24,008 research outputs found

    A conceptual frame with two neural mechanisms to model selective visual attention processes

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    An important problem in artificial intelligence (AI) is to find calculation procedures to save the semantic gap between the analytic formulations of the neuronal models and the concepts of the natural language used to describe the cognitive processes. In this work we explore a way of saving this gap for the case of the attentional processes, consisting in (1) proposing in first place a conceptual model of the attention double bottom-up/top-down organization, (2) proposing afterwards a neurophysiological model of the cortical and sub-cortical involved structures, (3) establishing the correspondences between the entities of (1) and (2), (4) operationalizing the model by using biologically inspired calculation mechanisms (algorithmic lateral inhibition and accumulative computation) formulated at symbolic level, and, (5) assessing the validity of the proposal by accommodating the works of the research team on diverse aspects of attention associated to visual surveillance tasks. The results obtained support in a reasonable way the validity of the proposal and enable its application in surveillance tasks different from the ones considered in this work. In particular, this is the case when linking the geometric descriptions of a scene with the corresponding activity level

    Classification systems offer a microcosm of issues in conceptual processing: A commentary on Kemmerer (2016)

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    This is a commentary on Kemmerer (2016), Categories of Object Concepts Across Languages and Brains: The Relevance of Nominal Classification Systems to Cognitive Neuroscience, DOI: 10.1080/23273798.2016.1198819

    A computer vision model for visual-object-based attention and eye movements

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    This is the post-print version of the final paper published in Computer Vision and Image Understanding. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2008 Elsevier B.V.This paper presents a new computational framework for modelling visual-object-based attention and attention-driven eye movements within an integrated system in a biologically inspired approach. Attention operates at multiple levels of visual selection by space, feature, object and group depending on the nature of targets and visual tasks. Attentional shifts and gaze shifts are constructed upon their common process circuits and control mechanisms but also separated from their different function roles, working together to fulfil flexible visual selection tasks in complicated visual environments. The framework integrates the important aspects of human visual attention and eye movements resulting in sophisticated performance in complicated natural scenes. The proposed approach aims at exploring a useful visual selection system for computer vision, especially for usage in cluttered natural visual environments.National Natural Science of Founda- tion of Chin

    Fluctuations in instantaneous frequency predict alpha amplitude during visual perception.

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    Rhythmic neural activity in the alpha band (8-13 Hz) is thought to have an important role in the selective processing of visual information. Typically, modulations in alpha amplitude and instantaneous frequency are thought to reflect independent mechanisms impacting dissociable aspects of visual information processing. However, in complex systems with interacting oscillators such as the brain, amplitude and frequency are mathematically dependent. Here, we record electroencephalography in human subjects and show that both alpha amplitude and instantaneous frequency predict behavioral performance in the same visual discrimination task. Consistent with a model of coupled oscillators, we show that fluctuations in instantaneous frequency predict alpha amplitude on a single trial basis, empirically demonstrating that these metrics are not independent. This interdependence suggests that changes in amplitude and instantaneous frequency reflect a common change in the excitatory and inhibitory neural activity that regulates alpha oscillations and visual information processing

    Introduction: The Third International Conference on Epigenetic Robotics

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    This paper summarizes the paper and poster contributions to the Third International Workshop on Epigenetic Robotics. The focus of this workshop is on the cross-disciplinary interaction of developmental psychology and robotics. Namely, the general goal in this area is to create robotic models of the psychological development of various behaviors. The term "epigenetic" is used in much the same sense as the term "developmental" and while we could call our topic "developmental robotics", developmental robotics can be seen as having a broader interdisciplinary emphasis. Our focus in this workshop is on the interaction of developmental psychology and robotics and we use the phrase "epigenetic robotics" to capture this focus

