This work was supported by the Ray and Dagmar Dolby Family Fund through the Department of Psychiatry at UCSF (KKS, ANK, NS, JF, VRR, KWS, EFC, ADK), by a National Institutes of Health award no. K23NS110962 (KWS), NARSAD Young Investigator grant from the Brain &#38; Behavior Research Foundation (KWS), and 1907 Trailblazer Award (KWS).

This protocol has been reviewed and approved by the University of California, San Francisco Institutional Review Board.
1. Device setup for patient at-home recordings
<ol>
	<li>Work with a representative from the device company to set four configured channels for acquisition, two from each implanted lead. 
	NOTE: Each channel records a bipolar recording. Configured channels may use adjacent (e.g., 1-2, 3-4) or interleaved (e.g., 1-3, 2-4) electrode contacts. When leads with&#160;10 mm spacing are implanted, adjacent contacts are typically used. When leads with&#160;3.5 mm spacing are implanted, either adjacent or interleaved contacts are used. This is determined by examining the reconstruction of electrode implant location relative to anatomical targets and examining the amplitude of signals. If adjacent contacts produce low amplitude signals, interleaved contacts are preferable. Each contact can only be used in the montage once.</li>
	<li>Ensure the patient has fully recovered from surgery following the implantation of the device with cortical and/or depth leads (see24 for additional information on implantation technique).</li>
	<li>Connect the telemetry wand to the programmer (clinician tablet) and have the patient hold the wand over their INS or attach it to a tethering hat (custom-made, not part of the device system; see Figure 1).</li>
	<li>Using the programmer, log on to the patient data management system (PDMS; https://pdms.neuropace.com/login.php), navigate to the correct patient, and select Programming and then Change ECoG Capture. Set the Capture Window to the maximum of 240 s for the four configured channels using the dropdown selection. 
	NOTE: The device sampling rate is 250 Hz.</li>
	<li>On the same settings page, set Reserve Space for magnet reservations to two and to zero for all other trigger types using the dropdown selections. This allows for prioritized saving of two recordings triggered by magnet swipes. 
	NOTE: Scheduled storage can also be enabled, for automatic and non-prioritized saving of neural recordings at set times of day. These recordings will not be used for determining a biomarker but may be useful for other purposes.</li>
	<li>Synchronize the newly programmed settings with the patient&#39;s INS by selecting the Review &#38; Program button, confirming changes shown in the presented table, and selecting the Confirm Programming button. 
	&#8203;NOTE: Detection and Stimulation should both be set to Disabled.</li>
</ol>
2. Symptom collection during patient at-home recordings
<ol>
	<li>Prepare the web-based survey for the patient symptom report (e.g. REDCap25), including sliders for VAS-D, VAS-A, VAS-E, and selection responses for each question of the HAMD-6. Ensure the time of survey start and completion is logged.</li>
	<li>Provide the patient with the unique URL generated by REDCap to access the symptom surveys either via text message or email</li>
</ol>
3. Procedure for concurrent at-home symptom reports and neural recordings
<ol>
	<li>Instruct the patient to set up the equipment, including a remote monitor (patient laptop) and wand, magnet, and device for completing survey (e.g. smartphone, tablet, or computer) (Figure 1). Steps 3.2-3.8 are performed by the patient. 
	NOTE: Most patients quickly learn this procedure. In-person training sessions while the patient is still in the hospital following device implantation are helpful for familiarization with the components. After the patient has returned home, a video call while the patient is doing an at-home recording can serve as a useful refresher.</li>
	<li>Turn on the remote monitor and interrogate the&#160;device using the wand, downloading electrocorticography (ECoG) recordings that have occurred since the last interrogation to the remote monitor.</li>
	<li>Swipe the magnet over the INS to trigger a magnet recording. 
	NOTE: The magnet swipe triggers a recording with a 2:1 before:after the swipe ratio. In the case of an ECoG capture that is programmed to 240 s, this means that 160 s of data prior to the swipe and 80 s following the swipe will be stored.</li>
	<li>Start a timer. Use the unique URL to complete a symptom survey.</li>
	<li>After 4 min have elapsed or the patient finishes the survey (whichever happens later), swipe the magnet over the INS again to trigger another recording.</li>
	<li>After at least 80 s, use the wand to interrogate the device again, transferring the data from the two magnet swipes to the remote monitor. 
	NOTE: Due to the limited on-board memory of the INS (up to 53 channel-minutes of data, depending on configuration13), it is desirable to immediately transfer these ECoG recordings to the remote monitor so that they are not overwritten by subsequent recordings.</li>
	<li>Complete steps 3.1-3.6 at least twice daily.</li>
	<li>At least once daily, connect the remote monitor to the internet via ethernet and select Transfer Data and Synchronize on the remote monitor to send data to the cloud.</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65177/65177fig01.jpg" /> 
Figure 1: Patient equipment for at-home recordings. A remote monitor, wand tethered to a hat, magnet, and smartphone with REDCap survey. Inlaid images show right OFC (blue) and right SGC (orange) electrode implant locations superimposed on a white-matter nulled 1 mm isotropic T1 sequence from the preoperative magnetic resonance imaging (MRI). The depicted coronal slice is in the plane of the deepest contact, so the other contacts may not be centered on this exact slice (due to the fact that the electrode trajectory is not in the coronal plane). <a href="https://www.jove.com/files/ftp_upload/65177/65177fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
4. Determining a personalized biomarker
<ol>
	<li>Create a dataframe of self-reported symptom survey responses (e.g. JOVE.PR03_Symptoms.pkl).</li>
	<li>Calculate spectral power profiles for each channel of ECoG recording by convolving ECoG activity with a family of Morlet wavelets (40 kernels, 12 cycles, log-spaced between 1-120 Hz), creating a new dataframe (e.g., JOVE.PR03_NeuralPower.pkl).</li>
	<li>Associate ECoG recordings with symptom reports that occurred within a time window spanning 5 min before to 5 min after initiation of the symptom report, using the trial_id field in the NeuralPower dataframe.</li>
	<li>Identify symptom states (Figure 2)
	<ol>
		<li>Using Python 3.10, install requirements listed in the requirements.txt file (Supplementary Folder 1) to a new environment. This can be done using pip install -r requirements.txt.</li>
		<li>Open JOVE-Symptom_State_and_Biomarker_Analysis.ipynb (Supplementary Folder 1) using the Jupyter Notebook.</li>
		<li>Verify the kernel is set to the environment into which requirements.txt were installed and run JOVE-Symptom_State_and_Biomarker_Analysis.ipynb. 
		NOTE: JOVE-Symptom_State_and_Biomarker_Analysis.ipynb calculates the statistical similarity between scores on patient surveys using the cosine similarity metric, which ranges from 0 (no similarity) to 1 (identical) and constructs a symptom state graph by aggregating the similarity values across all possible pairs of at-home patient symptom reports. Spectral power features for each symptom state are calculated by aggregating spectral power profiles associated with each inferred symptom state; this procedure yields a distribution of spectral power profiles linked to each symptom state (Figure 3).</li>
	</ol>
	</li>
	<li>In scenarios where more than two symptom states are identified, the distributions of spectral power corresponding to the most severe symptom state and the least severe symptom state are statistically compared.</li>
