Vision : a model to study cognition

Our senses – vision, audition, touch, taste and smell – constantly receive a large amount of information. This information is processed and used in order to guide our actions. Cognitive sciences consist in studying mental abilities through different disciplines, e.g. linguistic, neuropsychology, neuroscience or modelling. Each discipline considers mental phenomena and their physical substrate, the nervous system, as a tool to process information in order to guide behavior adaptively (Collins, Andler, & Tallon-Baudry, 2018). Cognitive functions are a collection of processing systems serving different goals, and whose interactions are key to the complexity of cognition. Studying cognition often implies operationalizing each of these functions separately. For example, memory allows to store and reuse information, and attention allows to select relevant information for the task at hand, and to facilitate its processing. To characterize the processes of specific cognitive functions, it is thus necessary to provide to the studied subject – here we concentrate on human and non-human primates – an information to be processed, through different sensory modalities. In this essay, we concentrate on vision as a unique model to study cognition through different fields of cognitive sciences, from cognitive psychology to neurosciences, mentioning also briefly modeling and neuropsychology. Our objective is not to do an exhaustive description of the visual system, nor to compare in detail vision with other sensory modalities, but to argue that the accumulation of evidence on the visual system, as well as its characteristic perceptual, algorithmic and physiological organization, make it a particularly rich model to study cognitive functions. After a brief presentation of some properties of vision, we will illustrate our argument focusing on a specific cognitive function: attention, and in particular its study in cognitive psychology and neuroscience. We will discuss how our knowledge of vision allowed us to understand the behavioral and neuronal mechanisms underlying attentional selection and facilitation of information. We will finally conclude that sensory systems can be used as models to study cognition in different fields of cognitive sciences.Nos différents sens−la vue, l’audition, le toucher, le goût, l’odorat− reçoivent constamment un flux massif d’informations. Toutes ces informations sont traitées et utilisées afin de guider nos actions. Les sciences cognitives représentent l’étude de ces facultés mentales par le prisme de différentes disciplines, par exemple linguistique, neuropsychologie, neuroscience ou modélisation. Chacune de ces disciplines considère les phénomènes mentaux et leur substrat physique, le système nerveux, comme un outil de traitement de l’information ayant pour but de guider le comportement de façon adaptative (Collins, Andler, & Tallon-Baudry, 2018). Les fonctions cognitives constituent ainsi une collection de systèmes de traitement de l'information servant différents buts, et dont les interactions sont à l’origine de la complexité de la cognition. L ’ étude de la cognition passe souvent par l’opérationnalisation de chacune de ces fonctions séparément. Par exemple, la mémoire permet de stocker et de réutiliser l’information, et l’attention permet de sélectionner celle qui est pertinente pour la tâche à effectuer, et d’en faciliter son traitement. Afin de caractériser les processus propres à une fonction cognitive donnée, il est alors nécessaire de fournir au sujet d’étude − ici nous nous concentrerons sur le primate humain et non-humain − une information à traiter, via différentes modalités sensorielles. Dans cet article d’opinion, nous nous concentrons sur la vision comme modèle d’étude singulier de la cognition à travers différents champs des sciences cognitives, de la psychologie cognitive aux neurosciences, en passant brièvement par la modélisation et la neuropsychologie. Notre objectif n’est pas de faire une description exhaustive de la modalité visuelle ni de faire une comparaison détaillée avec les autres modalités sensorielles, mais d’argumenter que l’accumulation des connaissances que nous en avons, ainsi que son organisation caractéristique du point de vue perceptif, algorithmique et physiologique, en font un modèle particulièrement riche de l’étude des fonctions cognitives. Après une brève présentation de certaines bases de la vision, nous illustrerons notre argument en nous concentrant sur une fonction cognitive spécifique : l’attention, et en particulier, son étude en psychologie cognitive et neurosciences. Nous aborderons notamment la façon grâce à laquelle nos connaissances sur la vision nous ont permis de comprendre les mécanismes comportementaux et neuronaux qui sous-tendent la sélection de l’information par l’attention, et la facilitation de son traitement. Nous conclurons que les systèmes sensoriels peuvent être utilisés comme modèles d’étude de la cognition dans divers domaines des sciences cognitives

Second order scattering descriptors predict fMRI activity due to visual textures

Second layer scattering descriptors are known to provide good classification performance on natural quasi-stationary processes such as visual textures due to their sensitivity to higher order moments and continuity with respect to small deformations. In a functional Magnetic Resonance Imaging (fMRI) experiment we present visual textures to subjects and evaluate the predictive power of these descriptors with respect to the predictive power of simple contour energy - the first scattering layer. We are able to conclude not only that invariant second layer scattering coefficients better encode voxel activity, but also that well predicted voxels need not necessarily lie in known retinotopic regions.Comment: 3nd International Workshop on Pattern Recognition in NeuroImaging (2013

