Present and permanent address: Physik-Department der TU Munchen Exploiting local stability we show what neuronal characteristics are essential to ensure that coherent oscillations are asymptotically stable in a spatially homogeneous network of spiking neurons. Under standard conditions, a necessary and in the limit of a large number of interacting neighbors also sufficient condition is that the postsynaptic potential is increasing in time as the neurons fire. If the postsynaptic potential is decreasing, oscillations are bound to be unstable. This is a kind of locking theorem and boils down to a subtle interplay of axonal delays, postsynaptic potentials, and refractory behavior. The theorem also allows for mixtures of excitatory and inhibitory interactions. On the basis of the locking theorem we present a simple geometric method to verify existence and local stability of a coherent oscillation. 2 1

pyramidal neurons was studied by use of computer simulations to test whether inhibitory interneurons could assist in phaselocking postsynaptic cells. Two models were used: a simplified model, which included only 3 membrane channels, and a detailed 1 l-channel model. 2. The 1 l-channel model included most of the ion channels known to be present in neocortical pyramidal neurons as well as calcium diffusion and other membrane mechanisms. The kinetics for the channels were obtained from voltage-clamp studies in a variety of preparations. The parameters were then adjusted to produce repetitive bursting similar to that seen in some cortical pyramidal cells entrained during visual stimulation. 3. Phase-locking to a train of inhibitory postsynaptic potentials (IPSPs) located on or near the soma was observed in the 3-channel model cell subjected to random synaptic bombardment. In the

How does the brain group together different parts of an object into a coherent visual object representation? Different parts of an object may be processed by the brain at different rates and may thus become desynchronized. Perceptual framing is a process that resynchronizes cortical activities corresponding to the same retinal object. A neural network model is presented that is able to rapidly resynchronize desynchronized neural activities. The model provides a link between perceptual and brain data. Model properties quantitatively simulate perceptual framing data, including psychophysical data about temporal order judgments and the reduction of threshold contrast as a function of stimulus length. Such a model has earlier been used to explain data about illusory contour formation, texture segregation, shape-from-shading, 3-D vision, and cortical receptive fields. The model hereby shows how many data may be understood as manifestations of a cortical grouping process that can rapidly res...

We present a cortical-based model for computing the perceptual salience of contours embedded in noisy images. It has been suggested (Gilbert, 1992; Field, Hayes & Hess, 1993) that horizontal intra-cortical connections in primary visual cortex may modulate contrast detection thresholds and pre-attentive "popout ". In our model, horizontal connections mediate context-dependent facilitatory and inhibitory interactions among oriented cells. Strongly facilitated cells undergo temporal synchronization; and perceptual salience is determined by the level of synchronized activity. The model accounts for a range of reported psychophysical and physiological effects of contour salience (Polat & Sagi, 1993, 1994; Kapadia, Ito, Gilbert & Westheimer, 1995; Field et al., 1993; Kovács, Polat & Norcia, 1996; Pettet, McKee & Grzywacz, 1996). In particular, the model proposes that intrinsic properties of synchronization account for the increased salience of smooth, closed contours (Kovács & Julesz, 1993, ...

Synchrony among multicortical EEGs 2 Freeman, Gaál & Jörnsten Information transfer and integration among functionally distinct areas of cerebral cortex of oscillatory activity requires some degree of phase synchrony of the trains of action potentials that carry the information prior to the integration. However, propagation delays are obligatory. Delays vary with the lengths and conduction velocities of the axons carrying the information, causing phase dispersion. In order to determine how synchrony is achieved despite dispersion, we recorded EEG signals from multiple electrode arrays on five cortical areas in cats and rabbits, that had been trained to discriminate visual or auditory conditioned stimuli. Analysis by time-lagged correlation, multiple correlation and PCA, showed that maximal correlation was at zero lag and averaged.7, indicating that 50 % of the power in the gamma range among the five areas was at zero lag irrespective of phase or frequency. There were no stimulus-related episodes of transiently increased phase locking among the areas, nor EEG "bursts " of transiently increased amplitude above the sustained level of synchrony. Three operations were identified to account for the sustained correlation. Cortices broadcast their outputs over divergent-convergent axonal

Scene analysis in the mammalian visual system, conceived as a distributed and parallel process, faces the so-called binding problem. As a possible solution, the temporal correlation hypothesis has been suggested and implemented in phase-coding models.

A network of Wilson-Cowan oscillators is constructed, and its emergent properties of synchronization and desynchronization are investigated by both computer simulation and formal analysis. The network is a two-dimensional matrix, where each oscillator is coupled only to its neighbors. We show analytically that a chain of locally coupled oscillators (the piece-wise linear approximation to the Wilson-Cowan oscillator) synchronizes, and present a technique to rapidly entrain finite numbers of oscillators. The coupling strengths change on a fast time scale based on a Hebbian rule. A global separator is introduced which receives input from and sends feedback to each oscillator in the matrix. The global separator is used to desynchronize different oscillator groups. Unlike many other models, the properties of this network emerge from local connections, that preserve spatial relationships among components, and are critical for encoding Gestalt principles of feature grouping. The ability to sy...

. We present the requirements for a neurocomputer for spike-processing neural networks. In a simulation study we investigated the performance of available hardware and showed, that there is still a need for a specific neurocomputer dedicated to the simulation of spike-processing networks. On the basis of our simulation study and an investigation of the features of spike-processing networks we analyses the requirements for the design of dedicated hardware. An efficient hardware architecture should contain an event-list module, a sender-oriented connection module and a number of fixed-point processing units. 1 Introduction Experimental results [1] [2] together with theoretical studies [3] [4] suggest that the time structure of neuronal spike trains is relevant in neuronal signal processing. The synchronized firing of neuronal assemblies could serve as a versatile and general mechanism for feature binding, pattern segmentation and figure/ground separation. This mechanism could also be u...

To explain how stimuli cause consciousness, we have to explain causality. We can't trace linear causal chains from receptors after the first cortical synapse, so we use circular causality to explain neural pattern formation by self-organizing dynamics. But an aspect of intentional action is causality, which we extrapolate to material objects in the world. Thus causality is a property of mind, not matter.

Introduction In the eighties interest in artificial neural networks was revived by the incorporation of statistical methods and analogies in physical systems, e.g. the back-propagation algorithm and the Hopfield model. This led to the well-known growth of this field. For a few years there has been a strong tendency towards a return to biology and towards including more details of neuronal signal processing. The background of this shift of interest is the experimental proof of stimulus-induced synchronized brain activity [Eckh88] [Gray89]. Together with the Correlation Theory by von der Malsburg [Mals86] this results in the assumption, that temporal correlation of activity might be used by the brain as a code to bind features to one object and to segregate one object from others. The synchronised firing of neuronal assemblies could serve as a versatile and general mechanism for feature binding, pattern segmentation and figure /ground separation. How the brain accomplishes these