Fundamental Mechanisms of NeuroInformation Processing: Inverse Problems and Spike Processing
Abstract
During the research period we: (i) devised path breaking algorithms for the functional identification and evaluation of non-linear dendritic processing, and (ii) released a groundbreaking open source platform for the isolated and integrated emulation of the fruit fly brain on multiple GPUs (Neurokernel). We established that identifying a single dendritic stimulus processor (DSP) is mathematically dual to decoding of stimuli encoded by a population of neurons with a bank of DSPs. Building on this key duality property, we (i) demonstrated that the evaluation of the functional identification methodology can be effectively and intuitively performed in the stimulus space, and (ii) characterized the effect of noise parameters on the precision of the functional identification of feed forward, feedback and cross-feedback neural circuits with DSP/biological spike generator neuron models. We demonstrated the power of Neurokernel's model integration by combining independently developed models of the retina and lamina neuropils in the fly's visual system and by demonstrating their neuroinformation processing capability.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 04, 2016
- Accession Number
- AD1012924
Entities
People
- Aurel A Lazar
Organizations
- Columbia University