooling slowing the conduction velocity19. Thus, any software seeking to perform closed-loop electrical threshold tracking of nociceptive C-fibers must allow for changes in latency in electrically evoked action potentials.
To achieve our goal of cross-species electrical threshold tracking of C-fiber nociceptors, we developed APTrack, an open-source software plugin for the Open Ephys platform21, to enable real-time, closed-loop, electrical threshold tracking, and latency tracking. We provide proof-of-concept data demonstrating that C-fiber nociceptor electrical threshold tracking during human microneurography is possible. Furthermore, we show that this tool can be used in rodent ex vivo teased-fiber electrophysiology, thus enabling translational studies between humans and rodents. Here, we will describe in detail how researchers can implement and use this tool to aid their study of nociceptor function and excitability.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>12V DC Power Supply&#160;</td>
			<td>NA</td>
			<td>NA</td>
			<td>To power uStepper S-lite. Required for dial-controlled stimulators.</td>
		</tr>
		<tr>
			<td>36 Pin Electrode Adapter Board</td>
			<td>Intan Technology</td>
			<td>C3410</td>
			<td>APTrack Dependency. For connecting electrode input to headstage. $255 USD as of March 2021.</td>
		</tr>
		<tr>
			<td>APTrack Plugin</td>
			<td>NA</td>
			<td>NA</td>
			<td>https://github.com/Microneurography/APTrack</td>
		</tr>
		<tr>
			<td>Bipolar Ag/AgCl Recording Electrode</td>
			<td>Custom</td>
			<td>NA</td>
			<td>Recording electrode for the skin-nerve preparation. Or equivalent.</td>
		</tr>
		<tr>
			<td>Bipolar Concentric Stimulating Electrode</td>
			<td>World Precision Instruments</td>
			<td>SNE-100</td>
			<td>For electrical stimulation in the mouse skin-nerve preparation. Or equivalent.</td>
		</tr>
		<tr>
			<td>Bipolar Transcutaneous Stimulating Electrode</td>
			<td>Custom</td>
			<td>NA</td>
			<td>For transcutaneous electrical stimulation while searching for single-neuron action potentials during microneurography.</td>
		</tr>
		<tr>
			<td>BNC T Splitter (1+)</td>
			<td>NA</td>
			<td>NA</td>
			<td>APTrack Dependency. Any standard BNC T splitter.</td>
		</tr>
		<tr>
			<td>BNC to BNC cables (3+)</td>
			<td>NA</td>
			<td>NA</td>
			<td>APTrack Dependency. Any standard BNC cables.&#160;</td>
		</tr>
		<tr>
			<td>C6H11NaO7</td>
			<td>Merck</td>
			<td>S2054</td>
			<td>Skin-nerve preparation synthetic interstitial fluid constituent. Or equivalent.</td>
		</tr>
		<tr>
			<td>CaCl2</td>
			<td>Merck</td>
			<td>C5670</td>
			<td>Skin-nerve preparation synthetic interstitial fluid constituent. Or equivalent.</td>
		</tr>
		<tr>
			<td>Digitimer DS4 Constant Current Stimulator</td>
			<td>Digitimer</td>
			<td>DS4</td>
			<td>Constant current stiulator for animal research. &#163;1,695 GBP as of September 2022.&#160;</td>
		</tr>
		<tr>
			<td>Digitimer DS7 Constant Current Stimulator</td>
			<td>Digitimer</td>
			<td>DS7A</td>
			<td>Constant current stiulator for human research. &#163;3,400 GBP as of September 2022.&#160;</td>
		</tr>
		<tr>
			<td>Electroaccupuncture Classic Plus Stimulating Electrodes</td>
			<td>Harmony Medical</td>
			<td>NA</td>
			<td>For fixed position intradermal electrical stimulation of the dorsal aspect of the foot during human microneurography.</td>
		</tr>
		<tr>
			<td>Glucose</td>
			<td>Fisher Scientific</td>
			<td>G/0450/60</td>
			<td>Skin-nerve preparation synthetic interstitial fluid constituent. Or equivalent.</td>
		</tr>
		<tr>
			<td>HDMI Cable</td>
			<td>NA</td>
			<td>NA</td>
			<td>APTrack Dependency. Any standard passive HMDI cable. To connect OE I/O Board to OE Acquisition Board.</td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>Merck</td>
