Peer Support for Caregivers of People Living with Posterior Cortical Atrophy in Melbourne, Australia: A Feasibility Study.

Posterior Cortical Atrophy (PCA) is a rare form of young-onset dementia that causes early visuospatial and visuoperceptual deficits. The symptom profile of Posterior Cortical Atrophy leads to very specific care needs for those affected, who often rely on informal caregivers (including friends and family). Rare dementia support groups can be useful for both patients and their caregivers to assist with knowledge sharing, psychoeducation, and the provision of psychosocial support. Despite this, few such support groups exist. The purpose of this study was to examine a PCA support group for caregivers of individuals living with PCA. We held a structured psychoeducation support group comprised of four sessions with the aim being to provide education, strategies for the management of the disease, and peer support. Caregivers' mental health and quality of life were assessed. The results of our study showed that support group participation was a positive experience and assisted with increasing the knowledge of caregivers and fostering social connections. We suggest that peer support groups may be beneficial for both people living with PCA and their caregivers. We recommend that future quantitative and qualitative research is conducted to further assess health-promotion benefits to people living with PCA and their caregivers, and to assess their development and implementation in different contexts.

Oscillating latent dynamics in robot systems during walking and reaching.

Sensorimotor control of complex, dynamic systems such as humanoids or quadrupedal robots is notoriously difficult. While artificial systems traditionally employ hierarchical optimisation approaches or black-box policies, recent results in systems neuroscience suggest that complex behaviours such as locomotion and reaching are correlated with limit cycles in the primate motor cortex. A recent result suggests that, when applied to a learned latent space, oscillating patterns of activation can be used to control locomotion in a physical robot. While reminiscent of limit cycles observed in primate motor cortex, these dynamics are unsurprising given the cyclic nature of the robot's behaviour (walking). In this preliminary investigation, we consider how a similar approach extends to a less obviously cyclic behaviour (reaching). This has been explored in prior work using computational simulations. But simulations necessarily make simplifying assumptions that do not necessarily correspond to reality, so do not trivially transfer to real robot platforms. Our primary contribution is to demonstrate that we can infer and control real robot states in a learnt representation using oscillatory dynamics during reaching tasks. We further show that the learned latent representation encodes interpretable movements in the robot's workspace. Compared to robot locomotion, the dynamics that we observe for reaching are not fully cyclic, as they do not begin and end at the same position of latent space. However, they do begin to trace out the shape of a cycle, and, by construction, they are driven by the same underlying oscillatory mechanics.