Tielin Zhang

BCIJelly: An integrated ecosystem for brain-computer interface research

BCIJelly provides a unified ecosystem for BCI research, standardizing data, integrating decoders, and enabling efficient deployment on neuromorphic hardware.

Incorporation of single-neuron projectome-based connectivity motifs enhances the cortex-specific performance of artificial neural networks

This paper develops a connectome-informed neural network algorithm that improves RNN and LLM performance by incorporating natural cortical connectivity motifs.

DigiMus: a connectome-informed spiking framework for multi-region mouse neural-behavior modeling

DigiMus integrates connectome-derived structural priors into a spiking neural network framework for mouse neural-behavior modeling, showing improved performance in complex tasks.

Rhythmic temporal structure organizes recurrent dynamics to support sequential working memory

This study shows that rhythmic input improves sequential working memory by organizing recurrent neural dynamics around a dominant frequency, enhancing temporal-order representations.

A dataset of simultaneous two-photon calcium imaging and auditory discrimination behavior

The paper presents a dataset linking two-photon calcium imaging with auditory behavior in mice, validated for use in decoding algorithms and computational models.

Modular organization and selective motifs in the insula provide structural priors for efficient learning

The paper maps the insular cortex's intra-architecture and shows it provides computational advantages for efficient learning in neural networks.

Aligned recordings of neural spiking activity and licking behavior in thirsty mice

The paper presents a dataset of neural spiking activity and licking behavior in thirsty mice, enabling precise spike-to-event mapping and benchmarking for neural decoding algorithms.