	<li>Use a cluster-based permutation t-test to identify spectral frequencies in which the spectral power of the severe symptom state is significantly greater than the spectral power of the least severe symptom state. The range of contiguous spectral frequencies that differentiate the symptom states is considered as a single candidate biomarker.</li>
</ol>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65177/65177fig02.jpg" /> 
Figure 2: Schematic of the methodological approach for measuring symptom states, showing results from a representative example. Patient self-reported surveys are obtained and itemized symptom scores are normalized to a range between 0 and 1 (darker colors reflect lower symptom severity and brighter colors reflect higher symptom severity). (1) Each completed survey represents a snapshot in time of the patient&#39;s symptoms and is represented as a point (black) in high-dimensional space. (2) Time points are linked together in a symptom survey graph, which relates the cosine similarity between survey reports (lines between points). (3) Graph community detection assigns each time point to a community or symptom state (colored points and lines) based on the pattern of graph connections. (4) Symptom severity scores are averaged according to state assignment and provide a general symptom phenotype for each state. (5) The occurrence of each state may be tracked over time as a raster plot (vertical lines reflect a symptom report assigned to one state). <a href="https://www.jove.com/files/ftp_upload/65177/65177fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
5. Programming device detector settings
<ol>
	<li>Using the programmer, log on to the PDMS and select the correct patient, Programming, and Change Detection.</li>
	<li>Based on the selected personalized biomarker, select the correct channel for detecting activity.
	<ol>
		<li>When creating a Pattern&#160;for the first time, first select an ECoG by clicking on one from those shown below, a channel chosen from that ECoG, and a time period highlighted.</li>
		<li>When creating a pattern&#160;from a preexisting one, change the channel by clicking on Pattern and selecting the Change Channel button.</li>
	</ol>
	</li>
	<li>For Detect, select Rhythmic Activity, which connotes a bandpass detector.</li>
	<li>Click More Controls and Adv Settings. Select the desired minimum frequency and maximum frequency. Ensure the settings are as follows: Bandpass: On; Line Length: Off; Area: Off; Inversion Logic: Not Inverted.</li>
	<li>Program the Min Amplitude and Minimum Duration for the detector. Start with a minimum amplitude of 0.8% and a minimum duration of 0.64 s (equivalent to a Bandpass Threshold of five and Detect Analysis Window Size of 1280 ms). 
	NOTE: Min Amplitude is a percentage of the total signal amplitude that the detected activity must exceed. Only amplitudes above this threshold can be used for detection. Minimum Duration is how long the high amplitude signal must be sustained. This is tracked as a count of fixed-duration time bins. Specifically, x of y 128 ms time bins must meet these criteria, where x is Bandpass Threshold and y is [Detect Analysis Window Size/128], as displayed in Technical Parameters. An episode (i.e. triggering of the detector) must be exited before a subsequent trigger can occur. Some settings may be too sensitive and result in staying in one episode indefinitely, thereby preventing subsequent triggers.</li>
	<li>Once all the detector settings are selected, click Done to close all the programming windows. 
	NOTE: Multiple detectors can be programmed; detection can be triggered based on AND/OR logic between these detectors. Start with one detector to understand the behavior before introducing a second detector.</li>
	<li>With the wand placed over the patient&#39;s INS, select Review &#38; Program and click through the confirmation messages to initialize this detector setting.</li>
</ol>
6. Titrating device detector settings
<ol>
	<li>After the device detector has been programmed and initialized on the device, conduct test recordings to assess if the sensitivity of the detector should be adjusted to achieve the desired triggering frequency. This can be achieved using Live ECoGs or the interrogation report. Adjustments to the sensitivity of the detector are determined empirically based on patient symptom reports, side effects, and outcomes. These adjustments may be needed throughout the course of treatment. Per day, 30 min of stimulation can be used as a conservative starting point to assess the clinical efficacy while also preserving battery life.</li>
	<li>Live ECoGs
	<ol>
		<li>With the wand placed over the patient&#39;s INS, select Live ECOGs on the programmer.</li>
		<li>During the live recording, count the number of detections that occur for the duration of the recording. This provides an indication of how often the detector will trigger. 
		NOTE: Some detectors may be state-dependent, particularly detectors set to low frequencies (e.g., more active during periods of sleep or drowsiness). Thus, live recordings have limitations for estimating how often a detector may trigger. Live recordings may also suffer from electromagnetic interference (e.g., line noise) or poor wand positioning.</li>
	</ol>
	</li>
	<li>Interrogation report
	<ol>
		<li>Minutes to hours after setting the detector, place the wand over the patient&#39;s INS to interrogate the device.</li>
		<li>In the PDMS, navigate to Activity, select Event List, and click on Initial Interrogation from the time of the recording. The table at the bottom provides a list, with times, of all the detection events. This document can be exported in pdf format and parsed for quantification.</li>
	</ol>
	</li>
	<li>Based on the number of detections per unit time recorded versus the desired density of stimulation, adjust the detector duration and amplitude parameters if needed. Be sure to click on Review &#38; Program after each set of changes to initialize these on the patient&#39;s INS.</li>
</ol>
7. Programming device stimulation settings
<ol>
	<li>Using the programmer, log on to the PDMS and select the correct patient, Programming, and Change Stimulation.</li>
	<li>Select the desired lead contacts or Can (INS) to be anode(s) and cathode(s). Select the desired stimulation current, pulse width, duration, and frequency. 
	NOTE: Up to five stimulation therapies can be programmed; each therapy comprises two bursts of stimulation, which can be programmed to be the same or different. A given detector trigger can lead to a variable number of stimulation therapies, depending upon the sustained duration of the episode. Only program Therapy 1, with both bursts having the same parameters, which will lead to a consistent duration of stimulation being delivered each time the detector is triggered. In this configuration, the total duration of stimulation delivered when the detector is triggered will be the sum of Stim 1 Burst 1 and Stim 1 Burst 2. If multiple therapies are programmed and delivered, a maximum of five therapies can be delivered during a given episode. The episode must be exited and a new episode triggered in order for subsequent stimulation to be delivered.</li>
	<li>If desired to limit the total amount of stimulation delivered per day, select a value for Therapy Limit per Day and a Therapy Limit Reset Time. 
	NOTE: The Therapy Limit Reset Time timezone is set to the patient&#39;s primary center. If patients have relocated, this may be different than the patient&#39;s home time zone.</li>
	<li>Specifically, if no overnight stimulation is desired, set the Therapy Limit per Day and Therapy Limit Reset Time&#160;such that the detector achieves the therapy limit between the reset time and the patient&#39;s bedtime.</li>
	<li>With the wand placed over the patient&#39;s INS, select Review &#38; Program and click through the confirmation messages to initialize the stimulation settings.</li>
</ol>

