Decoding naturalistic affective behaviour from spectro-spatial features in multiday human iEEG

Bijanzadeh, Maryam; Khambhati, Ankit N.; Desai, Maansi; Wallace, Deanna L.; Shafi, Alia; Dawes, Heather E.; Sturm, Virginia E.; Chang, Edward F.

doi:10.1038/s41562-022-01310-0

Cited by 35 publications

(41 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The spectral pattern of correlation we observed, increased high-frequency activity and reduced low-frequency activity, has also been found to be important for decoding positive and negative affect in epilepsy patients 40 . While affective state is not identical to our depression-specific measures, it is likely related.…”

Section: Discussionsupporting

confidence: 64%

“…Due to the sparse sampling of symptom state relative to that of the electrophysiological data, we began with a model formulation forced to use only the smallest subset of regions, thus producing a model that is more generalizable and less prone to overfitting. The consistent selection of ACC in all patients speaks to the importance of this region in mood and cognitive regulation 40,54 . Even as the region selectivity requirement was relaxed, the prominence of ACC remained (Fig.…”

Section: Discussionmentioning

confidence: 88%

“…To evaluate how neural activity varied throughout the NMU stay, we extracted spectral power from six frequency bands: delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), gamma (35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50), and high-gamma (70-150 Hz), yielding six spectral power features per channel for each depression severity measurement. Spectral power features in prefrontal channels showed strong correlations with symptom severity scores after correcting for multiple comparisons.…”

Section: Spectral Activity Across Prefrontal Regions Correlates With ...mentioning

confidence: 99%

See 2 more Smart Citations

Decoding Depression Severity from Intracranial Neural Activity

Xiao

Provenza

Asfouri

et al. 2022

Preprint

View full text Add to dashboard Cite

Disorders of mood and cognition are prevalent, disabling, and notoriously difficult to treat. Fueling this challenge in treatment is a significant gap in our understanding of their neurophysiological basis. Here, we used intracranial neural recordings in three patients with severe depression to investigate the neural substrates of this disorder. Across prefrontal regions, we found that reduced depression severity is associated with decreased low-frequency neural activity and increased high-frequency activity. When constraining our model to decode using a single region, spectral changes in the anterior cingulate cortex best predicted depression severity in all three subjects. Relaxing this constraint revealed unique, individual-specific sets of spatio-spectral features predictive of symptom severity, reflecting the heterogeneous nature of depression. The ability to decode depression severity from neural activity increases our fundamental understanding of how depression manifests in the human brain and provides a target neural signature for personalized neuromodulation therapies.

show abstract

Section: Discussionsupporting

confidence: 64%

Section: Discussionmentioning

confidence: 88%

Section: Spectral Activity Across Prefrontal Regions Correlates With ...mentioning

confidence: 99%

See 1 more Smart Citation

Decoding Depression Severity from Intracranial Neural Activity

Xiao

Provenza

Asfouri

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The evidence of a path from the midcingulate cortex to the : posterior insula, which increases hypersensitivity to nociceptive stimuli, further solidifies the view that the coherent activity between the midcingulate and insula supports the processing of emotions (Tan et al, 2017). In an intracranial EEG study using a more ecologically valid paradigm with epilepsy patients, insula and anterior cingulate cortex were observed to be relatively more associated with the positive and negative affective behaviours than the amygdala and orbitofrontal cortex in the high-frequency band (Bijanzadeh et al, 2022).…”

Section: Role Of Cingulate Cortex Insula and Parahippocampal Gyrus In...supporting

confidence: 53%

Manuscript

Mishra¹,

Srinivasan²,

Tiwary³

2022

Preprint

View full text Add to dashboard Cite

While naturalistic stimuli like movies better resemble the complexity of the real world and are perhaps crucial to understanding the dynamics of emotion processing, there is limited research on emotions with naturalistic stimuli. There is a need to understand the temporal dynamics of emotion processing and their relationship to different dimensions of emotion experience. In addition, there is a need to understand the dynamics of functional connectivity underlying different emotional experiences that occur during or prior to such experiences. To address these questions, we recorded EEG and asked participants to mark the temporal location of their emotional experience as they watched a video. We also obtained self-assessment ratings for emotional multimedia stimuli. We obtained dynamic functional connectivity (DFC) patterns in all the frequency bands. We also performed regression analysis to evaluate whether temporal variability in DFC (tvDFC) could predict different dimensions of emotional experience. We observed that the connectivity patterns in the upper beta band could differentiate emotion categories better during or prior to the reported emotional experience. The functional connectivity dynamics is primarily related to emotional arousal followed by dominance. The hubs in the functional networks were found across the right frontal and bilateral parietal lobes, which have been reported to facilitate affect, interoception, action and memory related processing. The results support constructivist theories of emotional experience and show that changes in dynamic functional connectivity can predict aspects of our emotional experience.

show abstract

“…28 Other authors analyzed amygdala activity via restingstate or naturalistic paradigms to classify neural activity predictive of affective states. 14,16,29,30 Scangos et al examined 24-hour resting-state recordings in 13 patients who were categorized to low-or high-depression groups based on the Patient Health Questionnaire-9 (PHQ-9). 14 With the use of principal components analysis, a biomarker based on decreased amygdala and hippocampal beta power and increased OFC and cingulate beta power correctly classified 78% of patients with a high level of depression symptoms.…”

Section: Amygdala and Hippocampusmentioning

confidence: 99%

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

Tan

Yamamoto

Cleary

et al. 2023

Neurosurgical Focus

View full text Add to dashboard Cite

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.

show abstract

Decoding naturalistic affective behaviour from spectro-spatial features in multiday human iEEG

Cited by 35 publications

References 56 publications

Decoding Depression Severity from Intracranial Neural Activity

Decoding Depression Severity from Intracranial Neural Activity

Manuscript

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

Contact Info

Product

Resources

About