Daniel R. Kramer

The paper identifies distinct large-scale brain network configurations associated with successful versus unsuccessful visual recognition memory using intracranial EEG data.

The paper identifies order-selective cells in the human brain that represent temporal order during memory encoding and retrieval, predicting memory accuracy.

This paper introduces a deep multi-state DRNN for BMIs that outperforms existing methods using wavelet-based features on single- and multi-day data.