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Melland P, Curtu R. Attractor-Like Dynamics Extracted from Human Electrocorticographic Recordings Underlie Computational Principles of Auditory Bistable Perception. J Neurosci 2023; 43:3294-3311. [PMID: 36977581 PMCID: PMC10162465 DOI: 10.1523/jneurosci.1531-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 03/03/2023] [Accepted: 03/15/2023] [Indexed: 03/30/2023] Open
Abstract
In bistable perception, observers experience alternations between two interpretations of an unchanging stimulus. Neurophysiological studies of bistable perception typically partition neural measurements into stimulus-based epochs and assess neuronal differences between epochs based on subjects' perceptual reports. Computational studies replicate statistical properties of percept durations with modeling principles like competitive attractors or Bayesian inference. However, bridging neuro-behavioral findings with modeling theory requires the analysis of single-trial dynamic data. Here, we propose an algorithm for extracting nonstationary timeseries features from single-trial electrocorticography (ECoG) data. We applied the proposed algorithm to 5-min ECoG recordings from human primary auditory cortex obtained during perceptual alternations in an auditory triplet streaming task (six subjects: four male, two female). We report two ensembles of emergent neuronal features in all trial blocks. One ensemble consists of periodic functions that encode a stereotypical response to the stimulus. The other comprises more transient features and encodes dynamics associated with bistable perception at multiple time scales: minutes (within-trial alternations), seconds (duration of individual percepts), and milliseconds (switches between percepts). Within the second ensemble, we identified a slowly drifting rhythm that correlates with the perceptual states and several oscillators with phase shifts near perceptual switches. Projections of single-trial ECoG data onto these features establish low-dimensional attractor-like geometric structures invariant across subjects and stimulus types. These findings provide supporting neural evidence for computational models with oscillatory-driven attractor-based principles. The feature extraction techniques described here generalize across recording modality and are appropriate when hypothesized low-dimensional dynamics characterize an underlying neural system.SIGNIFICANCE STATEMENT Irrespective of the sensory modality, neurophysiological studies of multistable perception have typically investigated events time-locked to the perceptual switching rather than the time course of the perceptual states per se. Here, we propose an algorithm that extracts neuronal features of bistable auditory perception from largescale single-trial data while remaining agnostic to the subject's perceptual reports. The algorithm captures the dynamics of perception at multiple timescales, minutes (within-trial alternations), seconds (durations of individual percepts), and milliseconds (timing of switches), and distinguishes attributes of neural encoding of the stimulus from those encoding the perceptual states. Finally, our analysis identifies a set of latent variables that exhibit alternating dynamics along a low-dimensional manifold, similar to trajectories in attractor-based models for perceptual bistability.
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Affiliation(s)
- Pake Melland
- Department of Mathematics, Southern Methodist University, Dallas, Texas 75275
- Applied Mathematical & Computational Sciences, The University of Iowa, Iowa City, Iowa 52242
| | - Rodica Curtu
- Department of Mathematics, The University of Iowa, Iowa City, Iowa 52242
- The Iowa Neuroscience Institute, The University of Iowa, Iowa City, Iowa 52242
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2
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Barkdoll K, Lu Y, Barranca VJ. New insights into binocular rivalry from the reconstruction of evolving percepts using model network dynamics. Front Comput Neurosci 2023; 17:1137015. [PMID: 37034441 PMCID: PMC10079880 DOI: 10.3389/fncom.2023.1137015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 03/07/2023] [Indexed: 04/11/2023] Open
Abstract
When the two eyes are presented with highly distinct stimuli, the resulting visual percept generally switches every few seconds between the two monocular images in an irregular fashion, giving rise to a phenomenon known as binocular rivalry. While a host of theoretical studies have explored potential mechanisms for binocular rivalry in the context of evoked model dynamics in response to simple stimuli, here we investigate binocular rivalry directly through complex stimulus reconstructions based on the activity of a two-layer neuronal network model with competing downstream pools driven by disparate monocular stimuli composed of image pixels. To estimate the dynamic percept, we derive a linear input-output mapping rooted in the non-linear network dynamics and iteratively apply compressive sensing techniques for signal recovery. Utilizing a dominance metric, we are able to identify when percept alternations occur and use data collected during each dominance period to generate a sequence of percept reconstructions. We show that despite the approximate nature of the input-output mapping and the significant reduction in neurons downstream relative to stimulus pixels, the dominant monocular image is well-encoded in the network dynamics and improvements are garnered when realistic spatial receptive field structure is incorporated into the feedforward connectivity. Our model demonstrates gamma-distributed dominance durations and well obeys Levelt's four laws for how dominance durations change with stimulus strength, agreeing with key recurring experimental observations often used to benchmark rivalry models. In light of evidence that individuals with autism exhibit relatively slow percept switching in binocular rivalry, we corroborate the ubiquitous hypothesis that autism manifests from reduced inhibition in the brain by systematically probing our model alternation rate across choices of inhibition strength. We exhibit sufficient conditions for producing binocular rivalry in the context of natural scene stimuli, opening a clearer window into the dynamic brain computations that vary with the generated percept and a potential path toward further understanding neurological disorders.
