Invited Talks
Last update: Mar 5, 1997
Larry Cauller NeuroInteractivism: Explaining emergence without representation
Recently established principles of neural connectionism promote a neurointeractivist paradigm of brain and behavior which emphasizes interactivity between neurons within cortical areas, between areas of the cerebral cortex, and between the cortex and the environment. This paradigm recognizes the closed architecture of the behaving organism with respect to motor/sensory integration within a dynamic environment where the majority of sensory activity is the direct consequence of self-initiated motor actions. We have found that top-down cortical inputs to primary sensory areas which predict discrimination behavior in monkeys selectively activate the cortico-bulbar neurons that mediate directed movements. Unlike the widely distributed axons and long-lasting excitatory synaptic effects of the top-down projections which generate the associative context for motor/sensory interactivity, the bottom-up sensory projections are spatially precise and activate a brief excitation followed by a long-lasting inhibition. Therefore, the sensory consequences of a motor action are the major sources of negative feedback which complete an interactive cycle of associative hypothesis testing: a winner-take-all motor/sensory pattern initiates an action within a top-down associative context; the bottom-up sensory consequences of that action interfere with top-down sensory predictions for refinement of the associative hypothesis; then the testing cycle repeats as the sensory inhibition releases the next motor/sensory winner-take-all action. Given this interactivity, perception is a proactive behavior rather than information processing, neurons simply respond to their inputs rather than encode sensory properties, so there is no need to impose representationalism because neural activity patterns are dynamical attractors associating sensory predictions with motor actions. The associative hypothesis is the neurointeractive equivalent to awareness and hypothesis testing is the basis for attention. The formation of action/prediction associations by interactivity explains early development from self-organized cortical attractor spaces in utero, to the emergence of self-identity in the newborn which learns to predict the immediate effects of self-action (i.e., listening to its own speech sounds), to the emergence of recognition by prediction of ecological contingencies, to the emergence of speech by prediction of mother’s responses to infant speech. Ultimately, our scientific paradigm likewise emerges by neurointeractivity as we learn to see the world in a way that explains more of the effects of our actions.
Georg Dorffner The connectionist route to embodiment and dynamicism
This talk discusses the possible contributions of connectionism to new trends in cognitive science, in particular to cognitive models that focus on issues of embodiment, and on viewing cognition from a dynamical point of view. It will be argued that connectionism has had its fair share in driving cognitive science towards new horizons, and that its potentials are far from being fully exploited -- despite the fact that connectionism has seem to become an established subfield of cognitive science more in the realm of classical encoding theories.The most important contribution of connectionism is its provision of concrete modeling frameworks that help in replacing traditional conceptions of representation by an approach that views representation in the constructivist sense of behavior-guiding structures, which are inextricably tied to an agent's bodily actions in an environment. Although hardly exploited in recent models, taking connectionism seriously almost naturally leads to such a novel approach. This talk will discuss the major reasons why this is so.
A second contribution becomes obvious when one realizes that connectionism again provides a natural basis for shifting one's view of cognition from a computational to a dynamical point of view (such as exemplified in the work of Tim van Gelder). Concrete issues such as complexity in dynamic state spaces -- and why one would want to realize them in a connectionist network -- will be discussed.
As a concrete example, the issue of categorization will be presented. Categorization can be viewed as an essential component for concept formation in connectionist models. It can also be seen as an important mechanism enhancing the capabilities of autonomous agents. Finally it can be viewed as the process of inducing certain kinds of attractors in a dynamic state space. Thus, categorization is one example of how results from more traditionally applied connectionism, results from work on embodied autonomous agents, and results from work on dynamical approaches to cognitive modeling can be brought together.
Ernst von Glasersfeld Piaget's legacy: Cognition as adaptive activity
In the visual arts, "representation" usually means a copy or reproduction of some original. In that context it is clear that the original is always something the representer has seen, something that is the product of ordinary visual perception. With the introduction of the term in philosophical writings, the spurious question has arisen whether or not representations could reproduce, replicate, or correspond to things-in-themselves. The question was long ago given a negative answer on logical grounds by neurophysiology. Most arguments on the topic could have been avoided if one had followed Mark Baldwin, the pioneer of cognitive psychology, and had used the term "representation" which has the added advantage of being a viable translation of the German "Vorstellung".
Stevan Harnad Keeping a grip on the real/virtual distinction in this representationalist age
Representation is a three part relation. There is (1) an object (the "representation"), plus (2) whatever the object is a representation of, plus (3) whoever the object is a representation to. Only cognitive scientists have to worry about all three of these parts. Other disciplines, such as archeology and theology can concern themselves only with one or two of them. Cognitive scientists deal with internal representations (hence the object is inside a brain or a machine) and they must avoid the symbol grounding problem, which is to dub the internal object a representation merely because it represents something to the cognitive scientist. Current undergraduates, motherboard-bred, are losing their grip on the distinction between the virtual and the real, ready to believe such incoherencies as that they themselves might merely be objects in someone else's virtual world. The best cure is to abandon representationalist talk and mentalism altogether, and focus only on the internal structures and processes that make it possible to do what robotic models can do. Leave the question of whether or not they mean something till the work of scaling up to our full robotic capacity is complete.