Leave-One-Trial-Out (LOTO) is a general, efficient and easily implementable approach for inferring trial-by-trial measures of computational model parameters in order to link these measures to neural mechanisms.
Direct in-vivo measurements in the human brain test validity of detailed computational models of trancranial electric stimulation and show that electric fields in the brain are weaker than currently assumed.
Spontaneous theta oscillations and interneuron-specific phase preferences emerge spontaneously in a full-scale model of the isolated hippocampal CA1 subfield, corroborating and extending recent experimental findings.
A spiking network model that examines the transformation of odor information from olfactory bulb to piriform cortex demonstrates how intrinsic cortical circuitry preserves representations of odor identity across odorant concentrations.
A novel analysis of neural activity recorded in monkeys performing a “brain-machine interface” task reveals that a mismatch between motor effectors and the brains’ internal models of those effectors can explain a substantial portion of movement errors.