We develop a theory for the temporal integration of visual motion motivated by psychophysical experiments. The theory proposes that input data are temporally grouped and used to predict and estimate the motion flows in the image sequence. This temporal grouping can be considered a generalization of the data association techniques that engineers use to study motion sequences. Our temporal grouping theory is expressed in terms of the Bayesian generalization of standard Kalman filtering. To implement the theory, we derive a parallel network that shares some properties of cortical networks. Computer simulations of this network demonstrate that our theory qualitatively accounts for psychophysical experiments on motion occlusion and motion outliers. In deriving our theory, we assumed spatial factorizability of the probability distributions and made the approximation of updating the marginal distributions of velocity at each point. This allowed us to perform local computations and simplified our implementation. We argue that these approximations are suitable for the stimuli we are considering (for which spatial coherence effects are negligible).

Although the commonly used quadratic Hebbian-;anti-Hebbian rules lead to successful models of plasticity and learning, they are inconsistent with neurophysiology. Other rules, more physiologically plausible, fail to specify the biological mechanism of bidirectionality and the biological mechanism that prevents synapses from changing from excitatory to inhibitory, and vice versa. We developed a synaptic bidirectional Hebbian rule that does not suffer from these problems. This rule was compared with physiological homosynaptic conditions in the hippocampus, with the results indicating the consistency of this rule with long-term potentiation (LTP) and long-term depression (LTD) phenomenologies. The phenomenologies considered included the reversible dynamics of LTP and LTD and the effects of N -methyl- D -aspartate blockers and phosphatase inhibitors.

Several models of cortical development postulate that a Hebbian process fed by spontaneous activity amplifies orientation biases occurring randomly in early wiring, to form orientation selectivity. These models are not applicable to the development of retinal orientation selectivity, since they neglect the polarization of the retina's poorly branched early dendritic trees and the wavelike organization of the retina's early noise. There is now evidence that dendritic polarization and spontaneous waves are key in the development of retinal receptive fields. When models of cortical development are modified to take these factors into account, one obtains a model of retinal development in which early dendritic polarization is the seed of orientation selectivity, while the spatial extent of spontaneous waves controls the spatial profile of receptive fields and their tendency to be isotropic.

Waves of action-potential bursts propagate across the ganglion-cell surface of isolated developing retinas. It has been suggested that the rise of extracellular potassium concentration following a burst of action potentials in a cell may underlie these waves by depolarizing neighbor cells. This suggestion is sensible for developing tissues, since their glial system is immature. We tested whether this extracellular-potassium suggestion is feasible. For this purpose, we built a realistic biophysical model of the ganglion-cell layer of the developing retina. Simulations with this model show that increases of extracellular potassium are sufficiently high (about fourfold) to mediate the waves consistently with experimental physiological and pharmacological data. Even if another mechanism mediates the waves, these simulations indicate that extracellular potassium should significantly modulate the waves' properties.