A model of hippocampal spiking responses to items during learning of a context-dependent task

BiCoSS: Toward Large-Scale Cognition Brain With Multigranular Neuromorphic Architecture

The further exploration of the neural mechanisms underlying the biological activities of the human brain depends on the development of large-scale spiking neural networks (SNNs) with different categories at different levels, as well as the corresponding computing platforms. Neuromorphic engineering provides approaches to high-performance biologically plausible computational paradigms inspired by neural systems. In this article, we present a biological-inspired cognitive supercomputing system (BiCoSS) that integrates multiple granules (GRs) of SNNs to realize a hybrid compatible neuromorphic platform. A scalable hierarchical heterogeneous multicore architecture is presented, and a synergistic routing scheme for hybrid neural information is proposed. The BiCoSS system can accommodate different levels of GRs and biological plausibility of SNN models in an efficient and scalable manner. Over four million neurons can be realized on BiCoSS with a power efficiency of 2.8k larger than the GPU platform, and the average latency of BiCoSS is 3.62 and 2.49 times higher than conventional architectures of digital neuromorphic systems. For the verification, BiCoSS is used to replicate various biological cognitive activities, including motor learning, action selection, context-dependent learning, and movement disorders. Comprehensively considering the programmability, biological plausibility, learning capability, computational power, and scalability, BiCoSS is shown to outperform the alternative state-of-the-art works for large-scale SNN, while its real-time computational capability enables a wide range of potential applications.

A limited positioning system for memory

The 2014 Nobel Prize for Physiology or Medicine is an enormous triumph for John O'Keefe and May-Britt and Edvard Moser and an historic event for cognitive and behavioral neuroscience. Neuronal representations decoded from action potentials form a mechanistic bridge between brain and mind and demonstrate the continuity of psychology with biology and physical science. The cognitive map theory powered an ongoing, international research program inspired by Hebb (The Organization of Behavior. New York, NY: Wiley) that showed the way toward linking specific patterns of neuronal activity to high level representation and processing. The prize celebrates a path that led from fundamental, philosophical questions about psychological space to enduring, scientific facts: place, head direction, grid, and boundary fields in the hippocampus, presubiculum, entorhinal cortex, and other brain circuits provide a cellular basis for spatial behavior, learning, and memory. By awarding this prize, the Nobel committee affirmed neuroethology and comparative psychology, marked the end of a chapter in one debate about the existence of animal cognition, and recognized cognitive neurophysiology. The "inner GPS" in the brain" demonstrates "a cellular basis for higher cognitive function." Animals represent, process, and use information defined by abstract relationships among items (O'Keefe and Conway,) to guide flexible, goal-directed actions. Beyond raising the ontological status of "animal mind," the committee agreed that abstract mental representations can be investigated rigorously by recording single unit activity in the brain of behaving animals.