			<td>P9541</td>
			<td>Skin-nerve preparation synthetic interstitial fluid constituent. Or equivalent.</td>
		</tr>
		<tr>
			<td>MgSO4</td>
			<td>Acros Organics</td>
			<td>213115000</td>
			<td>Skin-nerve preparation synthetic interstitial fluid constituent. Or equivalent.</td>
		</tr>
		<tr>
			<td>Mineral Oil</td>
			<td>Merck</td>
			<td>330779</td>
			<td>Electrical insulation for nerve recordings in th skin-nerve preparation. Or equivalent.</td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>Merck</td>
			<td>S9888</td>
			<td>Skin-nerve preparation synthetic interstitial fluid constituent. Or equivalent.</td>
		</tr>
		<tr>
			<td>NaHCO3</td>
			<td>Merck</td>
			<td>S6014</td>
			<td>Skin-nerve preparation synthetic interstitial fluid constituent. Or equivalent.</td>
		</tr>
		<tr>
			<td>NaHCO3</td>
			<td>Merck</td>
			<td>S0751</td>
			<td>Skin-nerve preparation synthetic interstitial fluid constituent. Or equivalent.</td>
		</tr>
		<tr>
			<td>Open Ephys Acquisition Board</td>
			<td>Open Ephys</td>
			<td>NA</td>
			<td>APTrack Dependency. Includes USB cable to connect to computer and mains socket power supply. &#8364;2,955 EUR as of September 2022.</td>
		</tr>
		<tr>
			<td>Open Ephys Graphical User Interface</td>
			<td>Open Ephys</td>
			<td>NA</td>
			<td>https://github.com/open-ephys/plugin-GUI</td>
		</tr>
		<tr>
			<td>Open Ephys I/O Board</td>
			<td>Open Ephys</td>
			<td>NA</td>
			<td>APTrack Dependency. For ADC voltage inputs via BNC cables. &#8364;12.5 EUR without connectors, &#8364;85 EUR with connectors as of September 2022.</td>
		</tr>
		<tr>
			<td>PulsePal V2</td>
			<td>Sanworks</td>
			<td>1102</td>
			<td>APTrack Dependency. Open-source DAC and train generator. $725 USD pre-assembled as of September 2022. Approx. $275 USD for self-assembly.</td>
		</tr>
		<tr>
			<td>RHD 6ft SPI Cable</td>
			<td>Intan Technology</td>
			<td>C3206</td>
			<td>APTrack Dependency. For connecting headstage to OE Acquisition Board. $295 USD as of March 2021</td>
		</tr>
		<tr>
			<td>RHD2216 16ch Bipolar Headstage</td>
			<td>Intan Technology</td>
			<td>C3313</td>
			<td>APTrack Dependency. For data acquisition and digitization. $725 USD as of March 2021. Or equivalent RHD2000 series headstage.</td>
		</tr>
		<tr>
			<td>Sucrose</td>
			<td>Fisher Scientific</td>
			<td>S/8560/60</td>
			<td>Skin-nerve preparation synthetic interstitial fluid constituent. Or equivalent.</td>
		</tr>
		<tr>
			<td>TCS-II Thermal Stimulator</td>
			<td>QST.Lab</td>
			<td>NA</td>
			<td>For thermal stimualtion of nociceptor receptive fields during human microneurography.</td>
		</tr>
		<tr>
			<td>Tungsten Microelectrode Pair (Active + Reference)</td>
			<td>FHC</td>
			<td>30085</td>
			<td>For microneurography recordings. 35mm.</td>
		</tr>
		<tr>
			<td>Ultrasound Scanner iQ+&#160;</td>
			<td>Butterfly Network</td>
			<td>NA</td>
			<td>For ultrasound-guided electrode insertion during microneurography.</td>
		</tr>
		<tr>
			<td>USB 3.0 5kV RMS Isolation</td>
			<td>Inota Technology</td>
			<td>7055-D</td>
			<td>For isolating human microneuroography participant from computer. &#8364;459 EUR as of September 2022.</td>
		</tr>
		<tr>
			<td>USB-A to micro USB-B cable (2)</td>
			<td>NA</td>
			<td>NA</td>
			<td>APTrack Dependency. To connect computer to PulsePal and to uStepper S-lite if using stepper-stimulator interfacing.&#160;</td>
		</tr>
		<tr>
			<td>uStepper S-lite + NEMA17 motor</td>
			<td>uStepper</td>
			<td>NA</td>
			<td>To interface with stimulators via a control dial. &#8364;50 EUR as of September 2022.</td>
		</tr>
		<tr>
			<td>Von Frey Filaments</td>
			<td>Ugo Basile</td>
			<td>37450-275</td>
			<td>For mechanical stimulation of receptive fields during sensory phenotyping of nociceptors.</td>
		</tr>
	</tbody>
</table>

