93 research outputs found

    Jornadas Nacionales de InvestigaciĂłn en Ciberseguridad: actas de las VIII Jornadas Nacionales de InvestigaciĂłn en ciberseguridad: Vigo, 21 a 23 de junio de 2023

    Get PDF
    Jornadas Nacionales de InvestigaciĂłn en Ciberseguridad (8ÂȘ. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernizaciĂłn tecnolĂłxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida

    Contribution du cortex prémoteur à la locomotion entravée chez le chat

    Full text link
    La locomotion est une composante fondamentale de la vie animale : elle permet l’accĂšs continu aux ressources nĂ©cessaires Ă  la survie ainsi que l’évitement de pĂ©rils variĂ©s. Les milieux naturels comme anthropiques regorgent toutefois d’obstacles s’élevant contre notre progression. Pour l’humain et les autres mammifĂšres terrestres naviguant principalement par la vision, le franchissement efficace de ces obstacles repose critiquement sur la capacitĂ© de modifier proactivement le positionnement et la trajectoire des pas en fonction des informations visuelles extraites durant leur approche. Au niveau du systĂšme nerveux, cette capacitĂ© implique un processus complexe oĂč le traitement des signaux visuels reflĂ©tant les paramĂštres de l’obstacle spĂ©cifie un cours d’action sĂ©curisant son franchissement, lequel est ultimement exĂ©cutĂ© par des altĂ©rations prĂ©cises Ă  l’activitĂ© musculaire. Des Ă©tudes approfondies chez le chat, l’un des modĂšles animaux les plus dĂ©veloppĂ©s et investiguĂ©s vis-Ă -vis du contrĂŽle locomoteur, ont prĂ©sentement impliquĂ© deux structures corticales dans ce processus. Le cortex pariĂ©tal postĂ©rieur contribuerait ainsi Ă  dĂ©terminer la position relative de l’obstacle et le cortex moteur primaire serait central Ă  l’exĂ©cution des modifications de la dĂ©marche. Cependant, notre comprĂ©hension du substrat neural impliquĂ© dans la transformation sensorimotrice joignant ces deux Ă©tapes est extrĂȘmement limitĂ©e. Plusieurs lignes d’évidences, particuliĂšrement dĂ©rivĂ©es de travaux chez le primate investiguant le contrĂŽle des mouvements volontaires du bras, pointent cependant vers une contribution potentiellement majeure du cortex prĂ©moteur Ă  cette fonction. Cette thĂšse entreprend de dĂ©terminer directement la contribution prĂ©motrice aux modifications de la dĂ©marche. Deux Ă©tudes rapportent ainsi l’activitĂ© de neurones individuels enregistrĂ©s dans deux larges subdivisions du cortex prĂ©moteur, les aires 6iffu et 4delta, chez le chat Ă©veillĂ© accomplissant librement une tĂąche de nĂ©gociation d’obstacles sur tapis roulant. Ces Ă©tudes font Ă©tat de changements d’activitĂ© distincts d’une subdivision Ă  l’autre et corrĂ©lĂ©s Ă  des aspects spĂ©cifiques de la tĂąche, incluant des changements prĂ©paratoires liĂ©s Ă  l’approche finale de l’obstacle et d’autres liĂ©s Ă  une ou plusieurs Ă©tapes des ajustements locomoteurs sĂ©quentiels entourant sa nĂ©gociation. Une troisiĂšme Ă©tude investigue par microstimulation intracorticale la capacitĂ© des diffĂ©rentes subdivisions prĂ©motrices du chat Ă  modifier la dĂ©marche. Cette Ă©tude expose une variĂ©tĂ© de rĂ©ponses Ă©lectromyographiques complexes s’intĂ©grant en phase avec la marche, oĂč plusieurs subdivisions prĂ©sentent des signatures distinctes d’effets multi-membres contrastant avec l’influence focale du cortex moteur primaire. Chacune de ces trois Ă©tudes est finalement complĂ©mentĂ©e d’investigations par traçage rĂ©trograde de connexions anatomiques dĂ©cisives Ă  l’interprĂ©tation fonctionnelle des subdivisions investiguĂ©es. Ensemble, ces travaux soutiennent et prĂ©cisent une contribution centrale du cortex prĂ©moteur aux modifications de la dĂ©marche sous guidage visuel. D’une part, ils rapportent pour la premiĂšre fois que l’activitĂ© neuronale de multiples subdivisions du cortex prĂ©moteur reflĂšte diffĂ©rentes Ă©tapes de la planification locomotrice stipulant les altĂ©rations Ă  entreprendre Ă  l’approche d’un obstacle et durant son franchissement. D’autre part, ils rĂ©vĂšlent complĂ©mentairement que l’activation de ces subdivisions a le pouvoir d’influencer profondĂ©ment la marche. Les donnĂ©es collectĂ©es soulignent finalement plusieurs points de comparaison entre les aires prĂ©motrices du chat et du primate, suggĂ©rant un degrĂ© d’analogie fonctionnelle extensible Ă  la locomotion humaine.Locomotion is a fundamental component of animal life: it provides continuous access to the resources necessary for survival as well as the means to elude potential perils. However, both natural and built environments teem with obstacles impeding one’s progress. For humans and other terrestrial mammals navigating primarily through vision, efficiently negotiating these obstacles critically requires the capacity to proactively adapt the positioning and trajectory of each step on the basis of visual information extracted during their approach. In the nervous system, this capacity involves a complex process through which the integration of visual signals reflecting the parameters and location of an obstacle specifies a course of action to ensure its negotiation, Extensive studies in the cat, one of the most common models used to study the neural mechanisms involved in the control of locomotion, have currently implicated two cortical structures to this process. The posterior parietal cortex is suggested to contribute to the determination of the obstacle’s relative position (with respect to the body) while the primary motor cortex is central to the execution of the gait modifications. However, our comprehension of the neural substrate implicated in the sensorimotor transformation linking these defined stages is extremely limited. Several lines of evidence, predominantly derived from work in the primate investigating the voluntary control of arm movements, nonetheless point towards a potentially major contribution of the premotor cortex to this function. This thesis sets out to directly determine the premotor contribution to the control of gait modifications. Two studies report the activity of individual neurons recorded in two large subdivisions of premotor cortex, areas 6iffu and 4delta, in awake cats freely performing an obstacle negotiation task on treadmill. These studies describe distinct changes in activity across subdivisions that correlate with specific aspects of the task, including preparatory changes related to the final approach of the obstacle and others related to one or more stages of the sequential locomotor adjustments surrounding its negotiation. A third study used intracortical microstimulation to investigate the capacity of different premotor subdivisions of the cat to modify gait. This study reveals a variety of complex electromyographic responses that are integrated into the gait cycle. Moreover, several subdivisions show distinct signatures of multi-limb effects that contrast with the focal influence of the primary motor cortex. Each of these three studies is finally complemented by retrograde tracing investigations of anatomical connections critical to the functional interpretation of the subdivisions examined. Together, these studies support and clarify a central contribution of the premotor cortex to the modification of gait under visual guidance. We report for the first time that the neural activity of multiple subdivisions of the premotor cortex reflects different stages of the locomotor plan specifying the gait alterations to perform during the approach and crossing of an obstacle. In addition, we reveal that activation of these subdivisions has the power to profoundly influence walking. The data collected finally highlight several points of comparison between the premotor areas of the cat and the primate, suggesting a degree of functional analogy extensible to human locomotion