    NĂ€gemistaju automaatsete protsesside eksperimentaalne uurimine

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    VĂ€itekirja elektrooniline versioon ei sisalda publikatsiooneVĂ€itekiri keskendub nĂ€gemistaju protsesside eksperimentaalsele uurimisele, mis on suuremal vĂ”i vĂ€hemal mÀÀral automaatsed. Uurimistöös on kasutatud erinevaid eksperimentaalseid katseparadigmasid ja katsestiimuleid ning nii kĂ€itumuslikke- kui ka ajukuvamismeetodeid. Esimesed kolm empiirilist uurimust kĂ€sitlevad liikumisinformatsiooni töötlust, mis on evolutsiooni kĂ€igus kujunenud ĂŒheks olulisemaks baasprotsessiks nĂ€gemistajus. Esmalt huvitas meid, kuidas avastatakse liikuva objekti suunamuutusi, kui samal ajal toimub ka taustal liikumine (Uurimus I). NĂ€gemistaju uurijad on pikka aega arvanud, et liikumist arvutatakse alati mĂ”ne vĂ€lise objekti vĂ”i tausta suhtes. Meie uurimistulemused ei kinnitanud taolise suhtelise liikumise printsiibi paikapidavust ning toetavad pigem seisukohta, et eesmĂ€rkobjekti liikumisinformatsiooni töötlus on automaatne protsess, mis tuvastab silma pĂ”hjas toimuvaid nihkeid, ja taustal toimuv seda eriti ei mĂ”juta. Teise uurimuse tulemused (Uurimus II) nĂ€itasid, et nĂ€gemissĂŒsteem töötleb vĂ€ga edukalt ka seda liikumisinformatsiooni, millele vaatleja teadlikult tĂ€helepanu ei pööra. See tĂ€hendab, et samal ajal, kui inimene on mĂ”ne tĂ€helepanu hĂ”lmava tegevusega ametis, suudab tema aju taustal toimuvaid sĂŒndmusi automaatselt registreerida. IgapĂ€evaselt on inimese nĂ€gemisvĂ€ljas alati palju erinevaid objekte, millel on erinevad omadused, mistĂ”ttu jĂ€rgmiseks huvitas meid (Uurimus III), kuidas ĂŒhe tunnuse (antud juhul vĂ€rvimuutuse) töötlemist mĂ”jutab mĂ”ne teise tunnusega toimuv (antud juhul liikumiskiiruse) muutus. NĂ€itasime, et objekti liikumine parandas sama objekti vĂ€rvimuutuse avastamist, mis viitab, et nende kahe omaduse töötlemine ajus ei ole pĂ€ris eraldiseisev protsess. Samuti tĂ€hendab taoline tulemus, et hoolimata ĂŒhele tunnusele keskendumisest ei suuda inimene ignoreerida teist tĂ€helepanu tĂ”mbavat tunnust (liikumine), mis viitab taas kord automaatsetele töötlusprotsessidele. Neljas uurimus keskendus emotsionaalsete nĂ€ovĂ€ljenduste töötlusele, kuna need kannavad keskkonnas hakkamasaamiseks vajalikke sotsiaalseid signaale, mistĂ”ttu on alust arvata, et nende töötlus on kujunenud suuresti automaatseks protsessiks. NĂ€itasime, et emotsiooni vĂ€ljendavaid nĂ€gusid avastati kiiremini ja kergemini kui neutraalse ilmega nĂ€gusid ning et vihane nĂ€gu tĂ”mbas rohkem tĂ€helepanu kui rÔÔmus (Uurimus IV). VĂ€itekirja viimane osa puudutab visuaalset lahknevusnegatiivsust (ingl Visual Mismatch Negativity ehk vMMN), mis nĂ€itab aju vĂ”imet avastada automaatselt erinevusi enda loodud mudelist ĂŒmbritseva keskkonna kohta. Selle automaatse erinevuse avastamise mehhanismi uurimisse andsid oma panuse nii Uurimus II kui Uurimus IV, mis mĂ”lemad pakuvad vĂ€lja tĂ”endusi vMMN tekkimise kohta eri tingimustel ja katseparadigmades ning ka vajalikke metodoloogilisi tĂ€iendusi. Uurimus V on esimene kogu siiani ilmunud temaatilist teadustööd hĂ”lmav ĂŒlevaateartikkel ja metaanalĂŒĂŒs visuaalsest lahknevusnegatiivsusest psĂŒhhiaatriliste ja neuroloogiliste haiguste korral, mis panustab oluliselt visuaalse lahknevusnegatiivsuse valdkonna arengusse.The research presented and discussed in the thesis is an experimental exploration of processes in visual perception, which all display a considerable amount of automaticity. These processes are targeted from different angles using different experimental paradigms and stimuli, and by measuring both behavioural and brain responses. In the first three empirical studies, the focus is on motion detection that is regarded one of the most basic processes shaped by evolution. Study I investigated how motion information of an object is processed in the presence of background motion. Although it is widely believed that no motion can be perceived without establishing a frame of reference with other objects or motion on the background, our results found no support for relative motion principle. This finding speaks in favour of a simple and automatic process of detecting motion, which is largely insensitive to the surrounding context. Study II shows that the visual system is built to automatically process motion information that is outside of our attentional focus. This means that even if we are concentrating on some task, our brain constantly monitors the surrounding environment. Study III addressed the question of what happens when multiple stimulus qualities (motion and colour) are present and varied, which is the everyday reality of our visual input. We showed that velocity facilitated the detection of colour changes, which suggests that processing motion and colour is not entirely isolated. These results also indicate that it is hard to ignore motion information, and processing it is rather automatically initiated. The fourth empirical study focusses on another example of visual input that is processed in a rather automatic way and carries high survival value – emotional expressions. In Study IV, participants detected emotional facial expressions faster and more easily compared with neutral facial expressions, with a tendency towards more automatic attention to angry faces. In addition, we investigated the emergence of visual mismatch negativity (vMMN) that is one of the most objective and efficient methods for analysing automatic processes in the brain. Study II and Study IV proposed several methodological gains for registering this automatic change-detection mechanism. Study V is an important contribution to the vMMN research field as it is the first comprehensive review and meta-analysis of the vMMN studies in psychiatric and neurological disorders

