The generation of receptive-field structure in cat primary visual cortex

A dendritic mechanism for decoding traveling waves: principles and applications to motor cortex

Traveling waves of neuronal oscillations have been observed in many cortical regions, including the motor and sensory cortex. Such waves are often modulated in a task-dependent fashion although their precise functional role remains a matter of debate. Here we conjecture that the cortex can utilize the direction and wavelength of traveling waves to encode information. We present a novel neural mechanism by which such information may be decoded by the spatial arrangement of receptors within the dendritic receptor field. In particular, we show how the density distributions of excitatory and inhibitory receptors can combine to act as a spatial filter of wave patterns. The proposed dendritic mechanism ensures that the neuron selectively responds to specific wave patterns, thus constituting a neural basis of pattern decoding. We validate this proposal in the descending motor system, where we model the large receptor fields of the pyramidal tract neurons — the principle outputs of the motor cortex — decoding motor commands encoded in the direction of traveling wave patterns in motor cortex. We use an existing model of field oscillations in motor cortex to investigate how the topology of the pyramidal cell receptor field acts to tune the cells responses to specific oscillatory wave patterns, even when those patterns are highly degraded. The model replicates key findings of the descending motor system during simple motor tasks, including variable interspike intervals and weak corticospinal coherence. By additionally showing how the nature of the wave patterns can be controlled by modulating the topology of local intra-cortical connections, we hence propose a novel integrated neuronal model of encoding and decoding motor commands.

Physiological studies in humans and monkeys have revealed spatially organized waves of neuronal activity that propagate across the cortex during sensory or behavioral tasks. However the functional role of such waves remains elusive. In the present study, we use numerical simulation to investigate whether wave patterns may serve as a basis for neural coding in cortex. Specifically, we propose a theoretical dendritic mechanism which permits neurons to respond selectively to the morphological properties of waves. In this proposal, the arrangement of excitatory and inhibitory receptors within the dendritic receptor field constitutes a spatial filter of the incoming wave patterns. The proposed mechanism allows the neuron to discriminate waves based on wavelength and orientation, thereby providing a basis for neural decoding. We explore this concept in the context of the descending motor system where the pyramidal tract neurons of motor cortex monosynaptically innervate motor neurons in the spinal cord. Pyramidal tract neurons have broad dendritic fields which make them ideal candidates for spatial filters of waves in motor cortex. Our model demonstrates how wave patterns in motor cortex can be transformed into a descending motor drive which replicates some fundamental oscillatory properties of human motor physiology.

Auditory cortical receptive fields: stable entities with plastic abilities

To form a reliable, consistent, and accurate representation of the acoustic scene, a reasonable conjecture is that cortical neurons maintain stable receptive fields after an early period of developmental plasticity. However, recent studies suggest that cortical neurons can be modified throughout adulthood and may change their response properties quite rapidly to reflect changing behavioral salience of certain sensory features. Because claims of adaptive receptive field plasticity could be confounded by intrinsic, labile properties of receptive fields themselves, we sought to gauge spontaneous changes in the responses of auditory cortical neurons. In the present study, we examined changes in a series of spectrotemporal receptive fields (STRFs) gathered from single neurons in successive recordings obtained over time scales of 30-120 min in primary auditory cortex (A1) in the quiescent, awake ferret. We used a global analysis of STRF shape based on a large database of A1 receptive fields. By clustering this STRF space in a data-driven manner, STRF sequences could be classified as stable or labile. We found that >73% of A1 neurons exhibited stable receptive field attributes over these time scales. In addition, we found that the extent of intrinsic variation in STRFs during the quiescent state was insignificant compared with behaviorally induced STRF changes observed during performance of spectral auditory tasks. Our results confirm that task-related changes induced by attentional focus on specific acoustic features were indeed confined to behaviorally salient acoustic cues and could be convincingly attributed to learning-induced plasticity when compared with "spontaneous" receptive field variability.

Spatiotemporal structure of complex cell receptive fields and influence of GABAergic inhibition

Spatiotemporal receptive field (RF) profiles were mapped with reverse correlation technique for complex cells in the striate cortex of cat. The RFs were constituted with ON and OFF subfields that overlapped much extensively in space and also largely in time. The subfields had spatial width of 1.0-4.3 degrees and temporal duration of 33-139 ms, whereas late responses were absent in most cases. When microiontophoresis of gamma-aminobutyric acid type A (GABAA) antagonist bicuculline was performed on the cells, little change occurred in width and onset time of the subfields, but the duration was prolonged in a subset of cells. These results suggest that intracortical inhibition may contribute to improve the accuracy of visual signals encoded in neuronal activities, but is unlikely critical for determining the primary structure of complex cell RF.