The atoms of neural computation

By Gary F. Marcus, Adam Henry Marblestone, Thomas L. Dean. 2014

79 citations recorded by the source corpus.

Does the brain depend on a set of elementary, reusable computations? The human cerebral cortex is central to a wide array of cognitive functions, from vision to language, reasoning, decision-making, and motor control. Yet, nearly a century after the neuroanatomical organization of the cortex was first defined, its basic logic remains unknown. One hypothesis is that cortical neurons form a single, massively repeated “canonical” circuit, characterized as a kind of a “nonlinear spatiotemporal filter with adaptive properties” (1). In this classic view, it was “assumed that these…properties are identical for all neocortical areas.” Nearly four decades later, there is still no consensus about whether such a canonical circuit exists, either in terms of its anatomical basis or its function. Likewise, there is little evidence that such uniform architectures can capture the diversity of cortical function in simple mammals, let alone characteristically human processes such as language and abstract thinking (2). Analogous software implementations in artificial intelligence (e.g., deep learning networks) have proven effective in certain pattern classification tasks, such as speech and image recognition, but likewise have made little inroads in areas such as reasoning and natural language understanding. Is the search for a single canonical cortical circuit misguided?

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Plant Science, Neuroscience

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Citations in the corpus

The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence (2020, background): “Adam Marblestone, Tom Dean and I argued (Marcus et al., 2014), the cortex is (contra a common trope) unlikely to compute all of its functions with a single canonical circuit; there is likely to be an important diversity in neural computation that has not yet been captured either in computational…”
The hardware lottery (2020, background): “Humans have highly optimized and speciﬁc pathways developed in our biological hardware for diﬀerent tasks (Von Neumann et al., 2000; Marcus et al., 2014; Kennedy, 2000).”
Toward an Integration of Deep Learning and Neuroscience (2016, methodology): “Thus, while the precise degree of architectural speciﬁcity of particular cortical regions is still under debate (Marcus et al., 2014a,b), various mechanisms could oﬀer pre-speciﬁed heterogeneity.”