The forelimb representation in motor cortex (M1) is an important model system in contemporary neuroscience. Efforts to understand the organization of the M1 forelimb representation in monkeys have focused on inputs and outputs. In contrast, intrinsic M1 connections remain mostly unexplored, which is surprising given that intra-areal connections universally outnumber extrinsic connections. To address this knowledge gap, we first mapped the M1 forelimb representation with intracortical microstimulation (ICMS) in male squirrel monkeys. Next, we determined the connectivity of individual M1 sites with ICMS 1 intrinsic signal optical imaging (ISOI). Every stimulation site activated a distinctive pattern of patches (;0.25 to 1.0 mm radius) that we quantified in relation to the motor map. Arm sites activated patches that were mostly in arm zones. Hand sites followed the same principle, but to a lesser extent. The results collectively indicate that preferential connectivity between functionally matched patches is a prominent organizational principle in M1. Connectivity patterns for a given site were conserved across a range of current amplitudes, train durations, pulse frequencies, and microelectrode depths. In addition, we found close correspondence in somatosensory cortex between connectivity that we revealed with ICMS1ISOI and connections known from tracers. ICMS1ISOI is therefore an effective tool for mapping cortical connectivity and is particularly advantageous for sampling large numbers of sites. This feature was instrumental in revealing the spatial specificity of intrinsic M1 connections, which appear to be woven into the somatotopic organization of the forelimb representation. Such a framework invokes the modular organization well-established for sensory cortical areas.
Brain computer interface (BCI) control predominately uses visual feedback. Real arm movements, however, are controlled under a diversity of feedback mechanisms. The lack of additional BCI feedback modalities forces users to maintain visual contact while performing tasks. Such stringent requirements result in poor BCI control during tasks that inherently lack visual feedback, such as grasping, or when visual attention is diverted. Using a modified version of the Critical Tracking Task [1] which we call the Critical Stability Task (CST), we tested the ability of 9 human subjects to control an unstable system using either free arm movements or pinch force. The subjects were provided either visual feedback, ‘proportional’ vibrotactile feedback, or ‘on-off’ vibrotactile feedback about the state of the unstable system. We increased the difficulty of the control task by making the virtual system more unstable. We judged the effectiveness of a particular form of feedback as the maximal instability the system could reach before the subject lost control of it. We found three main results. First, subjects can use solely vibrotactile feedback to control an unstable system, although control was better using visual feedback. Second, ‘proportional’ vibrotactile feedback provided slightly better control than ‘on-off’ vibrotactile feedback. Third, there was large intra-subject variability in terms of the most effective input and feedback methods. This highlights the need to tailor the input and feedback methods to the subject when a high degree of control is desired. Our new task can provide a complement to traditional center-out paradigms to help boost the real-world relevance of BCI research in the lab.
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