The HeartLogic multisensor index and alert algorithm provides a sensitive and timely predictor of impending HF decompensation. (Evaluation of Multisensor Data in Heart Failure Patients With Implanted Devices [MultiSENSE]; NCT01128166).

Although the human hand has a complex structure with many individual degrees of freedom, joint movements are correlated. Studies involving simple tasks (grasping) or skilled tasks (typing or finger spelling) have shown that a small number of combined joint motions (i.e., synergies) can account for most of the variance in observed hand postures. However, those paradigms evoked a limited set of hand postures and as such the reported correlation patterns of joint motions may be task-specific. Here, we used an unconstrained haptic exploration task to evoke a set of hand postures that is representative of most naturalistic postures during object manipulation. Principal component analysis on this set revealed that the first seven principal components capture Ͼ90% of the observed variance in hand postures. Further, we identified nine eigenvectors (or synergies) that are remarkably similar across multiple subjects and across manipulations of different sets of objects within a subject. We then determined that these synergies are used broadly by showing that they account for the changes in hand postures during other tasks. These include hand motions such as reach and grasp of objects that vary in width, curvature and angle, and skilled motions such as precision pinch. Our results demonstrate that the synergies reported here generalize across tasks, and suggest that they represent basic building blocks underlying natural human hand motions.

The detailed functional organization of the macaque second somatosensory cortex (SII) is not well understood. Here we report the results of a study of the functional organization of the SII hand region that combines microelectrode mapping using hand-held stimuli with single-unit recordings using a motorized, computer-controlled tactile oriented bar. The data indicate that the SII hand region extends ϳ10 mm in the anteroposterior (AP) dimension, primarily within the upper bank of the lateral sulcus. Furthermore, we find evidence that this region consists of multiple functional fields, with a central field containing neurons that are driven well by cutaneous stimuli, flanked by an anterior field and a posterior field that each contain neurons that are driven well by proprioceptive stimuli and less well by cutaneous stimuli. The anterior field extends ϳ4 -5 mm AP, the central field extends ϳ3-4 mm, and the posterior field extends ϳ3 mm. Data from the motorized stimulator indicate that neurons in the central field are more responsive to oriented bars, more frequently exhibit orientation tuning, and have larger receptive fields than neurons in the anterior and posterior fields. We speculate that the three putative fields play different functional roles in tactile perception; the anterior and posterior fields process information that involves both proprioceptive and cutaneous input such as sensorimotor integration or stereognosis, whereas the central field processes primarily cutaneous information.

The classical view of somatosensory processing holds that proprioceptive and cutaneous inputs are conveyed to cortex through segregated channels, initially synapsing in modality-specific areas 3a (proprioception) and 3b (cutaneous) of primary somatosensory cortex (SI). These areas relay their signals to areas 1 and 2 where multimodal convergence first emerges. However, proprioceptive and cutaneous maps have traditionally been characterized using unreliable stimulation tools. Here, we employed a mechanical stimulator that reliably positioned animals' hands in different postures and presented tactile stimuli with superb precision. Single-unit recordings in SI revealed that most neurons responded to cutaneous and proprioceptive stimuli, including cells in areas 3a and 3b. Multimodal responses were characterized by linear and nonlinear effects that emerged during early (∼20ms) and latter (>100ms) stages of stimulus processing, respectively. These data are incompatible with the modality specificity model in SI, and provide evidence for distinct mechanisms of multimodal processing in the somatosensory system.