On the computational architecture of the neocortex

By David Mumford. 2004

1,006 citations recorded by the source corpus.

This paper proposes that each area of the cortex carries on its calculations with the active participation of a nucleus in the thalamus with which it is reciprocally and topographically connected. Each cortical area is responsible for maintaining and updating the organism's knowledge of a specific aspect of the world, ranging from low level raw data to high level abstract representations, and involving interpreting stimuli and generating actions. In doing this, it will draw on multiple sources of expertise, learned from experience, creating multiple, often conflicting, hypotheses which are integrated by the action of the thalamic neurons and then sent back to the standard input layer of the cortex. Thus this nucleus plays the role of an ‘active blackboard’ on which the current best reconstruction of some aspect of the world is always displayed. Evidence for this theory is reviewed and experimental tests are proposed. A sequel to this paper will discuss the cortico-cortical loops and propose quite different computational roles for them.

Subfields: Artificial Intelligence, Cognitive Neuroscience

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Citations in the corpus

Theory of Mind: A Neural Prediction Problem (2013, positive): “In fact, predictive coding was initially suggested as a model for visual perception (Barlow, 1961; Gregory, 1980; Mumford, 1992), using a visual error code that preferentially encodes unexpected visual information.”
Free-Energy Minimization and the Dark-Room Problem (2012, background): “Indeed, some specific neurobiological proposals for the computational anatomy of the brain are based on this formulation of perception (Mumford, 1992).”
Object perception as Bayesian inference. (2004, methodology): “…depth, or background clutter) may require an internal generative process that in some sense mirrors aspects of the external generative model used for inference (Grenander 1996, Mumford 1992,Rao & Ballard 1999,Tu & Zhu 2002a,Tu et al 2003) or for learning (Dayan et al 1995,Hinton & Ghahramani 1997).”
Toward a neurophenomenology as an account of generative passages: a first empirical case study (2002, background): “" 5 Varela (1996), or for a collection of papers see the contemplative and phenomenological section in Varela and Shear (1999) or Petitot et al. (1999). 6 See the introspection section in Varela and Shear (1999) 7 For a cross-disciplinary study of this topic see Depraz et al.”
Predictive Coding as a Model of Response Properties in Cortical Area V1 (2010, background): “…regions at preceding stages along an information processing pathway to calculate the residual error, which is then propagated via cortical feedforward connections (Mumford, 1992; Barlow, 1994; Rao and Ballard, 1999; Murray et al., 2004; Friston, 2005, 2009; Jehee et al., 2006; Kilner et al., 2007).”
A review of predictive coding algorithms. (2017, background): “1; Mumford, 1992), hypothesises that cortical feedback connections act to suppress information which is predicted by higher-level cortical regions.”
Prediction, Cognition and the Brain (2009, background): “…of how errors of prediction are processed online relates strongly to the general issue of the integration of top-down and bottom-up information which has been posited to rely on error-minimalization mechanisms (Grossberg, 1980; Mumford, 1992; Ullman, 1995; Friston, 2005; Kveraga et al., 2007b).”
Attention, Uncertainty, and Free-Energy (2010, background): “This section focuses on directed spatial attention predictive coding (Rao and Ballard, 1998) and involves recurrent message passing among hierarchical levels of cortical systems to optimize a probabilistic representation of the world (Mumford, 1992; Friston, 2009).”
Active interoceptive inference and the emotional brain (2016, background): “Current interpretations suggest that superficial pyramidal cells (red triangles) compare the expectations (at each level) with top-down predictions from deep pyramidal cells (black triangles) of higher levels (22, 23).”
The neural architecture of language: Integrative modeling converges on predictive processing (2020, positive): “…McRae et al., 1998; Rohde & Plaut, 1999; Spivey & Tanenhaus, 1998; Tenenbaum et al., 2011) and neuroscience (Bastos et al., 2012; Keller & Mrsic-Flogel, 2018; Mumford, 1992; Rao & Ballard, 1999; Srinivasan et al., 1982), including in the domain of language (Kuperberg & Jaeger, 2016; Levy, 2008a).”
Varieties of cognitive penetration in visual perception. (2014, neutral): “…coding has been put forward by Friston (2010) and Clark (2013) while the basic ideas have been developed already earlier going back to Helmholtz (1860), Sokolov (1960), Gegory (1968) and Mumford (1992) (see Clark (2013) and commentaries for an extensive review and the history of these ideas).”
The functional logic of cortico-pulvinar connections. (2003, result): “The proposal was put forward specifically for geniculostriate interactions, but is equally applicable to pulvinar-prestriate reciprocal circuits, and similar in principle to the idea of the thalamus as an ‘active blackboard’ for the cortex (Mumford 1991).”