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Alternative female and male developmental trajectories in the dynamic balance of human visual perception. Sci Rep 2022; 12:1674. [PMID: 35102227 PMCID: PMC8803928 DOI: 10.1038/s41598-022-05620-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 12/17/2021] [Indexed: 12/21/2022] Open
Abstract
The numerous multistable phenomena in vision, hearing and touch attest that the inner workings of perception are prone to instability. We investigated a visual example-binocular rivalry-with an accurate no-report paradigm, and uncovered developmental and maturational lifespan trajectories that were specific for age and sex. To interpret these trajectories, we hypothesized that conflicting objectives of visual perception-such as stability of appearance, sensitivity to visual detail, and exploration of fundamental alternatives-change in relative importance over the lifespan. Computational modelling of our empirical results allowed us to estimate this putative development of stability, sensitivity, and exploration over the lifespan. Our results confirmed prior findings of developmental psychology and appear to quantify important aspects of neurocognitive phenotype. Additionally, we report atypical function of binocular rivalry in autism spectrum disorder and borderline personality disorder. Our computational approach offers new ways of quantifying neurocognitive phenotypes both in development and in dysfunction.
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Ferrario A, Rankin J. Auditory streaming emerges from fast excitation and slow delayed inhibition. JOURNAL OF MATHEMATICAL NEUROSCIENCE 2021; 11:8. [PMID: 33939042 PMCID: PMC8093365 DOI: 10.1186/s13408-021-00106-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 04/22/2021] [Indexed: 05/29/2023]
Abstract
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.
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Affiliation(s)
- Andrea Ferrario
- Department of Mathematics, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter, UK.
| | - James Rankin
- Department of Mathematics, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter, UK
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5
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Dynamics of a Mutual Inhibition Circuit between Pyramidal Neurons Compared to Human Perceptual Competition. J Neurosci 2021; 41:1251-1264. [PMID: 33443089 DOI: 10.1523/jneurosci.2503-20.2020] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 11/16/2020] [Accepted: 12/09/2020] [Indexed: 11/21/2022] Open
Abstract
Neural competition plays an essential role in active selection processes of noisy and ambiguous input signals, and it is assumed to underlie emergent properties of brain functioning, such as perceptual organization and decision-making. Despite ample theoretical research on neural competition, experimental tools to allow neurophysiological investigation of competing neurons have not been available. We developed a "hybrid" system where real-life neurons and a computer-simulated neural circuit interacted. It enabled us to construct a mutual inhibition circuit between two real-life pyramidal neurons. We then asked what dynamics this minimal unit of neural competition exhibits and compared them with the known behavioral-level dynamics of neural competition. We found that the pair of neurons shows bistability when activated simultaneously by current injections. The addition of modeled synaptic noise and changes in the activation strength showed that the dynamics of the circuit are strikingly similar to the known properties of bistable visual perception: The distribution of dominance durations showed a right-skewed shape, and the changes of the activation strengths caused changes in dominance, dominance durations, and reversal rates as stated in the well-known empirical laws of bistable perception known as Levelt's propositions.SIGNIFICANCE STATEMENT Visual perception emerges as the result of neural systems actively organizing visual signals that involves selection processes of competing neurons. While the neural competition, realized by a "mutual inhibition" circuit has been examined in many theoretical studies, its properties have not been investigated in real neurons. We have developed a "hybrid" system where two real-life pyramidal neurons in a mouse brain slice interact through a computer-simulated mutual inhibition circuit. We found that simultaneous activation of the neurons leads to bistable activity. We investigated the effect of noise and the effect of changes in the activation strength on the dynamics. We observed that the pair of neurons exhibit dynamics strikingly similar to the known properties of bistable visual perception.
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Generation of Sharp Wave-Ripple Events by Disinhibition. J Neurosci 2020; 40:7811-7836. [PMID: 32913107 PMCID: PMC7548694 DOI: 10.1523/jneurosci.2174-19.2020] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 06/29/2020] [Accepted: 07/17/2020] [Indexed: 11/21/2022] Open
Abstract
Sharp wave-ripple complexes (SWRs) are hippocampal network phenomena involved in memory consolidation. To date, the mechanisms underlying their occurrence remain obscure. Here, we show how the interactions between pyramidal cells, parvalbumin-positive (PV+) basket cells, and an unidentified class of anti-SWR interneurons can contribute to the initiation and termination of SWRs. Using a biophysically constrained model of a network of spiking neurons and a rate-model approximation, we demonstrate that SWRs emerge as a result of the competition between two interneuron populations and the resulting disinhibition of pyramidal cells. Our models explain how the activation of pyramidal cells or PV+ cells can trigger SWRs, as shown in vitro, and suggests that PV+ cell-mediated short-term synaptic depression influences the experimentally reported dynamics of SWR events. Furthermore, we predict that the silencing of anti-SWR interneurons can trigger SWRs. These results broaden our understanding of the microcircuits supporting the generation of memory-related network dynamics. SIGNIFICANCE STATEMENT The hippocampus is a part of the mammalian brain that is crucial for episodic memories. During periods of sleep and inactive waking, the extracellular activity of the hippocampus is dominated by sharp wave-ripple events (SWRs), which have been shown to be important for memory consolidation. The mechanisms regulating the emergence of these events are still unclear. We developed a computational model to study the emergence of SWRs and to explain the roles of different cell types in regulating them. The model accounts for several previously unexplained features of SWRs and thus advances the understanding of memory-related dynamics.