Deep Brain Stimulation for Treatment of Major Depression

<ol>
	<li>Kaiser, R. H., Andrews-Hanna, J. R., Wager, T. D., Pizzagalli, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Large-scale+network+dysfunction+in+major+depressive+disorder:+A+meta-analysis+of+resting-state+functional+connectivity.">Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity.</a> JAMA Psychiatry. 72 (6), 603-611 (2015).</li><li>Goldstein-Piekarski, A. N., 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=Mapping+neural+circuit+biotypes+to+symptoms+and+behavioral+dimensions+of+depression+and+anxiety.">Mapping neural circuit biotypes to symptoms and behavioral dimensions of depression and anxiety.</a> Biological Psychiatry. 91 (6), 561-571 (2022).</li><li>Williams, L. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Precision+psychiatry:+a+neural+circuit+taxonomy+for+depression+and+anxiety.">Precision psychiatry: a neural circuit taxonomy for depression and anxiety.</a> The Lancet Psychiatry. 3 (5), 472-480 (2016).</li><li>Ionescu, D. F., Rosenbaum, J. F., Alpert, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pharmacological+approaches+to+the+challenge+of+treatment-resistant+depression.">Pharmacological approaches to the challenge of treatment-resistant depression.</a> Dialogues in Clinical Neuroscience. 17 (2), 111-126 (2015).</li><li>Mayberg, H. S., 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=Deep+brain+stimulation+for+treatment-resistant+depression.">Deep brain stimulation for treatment-resistant depression.</a> Neuron. 45 (5), 651-660 (2005).</li><li>Kennedy, S. 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=Deep+brain+stimulation+for+treatment-resistant+depression:+follow-up+after+3+to+6+years.">Deep brain stimulation for treatment-resistant depression: follow-up after 3 to 6 years.</a> The American Journal of Psychiatry. 168 (5), 502-510 (2011).</li><li>Holtzheimer, P. E., 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=Subcallosal+cingulate+deep+brain+stimulation+for+treatment-resistant+depression:+a+multisite,+randomised,+sham-controlled+trial.">Subcallosal cingulate deep brain stimulation for treatment-resistant depression: a multisite, randomised, sham-controlled trial.</a> The Lancet Psychiatry. 4 (11), 839-849 (2017).</li><li>Dougherty, D. D., 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=A+randomized+sham-controlled+trial+of+deep+brain+stimulation+of+the+ventral+capsule/ventral+striatum+for+chronic+treatment-resistant+depression.">A randomized sham-controlled trial of deep brain stimulation of the ventral capsule/ventral striatum for chronic treatment-resistant depression.</a> Biological Psychiatry. 78 (4), 240-248 (2015).</li><li>Morishita, T., Fayad, S. M., Higuchi, M., Nestor, K. A., Foote, K. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deep+brain+stimulation+for+treatment-resistant+depression:+systematic+review+of+clinical+outcomes.">Deep brain stimulation for treatment-resistant depression: systematic review of clinical outcomes.</a> Neurotherapeutics. 11 (3), 475-484 (2014).</li><li>Lo, M. -. C., Widge, A. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Closed-loop+neuromodulation+systems:+next-generation+treatments+for+psychiatric+illness.">Closed-loop neuromodulation systems: next-generation treatments for psychiatric illness.</a> International Review of Psychiatry. 29 (2), 191-204 (2017).</li><li>Hoang, K. B., Cassar, I. R., Grill, W. M., Turner, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biomarkers+and+stimulation+algorithms+for+adaptive+brain+stimulation.">Biomarkers and stimulation algorithms for adaptive brain stimulation.</a> Frontiers in Neuroscience. 11, 564 (2017).</li><li>Little, S., 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=Adaptive+deep+brain+stimulation+in+advanced+Parkinson+disease.">Adaptive deep brain stimulation in advanced Parkinson disease.</a> Annals of Neurology. 74 (3), 449-457 (2013).</li><li>Jarosiewicz, B., Morrell, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+RNS+system:+brain-responsive+neurostimulation+for+the+treatment+of+epilepsy.">The RNS system: brain-responsive neurostimulation for the treatment of epilepsy.</a> Expert Review of Medical Devices. 18 (2), 129-138 (2021).</li><li>Scangos, K. W., 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=Closed-loop+neuromodulation+in+an+individual+with+treatment-resistant+depression.">Closed-loop neuromodulation in an individual with treatment-resistant depression.</a> Nature Medicine. 27 (10), 1696-1700 (2021).</li><li>Cagle, J. N., 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=Embedded+human+closed-loop+deep+brain+stimulation+for+Tourette+syndrome:+a+nonrandomized+controlled+trial.">Embedded human closed-loop deep brain stimulation for Tourette syndrome: a nonrandomized controlled trial.</a> JAMA Neurology. 79 (10), 1064-1068 (2022).