de Lussanet, M. H. E. | bioRxiv Science

bioRxiv2021

Multimodal sensorimotor integration of visual and kinaesthetic afferents modulates motor circuits in humans

Optimal motor control requires the effective integration of multi-modal information. Visual information of movement performed by others even enhances potentials in the upper motor neurons, through the mirror-neuron system. On the other hand, it is known that motor control is intimately associated with afferent proprioceptive information. Kinaesthetic information is also generated by passive, external-driven movements. In the context of sensory integration, its an important question, how such passive kinaesthetic information and visually perceived movements are integrated. We studied the effects of visual and kinaesthetic information in combination, as well as isolated, on sensorimotor-integration - compared to a control condition. For this, we measured the change in the excitability of motor cortex (M1) using low-intensity TMS. We hypothesised that both visual motoneurons and kinaesthetic motoneurons could enhance the excitability of motor responses. We found that passive wrist movements increase the motor excitability, suggesting that kinaesthetic motoneurons do exist. The kinaesthetic influence on the motor threshold was even stronger than the visual information. Moreover, the simultaneous visual and passive kinaesthetic information increased the cortical excitability more than each of them independently. Thus, for the first time, we found evidence for the integration of passive kinaesthetic- and visual-sensory stimuli.

neuroscience↗

bioRxiv2020

A model of uniform cortical composition predicts the scaling laws of the mammalian cerebrum

The size of the mammalian cerebrum spans more than 5 orders of magnitude. The smallest cerebrums have a smooth (lissencephalic) cortical surface, which gets increasingly folded (gyrencephalic) with cerebral size. Further, the proportion of white-to-gray matter volume increases with the total volume. These scaling relations have unusually little variation. Even though a number of theories and models have been proposed, it remains an open question, why this is so. Here, we show that almost all variance is explained by assuming a homogeneous composition of the cortex across mammals. On the basis of this assumption we derive quantitative analytical computational models. The first model predicts the cortical surface area from the gray and white matter volume. A single free parameter, for the height of cortical columns is estimated as{lambda} = 2.9 mm (r2 = 0.996). The second model predicts the white matter volume as a function of the gray volume and the cerebral size (with parameters for intra- and extra-gyral connections lint, lext; [Formula]). The models are validated by predicting the effective cortical thickness and the folding parameter{kappa} . The results accurately predict the human intraspecific variation of the surface relations. As expected, we find a reduced{lambda} for cetaceans, and that preterm human infants do not follow the model. We also find deviations of gray and white matter volume for large cerebrums. Overall, the models thus show how the regular architecture of the cortex shapes the cerebrum. We conclude that the mammalian cerebrum scales in an isomorphic, rather than isometric, manner.

neuroscience↗