Tuesday, October 26, 2010

Did neural reuse play a role in language evolution?

There's an interesting article in the new of the Behavioral and Brain Sciences along with a number of equally interesting commentaries:

An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role of neural plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language [-my emphasis, M.P.]; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design.
I think stressing the importance of things like neural reuse and recruitment also fits in nicely with a recent post over at Replicated Typo about the role of "Domain-General Regions and Domain-Specific Networks" in the evolution of language, where Wintz proposes a rough outline of a possible evolutionary scenario for the emergence of language:
  1. Relaxed selection allowed developmental processes to open up new levels of functional complexity;
  2. This functional complexity was achieved through allowing additional neural systems to influence a specific type of behaviour;
  3. With these new possibilities now unmasked, natural selection then operated on maintaining this functional complexity by preparing individuals for linguistic input;
  4. One suggestion for how this might be achieved is through selection for neural circuitry that aids in creating the networks that subserve language processing;
  5. So instead of having domain-specific modules, humans have domain-general modules that are networked in a domain-specific manner.
  6. Rapidly acquired, and seemingly ubiquitous, features across languages are therefore more likely to have been the product of cultural evolutionary processes that enable a language to adapt to various constraints, including: domain-general mechanisms, the transmission vector, demography, the environment etc.

Saturday, October 23, 2010

New Issue of Trends in Cognitive Sciences: relational knowledge and killjoy explanations in comparative psychology

The lates issue of Trends in Cognitive Sciences has just been published. Two of the articles look escpecially interesting:

From the process of organic evolution to the analysis of insect societies as self-organizing systems, biology is full of awe-inspiring examples of complexity arising from simplicity. Yet in the contemporary study of animal cognition, demonstrations that complex human-like behavior arises from simple mechanisms rather than from ‘higher’ processes, such as insight or theory of mind, are often seen as uninteresting and ‘killjoy’, almost a denial of mental continuity between other species and humans. At the same time, however, research elsewhere in psychology increasingly reveals an unexpected role in human behavior for simple, unconscious and sometimes irrational processes shared by other animals. Greater appreciation of such mechanisms in nonhuman species would contribute to a deeper, more truly comparative psychology.
Accumulating evidence on the nature, function and acquisition of relational knowledge indicates a crucial role of such knowledge in higher cognitive processes. In this review, we specify the essential properties of relational knowledge, together with the role it plays in reasoning, categorisation, planning, quantification and language. Furthermore, we discuss the processes involved in its acquisition and how these processes have been implemented in contemporary neural network models. We present evidence demonstrating that relational knowledge integrates heuristic and analytic cognition, is important for symbolic processes and the creation of novelty, activates specific regions of the prefrontal cortex, and is the most recently evolved and slowest-developing cognitive process. Arguably, relational knowledge represents the core of higher cognition.

Saturday, October 16, 2010

30th Anniversary Perspectives on Cognitive Science

The lates two issues of the journal Topics in Cognitive Science feature a very interesting collection of reviews that cover
"disciplines and perspectives that have been central to Cognitive Science for the past 30 years and that are likely to be central for the next 30 years and beyond."
(see here and here, subscription required)

To further quote the introduction by Lawrence W. Barsalou,
"the disciplines (and the authors addressing them) include the following:

"Psychology (Dedre Gentner)

Artificial Intelligence (Kenneth D. Forbus)

Philosophy (William Bechtel)

Linguistics (Elissa L. Newport)

Anthropology (Andrea Bender, Edwin Hutchins, and Douglas L. Medin)

Education (Susan Chipman)

Neuroscience (Rick Cooper and Tim Shallice)

Primate Cognition (Amanda Seed and Michael Tomasello)

The theoretical perspectives (and the authors addressing them) include the following:

Cognitive Architectures (Neils Taatgen and John R. Anderson)

Emergentist Approaches (James L. McClelland)

Formal Modeling (Richard Shiffrin)

Developmental Systems (Linda B. Smith)

Cognitive Ecology (Edwin Hutchins)

Grounded Cognition (Lawrence W. Barsalou)"
The article by Lawrence Barsalou on 'Grounded Cognition' in particular looks very interesting to me (pre-final draft can be found here). Here's the abstract:
"Thirty years ago, grounded cognition had roots in philosophy, perception, cognitive linguistics, psycholinguistics, cognitive psychology, and cognitive neuropsychology. During the next 20 years, grounded cognition continued developing in these areas, and it also took new forms in robotics, cognitive ecology, cognitive neuroscience, and developmental psychology. In the past 10 years, research on grounded cognition has grown rapidly, especially in cognitive neuroscience, social neuroscience, cognitive psychology, social psychology, and developmental psychology. Currently, grounded cognition appears to be achieving increased acceptance throughout cognitive science, shifting from relatively minor status to increasing importance. Nevertheless, researchers wonder whether grounded mechanisms lie at the heart of the cognitive system or are peripheral to classic symbolic mechanisms. Although grounded cognition is currently dominated by demonstration experiments in the absence of well-developed theories, the area is likely to become increasingly theory driven over the next 30 years. Another likely development is the increased incorporation of grounding mechanisms into cognitive architectures and into accounts of classic cognitive phenomena. As this incorporation occurs, much functionality of these architectures and phenomena is likely to remain, along with many original mechanisms. Future theories of grounded cognition are likely to be heavily influenced by both cognitive neuroscience and social neuroscience, and also by developmental science and robotics. Aspects from the three major perspectives in cognitive science—classic symbolic architectures, statistical/dynamical systems, and grounded cognition—will probably be integrated increasingly in future theories, each capturing indispensable aspects of intelligence."