Towards Identifying the Systems-Level Primitives of Cortex by In-Circuit Testing
The hypothesis considered here is that cognition is based on a small set of systems-level computational primitives that are defined at a level higher than single neurons. It is pointed out that for one such set of primitives, whose quantitative effectiveness has been demonstrated by analysis and computer simulation, emerging technologies for stimulation and recording are making it possible to test directly whether cortex is capable of performing them.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
An interpretable deep-learning architecture of capsule networks for identifying cell-type gene expression programs from single-cell RNA-sequencing data
The mammalian prefrontal cortex comprises a set of highly specialized brain areas containing billions of cells and serves as the centre of the highest-order cognitive functions, such as memory, cognitive ability, deci…
Compression supports low-dimensional representations of behavior across neural circuits
Dimensionality reduction, a form of compression, can simplify representations of information to increase efficiency and reveal general patterns. Yet, this simplification also forfeits information, thereby reducing repres…
Dimensionality ReductionThe brain versus AI: World-model-based versatile circuit computation underlying diverse functions in the neocortex and cerebellum
AI's significant recent advances using general-purpose circuit computations offer a potential window into how the neocortex and cerebellum of the brain are able to achieve a diverse range of functions across sensory, cog…
3D-aCortex: An Ultra-Compact Energy-Efficient Neurocomputing Platform Based on Commercial 3D-NAND Flash Memories
The first contribution of this paper is the development of extremely dense, energy-efficient mixed-signal vector-by-matrix-multiplication (VMM) circuits based on the existing 3D-NAND flash memory blocks, without any need…
The brain-AI convergence: Predictive and generative world models for general-purpose computation
Recent advances in general-purpose AI systems with attention-based transformers offer a potential window into how the neocortex and cerebellum, despite their relatively uniform circuit architectures, give rise to diverse…