The approach adopted by Posner & Raichle in this book, with its strong emphasis on the cognitive level of description, is ideally suited to the study of psychotic illnesses. However, their discussion of depression and schizophrenia is based on a very small number of studies and involves ad hoc arguments derived largely from neuroanatomy. Their conclusions are almost certainly wrong.

Recurrent excitation is experimentally well documented in cortical populations. It provides for intracortical excitatory biases that linearize negative feedback interactions and induce macroscopic state transitions during perception. The concept of the local neighborhood should be expanded to spatial patterns as the basis for perception, in which large areas of cortex are bound into cooperative behavior with near-silent columns as important as active columns revealed by unit recording.

Two hypotheses concerning nonlinear elements in complex systems are contrasted: that neurons, intrinsically unstable, are stabilized through embedding in networks and populations; and, conversely, that cortical neurons are intrinsically stable, but are destabilized through embedding in cortical populations and corticostriatal feedback systems. Tests are made by piecewise linearization of nonlinear dynamics at nonequilibriumoperating points, followed by linear stability analysis.

Posner & Raichle's book presents methods and data that increase support for mind-brain unity and provide a method for studying and verifying brain dysfunction objectively. Their incorporation into the assessment technology of neuropsychology should accordingly constitute a major advance. In addition, these techniques may help clarify longstanding controversies in cognitive psychology such as whether perception is multimodal or amodal.

Encoding articulate speech is widely accepted as the principal (or sole) role of the frontal operculum. Clinical observations of speech apraxia have been confirmed by brain-imaging studies of speech production. We present evidence that the frontal operculum also programs limb movements. We argue that this area is a ventral counterpart of the dorsal premotor area. The two are functionally distinguished by specialization for somatic and visual space, respectively.

A theory of consciousness is proposed which integrates much of what we know about the evolution and functioning of the human brammmd. The organism constructs its world of experience as an adaptation to the problem of moving in the world. The relationship between the observed and unobserved world is discussed. A cartography of state-bound meaning is described in which the continuum of arousal states is linked to different states of consciousness. The inevitable ambiguity of perception is addressed and the evolutionary (...) and developmental importance of self-awareness is emphasized. All of this is related to poststructuralist formulations. (shrink)

A methodological problem may distort the implications derived from the metabolism scans of the brain, but Posner & Raichle may have found neural networks which underlie the analytical and synthetical hemispheric data processing mechanism. This methodological problem is that a large regional consumption of energy, detected by the PET technique, is not necessarily related to more data processing. It may be related to the inefficiency of the neural system at this region.

Wright & Liley provide an advance in addressing the interaction of multiple scales of processing in the brain. It should address in more detail the biological evidence that underlies the models it proposes to replace.

In a recent series of publications, dynamicist researchers have proposed a new conception of cognitive functioning. This conception is intended to replace the currently dominant theories of connectionism and symbolicism. The dynamicist approach to cognitive modeling employs concepts developed in the mathematical field of dynamical systems theory. They claim that cognitive models should be embedded, low-dimensional, complex, described by coupled differential equations, and non-representational. In this paper I begin with a short description of the dynamicist project and its role as (...) a cognitive theory. Subsequently, I determine the theoretical commitments of dynamicists, critically examine those commitments and discuss current examples of dynamicist models. In conclusion, I determine dynamicism's relation to symbolicism and connectionism and find that the dynamicist goal to establish a new paradigm has yet to be realized. (shrink)

In this paper we present Drama, a distributed model of analogical mapping that integrates semantic and structural constraints on constructing analogies. Specifically, Drama uses holographic reduced representations (Plate, 1994), a distributed representation scheme, to model the effects of structure and meaning on human performance of analogical mapping. Drama is compared to three symbolic models of analogy (SME, Copycat, and ACME) and one partially distributed model (LISA). We describe Drama's performance on a number of example analogies and assess the model in (...) terms of neurological and psychological plausibility. We argue that Drama's successes are due largely to integrating structural and semantic constraints throughout the mapping process. We also claim that Drama is an existence proof of using distributed representations to model high‐level cognitive phenomena. (shrink)

