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Attending to a stimulus is known to enhance the neural responses to that stimulus. Recent experiments on visual attention have shown that this modulation can have object-based characteristics, such that, when certain parts of a visual object are attended, other parts automatically also receive enhanced processing. Here, we investigated whether visual attention can modulate neural responses to other components of a multisensory object defined by synchronous, but spatially disparate, auditory and visual stimuli. The audiovisual integration of such multisensory stimuli typically leads to mislocalization of the sound toward the visual stimulus (ventriloquism illusion). Using event-related potentials and functional MRI, we found that the brain's response to task-irrelevant sounds occurring synchronously with a visual stimulus from a different location was larger when that accompanying visual stimulus was attended versus unattended. The event-related potential effect consisted of sustained, frontally distributed, brain activity that emerged relatively late in processing, an effect resembling attention-related enhancements seen at earlier latencies during intramodal auditory attention. Moreover, the functional MRI data confirmed that the effect included specific enhancement of activity in auditory cortex. These findings indicate that attention to one sensory modality can spread to encompass simultaneous signals from another modality, even when they are task-irrelevant and from a different location. This cross-modal attentional spread appears to reflect an object-based, late selection process wherein spatially discrepant auditory stimulation is grouped with synchronous attended visual input into a multisensory object, resulting in the auditory information being pulled into the attentional spotlight and bestowed with enhanced processing.

Reaching and grasping in primates depend on the coordination of neural activity in large frontoparietal ensembles. Here we demonstrate that primates can learn to reach and grasp virtual objects by controlling a robot arm through a closed-loop brain–machine interface (BMIc) that uses multiple mathematical models to extract several motor parameters (i.e., hand position, velocity, gripping force, and the EMGs of multiple arm muscles) from the electrical activity of frontoparietal neuronal ensembles. As single neurons typically contribute to the encoding of several motor parameters, we observed that high BMIc accuracy required recording from large neuronal ensembles. Continuous BMIc operation by monkeys led to significant improvements in both model predictions and behavioral performance. Using visual feedback, monkeys succeeded in producing robot reach-and-grasp movements even when their arms did not move. Learning to operate the BMIc was paralleled by functional reorganization in multiple cortical areas, suggesting that the dynamic properties of the BMIc were incorporated into motor and sensory cortical representations.

A paradigm is described for recording the activity of single cortical neurons from awake, behaving macaque monkeys. Its unique features include high-density microwire arrays and multichannel instrumentation. Three adult rhesus monkeys received microwire array implants, totaling 96–704 microwires per subject, in up to five cortical areas, sometimes bilaterally. Recordings 3–4 weeks after implantation yielded 421 single neurons with a mean peak-to-peak voltage of 115 ± 3 μV and a signal-to-noise ratio of better than 5:1. As many as 247 cortical neurons were recorded in one session, and at least 58 neurons were isolated from one subject 18 months after implantation. This method should benefit neurophysiological investigation of learning, perception, and sensorimotor integration in primates and the development of neuroprosthetic devices.

Crucial for the perception of form are the spatial relationships between the elements of a visual stimulus. To investigate the mechanisms involved in coding the distance between visual stimuli, thresholds for detecting whether a central marker accurately bisects a spatial interval were compared for a variety of configurations. Thresholds are best when all three members of the bisection configuration are identical. Performance is impaired, often by as much as a factor of two, when the outer delimiters of the spatial interval differ from the central marker in either length, orientation or contrast polarity. Illusory contours act poorly as borders for bisection by a central line. Disparity thresholds are not affected by orientation differences between test and flanking lines. Because in peripheral vision bisection acuity improves with practice, transfer of training between configurations can be used to gauge overlap of neural processing mechanisms. Transfer is complete only between patterns where all markers are similar, reduced when the outer markers differ by 20° in orientation and absent when they are orthogonal. The dependence of bisection discrimination on similarity between the elements of the stimulus demonstrates that the encoding of spatial location and spatial extent are coupled to the coding of other stimulus properties

Crist, Roy E., Mitesh K. Kapadia, Gerald Westheimer, and Charles D. Gilbert. Perceptual learning of spatial localization: specificity for orientation, position, and context. J. Neurophysiol. 78: 2889–2894, 1997. Discrimination of simple visual attributes can improve significantly with practice. We have trained human observers to perform peripherally presented tasks involving the localization of short line segments and examined the specificity of the learning for the visual location, orientation, and geometric arrangement of the trained stimulus. Several weeks of training resulted in dramatic threshold reductions. The learning was specific for the orientation and location of the trained stimulus, indicating the involvement of the earliest cortical stages in the visual pathway where the orientation and location of stimuli are mapped with highest resolution. Furthermore, improvement was also specific for both the configuration of the trained stimulus and the attribute of the stimulus that was under scrutiny during training. This degree of specificity suggests that the learning cannot be achieved by cortical recruitment alone, as proposed in current models, but is likely to involve a refinement of lateral interactions within the cortex and possibly a gating of lower level changes by attentional mechanisms.

Perceptual learning is a lifelong process. We begin by encoding information about the basic structure of the natural world and continue to assimilate information about specific patterns with which we become familiar. The specificity of the learning suggests that all areas of the cerebral cortex are plastic and can represent various aspects of learned information. The neural substrate of perceptual learning relates to the nature of the neural code itself, including changes in cortical maps, in the temporal characteristics of neuronal responses, and in modulation of contextual influences. Top-down control of these representations suggests that learning involves an interaction between multiple cortical areas.