6 papers
Transferable conditional brain charts link cortico-subcortical structure to Alzheimer's disease progression
Nitin Sharma, Sicheng Dai, Francesco A. Mallus +29
Normative models chart how brain measures vary across the lifespan, expressing each individual as a deviation from a healthy reference. However, most regional models of cortical th…
Towards Unified Multi-task EEG Analysis with Low-Rank Adaptation
Sicheng Dai, Kai Chen, Hongwang Xiao +2
Recent self-supervised pre-training methods for electroencephalogram (EEG) have shown promising results. However, the pre-trained models typically require full fine-tuning on each…
Autoregressive Visual Decoding from EEG Signals
Sicheng Dai, Hongwang Xiao, Shan Yu +1
Electroencephalogram (EEG) signals have become a popular medium for decoding visual information due to their cost-effectiveness and high temporal resolution. However, current appro…
Energy-based Autoregressive Generation for Neural Population Dynamics
Ningling Ge, Sicheng Dai, Yu Zhu +1
Understanding brain function represents a fundamental goal in neuroscience, with critical implications for therapeutic interventions and neural engineering applications. Computatio…
Self-Supervised Masked Mesh Learning for Unsupervised Anomaly Detection on 3D Cortical Surfaces
Hao-Chun Yang, Sicheng Dai, Saige Rutherford +4
Unsupervised anomaly detection in brain imaging is challenging. In this paper, we propose self-supervised masked mesh learning for unsupervised anomaly detection on 3D cortical sur…
Recurrent networks improve neural response prediction and provide insights into underlying cortical circuits
Yimeng Zhang, Harold Rockwell, Sicheng Dai +4
Feedforward CNN models have proven themselves in recent years as state-of-the-art models for predicting single-neuron responses to natural images in early visual cortical neurons.…