Time-Domain Brain: Temporal Mechanisms for Brain Functions, Time-Delay Nets, Holographic Processes, Radio Communications, and Emergent Oscillatory Sequences

Janet MacIver Baker ^1* Peter Cariani ²

• ¹ Massachusetts Institute of Technology, Cambridge, United States
• ² Harvard Medical School, Boston, Massachusetts, United States

Time is essential for understanding the brain. A temporal theory for realizing major brain functions (e.g. sensation, cognition, motivation, attention, memory, learning, motor action) is proposed that uses temporal codes, time-domain neural networks, correlation-based binding processes and signal dynamics. It adopts a signalcentric perspective in which neural assemblies produce circulating and propagating characteristic temporallypatterned signals for each attribute (feature). Temporal precision is essential for temporal coding and processing.The characteristic spike patterns that constitute the signals enable general-purpose, multimodal, multidimensional vectorial representations of objects, events, situations, and procedures. Signals are broadcast and interact with each other in spreading activation time-delay networks to mutually reinforce, compete, and create new composite patterns. Sequences of events are directly encoded in the relative timings of event onsets.New temporal patterns are created through nonlinear multiplicative and thresholding signal interactions, such as mixing operations found in radio communications systems and wave interference patterns. The newly-created patterns then become markers for bindings of specific combinations of signals and attributes (e.g. perceptual symbols, semantic pointers, tags for cognitive nodes). Correlation operations enable both bottom-up productions of new composite signals and top-down recovery of constituent signals.Memory operates using the same principles: nonlocal, distributed, temporally-coded memory traces, signal interactions and amplifications, content-addressable access and retrieval. A short-term temporary store is based on circulating temporal spike patterns in reverberatory, spike-timing-facilitated circuits. A long-term store is based on synaptic modifications and neural resonances that select specific delay-paths to produce temporallypatterned signals.Holographic principles of nonlocal representation, storage, and retrieval can be applied to temporal patterns as well as spatial patterns. These can automatically generate pattern recognition (wavefront reconstruction) capabilities, ranging from objects to concepts, for distributed associative memory applications.