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 ...

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 border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<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&#160;</td>
		</tr>
		<tr>
			<td>Responsive Neurostimulation System (RNS)&#160;</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.

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

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

We are assessing the therapeutic benefit of closed-loop personalized deep brain stimulation for the treatment of major depressive disorder. This protocol outlines how to identify a personalized neural biomarker that is correlated with symptom severity, and then program an implanted neurostimulator to administer stimulation using that biomarker. Prior applications of deep brain stimulation for depression used continuous stimulation, which was always on, regardless of symptom status.This protocol describes using closed-loop stimulation in which we only deliver stimulation during high symptom states. Continued work to identify biomarkers for control of closed-loop stimulation will facilitate an approach where we can target the unique time courses of different symptoms.

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

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.

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

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Neuroscience

Neurostimulation System Setup and Symptom Collection for Patient At-Home Recordings

To begin, ensure the patient has fully recovered from surgery following the implantation of the device with cortical in depth leads. Connect the telemetry wand to the programmer and instruct the patient to hold it over the implantable neurostimulator to attach it to a tethering hat. Using the programmer, log onto the patient data management system, navigate to the correct patient, select Programming, and then choose the Change ECOG Capture option.Proceed to set the capture window to a maximum of 240 seconds for the four configured channels using the dropdown selection. Using the dropdown selections, set the reserve space for magnet reservations to two and the value to zero for any other trigger types. Select the Review and Program button to synchronize the newly programmed settings with the patient's implantable neurostimulator.Verify any changes in the table and select the Confirm Programming button. To prepare for the Patient Symptom Report Survey, use a web-based survey tool such as REDCap, including sliders for VAS D, VAS A, VAS E, and selection responses for each question of the HAM-D 6. Ensure to log the time of survey start and completion.Provide the patient with the unique URL generated by REDCap for assessing the symptom surveys through either email or text message.

Procedure for Concurrent At-Home Symptom Reports and Neural Recordings

Instruct the patient to set up the equipment, including the remote monitor and wand, magnet, and device for completing the survey. Turn on the remote monitor and, using the wand, interrogate the device. Then download the electrocorticography recordings since the last interrogation to the remote monitor.Swipe the magnet over the implantable neurostimulator to trigger a magnet recording. Start a timer and use the previously generated, unique REDCap URL to complete the symptom survey. After four minutes have elapsed or the patient completes the survey, whichever is longer, the patient will swipe the magnet over the implantable neurostimulator again to trigger another recording After at least 80 seconds, use the wand to interrogate the device again and transfer the data from the two magnet swipes to the remote monitor At least once a day, connect the remote monitor to the internet using ethernet and select Transfer Data and Synchronize on the remote monitor to send the collected data to the cloud.

Programming Device Detector Settings for Closed-Loop Neurostimulation

Begin by logging onto the patient Data Management System, using the programmer. Next, select the correct Patient, Programming, and Change Detection. Based on the selected personalized biomarker, select the correct channel for detecting the activity.For activity detection, select Rhythmic Activity, which connotes a band pass detector. Click More Controls in Advanced Settings. Select the desired minimum and maximum frequency.Ensure to turn on the band pass and turn off the line length in Area Settings. Additionally, set the inversion logic to Not Inverted. Program the detector by setting the minimum amplitude to 0.8%and the minimum duration to 0.64 seconds.After selecting all the detector settings, click the Done button to close all programming windows. Place the wand over the patient's implantable neurostimulator, and select Review All Changes in Program RNS. The biomarker discovery of symptoms was performed based on the neurospectral power between the low depression and the high depression states.It was found that the best choice for a frequency-specific biomarker in this example is 13 to 30 hertz of OFC, three to four.

1.6K Views.  University of California, San Francisco.  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. 

Deep Brain Stimulation for Treatment of Major Depression

Summary