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PROJECT SUMMARY: PROJECT 4
The purpose of PROJECT 4 is to investigate computationally-informed precision treatments to improve two
forms of state representation dysfunction in early psychosis: 1) State estimation processes at the perceptual
input level, which we will target through auditory discrimination training; 2) State representation stability of
auditory information, which we will target through auditory working memory training. Participants will be drawn
from PROJECT 3, where they will have been assessed with behavioral and EEG-fMRI measures at baseline
and after 6 months of usual care, so that their initial characteristics and clinical trajectory will be
known. Participants will be stratified on an EEG index of state estimation processes (fronto-parietal theta
power at DPX encoding), which we posit to be present in ~60% of subjects, and randomly assigned to one of
the two training strategies. Our goal is not to perform a treatment efficacy study comparing these two
interventions. Rather, we seek to use predictions derived from attractor network models to test the effects of
neuroplasticity-based precision treatments targeting two distinct information processing pathologies in early
psychosis, with the ultimate goal of improving state representation processes and cognition.
In Aim 1, we will investigate parameter changes in the fit attractor network models in each subject group, fit to
DPX and Bandit Task behavioral data immediately after training and 3 months later, and we will assess
whether parameter changes reflect restorative or compensatory modifications. We will also test the hypothesis
that state representation processes and cognitive performance show greater improvement in subjects who
received training tailored to their state estimation parameter. In Aim 2, we will examine how specific
parameter changes in attractor network models relate to neurophysiological changes in measures indexing
activity timing, excitatory-inhibitory balance, and system noise, in order to identify which changes are the most
predictive of improved cognition. Causal discovery analyses will be employed to identify causal relationships
among computational parameters, behavioral data, neurophysiologic indices, treatment assignment, and one-
year clinical trajectories.
Status | Finished |
---|---|
Effective start/end date | 4/1/20 → 3/31/24 |
Funding
- National Institute of Mental Health: $414,577.00
- National Institute of Mental Health: $317,369.00
- National Institute of Mental Health: $409,433.00
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Projects
- 1 Finished