Cognitive reserve in dementia: Implications for cognitive training

open9noCognitive reserve (CR) is a potential mechanism to cope with brain damage. The aim of this study was to evaluate the effect of CR on a cognitive training (CT) in a group of patients with dementia. Eighty six participants with mild to moderate dementia were identified by their level of CR quantified by the CR Index questionnaire (CRIq) and underwent a cycle of CT. A global measure of cognition mini mental state examination (MMSE) was obtained before (T0) and after (T1) the training. Multiple linear regression analyses highlighted CR as a significant factor able to predict changes in cognitive performance after the CT. In particular, patients with lower CR benefited from a CT program more than those with high CR. These data show that CR can modulate the outcome of a CT program and that it should be considered as a predictive factor of neuropsychological rehabilitation training efficacy in people with dementia.openMondini, Sara; Madella, Ileana; Zangrossi, Andrea; Bigolin, Angela; Tomasi, Claudia; Michieletto, Marta; Villani, Daniele; Di Giovanni, Giuseppina; Mapelli, DanielaMondini, Sara; Madella, Ileana; Zangrossi, Andrea; Bigolin, Angela; Tomasi, Claudia; Michieletto, Marta; Villani, Daniele; Di Giovanni, Giuseppina; Mapelli, Daniel

Analysis of attractor distances in Random Boolean Networks

We study the properties of the distance between attractors in Random Boolean Networks, a prominent model of genetic regulatory networks. We define three distance measures, upon which attractor distance matrices are constructed and their main statistic parameters are computed. The experimental analysis shows that ordered networks have a very clustered set of attractors, while chaotic networks' attractors are scattered; critical networks show, instead, a pattern with characteristics of both ordered and chaotic networks.Comment: 9 pages, 6 figures. Presented at WIRN 2010 - Italian workshop on neural networks, May 2010. To appear in a volume published by IOS Pres

Polya-Szego inequality and Dirichlet pp-spectral gap for non-smooth spaces with Ricci curvature bounded below

We study decreasing rearrangements of functions defined on (possibly non-smooth) metric measure spaces with Ricci curvature bounded below by $K>0$ and dimension bounded above by $N\in (1,\infty)$ in a synthetic sense, the so called $CD(K,N)$ spaces. We first establish a Polya-Szego type inequality stating that the $W^{1,p}$-Sobolev norm decreases under such a rearrangement and apply the result to show sharp spectral gap for the $p$-Laplace operator with Dirichlet boundary conditions (on open subsets), for every $p\in (1,\infty)$. This extends to the non-smooth setting a classical result of B\'erard-Meyer and Matei; remarkable examples of spaces fitting out framework and for which the results seem new include: measured-Gromov Hausdorff limits of Riemannian manifolds with Ricci$\geq K>0$, finite dimensional Alexandrov spaces with curvature$\geq K>0$, Finsler manifolds with Ricci$\geq K>0$. In the second part of the paper we prove new rigidity and almost rigidity results attached to the aforementioned inequalities, in the framework of $RCD(K,N)$ spaces, which seem original even for smooth Riemannian manifolds with Ricci$\geq K>0$.Comment: 33 pages. Final version published in Journal de Math\'ematiques Pures et Appliqu\'ee

Sectional and intermediate Ricci curvature lower bounds via Optimal Transport

The goal of the paper is to give an optimal transport characterization of sectional curvature lower (and upper) bounds for smooth $n$-dimensional Riemannian manifolds. More generally we characterize, via optimal transport, lower bounds on the so called $p$-Ricci curvature which corresponds to taking the trace of the Riemann curvature tensor on $p$-dimensional planes, $1\leq p\leq n$. Such characterization roughly consists on a convexity condition of the $p$-Renyi entropy along $L^{2}$-Wasserstein geodesics, where the role of reference measure is played by the $p$-dimensional Hausdorff measure. As application we establish a new Brunn-Minkowski type inequality involving $p$-dimensional submanifolds and the $p$-dimensional Hausdorff measure.Comment: Final version, published by Advances in Mathematic

Editorial: Positive Technology: Designing E-experiences for Positive Change

While there is little doubt that our lives are becoming increasingly digital, whether this change is for the better or for the worse is far from being settled. Rather, over the past years concerns about the personal and social impacts of technologies have been growing, fueled by dystopian Orwellian scenarios that almost on daily basis are generously dispensed by major Western media outlets. According to a recent poll involving some 1,150 experts, 47% of respondents predict that individuals’ well-being will bemore helped than harmed by digital life in the next decade, while 32% say people’s well-being will bemore harmed than helped. Only 21% of those surveyed indicated that the impact of technologies on people well-being will be negligible compared to now (Pew Research Center, 2018)

New formulas for the Laplacian of distance functions and applications

The goal of the paper is to prove an exact representation formula for the Laplacian of the distance (and more generally for an arbitrary 1-Lipschitz function) in the framework of metric measure spaces satisfying Ricci curvature lower bounds in a synthetic sense (more precisely in essentially non-branching MCP(K,N)-spaces). Such a representation formula makes apparent the classical upper bounds and also some new lower bounds, together with a precise description of the singular part. The exact representation formula for the Laplacian of 1-Lipschitz functions (in particular for distance functions) holds also (and seems new) in a general complete Riemannian manifold. We apply these results to prove the equivalence of CD(K,N) and a dimensional Bochner inequality on signed distance functions. Moreover we obtain a measure-theoretic Splitting Theorem for infinitesimally Hilbertian essentially non-branching spaces verifying MCP(0,N).Comment: Final version to appear in Analysis and PD