How the human brain controls hand movements to carry out different tasks is still debated. The concept of synergy has been proposed to indicate functional modules that may simplify the control of hand postures by simultaneously recruiting sets of muscles and joints. However, whether and to what extent synergic hand postures are encoded as such at a cortical level remains unknown. Here, we combined kinematic, electromyography, and brain activity measures obtained by functional magnetic resonance imaging while subjects performed a variety of movements towards virtual objects. Hand postural information, encoded through kinematic synergies, were represented in cortical areas devoted to hand motor control and successfully discriminated individual grasping movements, significantly outperforming alternative somatotopic or muscle-based models. Importantly, hand postural synergies were predicted by neural activation patterns within primary motor cortex. These findings support a novel cortical organization for hand movement control and open potential applications for brain-computer interfaces and neuroprostheses.
Humans use emotions to decipher complex cascades of internal events. However, which mechanisms link descriptions of affective states to brain activity is unclear, with evidence supporting either local or distributed processing. A biologically favorable alternative is provided by the notion of gradient, which postulates the isomorphism between functional representations of stimulus features and cortical distance. Here, we use fMRI activity evoked by an emotionally charged movie and continuous ratings of the perceived emotion intensity to reveal the topographic organization of affective states. Results show that three orthogonal and spatially overlapping gradients encode the polarity, complexity and intensity of emotional experiences in right temporo-parietal territories. The spatial arrangement of these gradients allows the brain to map a variety of affective states within a single patch of cortex. As this organization resembles how sensory regions represent psychophysical properties (e.g., retinotopy), we propose emotionotopy as a principle of emotion coding.
How conceptual knowledge is represented in the human brain remains to be determined. To address the differential role of low-level sensory-based and high-level abstract features in semantic processing, we combined behavioral studies of linguistic production and brain activity measures by functional magnetic resonance imaging in sighted and congenitally blind individuals while they performed a property-generation task with concrete nouns from eight categories, presented through visual and/or auditory modalities. Patterns of neural activity within a large semantic cortical network that comprised parahippocampal, lateral occipital, temporo-parieto-occipital and inferior parietal cortices correlated with linguistic production and were independent both from the modality of stimulus presentation (either visual or auditory) and the (lack of) visual experience. In contrast, selected modality-dependent differences were observed only when the analysis was limited to the individual regions within the semantic cortical network. We conclude that conceptual knowledge in the human brain relies on a distributed, modality-independent cortical representation that integrates the partial category and modality specific information retained at a regional level.