in virtually all Vl and MT neurons was nearly consistent with a completely random process (e.g., C, = 1). We tried to model this high variability by small, indepen-dent, and random EPSPs converging onto a leaky integrate-and-fire neuron (Knight, 1972). Both this and related models

PDP (parallel distributed processing, or artificial neural network) models were too biologically unrealistic to provide viable interpretations of the single-cell data. Churchland and Sejnowski show how distributed models can now attack this problem, providing significant insights into brain function

The development of stimulus selectivity in the primary sensory cortex of higher vertebrates is considered in a general mathematical framework. A synaptic evolution scheme of a new kind is proposed in which incoming patterns rather than converging afferents compete. The change in the efficacy of a

Integrating conceptually similar models of the growth of marine and terrestrial primary producers yielded an estimated global net primary production (NPP) of 104.9 petagrams of carbon per year, with roughly equal contributions from land and oceans. Approaches based on satellite indices of absorbed

Vision is a very important issue developing artificial anthropomorphic systems. Starting from traditional knowledge about ocular movements, mainly due to physiological observations, the paper revisits primary ocular processes and proposes some new ideas for oculomotor control. It is shown

integral in stochastic integration theory. The results are applied to ODE driven by fractal functions and to anticipative SDE whose noise processes possess absolutely continuous generalized covariation processes. Mathematics Subject Classification: Primary 60H, Secondary 26A42

Reliability assessment is an important part of the design process of digital integrated circuits. We observe that a common thread that runs through most causes of run-time failure is the extent of circuit activity, i.e., the rate at which its nodes are switching. We propose a new measure

that can conceptualize the different effects of rewards on behavior. The scientific investigation of behavioral processes by animal learning theory and economic utility theory has produced a theoretical framework that can help to elucidate the neural correlates for reward functions in learning, goal

when the integrand is a distribution, the value of our stochastic integral process is a real-valued martingale. We use this extended integral to recover necessary and su#cient conditions under which the linear wave equation driven by spatially homogeneous Gaussian noise has a process solution

Processing of retinal images is carried out in the myriad dendritic arborizations of cortical neurons. Such processing involves complex dendritic integration of numerous inputs, and the subsequent output is transmitted to multiple targets by extensive axonal arbors. Thus far, details