Jacob R. Pennington

This paper introduces a live spike sorting system that achieves performance comparable to offline sorting and enables closed-loop interventions in neural recordings.

The paper develops a population encoding model using CNNs to predict auditory neuron activity across natural sounds, showing improved generalizability compared to traditional models.

The paper isolates task engagement and arousal effects in auditory cortex and midbrain using single-unit recordings and generalized linear modeling, finding distinct neural population responses to each.

The paper compares two models of auditory coding, STP and GC, and finds that a hybrid model combining both mechanisms better captures neural responses to natural sounds.