Hannah Choi

Rank dependency of rescaled pruning in recurrent neural networks

The paper shows that synaptic rescaling preserves low-dimensional dynamics in low-rank RNNs but fails in high-rank networks during pruning.

Inhibitory cell type heterogeneity in a spatially structured mean-field model of V1

The paper develops a mean-field model to study how heterogeneous inhibitory cell types in V1 affect network dynamics and stability through spatial connectivity properties.

Non-canonical Sodium Channel Isoforms Underlie Chamber Specific Cardiac Excitability

This study identifies chamber-specific contributions of non-NaV1.5 sodium channel isoforms to cardiac excitability using a chemical-genetic mouse model and electrophysiological recordings.

Cell-type-specific encoding of prediction and reward in cortical microcircuits during novelty detection

The paper introduces a computational model of cortical circuits that explains cell-type-specific responses to novelty through predictive coding, energy efficiency, and reinforcement learning.

Integrated Classification of Cortical Cells and Quantitative Projectomic Mapping Unveil Organizational Principles of Brain-Wide Connectomes at Single Cell Level

This study integrates molecular and morphological data to classify cortical neurons and map their connectomes, revealing organizational principles of brain-wide networks at the single-cell level.

Cortex-wide voltage imaging in a sensory cued reaching task reveals fast subnetwork dynamics

The paper uses voltage imaging to study fast cortical dynamics during a reaching task, identifying distinct oscillatory patterns and network behaviors.

Temporal resolution of spike coding in feedforward networks with signal convergence and divergence

The paper models spike coding in feedforward networks with convergence and divergence, showing structural bottlenecks prefer spike timing over expansion layers and linking network structure to coding strategies.

Lateral inhibition in V1 controls neural & perceptual contrast sensitivity

The paper investigates how lateral inhibition from PV and SST neurons in mouse V1 affects neural and perceptual contrast sensitivity, revealing distinct computational roles for each cell type.

Constructing Biologically Constrained RNNs via Dale's Backprop and Topologically-Informed Pruning

The paper develops RNNs that incorporate biological constraints like Dale's law and structured connectivity to better model cortical function and validate insights through mouse calcium imaging data.

Stimulus-dependent functional network topology in mouse visual cortex

The paper examines how functional connectivity in mouse visual cortex changes with different stimuli, finding that motif frequencies are preserved while neuron identities within motifs shift, and functional modules become more regionally contained with complex stimuli.

Exploring the Architectural Biases of the Canonical Cortical Microcircuit

This study uses recurrent neural networks to analyze how inter-areal connections affect cortical microcircuit function during learning, finding feedback connections enhance modularization and predictive coding.

On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks

The paper uses mathematical models to study how structural and physiological factors affect excitation-inhibition balance in cortical networks and identifies key parameters for stability.

Differential encoding of temporal context and expectation under representational drift across hierarchically connected areas

The paper shows that visual areas differentially encode temporal context and expectation in natural scenes, with representational drift observed in lower areas but not higher ones.

A survey of spiking activity reveals a functional hierarchy of mouse corticothalamic visual areas

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

A Comprehensive Multi-Center Cross-platform Benchmarking Study of Single-cell RNA Sequencing Using Reference Samples

This study benchmarks scRNA-seq reproducibility across platforms and pipelines, finding that batch correction methods significantly affect results.

The organization of intracortical connections by layer and cell class in the mouse brain

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.

Synchronization dependent on spatial structures of a mesoscopic whole-brain network

The paper examines how spatial connectivity structures in a mesoscopic whole-brain network influence synchronization patterns in coupled phase oscillators.