Daniel J. Denman

This study investigates how electrical stimulation of the neocortex affects neural activity and perception in mice, finding that anatomical structure and spatiotemporal patterns, rather than spike counts, determine physiological and perceptual outcomes.

This study shows that myelin loss impairs movement efficiency and alters neuronal activity, with partial remyelination restoring some network metrics but not smooth movement.

The paper analyzes mixed single neuron selectivity in mouse visual system and finds that population representations form high-dimensional, separable representations rather than categorical structures.

The paper identifies neural assemblies consistent with Hebb's theory using a novel dataset linking optical physiology to connectivity, finding they are structurally integrated but not defined by strong monosynaptic connections.

The paper analyzes neuronal variability across brain states to understand how factors like internal dynamics, behavior, and stimuli influence sensory processing over time.

The paper introduces a cost-effective, customizable open-source device for multipolar brain stimulation experiments, demonstrating its effectiveness through bench-top and in vivo testing.

This study shows that partial oligodendrocyte restoration after demyelination is sufficient to recover visual cortical function in mice.

The paper links in vitro, in vivo, and in silico cell classes in mouse visual cortex using computational modeling and optotagging experiments to identify distinct clusters with specific properties.

The paper introduces GEMsort, a multichannel neural spike sorting algorithm that reduces data volume and improves sorting speed using signal processing modifications.

This study compares neuronal responses in visual cortex using electrophysiology and two-photon imaging in awake mice, finding differences in responsiveness and selectivity and exploring data transformations to reconcile them.

The paper presents a dataset and analysis of spiking activity across multiple mouse visual areas, revealing that functional connectivity mirrors anatomical hierarchy.

The paper analyzes population coding in the early visual system of mice, finding synergistic and redundant coding patterns that vary with population size and timescale.

The paper uses high-density extracellular recordings to classify neurons by brain region and identify dendritic backpropagation through waveform analysis.

The paper develops a biophysically detailed in silico model of layer 4 of the mouse primary visual cortex, showing how functional synaptic connectivity reproduces experimental observations of neuronal responses to visual stimuli.

The paper investigates how mice perceive hue and wavelength-specific luminance contrast across visual space, finding non-uniform sensitivity patterns.