Visual and somatosensory information contribute to distortions of the body model

Abstract

Distorted representations of the body are observed in healthy individuals as well as in neurological and psychiatric disorders. Distortions of the body model have been attributed to the somatotopic cerebral representation. Recently, it has been demonstrated that visual biases also contribute to those distortions. To better understand the sources of such distortions, we compared the metric representations across five body parts affording different degrees of tactile sensitivity and visual accessibility. We evaluated their perceived dimensions using a Line Length Judgment task. We found that most body parts were underestimated in their dimensions. The estimation error relative to their length was predicted by their tactile acuity, supporting the influence of the cortical somatotopy on the body model. However, tactile acuity did not explain the distortions observed for the width. Visual accessibility in turn does appear to mediate body distortions, as we observed that the dimensions of the dorsal portion of the neck were the only ones accurately perceived. Coherent with the multisensory nature of body representations, we argue that the perceived dimensions of body parts are estimated by integrating visual and somatosensory information, each weighted differently, based on their availability for a given body part and a given spatial dimension.

Proprioceptive errors in the localization of hand landmarks: What can be learnt about the hand metric representation?

“…However, a smaller albeit significant underestimation of the perceived finger length has been reported in visual-based body representation tasks as well, which did not involve proprioceptive localization. For instance, in a recent study [ 44 ] we asked participants to compare the perceived dimensions of their unseen hand with the perceived length of line segments presented on a computer screen, using a two-alternative forced choice task. The finger length was underestimated on average, suggesting that the finger length underestimation observed in the LT does not uniquely reflect a domain-general spatial bias, such as the prototype bias.…”

“…Concretely, participants misplaced the fingertips towards the center of the categorical space, which in this case could be the hand, or the finger itself. Second, in the condition of poor proprioceptive signal, participants may have relied on an underestimated representation of their finger length, which has been described in visual-based body representation tasks as well [ 44 ]. Further studies need to explore the weight of domain-general and body-specific sources of information affecting the fingertip misplacement.…”

“…The spatial preprocessing and statistical analyses were performed in MATLAB [34]. The MATLAB code for data preprocessing and visualization is freely accessible (Peviani, 2019).…”

The self-perceived body size in obesity: Evidence from the implicit representation of the hand

“…Later studies showed that the dimensions of body parts with higher tactile acuity are perceived more accurately than those with lower tactile acuity when participants explicitly estimate the body size relative to either other body parts or objects (Linkenauger et al, 2015; Sadibolova et al, 2019). Also, Peviani and colleagues (2019) found that, when participants estimate the dimensions of the hand relative to visually presented lines, body parts with lower tactile acuity were perceived longer (i.e., underestimated less) than body parts with higher tactile acuity. Furthermore, temporary alterations of tactile sensitivity induced by local anaesthesia determined body size overestimation (Proske & Gandevia, 2012).…”

Inferring the Evolutionary History of Your Favorite Protein: A Guide for Molecular Biologists

“…In collaboration with molecular biologists, we studied diverse eukaryotic proteins, varying from chromatin remodelers and bZIP transcription factors to flagellum and kinetochore components. [2,[33][34][35] We experienced that for nonbioinformaticians various challenges arise regarding the use of tools, the knowledge of genome evolution and of the species tree, and, importantly, how complicated evolutionary histories are reflected in a myriad of computational tools and sequence databases. Such challenges may cause flawed evolutionary inferences, which in turn may cause incorrect, or incomplete, function prediction.…”