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7
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Nguyen QA, Rinzel J, Curtu R. Buildup and bistability in auditory streaming as an evidence accumulation process with saturation. PLoS Comput Biol 2020; 16:e1008152. [PMID: 32853256 PMCID: PMC7480857 DOI: 10.1371/journal.pcbi.1008152] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 09/09/2020] [Accepted: 07/15/2020] [Indexed: 12/23/2022] Open
Abstract
A repeating triplet-sequence ABA- of non-overlapping brief tones, A and B, is a valued paradigm for studying auditory stream formation and the cocktail party problem. The stimulus is "heard" either as a galloping pattern (integration) or as two interleaved streams (segregation); the initial percept is typically integration then followed by spontaneous alternations between segregation and integration, each being dominant for a few seconds. The probability of segregation grows over seconds, from near-zero to a steady value, defining the buildup function, BUF. Its stationary level increases with the difference in tone frequencies, DF, and the BUF rises faster. Percept durations have DF-dependent means and are gamma-like distributed. Behavioral and computational studies usually characterize triplet streaming either during alternations or during buildup. Here, our experimental design and modeling encompass both. We propose a pseudo-neuromechanistic model that incorporates spiking activity in primary auditory cortex, A1, as input and resolves perception along two network-layers downstream of A1. Our model is straightforward and intuitive. It describes the noisy accumulation of evidence against the current percept which generates switches when reaching a threshold. Accumulation can saturate either above or below threshold; if below, the switching dynamics resemble noise-induced transitions from an attractor state. Our model accounts quantitatively for three key features of data: the BUFs, mean durations, and normalized dominance duration distributions, at various DF values. It describes perceptual alternations without competition per se, and underscores that treating triplets in the sequence independently and averaging across trials, as implemented in earlier widely cited studies, is inadequate.
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Affiliation(s)
- Quynh-Anh Nguyen
- Department of Mathematics, The University of Iowa, Iowa City, Iowa, United States of America
| | - John Rinzel
- Center for Neural Science, New York University, New York, New York, United States of America
- Courant Institute of Mathematical Sciences, New York University, New York, New York, United States of America
| | - Rodica Curtu
- Department of Mathematics, The University of Iowa, Iowa City, Iowa, United States of America
- Iowa Neuroscience Institute, Human Brain Research Laboratory, Iowa City, Iowa, United States of America
- * E-mail:
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Darki F, Rankin J. Methods to assess binocular rivalry with periodic stimuli. JOURNAL OF MATHEMATICAL NEUROSCIENCE 2020; 10:10. [PMID: 32542516 PMCID: PMC7295892 DOI: 10.1186/s13408-020-00087-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 06/04/2020] [Indexed: 05/29/2023]
Abstract
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.
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Affiliation(s)
- Farzaneh Darki
- Department of Mathematics, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter, UK.
| | - James Rankin
- Department of Mathematics, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter, UK
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9
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A hierarchical model of perceptual multistability involving interocular grouping. J Comput Neurosci 2020; 48:177-192. [PMID: 32338341 DOI: 10.1007/s10827-020-00743-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 02/04/2020] [Accepted: 02/11/2020] [Indexed: 10/24/2022]
Abstract
Ambiguous visual images can generate dynamic and stochastic switches in perceptual interpretation known as perceptual rivalry. Such dynamics have primarily been studied in the context of rivalry between two percepts, but there is growing interest in the neural mechanisms that drive rivalry between more than two percepts. In recent experiments, we showed that split images presented to each eye lead to subjects perceiving four stochastically alternating percepts (Jacot-Guillarmod et al. Vision research, 133, 37-46, 2017): two single eye images and two interocularly grouped images. Here we propose a hierarchical neural network model that exhibits dynamics consistent with our experimental observations. The model consists of two levels, with the first representing monocular activity, and the second representing activity in higher visual areas. The model produces stochastically switching solutions, whose dependence on task parameters is consistent with four generalized Levelt Propositions, and with experiments. Moreover, dynamics restricted to invariant subspaces of the model demonstrate simpler forms of bistable rivalry. Thus, our hierarchical model generalizes past, validated models of binocular rivalry. This neuromechanistic model also allows us to probe the roles of interactions between populations at the network level. Generalized Levelt's Propositions hold as long as feedback from the higher to lower visual areas is weak, and the adaptation and mutual inhibition at the higher level is not too strong. Our results suggest constraints on the architecture of the visual system and show that complex visual stimuli can be used in perceptual rivalry experiments to develop more detailed mechanistic models of perceptual processing.
