Extracting common patterns of neural circuit computations in autism spectrum and pinning them as a cause of specific core traits of autism is the first step towards identifying cell- and circuit-level targets for effective clinical intervention. Studies in human subjects with autism have identified functional links and common anatomical substrates between core restricted behavioral repertoire, cognitive rigidity, and over-stability of visual percepts during visual rivalry. To be able to study these processes with single-cell precision and exhaustive neuronal population coverage, we developed the visual bi-stable perception task for mice. Our task is based on plaid patterns consisting of two transparent gratings drifting at an angle of 120 degrees relative to each other. This results in spontaneous reversals of the perception between local component motion (motion of the plaid perceived as two separate moving grating components) and integrated global pattern motion (motion of the plaid perceived as a fused moving texture). This robust paradigm does not depend on the explicit report of the mouse, as the direction of the optokinetic nystagmus (OKN, rapid eye movements driven by either pattern or component motion) is used to infer the dominant percept. Using this paradigm, we found that the rate of perceptual reversals between global and local motion interpretations of the stimulus is reduced in MECP2 duplication mouse model of autism. Moreover, the stability of local motion percepts is greatly increased in MECP2 duplication mice at the expense of global motion percepts. Thus, our model reproduces a subclass of core features in human autism (reduced rate of visual rivalry and atypical perception of visual motion). This further offers a well-controlled approach for dissecting neuronal circuits underlying these core features if combined with mesoscale 2-photon imaging and optogenetic manipulation of neuronal circuits.

The Arctic coastal environment is a very dynamic system and sensitive to any changes. In our research we demonstrate that nivation (snow patch activity) impacts the Arctic landscape especially in the coastal dynamic at the western part of Russian Arctic. During fieldwork, snowbanks were described and studied and their qualitative role in the development of coastal systems was revealed for Baydaratskaya Bay coast, the Kara Sea. On one side, the large snow cover protects the coastal slope from thermodenudation and thermoabrasion; on the other side, a thick layer of snow affects the ground temperature regime. During snow melting, snow patches contribute to the removal of material from the coastal slope. The quantitative effect of snow on the ground temperature regime was assessed according to numerical simulations. The critical snow thickness was determined based on a calculation. Critical snow thicknesses based on simulation and field data correlated well. The numerical simulation showed the talik formation under the snow patch. Talik size essentially depends on the freezing temperature of sediment (influenced by salinity). The changes of ground temperature regime might further generate thawing settlement of sediment under snow and contribute to beach topography, which might be a trigger for thermoabrasion.