10 research outputs found

    Methods to assess binocular rivalry with periodic stimuli

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    This is the final version. Available on open access from SpringerOpen via the DOI in this recordAvailability of data and materials: Source code for the model is available in the GitHub repository farzaneh-darki/Darki2020_methods: https://github.com/farzaneh-darki/Darki2020_methods.Binocular rivalry occurs when the two eyes are presented with incompatible stimuli and perception alternates between these two stimuli. This phenomenon has been investigated in two types of experiments: (1) Traditional experiments where the stimulus is fixed, (2) eye-swap experiments in which the stimulus periodically swaps between eyes many times per second (Logothetis et al. in Nature 380(6575):621–624, 1996). In spite of the rapid swapping between eyes, perception can be stable for many seconds with specific stimulus parameter configurations. Wilson introduced a two-stage, hierarchical model to explain both types of experiments (Wilson in Proc. Natl. Acad. Sci. 100(24):14499–14503, 2003). Wilson’s model and other rivalry models have been only studied with bifurcation analysis for fixed inputs and different types of dynamical behavior that can occur with periodically forcing inputs have not been investigated. Here we report (1) a more complete description of the complex dynamics in the unforced Wilson model, (2) a bifurcation analysis with periodic forcing. Previously, bifurcation analysis of the Wilson model with fixed inputs has revealed three main types of dynamical behaviors: Winner-takes-all (WTA), Rivalry oscillations (RIV), Simultaneous activity (SIM). Our results have revealed richer dynamics including mixed-mode oscillations (MMOs) and a period-doubling cascade, which corresponds to low-amplitude WTA (LAWTA) oscillations. On the other hand, studying rivalry models with numerical continuation shows that periodic forcing with high frequency (e.g. 18 Hz, known as flicker) modulates the three main types of behaviors that occur with fixed inputs with forcing frequency (WTA-Mod, RIV-Mod, SIM-Mod). However, dynamical behavior will be different with low frequency periodic forcing (around 1.5 Hz, so-called swap). In addition to WTA-Mod and SIM-Mod, cycle skipping, multi-cycle skipping and chaotic dynamics are found. This research provides a framework for either assessing binocular rivalry models to check consistency with empirical results, or for better understanding neural dynamics and mechanisms necessary to implement a minimal binocular rivalry model.Engineering and Physical Sciences Research Council (EPSRC

    The uncoupling limit of identical Hopf bifurcations with an application to perceptual bistability

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    We study the dynamics arising when two identical oscillators are coupled near a Hopf bifurcation where we assume a parameter Ï”\epsilon uncouples the system at Ï”=0\epsilon=0. Using a normal form for N=2N=2 identical systems undergoing Hopf bifurcation, we explore the dynamical properties. Matching the normal form coefficients to a coupled Wilson-Cowan oscillator network gives an understanding of different types of behaviour that arise in a model of perceptual bistability. Notably, we find bistability between in-phase and anti-phase solutions that demonstrates the feasibility for synchronisation to act as the mechanism by which periodic inputs can be segregated (rather than via strong inhibitory coupling, as in existing models). Using numerical continuation we confirm our theoretical analysis for small coupling strength and explore the bifurcation diagrams for large coupling strength, where the normal form approximation breaks down

    Sensorimotor computation underlying phototaxis in zebrafish

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    Animals continuously gather sensory cues to move towards favourable environments. Efficient goal-directed navigation requires sensory perception and motor commands to be intertwined in a feedback loop, yet the neural substrate underlying this sensorimotor task in the vertebrate brain remains elusive. Here, we combine virtual-reality behavioural assays, volumetric calcium imaging, optogenetic stimulation and circuit modelling to reveal the neural mechanisms through which a zebrafish performs phototaxis, i.e. actively orients towards a light source. Key to this process is a self-oscillating hindbrain population (HBO) that acts as a pacemaker for ocular saccades and controls the orientation of successive swim-bouts. It further integrates visual stimuli in a state-dependent manner, i.e. its response to visual inputs varies with the motor context, a mechanism that manifests itself in the phase-locked entrainment of the HBO by periodic stimuli. A rate model is developed that reproduces our observations and demonstrates how this sensorimotor processing eventually biases the animal trajectory towards bright regions

