Chengcheng Huang

Neuronal heterogeneity of normalization strength in a circuit model

This study uses a spiking neuron network model to show that normalization strength heterogeneity in the visual cortex correlates with inhibitory current and enhances information encoding.

Noise Correlations in Balanced Networks with Unreliable Synapses

This study investigates how synaptic unreliability affects noise correlations in balanced neuronal networks, finding opposing effects of feedforward and recurrent synaptic reliability.

Automated customization of large-scale spiking network models to neuronal population activity

This paper introduces SNOPS, a method to automatically customize spiking network models to match large-scale neuronal recordings, revealing limitations of current models.

State modulation in spatial networks with three interneuron subtypes

The paper investigates how different interneuron subtypes contribute to network synchrony in spatially organized spiking neuron networks and identifies SOM cells as the main driver of synchrony.

An EEG Signature of MCH Neuron Activities Predicts Cocaine Seeking

This study identifies an EEG signature that tracks MCH neuron activity and predicts cocaine seeking behavior in rats.

Chaotic dynamics in spatially distributed neuronal networks generate population-wide shared variability

The paper shows that chaotic dynamics in spatially distributed neuronal networks explain shared variability in population responses.

Subpopulation Codes Permit Information Modulation Across Cortical States

The paper shows that subpopulation codes can modulate information across cortical states, with inhibitory circuitry playing a key role in this process.

Internally generated population activity in cortical networks hinders information transmission

This study shows that network connectivity determines population code performance by influencing stimulus tuning and internally generated fluctuations in spiking neuron models.

A general decoding strategy explains the relationship between behavior and correlated variability

The paper shows that perceptual performance and correlated variability in sensory cortex are inversely related due to observers using a general decoding strategy rather than optimal stimulus-specific decoding.

Topological insights into the neural basis of flexible behavior

This paper uses topological data analysis to link neural activity, cognitive processes, and behavior by showing how topological changes in neural populations relate to task performance and model discrimination.

Circuit models of low dimensional shared variability in cortical networks

The paper shows that model cortical networks with physiologically accurate inhibitory coupling generate low-dimensional shared variability, matching in vivo recordings and explaining attentional modulation of variability between brain areas.