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10
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Zhang-Molina C, Schmit MB, Cai H. Neural Circuit Mechanism Underlying the Feeding Controlled by Insula-Central Amygdala Pathway. iScience 2020; 23:101033. [PMID: 32311583 PMCID: PMC7168768 DOI: 10.1016/j.isci.2020.101033] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 01/02/2020] [Accepted: 03/31/2020] [Indexed: 12/16/2022] Open
Abstract
The Central nucleus of amygdala (CeA) contains distinct populations of neurons that play opposing roles in feeding. The circuit mechanism of how CeA neurons process information sent from their upstream inputs to regulate feeding is still unclear. Here we show that activation of the neural pathway projecting from insular cortex neurons to the CeA suppresses food intake. Surprisingly, we find that the inputs from insular cortex form excitatory connections with similar strength to all types of CeA neurons. To reconcile this puzzling result, and previous findings, we developed a conductance-based dynamical systems model for the CeA neuronal network. Computer simulations showed that both the intrinsic electrophysiological properties of individual CeA neurons and the overall synaptic organization of the CeA circuit play a functionally significant role in shaping CeA neural dynamics. We successfully identified a specific CeA circuit structure that reproduces the desired circuit output consistent with existing experimentally observed feeding behaviors. Activation of the insular cortex→central amygdala (CeA) pathway suppresses feeding Insular cortex neurons send similar excitatory inputs to different types of CeA neurons Model suggests a required circuit with both late firing and regular spiking cells The circuit model can explain current and previous CeA-mediated feeding behaviors
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Affiliation(s)
| | - Matthew B Schmit
- Department of Neuroscience, University of Arizona, Tucson, AZ 85721, USA; Graduate Interdisciplinary Program in Neuroscience, University of Arizona, Tucson, AZ 85721, USA
| | - Haijiang Cai
- Department of Neuroscience, University of Arizona, Tucson, AZ 85721, USA; Bio5 Institute and Department of Neurology, University of Arizona, Tucson, AZ 85721, USA.
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11
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A neural network model for exogenous perceptual alternations of the Necker cube. Cogn Neurodyn 2019; 14:229-237. [PMID: 32226564 DOI: 10.1007/s11571-019-09565-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2019] [Revised: 09/20/2019] [Accepted: 11/22/2019] [Indexed: 10/25/2022] Open
Abstract
When a bistable visual image, such as the Necker cube, is continuously viewed, the percept of the image endogenously alternates between one possible percept and the other. However, perceptual alternation can also be induced by an exogenous perturbation. For example, a typical external perturbation is the flashlight, which is expected to pervasively activate many brain regions. Therefore, the neural mechanism related to exogenous perceptual alternation remains to be clarified. As a cue to solving this problem, our recent psychophysiological experiment reported a positive correlation between the enhancement of visual mismatch negativity evoked by breaks in the sequential regularity of the visual stimuli and the proportion of perceptual alternation. To elucidate the mechanism underlying exogenous perceptual alternation induced by visual mismatch negativity, the present study attempted to construct a neural network model for bistable perception of the Necker cube, whose perceptual alternation is facilitated by an increase in visual mismatch negativity. The model consists of both a prediction layer and a prediction error layer, following the predictive coding framework for biologically plausible relationships between the change detection process and the perceptual alternation mechanism. Computer simulations showed that the mean duration of perception decreased as the response increased, which is in concordance with the experimental data. This result suggested that the excitatory feedforward and inhibitory feedback connections play an important role. Additionally, the validity of this model suggests that the visual mismatch signal propagates in the neural systems and affects the visual perceptual mechanism as a prediction error signal.
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Golubitsky M, Zhao Y, Wang Y, Lu ZL. Symmetry of generalized rivalry network models determines patterns of interocular grouping in four-location binocular rivalry. J Neurophysiol 2019; 122:1989-1999. [PMID: 31533006 DOI: 10.1152/jn.00438.2019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Previously, symmetry of network models has been proposed to account for interocular grouping during binocular rivalry. Here, we construct and analyze generalized rivalry network models with different types of symmetry (based on different kinds of excitatory coupling) to derive predictions of possible perceptual states in 12 experiments with four retinal locations. Percepts in binocular rivalry involving more than three locations have not been empirically investigated due to the difficulty in reporting simultaneous percepts at multiple locations. Here, we develop a novel reporting procedure in which the stimulus disappears when the subject is cued to report the simultaneously perceived colors in all four retinal locations. This procedure ensures that simultaneous rather than sequential percepts are reported. The procedure was applied in 12 experiments with six binocular rivalry stimulus configurations, all consisting of dichoptic displays of red and green squares at four locations. We call configurations with an even or odd number of red squares even or odd configurations, respectively. In experiments using even stimulus configurations, we found that even percepts were more frequently observed than odd percepts, whereas in experiments using odd stimulus configurations even and odd percepts were observed with equal probability. The generalized rivalry network models in which couplings depend on stimulus features and spatial configurations was in better agreement with the empirical results. We conclude that the excitatory coupling strength in the horizontal and vertical configurations are different and the coupling strengths between the same color and between different colors are different.NEW & NOTEWORTHY Wilson network models of interocular groupings during binocular rivalry are constructed by considering features that indicate equal coupling strengths. Network symmetries, based on equal couplings, predict percepts. For a four-location rivalry experiment with red or green squares at each location, we analyze different possible Wilson networks. In our experiments we develop a novel reporting procedure and show that networks in which stimulus features and spatial configurations are distinguished best agree with experiments.