</li><li>He, S., 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=Closed-loop+deep+brain+stimulation+for+essential+tremor+based+on+thalamic+local+field+potentials.">Closed-loop deep brain stimulation for essential tremor based on thalamic local field potentials.</a> Movement Disorders. 36 (4), 863-873 (2021).</li><li>Drysdale, A. T., 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=Resting-state+connectivity+biomarkers+define+neurophysiological+subtypes+of+depression.">Resting-state connectivity biomarkers define neurophysiological subtypes of depression.</a> Nature Medicine. 23 (1), 28-38 (2017).</li><li>Siddiqi, S. 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=Brain+stimulation+and+brain+lesions+converge+on+common+causal+circuits+in+neuropsychiatric+disease.">Brain stimulation and brain lesions converge on common causal circuits in neuropsychiatric disease.</a> Nature Human Behaviour. 5 (12), 1707-1716 (2021).</li><li>Ahearn, E. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+visual+analog+scales+in+mood+disorders:+A+critical+review.">The use of visual analog scales in mood disorders: A critical review.</a> Journal of Psychiatric Research. 31 (5), 569-579 (1997).</li><li>Bech, P., 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=The+Hamilton+depression+scale.+Evaluation+of+objectivity+using+logistic+models.">The Hamilton depression scale. Evaluation of objectivity using logistic models.</a> Acta Psychiatrica Scandinavica. 63 (3), 290-299 (1981).</li><li>Khambhati, A. N., Sizemore, A. E., Betzel, R. F., Bassett, D. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+and+interpreting+mesoscale+network+dynamics.">Modeling and interpreting mesoscale network dynamics.</a> NeuroImage. 180, 337-349 (2018).</li><li>Zamani Esfahlani, F., Bertolero, M. A., Bassett, D. S., Betzel, R. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Space-independent+community+and+hub+structure+of+functional+brain+networks.">Space-independent community and hub structure of functional brain networks.</a> NeuroImage. 211, 116612 (2020).</li><li>Kleen, J. K., Rao, V. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Managing+neurostimulation+for+epilepsy.">Managing neurostimulation for epilepsy.</a> Deep Brain Stimulation Management. , 177-197 (2022).</li><li>Krucoff, M. O., Wozny, T. A., Lee, A. T., Rao, V. R., Chang, E. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Operative+technique+and+lessons+learned+from+surgical+implantation+of+the+NeuroPace+Responsive+Neurostimulation&#174;+system+in+57+consecutive+patients.">Operative technique and lessons learned from surgical implantation of the NeuroPace Responsive Neurostimulation&#174; system in 57 consecutive patients.</a> Operative Neurosurgery. 20 (2), E98-E109 (2021).</li><li>Harris, P. A., 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=The+REDCap+consortium:+Building+an+international+community+of+software+platform+partners.">The REDCap consortium: Building an international community of software platform partners.</a> Journal of Biomedical Informatics. 95, 103208 (2019).</li><li>Krauss, J. 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=Technology+of+deep+brain+stimulation:+current+status+and+future+directions.">Technology of deep brain stimulation: current status and future directions.</a> Nature Reviews Neurology. 17 (2), 75-87 (2021).</li><li>Dougherty, D. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deep+brain+stimulation:+clinical+applications.">Deep brain stimulation: clinical applications.</a> The Psychiatric Clinics of North America. 41 (3), 385-394 (2018).</li><li>Drobisz, D., Damborsk&#225;, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deep+brain+stimulation+targets+for+treating+depression.">Deep brain stimulation targets for treating depression.</a> Behavioural Brain Research. 359, 266-273 (2019).</li><li>Lee, D. J., Lozano, C. S., Dallapiazza, R. F., Lozano, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Current+and+future+directions+of+deep+brain+stimulation+for+neurological+and+psychiatric+disorders.">Current and future directions of deep brain stimulation for neurological and psychiatric disorders.</a> Journal of Neurosurgery. 131 (2), 333-342 (2019).</li><li>Sun, F. T., Morrell, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Closed-loop+neurostimulation:+the+clinical+experience.">Closed-loop neurostimulation: the clinical experience.</a> Neurotherapeutics. 11 (3), 553-563 (2014).</li><li>Malone, D. A., 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=Deep+brain+stimulation+of+the+ventral+capsule/ventral+striatum+for+treatment-resistant+depression.">Deep brain stimulation of the ventral capsule/ventral striatum for treatment-resistant depression.</a> Biological Psychiatry. 65 (4), 267-275 (2009).</li><li>Zuo, X. -. N., Xu, T., Milham, M. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Harnessing+reliability+for+neuroscience+research.">Harnessing reliability for neuroscience research.</a> Nature Human Behaviour. 3 (8), 768-771 (2019).</li></ol>

