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We have used information-theoretic ideas to derive a class of practical and nearly optimal schemes for adapting the size of a neural network. By removing unimportant weights from a network, several improvements can be expected: better generalization, fewer training examples required, and improved speed of learning and/or classification. The basic idea is to(More)
  • References, D B Schwartz, +5 authors B A Huberman Generalization
  • 1992
it is strictly only valid in a little neighborhood around that vector. The improvement from a weight decay was also tested by simulations. For the NetTalk data it was shown that a weight decay can decrease the generalization error (squared error) and also, although less signiicantly, the actual mistake rate of the network when the phoneme closest to the(More)
Cortical layering is a hallmark of the mammalian neocortex and a major determinant of local synaptic circuit organization in sensory systems. In motor cortex, the laminar organization of cortical circuits has not been resolved, although their input-output operations are crucial for motor control. Here, we developed a general approach for estimating(More)
We study the dynamics of excitable integrate-and-fire neurons in a small-world network. At low densities p of directed random connections, a localized transient stimulus results either in self-sustained persistent activity or in a brief transient followed by failure. Averages over the quenched ensemble reveal that the probability of failure changes from 0(More)
Single-unit activity in the neostriatum of awake monkeys shows a marked dependence on expected reward. Responses to visual cues differ when animals expect primary reinforcements, such as juice rewards, in comparison to secondary reinforcements, such as tones. The mechanism of this reward-dependent modulation has not been established experimentally. To(More)
The prefrontal cortex and basal ganglia are deeply implicated in working memory. Both structures are subject to dopaminergic neuromodulation in a way that exerts a critical influence on the proper operation of working memory. We present a novel network model to elucidate the role of phasic dopamine in the interaction of these two structures in initiating(More)
Plasticity is a crucial component of normal brain function and a critical mechanism for recovery from injury. In vitro, associative pairing of presynaptic spiking and stimulus-induced postsynaptic depolarization causes changes in the synaptic efficacy of the presynaptic neuron, when activated by extrinsic stimulation. In vivo, such paradigms can alter the(More)
Abst ract. Since an tiquity, man has dreamed of building a de vice that would "learn from examples" 1 "form ge neralizations", and "dis-cover t he rules" behin d patt ern s in t he data. Recent work has shown t hat a high ly connect ed , layered net wor k of simple an alog pr o cessing element s can be astonishingly successful at this, in some cases. In ord(More)
Movement representation by the motor cortex (M1) has been a theoretical interest for many years, but in the past several years it has become a more practical question, with the advent of the brain-machine interface. An increasing number of groups have demonstrated the ability to predict a variety of kinematic signals on the basis of M1 recordings and to use(More)