Variability in non-invasive brain stimulation studies: reasons and results

Non-invasive brain stimulation techniques (NIBS), such as Theta Burst Stimulation (TBS), Paired Associative Stimulation (PAS) and transcranial Direct Current Stimulation (tDCS), are widely used to probe plasticity in the human motor cortex (M1). Although TBS, PAS and tDCS differ in terms of physiological mechanisms responsible for experimentally-induced cortical plasticity, they all share the ability to elicit long-term potentiation (LTP) and depression (LTD) in M1. However, NIBS techniques are all affected by relevant variability in intra- and inter-subject responses. A growing number of factors contributing to NIBS variability have been recently identified and reported. In this review, we have readdressed the issue of variability in human NIBS studies. We have first briefly discussed the physiological mechanisms responsible for TBS, PAS and tDCS-induced cortical plasticity. Then, we have provided statistical measures of intra- and inter-subject variability, as calculated in previous studies. Finally, we have reported in detail known sources of variability by categorizing them into physiological, technical and statistical factors. Improving knowledge about sources of variability could lead to relevant advances in designing new tailored NIBS protocols in physiological and pathological conditions

On quantum and relativistic mechanical analogues in mean field spin models

Conceptual analogies among statistical mechanics and classical (or quantum) mechanics often appeared in the literature. For classical two-body mean field models, an analogy develops into a proper identification between the free energy of Curie-Weiss type magnetic models and the Hamilton-Jacobi action for a one dimensional mechanical system. Similarly, the partition function plays the role of the wave function in quantum mechanics and satisfies the heat equation that plays, in this context, the role of the Schrodinger equation in quantum mechanics. We show that this identification can be remarkably extended to include a wide family of magnetic models classified by normal forms of suitable real algebraic dispersion curves. In all these cases, the model turns out to be completely solvable as the free energy as well as the order parameter are obtained as solutions of an integrable nonlinear PDE of Hamilton-Jacobi type. We observe that the mechanical analog of these models can be viewed as the relativistic analog of the Curie-Weiss model and this helps to clarify the connection between generalised self-averaging and in statistical thermodynamics and the semi-classical dynamics of viscous conservation laws.Comment: Dedicated to Sandro Graffi in honor of his seventieth birthda

La palabra Rafue como imaginario para una poética de los mitos uitotos

Rafue es entendido como palabra-acción y de sabiduría y es la base de cuanto existe en la cultura uitoto. En este estudio se explica la importancia que tiene rafue dentro de la comunidad y en la creación de su imaginario. También se ilustra del papel que cumple dentro de la mitología y su relevancia en la conformación de la simbología y de la estructura de los mitos, estableciendo una base para una poética de los mitos uitotos. Se explica la relación que existe entre esta poética y el imaginario, teniendo a rafue como base y elemento común. Adicional a esto, se establece un puente entre la cultura occidental y la uitoto, teniendo a la Palabra y a rafue como base de este. Esta relación se hace sobre todo en el plano del sistema de creencias uitotos y católico-cristianas.Rafue is understood as word of action and wisdom and is the basis of all of what's in the uitoto culture. In this study, the importance of rafue within the community and the creation of its imaginary are explained. It also illustrates the role within the mythology and its relevance in the constitution of the symbolism and structure of myths, establishing a basis for a poetics of uitoto myths. The relationship between this poetics and imaginary, having rafue as a base and common element is explained. Additional to this, a bridge is established between Western and uitoto cultures, taking Word and rafue as the basis of this. This relationship is mostly about uitoto and Christian beliefs.Profesional en Estudios LiterariosPregrad

Graphene on h-BN: to align or not to align?

The contact strength, adhesion and friction, between graphene and an incommensurate crystalline substrate such as {\it h}-BN depends on their relative alignment angle $\theta$. The well established Novaco-McTague (NM) theory predicts for a monolayer graphene on a hard bulk {\it h}-BN crystal face a small spontaneous misalignment, here $\theta_{NM}$\,$\simeq$\,0.45 degrees which if realized would be relevant to a host of electronic properties besides the mechanical ones. Because experimental equilibrium is hard to achieve, we inquire theoretically about alignment or misalignment by simulations based on dependable state-of-the-art interatomic force fields. Surprisingly at first, we find compelling evidence for $\theta = 0$, i.e., full energy-driven alignment in the equilibrium state of graphene on {\it h}-BN. Two factors drive this deviation from NM theory. First, graphene is not flat, developing on {\it h}-BN a long-wavelength out-of-plane corrugation. Second, {\it h}-BN is not hard, releasing its contact stress by planar contractions/expansions that accompany the interface moir\'e structure. Repeated simulations by artificially forcing graphene to keep flat, and {\it h}-BN to keep rigid, indeed yield an equilibrium misalignment similar to $\theta_{NM}$ as expected. Subsequent sliding simulations show that friction of graphene on {\it h}-BN, small and essentially independent of misalignments in the artificial frozen state, strongly increases in the more realistic corrugated, strain-modulated, aligned state