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Affiliation(s)
- Martin Golubitsky
- Department of Mathematics, The Ohio State University, Columbus, Ohio
| | - Yukai Zhao
- Department of Psychology, The Ohio State University, Columbus, Ohio
| | - Yunjiao Wang
- Department of Mathematics, Texas Southern University, Houston, Texas
| | - Zhong-Lin Lu
- Division of Arts and Sciences, NYU Shanghai, Shanghai, China.,Center for Neural Science and Department of Psychology, New York University, New York, New York.,NYU-ECNU Institute of Brain and Cognitive Neuroscience, Shanghai, China
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13
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Cohen BP, Chow CC, Vattikuti S. Dynamical modeling of multi-scale variability in neuronal competition. Commun Biol 2019; 2:319. [PMID: 31453383 PMCID: PMC6707190 DOI: 10.1038/s42003-019-0555-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 07/15/2019] [Indexed: 01/03/2023] Open
Abstract
Variability is observed at multiple-scales in the brain and ubiquitous in perception. However, the nature of perceptual variability is an open question. We focus on variability during perceptual rivalry, a form of neuronal competition. Rivalry provides a window into neural processing since activity in many brain areas is correlated to the alternating perception rather than a constant ambiguous stimulus. It exhibits robust properties at multiple scales including conscious awareness and neuron dynamics. The prevalent theory for spiking variability is called the balanced state; whereas, the source of perceptual variability is unknown. Here we show that a single biophysical circuit model, satisfying certain mutual inhibition architectures, can explain spiking and perceptual variability during rivalry. These models adhere to a broad set of strict experimental constraints at multiple scales. As we show, the models predict how spiking and perceptual variability changes with stimulus conditions.
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Affiliation(s)
- Benjamin P. Cohen
- Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, MD USA
| | - Carson C. Chow
- Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, MD USA
| | - Shashaank Vattikuti
- Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, MD USA
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Neural Signatures of Auditory Perceptual Bistability Revealed by Large-Scale Human Intracranial Recordings. J Neurosci 2019; 39:6482-6497. [PMID: 31189576 PMCID: PMC6697394 DOI: 10.1523/jneurosci.0655-18.2019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 05/26/2019] [Accepted: 05/28/2019] [Indexed: 11/25/2022] Open
Abstract
A key challenge in neuroscience is understanding how sensory stimuli give rise to perception, especially when the process is supported by neural activity from an extended network of brain areas. Perception is inherently subjective, so interrogating its neural signatures requires, ideally, a combination of three factors: (1) behavioral tasks that separate stimulus-driven activity from perception per se; (2) human subjects who self-report their percepts while performing those tasks; and (3) concurrent neural recordings acquired at high spatial and temporal resolution. In this study, we analyzed human electrocorticographic recordings obtained during an auditory task which supported mutually exclusive perceptual interpretations. Eight neurosurgical patients (5 male; 3 female) listened to sequences of repeated triplets where tones were separated in frequency by several semitones. Subjects reported spontaneous alternations between two auditory perceptual states, 1-stream and 2-stream, by pressing a button. We compared averaged auditory evoked potentials (AEPs) associated with 1-stream and 2-stream percepts and identified significant differences between them in primary and nonprimary auditory cortex, surrounding auditory-related temporoparietal cortex, and frontal areas. We developed classifiers to identify spatial maps of percept-related differences in the AEP, corroborating findings from statistical analysis. We used one-dimensional embedding spaces to perform the group-level analysis. Our data illustrate exemplar high temporal resolution AEP waveforms in auditory core region; explain inconsistencies in perceptual effects within auditory cortex, reported across noninvasive studies of streaming of triplets; show percept-related changes in frontoparietal areas previously highlighted by studies that focused on perceptual transitions; and demonstrate that auditory cortex encodes maintenance of percepts and switches between them. SIGNIFICANCE STATEMENT The human brain has the remarkable ability to discern complex and ambiguous stimuli from the external world by parsing mixed inputs into interpretable segments. However, one's perception can deviate from objective reality. But how do perceptual discrepancies occur? What are their anatomical substrates? To address these questions, we performed intracranial recordings in neurosurgical patients as they reported their perception of sounds associated with two mutually exclusive interpretations. We identified signatures of subjective percepts as distinct from sound-driven brain activity in core and non-core auditory cortex and frontoparietal cortex. These findings were compared with previous studies of auditory bistable perception and suggested that perceptual transitions and maintenance of perceptual states were supported by common neural substrates.
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Abstract
Multistable illusions occur when the visual system interprets the same image in two different ways. We model illusions using dynamic systems based on Wilson networks, which detect combinations of levels of attributes of the image. In most examples presented here, the network has symmetry, which is vital to the analysis of the dynamics. We assume that the visual system has previously learned that certain combinations are geometrically consistent or inconsistent, and model this knowledge by adding suitable excitatory and inhibitory connections between attribute levels. We first discuss 4-node networks for the Necker cube and the rabbit/duck illusion. The main results analyze a more elaborate model for the Necker cube, a 16-node Wilson network whose nodes represent alternative orientations of specific segments of the image. Symmetric Hopf bifurcation is used to show that a small list of natural local geometric consistency conditions leads to alternation between two global percepts: cubes in two different orientations. The model also predicts brief transitional states in which the percept involves impossible rectangles analogous to the Penrose triangle. A tristable illusion generalizing the Necker cube is modelled in a similar manner.
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16
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Bielczyk NZ, Piskała K, Płomecka M, Radziński P, Todorova L, Foryś U. Time-delay model of perceptual decision making in cortical networks. PLoS One 2019; 14:e0211885. [PMID: 30768608 PMCID: PMC6377186 DOI: 10.1371/journal.pone.0211885] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 01/23/2019] [Indexed: 11/18/2022] Open
Abstract
It is known that cortical networks operate on the edge of instability, in which oscillations can appear. However, the influence of this dynamic regime on performance in decision making, is not well understood. In this work, we propose a population model of decision making based on a winner-take-all mechanism. Using this model, we demonstrate that local slow inhibition within the competing neuronal populations can lead to Hopf bifurcation. At the edge of instability, the system exhibits ambiguity in the decision making, which can account for the perceptual switches observed in human experiments. We further validate this model with fMRI datasets from an experiment on semantic priming in perception of ambivalent (male versus female) faces. We demonstrate that the model can correctly predict the drop in the variance of the BOLD within the Superior Parietal Area and Inferior Parietal Area while watching ambiguous visual stimuli.