Attention explores space periodically at the theta frequency

Voluntary attention is at the core of a wide variety of cognitive functions. Attention can be oriented to and sustained at a location or reoriented in space to allow processing at other locations—critical in an ever-changing environment. Numerous studies have investigated attentional orienting in time and space, but little is known about the spatiotemporal dynamics of attentional reorienting. Here we explicitly manipulated attentional reorienting using a cuing procedure in a two- alternative forced-choice orientation-discrimination task. We interrogated attentional distribution by flashing two probe stimuli with various delays between the precue and target stimuli. Then we used the probabilities that both probes and neither probe were correctly reported to solve a second-degree equation, which estimates the report probability at each probe location. We demonstrated that attention reorients periodically at ~4 Hz (theta) between the two stimulus locations. We further characterized the processing dynamics at each stimulus location, and demonstrated that attention samples each location periodically at ;11 Hz (alpha). Finally, simulations support our findings and show that this method is sufficiently powered, making it a valuable tool for studying the spatiotemporal dynamics of attention

La vision : un modèle d'étude de la cognition

Our senses-vision, audition, touch, taste and smell-constantly receive a large amount of information. This information is processed and used in order to guide our actions. Cognitive sciences consist in studying mental abilities through different disciplines, e.g. linguistic, neuropsychology or modeling. Each discipline considers mental phenomena and their physical substrate, the nervous system, as a tool to process information in order to guide behavior adaptively (Collins, Andler, & Tallon-Baudry, 2018). Cognitive functions are a collection of processing systems serving different goals. For example, memory allows to store and reuse information, and attention allows to select relevant information for the task at hand, and to facilitate its processing. To characterize the processes of specific cognitive functions, it is thus necessary to provide to the studied subject – here we concentrate on human and non-human primates – an information to be processed, through different sensory modalities. In this opinion piece, we concentrate on vision as a unique model to study cognition through different fields of cognitive sciences, from cognitive psychology to neurosciences, mentioning also briefly modeling and neuropsychology. Our objective is not to do an exhaustive description of the visual system, nor to compare in detail vision with other sensory modalities, but to argue that the accumulation of evidence on the visual system, as well as its characteristic perceptual, algorithmic and physiological organization, make it a particularly rich model to study cognitive functions. After a brief presentation of some vision properties, we will illustrate our argument focusing on a specific cognitive function: attention, and in particular its study in cognitive psychology and neuroscience. We will discuss how our knowledge of vision allowed us to understand the behavioral and neural mechanisms underlying attentional selection and facilitation of information. We will finally conclude that sensory systems can be used as model to study cognition in different fields of cognitive sciences.Nos différents sens − la vue, l'audition, le toucher, le goût, l'odorat − reçoivent constamment un flux massif d'informations. Toutes ces informations sont traitées et utilisées afin de guider nos actions. Les sciences cognitives représentent l'étude de ces facultés mentales par le prisme de différentes disciplines, e.g. linguistique, neuropsychologie ou modélisation. Chacune de ces disciplines considèrent les phénomènes mentaux et leur substrat physique, le système nerveux, comme un outil de traitement de l'information ayant pour but de guider le comportement de façon adaptative (Collins, Andler, & Tallon-Baudry, 2018). Les fonctions cognitives constituent ainsi une collection de systèmes de traitement de l'information servant différents buts. Par exemple, la mémoire permet de stocker et de réutiliser l'information, et l'attention permet de sélectionner celle qui est pertinente pour la tâche à effectuer, et d'en faciliter son traitement. Afin de caractériser les processus propres à une fonction cognitive donnée, il est alors nécessaire de fournir au sujet d'étude − ici nous nous concentrerons sur le primate humain et non-humain − une information à traiter, via différentes modalités sensorielles. Dans cet article d'opinion, nous nous concentrons sur la vision comme modèle d'étude singulier de la cognition à travers différents champs des sciences cognitives, de la psychologie cognitive aux neurosciences, en passant brièvement par la modélisation et la neuropsychologie. Notre objectif n'est pas de faire une description exhaustive de la modalité visuelle ni de faire une comparaison détaillée avec les autres modalités sensorielles, mais d'argumenter que l'accumulation des connaissances que nous en avons, ainsi que son organisation caractéristique du point de vue perceptif, algorithmique et physiologique, en font un modèle particulièrement riche de l'étude des fonctions cognitives. Après une brève présentation de certaines bases de la vision, nous illustrerons notre argument en nous concentrant sur une fonction cognitive spécifique : l'attention, et en particulier, son étude en psychologie cognitive et neurosciences. Nous aborderons notamment la façon grâce à laquelle nos connaissances sur la vision nous ont permis de comprendre les mécanismes comportementaux et neuraux sous-tendant la sélection de l'information par l'attention, et la facilitation de son traitement. Nous conclurons que les systèmes sensoriels peuvent être utilisés comme modèles d'étude de la cognition dans divers domaines des sciences cognitives

