Phenotype Scoring of Population Scale Single-Cell Data Dissects Alzheimer's Disease Complexity.

The complexity of Alzheimer's disease (AD) manifests in diverse clinical phenotypes, including cognitive impairment and neuropsychiatric symptoms (NPSs). However, the etiology of these phenotypes remains elusive. To address this, the PsychAD project generated a population-level single-nucleus RNA-seq dataset comprising over 6 million nuclei from the prefrontal cortex of 1,494 individual brains, covering a variety of AD-related phenotypes that capture cognitive impairment, severity of pathological lesions, and the presence of NPSs.

NeuroTD: A Time-Frequency Based Multimodal Learning Approach to Analyze Time Delays in Neural Activities.

Studying temporal features of neural activities is crucial for understanding the functions of neurons as well as underlying neural circuits. To this end, recent researches employ emerging techniques including calcium imaging, Neuropixels, depth electrodes, and Patch-seq to generate multimodal time-series data that depict the activities of single neurons, groups of neurons, and behaviors. However, challenges persist, including the analysis of noisy, high-sampling-rate neuronal data, and the modeling of temporal dynamics across various modalities.