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Affiliation(s)
| | | | - Martyna Płomecka
- Methods of Plasticity Research, Department of Psychology, University of Zürich, Zürich, Switzerland
- Laboratory of Brain Imaging, Neurobiology Center, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Piotr Radziński
- Faculty of Mathematics, University of Warsaw, Warsaw, Poland
| | - Lara Todorova
- Faculty of Social Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behavior, Nijmegen, the Netherlands
| | - Urszula Foryś
- Faculty of Mathematics, University of Warsaw, Warsaw, Poland
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17
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Lankow BS, Goldman MS. Competing inhibition-stabilized networks in sensory and memory processing. CONFERENCE RECORD. ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS 2018; 2018:97-103. [PMID: 35859653 PMCID: PMC9293748 DOI: 10.1109/acssc.2018.8645209] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In simplified models of neocortical circuits, inhibition is either modeled in a feedforward manner or through mutual inhibitory interactions that provide for competition between neuronal populations. By contrast, recent work has suggested a critical role for recurrent inhibition as a negative feedback element that stabilizes otherwise unstable recurrent excitation. Here, we show how models based upon a motif of recurrently connected "E-I" pairs of excitatory and inhibitory units can be used to describe experimental observations in sensory and memory networks. In a sensory network model of binocular rivalry, a model based on competing E-I motifs captures psychophysical observations about how incongruous images presented to the two eyes compete. In a model of cortical working memory, an architecturally similar model with modified synaptic time constants can mathematically accumulate signals into a working memory buffer in a manner that is robust to the abrupt removal of cells. These results suggest the inhibition-stabilized E-I motif as a fundamental building block for models of a wide array of neocortical dynamics.
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Affiliation(s)
- Benjamin S Lankow
- Center for Neuroscience, University of California at Davis, Davis, USA
| | - Mark S Goldman
- Dept of Neurobiology, Physiology, and Behavior, University of California at Davis, Davis, USA
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18
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Varshney V, Saxena G, Biswal B, Prasad A. Oscillation death and revival by coupling with damped harmonic oscillator. CHAOS (WOODBURY, N.Y.) 2017; 27:093104. [PMID: 28964117 DOI: 10.1063/1.4990482] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Dynamics of nonlinear oscillators augmented with co- and counter-rotating linear damped harmonic oscillator is studied in detail. Depending upon the sense of rotation of augmenting system, the collective dynamics converges to either synchronized periodic behaviour or oscillation death. Multistability is observed when there is a transition from periodic state to oscillation death. In the periodic region, the system is found to be in mixed synchronization state, which is characterized by the newly defined "relative phase angle" between the different axes.
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Affiliation(s)
- Vaibhav Varshney
- Department of Physics and Astrophysics, University of Delhi, Delhi 110007, India
| | - Garima Saxena
- Sri Venkateswara College, University of Delhi, Delhi 110021, India
| | - Bibhu Biswal
- Cluster Innovation Center, University of Delhi, Delhi 110007, India
| | - Awadhesh Prasad
- Department of Physics and Astrophysics, University of Delhi, Delhi 110007, India
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19
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Abstract
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.
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20
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Vattikuti S, Thangaraj P, Xie HW, Gotts SJ, Martin A, Chow CC. Canonical Cortical Circuit Model Explains Rivalry, Intermittent Rivalry, and Rivalry Memory. PLoS Comput Biol 2016; 12:e1004903. [PMID: 27138214 PMCID: PMC4854419 DOI: 10.1371/journal.pcbi.1004903] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2015] [Accepted: 04/06/2016] [Indexed: 01/10/2023] Open
Abstract
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. When the brain is presented with an ambiguous stimulus like the Necker cube or what is known as the quartet illusion, the perception will alternate or rival between the possible interpretations. There are neurons in the brain whose activity is correlated with the perception and not the stimulus. Hence, perceptual rivalry provides a unique probe of cortical function and could possibly serve as a diagnostic tool for cognitive disorders such as autism. A mathematical model based on the known biology of the brain has been developed to account for perceptual rivalry when the stimulus is static. The basic model also accounts for other neural responses to stimuli that do not elicit rivalry. However, these models cannot explain illusions where the stimulus is intermittently switched on and off and the same perception returns after an off period because there is no built-in mechanism to hold the memory. Here, we show that the inclusion of experimentally observed low-level background neural activity is sufficient to explain rivalry for static inputs, and rivalry for intermittent inputs. We validate the model with new experiments.
