Neural Signal Compression

This lecture covers the basics of analog-to-digital conversion, sampling, quantization, and encoding in the context of neural signal processing. It delves into the optimization of ADCs for neuro applications, focusing on linear and non-linear quantization methods. The lecture also discusses multichannel architectures for sensory circuits and the on-chip compression of neural signals. Various techniques for digitizing neural signals are explored, including spike detection and data compression methods. The instructor presents case studies and applications of these concepts in the field of neuroengineering.