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Author Xim Cerda-Company; Olivier Penacchio; Xavier Otazu edit   pdf
url  openurl
  Title Chromatic Induction in Migraine Type Journal
  Year 2021 Publication VISION Abbreviated Journal  
  Volume 5 Issue 3 Pages 37  
  Keywords migraine; vision; colour; colour perception; chromatic induction; psychophysics  
  Abstract The human visual system is not a colorimeter. The perceived colour of a region does not only depend on its colour spectrum, but also on the colour spectra and geometric arrangement of neighbouring regions, a phenomenon called chromatic induction. Chromatic induction is thought to be driven by lateral interactions: the activity of a central neuron is modified by stimuli outside its classical receptive field through excitatory–inhibitory mechanisms. As there is growing evidence of an excitation/inhibition imbalance in migraine, we compared chromatic induction in migraine and control groups. As hypothesised, we found a difference in the strength of induction between the two groups, with stronger induction effects in migraine. On the other hand, given the increased prevalence of visual phenomena in migraine with aura, we also hypothesised that the difference between migraine and control would be more important in migraine with aura than in migraine without aura. Our experiments did not support this hypothesis. Taken together, our results suggest a link between excitation/inhibition imbalance and increased induction effects.  
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  Notes NEUROBIT; no proj Approved no  
  Call Number Admin @ si @ CPO2021 Serial 3589  
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Author Olivier Penacchio; Xavier Otazu; Arnold J Wilkings; Sara M. Haigh edit  url
openurl 
  Title A mechanistic account of visual discomfort Type Journal Article
  Year 2023 Publication Frontiers in Neuroscience Abbreviated Journal FN  
  Volume 17 Issue Pages  
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  Abstract Much of the neural machinery of the early visual cortex, from the extraction of local orientations to contextual modulations through lateral interactions, is thought to have developed to provide a sparse encoding of contour in natural scenes, allowing the brain to process efficiently most of the visual scenes we are exposed to. Certain visual stimuli, however, cause visual stress, a set of adverse effects ranging from simple discomfort to migraine attacks, and epileptic seizures in the extreme, all phenomena linked with an excessive metabolic demand. The theory of efficient coding suggests a link between excessive metabolic demand and images that deviate from natural statistics. Yet, the mechanisms linking energy demand and image spatial content in discomfort remain elusive. Here, we used theories of visual coding that link image spatial structure and brain activation to characterize the response to images observers reported as uncomfortable in a biologically based neurodynamic model of the early visual cortex that included excitatory and inhibitory layers to implement contextual influences. We found three clear markers of aversive images: a larger overall activation in the model, a less sparse response, and a more unbalanced distribution of activity across spatial orientations. When the ratio of excitation over inhibition was increased in the model, a phenomenon hypothesised to underlie interindividual differences in susceptibility to visual discomfort, the three markers of discomfort progressively shifted toward values typical of the response to uncomfortable stimuli. Overall, these findings propose a unifying mechanistic explanation for why there are differences between images and between observers, suggesting how visual input and idiosyncratic hyperexcitability give rise to abnormal brain responses that result in visual stress.  
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  Notes NEUROBIT Approved no  
  Call Number Admin @ si @ POW2023 Serial 3886  
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Author David Berga; Xavier Otazu edit   pdf
url  openurl
  Title Modeling Bottom-Up and Top-Down Attention with a Neurodynamic Model of V1 Type Journal Article
  Year 2020 Publication Neurocomputing Abbreviated Journal NEUCOM  
  Volume 417 Issue Pages 270-289  
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  Abstract Previous studies suggested that lateral interactions of V1 cells are responsible, among other visual effects, of bottom-up visual attention (alternatively named visual salience or saliency). Our objective is to mimic these connections with a neurodynamic network of firing-rate neurons in order to predict visual attention. Early visual subcortical processes (i.e. retinal and thalamic) are functionally simulated. An implementation of the cortical magnification function is included to define the retinotopical projections towards V1, processing neuronal activity for each distinct view during scene observation. Novel computational definitions of top-down inhibition (in terms of inhibition of return, oculomotor and selection mechanisms), are also proposed to predict attention in Free-Viewing and Visual Search tasks. Results show that our model outpeforms other biologically inspired models of saliency prediction while predicting visual saccade sequences with the same model. We also show how temporal and spatial characteristics of saccade amplitude and inhibition of return can improve prediction of saccades, as well as how distinct search strategies (in terms of feature-selective or category-specific inhibition) can predict attention at distinct image contexts.  
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  Notes NEUROBIT Approved no  
  Call Number Admin @ si @ BeO2020c Serial 3444  
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Author David Berga; Xose R. Fernandez-Vidal; Xavier Otazu; V. Leboran; Xose M. Pardo edit   pdf
url  openurl
  Title Psychophysical evaluation of individual low-level feature influences on visual attention Type Journal Article
  Year 2019 Publication Vision Research Abbreviated Journal VR  
  Volume 154 Issue Pages 60-79  
  Keywords Visual attention; Psychophysics; Saliency; Task; Context; Contrast; Center bias; Low-level; Synthetic; Dataset  
  Abstract In this study we provide the analysis of eye movement behavior elicited by low-level feature distinctiveness with a dataset of synthetically-generated image patterns. Design of visual stimuli was inspired by the ones used in previous psychophysical experiments, namely in free-viewing and visual searching tasks, to provide a total of 15 types of stimuli, divided according to the task and feature to be analyzed. Our interest is to analyze the influences of low-level feature contrast between a salient region and the rest of distractors, providing fixation localization characteristics and reaction time of landing inside the salient region. Eye-tracking data was collected from 34 participants during the viewing of a 230 images dataset. Results show that saliency is predominantly and distinctively influenced by: 1. feature type, 2. feature contrast, 3. temporality of fixations, 4. task difficulty and 5. center bias. This experimentation proposes a new psychophysical basis for saliency model evaluation using synthetic images.  
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  Notes NEUROBIT; 600.128; 600.120 Approved no  
  Call Number Admin @ si @ BFO2019a Serial 3274  
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Author C. Alejandro Parraga; Arash Akbarinia edit   pdf
doi  openurl
  Title NICE: A Computational Solution to Close the Gap from Colour Perception to Colour Categorization Type Journal Article
  Year 2016 Publication PLoS One Abbreviated Journal Plos  
  Volume 11 Issue 3 Pages e0149538  
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  Abstract The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms.  
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  Notes NEUROBIT; 600.068 Approved no  
  Call Number Admin @ si @ PaA2016a Serial 2747  
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