Christof Koch A

The paper compares cellular diversity in the primary motor cortex across human, marmoset, and mouse using single-nucleus transcriptomics and epigenomics, finding conserved cell types and species-specific adaptations.

This paper compares neural adaptation mechanisms to persistent activity in a visual change detection task using mice and artificial neural networks, finding that adaptation better matches neural and behavioral data.

The paper identifies conserved and divergent morpho-electric and transcriptomic properties of human and rodent layer 5 extratelencephalic-projecting neurons using patch-seq in human brain slices.

The paper uses single-cell RNA-seq to analyze relay neurons in the dLGN across species, finding subtle transcriptomic differences compared to morphological and functional distinctions.

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 uses microendoscope imaging in mice to show that anterior claustrum Gnb4+ neurons are active during behavior but not during passive sensory stimulation.

The paper characterizes the relationship between spiking activity and fluorescence signals in GCaMP6-expressing neurons, finding GCaMP6s has better single-spike detection than GCaMP6f.

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

The paper tracks spiking activity across six levels of the mouse visual hierarchy to identify two multi-regional communication modules with distinct signal flow and functional roles.

The paper introduces BMTK, an open-source software suite for multiscale brain circuit modeling, enabling simulations across different resolution levels with reduced coding requirements.

The paper characterizes transcriptomic and physiological properties of GABAergic cortical neurons in mice, identifying 20 interneuron met-types with consistent features across modalities.

Complete morphologies of 1,708 neurons, sparsely labelled and imaged whole-brain with fMOST, expose region-specific long-range projection rules and finer diversity than current transcriptomic subtypes capture.

The paper identifies 27 transcriptomic cell types in mouse subiculum and prosubiculum, defines their anatomical boundaries, and reveals distinct neural circuits and projections along the dorsal-ventral axis.

The paper uses a mouse V1 model to study how perturbations affect coding efficiency and robustness, showing shifts in inhibition and excitation based on stimulus contrast.

The paper develops a multi-scale model of mouse primary visual cortex integrating structural and functional data to identify cell-class specific connectivity rules.

The paper identifies von Economo neurons as a regionally specialized subtype of extratelencephalic-projecting excitatory neurons using single nucleus RNA-sequencing and cross-species comparisons.

The paper presents a large-scale dataset of neural activity in the mouse visual cortex and shows that responses to different stimuli are largely independent, suggesting multi-layer hierarchical computation.

The paper expands the Allen Mouse Brain Connectivity Atlas by analyzing intracortical connections at the layer and cell class level, revealing modular organization and distinct projection patterns.

The paper compares neural precursors of arbitrary and deliberate decisions, finding readiness potentials before arbitrary decisions but not deliberate ones, suggesting different neural mechanisms.

This study calibrates two-photon calcium imaging to recover action potentials in mice, finding that fluorescence changes are inconsistent for small spike numbers and vary by mouse line.

The paper compares cell types in human and mouse cortex using single nucleus RNA-sequencing, finding conserved architecture with species-specific differences.

The paper classifies neurons in mouse visual cortex into 17 electrophysiological and 35 morphological types using unsupervised methods and links them to transcriptomic types.

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 shows that h-channels contribute to differences in electrophysiological properties between human and mouse supragranular pyramidal neurons.

The paper identifies shared and distinct transcriptomic cell types in two mouse neocortical regions using scRNA-seq, showing most excitatory types are region-specific while inhibitory types are shared.

The paper examines sparse excitatory connectivity in adult mouse and human cortex using electrophysiology and optogenetics, finding sparse connections and synaptic dynamics across layers.

This paper describes an ex vivo platform for studying adult human neocortical cell types and circuits using acute and cultured brain slices, enabling molecular-genetic manipulation and neuronal activity monitoring.

The paper develops generalized leaky integrate-and-fire models to classify neuron types in the mammalian neocortex using electrophysiological data.

This paper reviews clinical and neuroimaging evidence to debate whether consciousness is linked to the frontal or posterior cortex.