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Affiliation(s)
- Shashaank Vattikuti
- Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (SV); (CCC)
| | - Phyllis Thangaraj
- Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Hua W. Xie
- Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Stephen J. Gotts
- Cognitive Neuropsychology Section, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Alex Martin
- Cognitive Neuropsychology Section, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Carson C. Chow
- Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (SV); (CCC)
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21
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Brascamp JW, Klink PC, Levelt WJM. The 'laws' of binocular rivalry: 50 years of Levelt's propositions. Vision Res 2015; 109:20-37. [PMID: 25749677 DOI: 10.1016/j.visres.2015.02.019] [Citation(s) in RCA: 109] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2015] [Revised: 02/13/2015] [Accepted: 02/19/2015] [Indexed: 11/26/2022]
Abstract
It has been fifty years since Levelt's monograph On Binocular Rivalry (1965) was published, but its four propositions that describe the relation between stimulus strength and the phenomenology of binocular rivalry remain a benchmark for theorists and experimentalists even today. In this review, we will revisit the original conception of the four propositions and the scientific landscape in which this happened. We will also provide a brief update concerning distributions of dominance durations, another aspect of Levelt's monograph that has maintained a prominent presence in the field. In a critical evaluation of Levelt's propositions against current knowledge of binocular rivalry we will then demonstrate that the original propositions are not completely compatible with what is known today, but that they can, in a straightforward way, be modified to encapsulate the progress that has been made over the past fifty years. The resulting modified, propositions are shown to apply to a broad range of bistable perceptual phenomena, not just binocular rivalry, and they allow important inferences about the underlying neural systems. We argue that these inferences reflect canonical neural properties that play a role in visual perception in general, and we discuss ways in which future research can build on the work reviewed here to attain a better understanding of these properties.
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Affiliation(s)
- J W Brascamp
- Helmholtz Institute and Division of Experimental Psychology, Department of Psychology, Utrecht University, Utrecht, The Netherlands.
| | - P C Klink
- Vision & Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts & Sciences, Amsterdam, The Netherlands; Neuromodulation & Behaviour, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts & Sciences, Amsterdam, The Netherlands; Department of Psychiatry, Academic Medical Center, University of Amsterdam, The Netherlands
| | - W J M Levelt
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
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22
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Cao R, Braun J, Mattia M. Stochastic accumulation by cortical columns may explain the scalar property of multistable perception. PHYSICAL REVIEW LETTERS 2014; 113:098103. [PMID: 25216009 DOI: 10.1103/physrevlett.113.098103] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2014] [Indexed: 06/03/2023]
Abstract
The timing of certain mental events is thought to reflect random walks performed by underlying neural dynamics. One class of such events--stochastic reversals of multistable perceptions--exhibits a unique scalar property: even though timing densities vary widely, higher moments stay in particular proportions to the mean. We show that stochastic accumulation of activity in a finite number of idealized cortical columns--realizing a generalized Ehrenfest urn model--may explain these observations. Modeling stochastic reversals as the first-passage time of a threshold number of active columns, we obtain higher moments of the first-passage time density. We derive analytical expressions for noninteracting columns and generalize the results to interacting columns in simulations. The scalar property of multistable perception is reproduced by a dynamic regime with a fixed, low threshold, in which the activation of a few additional columns suffices for a reversal.
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Affiliation(s)
- Robin Cao
- Cognitive Biology, Center for Behavioral Brain Sciences, Otto von Guericke University, 39106 Magdeburg, Germany and Department of Technologies and Health, Istituto Superiore di Sanità, 00161 Roma, Italy
| | - Jochen Braun
- Cognitive Biology, Center for Behavioral Brain Sciences, Otto von Guericke University, 39106 Magdeburg, Germany
| | - Maurizio Mattia
- Department of Technologies and Health, Istituto Superiore di Sanità, 00161 Roma, Italy
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23
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Diekman CO, Golubitsky M. Network symmetry and binocular rivalry experiments. JOURNAL OF MATHEMATICAL NEUROSCIENCE 2014; 4:12. [PMID: 24872926 PMCID: PMC4013122 DOI: 10.1186/2190-8567-4-12] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2013] [Accepted: 04/24/2014] [Indexed: 05/29/2023]
Abstract
Hugh Wilson has proposed a class of models that treat higher-level decision making as a competition between patterns coded as levels of a set of attributes in an appropriately defined network (Cortical Mechanisms of Vision, pp. 399-417, 2009; The Constitution of Visual Consciousness: Lessons from Binocular Rivalry, pp. 281-304, 2013). In this paper, we propose that symmetry-breaking Hopf bifurcation from fusion states in suitably modified Wilson networks, which we call rivalry networks, can be used in an algorithmic way to explain the surprising percepts that have been observed in a number of binocular rivalry experiments. These rivalry networks modify and extend Wilson networks by permitting different kinds of attributes and different types of coupling. We apply this algorithm to psychophysics experiments discussed by Kovács et al. (Proc. Natl. Acad. Sci. USA 93:15508-15511, 1996), Shevell and Hong (Vis. Neurosci. 23:561-566, 2006; Vis. Neurosci. 25:355-360, 2008), and Suzuki and Grabowecky (Neuron 36:143-157, 2002). We also analyze an experiment with four colored dots (a simplified version of a 24-dot experiment performed by Kovács), and a three-dot analog of the four-dot experiment. Our algorithm predicts surprising differences between the three- and four-dot experiments.