ADK consults for Eisai, Evecxia Therapeutics, Ferring Pharmaceuticals, Galderma, Harmony Biosciences, Idorsia, Jazz Pharmaceuticals, Janssen Pharmaceuticals, Merck, Neurocrine Biosciences, Pernix Pharma, Sage Therapeutics, Takeda Pharmaceutical Company, Big Health, Millennium Pharmaceuticals, Otsuka Pharmaceutical, and Neurawell Therapeutics. ADK acknowledges support from Janssen Pharmaceuticals, Jazz Pharmaceuticals, Axsome Therapeutics (no. AXS-05-301), and Reveal Biosensors. KWS serves on the advisory board of Nesos. UCSF and EFC have patents related to brain stimulation for the treatment of neuropsychiatric disorders. The other authors declare no competing interests.

Deep brain stimulation has become an established therapy for Parkinson&#39;s disease, essential tremor, dystonia, and epilepsy, and is actively being investigated in numerous other neuropsychiatric conditions26,27,28,29. The vast majority of DBS is delivered in open-loop mode, in which stimulation is delivered continuously. For symptoms which are paroxysmal in nature, continuous stimulation may...

Major depressive disorder (MDD) is a neuropsychiatric disease characterized by network-level aberrant activity and connectivity1. The disease manifests a variety of symptoms that vary across individuals, fluctuate over time, and may stem from different neural circuits2,3. Approximately 30% of individuals with MDD are refractory to standard-of-care treatments4, highlighting a need for new approaches.
Deep brain stimulation (DBS) is a form of neuromodulation in which electrical current is delivered to targeted areas of the brain with the goal of modulating the activity. DBS for the treatment of MDD has been very successful in some applications5,6, but has also failed to replicate in larger studies7,8. All of the cited studies employed open-loop stimulation9, in which the delivery of putative therapeutic stimulation was continuous with fixed parameters. In contrast, closed-loop stimulation delivers stimulation based on a programmed biomarker or neural activity pattern associated with the symptom state10. There are two main implementations of closed-loop stimulation: responsive stimulation and adaptive stimulation11. Responsive stimulation delivers bursts of stimulation with constant parameters (e.g., frequency, amplitude, pulse width) when the programmed criteria are met. With adaptive stimulation, stimulation parameters dynamically change as a function of the measured biomarker, according to the algorithm, which may have multiple fix points or automated continuous adjustment. Stimulation can be continuous or intermittent with adaptive stimulation. Adaptive stimulation has shown superior efficacy to open-loop stimulation in controlling symptoms of Parkinson&#39;s disease12. Responsive neurostimulation for epilepsy13 is Food and Drug Administration (FDA)-approved, while early investigations of responsive stimulation for MDD14 and adaptive stimulation for Tourette syndrome15 and essential tremor16 also show therapeutic benefit.
To implement closed-loop stimulation, a physiological signal must be selected and tracked to inform when stimulation should be delivered. This feedback is the key difference between open-loop and closed-loop stimulation and is realized by selecting a biomarker. This protocol provides a procedure for determining a personalized biomarker according to the constellation of symptoms experienced by a given individual. Future meta-analyses across patients will reveal if there are common biomarkers across individuals or if the heterogeneous presentation of MDD symptoms and the underlying circuitry necessitates a personalized approach17,18. Using DBS devices capable of both sensing neural activity and delivering electrical stimulation allows for both the discovery of this biomarker and the subsequent implementation of closed-loop neuromodulation. This approach presupposes a close temporal relationship between neural activity and specific symptom states and may not be applicable for all indications or symptoms.
While indications such as Parkinson&#39;s disease and essential tremor have symptoms that can be measured using peripheral sensors (e.g., tremor, rigidity), symptoms of MDD are typically reported by the patient or assessed by a clinician using standardized questions and observation. In the context of amassing sufficient data to calculate a personalized biomarker, clinician assessments are not practical, and thus patient reports of symptoms through rating scales are used. Such scales include visual analog scales of depression (VAS-D), anxiety (VAS-A), and energy (VAS-E)19, and the six-question form of the Hamilton Depression Rating Scale (HAMD-6)20. Concurrent recordings of neural activity and completion of these self-report symptom ratings provide a paired dataset that can be used to look at relationships between spectral features of the neural signal related to or predictive of high-symptom states.
Computational approaches, such as state-space modeling, can be used to uncover relationships between symptom states and neural features. Graph theoretic methods are attractive for characterizing a state-space21 because they enable the discovery of states over different timescales by explicitly modeling the temporal proximity between measurements22. A symptom state-space model identifies periods of time in which there is a common phenotype of the patient&#39;s symptoms and may pinpoint symptom sub-states in which the ratings on specific dimensions of the patient&#39;s depression differ based on the environment or context. A closed-loop approach relies on the detection of symptom states based on underlying brain activity. Machine learning classification is a final step that helps identify a combination of statistical features derived from brain activity signals that best distinguishes two or more symptom states14. This two-stage approach explains the variability in a patient&#39;s symptoms over time and links systematic patterns of symptom variation to brain activity.
The present protocol utilizes the NeuroPace Responsive Neurostimulation System (RNS)13,23. Procedures to determine the optimal stimulation site(s) and parameters are outside the scope of this protocol. However, the stimulation capabilities of a given device are important to consider when designing closed-loop neurostimulation. For the device used in this protocol, stimulation is current-controlled and delivered between the anode(s) and cathode(s). One or more electrode contacts or the Can (implantable neurostimulator [INS]) can be selected as the anode(s) or cathode(s). Stimulation frequency (1-333.3 Hz), amplitude (0-12 mA), pulse width (40-1000 &#181;s per phase), and duration (10-5000 ms, per stim) are all pre-programmed. The prior parameters can be set independently for up to five stimulation therapies; these therapies are delivered sequentially if the detection criteria continue to be met. It is not possible to deliver multiple stimulation waveforms simultaneously (e.g., one cannot deliver two different frequencies of stimulation concurrently). The stimulation waveform is a symmetric biphasic rectangular wave and cannot be changed.