open-source real-time closed-loop electrical threshold tracking for translational pain research

Nociceptors are a class of primary afferent neurons that signal potentially harmful noxious stimuli. An increase in nociceptor excitability occurs in acute and chronic pain conditions. This produces abnormal ongoing activity or reduced activation thresholds to noxious stimuli. Identifying the cause of this increased excitability is required for the development and validation of mechanism-based treatments. Single-neuron electrical threshold tracking can quantify nociceptor excitability. Therefore, we have developed an application to allow such measurements and demonstrate its use in humans and rodents. APTrack provides real-time data visualization and action potential identification using a temporal raster plot. Algorithms detect action potentials by threshold crossing and monitor their latency after electrical stimulation. The plugin then modulates the electrical stimulation amplitude using an up-down method to estimate the electrical threshold of the nociceptors. The software was built upon the Open Ephys system (V0.54) and coded in C++ using the JUCE framework. It runs on Windows, Linux, and Mac operating systems. The open-source code is available (<a data-saferedirecturl="https://www.google.com/url?q=https://github.com/Microneurography/APTrack&amp;source=gmail&amp;ust=1680789829274000&amp;usg=AOvVaw0nMk9J_EI2jUn8SlmC5JJm" href="https://github.com/Microneurography/APTrack" target="_blank">https://github.com/Microneurography/APTrack</a>). The electrophysiological recordings were taken from nociceptors in both a mouse skin-nerve preparation using the teased fiber method in the saphenous nerve and in healthy human volunteers using microneurography in the superficial peroneal nerve. Nociceptors were classified by their response to thermal and mechanical stimuli, as well as by monitoring the activity-dependent slowing of the conduction velocity. The software facilitated the experiment by simplifying the action potential identification through the temporal raster plot. We demonstrate real-time closed-loop electrical threshold tracking of single-neuron action potentials during&#160;in vivo&#160;human microneurography, for the first time, and during&#160;ex vivo&#160;mouse electrophysiological recordings of C-fibers and A&#948;-fibers. We establish proof of principle by showing that the electrical threshold of a human heat-sensitive C-fiber nociceptor is reduced by heating the receptive field. This plugin enables the electrical threshold tracking of single-neuron action potentials and allows the quantification of changes in nociceptor excitability.

