@article {15, title = {Neural dynamics at successive stages of the ventral visual stream are consistent with hierarchical error signals.}, journal = {eLife}, volume = {7}, year = {2018}, month = {11/2018}, abstract = {

Ventral visual stream neural responses are dynamic, even for static image presentations. However, dynamical neural models of visual cortex are lacking as most progress has been made modeling static, time-averaged responses. Here, we studied population neural dynamics during face detection across three cortical processing stages. Remarkably,~30 milliseconds after the initially evoked response, we found that neurons in intermediate level areas decreased their responses to typical configurations of their preferred face parts relative to their response for atypical configurations even while neurons in higher areas achieved and maintained a preference for typical configurations. These hierarchical neural dynamics were inconsistent with standard feedforward circuits. Rather, recurrent models computing prediction errors between stages captured the observed temporal signatures. This model of neural dynamics, which simply augments the standard feedforward model of online vision, suggests that neural responses to static images may encode top-down prediction errors in addition to bottom-up feature estimates.

}, keywords = {Animals, Brain Mapping, Face, Humans, Macaca mulatta, Models, Neurological, Neurons, Pattern Recognition, Photic Stimulation, Reaction Time, Visual, Visual Cortex, Visual Perception}, issn = {2050-084X}, doi = {10.7554/eLife.42870}, url = {https://elifesciences.org/articles/42870https://cdn.elifesciences.org/articles/42870/elife-42870-v2.pdf}, author = {Issa, Elias B and Cadieu, Charles F and DiCarlo, James J} } @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 {103, title = {Spatial and Temporal Structure of Receptive Fields in Primate Somatosensory Area 3b: Effects of Stimulus Scanning Direction and Orientation}, journal = {The Journal of Neuroscience}, volume = {20}, year = {2000}, month = {01/2000}, pages = {495 - 510}, abstract = {

This is the third in a series of studies of the neural representation of tactile spatial form in somatosensory cortical area 3b of the alert monkey. We previously studied the spatial structure of \>350 fingerpad receptive fields (RFs) with random-dot patterns scanned in one direction (DiCarlo et al., 1998) and at varying velocities (DiCarlo and Johnson, 1999). Those studies showed that area 3b RFs have a wide range of spatial structures that are virtually unaffected by changes in scanning velocity. In this study, 62 area 3b neurons were studied with three to eight scanning directions (58 with four or more directions). The data from all three studies are described accurately by an RF model with three components: (1) a single, central excitatory region of short duration, (2) one or more inhibitory regions, also of short duration, that are adjacent to and nearly synchronous with the excitation, and (3) a region of inhibition that overlaps the excitation partially or totally and is temporally delayed with respect to the first two components. The mean correlation between the observed RFs and the RFs predicted by this three-component model was 0.81. The three-component RFs also predicted orientation sensitivity and preferred orientation to a scanned bar accurately. The orientation sensitivity was determined most strongly by the intensity of the coincident RF inhibition in relation to the excitation. Both orientation sensitivity and this ratio were stronger in the supragranular and infragranular layers than in layer IV.

}, keywords = {Action Potentials, Animals, Discrimination Learning, Fingers, Macaca mulatta, Movement, Normal Distribution, Reaction Time, Somatosensory Cortex, Space Perception, Time Factors, Touch}, issn = {0270-6474}, doi = {10.1523/JNEUROSCI.20-01-00495.2000}, url = {http://www.jneurosci.org/lookup/doi/10.1523/JNEUROSCI.20-01-00495.2000}, author = {DiCarlo, James J. and Johnson, Kenneth O.} } @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.} }