Nicholas A. Steinmetz

The paper introduces Neuropixels Opto probes that combine high-resolution electrophysiology with optogenetics for spatially addressable neuronal manipulation and recording.

The paper introduces a new quality metric for electrophysiological recordings that adapts to varying refractory period durations across brain regions and species.

The paper shows recurrent cortical networks in mouse visual cortex encode natural sensory statistics by filtering input sequences rather than generating them.

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 presents a brain-wide neural activity map from 621,733 neurons across 139 mice performing a decision-making task, showing how neural activity encodes task variables across brain regions.

The paper investigates trial-to-trial variability in visual cortex spike counts and finds that global cortical activity explains more variability than behavioral factors.

This paper introduces PhysMAP, a framework that uses multimodal electrophysiological data to identify and study cell types in vivo, showing improved alignment with transcriptomic cell types and circuit dynamics.

The paper shows that mice with ASD-related mutations exhibit similar computational and neural anomalies in prior updating during decision-making.

This study evaluates the reproducibility of electrophysiological measurements across ten labs using standardized protocols and finds that variability in electrode targeting and statistical methods affects reproducibility.

DREDge improves motion correction in high-density extracellular recordings across species, enhancing reliability and reducing errors in electrophysiological data.

The paper shows that intrinsic and task-related neural timescales increase hierarchically across mammalian cortices, but thalamic timescales differ from this pattern.

This paper introduces NEMO, a multimodal contrastive learning method for classifying cell types and brain regions from electrophysiological data, achieving state-of-the-art results on two opto-tagged datasets and the International Brain Laboratory Brain-wide Map dataset.

This paper develops a system to simultaneously record and manipulate mesoscopic cortical activity in awake mice, enabling study of its effects on behavior and subcortical activity.

The paper introduces two public websites for exploring large-scale electrophysiology data from the International Brain Laboratory, enabling cross-platform access to behavioral trials and neuronal data.

This study investigates how mouse olfactory bulb spiking activity encodes temporal features of natural odor plumes, finding that population-level activity captures plume onset, offset, and presence/absence, while individual cells encode only limited features.

The paper investigates traveling spiral waves in the brain, showing they are organized across spatial scales and coordinated with subcortical patterns.

This paper introduces a spike sorting-free decoding method using density-based modeling to improve neural decoding performance without explicitly clustering spikes.

This paper introduces NP Ultra, a high-density electrode that improves neuronal recording yield, detection, and cell type classification in mice.

Pinpoint is a web-based tool for planning and automating multi-probe electrophysiology and injection procedures in 3D space, improving efficiency and reproducibility.

The paper measures intrinsic timescales in the visual cortex during attention tasks and finds they change with attention and spatial connectivity.

This study identifies stable, distributed coding of cue value in mouse prefrontal cortex during reward learning.

The paper introduces a scale-dependent measure of system dimensionality and applies it to neural recordings, showing differences in effective dimensionality between behaviorally engaged and spontaneous brain states.

The paper investigates how On-Off dynamics and selective attention shape spatial patterns of correlated variability in neocortex using columnar recordings and a network model.

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

Neurogrid simulates cortical models across multiple levels, revealing active dendrites mediate top-down attention.

The paper introduces Neuropixels 2.0, a high-density probe for long-term brain recordings, and demonstrates its stability across months in multiple labs and species.

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

The paper shows that local cortical state coordination during selective attention is retinotopically precise and progresses in a reverse hierarchical manner across brain areas.

This study investigates cortical state fluctuations during sensory decision making and finds that desynchronization correlates with task engagement rather than accuracy.

The paper shows that retinal outputs in mice are modulated by behavioural state, as observed in the superficial superior colliculus and optic tract, even in darkness.