Major depressive disorder (MDD) is common and causes significant disability world-wide. While typically responsive to medications and therapy, there remain a subset of patients who are treatment resistant. Novel approaches are critical to treat these patients. MDD is likely caused by dysfunction in distributed neural networks, a perspective consistent with the etiological and diagnostic heterogeneity of this disorder. While imaging and electroencephalography (EEG) have helped identify MDD circuitry, no consensus has been reached on the identification of diagnostic biomarkers. Furthermore, the dynamics of MDD circuitry in relation to symptom severity is unknown. Characterization of circuit signatures that define MDD symptom severity states and the extent to which these circuits are modifiable using electrical stimulation are critical for therapeutic advancement. Intracranial EEG (iEEG) offers a high spatial and temporal resolution method to study depression networks. For the first time, we have an unparalleled opportunity to study such circuits in MDD patients participating in a clinical trial of personalized responsive neurostimulation for treatment resistant depression (PRESIDIO). In stage 1 of this trial, participants are implanted with 160 electrodes from 10 sub-chronic intracranial leads across 10 brain sites for 10 days. The goal of this parent study stage is to optimize brain-site targeting for deep brain stimulation. In the current project, we will leverage the opportunity to study MDD circuit principles from cortical and deep brain structures over a multi-day time period. In this ancillary study to the parent clinical trial, we carry out a set of experiments that establish basic principles of network dynamics underlying MDD from direct neural recordings. This study is organized around the principal concept that brain circuit dysfunction is reflected in abnormal signatures of functional connectivity and rhythmic local-field activity. This concept is supported by our pilot work where we found evidence of distinct MDD networks characterized by functional connectivity and spectral activity. This project builds on our preliminary findings in two aims. In Aim 1, we characterize state-dependent functional connectivity and spectral activity in relation to symptom severity. In Aim 2, we will examine the manner and time course in which targeted electrical stimulation acutely modifies circuits. Together, this research will yield the first characterization of connectivity and activity dynamics in MDD over a multi-day period from direct neural recordings. This rare insight into MDD circuity provided by this novel dataset establishes proof-of-concept principles for biomarker development and therapeutic target selection that could critically advance personalized MDD treatments.

Background:

Major depression (MDD) is a leading cause of disability worldwide, with high rates of treatment resistance. This speaks strongly for the need to improve our understanding of the causes and underlying neurobiology of this condition so that we can developed improved treatments. Our current understanding of MDD is quite limited. However, available evidence points to dysfunction in distributed neural networks, a perspective consistent with the etiological and diagnostic heterogeneity of this disorder. While imaging and electroencephalography (EEG) have helped identify MDD circuitry, no consensus has been reached on the identification of diagnostic biomarkers. Furthermore, the dynamics of MDD circuitry in relation to symptom severity is unknown. Whether there are neural signatures of circuits that define MDD symptom severity states and the extent to which these circuits are modifiable using direct electrical stimulation are unanswered questions critical for therapeutic advancement.

Intracranial EEG (iEEG) offers a promising high-resolution method to study network fundamentals and help elucidate the neural dysfunction underlying MDD. For the first time, we have the opportunity to use this technique to study circuits in MDD in patients participating in a clinical trial of personalized responsive neurostimulation for treatment resistant depression (PRESIDIO). In stage 1, participants are implanted with 160 electrodes across 10 brain sites for 10 days to target brain site placement of chronic deep brain stimulation leads in stage 2. This stage offers the unique opportunity to study principles of MDD circuits from cortical and deep brain structures over a multi-day time period. The current study capitalizes on that opportunity. It is an ancillary study to the PRESIDIO trial where we will have the opportunity to perform a set of experiments that establish basic principles of network dynamics underlying MDD from direct neural recordings.

This project is organized around the principal concept that brain circuit dysfunction is reflected in abnormal signatures of functional connectivity and rhythmic local-field activity. The overarching objective is to establish proof-of concept for two fundamental principles of circuit function in depression: i) that circuit features are related to MDD symptom severity, and ii) that perturbation with focal electrical stimulation can acutely modify these circuits. Our rationale for this study is based on: 1) preliminary work, in which we identified a set of connectivity and activity features that were predictive of a diagnosis of co-morbid depression in patients with epilepsy; 2) published work by our group that found targeted stimulation acutely changes mood and spectral power across a broad network in patients with epilepsy; and 3) pilot data for this proposal in which we establish proof-of-concept that MDD symptom severity states can be defined using a 6-question version of the Hamilton Depression Rating Scale (HAMD6). It remains unknown whether circuit features identified in an epilepsy population are generalizable to patients with MDD in the absence of epilepsy, and the manner in which these neural features vary with symptom states - questions we can address in this proposal. We hypothesize that a set of neural connectivity and activity features will characterize symptom severity states in MDD implicating their potential to serve as a state vs. trait MDD biomarker, and that circuit features can be acutely modified by brain stimulation indicating their potential to serve as a therapy target.