Meta-stable states in the hierarchical Dyson model drive parallel processing in the hierarchical Hopfield network

In this paper we introduce and investigate the statistical mechanics of hierarchical neural networks: First, we approach these systems \`a la Mattis, by thinking at the Dyson model as a single-pattern hierarchical neural network and we discuss the stability of different retrievable states as predicted by the related self-consistencies obtained from a mean-field bound and from a bound that bypasses the mean-field limitation. The latter is worked out by properly reabsorbing fluctuations of the magnetization related to higher levels of the hierarchy into effective fields for the lower levels. Remarkably, mixing Amit's ansatz technique (to select candidate retrievable states) with the interpolation procedure (to solve for the free energy of these states) we prove that (due to gauge symmetry) the Dyson model accomplishes both serial and parallel processing. One step forward, we extend this scenario toward multiple stored patterns by implementing the Hebb prescription for learning within the couplings. This results in an Hopfield-like networks constrained on a hierarchical topology, for which, restricting to the low storage regime (where the number of patterns grows at most logarithmical with the amount of neurons), we prove the existence of the thermodynamic limit for the free energy and we give an explicit expression of its mean field bound and of the related improved boun

Topological properties of hierarchical networks

Hierarchical networks are attracting a renewal interest for modelling the organization of a number of biological systems and for tackling the complexity of statistical mechanical models beyond mean-field limitations. Here we consider the Dyson hierarchical construction for ferromagnets, neural networks and spin-glasses, recently analyzed from a statistical-mechanics perspective, and we focus on the topological properties of the underlying structures. In particular, we find that such structures are weighted graphs that exhibit high degree of clustering and of modularity, with small spectral gap; the robustness of such features with respect to link removal is also studied. These outcomes are then discussed and related to the statistical mechanics scenario in full consistency. Lastly, we look at these weighted graphs as Markov chains and we show that in the limit of infinite size, the emergence of ergodicity breakdown for the stochastic process mirrors the emergence of meta-stabilities in the corresponding statistical mechanical analysis

Hierarchical neural networks perform both serial and parallel processing

In this work we study a Hebbian neural network, where neurons are arranged according to a hierarchical architecture such that their couplings scale with their reciprocal distance. As a full statistical mechanics solution is not yet available, after a streamlined introduction to the state of the art via that route, the problem is consistently approached through signal- to-noise technique and extensive numerical simulations. Focusing on the low-storage regime, where the amount of stored patterns grows at most logarithmical with the system size, we prove that these non-mean-field Hopfield-like networks display a richer phase diagram than their classical counterparts. In particular, these networks are able to perform serial processing (i.e. retrieve one pattern at a time through a complete rearrangement of the whole ensemble of neurons) as well as parallel processing (i.e. retrieve several patterns simultaneously, delegating the management of diff erent patterns to diverse communities that build network). The tune between the two regimes is given by the rate of the coupling decay and by the level of noise affecting the system. The price to pay for those remarkable capabilities lies in a network's capacity smaller than the mean field counterpart, thus yielding a new budget principle: the wider the multitasking capabilities, the lower the network load and viceversa. This may have important implications in our understanding of biological complexity

From Dyson to Hopfield: Processing on hierarchical networks

We consider statistical-mechanical models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling decay with spin distance can give rise to peculiar features and phase diagrams much richer that their mean-field counterpart. In particular, we consider the Dyson model, mimicking ferromagnetism in lattices, and we prove the existence of a number of meta-stabilities, beyond the ordered state, which get stable in the thermodynamic limit. Such a feature is retained when the hierarchical structure is coupled with the Hebb rule for learning, hence mimicking the modular architecture of neurons, and gives rise to an associative network able to perform both as a serial processor as well as a parallel processor, depending crucially on the external stimuli and on the rate of interaction decay with distance; however, those emergent multitasking features reduce the network capacity with respect to the mean-field counterpart. The analysis is accomplished through statistical mechanics, graph theory, signal-to-noise technique and numerical simulations in full consistency. Our results shed light on the biological complexity shown by real networks, and suggest future directions for understanding more realistic models

Preventive strategies in oral health for special needs patients

As regards to the most common oral disease in pediatric patients, intellectual disability is not a risk factor for caries disease itself, but it rather reduces the individual capability to self-care and therefore to his own oral care. Children suffering of systemic pathologies and/or with different stages of disability are to be considered at high risk for dental caries development. According to recent guidelines for oral health prevention in childhood, individual additional strategies for a preventive care should be applied for these patients. All the health providers, family and caregivers should be involved with the aim of being aware, motivated and informed on oral health issues, and a better access system to the dental care structure, both logistic, professional and economical should be assured