A representative example of the software working to control an experiment is shown in Figure 7. It iteratively adjusts the stimulation amplitude using an up-down method to effectively find the electrical threshold of single nociceptors. For the first time, we demonstrate the feasibility of real-time single-neuron electrical threshold tracking in humans during microneurography (Figure 7A). Additionally, we show electrical threshold tracking in a mouse A&#948;-fiber (Figure 7B). The identification of action potentials by threshold crossing, as used here, is sufficient for tracking electrical thresholds over time. We recommend users take steps to minimize electrical noise during their recordings, such as by using a Faraday cage and bandpass filters to improve the signal-to-noise ratio.
To demonstrate that electrical threshold tracking can be used as a measure of changes in nociceptor excitability in humans, tracking of the electrical threshold during a stepped heating paradigm was performed (Figure 8). Increasing the temperature of the nociceptor terminals decreased the electrical stimulation current required to elicit an action potential, reflecting an increase in nociceptor excitability (Figure 8C). This was likely caused by the generation of receptor potentials by the heat-sensitive ion channels expressed in the C-fiber nociceptor14. At the highest temperature step, 44 &#176;C, thermally evoked action potentials were elicited (Figure 8A, stimulus number 86-96). This causes an increase in the electrical threshold as the nociceptor may be in a refractory state following high-frequency discharge. As expected, the latency of the tracked action potential decreased as the temperature increased. This is thought to occur due to a thermodynamic effect on the conduction machinery, which increases the conduction velocity of the C-fiber. This C-fiber may also be exhibiting flip-flop (Figure 8B, stimulus number 47-54), which can result in the following electrical stimulation being erroneously increased in amplitude if the action potential falls outside of the algorithm search window.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64898/64898fig01.jpg" /> 
Figure 1: A schematic of the equipment setup and cable connections required for nociceptor electrical threshold tracking with APTrack in rodents and humans. Note the two different methods of stimulation amplitude controls: a stepper motor for manually adjusted stimulators in our human setup, and a PulsePal for input voltage-controlled stimulators in our rodent setup. (1) A PC (Windows, Mac, or Linux) running the plugin for the Open Ephys platform. (2) A stepper motor that operates the stimulation amplitude dial on the DS7. (3) A constant current stimulator approved for use in humans; here we used a DS7. (4) A USB 3.0 optoisolator, which isolates the human participant from the PC (optional, only required for human research). (5) A PulsePal V2 Pulse Generator, which generates TTL time stamps (output channel 2) and voltage steps corresponding to the requested stimulation amplitude (output channel 1). (6) A constant current stimulator for use in animals; here, we used a DS4. (7) A DC power supply for the system (mains DC power supply used for the rodent setup and battery DC power supply used for the human setup). (8) An acquisition board. (9) An I/O board to connect the BNC coaxial cables carrying the signals to be recorded, such as the thermocouple outputs and TTL markers. (10) The mouse skin-nerve preparation undergoing nociceptor electrophysiological recordings. (11) A human participant undergoing microneurography recording from C-fibers in the superficial peroneal nerve. (12) An Intan RHD2216 headstage for the acquisition and digitization of the recordings. (13) An Intan Electrode Adapter Board, which the recording electrodes are connected to and which allows the signal to be passed to the RHD2216 headstage. (14) A thermal stimulation system that can output the temperature via a BNC coaxial connection. (15) A 3.3 V battery-powered button/foot pedal that is used for marking the mechanical stimulation events and drug applications. <a href="https://www.jove.com/files/ftp_upload/64898/64898fig01large.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/64898/64898fig02.jpg" /> 
Figure 2: Template signal chain. The red arrow points to the button for enabling the ADC input from the I/O board. The yellow arrow indicates the drop-down menu for selecting the Open Ephys file format. The green arrow indicates the Play and Record buttons. <a href="https://www.jove.com/files/ftp_upload/64898/64898fig02large.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/64898/64898fig03.jpg" /> 
