Towards the Modeling of Neuronal Firing by Gaussian Processes

This paper focuses on the outline of some computational methods for the approximate solution of the integral equations for the neuronal firing probability density and an algorithm for the generation of sample-paths in order to construct histograms estimating the firing densities. Our results originate from the study of non-Markov stationary Gaussian neuronal models with the aim to determine the neuron's firing probability density function. A parallel algorithm has been implemented in order to simulate large numbers of sample paths of Gaussian processes characterized by damped oscillatory covariances in the presence of time dependent boundaries. The analysis based on the simulation procedure provides an alternative research tool when closed-form results or analytic evaluation of the neuronal firing densities are not available.Comment: 10 pages, 3 figures, to be published in Scientiae Mathematicae Japonica

On Myosin II dynamics in the presence of external loads

We address the controversial hot question concerning the validity of the loose coupling versus the lever-arm theories in the actomyosin dynamics by re-interpreting and extending the phenomenological washboard potential model proposed by some of us in a previous paper. In this new model a Brownian motion harnessing thermal energy is assumed to co-exist with the deterministic swing of the lever-arm, to yield an excellent fit of the set of data obtained by some of us on the sliding of Myosin II heads on immobilized actin filaments under various load conditions. Our theoretical arguments are complemented by accurate numerical simulations, and the robustness of the model is tested via different choices of parameters and potential profiles.Comment: 6 figures, 8 tables, to appear on Biosystem

Fractional queues with catastrophes and their transient behaviour

Starting from the definition of fractional M/M/1 queue given in the reference by Cahoy et al. in 2015 and M/M/1 queue with catastrophes given in the reference by Di Crescenzo et al. in 2003, we define and study a fractional M/M/1 queue with catastrophes. In particular, we focus our attention on the transient behaviour, in which the time-change plays a key role. We first specify the conditions for the global uniqueness of solutions of the corresponding linear fractional differential problem. Then, we provide an alternative expression for the transient distribution of the fractional M/M/1 model, the state probabilities for the fractional queue with catastrophes, the distributions of the busy period for fractional queues without and with catastrophes and, finally, the distribution of the time of the first occurrence of a catastrophe

Regional Brain Morphometry Predicts Memory Rehabilitation Outcome after Traumatic Brain Injury

Cognitive deficits following traumatic brain injury (TBI) commonly include difficulties with memory, attention, and executive dysfunction. These deficits are amenable to cognitive rehabilitation, but optimally selecting rehabilitation programs for individual patients remains a challenge. Recent methods for quantifying regional brain morphometry allow for automated quantification of tissue volumes in numerous distinct brain structures. We hypothesized that such quantitative structural information could help identify individuals more or less likely to benefit from memory rehabilitation. Fifty individuals with TBI of all severities who reported having memory difficulties first underwent structural MRI scanning. They then participated in a 12 session memory rehabilitation program emphasizing internal memory strategies (I-MEMS). Primary outcome measures (HVLT, RBMT) were collected at the time of the MRI scan, immediately following therapy, and again at 1-month post-therapy. Regional brain volumes were used to predict outcome, adjusting for standard predictors (e.g., injury severity, age, education, pretest scores). We identified several brain regions that provided significant predictions of rehabilitation outcome, including the volume of the hippocampus, the lateral prefrontal cortex, the thalamus, and several subregions of the cingulate cortex. The prediction range of regional brain volumes were in some cases nearly equal in magnitude to prediction ranges provided by pretest scores on the outcome variable. We conclude that specific cerebral networks including these regions may contribute to learning during I-MEMS rehabilitation, and suggest that morphometric measures may provide substantial predictive value for rehabilitation outcome in other cognitive interventions as well

Calibration of tactile/force sensors for grasping with the PRISMA Hand II

The PRISMA Hand II is a mechanically robust anthropomorphic hand developed at PRISMA Lab, University of Naples Federico II. The hand is highly underactuated, three motors drive 19 joints via elastic tendons. Thanks to its particular mechanical design, the hand can perform not only adaptive grasps but also in-hand manipulation. Each fingertip integrates a tactile/force sensor, based on optoelectronic technology, to provide tactile/force feedback during grasping and manipulation, particularly useful with deformable objects. The paper briefly describes the mechanical design and sensor technology of the hand and proposes a calibration procedure for tactile/force sensors. A comparison between different models of Neural Networks architectures, suitable for sensors calibration, is shown. Experimental tests are provided to choose the optimal tactile sensing suite. Finally, experiments for the regulation of the forces are made to show the effectiveness of calibrated sensors