The Computational Brain

@article{Reeke1992TheCB,
  title={The Computational Brain},
  author={George N. Reeke and Patricia S. Churchland and Terrence J. Sejnowski},
  journal={Artif. Intell.},
  year={1992},
  volume={82},
  pages={381-391}
}

Brain Networks and Cognitive Architectures

Central Nervous System and Computation

TLDR
The emerging picture shows the brain as a very peculiar system, in which genuine computational features act in concert with noncomputational dynamical processes, leading to continuous self-organization and remodeling under the action of external stimuli from the environment and from the rest of the organism.

A neurocomputational approach to delusions.

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This chapter proposes a line of research that could help to uncover new principles of cortical function by uncovering the projective fields of tightly interacting neurons, which would complement the knowledge the authors now have of their receptive fields.

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This review discusses the utility of network neuroscience as a tool to build a quantitative framework in which to study human learning, which seeks to explain the full chain of events in the brain from sensory input to motor output, and lays out important remaining challenges in network neuroscience in explicitly bridging spatial scales at which neurophysiological processes occur.

Specializations of the granular prefrontal cortex of primates: implications for cognitive processing.

TLDR
It is demonstrated that the basic neuronal building block of the cerebral cortex, the pyramidal cell, is characterized by marked differences in structure among primate species, and comparison of the complexity of neuron structure with the size of the cortical area/region in which the cells are located revealed that trends in the granular prefrontal cortex (gPFC) were dramatically different to those in visual cortex.

Computational analysis of the role of the hippocampus in memory

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The authors draw together the results of a series of detailed computational studies and show how they are contributing to the development of a theory of hippocampal function by producing a computational theory of how it operates, based on neuroanatomical and neurophysiological information about the different neuronal systems contained within the hippocampus.

Bridging language with the rest of cognition: computational, algorithmic and neurobiological issues and methods

TLDR
This chapter discusses some of the general computational principles that emerge as useful for understanding cognition, focusing on those that are likely to be especially relevant in dealing with structured knowledge.
...

References

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Using a combined experimental-theoretical approach unique in neuroscience, the authors present important new techniques for the physiological reconstruction of a large biological neuronal network in the CA3 hippocampal region in vitro.

How Cortical Interconnectedness Varies with Network Size

TLDR
The conclusion will be that neocortical neurons are rather sparsely interconnected each neuron receives direct synaptic input from fewer than 3% of its neighbors underlying the surrounding square millimeter of cortex and the extent of connectedness hardly changes for brains that range in size over about four orders of magnitude.

Behaviorally based modeling and computational approaches to neuroscience.

TLDR
The theory of neuronal group selection provides a useful basis for further work by virtue of its consistency with basic evolutionary and physiological principles and the power of the selection paradigm to shape neural networks in behaviorally adaptive directions.

Connectionist modeling and brain function : the developing interface

TLDR
This book offers a solid tutorial on current research activity in connectionist-inspired biology-based modeling that describes specific experimental approaches and also confronts general issues related to learning associative memory, and sensorimotor development.

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    Annual review of neuroscience
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TLDR
The authors' knowledge of signals and connections in the oculomotor system is still at a stage where much more information is needed, but, thanks to recent advances in tracing nerve cell processes and recording from cells in alert animals, coupled with certain simplifying features of the eye movement, the question is perceived quite differently by people working at the many levels of the nervous system.

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TLDR
Computational maps enable several classes of neuronal mechanisms to sharpen tuning in a manner not possible for information that is represented in a non-topographic code.

A Simple Model of Prefrontal Cortex Function in Delayed-Response Tasks

TLDR
A simulation model is described that relates behavioral and electrophysiological-data relevant to these tasks into a minimal neural network that acquires systematic rules of behavior by mere reinforcement and rapidly adapts to changes in the reinforcement schedule.

Learning and Computational Neuroscience: Foundations of Adaptive Networks

"Learning and Computational Neuroscience" presents recent advances in understanding the brain processes underlying learning and memory, including neural systems analyses of dynamic circuit
...