Paul Nuyujukian

This paper shows that motor cortex maintains a dynamic library of state eigenvectors that generalize over reach directions, with stable dynamics that drift and jump during repetitive tasks.

This paper investigates the effects of covert neuron loss on local field potential spectra in motor cortex using electrolytic lesions in large animals, finding prolonged spectral changes despite no behavioral impact.

The paper shows that unsupervised dimensionality in motor cortex does not reflect movement complexity but instead scales with neuron count and is context-dependent, challenging assumptions about neural representation.

This paper uses compression metrics to detect changes in spiking neural data from cortical lesions, finding that compression-based methods outperform single-neuron metrics in lesion detection accuracy.

This paper introduces SMDS, a model that accounts for representational drift in neural data, outperforming LDS in log-likelihood and requiring fewer latent dimensions.

The paper shows that neural manifolds remain stable in low dimensions despite motor representation drift, with encoding maps changing while latent maps stay stable.

The paper compares neural dynamics during walking and reaching, finding that reaching has higher dimensionality and faster decay in dynamical systems than walking.

This paper examines damage to implanted multielectrode arrays after electrolytic lesioning and finds no significant difference in damage compared to normal arrays.

This paper introduces an electrolytic lesioning technique compatible with neuroelectrophysiology recordings, enabling precise brain lesioning without disrupting electrophysiological measurements.

The paper decodes real-time decision variables from motor cortex activity and shows their link to choice behavior and decision dynamics.