<table><tbody><tr><td>Depth Lead</td><td>Neuropace</td><td>DL-330-3.5</td><td>30 cm length, 3.5 mm contact spacing</td></tr><tr><td>Depth Lead</td><td>Neuropace</td><td>DL-330-10</td><td>30 cm length, 10 mm contact spacing</td></tr><tr><td>Depth Lead</td><td>Neuropace</td><td>DL-344-3.5</td><td>44 cm length, 3.5 mm contact spacing</td></tr><tr><td>Depth Lead</td><td>Neuropace</td><td>DL-344-10</td><td>44 cm length, 10 mm contact spacing</td></tr><tr><td>Hat with velcro</td><td>Self-assembled</td><td>NA</td><td>Optional</td></tr><tr><td>Jupyter Notebook</td><td>Project Jupyter</td><td>NA</td><td></td></tr><tr><td>Magnet</td><td>Neuropace</td><td>M-01</td><td></td></tr><tr><td>Programmer</td><td>Neuropace</td><td>PGM-300</td><td>Clinician tablet</td></tr><tr><td>Python 3.10</td><td>Python</td><td>NA</td><td></td></tr><tr><td>Remote Monitor</td><td>Neuropace</td><td>5000</td><td>Patient laptop&amp;nbsp;</td></tr><tr><td>Responsive Neurostimulation System (RNS)&amp;nbsp;</td><td>Neuropace</td><td>RNS-320</td><td></td></tr><tr><td>Wand</td><td>Neuropace</td><td>W-02</td><td></td></tr></tbody></table>

closed-loop neurostimulation for biomarker-driven, personalized treatment of major depressive disorder

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

Data collected and presented here are from a single patient with four-channel leads implanted in the right orbitofrontal cortex (OFC) and the right subgenual cingulate (SGC) (Figure 1). A lead with 10 mm center-to-center pitch was used for the OFC in order to target both the medial and lateral aspects, while a lead with 3.5 mm pitch was used for the SGC in order to have more spatially concentrated coverage. Four bipolar recording channels were programmed using adjacent contacts: OFC1-OFC2, O...

Watch this Scientific Journal Video about Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment at JoVE.com

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment 

Deep brain stimulation triggered by a patient-specific neural biomarker of a high-symptom state may better control symptoms of major depressive disorder compared to continuous, open-loop stimulation. This protocol provides a workflow for identifying a patient-specific neural biomarker and controlling the delivery of therapeutic stimulation based on the identified biomarker.

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder

Deep brain stimulation involves the administration of electrical stimulation to targeted brain regions for therapeutic benefit. In the context of major ...

closed-loop-neurostimulation-for-biomarker-driven-personalized

Research

JoVE Journal

Neuroscience

2.2K Views.  University of California, San Francisco. We beoordelen het therapeutische voordeel van closed-loop gepersonaliseerde diepe hersenstimulatie voor de behandeling van depressieve stoornis. Dit protocol schetst hoe een gepersonaliseerde neurale biomarker te identificeren die gecorreleerd is met de ernst van de symptomen en vervolgens een geïmplanteerde neurostimulator te programmeren om stimulatie toe te dienen met behulp van die biomarker. Eerdere toepassingen van diepe hersenstimulatie voor depressie gebruikten continue stimulatie, d...

Video: Auteur in de schijnwerpers: therapeutisch voordeel van closed-loop diepe hersenstimulatie bij de behandeling van depressie 

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 ...

The NeuroStar TMS Device: Conducting the FDA Approved Protocol for Treatment of Depression

The Neuronetics NeuroStar Transcranial Magnetic Stimulation (TMS) System is a class II medical device that produces brief duration, pulsed magnetic fields. These rapidly alternating fields induce electrical currents within localized, targeted regions of the cortex which are associated with various physiological and functional brain changes.1,2,3
In 2007, O'Reardon et al., utilizing the NeuroStar device, published the results of an industry-sponsored, multisite, randomized, sham-stimulation controlled clinical trial in which 301 patients with major depression, who had previously failed to respond to at least one adequate antidepressant treatment trial, underwent either active or sham TMS over the left dorsolateral prefrontal cortex (DLPFC). The patients, who were medication-free at the time of the study, received TMS five times per week over 4-6 weeks.4
The results demonstrated that a sub-population of patients (those who were relatively less resistant to medication, having failed not more than two good pharmacologic trials) showed a statistically significant improvement on the Montgomery-Asberg Depression Scale (MADRS), the Hamilton Depression Rating Scale (HAMD), and various other outcome measures. In October 2008, supported by these and other similar results5,6,7, Neuronetics obtained the first and only Food and Drug Administration (FDA) approval for the clinical treatment of a specific form of medication-refractory depression using a TMS Therapy device (FDA approval K061053).
In this paper, we will explore the specified FDA approved NeuroStar depression treatment protocol (to be administered only under prescription and by a licensed medical profession in either an in- or outpatient setting).

