Michael Anderson

Part of understanding the functional organization of the brain is understanding how it evolved. This talk presents evidence suggesting that while the brain may have originally emerged as an organ with functionally dedicated regions, the creative re-use of these regions has played a significant role in its evolutionary development. This would parallel the evolution of other capabilities wherein existing structures, evolved for other purposes, are re-used and built upon in the course of continuing evolutionary development (“exaptation”: Gould & Vrba 1982). There is psychological support for exaptation in cognition (e.g. Cosmides 1989), theoretical reason to expect it (Anderson 2003; in press-a; in press-b) and neuroanatomic evidence that the brain evolved by preserving, extending, and combining existing network components, rather than by generating complex structures de novo (Sporns & Kötter 2004). However, there has been little evidence that integrates these perspectives, bringing such an account of the evolution of cognitive function into the realm of cognitive neuroscience (although see, e.g., Barsalou 1999).

This essay introduces the massive redeployment hypothesis, an account of the functional organization of the brain that centrally features the fact that brain areas are typically employed to support numerous functions. The central contribution of the essay is to outline a middle course between strict localization on the one hand, and holism on the other, in such a way as to account for the supporting data on both sides of the argument. The massive redeployment hypothesis is supported by case studies of redeployment, and compared and contrasted with other theories of the localization of function.

The massive redeployment hypothesis (MRH) is a theory about the functional topography of the human brain, offering a middle course between strict localization on the one hand, and holism on the other. Central to MRH is the claim that cognitive evolution proceeded in a way analogous to component reuse in software engineering, whereby existing components-originally developed to serve some specific purpose-were used for new purposes and combined to support new capacities, without disrupting their participation in existing programs. If the evolution of cognition was indeed driven by such exaptation, then we should be able to make some specific empirical predictions regarding the resulting functional topography of the brain. This essay discusses three such predictions, and some of the evidence supporting them. Then, using this account as a background, the essay considers the implications of these findings for an account of the functional integration of cognitive operations. For instance, MRH suggests that in order to determine the functional role of a given brain area it is necessary to consider its participation across multiple task categories, and not just focus on one, as has been the typical practice in cognitive neuroscience. This change of methodology will motivate (even perhaps necessitate) the development of a new, domain-neutral vocabulary for characterizing the contribution of individual brain areas to larger functional complexes, and direct particular attention to the question of how these various area roles are integrated and coordinated to result in the observed cognitive effect. Finally, the details of the mix of cognitive functions a given area supports should tell us something interesting not just about the likely computational role of that area, but about the nature of and relations between the cognitive functions themselves. For instance, growing evidence of the role of “motor” areas like M1, SMA and PMC in language processing, and of “language” areas like Broca’s area in motor control, offers the possibility for significantly reconceptualizing the nature both of language and of motor control.

Multi-voxel pattern analysis (MVPA) is a popular analytical technique in neuroscience that involves identifying patterns in fMRI BOLD signal data that are predictive of task conditions. But the technique is also frequently used to make inferences about the regions of the brain that are most important to the tasks in question, and our analysis shows that this is a mistake. MVPA does not provide a reliable guide to what information is being used by the brain during cognitive tasks, nor where that information is. This is due in part to inherent run to run variability in the decision space generated by the classifier, but there are also several other issues, discussed below, that make inference from the characteristics of the learned models to relevant brain activity deeply problematic. These issues have significant implications both for many papers already published, and for how the field uses this technique in the future.

The representations formed by the ventral and dorsal streams of a prelinguistic agent will tend to be too qualitatively similar to support the distinct roles required by PREDICATE(x) structure. We suggest that the attachment of qualities to objects is not a product of the combination of these separate processing streams, but is instead a part of the processing required in each. In addition, we suggest that the formation of objective predicates is inextricably bound up with the emergence of language itself, and so cannot be cleanly identified with any prelinguistic cognitive capacities.

For the least the last 10 years, there has been growing interest in, and grow- ing evidence for, the intimate relations between more abstract or higher order cognition—such as reasoning, planning, and language use—and the more con- crete, immediate, or lower order operations of the perceptual and motor sys- tems that support seeing, feeling, moving, and manipulating. A sub-field of the larger research program in embodied cognition (Clark, 1997, 1998; Wilson, 2001; Anderson, 2003, 2007d, 2008; Gibbs, 2006), this work has generally pro- ceeded under the banner of grounded cognition, and works to support the claim that thinking is inherently tied to—grounded in—perceiving and acting. Thus, Glenberg and Kaschak (2002) discuss “grounding language in action”; Gallese and Lakoff (2005) argue that concepts are “grounded in the sensory–motor sys- tem;” and Barsalou (1999) at various times talks of “grounding cognition in perception,” “grounding conceptual knowledge in modality-specific systems” (Barsalou et al., 2003), and most recently simply of “grounded cognition” (Barsalou, 2008).

Maintaining adequate performance in dynamic and uncertain settings has been a perennial stumbling block for intelligent systems. Nevertheless, any system intended for real-world deployment must be able to accommodate unexpected change—that is, it must be perturbation tolerant. We have found that metacognitive monitoring and control—the ability of a system to self-monitor its own decision-making processes and ongoing performance, and to make targeted changes to its beliefs and action-determining components—can play an important role in helping intelligent systems cope with the perturbations that are the inevitable result of real-world deployment. In this article we present the results of several experiments demonstrating the efficacy of metacognition in improving the perturbation tolerance of reinforcement learners, and discuss a general theory of metacognitive monitoring and control, in a form we call the metacognitive loop.

Embodied cognition (EC) is growing up, and How the Body Shapes the Mind is both a sign of, and substantive contributor to, this ongoing development. Born in or about 1991 (the year of publication of seminal works by Brooks, Dreyfus, and Varela, Thompson & Rosch), EC is only now emerging from a tumultuous but exciting childhood marked in particular by the size and breadth of the extended family hoping to have some impact on its early education and upbringing. As family members include computer science, phenomenology, developmental and cognitive psychology, analytic philosophy of mind, linguistics, neuroscience, and eastern mysticism—just to name a few—EC has both benefited and suffered from a wealth of different and often incompatible ideas about who and what it is, what it should do with its life, even what language it should speak. Gallagher brings some cohesion and consistency to this situation, not by surveying and synthesizing these competing approaches, but by carefully marshalling the evidence and developing the vocabulary to thoroughly consider a few fundamental issues.

Description: The massive redeployment hypothesis (MRH) is a theory about the functional organization of the human cortex, offering a middle course between strict localization on the one hand, and holism on the other. Central to MRH is the claim that cognitive evolution proceeded in a way analogous to component reuse in software engineering, whereby existing components—originally developed to serve some specific purpose—were used for new purposes and combined to support new capacities, without disrupting their participation in existing programs.