Figure 3: Graphical user interface. The GUI consists of four main components. (1) Temporal Raster Plot panel (green) for data visualization and the settings associated with controlling the plot. A constant latency response showing gradual activity-dependent slowing is indicated by the green arrow. (2) Stimulation Control panel (yellow) for setting the stimulation amplitude parameters and loading the stimulation paradigm scripts. (3) Multi-Unit Tracking Table (blue) for adding the action potentials for tracking and activating the latency and electrical threshold tracking. (4) Options Menu for selecting the color styles and the input channel for the data and TTL triggers. <a href="https://www.jove.com/files/ftp_upload/64898/64898fig03large.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/64898/64898fig04.jpg" /> 
Figure 4: Facilitation of the identification of constant latency action potentials through real-time data visualization on a temporal raster plot using APTrack. This is a high signal-to-noise ratio example. The data presented in the temporal raster plot are from a human C-fiber recording from the superficial peroneal nerve during microneurography. Voltage Trace is the oscilloscope-like LFP Viewer plugin within Open Ephys. The APTrack User Interface is the graphical user interface of the plugin. The tracked action potential is indicated by green arrows, and the circular slider on the border of the temporal raster plot is for controlling the search box position where the algorithms will search for threshold crossing events. The electrical stimulation artifact is marked in blue on the voltage trace. The stimulation amplitude of the analog voltage command is indicated in red; note that this may not be the same as the stimulation current amplitude depending on the scaling factor set on the stimulator. <a href="https://www.jove.com/files/ftp_upload/64898/64898fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/64898/64898fig05.jpg" /> 
Figure 5: Graphical representation of the latency tracking algorithm. In simple terms, if an action potential is detected by threshold crossing, the search box will adjust its position to center itself at the time of the peak voltage. <a href="https://www.jove.com/files/ftp_upload/64898/64898fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/64898/64898fig06.jpg" /> 
Figure 6: Graphical representation of the electrical threshold tracking algorithm. In simple terms, if an action potential is detected by threshold crossing, the stimulation amplitude will be decreased by the decrement rate. If no action potential is detected, the stimulation amplitude will be increased by the increment rate. <a href="https://www.jove.com/files/ftp_upload/64898/64898fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/64898/64898fig07.jpg" /> 
Figure 7: Automated electrical threshold tracking of single-neuron action potentials at a 0.25 Hz stimulation frequency. (A) Sequential traces of a human C-fiber of the superficial peroneal nerve during a microneurography experiment. (B) Sequential traces of a mouse A&#948;-fiber of the saphenous nerve during skin-nerve preparation teased fiber electrophysiology. The traces were colored red when an action potential was identified, resulting in a decrease in the stimulus amplitude. The software algorithm effectively finds the stimulus amplitude required for a 50% likelihood of firing. <a href="https://www.jove.com/files/ftp_upload/64898/64898fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/64898/64898fig08.jpg" /> 
Figure 8: Electrical threshold tracking at a 0.25 Hz stimulation frequency during the thermal stimulation of a human C-fiber nociceptor. The y-axis encodes the stimulation number from the start of the paradigm. (A) Voltage trace for 4,000 ms following electrical stimulation, with threshold crossing events marked in red. (B) Voltage trace from A zoomed in around the tracked action potential. The traces were colored red when the tracked action potential was detected. The vertical blue line is the baseline latency of the tracked unit. (C) Stimulation current commanded by APTrack. The vertical blue line is the baseline electrical threshold. (D) Receptive field TCS-II thermal stimulating probe temperature. <a href="https://www.jove.com/files/ftp_upload/64898/64898fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Compound</td>
			<td>Concentration</td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>107.8 mM</td>
		</tr>
		<tr>
			<td>NaHCO3</td>
			<td>26.2 mM</td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>3.5 mM</td>
		</tr>
		<tr>
			<td>NaH2PO4</td>
			<td>1.67 mM</td>
		</tr>
		<tr>
			<td>CaCl2</td>
			<td>1.53 mM</td>
		</tr>
		<tr>
			<td>MgSO4</td>
			<td>0.69 mM</td>
		</tr>
		<tr>
			<td>Sodium Gluconate</td>
			<td>9.64 mM</td>
		</tr>
		<tr>
			<td>Sucrose</td>
			<td>7.6 mM</td>
		</tr>
		<tr>
			<td>Glucose</td>
			<td>5.55 mM</td>
		</tr>
	</tbody>
</table>
Table 1: Contents of the synthetic interstitial fluid for the mouse skin-nerve preparation23.