Pre-stimulus antero-posterior EEG connectivity predicts performance in a UAV monitoring task

Long monitoring tasks without regular actions, are becoming increasingly common from aircraft pilots to train conductors as these systems grow more automated. These task contexts are challenging for the human operator because they require inputs at irregular and highly interspaced moments even though these actions are often critical. It has been shown that such conditions lead to divided and distracted attentional states which in turn reduce the processing of external stimuli (e.g. alarms) and may lead to miss critical events. In this study we explored to which extent it is possible to predict an operator’s behavioural performance in a Unmanned Aerial Vehicle (UAV) monitoring task using electroencephalographic (EEG) activity. More specifically we investigated the relevance of large-scale EEG connectivity for performance prediction by correlating relative coherence with reaction times (RT). We show that long-range EEG relative coherence, i.e. between occipital and frontal electrodes, is significantly correlated with RT and that different frequency bands exhibit opposite effects. More specifically we observed that coherence between occipital and frontal electrodes was: negatively correlated with RT at 6Hz (theta band), more coherence leading to better performance, and positively correlated with RT at 8Hz (lower alpha band), more coherence leading to worse performance. Our results suggest that EEG connectivity measures could be useful in predicting an operator’s attentional state and her/his performances in ecological settings. Hence these features could potentially be used in a neuro-adaptive interface to improve operator-system interaction and safety in critical systems

La vision : un modèle d'étude de la cognition

Our senses-vision, audition, touch, taste and smell-constantly receive a large amount of information. This information is processed and used in order to guide our actions. Cognitive sciences consist in studying mental abilities through different disciplines, e.g. linguistic, neuropsychology or modeling. Each discipline considers mental phenomena and their physical substrate, the nervous system, as a tool to process information in order to guide behavior adaptively (Collins, Andler, & Tallon-Baudry, 2018). Cognitive functions are a collection of processing systems serving different goals. For example, memory allows to store and reuse information, and attention allows to select relevant information for the task at hand, and to facilitate its processing. To characterize the processes of specific cognitive functions, it is thus necessary to provide to the studied subject – here we concentrate on human and non-human primates – an information to be processed, through different sensory modalities. In this opinion piece, we concentrate on vision as a unique model to study cognition through different fields of cognitive sciences, from cognitive psychology to neurosciences, mentioning also briefly modeling and neuropsychology. Our objective is not to do an exhaustive description of the visual system, nor to compare in detail vision with other sensory modalities, but to argue that the accumulation of evidence on the visual system, as well as its characteristic perceptual, algorithmic and physiological organization, make it a particularly rich model to study cognitive functions. After a brief presentation of some vision properties, we will illustrate our argument focusing on a specific cognitive function: attention, and in particular its study in cognitive psychology and neuroscience. We will discuss how our knowledge of vision allowed us to understand the behavioral and neural mechanisms underlying attentional selection and facilitation of information. We will finally conclude that sensory systems can be used as model to study cognition in different fields of cognitive sciences.Nos différents sens − la vue, l'audition, le toucher, le goût, l'odorat − reçoivent constamment un flux massif d'informations. Toutes ces informations sont traitées et utilisées afin de guider nos actions. Les sciences cognitives représentent l'étude de ces facultés mentales par le prisme de différentes disciplines, e.g. linguistique, neuropsychologie ou modélisation. Chacune de ces disciplines considèrent les phénomènes mentaux et leur substrat physique, le système nerveux, comme un outil de traitement de l'information ayant pour but de guider le comportement de façon adaptative (Collins, Andler, & Tallon-Baudry, 2018). Les fonctions cognitives constituent ainsi une collection de systèmes de traitement de l'information servant différents buts. Par exemple, la mémoire permet de stocker et de réutiliser l'information, et l'attention permet de sélectionner celle qui est pertinente pour la tâche à effectuer, et d'en faciliter son traitement. Afin de caractériser les processus propres à une fonction cognitive donnée, il est alors nécessaire de fournir au sujet d'étude − ici nous nous concentrerons sur le primate humain et non-humain − une information à traiter, via différentes modalités sensorielles. Dans cet article d'opinion, nous nous concentrons sur la vision comme modèle d'étude singulier de la cognition à travers différents champs des sciences cognitives, de la psychologie cognitive aux neurosciences, en passant brièvement par la modélisation et la neuropsychologie. Notre objectif n'est pas de faire une description exhaustive de la modalité visuelle ni de faire une comparaison détaillée avec les autres modalités sensorielles, mais d'argumenter que l'accumulation des connaissances que nous en avons, ainsi que son organisation caractéristique du point de vue perceptif, algorithmique et physiologique, en font un modèle particulièrement riche de l'étude des fonctions cognitives. Après une brève présentation de certaines bases de la vision, nous illustrerons notre argument en nous concentrant sur une fonction cognitive spécifique : l'attention, et en particulier, son étude en psychologie cognitive et neurosciences. Nous aborderons notamment la façon grâce à laquelle nos connaissances sur la vision nous ont permis de comprendre les mécanismes comportementaux et neuraux sous-tendant la sélection de l'information par l'attention, et la facilitation de son traitement. Nous conclurons que les systèmes sensoriels peuvent être utilisés comme modèles d'étude de la cognition dans divers domaines des sciences cognitives