    Attention model of binocular rivalry

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    This is the final version of the article. Available from National Academy of Sciences from the DOI in this record.When the corresponding retinal locations in the two eyes are presented with incompatible images, a stable percept gives way to perceptual alternations in which the two images compete for perceptual dominance. As perceptual experience evolves dynamically under constant external inputs, binocular rivalry has been used for studying intrinsic cortical computations and for understanding how the brain regulates competing inputs. Converging behavioral and EEG results have shown that binocular rivalry and attention are intertwined: binocular rivalry ceases when attention is diverted away from the rivalry stimuli. In addition, the competing image in one eye suppresses the target in the other eye through a pattern of gain changes similar to those induced by attention. These results require a revision of the current computational theories of binocular rivalry, in which the role of attention is ignored. Here, we provide a computational model of binocular rivalry. In the model, competition between two images in rivalry is driven by both attentional modulation and mutual inhibition, which have distinct selectivity (feature vs. eye of origin) and dynamics (relatively slow vs. relatively fast). The proposed model explains a wide range of phenomena reported in rivalry, including the three hallmarks: (i) binocular rivalry requires attention; (ii) various perceptual states emerge when the two images are swapped between the eyes multiple times per second; (iii) the dominance duration as a function of input strength follows Levelt’s propositions. With a bifurcation analysis, we identified the parameter space in which the model’s behavior was consistent with experimental results.This work was supported by NIH National Eye Institute Grants R01-EY019693 (to M.C. and D.J.H.) and R01-EY025673 (to D.J.H.). H.-H.L. was supported by NIH Grant R90DA043849. J. Rankin was supported by the Swartz Foundation

    Canonical Cortical Circuit Model Explains Rivalry, Intermittent Rivalry, and Rivalry Memory

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    <div><p>It has been shown that the same canonical cortical circuit model with mutual inhibition and a fatigue process can explain perceptual rivalry and other neurophysiological responses to a range of static stimuli. However, it has been proposed that this model cannot explain responses to dynamic inputs such as found in intermittent rivalry and rivalry memory, where maintenance of a percept when the stimulus is absent is required. This challenges the universality of the basic canonical cortical circuit. Here, we show that by including an overlooked realistic small nonspecific background neural activity, the same basic model can reproduce intermittent rivalry and rivalry memory without compromising static rivalry and other cortical phenomena. The background activity induces a mutual-inhibition mechanism for short-term memory, which is robust to noise and where fine-tuning of recurrent excitation or inclusion of sub-threshold currents or synaptic facilitation is unnecessary. We prove existence conditions for the mechanism and show that it can explain experimental results from the quartet apparent motion illusion, which is a prototypical intermittent rivalry stimulus.</p></div

    Auditory streaming emerges from fast excitation and slow delayed inhibition

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    This is the final version. Available on open access from Springer via the DOI in this recordAvailability of data and materials: Source code to reproduce the results presented are available on a public GitHub repository at https://github.com/ferrarioa5/ferrario_rankin2021.git.In the auditory streaming paradigm, alternating sequences of pure tones can be perceived as a single galloping rhythm (integration) or as two sequences with separated low and high tones (segregation). Although studied for decades, the neural mechanisms underlining this perceptual grouping of sound remains a mystery. With the aim of identifying a plausible minimal neural circuit that captures this phenomenon, we propose a firing rate model with two periodically forced neural populations coupled by fast direct excitation and slow delayed inhibition. By analyzing the model in a non-smooth, slow-fast regime we analytically prove the existence of a rich repertoire of dynamical states and of their parameter dependent transitions. We impose plausible parameter restrictions and link all states with perceptual interpretations. Regions of stimulus parameters occupied by states linked with each percept match those found in behavioural experiments. Our model suggests that slow inhibition masks the perception of subsequent tones during segregation (forward masking), whereas fast excitation enables integration for large pitch differences between the two tones.Engineering and Physical Sciences Research Council (EPSRC

    Experimental Manipulation of Action Perception Based on Modeling Computations in Visual Cortex

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    Action perception, planning and execution is a broad area of study, crucial for future development of clinical therapies treating social cognitive disorders, as well as for building human-computer interaction systems and for giving foundation to an emerging field of developmental robotics. We took interest in basic mechanisms of action perception, and as a model area chose dynamic perception of body motion. The focus of this thesis has been on understanding how perception of actions can be manipulated, how to distill this understanding experimentally, and how to summarize via numerical simulation the neural mechanisms helping explain observed dynamic phenomena. Experimentally we have, first, shown how a careful manipulation of a static object depth cue can in principle modulate perception of actions. We chose the luminance gradient as a model cue, and linked action perception to a perceptual prior previously studied in object recognition – the lighting from above-prior. Second, we have explored the dynamic relationship between representations of actions that are naturally observed in spatiotemporal proximity. We have shown an adaptation aftereffect that may speak of brain mechanisms encoding social interactions. To qualitatively capture neural mechanisms behind ours and previous findings, we have additionally appealed to the perceptual bistability phenomenon. Bistable perception refers to the ability to spontaneously switch between two perceptual alternatives arising from an observation of a single stimulus. Addition of depth cues to biological motion stimulus resolves depth-ambiguity. To account for neural dynamics as well as for modulation of action percept by light source position, we used a combined architecture with a convolutional neural network computing shading and form features in biological motion stimuli, and a 2-dimensional neural field coding for walking direction and body configuration in the gait cycle. This single unified model matches experimentally observed switching statistics, dependence of recognized walking direction on the light source position, and makes a prediction for the adaptation aftereffect in perception of biological motion

    26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

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    This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)
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