We use computational models to study the mechanisms of cortical microcircuit activity and brain signals in mental health. We develop biophysical models of human cortical circuits that integrate unique human cellular and connectivity data. We study how disease-related changes in synaptic connections and ion channels affect information processing in cortical circuits, and identify biomarkers of the circuit changes in brain signals to improve diagnosis, monitoring and treatment of mental disorders.
Current research projects in the lab:
Somatostatin synaptic inhibition and cortical microcircuit processing in health and depression
We use our detailed models of human cortical circuits to study the effect of reduced synaptic inhibition by somatostatin (SST) interneurons on cortical pyramidal neuron spiking and cortical processing in depression.
Identifying EEG biomarkers of reduced SST inhibition in cortical microcircuits models of depression
We use our detailed models of human cortical circuits to identify biomarkers in cortical LFP and EEG that are signatures of reduced SST inhibition in depression.
In-silico testing synaptic modulation in cortical microcircuits by pharmacology for depression
We use our detailed models of human cortical circuits to test in silico the effect of candidate pharmacology for treating depression (GABA positive-allosteric-modulators) on spiking activity and LFP in human cortical slices. We then characterize the effect of the pharmacology on cortical processing.
Inhibition effects on prefrontal cortical microcircuit processing in Schizophrenia
We model prefrontal cortical microcircuit processing of oddball stimuli in health and Schizophrenia, to identify target mechanisms and EEG biomarkers.