Watch this Scientific Journal Video about Open-Source Real-Time Closed-Loop Electrical Threshold Tracking for Translational Pain Research at JoVE.com

Open-Source Real-Time Closed-Loop Electrical Threshold Tracking for Translational Pain Research

APTrack is a software plugin developed for the Open Ephys platform that enables real-time data visualization and the closed-loop electrical threshold tracking of neuronal action potentials. We have successfully used this in microneurography for human C-fiber nociceptors and mouse C-fiber and A&#948;-fiber nociceptors.

Nociceptors are a class of primary afferent neurons that signal potentially harmful noxious stimuli. An increase in nociceptor excitability occurs in ...

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Introduction to Control Systems

SCIENTISTS IN ACTION

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 ...

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), magnetoencephalography or functional magnetic-resonance imaging. These techniques have either inherently low temporal or low spatial resolution, and suffer from low signal-to-noise ratio and/or poor high-frequency sensitivity. Thus, they are suboptimal for exploring the short-lived spatio-temporal dynamics of many of the underlying brain processes. In contrast, the invasive technique of electrocorticography (ECoG) provides brain signals that have an exceptionally high signal-to-noise ratio, less susceptibility to artifacts than EEG, and a high spatial and temporal resolution (i.e., &lt;1 cm/&lt;1 millisecond, respectively). ECoG involves measurement of electrical brain signals using electrodes that are implanted subdurally on the surface of the brain. Recent studies have shown that ECoG amplitudes in certain frequency bands carry substantial information about task-related activity, such as motor execution and planning1, auditory processing2 and visual-spatial attention3. Most of this information is captured in the high gamma range (around 70-110 Hz). Thus, gamma activity has been proposed as a robust and general indicator of local cortical function1-5. ECoG can also reveal functional connectivity and resolve finer task-related spatial-temporal dynamics, thereby advancing our understanding of large-scale cortical processes. It has especially proven useful for advancing brain-computer interfacing (BCI) technology for decoding a user's intentions to enhance or improve communication6 and control7. Nevertheless, human ECoG data are often hard to obtain because of the risks and limitations of the invasive procedures involved, and the need to record within the constraints of clinical settings. Still, clinical monitoring to localize epileptic foci offers a unique and valuable opportunity to collect human ECoG data. We describe our methods for collecting recording ECoG, and demonstrate how to use these signals for important real-time applications such as clinical mapping and brain-computer interfacing. Our example uses the BCI2000 software platform8,9 and the SIGFRIED10 method, an application for real-time mapping of brain functions. This procedure yields information that clinicians can subsequently use to guide the complex and laborious process of functional mapping by electrical stimulation.
Prerequisites and Planning:
Patients with drug-resistant partial epilepsy may be candidates for resective surgery of an epileptic focus to minimize the frequency of seizures. Prior to resection, the patients undergo monitoring using subdural electrodes for two purposes: first, to localize the epileptic focus, and second, to identify nearby critical brain areas (i.e., eloquent cortex) where resection could result in long-term functional deficits. To implant electrodes, a craniotomy is performed to open the skull. Then, electrode grids and/or strips are placed on the cortex, usually beneath the dura. A typical grid has a set of 8 x 8 platinum-iridium electrodes of 4 mm diameter (2.3 mm exposed surface) embedded in silicon with an inter-electrode distance of 1cm. A strip typically contains 4 or 6 such electrodes in a single line. The locations for these grids/strips are planned by a team of neurologists and neurosurgeons, and are based on previous EEG monitoring, on a structural MRI of the patient's brain, and on relevant factors of the patient's history. Continuous recording over a period of 5-12 days serves to localize epileptic foci, and electrical stimulation via the implanted electrodes allows clinicians to map eloquent cortex. At the end of the monitoring period, explantation of the electrodes and therapeutic resection are performed together in one procedure.
In addition to its primary clinical purpose, invasive monitoring also provides a unique opportunity to acquire human ECoG data for neuroscientific research. The decision to include a prospective patient in the research is based on the planned location of their electrodes, on the patient's performance scores on neuropsychological assessments, and on their informed consent, which is predicated on their understanding that participation in research is optional and is not related to their treatment. As with all research involving human subjects, the research protocol must be approved by the hospital's institutional review board. The decision to perform individual experimental tasks is made day-by-day, and is contingent on the patient's endurance and willingness to participate. Some or all of the experiments may be prevented by problems with the clinical state of the patient, such as post-operative facial swelling, temporary aphasia, frequent seizures, post-ictal fatigue and confusion, and more general pain or discomfort.
At the Epilepsy Monitoring Unit at Albany Medical Center in Albany, New York, clinical monitoring is implemented around the clock using a 192-channel Nihon-Kohden Neurofax monitoring system. Research recordings are made in collaboration with the Wadsworth Center of the New York State Department of Health in Albany. Signals from the ECoG electrodes are fed simultaneously to the research and the clinical systems via splitter connectors. To ensure that the clinical and research systems do not interfere with each other, the two systems typically use separate grounds. In fact, an epidural strip of electrodes is sometimes implanted to provide a ground for the clinical system. Whether research or clinical recording system, the grounding electrode is chosen to be distant from the predicted epileptic focus and from cortical areas of interest for the research. Our research system consists of eight synchronized 16-channel g.USBamp amplifier/digitizer units (g.tec, Graz, Austria). These were chosen because they are safety-rated and FDA-approved for invasive recordings, they have a very low noise-floor in the high-frequency range in which the signals of interest are found, and they come with an SDK that allows them to be integrated with custom-written research software. In order to capture the high-gamma signal accurately, we acquire signals at 1200Hz sampling rate-considerably higher than that of the typical EEG experiment or that of many clinical monitoring systems. A built-in low-pass filter automatically prevents aliasing of signals higher than the digitizer can capture. The patient's eye gaze is tracked using a monitor with a built-in Tobii T-60 eye-tracking system (Tobii Tech., Stockholm, Sweden). Additional accessories such as joystick, bluetooth Wiimote (Nintendo Co.), data-glove (5th Dimension Technologies), keyboard, microphone, headphones, or video camera are connected depending on the requirements of the particular experiment.
Data collection, stimulus presentation, synchronization with the different input/output accessories, and real-time analysis and visualization are accomplished using our BCI2000 software8,9. BCI2000 is a freely available general-purpose software system for real-time biosignal data acquisition, processing and feedback. It includes an array of pre-built modules that can be flexibly configured for many different purposes, and that can be extended by researchers' own code in C++, MATLAB or Python. BCI2000 consists of four modules that communicate with each other via a network-capable protocol: a Source module that handles the acquisition of brain signals from one of 19 different hardware systems from different manufacturers; a Signal Processing module that extracts relevant ECoG features and translates them into output signals; an Application module that delivers stimuli and feedback to the subject; and the Operator module that provides a graphical interface to the investigator.
A number of different experiments may be conducted with any given patient. The priority of experiments will be determined by the location of the particular patient's electrodes. However, we usually begin our experimentation using the SIGFRIED (SIGnal modeling For Realtime Identification and Event Detection) mapping method, which detects and displays significant task-related activity in real time. The resulting functional map allows us to further tailor subsequent experimental protocols and may also prove as a useful starting point for traditional mapping by electrocortical stimulation (ECS).
Although ECS mapping remains the gold standard for predicting the clinical outcome of resection, the process of ECS mapping is time consuming and also has other problems, such as after-discharges or seizures. Thus, a passive functional mapping technique may prove valuable in providing an initial estimate of the locus of eloquent cortex, which may then be confirmed and refined by ECS. The results from our passive SIGFRIED mapping technique have been shown to exhibit substantial concurrence with the results derived using ECS mapping10.
The protocol described in this paper establishes a general methodology for gathering human ECoG data, before proceeding to illustrate how experiments can be initiated using the BCI2000 software platform. Finally, as a specific example, we describe how to perform passive functional mapping using the BCI2000-based SIGFRIED system.

