Daniel B. Rubin

This study shows that speech motor cortex encodes sentence-level linguistic structure and semantic content through single-unit activity in three BrainGate2 participants.

The paper shows that during typing skill acquisition using a BCI, neural population dynamics in the dorsal premotor cortex become more compact, with left hemisphere showing enhanced firing-rate modulation and generalization.

The paper investigates how motor cortex activity changes during observation of different anthropomorphic effectors, finding increased neural modulation with greater human-likeness of the observed agents.

This paper demonstrates cross-brain transfer learning for intracortical BCIs decoding speech and handwriting, showing improved performance with limited training data and specific decoder design.

This paper decodes intended speech from a person with anarthria and locked-in syndrome using an intracortical brain-computer interface, showing that phonemes, words, and higher-order language units can be decoded above chance.

This paper introduces NoMAD, a method that stabilizes brain-computer interfaces by aligning latent dynamics, achieving stable decoding without supervised recalibration over long periods.

The paper maps human motor cortex using microelectrode recordings, finding whole-body representations and challenging the traditional motor homunculus model.

This study shows that co-occurring ripple oscillations enhance neuronal interactions between cortical locations in humans by facilitating prediction and co-firing of neurons.

This paper develops a continuous resting-state EEG model to predict recovery from disorders of consciousness after acute brain injury, achieving high accuracy across multiple time horizons.

This paper shows a circuit model of attention explains both neural and behavioral effects of visual attention across different experimental paradigms.

The paper shows that a stochastic Stabilized Supralinear Network model explains stimulus-induced changes in cortical variability and correlations.