Distributed Subnetworks of Depression Defined by Direct Intracranial Neurophysiology.

Major depressive disorder is a common and disabling disorder with high rates of treatment resistance. Evidence suggests it is characterized by distributed network dysfunction that may be variable across patients, challenging the identification of quantitative biological substrates. We carried out this study to determine whether application of a novel computational approach to a large sample of high spatiotemporal resolution direct neural recordings in humans could unlock the functional organization and coordinated activity patterns of depression networks. This group level analysis of depression networks from heterogenous intracranial recordings was possible due to application of a correlational model-based method for inferring whole-brain neural activity. We then applied a network framework to discover brain dynamics across this model that could classify depression. We found a highly distributed pattern of neural activity and connectivity across cortical and subcortical structures that was present in the majority of depressed subjects. Furthermore, we found that this depression signature consisted of two subnetworks across individuals. The first was characterized by left temporal lobe hypoconnectivity and pathological beta activity. The second was characterized by a hypoactive, but hyperconnected left frontal cortex. These findings have applications toward personalization of therapy.

Closed-loop neuromodulation in an individual with treatment-resistant depression.

Deep brain stimulation is a promising treatment for neuropsychiatric conditions such as major depression. It could be optimized by identifying neural biomarkers that trigger therapy selectively when symptom severity is elevated. We developed an approach that first used multi-day intracranial electrophysiology and focal electrical stimulation to identify a personalized symptom-specific biomarker and a treatment location where stimulation improved symptoms. We then implanted a chronic deep brain sensing and stimulation device and implemented a biomarker-driven closed-loop therapy in an individual with depression. Closed-loop therapy resulted in a rapid and sustained improvement in depression. Future work is required to determine if the results and approach of this n-of-1 study generalize to a broader population.

A Gaussian Process Model of Human Electrocorticographic Data.

We present a model-based method for inferring full-brain neural activity at millimeter-scale spatial resolutions and millisecond-scale temporal resolutions using standard human intracranial recordings. Our approach makes the simplifying assumptions that different people's brains exhibit similar correlational structure, and that activity and correlation patterns vary smoothly over space. One can then ask, for an arbitrary individual's brain: given recordings from a limited set of locations in that individual's brain, along with the observed spatial correlations learned from other people's recordings, how much can be inferred about ongoing activity at other locations throughout that individual's brain? We show that our approach generalizes across people and tasks, thereby providing a person- and task-general means of inferring high spatiotemporal resolution full-brain neural dynamics from standard low-density intracranial recordings.

Psychological Burden and Gender Differences in Methamphetamine-Dependent Individuals in Treatment.

BACKGROUND AND OBJECTIVES: Little is known about gender differences in methamphetamine (METH)-dependent users. The objective of this study was to examine potential gender differences in four domains: drug use history, psychological burden, current symptomology, and coping strategy. METHODS: One hundred twenty four METH-dependent individuals (men; n = 75) were enrolled from substance use treatment programs. Participants filled out detailed questionnaires in the four domains. RESULTS: Men reported earlier first alcohol and drug use than women, but there was no difference in the age of first METH use or frequency of METH use. Women reported experiencing problems because of METH use at a younger age. Women were also more likely to have injected METH in the past year and they reported greater severity of drug problems compared to men. METH-dependent women had greater psychological burden, reported more use of an emotional-coping strategy, and had greater childhood emotional and sexual trauma. CONCLUSIONS: Overall, this study suggests that, unlike many other illicit drugs, severity of use and problems associated with use were not elevated in METH-dependent men compared to women. In fact, several factors indicated more severe patterns of use or risk factors in women.