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

We present a method for collecting electrocorticographic signals for research purposes from humans who are undergoing invasive epilepsy monitoring. We show how to use the BCI2000 software platform for data collection, signal processing and stimulus presentation. Specifically, we demonstrate SIGFRIED, a BCI2000-based tool for real-time functional brain mapping.

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), ...

Building An Open-source Robotic Stereotaxic Instrument

This protocol includes the designs and software necessary to upgrade an existing stereotaxic instrument to a robotic (CNC) stereotaxic instrument for around $1,000 (excluding a drill), using industry standard stepper motors and CNC controlling software. Each axis has variable speed control and may be operated simultaneously or independently. The robot&#39;s flexibility and open coding system (g-code) make it capable of performing custom tasks that are not supported by commercial systems. Its applications include, but are not limited to, drilling holes, sharp edge craniotomies, skull thinning, and lowering electrodes or cannula. In order to expedite the writing of g-coding for simple surgeries, we have developed custom scripts that allow individuals to design a surgery with no knowledge of programming. However, for users to get the most out of the motorized stereotax, it would be beneficial to be knowledgeable in mathematical programming and G-Coding (simple programming for CNC machining).
The recommended drill speed is greater than 40,000 rpm. The stepper motor resolution is 1.8&#176;/Step, geared to 0.346&#176;/Step. A standard stereotax has a resolution of 2.88 &#956;m/step. The maximum recommended cutting speed is 500 &#956;m/sec. The maximum recommended jogging speed is 3,500 &#956;m/sec. The maximum recommended drill bit size is HP 2.

This protocol includes the designs and software necessary to upgrade an existing stereotaxic instrument to a robotic (computer numeric controlled; CNC) stereotaxic instrument for around $1,000 (excluding a drill).

This protocol includes the designs and software necessary to upgrade an existing stereotaxic instrument to a robotic (CNC) stereotaxic instrument for ...

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 ...

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain.

The ability to induce and/or control neural plasticity may be critical in future treatments for neurologic disorders and the recovery from brain injury. In this paper, we present a protocol on the use of neurofeedback training with functional magnetic resonance imaging to modulate human brain function.

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control ...

