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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.