    How active perception and attractor dynamics shape perceptual categorization: A computational model

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    We propose a computational model of perceptual categorization that fuses elements of grounded and sensorimotor theories of cognition with dynamic models of decision-making. We assume that category information consists in anticipated patterns of agent–environment interactions that can be elicited through overt or covert (simulated) eye movements, object manipulation, etc. This information is firstly encoded when category information is acquired, and then re-enacted during perceptual categorization. The perceptual categorization consists in a dynamic competition between attractors that encode the sensorimotor patterns typical of each category; action prediction success counts as ‘‘evidence’’ for a given category and contributes to falling into the corresponding attractor. The evidence accumulation process is guided by an active perception loop, and the active exploration of objects (e.g., visual exploration) aims at eliciting expected sensorimotor patterns that count as evidence for the object category. We present a computational model incorporating these elements and describing action prediction, active perception, and attractor dynamics as key elements of perceptual categorizations. We test the model in three simulated perceptual categorization tasks, and we discuss its relevance for grounded and sensorimotor theories of cognition.Peer reviewe

    The Problem of Mental Action

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    In mental action there is no motor output to be controlled and no sensory input vector that could be manipulated by bodily movement. It is therefore unclear whether this specific target phenomenon can be accommodated under the predictive processing framework at all, or if the concept of “active inference” can be adapted to this highly relevant explanatory domain. This contribution puts the phenomenon of mental action into explicit focus by introducing a set of novel conceptual instruments and developing a first positive model, concentrating on epistemic mental actions and epistemic self-control. Action initiation is a functionally adequate form of self-deception; mental actions are a specific form of predictive control of effective connectivity, accompanied and possibly even functionally mediated by a conscious “epistemic agent model”. The overall process is aimed at increasing the epistemic value of pre-existing states in the conscious self-model, without causally looping through sensory sheets or using the non-neural body as an instrument for active inference
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