1,721,635 research outputs found
Modeling a neurological disorder as the result of an operator acting on the brain: A first sketch based on network channel modeling
No full textThe brain is a complex network, and diseases can alter its structures and connections between regions. Therefore, we can try to formalize the action of diseases by using operators acting on the brain network. Here, we propose a conceptual model of the brain, seen as a multilayer network, whose intra-lobe interactions are formalized as the diagonal blocks of an adjacency matrix. We propose a general and abstract definition of disease as an operator altering the weights of the connections between neural agglomerates, that is, the elements of the brain matrix. As models, we consider examples from three neurological disorders: epilepsy, Alzheimer-Perusini’s disease, and schizophrenia. The alteration of neural connections can be seen as alterations of communication pathways, and thus, they can be described with a new channel model
Multi-Layer Networks and Routing Protocols for Aquatic Robotic Swarm Management
No full textThe paradigm of multi-layer networks can help devise a set of robotic swarms interacting with mobile computing centrals. We present here a distributed hierarchical network model and a related routing protocol (based on static routing and/or AODV protocol for peer nodes) for swarm robotics in aquatic environment, defining also which packets need to be exchanged to guarantee the mission accomplishment. Joining concepts and techniques from different disciplines allows us building a robust system with potential practical applications in scenarios such as environmental care. We discuss our results and further developments of the proposed approach
Sketching a Space of Brain States
No full textBrain functional connectivity alterations, that is, pathological changes in the signal exchange between areas of the brain, are occurring in several neurological diseases, including neurodegenerative and neuropsychiatric ones. They consist in changes in how brain functional networks work. By conceptualising a brain space as a space whose points are connectome configurations representing brain functional states, changes in brain network functionality can be represented by paths between these points. Paths from a healthy state to a diseased one, or between diseased states as instances of disease progression, are modelled as the action of the Krankheit-Operator, that produces changes from a brain functional state to another one. This study proposes a formal representation of the space of brain states and presents its computational definition. Moreover, references to patients affected by Parkinson’s disease, schizophrenia, and Alzheimer-Perusini’s disease are included for discussing the proposed approach and possible developments of the research toward a generalisation
A brain-network operator for modeling disease: a first data-based application for Parkinson’s disease
No full textThe complexity of our brains can be described as a multi-layer network: neurons, neural agglomerates, and lobes. Neurological diseases are often related to malfunctions in this network. We propose a conceptual model of the brain, describing the disease as the result of an operator affecting and disrupting the network organization. We adopt the formalism of operators, matrices, and tensor products adapted from theoretical physics. This novel approach can be tested and instantiated for different diseases, balancing mathematical formalism and data-driven findings, including pathologies where aging is included as a risk factor. We quantitatively model the K-operator from real data of Parkinson’s Disease, from the Parkinson’s Progression Markers Initiative (PPMI) upon concession by the University of Southern California. The networks are reconstructed from fMRI analysis, resulting in a matrix acting on the healthy brain and giving as output the diseased brain. We finally decompose the K-operator into the tensor product of its submatrices and we are able to assess its action on each region of interest (ROI) characterizing the brain for the specific considered samples. We also approximate the time-dependent K-operator from the fMRI of the same patient at the baseline and at the first follow-up. Our results confirm the findings of the literature on the topic. Also, these applications confirm the feasibility of the proposed analytic technique. Further research developments can compare operators for different patients and for different diseases, looking for commonalities and aiming to develop a comprehensive theoretical approach
Nonlinear time series analysis of dissolved oxygen in the Orbetello Lagoon
No full textIn this paper, a nonlinear time series analysis of data representing dissolved oxygen collected in the Lagoon of Orbetello (Grosseto, Italy) is performed. A first biological inspection of the data shows that the coastal area is highly eutrophic and subject to unexpected phenomena, like anoxic and distrophic crises. We use the recurrence plots and the recurrence quantification analysis to show that, even if the time series are short and strongly nonstationary, it is possible to characterize the oscillations of dissolved oxygen and the oxygen crises in terms of nonlinear dynamical systems
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
K-operator as a predictor for Alzheimer-Perusini's disease
No full textProgressive memory loss occurring in age-related neurological diseases contributes to the disgregation of the individual, with serious personal and social consequences. We model the brain network damage provoked by a neurological disease through a physics-inspired mathematical operator, K. Acting on a diseased brain, K provides the disease time evolution. Focusing on Alzheimer-Perusini's disease (AD), we approximate the K-operator considering selected patients of the ADNI 2 dataset. We also propose K as a predictor for the disease progress over time and give its preliminary evaluation in the AD progression from the cognitive normal (CN) stage to AD through intermediate mild cognitive impairment (MCI) stages
Limbic and cerebellar effects in Alzheimer-Perusini's disease: A physics-inspired approach
No full textAlzheimer-Perusini's disease (AD) is a severe neurodegenerative pathology mostly characterized by memory loss, with aging as a significant risk factor. While normal aging involves non-pathological changes in the brain, pathological aging involves the formation of neuronal plaques, leading to neuronal death and the macroscopic shrinkage of major brain regions. Prodromic dopaminergic alterations also affect the limbic system. We adopt a physics-inspired mathematical operator, the Krankheit-Operator, denoted as K, to model brain network impairment caused by a neurological disorder. By acting on a pathological brain, K plays a role in modulating disease progression. The evaluation of the K-operator is conducted across different stages, from cognitive normal (CN) to Mild Cognitive Impairment (MCI) and AD. Furthermore, by adopting a machine learning-based approach, we also explore the potential use of the K-operator as a diagnostic tool for predicting AD progression by starting from rs-fMRI at the initial visit. Our findings are consistent with the literature on the effects of AD on the limbic system, subcortical areas, cerebellum, and temporal lobe
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
- …
