Sensory feedback-dependent coding of arm position in local field potentials of the posterior parietal cortex.

Although multisensory integration is crucial for sensorimotor function, it is unclear how visual and proprioceptive sensory cues are combined in the brain during motor behaviors. Here we characterized the effects of multisensory interactions on local field potential (LFP) activity obtained from the superior parietal lobule (SPL) as non-human primates performed a reaching task with either unimodal (proprioceptive) or bimodal (visual-proprioceptive) sensory feedback. Based on previous analyses of spiking activity, we hypothesized that evoked LFP responses would be tuned to arm location but would be suppressed on bimodal trials, relative to unimodal trials.

Multisensory Interactions Influence Neuronal Spike Train Dynamics in the Posterior Parietal Cortex.

Although significant progress has been made in understanding multisensory interactions at the behavioral level, their underlying neural mechanisms remain relatively poorly understood in cortical areas, particularly during the control of action. In recent experiments where animals reached to and actively maintained their arm position at multiple spatial locations while receiving either proprioceptive or visual-proprioceptive position feedback, multisensory interactions were shown to be associated with reduced spiking (i.e.

Efficiency of visual feedback integration differs between dominant and non-dominant arms during a reaching task.

Recent studies have shown that patterns of endpoint variability following double-step reach sequences reflect the influence of both planning and execution-related processes, but are strongly dominated by noise associated with the online updating of movement plans based on visual feedback. However, it is currently unclear whether these results reflect the dominant arm/hemisphere's postulated specialization for visual feedback processing, or whether these effects reflect a more general "arm/hemisphere independent" preference for visual feedback in the control of reaching. To explore this, twelve subjects performed double-step reach sequences with their dominant and non-dominant arms to targets in 3D space with and without visual feedback of the arm.

Estimating endogenous changes in task performance from EEG.

Brain wave activity is known to correlate with decrements in behavioral performance as individuals enter states of fatigue, boredom, or low alertness.Many BCI technologies are adversely affected by these changes in user state, limiting their application and constraining their use to relatively short temporal epochs where behavioral performance is likely to be stable. Incorporating a passive BCI that detects when the user is performing poorly at a primary task, and adapts accordingly may prove to increase overall user performance.

Multimodal representation of limb endpoint position in the posterior parietal cortex.

Understanding the neural representation of limb position is important for comprehending the control of limb movements and the maintenance of body schema, as well as for the development of neuroprosthetic systems designed to replace lost limb function. Multiple subcortical and cortical areas contribute to this representation, but its multimodal basis has largely been ignored. Regarding the parietal cortex, previous results suggest that visual information about arm position is not strongly represented in area 5, although these results were obtained under conditions in which animals were not using their arms to interact with objects in their environment, which could have affected the relative weighting of relevant sensory signals.

Contribution of execution noise to arm movement variability in three-dimensional space.

Reaching movements are subject to noise associated with planning and execution, but precisely how these noise sources interact to determine patterns of endpoint variability in three-dimensional space is not well understood. For frontal plane movements, variability is largest along the depth axis (the axis along which visual planning noise is greatest), with execution noise contributing to this variability along the movement direction. Here we tested whether these noise sources interact in a similar way for movements directed in depth.

Interacting noise sources shape patterns of arm movement variability in three-dimensional space.

Reaching movements are subject to noise in both the planning and execution phases of movement production. The interaction of these noise sources during natural movements is not well understood, despite its importance for understanding movement variability in neurologically intact and impaired individuals. Here we examined the interaction of planning and execution related noise during the production of unconstrained reaching movements.

Comparing the performance of three generations of ActiGraph accelerometers.

ActiGraph accelerometers are a useful tool for objective assessment of physical activity in clinical and epidemiological studies. Several generations of ActiGraph are being used; however, little work has been done to verify that measurements are consistent across generations. This study employed mechanical oscillations to characterize the dynamic response and intermonitor variability of three generations of ActiGraph monitors, from the oldest 7164 (n = 13), 71256 (n = 12), to the newest GT1M (n = 12).