@article {89, title = {Using Neuronal Latency to Determine Sensory{\textendash}Motor Processing Pathways in Reaction Time Tasks}, journal = {Journal of Neurophysiology}, volume = {93}, year = {2004}, month = {11/2004}, pages = {2974 - 2986}, abstract = {

We describe a new technique that uses the timing of neuronal and behavioral responses to explore the contributions of individual neurons to specific behaviors. The approach uses both the mean neuronal latency and the trial-by-trial covariance between neuronal latency and behavioral response. Reliable measurements of these values were obtained from single-unit recordings made from anterior inferotemporal (AIT) cortex and the frontal eye fields (FEF) in monkeys while they performed a choice reaction time task. These neurophysiological data show that the responses of AIT neurons and some FEF neurons have little covariance with behavioral response, consistent with a largely \"sensory\" response. The responses of another group of FEF neurons with longer mean latency covary tightly with behavioral response, consistent with a largely \"motor\" response. A very small fraction of FEF neurons had responses consistent with an intermediate position in the sensory-motor pathway. These results suggest that this technique is a valuable tool for exploring the functional organization of neuronal circuits that underlie specific behaviors.

}, keywords = {Action Potentials, Afferent, Animal, Animals, Behavior, Macaca mulatta, Male, Models, Motor Neurons, Neural Pathways, Neurological, Neurons, Photic Stimulation, Psychomotor Performance, Reaction Time, Task Performance and Analysis, Temporal Lobe, Time Factors, Visual Fields}, issn = {0022-3077}, doi = {10.1152/jn.00508.2004}, url = {https://www.physiology.org/doi/10.1152/jn.00508.2004}, author = {DiCarlo, James J. and Maunsell, John H. R.} } @article {119, title = {Stimulus configuration, classical conditioning, and hippocampal function.}, journal = {Psychological Review}, volume = {99}, year = {1992}, month = {04/1992}, pages = {268 - 305}, abstract = {

Hippocampal participation in classical conditioning is described in terms of a multilayer network that portrays stimulus configuration. The network (a) describes behavior in real time, (b) incorporates a layer of \"hidden\" units positioned between input and output units, (c) includes inputs that are connected to the output directly as well as indirectly through the hidden-unit layer, and (d) uses a biologically plausible backpropagation procedure to train the hidden-unit layer. Nodes and connections in the neural network are mapped onto regional cerebellar, cortical, and hippocampal circuits, and the effect of lesions of different brain regions is formally studied. Computer simulations of the following classical conditioning paradigms are presented: acquisition of delay and trace conditioning, extinction, acquisition-extinction series of delay conditioning, blocking, over-shadowing, discrimination acquisition, discrimination reversal, feature-positive discrimination, conditioned inhibition, negative patterning, positive patterning, and generalization. The model correctly describes the effect of hippocampal and cortical lesions in many of these paradigms, as well as neural activity in hippocampus and medial septum during classical conditioning. Some of these results might be extended to the description of anterograde amnesia in human patients.

}, keywords = {Animals, Association Learning, Brain Mapping, Cerebellum, Cerebral Cortex, Classical, Computer Simulation, Conditioning, Hippocampus, Humans, Models, Neural Pathways, Neurological}, issn = {0033-295X}, doi = {10.1037/0033-295X.99.2.268}, url = {http://doi.apa.org/getdoi.cfm?doi=10.1037/0033-295X.99.2.268}, author = {Schmajuk, Nestor A. and DiCarlo, James J.} } @article {122, title = {A neural network approach to hippocampal function in classical conditioning.}, journal = {Behavioral Neuroscience}, volume = {105}, year = {1991}, month = {01/1991}, pages = {82 - 110}, abstract = {

Hippocampal participation in classical conditioning in terms of S. Grossberg\&$\#$39;s (1975) attentional theory is described. According to the theory, pairing of a conditioned stimulus/stimuli (CS) with an unconditioned stimulus/stimuli (UCS) causes both an association of the sensory representation of the CS with the UCS (conditioned reinforcement learning) and an association of the sensory representation of the CS with the drive representation of the UCS (incentive motivation learning). Sensory representations compete for a limited-capacity short-term memory (STM). The STM regulation hypothesis, which proposes that the hippocampus controls incentive motivation, self-excitation, and competition among sensory representations thereby regulating the contents of a limited capacity STM, is introduced. Under the STM regulation hypothesis, nodes and connections in Grossberg\&$\#$39;s neural network are mapped onto regional hippocampal-cerebellar circuits. The resulting neural model provides (a) a framework for understanding the dynamics of information processing and storage in the hippocampus and cerebellum during classical conditioning of the rabbit\&$\#$39;s nictitating membrane, (b) principles for understanding the effect of different hippocampal manipulations on classical conditioning, and (c) novel and testable predictions.\ 

}, keywords = {Animals, Cerebellum, Classical, Computer Simulation, Conditioning, Extinction, Eyelid, Hippocampus, Models, Nerve Net, Neurological, Neurons, Psychological, Rabbits, Reaction Time}, issn = {0735-7044}, doi = {10.1037/0735-7044.105.1.82}, url = {http://doi.apa.org/getdoi.cfm?doi=10.1037/0735-7044.105.1.82}, author = {Schmajuk, Nestor A. and DiCarlo, James J.} }