In this article, we examine the methodology and considerations relevant to the FDA approved depression treatment protocol using the Neuronetics NeuroStar TMS device.

The Neuronetics NeuroStar Transcranial Magnetic Stimulation (TMS) System is a class II medical device that produces brief duration, pulsed magnetic ...

Treating Clinical Depression with Repetitive Deep Transcranial Magnetic Stimulation Using the Brainsway H1-coil

Repetitive transcranial magnetic stimulation (rTMS) is an emerging non-pharmacological approach to treating many brain-based disorders. rTMS uses electromagnetic coils to stimulate areas of the brain non-invasively. Deep transcranial magnetic stimulation (dTMS) with the Brainsway H1-coil system specifically is a type of rTMS indicated for treating patients with major depressive disorder (MDD) who are resistant to medication. The unique H1-coil design of this device is able to stimulate neuronal pathways that lie deeper in the targeted brain areas than those reached by conventional rTMS coils. dTMS is considered to be low-risk and well tolerated, making it a viable treatment option for people who have not responded to medication or psychotherapy trials for their depression.
Randomized, sham-control studies have demonstrated that dTMS produces significantly greater improvement in depressive symptoms than sham dTMS treatment in patients with major depression that has not responded to antidepressant medication. In this paper, we will review the methodology for treating major depression with dTMS using an H1-coil.

Here we present a protocol outlining the methodology for treatment of Major Depressive Disorder using the deep Transcranial Magnetic Stimulation (dTMS) system.

Repetitive transcranial magnetic stimulation (rTMS) is an emerging non-pharmacological approach to treating many brain-based disorders. rTMS uses ...

Behavior

A Visual Description of the Dissection of the Cerebral Surface Vasculature and Associated Meninges and the Choroid Plexus from Rat Brain

This video presentation was created to show a method of harvesting the two most important highly vascular structures, not residing within the brain proper, that support forebrain function. They are the cerebral surface (superficial) vasculature along with associated meninges (MAV) and the choroid plexus which are necessary for cerebral blood flow and cerebrospinal fluid (CSF) homeostasis. The tissue harvested is suitable for biochemical and physiological analysis, and the MAV has been shown to be sensitive to damage produced by amphetamine and hyperthermia 1,2. As well, the major and minor cerebral vasculatures harvested in MAV are of potentially high interest when investigating concussive types of head trauma. The MAV dissected in this presentation consists of the pial and some of the arachnoid membrane (less dura) of the meninges and the major and minor cerebral surface vasculature. The choroid plexus dissected is the structure that resides in the lateral ventricles as described by Oldfield and McKinley3,4,5,6. The methods used for harvesting these two tissues also facilitate the harvesting of regional cortical tissue devoid of meninges and larger cerebral surface vasculature, and is compatible with harvesting other brain tissues such as striatum, hypothalamus, hippocampus, etc. The dissection of the two tissues takes from 5 to 10 min total. The gene expression levels for the dissected MAV and choroid plexus, as shown and described in this presentation can be found at GSE23093 (MAV) and GSE29733 (choroid plexus) at the NCBI GEO repository. This data has been, and is being, used to help further understand the functioning of the MAV and choroid plexus and how neurotoxic events such as severe hyperthermia and AMPH adversely affect their function.

This video presentation shows a method of harvesting the two most important highly vascular structures that support forebrain function. They are the cerebral surface (superficial) vasculature along with associated meninges (MAV) and the choroid plexus which are necessary for cerebral blood flow and cerebrospinal fluid (CSF) homeostasis.

This video presentation was created to show a method of harvesting the two most important highly vascular structures, not residing within the brain ...

Controlling Parkinson's Disease With Adaptive Deep Brain Stimulation

Adaptive deep brain stimulation (aDBS) has the potential to improve the treatment of Parkinson&#39;s disease by optimizing stimulation in real time according to fluctuating disease and medication state. In the present realization of adaptive DBS we record and stimulate from the DBS electrodes implanted in the subthalamic nucleus of patients with Parkinson&#39;s disease in the early post-operative period. Local field potentials are analogue filtered between 3 and 47 Hz before being passed to a data acquisition unit where they are digitally filtered again around the patient specific beta peak, rectified and smoothed to give an online reading of the beta amplitude. A threshold for beta amplitude is set heuristically, which, if crossed, passes a trigger signal to the stimulator. The stimulator then ramps up stimulation to a pre-determined clinically effective voltage over 250 msec and continues to stimulate until the beta amplitude again falls down below threshold. Stimulation continues in this manner with brief episodes of ramped DBS during periods of heightened beta power.
Clinical efficacy is assessed after a minimum period of stabilization (5 min) through the unblinded and blinded video assessment of motor function using a selection of scores from the Unified Parkinson&#39;s Rating Scale (UPDRS). Recent work has demonstrated a reduction in power consumption with aDBS as well as an improvement in clinical scores compared to conventional DBS. Chronic aDBS could now be trialed in Parkinsonism.

Adaptive deep brain stimulation (aDBS) is effective for Parkinson&#8217;s disease, improving symptoms and reducing power consumption compared to conventional deep brain stimulation (cDBS). In aDBS we track a local field potential biomarker (beta oscillatory amplitude) in real time and use this to control the timing of stimulation.

Adaptive deep brain stimulation (aDBS) has the potential to improve the treatment of Parkinson&#39;s disease by optimizing stimulation in real time ...