    Evaluation of Different Types of Stimuli in a ERP-Based Brain-Computer Interface Speller under RSVP.

    Get PDF
    Rapid Serial Visual Presentation (RSVP) is currently one of the most suitable gaze-independent paradigms to control a visual brain-computer interface based on event related potentials (ERP-BCI) by patients with a lack of ocular motility. However, gaze-independent paradigms have not been studied as closely as gaze-dependent ones in reference to the type of stimuli presented. Under gaze-dependent paradigms, faces have been shown to be the most appropriate stimuli, especially when they are red. Therefore, the aim of the present work is to evaluate whether these results of the color of faces as visual stimuli also has an impact on ERP-BCI performance under the RSVP paradigm. In this preliminary study, six participants tested the ERP-BCI under RSVP using four different conditions for a speller application: letters, blue faces, red faces, and green faces. These preliminary results showed non-significant differences in accuracy or information transfer rate. The present work therefore shows that, unlike under gaze-dependent paradigms, the stimulus type has no impact on the performance of an ERP-BCI under RSVP. This finding should be considered in future ERP-BCI proposals aimed at users who need gaze-independent systems.Universidad de MĂĄlaga. Campus de Excelencia Internacional AndalucĂ­a Tech

    Social convergence in times of spatial distancing: The rRole of music during the COVID-19 Pandemic

    Get PDF

    Brain-Computer Interface

    Get PDF
    Brain-computer interfacing (BCI) with the use of advanced artificial intelligence identification is a rapidly growing new technology that allows a silently commanding brain to manipulate devices ranging from smartphones to advanced articulated robotic arms when physical control is not possible. BCI can be viewed as a collaboration between the brain and a device via the direct passage of electrical signals from neurons to an external system. The book provides a comprehensive summary of conventional and novel methods for processing brain signals. The chapters cover a range of topics including noninvasive and invasive signal acquisition, signal processing methods, deep learning approaches, and implementation of BCI in experimental problems

    Digital Human Representations for Health Behavior Change: A Structured Literature Review

    Get PDF
    Organizations have increasingly begun using digital human representations (DHRs), such as avatars and embodied agents, to deliver health behavior change interventions (BCIs) that target modifiable risk factors in the smoking, nutrition, alcohol overconsumption, and physical inactivity (SNAP) domain. We conducted a structured literature review of 60 papers from the computing, health, and psychology literatures to investigate how DHRs’ social design affects whether BCIs succeed. Specifically, we analyzed how differences in social cues that DHRs use affect user psychology and how this can support or hinder different intervention functions. Building on established frameworks from the human-computer interaction and BCI literatures, we structure extant knowledge that can guide efforts to design future DHR-delivered BCIs. We conclude that we need more field studies to better understand the temporal dynamics and the mid-term and long-term effects of DHR social design on user perception and intervention outcomes

    Emotion and Stress Recognition Related Sensors and Machine Learning Technologies

    Get PDF
    This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective

    Recent Applications in Graph Theory

    Get PDF
    Graph theory, being a rigorously investigated field of combinatorial mathematics, is adopted by a wide variety of disciplines addressing a plethora of real-world applications. Advances in graph algorithms and software implementations have made graph theory accessible to a larger community of interest. Ever-increasing interest in machine learning and model deployments for network data demands a coherent selection of topics rewarding a fresh, up-to-date summary of the theory and fruitful applications to probe further. This volume is a small yet unique contribution to graph theory applications and modeling with graphs. The subjects discussed include information hiding using graphs, dynamic graph-based systems to model and control cyber-physical systems, graph reconstruction, average distance neighborhood graphs, and pure and mixed-integer linear programming formulations to cluster networks
    • 

    corecore