Real-time Video Projection in an MRI for Characterization of Neural Correlates Associated with Mirror Therapy for Phantom Limb Pain

Mirror therapy (MT) has been proposed as an effective rehabilitative strategy to alleviate pain symptoms in amputees with phantom limb pain (PLP). However, establishing the neural correlates associated with MT therapy have been challenging given that it is difficult to administer the therapy effectively within a magnetic resonance imaging (MRI) scanner environment. To characterize the functional organization of cortical regions associated with this rehabilitative strategy, we have developed a combined behavioral and functional neuroimaging protocol that can be applied in participants with a leg amputation. This novel approach allows participants to undergo MT within the MRI scanner environment by viewing real-time video images captured by a camera. The images are viewed by the participant through a system of mirrors and a monitor that the participant views while lying on the scanner bed. In this manner, functional changes in cortical areas of interest (e.g., sensorimotor cortex) can be characterized in response to the direct application of MT.

We present a novel combined behavioral and neuroimaging protocol employing real-time video projection for the purpose of characterizing the neural correlates associated with mirror therapy within the magnetic resonance imaging scanner environment in leg amputee subjects with phantom limb pain.

Mirror therapy (MT) has been proposed as an effective rehabilitative strategy to alleviate pain symptoms in amputees with phantom limb pain (PLP). ...

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.

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 ...

Real-Time fMRI Brain Mapping in Animals

Dynamic fMRI responses vary largely according to the physiological conditions of animals either under anesthesia or in awake states. We developed a real-time fMRI platform to guide experimenters to monitor fMRI responses instantaneously during acquisition, which can be used to modify the physiology of animals to achieve desired hemodynamic responses in animal brains. The real-time fMRI set-up is based on a 14.1T preclinical MRI system, enabling the real-time mapping of dynamic fMRI responses in the primary forepaw somatosensory cortex (FP-S1) of anesthetized rats. Instead of a retrospective analysis to investigate confounding sources leading to the variability of fMRI signals, the real-time fMRI platform provides a more effective scheme to identify dynamic fMRI responses using customized macro-functions and a common neuroimage analysis software in the MRI system. Also, it provides immediate troubleshooting feasibility and a real-time biofeedback stimulation paradigm for brain functional studies in animals.

Animal brain functional mapping can benefit from the real-time functional magnetic resonance imaging (fMRI) experimental set-up. Using the latest software implemented in the animal MRI system, we established a real-time monitoring platform for small animal fMRI.

Dynamic fMRI responses vary largely according to the physiological conditions of animals either under anesthesia or in awake states. We developed a ...

Conventional and Threshold-Tracking Transcranial Magnetic Stimulation Tests for Single-handed Operation

Most single-pulse transcranial magnetic stimulation (TMS) parameters (e.g., motor threshold, stimulus-response function, cortical silent period) are used to examine corticospinal excitability. Paired-pulse TMS paradigms (e.g., short- and long-interval intracortical inhibition (SICI/LICI), short-interval intracortical facilitation (SICF), and short- and long-latency afferent inhibition (SAI/LAI)) provide information about intracortical inhibitory and facilitatory networks. This has long been done by the conventional TMS method of measuring changes in the size of the motor-evoked potentials (MEPs) in response to stimuli of constant intensity. An alternative threshold-tracking approach has recently been introduced whereby the stimulus intensity for a target amplitude is tracked. The diagnostic utility of threshold-tracking SICI in amyotrophic lateral sclerosis (ALS) has been shown in previous studies. However, threshold-tracking TMS has only been used in a few centers, in part due to the lack of readily available software but also perhaps due to uncertainty over its relationship to conventional single- and paired-pulse TMS measurements.
A menu-driven suite of semi-automatic programs has been developed to facilitate the broader use of threshold-tracking TMS techniques and to enable direct comparisons with conventional amplitude measurements. These have been designed to control three types of magnetic stimulators and allow recording by a single operator of the common single- and paired-pulse TMS protocols.
This paper shows how to record a number of single- and paired-pulse TMS protocols on healthy subjects and analyze the recordings. These TMS protocols are fast and easy to perform and can provide useful biomarkers in different neurological disorders, particularly neurodegenerative diseases such as ALS.

We present a suite of standardized single- and paired-pulse transcranial magnetic stimulation (TMS) recording protocols, with options for conventional amplitude measurements and threshold-tracking. This program can control three different types of magnetic stimulators and is designed to enable all tests to be performed conveniently by a single operator.

Most single-pulse transcranial magnetic stimulation (TMS) parameters (e.g., motor threshold, stimulus-response function, cortical silent period) are used ...