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O'Hare L, Tarasi L, Asher JM, Hibbard PB, Romei V. Excitation-Inhibition Imbalance in Migraine: From Neurotransmitters to Brain Oscillations. Int J Mol Sci 2023; 24:10093. [PMID: 37373244 DOI: 10.3390/ijms241210093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/07/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
Migraine is among the most common and debilitating neurological disorders typically affecting people of working age. It is characterised by a unilateral, pulsating headache often associated with severe pain. Despite the intensive research, there is still little understanding of the pathophysiology of migraine. At the electrophysiological level, altered oscillatory parameters have been reported within the alpha and gamma bands. At the molecular level, altered glutamate and GABA concentrations have been reported. However, there has been little cross-talk between these lines of research. Thus, the relationship between oscillatory activity and neurotransmitter concentrations remains to be empirically traced. Importantly, how these indices link back to altered sensory processing has to be clearly established as yet. Accordingly, pharmacologic treatments have been mostly symptom-based, and yet sometimes proving ineffective in resolving pain or related issues. This review provides an integrative theoretical framework of excitation-inhibition imbalance for the understanding of current evidence and to address outstanding questions concerning the pathophysiology of migraine. We propose the use of computational modelling for the rigorous formulation of testable hypotheses on mechanisms of homeostatic imbalance and for the development of mechanism-based pharmacological treatments and neurostimulation interventions.
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Affiliation(s)
- Louise O'Hare
- Division of Psychology, Nottingham Trent University, Nottingham NG1 4FQ, UK
| | - Luca Tarasi
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum-Università di Bologna, Campus di Cesena, Via Rasi e Spinelli, 176, 47521 Cesena, Italy
| | - Jordi M Asher
- Department of Psychology, University of Essex, Colchester CO4 3SQ, UK
| | - Paul B Hibbard
- Department of Psychology, University of Essex, Colchester CO4 3SQ, UK
| | - Vincenzo Romei
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum-Università di Bologna, Campus di Cesena, Via Rasi e Spinelli, 176, 47521 Cesena, Italy
- Facultad de Lenguas y Educación, Universidad Antonio de Nebrija, 28015 Madrid, Spain
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Troscianko J, Osorio D. A model of colour appearance based on efficient coding of natural images. PLoS Comput Biol 2023; 19:e1011117. [PMID: 37319266 DOI: 10.1371/journal.pcbi.1011117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 04/20/2023] [Indexed: 06/17/2023] Open
Abstract
An object's colour, brightness and pattern are all influenced by its surroundings, and a number of visual phenomena and "illusions" have been discovered that highlight these often dramatic effects. Explanations for these phenomena range from low-level neural mechanisms to high-level processes that incorporate contextual information or prior knowledge. Importantly, few of these phenomena can currently be accounted for in quantitative models of colour appearance. Here we ask to what extent colour appearance is predicted by a model based on the principle of coding efficiency. The model assumes that the image is encoded by noisy spatio-chromatic filters at one octave separations, which are either circularly symmetrical or oriented. Each spatial band's lower threshold is set by the contrast sensitivity function, and the dynamic range of the band is a fixed multiple of this threshold, above which the response saturates. Filter outputs are then reweighted to give equal power in each channel for natural images. We demonstrate that the model fits human behavioural performance in psychophysics experiments, and also primate retinal ganglion responses. Next, we systematically test the model's ability to qualitatively predict over 50 brightness and colour phenomena, with almost complete success. This implies that much of colour appearance is potentially attributable to simple mechanisms evolved for efficient coding of natural images, and is a well-founded basis for modelling the vision of humans and other animals.
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Affiliation(s)
- Jolyon Troscianko
- Centre for Ecology & Conservation, University of Exeter, Penryn, United Kingdom
| | - Daniel Osorio
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
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Multi-Frequency Image Completion via a Biologically-Inspired Sub-Riemannian Model with Frequency and Phase. J Imaging 2021; 7:jimaging7120271. [PMID: 34940739 PMCID: PMC8704454 DOI: 10.3390/jimaging7120271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 11/24/2021] [Accepted: 12/01/2021] [Indexed: 11/16/2022] Open
Abstract
We present a novel cortically-inspired image completion algorithm. It uses five-dimensional sub-Riemannian cortical geometry, modeling the orientation, spatial frequency and phase-selective behavior of the cells in the visual cortex. The algorithm extracts the orientation, frequency and phase information existing in a given two-dimensional corrupted input image via a Gabor transform and represents those values in terms of cortical cell output responses in the model geometry. Then, it performs completion via a diffusion concentrated in a neighborhood along the neural connections within the model geometry. The diffusion models the activity propagation integrating orientation, frequency and phase features along the neural connections. Finally, the algorithm transforms the diffused and completed output responses back to the two-dimensional image plane.
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Abstract
The Wilson-Cowan equations were developed to provide a simplified yet powerful description of neural network dynamics. As such, they embraced nonlinear dynamics, but in an interpretable form. Most importantly, it was the first mathematical formulation to emphasize the significance of interactions between excitatory and inhibitory neural populations, thereby incorporating both cooperation and competition. Subsequent research by many has documented the Wilson-Cowan significance in such diverse fields as visual hallucinations, memory, binocular rivalry, and epilepsy. The fact that these equations are still being used to elucidate a wide range of phenomena attests to their validity as a dynamical approximation to more detailed descriptions of complex neural computations.
