Jacob Reimer

This paper introduces VADER1, a red GEVI that enables reliable in vivo two-photon voltage imaging with millisecond resolution and supports dual-color imaging with calcium indicators.

The paper maps retinal ganglion cell functional diversity in the mouse superior colliculus and identifies specialized response types for collision detection.

The paper develops methods to infer norepinephrine dynamics from partial observations, revealing temporal patterns during arousal.

The paper develops two new genetically encoded voltage indicators (JEDI3sub and JEDI3hyp) for improved two-photon recording of subthreshold voltage dynamics in vivo.

The paper introduces FORCE1s, a GEVI that enables robust two-photon voltage imaging in awake mice with high signal-to-noise and reliable spike detection.

NEURD automates proofreading and feature extraction from connectomics data to improve accuracy and accessibility of neural morphology analyses.

The paper presents a functional connectomics dataset of mouse visual cortex, combining calcium imaging with EM reconstruction to study neural circuits and their connectivity.

Functionally similar neurons in mouse visual cortex connect preferentially across layers and areas, including feedback, and feature tuning, not receptive-field position, predicts synapses beyond axon-dendrite proximity.

The paper uses graph-based machine learning to analyze dendritic morphology of excitatory neurons in mouse visual cortex, finding a continuous morphological landscape rather than discrete types.

The paper examines cortical acetylcholine dynamics during behavioral state transitions, finding that axon activity and behavior predict ACh levels.

The paper investigates the synaptic connectivity of thick tufted layer 5 pyramidal neurons in the mouse visual cortex, revealing their local inhibitory and long-range excitatory connections.

This study compares odor responses in locust and mouse olfactory systems, finding conserved neural dynamics and computations that enhance odor contrast.

This paper trains a foundation model on neural activity data to predict responses to new stimuli and anatomical features, showing strong generalization across mice and tasks.

The paper identifies a novel bipartite invariance in mouse V1 neurons, where receptive fields encode shift-invariant high-frequency textures and fixed low-frequency patterns, contributing to segmentation.

The paper uses CNNs to analyze contextual modulation in visual cortex by synthesizing surround patterns, finding that pattern completion enhances responses while disruption suppresses them, consistent across mice and macaques.

Electron microscopy of 1352 neurons in a mouse visual cortex column reveals widespread cell-type-specific inhibition, a basket-cell-targeting disinhibitory class, and interneuron motif groups sharing excitatory targets.

The paper synthesizes neural metamers for the mouse visual system using deep encoding models and shows they reproduce neural activity across different animals.

The paper maps synaptic connectivity between cortical pyramidal neurons and shows synapse size is modeled by a combination of binary and analog variables.

The paper identifies distinct feedback circuit motifs in cortico-cortical pathways, showing different functional dynamics in motor-sensory and visual feedback circuits.

NeuVue is a framework for managing and prioritizing proofreading tasks in connectomic datasets, enabling scalable and coordinated error correction by over forty proofreaders.

The paper shows that pupil dilation in mice shifts color selectivity in the visual cortex towards ultraviolet stimuli, enhancing detection of ethological features like aerial predators.

Cloud-run convolutional nets aligned 19,939 serial EM sections of mouse visual cortex despite cracks and folds, segmented neurons and detected 523 million synapses; code and the reconstruction are public.

The paper introduces DataJoint Elements, a resource providing modular workflow designs for organizing data and computations in neurophysiology experiments.

The paper presents a semi-automated reconstruction of mouse primary visual cortex from electron microscopy data, revealing structural and functional relationships in cortical circuits.

Recordings of thousands of mouse visual cortex neurons reveal that lateral areas LM, LI, and AL carry higher linearly decodable object information associated with reduced object manifold dimension and radius.

The paper develops cell body-targeted calcium indicators to improve signal fidelity in one-photon imaging of neural activity in live mice and zebrafish.

The paper maps chandelier cell synapses onto pyramidal neurons and finds variability in synaptic input correlated with target neuron features, while showing functional correlation with arousal state.

The paper introduces EASE, a method that matches calcium imaging signals to EM-derived cell segments in mouse visual cortex, enabling dendritic functional analysis and denoising.

The paper uses advanced imaging techniques to show that mouse visual cortex has a global orientation tuning map, challenging previous assumptions about its structure.

~2-4x SNR gains and 20-300x compression on calcium and voltage imaging, from a patch-wise penalized matrix decomposition that splits signal from temporally uncorrelated noise without hyperparameter tuning.