Canonical circuits in neuroscience

Gary Marcus, Adam Marblestone, and Thomas Dean have a nice perspective piece in Science this week on the atoms of neural computation (gated):

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”. 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…

What would it mean for the cortex to be diverse rather than uniform? One possibility is that neuroscience’s quarry should be not a single canonical circuit, but a broad array of reusable computational primitives—elementary units of processing akin to sets of basic instructions in a microprocessor—perhaps wired together in parallel, as in the reconfigurable integrated circuit type known as the field-programmable gate array.

Candidate computational primitives might include circuits for shifting the focus of attention, for encoding and manipulating sequences, and for normalizing the ratio between the activity of an individual neuron and a set of neurons. These might also include circuits for switching or gating information flow between different parts of cortex, and for working memory storage, decision-making, storage and transformation of information via population coding and the manipulation and encoding of variables, alongside machinery for hierarchical pattern recognition…

And so on. People have long proposed that ‘all cortex is the same’ or some such rubbish, it being all made of cortical columns that are the same from one bit of tissue to another. I’m not sure how many people really believe that, but you see the statement a lot (and it is a big reason people studying visual cortex claim they’re just interested in ‘cortex’).

Of course, on a smaller scale there has been a long interest in more primitive ‘microcircuits’. A few examples:

The Reichardt (motion) detector:

Reichardt detector

There is strong experimental evidence for this in drosophila (the fly), and is a repeated motif across visual space.

(see source for review)

Inhibitory circuit motifs:


(see source)

Circuit motif for flexible categorization:

flexible categorization motif

(see source)

Since we know all the circuitry of the worm C. elegans, you can look at which motifs are overrepresented:

c elegans 4 neuron circuit motifs

(see source)

Qian, J., Hintze, A., & Adami, C. (2011). Colored Motifs Reveal Computational Building Blocks in the C. elegans Brain PLoS ONE, 6 (3) DOI: 10.1371/journal.pone.0017013

Borst, A. (2007). Correlation versus gradient type motion detectors: the pros and cons Philosophical Transactions of the Royal Society B: Biological Sciences, 362 (1479), 369-374 DOI: 10.1098/rstb.2006.1964

Pfeffer, C. (2014). Inhibitory Neurons: Vip Cells Hit the Brake on Inhibition Current Biology, 24 (1) DOI: 10.1016/j.cub.2013.11.001

Mysore, S., & Knudsen, E. (2012). Reciprocal Inhibition of Inhibition: A Circuit Motif for Flexible Categorization in Stimulus Selection Neuron, 73 (1), 193-205 DOI: 10.1016/j.neuron.2011.10.037

Marcus, G., Marblestone, A., & Dean, T. (2014). The atoms of neural computation Science, 346 (6209), 551-552 DOI: 10.1126/science.1261661

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