Kenneth D. Harris

This study shows the superior colliculus contributes additively to logistic decision-making by promoting competing actions independently of stimuli.

The paper shows spatial position is represented across the brain in mice, with the hippocampal formation showing slightly more uniform representation than other regions.

The paper demonstrates that apical dendrites in L5 neurons of the mouse visual cortex drive responses to large stimuli rather than suppress them, with extended synaptic inputs.

This paper introduces coppaFISH 3D and CASTalign to enable transcriptomic identification of thousands of in vivo recorded neurons at scale.

This study identifies the dorsal prefrontal cortex, specifically anterior supplementary motor cortex, as a driver of perseverative behavior in mice during a reward learning task.

The paper finds two opposing neural populations in the mouse brain that explain brainwide blood volume fluctuations across states and regions.

The paper shows that stable neural activity sequences are present across the entire mouse brain and remain consistent over weeks.

This study shows how the basal ganglia transform visual signals into behaviorally relevant signals through task training in mice.

DeepUnitMatch tracks individual neurons across days using deep neural networks, outperforming current methods by analyzing spike waveforms.

The paper introduces Zebra noise and a wavelet-based model to efficiently map visual preferences of thousands of neurons in the mouse visual cortex.

Mice infer stimulus-side priors from recent choices; prior signals are decodable pre-stimulus in 24.0% to 30.2% of 242 brain regions, including early visual and motor areas.

The paper shows that layer 2/3 and layer 5 excitatory neurons in the mouse visual cortex encode visual and nonvisual signals differently, with L2/3 more responsive to visual stimuli and L5 more responsive to movement.

Suite3D improves 3D cell detection in two-photon microscopy by correcting motion and segmenting cells across planes, enhancing detectability and signal quality.

The paper introduces AIRUS, an AI-assisted workflow enabling scientists to use LLMs for hypothesis generation, coding, and result interpretation without extensive AI expertise.

The paper introduces an adaptable implant for chronic Neuropixels recordings in mice, enabling stable, reusable, and lightweight neural recordings across multiple experimental conditions.

The paper presents a solvable RNN model showing low-dimensional latent dynamics can generate high-dimensional neuronal activity, and introduces NCE to demonstrate this in mouse visual cortex data.

The paper shows adaptation increases discriminability of frequent stimuli in mouse V1 by reshaping population response geometry, despite reduced individual neuron responses.

The paper introduces UnitMatch, a pipeline for tracking neurons across recordings using spike waveforms, showing stability in visual cortex and changes in striatum during learning.

This study creates a spatially-resolved transcriptional atlas of the murine dorsal pons using snRNA-seq and MERFISH, identifying 120 neuronal subtypes and their spatial distribution.

The paper describes a modular data architecture for a neuroscience collaboration, enabling data contribution, access, and analysis across multiple labs.

The paper shows that sound-evoked activity in mouse visual cortex is stereotyped and predictable from behavioral responses, suggesting it arises from low-dimensional internal state signals rather than direct multisensory integration.

The paper identifies a transcriptomic axis that predicts how cortical interneurons modulate activity across brain states.

This study identifies causal roles of visual and frontal cortex in a visual decision task using optogenetic inactivation and neural recordings.

The paper investigates how dopamine axons in different striatal regions encode sensory stimuli and actions during decision-making tasks in mice.

The paper shows that training on a visuomotor task alters visual cortical population codes by orthogonalizing responses to motor-associated stimuli, without improving optimal decoders but enhancing suboptimal ones.

The paper shows that mouse frontal cortex combines auditory and visual evidence additively during learning, mirroring behavior, and that this combination is impaired by optogenetic inactivation.

The paper shows spatial modulation of visual signals in higher visual areas but not in the thalamic pathway to V1, and links this modulation to active navigation and experience.

The paper shows that striatal activity patterns mirror cortical activity patterns, with an additive offset in learned tasks.

With slowly drifting simulated signals, pseudosession, session permutation and (if one series is stationary) linear shift tests stayed calibrated; circular shift, phase randomization, cross-validation and auto-decorrelation did not.

Rigbox is an open-source software toolbox for behavioral neuroscience experiments, offering modular design, hardware I/O, data synchronization, and stimulus presentation.