The mechanisms of perceptual learning are analyzed theoretically, probed in an orientationdiscrimination experiment involving a novel nonstationary context manipulation, and instantiated in a detailed computational model. Two hypotheses are examined: modification of early cortical representations versus task-specific selective reweighting. Representation modification seems neither functionally necessary nor implied by the available psychophysical and physiological evidence. Computer simulations and mathematical analyses demonstrate the functional and empirical adequacy of selective reweighting as a perceptual learning mechanism. The stimulus images are processed by standard orientation- and frequency-tuned representational units, divisively normalized. Learning occurs only in the “read-out” connections to a decision unit; the stimulus representations never change. An incremental Hebbian rule tracks the task-dependent predictive value of each unit, thereby improving the signal-to-noise ratio of their weighted combination. Each abrupt change in the environmental statistics induces a switch cost in the learning curves as the system temporarily works with suboptimal weights.

The position, size, and shape of the visual receptive field (RF) of some primary visual cortical neurons change dynamically, in response to artificial scotoma conditioning in cats (Pettet & Gilbert, 1992) and to retinal lesions in cats and monkeys (DarianSmith & Gilbert, 1995). The "EXIN" learning rules (Marshall, 1995) are used to model dynamic RF changes. The EXIN model is compared with an adaptation model (Xing & Gerstein, 1994) and the LISSOM model (Sirosh & Miikkulainen, 1994; Sirosh et al., 1996). To emphasize the role of the lateral inhibitory learning rules, the EXIN and the LISSOM simulations were done with only lateral inhibitory learning. During scotoma conditioning, the EXIN model without feedforward learning produces centrifugal expansion of RFs initially inside the scotoma region, accompanied by increased responsiveness, without changes in spontaneous activation. The EXIN model without feedforward learning is more consistent with the neurophysiological data than are the a...

... autonomously develops, stabilizes its own development, and then gives rise to visual perception in the adult. Much evidence suggests that the visual cortex generates representations of perceptual boundaries and surfaces. The present article focuses on how the visual cortex develops the circuitry that generates perceptual boundaries. Boundary formation is also known as perceptual grouping, or the binding problem. Developing cortical circuits may be refined by visual experience. The model clarifies how developing circuits protect themselves against being catastrophically eroded by fluctuations in visual inputs. Remarkably, the processes which stabilize development in the infant lead to properties in the adult of perceptual grouping, attention, and learning. Thus, the laws of adult perception seem to be strongly constrained by stability constraints on infant development. This modeling perspective opens a path towards unifying three fields: infant cortical development, adult cortical neurophysiology and anatomy, and adult visual psychophysics. The model further clarifies why visual cortex, indeed all neocortex, is organized into layered circuits. It hereby contributes to an understanding of how the laminar organization of neocortex supports biological intelligence.

Intracortical microstimulation (ICMS) of a single site in the somatosensory cortex of rats and monkeys for 2--6 hours produces a large increase in the number of neurons responsive to the skin region corresponding to the ICMS-site receptive field (RF), with very little effect on the position and size of the ICMS-site RF, and the response evoked at the ICMS site by tactile stimulation (Recanzone et al., 1992b). Large changes in RF topography are observed following several weeks of repetitive stimulation of a restricted skin region in monkeys (Jenkins et al., 1990; Recanzone et al., 1992acde). Repetitive stimulation of a localized skin region in monkeys produced by training the monkeys in a tactile frequency discrimination task improves their performance (Recanzone et al., 1992a). It has been suggested that these changes in RF topography are caused by competitive learning in excitatory pathways (Grajski & Merzenich, 1990; Jenkins et al., 1990; Recanzone et al., 1992abcde). ICMS almost sim...

You might find this additional information useful... This article cites 209 articles, 91 of which you can access free at:

While recent studies of synaptic stability in adult cerebral cortex have focused on dendrites, how much axons change is unknown. We have used advances in axon labeling by viruses and in vivo two-photon microscopy to investigate axon branching and bouton dynamics in primary visual cortex (V1) of adult Macaque monkeys. A nonreplicative adeno-associated virus bearing the gene for enhanced green fluorescent protein (AAV.EGFP) provided persistent labeling of axons, and a custom-designed two-photon microscope enabled repeated imaging of the intact brain over several weeks. We found that large-scale branching patterns were stable but that a subset of small branches associated with terminaux boutons, as well as a subset of en passant boutons, appeared and disappeared every week. Bouton losses and gains were both w7 % of the total population per week, with no net change in the overall density. These results suggest ongoing processes of synaptogenesis and elimination in adult V1.

The position, size, and shape of the receptive field (RF) of some cortical neurons change dynamically, in response to artificial scotoma conditioning (Pettet & Gilbert, 1992) and to retinal lesions (Chino et al., 1992; Darian-Smith & Gilbert, 1995) in adult animals. The RF dynamics are of interest because they show how visual systems may adaptively overcome damage (from lesions, scotomas, or other failures), may enhance processing efficiency by altering RF coverage in response to visual demand, and may perform perceptual learning. This paper presents an afferent excitatory synaptic plasticity rule and a lateral inhibitory synaptic plasticity rule -- the EXIN rules (Marshall, 1995a) -- to model persistent RF changes after artificial scotoma conditioning and retinal lesions. The EXIN model is compared to the LISSOM model (Sirosh et al., 1996) and to a neuronal adaptation model (Xing & Gerstein, 1994). The rules within each model are isolated and are analyzed independently, to elucidate t...