Connectionists: The Atoms of Neural Computation

[Randall O'Reilly]

Gary — you may be interested in our in-press chapter on the Leabra cognitive architecture, which enumerates 20 core principles instantiated in this architecture that have broad empirical and theoretical support:  https://grey.colorado.edu/CompCogNeuro/index.php/OReillyHazyHerdIP (here is an important new update too: https://grey.colorado.edu/CompCogNeuro/index.php/OReillyWyatteRohrlichIP )

Also, we have a more in-depth treatment of the binding and related issues here:
https://grey.colorado.edu/CompCogNeuro/index.php/OReillyPetrovCohenEtAl14

Cheers,
- Randy

> On Nov 2, 2014, at 2:57 PM, Gary Marcus <gary.marcus at nyu.edu> wrote:
> 
> New piece in Science, reevaluating the “canonical cortical computation” hypothesis: http://www.sciencemag.org/content/346/6209/551.short (First paragraph pasted in below)
> 
> And lot of further detail didn’t fit: http://biorxiv.org/content/early/2014/10/31/010983
> 
> I love a discussion here on the group,  especially re: the Table of possible computation and their neural realizations, in the Supplement. We plan to crowd-source a more detailed version of that table; please contact me if you are interested in contributing.
> 
> Cheers,
> Gary
> 
> 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?
> 
> 
> Gary Marcus
> Professor of Psychology and Neural Science
> New York University
> Visiting Cognitive Scientist
> Allen Institute for Brain Science
> Editor, The Future of the Brain (2014)
> http://garymarcus.com/
> New Yorker essays
> New York Times op-eds
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