Anticipatory reinstatement of expected perceptual events during visual sequence learning

Being able to predict future events in learned sequences is a fundamental cognitive ability. Successful behavior requires the brain to not only anticipate an upcoming event, but to also continue to keep track of the sequence in case of eventual disruptions, (e.g., when a predicted event does not occur). However, the precise neural mechanisms supporting such processes remain unknown. Here, using multivariate pattern classification based on electroencephalography (EEG) activity and time-frequency amplitude, we show that the visual system represents upcoming expected stimuli during a sequence-learning task. Stimulus-evoked neural representations were reinstated prior to expected stimulus onset, and when an anticipated stimulus was unexpectedly withheld, suggesting proactive reinstatement of sensory templates. Importantly, stimulus representation of the absent stimulus co-occurred with an emerging representation of the following stimulus in the sequence, showing that the brain actively maintained sequence order even when the sequence was perturbed. Finally, selective activity was evident in the alpha-beta band (9-20 Hz) amplitude topographies, confirming the role of alpha-beta oscillations in carrying information about the nature of sensory expectations. These results show that the brain dynamically implements anticipatory mechanisms that reinstate sensory representations, and that allow us to make predictions about events further in the future

Time-based binding as a solution to and a limitation for flexible cognition

Why can't we keep as many items as we want in working memory? It has long been debated whether this resource limitation is a bug (a downside of our fallible biological system) or instead a feature (an optimal response to a computational problem). We propose that the resource limitation is a consequence of a useful feature. Specifically, we propose that flexible cognition requires time-based binding, and time-based binding necessarily limits the number of (bound) memoranda that can be stored simultaneously. Time-based binding is most naturally instantiated via neural oscillations, for which there exists ample experimental evidence. We report simulations that illustrate this theory and that relate it to empirical data. We also compare the theory to several other (feature and bug) resource theories

Multivoxel Object Representations in Adult Human Visual Cortex Are Flexible: An Associative Learning Study

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Neural oscillations track the maintenance and proceduralization of novel instructions

Humans are capable of flexibly converting symbolic instructions into novel behaviors. Previous evidence and theoretical models suggest that the implementation of a novel instruction requires the reformatting of its declarative content into an action-oriented code optimized for the execution of the instructed behavior. While neuroimaging research focused on identifying the brain areas involved in such a process, the temporal and electrophysiological mechanisms remain poorly understood. These mechanisms, however, can provide information about the specific cognitive processes that characterize the proceduralization of information. In the present study, we recorded EEG activity while we asked participants to either simply maintain declaratively the content of novel S-R mappings or to proactively prepare for their implementation. By means of time-frequency analyses, we isolated the oscillatory features specific to the proceduralization of instructions. Implementation of the instructed mappings elicited stronger theta activity over frontal electrodes and suppression in mu and beta activity over central electrodes. On the contrary, activity in the alpha band, which has been shown to track the attentional deployment to task-relevant items, showed no differences between tasks. Together, these results support the idea that proceduralization of information is characterized by specific component processes such as orchestrating complex task settings and configuring the motor system that are not observed when instructions are held in a declarative format