A theory of representation is incomplete if it states “representations areX” whereXcan be symbols, cell assemblies, functional states, or the flock of birds fromTheaetetus, without explaining the nature of the link between the universe ofXs and the world. Amit's thesis, equating representations with reverberations in Hebbian cell assemblies, will only be considered a solution to the problem of representation when it is complemented by a theory of how a reverberation in the brain can be a representation of anything.

Chaos in nervous system is a fascinating but controversial field of investigation. To approach the role of chaos in the real brain, we theoretically and numerically investigate the occurrence of chaos inartificial neural networks. Most of the time, recurrent networks (with feedbacks) are fully connected. This architecture being not biologically plausible, the occurrence of chaos is studied here for a randomly diluted architecture. By normalizing the variance of synaptic weights, we produce a bifurcation parameter, dependent on this variance and on (...) the slope of the transfer function, that allows a sustained activity and the occurrence of chaos when reaching a critical value. Even for weak connectivity and small size, we find numerical results in accordance with the theoretical ones previously established for fully connected infinite sized networks. The route towards chaos is numerically checked to be a quasi-periodic one, whatever the type of the first bifurcation is. Our results suggest that such high-dimensional networks behave like low-dimensional dynamical systems. (shrink)

Chaos theory is a rapidly growing field. As a technical term, chaos refers to deterministic but unpredictable processes being sensitively dependent upon initial conditions. Neurobiological models and experimental results are very complicated and some research groups have tried to pursue the neuronal chaos. Babloyantz's group has studied the fractal dimension (d) of electroencephalograms (EEG) in various physiological and pathological states. From deep sleep (d=4) to full awakening (d>8), a hierarchy of strange attractors paralles the hierarchy of states of consciousness. In (...) epilepsy (petit mal), despite the turbulent aspect of a seizure, the attractor dimension was near to 2. In Creutzfeld-Jacob disease, the regular EEG activity corresponded to an attractor dimension less than the one measured in deep sleep. Is it healthy to be chaotic? An active desynchronisation could be favourable to a physiological system. Rapp's group reported variations of fractal dimension according to particular tasks. During a mental arithmetic task, this dimension increased. In another task, a P300 fractal index decreased when a target was identified. It is clear that the EEG is not representing noise. Its underlying dynamics depends on only a few degrees of freedom despite yet it is difficult to compute accurately the relevant parameters.What is the cognitive role of such a chaotic dynamics? Freeman has studied the olfactory bulb in rabbits and rats for 15 years. Multi-electrode recordings of a few mm2 showed a chaotic hierarchy from deep anaesthesia to alert state. When an animal identified a previously learned odour, the fractal dimension of the dynamics dropped off (near limit cycles). The chaotic activity corresponding to an alert-and-waiting state seems to be a field of all possibilities and a focused activity corresponds to a reduction of the attractor in state space. For a couple of years, Freeman has developed a model of the olfactory bulb-cortex system. The behaviour of the simple model without learning was quite similar to the real behaviour and a model with learning is developed. (shrink)

The dynamical behaviour of a very general model of neural networks with random asymmetric synaptic weights is investigated in the presence of random thresholds. Using mean-field equations, the bifurcations of the fixed points and the change of regime when varying control parameters are established. Different areas with various regimes are defined in the parameter space. Chaos arises generically by a quasi-periodicity route.

Images of mindmarks a new era in human cognitive neuroscience. Despite the difficult conceptual problems associated with using group-averaged data and paired subtractions, human PET images converge well with existing data from other areas of cognitive neuroscience while opening up new theoretical and experimental possibilities. However, greater attention to individual differences might prove necessary in the study of culturally driven adaptations such as literacy.