Goals:

1. Aim 1. Biomarker Development: Characterize the pattern of network connectivity and activity that is associated with symptom severity. The objective of this goal is to establish proof-of concept that circuit features are related to major depressive disorder (MDD) symptom severity. Our working hypothesis is that spectral activity and connectivity within and across the amygdala, hippocampus, SGC, OFC, and VC will capture the majority of variance in MDD symptom severity. The rationale behind this goal is preliminary work that implicates corticolimbic circuit features in diagnostic biomarkers in MDD, and our pilot data showing features to be predictive of symptom state.
2. Aim 2. Acute Change with Circuit Perturbation: Characterize the capacity for brief (2-10 min) periods of targeted electrical stimulation to acutely modify connectivity and activity. The objective of this goal is to establish proof-of-concept that targeted electrical stimulation can acutely modify circuit activity and connectivity features indicating their potential to serve as therapy targets. Our working hypothesis is that graph theoretic properties of MDD network nodes will distinguish their capacity to affect network connectivity and activity following stimulation. The rationale is work by our group that found stimulation to corticolimbic targets acutely changed spectral power across a network, and that nodal properties exert predictive effects of stimulation on networks in epilepsy. A node with high outdegree is a hub of high network influence and could be indicative of a good treatment target. In contrast, a node with high indegree suggests a region that is influenced by stimulation in other regions and may play a role in sensing modifiable neural signatures of MDD.

Inclusion Criteria:

• Meet Diagnostic and Statistical Manual-V (DSM-V) diagnostic criteria for Major Depressive Disorder (MDD) without psychosis based on a Structured Clinical Interview for DSM-V (SCID)
• Current episode ≥ 2 years
• Treatment-resistant (4 adequate trials including electroconvulsive therapy (ECT)), 3 classes of medications, one augmentation strategy, psychotherapy) as measured by the antidepressant treatment history form (ATHF)
• Failed ECT due to inability to achieve sustained response (2 failed attempts to discontinue ECT treatment) or discontinued due to intolerable side effects
• Montgomery Asberg Depression Rating Scale (MADRS) score of > 26 at both baseline and screening visit
• Presence of variability on repeated administrations of depression rating scales (minimum of 2-point variation on the HAMD-6 administered 3 times a day for 3 days), which is required for the identification of a neural biomarker
• No changes to psychotropic medication regimen during the 4 weeks prior to entry into and the duration of the study
• Willing and able to undergo invasive brain recording/stimulation study
• Willing and able to attend multiple research visits and perform at-home research protocol
• Willing and able to provide informed consent
• Ability to speak and read English

Exclusion Criteria:

• Meets DSM-V criteria for a psychotic disorder, eating disorder, panic disorder, posttraumatic stress disorder, bipolar disorder, obsessive compulsive disorder, tic disorder, or another comorbid psychiatric disorder other than MDD or generalized anxiety disorder based on a SCID
• Generalized anxiety disorder is the primary DSM-V disorder during the current MDD episode
• Active suicidal ideation with intent and plan as defined by a score of 5 on the Columbia suicide severity rating scale (C-SSRS)
• History of suicide attempt requiring hospitalization in previous 2 years
• Meets criteria for alcohol or substance abuse or dependence (other than caffeine) in previous 6 months, determined by the SCID
• Has a personality disorder based on the investigator's assessment that the investigator believes will adversely impact subject compliance or safety
• Fibromyalgia or chronic fatigue syndrome
• Current condition requiring chronic narcotic use
• History of traumatic brain injury, another neurological disorder, or developmental delay
• History of seizures
• MRI (done within one year of the first visit) with significant abnormalities
• Previous ablative intracranial surgery or previously implanted deep brain stimulation system or any previously implanted device treatment involving brain stimulation
• Implantable hardware not compatible with MRI or with the study
• Major medical co-morbidities increasing the risk of surgery including severe diabetes, major organ system failure, history of hemorrhagic stroke, need for chronic anticoagulation other than aspirin, active infection, intracranial space occupying lesion, increased intracranial pressure, cardiovascular accident within the last month, aneurysm abnormality, retinal detachment, unstable cardiovascular disease (recent MI, severe ischemia, severe or uncontrolled hypertension), immunocompromised state, or malignancy with < 5 years life expectancy
• Inability to stop Coumadin or platelet anti-aggregation therapy for surgery and after surgery
• Coagulopathy. Patients will be excluded unless assessed and cleared by hematology
• Allergies or known hypersensitivity to materials in the NeuroPace RNS® System (i.e. titanium, polyurethane, silicone, polyetherimide, stainless steel)
• Subject lives alone without possibility of caregiver support post-hospital stay
• Inability to comply with study follow-up visits
• Women who are pregnant, plan to become pregnant, or breast feeding
• Inability to speak and/or read English
• Inability to give consent
• Significant cognitive impairment or dementia (Montreal Cognitive Assessment (MoCA) < 25)

6 Individuals meeting the inclusion/exclusion criteria who are participating in the PRESIDIO trial of personalized intracranial closed-loop stimulation for treatment of treatment-resistant major depression.

All the values of the variables for all published findings, will be added to a data archive. This data archive will be free of identifiers that would permit linkages to individual research participants and variables that could lead to deductive disclosure of the identity of individual subjects. The data will be accompanied by a file including documentation of the data archive including information about the methodology and procedures used to collect the data, definitions of variables, and variable field locations. This file will also state the requirement that users submit an email notification of the intent to access the data and that any publications using these data acknowledge the source of the data. Should any intellectual property arise from the proposed study that may be patentable, UCSF will ensure that the related technology remains widely available in timely fashion to the research community in compliance with policies and regulations governing research awards from the NIH

We will release and share data in a timely manner, with the date of release to be no later than acceptance for publication of our main findings from our final data set.