Optimizing treatments in mental health requires an easy to obtain, continuous, and objective measure of internal mood. Unfortunately, current standard-of-care clinical scales are sparsely sampled, subject to recency bias, underutilized, and are not validated for acute mood monitoring. The recent shift to remote care also requires novel methods to measure internal mood. Recent advances in computer vision have allowed the accurate quantification of observable speech patterns and facial representations. The continuous and objective nature of these audio-facial behavioral outputs also enable the study of their neural correlates. Here, the investigators hypothesize that video-derived audio-facial behaviors have discrete neural representations in the limbic network and can provide a critical set of reliable longitudinal estimates of mood at low cost across home and clinic settings.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
NONE
Enrollment
10
Surgically-implanted intracranial electrodes.
Stanford University
Stanford, California, United States
RECRUITINGQuantitative Audio-Facial Change
Quantitative percent change in each audio-facial feature before and after direct electrical stimulation at each site.
Time frame: 5 minutes
Quantitative Mood Change
Quantitative percent change in Immediate Mood Scaler (IMS) after direct electrical stimulation at each site compared to a baseline period before sham. The minimum score on the IMS is 7 and the maximum is 154, with lower scores reflecting more negative mood states.
Time frame: 5 minutes
Correlation between Audio-Facial and Mood Change
Quantitative audio facial changes will be compared to quantitative changes in mood at each site by means of correlation and binary comparisons.
Time frame: 5 minutes
Qualitative Mood Change
Qualitative articulation of mood (participants freely articulate mood after direct electrical stimulation at each site) and speech transcripts will be analyzed for ratio of positive and negative valence words.
Time frame: 5 minutes
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