Emmanouil Froudarakis

EthoPy simplifies reproducible behavioral neuroscience by automating training workflows and integrating stimulus presentation, hardware management, and data logging.

The paper identifies a dual-feature encoding strategy in visual cortical neurons where neurons respond to both enhancing and suppressing visual features, showing this strategy is conserved across species.

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 demonstrates that individualized fMRI neuromodulation enhances visuospatial perception by increasing BOLD signal magnitude and classification performance in specific neural networks.

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 finds increased reliability of visually-evoked activity in V1 neurons of MECP2-duplication mice, suggesting altered sensory processing mechanisms in autism.

The paper uses digital twins to characterize the functional organization of mouse V1, revealing a combinatorial code of nonlinear response properties across 30 modes.

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 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 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 investigates how functional connectivity, synaptic connectivity, and external input variability can be distinguished in neural microcircuits using simulations, analysis, and calcium imaging data.

The paper identifies distinct cell types and circuit organization in layer 4 of primary sensory areas in adult mouse neocortex, challenging the canonical microcircuit model.

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

The paper develops inception loops to identify Most Exciting Images for V1 neurons in mice, finding that these images outperform linear model stimuli and reveal complex spatial features.

A deep recurrent encoding model predicts spiking of thousands of mouse V1 neurons during natural video and carries over to noise stimuli when only its last layer is retrained.

The paper benchmarks spike rate inference algorithms for two-photon calcium imaging data and finds that top-performing algorithms show high correlation despite diverse approaches.

The paper benchmarks spike rate inference algorithms using calcium imaging data and introduces a supervised learning method that outperforms existing techniques across diverse datasets.