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Reuse or re-function?
Published online by Cambridge University Press: 22 October 2010
Abstract
Simple specialization cannot account for brain functioning. Yet, we believe Anderson's reuse can be better explained by re-function. We suggest that functional demands shape brain changes and are the driving force behind reuse. For example, we suggest that the prefrontal cortex (PFC) is built as an infrastructure for multi-functions rather than as a module for reuse.
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Anderson is impressed by reuse; namely, by the fact that the same brain structures are used in different tasks and contexts. He points out that “in combination neural reuse and wiring optimization theory make some novel predictions for cortical layout” (sect. 2, para. 1). We agree that theories assuming simple structural specialization cannot account for all brain functioning. Yet, we suggest that functional demands drive reuse. More than thirty years ago, Paul Rozin suggested that the evolution of intelligence is marked by exploiting routines designed for a special task or goal, to achieve other goals (Rozin Reference Rozin, Sprague and Epstein1976). Namely, routines (programs, served by specific brain tissue) that were designed to provide specific solutions to unique problems become accessible to other systems through evolution and within the individual lifetime. Such routines are also examples for reuse, but they are better described as a change or expansion of function, rather than reuse, because we “make these (adaptive specializations) more generally available or accessible. This would have adaptive value when an area of behavioral function could profit from programs initially developed for another purpose” (Rozin Reference Rozin, Sprague and Epstein1976, p. 256).
Rozin connects such changes in accessibility to genetic programs in which “A specialization [circuit] could be extended by releasing (or depressing) the appropriate genetic program at the appropriate time in appropriate neural context. Such extensions have probably occurred many times in the evolution of organisms” (Rozin Reference Rozin, Sprague and Epstein1976, p. 260). Dehaene's neuronal recycling hypothesis (Dehaene Reference Dehaene, Dehaene, Duhamel, Hauser and Rizolatti2005; Dehaene & Cohen Reference Dehaene and Cohen2007) fits with this conceptualization; “ ‘neuronal recycling’… refer[s] to the putative mechanism by which a novel cultural object encroaches onto a pre-existing brain system … (which) occurs during the life span as a result of brain plasticity” (Dehaene & Cohen Reference Dehaene and Cohen2007, p. 384). We suggest that functional demands are the driving force behind reuse and that these demands shape brain changes.
Frontal control and brain connectivity
Anderson's second assumption in his massive redeployment hypothesis (MRH) is that older areas in the brain would be more subjective to reuse (sect. 1.1, para. 1). In contrast, the frontal lobes are able to perform more functions (or are more reused, in Anderson's words) than lower and older areas (Miller Reference Miller2000). The assumption that higher and more novel areas in the brain perform more functions can be explained by their connectivity. Specifically, it has been suggested that the prefrontal cortex (PFC) is “built for control,” because it is composed of several interconnected areas that are linked to cortical sensory and motor systems and to a wide range of subcortical structures, so that it is provided with the ability to synthesize a wide range of information. Miller (Reference Miller2000) and Duncan (Reference Duncan2001) suggested that the characteristics of the system and its connections allow flexibility that enables the system to adjust and control different situations. In addition, the PFC has widespread projections back to lower systems, which allow for a top-down influence. These features make it reasonable to assume that the PFC is built as an infrastructure for multi-functions, rather than as a module to be reused.
Attention
In visuo-spatial attention, responding is commonly faster and more efficient at cued (valid) than non-cued (invalid) locations. In exogenous-reflexive orienting of attention this validity effect is replaced, after 300 msec from cue onset, by faster responding to non-cued locations. This was described as inhibition of return (IOR), which helps to avoid automatic returning to already searched locations and is dependent on involvement of the midbrain superior colliculus (Klein Reference Klein2000; Posner & Cohen Reference Posner, Cohen, Bouma and Bouwhuis1984; Sapir et al. Reference Sapir, Soroker, Berger and Henik1999). It has been suggested that the evolutionarily older retinotectal visual system developed a mechanism (IOR) which, through connections with higher brain structures (e.g., parietal lobe; Sapir et al. Reference Sapir, Hayes, Henik, Danziger and Rafal2004), enabled coordination of reflexive and voluntary attentional systems (Sapir et al. Reference Sapir, Soroker, Berger and Henik1999). Connectivity with other brain areas helped to transfer control to higher brain centers.
Anterior cingulate cortex (ACC) – “Dedicated to one high-level use.”
In his target article, Anderson (suggests that “an individual brain region … will not be dedicated to … one high-level use” (sect. 2.1, para. 2). Anterior cingulate cortex (ACC) function is of interest here. There is wide agreement that the ACC is involved in conflict monitoring (Botvinick et al. Reference Botvinick, Cohen and Carter2004; Kerns et al. Reference Kerns, Cohen, MacDonald, Cho, Stenger and Carter2004). However, recent reports indicate that the ACC and close structures are also involved in outcome evaluation and in reward-based action (Botvinick et al. Reference Botvinick, Cohen and Carter2004; Ridderinkhof et al. Reference Ridderinkhof, Ullsperger, Crone and Nieuwenhuis2004). Such results suggest that conflict monitoring may be a manifestation of a more general function of the ACC. Specifically, the ACC is involved in monitoring and evaluating the outcomes of actions, and, in turn, serves to mold goal-directed behavior and achievement of planned behavior.
Numerical cognition
In the area of numerical cognition, many assume that the ability to grasp the number of displayed objects (e.g., counting) is an essential part of the core system that enables the development of the number sense and arithmetic skills. However, there are clear indications for a connection between numerical processing and size perception and judgment (Ashkenazi et al. Reference Ashkenazi, Henik, Ifergane and Shelef2008; Henik & Tzelgov Reference Henik and Tzelgov1982). Accordingly, it is possible that another system, heavily dependent on the processing of size, is the antecedent for the human numerical system. Namely, routines and neural structures built for size judgments were made available, through evolution, due to the need to develop an exact numerical system. Cantlon and colleagues (Cantlon et al. Reference Cantlon, Platt and Brannon2009) presented a similar idea: “a system that once computed one magnitude (e.g., size) could have been hi-jacked to perform judgments along a new dimension (e.g., number)” (p. 89).
Summary
We suggest that functional demands shape brain changes and are the driving force behind reuse. This is a different point of view, rather than just a terminology change.