Stereotactic electroencephalography in epilepsy patients for mapping of neural circuits related to emotional and psychiatric behaviors: a systematic review

Abstract

OBJECTIVE Stereotactic electroencephalography (sEEG) is an increasingly utilized method for identifying electrophysiological processes underlying sensorimotor, cognitive, and emotional behaviors. In this review, the authors outline current research using sEEG to investigate the neural activity underlying emotional and psychiatric behaviors. Understanding the current structure of intracranial research using sEEG will inform future studies of psychiatric disease and therapeutics for effective neuromodulation. METHODS The authors conducted a comprehensive systematic review of studies according to PRISMA guidelines to investigate behaviors related to psychiatric conditions in patients with epilepsy undergoing monitoring with sEEG. Articles indexed on PubMed between 2010 and 2022 were included if they studied emotions or affective behaviors or met the National Institute of Mental Health Research Domain Criteria positive and negative valence domains. Data extracted from articles included study sample size, paradigms and behavioral tasks employed, cortical and subcortical targets, EEG analysis methods, and identified electrophysiological activity underlying the studied behavior. The Newcastle-Ottawa Scale was used to assess bias risk. RESULTS Thirty-two primary articles met inclusion criteria. Study populations ranged from 3 to 39 patients. The most common structures investigated were the amygdala, insula, orbitofrontal cortex (OFC), hippocampus, and anterior cingulate cortex (ACC). Paradigms, stimuli, and behavioral tasks widely varied. Time-frequency analyses were the most common, followed by connectivity analyses. Multiple oscillations encoded a variety of behaviors related to emotional and psychiatric conditions. High gamma activity was observed in the amygdala and anterior insula in response to aversive audiovisual stimuli and in the OFC in response to reward processing. ACC beta band power increases and hippocampal-amygdala beta coherence variations were predictive of worsening mood states. Insular and amygdalar theta oscillations encoded social pain and fear learning, respectively. Most studies performed passing recordings, allowing for the decoding of affective states and depression symptoms, while other studies utilized direct stimulation, such as in the OFC to improve mood symptoms. CONCLUSIONS Stereotactic EEG in epilepsy has identified multiple corticolimbic structures with specific oscillatory and synchronization activity underlying a diverse range of behaviors related to emotions and affective conditions. Given the heterogeneity of psychiatric conditions, sEEG provides an opportunity to study these neural correlates to develop personalized effective neuromodulatory treatments. Future studies should focus on optimizing paradigms and tasks to investigate a broad range of behavioral phenotypes that overlap across psychiatric conditions.

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