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Sheets, D. E.

Publications and source records attributed to Sheets, D. E..

2 recordsLinked to original sources

Progressive loss of independence in neuronal representations predicts cognitive decline

Intelligent behavior depends on the brains ability to represent multiple features of the environment simultaneously while keeping those representations independent1,2. Patients with Alzheimers disease often mix up objects, people, and events3-7, raising the possibility that disease mixes up the way that information is represented in the brain. Here we show that the independence of visual representations progressively breaks down during early stages of disease progression in a rhesus macaque model of Alzheimers disease and related dementias8-10. In visual area V4, representations of different visual features become progressively less independent, such that the representation of one feature is increasingly influenced by the value of another. We term this loss of independence neuronal feature confusion. This neuronal change predicts a specific behavioral consequence: because feature representations become less independent, preferences associated with one visual feature increasingly influence visually guided choices associated with other, independent features. Using an analogous image-selection task, we found the same behavioral signature in people with mild cognitive impairment, distinguishing them from age-matched controls. These results identify a specific and measurable alteration in neuronal population representations that predicts a behavioral change observed across species. More broadly, these findings demonstrate that neuronal population representations can guide the development of sensitive, non-invasive behavioral methods for early detection of functional changes associated with Alzheimers disease.

neuroscience↗

The integration of tactile and proprioceptive signals to achieve haptic object perception

AO_SCPLOWBSTRACTC_SCPLOWStereognosis, the sense of the 3-dimensional shape of objects held in hand, requires the integration of somatosensory signals about local features -such as edges and surface curvature- with proprioceptive signals about the conformation of the fingers on the object. However, the mechanism of this integration remains unknown. Here, we investigated the spatial model that is used to integrate information about the global shape of the object with information about its local features at each point of contact. To this end, human observers judged the dissimilarity of pairs of objects that differed in their global shape, their local features, or both. We then compared the dissimilarity ratings when both global shape and local features changed to ratings when only global shape or only local features changed. We tested this with object sets of different levels of complexity, including spheres of different sizes and surface features to more varied shapes and features. For all object sets, we found that ratings when both global shape and local features changed was approximately an additive combination of the ratings when only global shape or only local features changed. For the majority of subjects, a city-block spatial model best explained their responses. Our results suggest that information about global shape is encoded independently from that about local features during interactions with objects. This implies that the neural representations of object shape and local features, though integrated, are separable.

neuroscience↗