Srivatsun Sadagopan

The paper uses a random forest classifier to distinguish neurons in two subdivisions of the inferior colliculus based on their response properties to pure tones.

The paper investigates adaptive mechanisms in an auditory categorization model to improve performance in noisy and reverberant environments, showing that multiple adaptations are needed to match biological performance.

This study shows a feature-based auditory categorization model matches guinea pig behavior in call categorization, especially under frequency shifts.

The paper uses deconvolution to show that linear superposition of F0 responses explains over 80% of the variance in FFRs to human speech in macaques.

This study investigates cortical sources of frequency following responses (FFRs) to speech across species, finding robust FFRs in auditory cortex and their contribution to scalp-recorded signals.

The paper shows that call feature selectivity emerges in superficial layers of primary auditory cortex through changes in neural representation.

The paper identifies mid-level acoustic features that enable accurate classification of vocalizations across species using an information-theoretic approach.