Medicine

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method

To achieve greater clinical efficacy, a revolution in treatment for major depressive disorder (MDD) is highly anticipated. Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive and safe neuromodulation technique that immediately changes brain activity. Despite its wide application in the treatment for MDD, the treatment response remains different among individuals, which may be attributable to the inaccurate positioning of the stimulation target. Our study aims to examine whether the functional magnetic resonance imaging (fMRI)-assisted positioning improves the efficacy of rTMS in treating depression. We intend to identify and stimulate the subregion of dorsolateral prefrontal cortex (DLPFC) in MDD with strongest anti-correlation with the subgenual anterior cingulate cortex (sgACC), and to conduct a comparative investigation of this novel method and the traditional 5-cm rule. To achieve more precise stimulation, both methods were applied under the guidance of neuronavigation system. We expected that the TMS treatment with individualized positioning based on resting state functional connectivity may show better clinical efficacy than the 5-cm method.

The present protocol describes the application of repetitive transcranial magnetic stimulation (rTMS), where a subregion of the dorsolateral prefrontal cortex (DLPFC) with the strongest functional anticorrelation with the subgenual anterior cingulate cortex (sgACC) was located as the stimulation target under the assistance of a fMRI-based neuronavigation system.

To achieve greater clinical efficacy, a revolution in treatment for major depressive disorder (MDD) is highly anticipated. Repetitive transcranial ...

Measuring Spinal Presynaptic Inhibition in Mice By Dorsal Root Potential Recording In Vivo

Presynaptic inhibition is one of the most powerful inhibitory mechanisms in the spinal cord. The underlying physiological mechanism is a depolarization of primary afferent fibers mediated by GABAergic axo-axonal synapses (primary afferent depolarization). The strength of primary afferent depolarization can be measured by recording of volume-conducted potentials at the dorsal root (dorsal root potentials, DRP). Pathological changes of presynaptic inhibition are crucial in the abnormal central processing of certain pain conditions and in some disorders of motor hyperexcitability. Here, we describe a method of recording DRP in vivo in mice. The preparation of spinal cord dorsal roots in the anesthetized animal and the recording procedure using suction electrodes are explained. This method allows measuring GABAergic DRP and thereby estimating spinal presynaptic inhibition in the living mouse. In combination with transgenic mouse models, DRP recording may serve as a powerful tool to investigate disease-associated spinal pathophysiology. In vivo recording has several advantages compared to ex vivo isolated spinal cord preparations, e.g. the possibility of simultaneous recording or manipulation of supraspinal networks and induction of DRP by stimulation of peripheral nerves.

Measuring Spinal Presynaptic Inhibition in Mice By Dorsal Root Potential Recording In Vivo

GABAergic presynaptic inhibition is a powerful inhibitory mechanism in the spinal cord important for motor and sensory signal integration in spinal cord networks. Underlying primary afferent depolarization can be measured by recording of dorsal root potentials (DRP). Here we demonstrate a method of in vivo recording of DRP in mice.

Presynaptic inhibition is one of the most powerful inhibitory mechanisms in the spinal cord. The underlying physiological mechanism is a depolarization of ...

MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder

Here we outline the protocol for magnetic resonance imaging (MRI) guided repetitive transcranial magnetic stimulation (rTMS) to the dorsal medial prefrontal cortex (dmPFC) in patients with major depressive disorder (MDD). Technicians used a neuronavigation system to process patient MRIs to generate a 3-dimensional head model. The head model was subsequently used to identify patient-specific stimulatory targets. The dmPFC was stimulated daily for 20 sessions. Stimulation intensity was titrated to address scalp pain associated with rTMS. Weekly assessments were conducted on the patients using the Hamilton Rating Scale for Depression (HamD17) and Beck Depression Index II (BDI-II). Treatment-resistant MDD patients achieved significant improvements on both HAMD and BDI-II. Of note, angled, double-cone coil rTMS at 120% resting motor threshold allows for optimal stimulation of deeper midline prefrontal regions, which results in a possible therapeutic application for MDD. One major limitation of the rTMS field is the heterogeneity of treatment parameters across studies, including duty cycle, number of pulses per session and intensity. Further work should be done to clarify the effect of stimulation parameters on outcome. Future dmPFC-rTMS work should include sham-controlled studies to confirm its clinical efficacy in MDD.

Here we outline the procedure for MRI-guided repetitive transcranial magnetic stimulation to the dorsomedial prefrontal cortex as an experimental treatment for major depressive disorder.

Here we outline the protocol for magnetic resonance imaging (MRI) guided repetitive transcranial magnetic stimulation (rTMS) to the dorsal medial ...

Vagus Nerve Stimulation As an Adjunctive Neurostimulation Tool in Treatment-resistant Depression

Vagus nerve stimulation (VNS) is an approved neurostimulation therapy. The purpose of the method is to treat patients with therapy-resistant depression (TRD). VNS exhibits antidepressive and stabilizing effects. This method is particularly useful as a long-term treatment, in which up to two-thirds of patients respond. The vagus nerve stimulator is positioned on the left vagus nerve during a surgical procedure and is activated telemetrically by a wand connected to a handheld computerized device. The treating physician can perform various adjustments of the vagus nerve stimulator during in-office visits (e.g., by modifying stimulation intensity or stimulation frequency) to achieve maximum therapeutic effects with low side effects. Set-up of the device usually takes several months. Typical side effects include wound infection, temporary salivation, coughing, paralysis of the vocal cords, bradycardia, or even asystole. The patient can stop the VNS by placing a magnet over the generator. The current protocol describes delivery of the specific stimulation tool and methods for adjusting the tuning parameters to achieve the best remission rates in patients with TRD.

Vagus nerve stimulation (VNS) has been shown to be effective as an adjunct treatment for treatment-resistant depression (TRD). VNS leads to antidepressive and antisuicidal effects and quality of life improvements. This protocol offers a step-by-step guide to managing and adjusting a vagus nerve stimulator for efficient treatment of TRD.

Vagus nerve stimulation (VNS) is an approved neurostimulation therapy. The purpose of the method is to treat patients with therapy-resistant depression ...

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder

Samenvatting

Meer video's verkennen

Hoofdstukken in deze video