The history of brain theory is described in terms of three kinds of theory of perception. The most widely used kind sees perception as dependent on passive inflow from the environment of information that is used to make and process representations of objects and events. A second kind views perception as an active search for information that is inherent in the environment and is extracted by tuned resonances in brain circuits. A third kind holds that perception works by the creation of information through chaotic dynamics by forming hypotheses about the environment, through which learning takes place. Experimental evidence for creative dynamics in brains is briefly sketched. The explanation is offered that brains, being finite systems, work this way in order to cope with the infinite complexity of the world. All that brains can know is the hypotheses they construct and the results of testing them by acting into the environment, and learning by assimilation from the sensory consequences of their actions. The process is described as intentionality. It works through the action-perception-assimilation cycle. The cost of this solution to the problem of infinite complexity by hypothesis testing is the progressive isolation of individuals, as they accumulate their unique experiences through which their personalities form. Socialization and the acquisition of shared knowledge requires the emergence of new personality structure by self-organization through chaotic dissolution of existing structure, as prelude to creation of new traits, habits and values. Dissolution works in a crisis situation by regression to earlier stages of development, from which a fresh start can be made. A state of malleability emerges in the depth of crisis, in which compassionate companions through lovin...

Fields of neural activity are seen in synchronized oscillations that are detected at mesoscopic scales in syntheses of multicellular recordings of action potentials and electroencephalograms (EEGs) over broad areas of cerebral cortex. The waves often have large-scale, highly textured spatial patterns of cortical activity that form in the context of associative learning under classical and operant conditioning in rabbits. The patterns show spatial amplitude modulation of shared oscillations of carrier waves in the beta and gamma ranges of the EEG, with recurrence at frame rates in the alpha and theta ranges. The frames also show spatial phase modulation that is inconsistent with driving of the oscillations by focal pacemakers. The hypothesis is developed that the synchronization manifests continuous distributions of activity in cortical neuropil that modulate firings of selected neural networks embedded in the neuropil. Five interactive agencies have been postulated to explain the mechanism for the field synchrony: electric fields; magnetic fields; electromagnetic fields (radio waves); diffusion chemical gradients; and order parameters that control self-organization of large populations of neurons by widespread synaptic interaction constituting negative and positive feedback. Only the last fits the data. The points are emphasized that these field patterns in frames require interactive neural dynamics that is modulated in respect to

The human data were collected in the EEG & Clinical Neurophysiology Laboratory, Harborview Medical Center, Seattle WA. The 8x8 electrode array was constructed by Ad-Tech Medical Instrument Corp. Racine WI 53404 in accordance with a Berkeley design. Programming was by Brian C. Burke in the Division of Neurobiology at Berkeley. Partial support was provided through grants NCC 2-1244 from NASA and EIA-0130352 from NSF to Robert Kozma. We are grateful for support from Dr. Scott Barnhart, Medical Director, Harborview Medical Center, Seattle WA.Stability and flexibility of human neocortex 2 Freeman, Holmes, West, Vanhatalo The electroencephalogram (EEG) in normal resting subjects is robustly stable. In epileptic subjects it reveals instability. We investigated EEGs in states of a neurosurgical patient awake and at rest, in sleep, and in intractable partial complex seizures. We used a microgrid array of 64 electrodes in a 1x1 cm window fixed on the right inferior temporal gyrus. EEG signals were recorded during a week of neurosurgical evaluation for treatment. Comparisons with normal intracranial EEG were perforce made with data from animal studies. Analytic phase and amplitude were calculated with the Hilbert transform to get the temporal resolution

Stability and flexibility of human neocortex 1 Freeman, Holmes, West, Vanhatalo Dynamics of human neocortex that optimizes its stability and flexibility

Modeling brain dynamics requires us to define the behavioral context in which brains interact with the world; to choose appropriate mathematics, here ordinary differential equations (ODE) and random graph theory (RGT); to choose the levels of description and scales in the hierarchy of neurodynamics; to define an appropriate module for each level; and to address questions of boundary conditions, linearity, time-variance, autonomy, and criticality. ODE applied to the olfactory system serves to model perception by a phase transition that reorganizes the background activity. Feedback control theory is used to model the dynamics of self-organized criticality and simulate the background activity and its reorganization, by which microscopic input triggers the construction of an order parameter that retrieves a mesoscopic spatiotemporal pattern expressing the class of input. Perception is shown to depend on the coincidence of three conditions: intentional prediction of a sensory input by an attractor landscape; emergence of a null spike in the background activity; and the presence in the sensory input of the expected stimulus. RGT serves to model criticality and the phase transition and the basic operations of perception in three-layered allocortex. Modeling six-layered neocortex faces the major problem