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Affiliation(s)
- Hugh R Wilson
- Centre for Vision Research, York University, Toronto, Canada.
| | - Jack D Cowan
- Department of Mathematics, University of Chicago, Chicago, USA
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Canham T, Vazquez-Corral J, Mathieu E, Bertalmío M. Matching visual induction effects on screens of different size. J Vis 2021; 21:10. [PMID: 34144607 PMCID: PMC8237091 DOI: 10.1167/jov.21.6.10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones. But visual induction, the perceptual phenomenon by which the appearance of a scene region is affected by its surroundings, will be different for the same image shown on two displays of different dimensions. This phenomenon presents a practical challenge for the preservation of the artistic intentions of filmmakers, because it can lead to shifts in image appearance between viewing destinations. In this work, we show that a neural field model based on the efficient representation principle is able to predict induction effects and how, by regularizing its associated energy functional, the model is still able to represent induction but is now invertible. From this finding, we propose a method to preprocess an image in a screen-size dependent way so that its perception, in terms of visual induction, may remain constant across displays of different size. The potential of the method is demonstrated through psychophysical experiments on synthetic images and qualitative examples on natural images.
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Affiliation(s)
- Trevor Canham
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.,
| | - Javier Vazquez-Corral
- Computer Vision Center and the Computer Sciences Department at Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain., http://www.jvazquez-corral.net
| | | | - Marcelo Bertalmío
- Instituto de óptica, Spanish National Research Council (CSIC), Spain.,
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A Cortical-Inspired Sub-Riemannian Model for Poggendorff-Type Visual Illusions. J Imaging 2021; 7:jimaging7030041. [PMID: 34460697 PMCID: PMC8321287 DOI: 10.3390/jimaging7030041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 01/27/2021] [Accepted: 02/11/2021] [Indexed: 11/20/2022] Open
Abstract
We consider Wilson-Cowan-type models for the mathematical description of orientation-dependent Poggendorff-like illusions. Our modelling improves two previously proposed cortical-inspired approaches, embedding the sub-Riemannian heat kernel into the neuronal interaction term, in agreement with the intrinsically anisotropic functional architecture of V1 based on both local and lateral connections. For the numerical realisation of both models, we consider standard gradient descent algorithms combined with Fourier-based approaches for the efficient computation of the sub-Laplacian evolution. Our numerical results show that the use of the sub-Riemannian kernel allows us to reproduce numerically visual misperceptions and inpainting-type biases in a stronger way in comparison with the previous approaches.
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Boscain U, Prandi D, Sacchelli L, Turco G. A bio-inspired geometric model for sound reconstruction. JOURNAL OF MATHEMATICAL NEUROSCIENCE 2021; 11:2. [PMID: 33394219 PMCID: PMC7782772 DOI: 10.1186/s13408-020-00099-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 12/08/2020] [Indexed: 05/03/2023]
Abstract
The reconstruction mechanisms built by the human auditory system during sound reconstruction are still a matter of debate. The purpose of this study is to propose a mathematical model of sound reconstruction based on the functional architecture of the auditory cortex (A1). The model is inspired by the geometrical modelling of vision, which has undergone a great development in the last ten years. There are, however, fundamental dissimilarities, due to the different role played by time and the different group of symmetries. The algorithm transforms the degraded sound in an 'image' in the time-frequency domain via a short-time Fourier transform. Such an image is then lifted to the Heisenberg group and is reconstructed via a Wilson-Cowan integro-differential equation. Preliminary numerical experiments are provided, showing the good reconstruction properties of the algorithm on synthetic sounds concentrated around two frequencies.
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Affiliation(s)
- Ugo Boscain
- CNRS, LJLL, Sorbonne Université, Université de Paris, Inria, Paris, France
| | - Dario Prandi
- Université Paris-Saclay, CNRS, CentraleSupélec, Laboratoire des signaux et systèmes, 91190 Gif-sur-Yvette, France
| | - Ludovic Sacchelli
- Université Lyon, Université Claude Bernard Lyon 1, CNRS, LAGEPP UMR 5007, 43 bd du 11 novembre 1918, F-69100 Villeurbanne, France
| | - Giuseppina Turco
- CNRS, Laboratoire de Linguistique Formelle, UMR 7110, Université de Paris, Paris, France
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Bertalmío M, Gomez-Villa A, Martín A, Vazquez-Corral J, Kane D, Malo J. Evidence for the intrinsically nonlinear nature of receptive fields in vision. Sci Rep 2020; 10:16277. [PMID: 33004868 PMCID: PMC7530701 DOI: 10.1038/s41598-020-73113-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 09/11/2020] [Indexed: 11/10/2022] Open
Abstract
The responses of visual neurons, as well as visual perception phenomena in general, are highly nonlinear functions of the visual input, while most vision models are grounded on the notion of a linear receptive field (RF). The linear RF has a number of inherent problems: it changes with the input, it presupposes a set of basis functions for the visual system, and it conflicts with recent studies on dendritic computations. Here we propose to model the RF in a nonlinear manner, introducing the intrinsically nonlinear receptive field (INRF). Apart from being more physiologically plausible and embodying the efficient representation principle, the INRF has a key property of wide-ranging implications: for several vision science phenomena where a linear RF must vary with the input in order to predict responses, the INRF can remain constant under different stimuli. We also prove that Artificial Neural Networks with INRF modules instead of linear filters have a remarkably improved performance and better emulate basic human perception. Our results suggest a change of paradigm for vision science as well as for artificial intelligence.
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Affiliation(s)
| | | | | | | | - David Kane
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Jesús Malo
- Universitat de Valencia, Valencia, Spain
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