Description This internationally authored volume presents major findings, concepts, and methods of behavioral neuroscience coordinated with their
simulation via neural networks. A central theme is that biobehaviorally constrained simulations provide a rigorous means to explore the
implications of relatively simple processes for the understanding of cognition (complex behavior). Neural networks are held to serve
the same function for behavioral neuroscience as population genetics for evolutionary science. The volume is divided into six sections,
each of which includes both experimental and simulation research: (1) neurodevelopment and genetic algorithms, (2) synaptic plasticity
(LTP), (3) sensory/hippocampal systems, (4) motor systems, (5) plasticity in large neural systems (reinforcement learning), and (6) neural
imaging and language. The volume also includes an integrated reference section and a comprehensive index.
Contents Permissions. List of Contents. List of Contributors. The necessity of neural networks (J.W. Donahoe).
Neural Development .
Mammalian forebrain development: how cells find a permanent home and establish their identity (M.B. Luskin). Development and plasticity
of neocortical processing architectures (W. Singer). A statistical framework for presenting developmental neuroanatomy (S. L Senft).
Evolving aritifial neural networks in Pavlovian environments (J.E. Burgos).
Neural Plasticity . Principles of neurotransmission
and implications for network modeling (J.S. Meyer). Cellular mechanisms of long-term potentiation: late maintenance (U. Frey). Temporal
information processing: a computational role for paired-pulse facilitation and slow inhibition (D.V. Buonomano, M.M. Merzenich).
Perceiving .
Inferotemporal cortex and object recognition (K. Tanaka). Sparse coding of faces in a neuronal model: interpreting cell population response
in object recognition (A. Trehub). Structure and binding in object perception (J.E. Hummel). A neural-network approach to adaptive similarity
and stimulus representations in cortico-hippocampal function (M.A. Gluck, C.E. Myers).
Behaving . Motor cortex: neural
and computational studies (A.P. Georgopoulos). Selectionist constraints on neural networks (D.C. Palmer). Analysis of reaching for stationary
and moving objects in the human infant (N.E. Berthier). Reinforcement learning or complex behavior through shaping (V. Gullapalli).
Reinforcement
Learning . Adaptive dopaminergic nuerons report the appetitive value of environmental stimuli (W. Schultz). Selection networks
(J.W. Donahoe). Reinforcement learning in articial intelligence (A.G. Barto, R.S. Sutton). The T-D model of classical conditioning: reponse
topography and brain implementation (J.W. Moore, J-S Choi). Biological substrates of predictive mechanisms in learning and action choice
(P. Read Montague). The role of training in reinforcement learning (J.A. Clouse).
Complex Behavior . Functional brain
imaging and verbal behavior (M.E. Raichle). Neural modelling of learning in verbal response tasks (V. Gullapalli, J.J. Gelfand). Serial
order: a parallel distributed processing approach (M.I. Jordan). Connectionist models of arbitrarily applicable relational responding:
a possible role for the hippocampal system (D. Barnes, P.J. Hampson). A recurrent-network account of reading, spelling, and dyslexia
(G.C. Van Orden et al.). References. Index.
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