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Affiliation(s)
- Casey O Diekman
- Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, NJ, 07102, USA
| | - Martin Golubitsky
- Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, 43210, USA
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24
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Wyffels F, Li J, Waegeman T, Schrauwen B, Jaeger H. Frequency modulation of large oscillatory neural networks. BIOLOGICAL CYBERNETICS 2014; 108:145-157. [PMID: 24515094 DOI: 10.1007/s00422-013-0584-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2013] [Accepted: 12/26/2013] [Indexed: 06/03/2023]
Abstract
Dynamical systems which generate periodic signals are of interest as models of biological central pattern generators and in a number of robotic applications. A basic functionality that is required in both biological modelling and robotics is frequency modulation. This leads to the question of whether there are generic mechanisms to control the frequency of neural oscillators. Here we describe why this objective is of a different nature, and more difficult to achieve, than modulating other oscillation characteristics (like amplitude, offset, signal shape). We propose a generic way to solve this task which makes use of a simple linear controller. It rests on the insight that there is a bidirectional dependency between the frequency of an oscillation and geometric properties of the neural oscillator's phase portrait. By controlling the geometry of the neural state orbits, it is possible to control the frequency on the condition that the state space can be shaped such that it can be pushed easily to any frequency.
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Affiliation(s)
- Francis Wyffels
- Electronics and Information Systems Department, Ghent University, Sint-Pietersnieuwstraat 41, 9000 , Ghent, Belgium,
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25
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Rankin J, Meso AI, Masson GS, Faugeras O, Kornprobst P. Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration. J Comput Neurosci 2014; 36:193-213. [PMID: 24014258 PMCID: PMC3950608 DOI: 10.1007/s10827-013-0465-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2013] [Revised: 05/19/2013] [Accepted: 05/20/2013] [Indexed: 11/17/2022]
Abstract
Perceptual multistability is a phenomenon in which alternate interpretations of a fixed stimulus are perceived intermittently. Although correlates between activity in specific cortical areas and perception have been found, the complex patterns of activity and the underlying mechanisms that gate multistable perception are little understood. Here, we present a neural field competition model in which competing states are represented in a continuous feature space. Bifurcation analysis is used to describe the different types of complex spatio-temporal dynamics produced by the model in terms of several parameters and for different inputs. The dynamics of the model was then compared to human perception investigated psychophysically during long presentations of an ambiguous, multistable motion pattern known as the barberpole illusion. In order to do this, the model is operated in a parameter range where known physiological response properties are reproduced whilst also working close to bifurcation. The model accounts for characteristic behaviour from the psychophysical experiments in terms of the type of switching observed and changes in the rate of switching with respect to contrast. In this way, the modelling study sheds light on the underlying mechanisms that drive perceptual switching in different contrast regimes. The general approach presented is applicable to a broad range of perceptual competition problems in which spatial interactions play a role.
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Affiliation(s)
- J Rankin
- Neuromathcomp Team, Inria Sophia Antipolis, 2004 Route des Lucioles-BP 93, Alpes-Maritimes, 06902, France,
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26
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Symmetry-Breaking in a Rate Model for a Biped Locomotion Central Pattern Generator. Symmetry (Basel) 2014. [DOI: 10.3390/sym6010023] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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27
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Platonov A, Goossens J. Influence of contrast and coherence on the temporal dynamics of binocular motion rivalry. PLoS One 2013; 8:e71931. [PMID: 23967265 PMCID: PMC3743782 DOI: 10.1371/journal.pone.0071931] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2013] [Accepted: 07/03/2013] [Indexed: 11/21/2022] Open
Abstract
Levelt’s four propositions (L1–L4), which characterize the relation between changes in “stimulus strength” in the two eyes and percept alternations, are considered benchmark for binocular rivalry models. It was recently demonstrated that adaptation mutual-inhibition models of binocular rivalry capture L4 only in a limited range of input strengths, predicting an increase rather than a decrease in dominance durations with increasing stimulus strength for weak stimuli. This observation challenges the validity of those models, but possibly L4 itself is invalid. So far, L1–L4 have been tested mainly by varying the contrast of static stimuli, but since binocular rivalry breaks down at low contrasts, it has been difficult to study L4. To circumvent this problem, and to test if the recent revision of L2 has more general validity, we studied changes in binocular rivalry evoked by manipulating coherence of oppositely-moving random-dot stimuli in the two eyes, and compared them against the effects of stimulus contrast. Thirteen human observers participated. Both contrast and coherence manipulations in one eye produced robust changes in both eyes; dominance durations of the eye receiving the stronger stimulus increased while those of the other eye decreased, albeit less steeply. This is inconsistent with L2 but supports its revision. When coherence was augmented in both eyes simultaneously, dominance durations first increased at low coherence, and then decreased for further increases in coherence. The same held true for the alternation periods. The initial increase in dominance durations was absent in the contrast experiments, but with coherence manipulations, rivalry could be tested at much lower stimulus strengths. Thus, we found that L4, like L2, is only valid in a limited range of stimulus strengths. Outside that range, the opposite is true. Apparent discrepancies between contrast and coherence experiments could be fully reconciled with adaptation mutual-inhibition models using a simple input transfer-function.
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Affiliation(s)
- Artem Platonov
- Section Biophysics, Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre Nijmegen, Nijmegen, The Netherlands
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28
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Diekman CO, Golubitsky M, Wang Y. Derived patterns in binocular rivalry networks. JOURNAL OF MATHEMATICAL NEUROSCIENCE 2013; 3:6. [PMID: 23657206 PMCID: PMC3698087 DOI: 10.1186/2190-8567-3-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2013] [Accepted: 04/22/2013] [Indexed: 05/08/2023]
Abstract
Binocular rivalry is the alternation in visual perception that can occur when the two eyes are presented with different images. Wilson proposed a class of neuronal network models that generalize rivalry to multiple competing patterns. The networks are assumed to have learned several patterns, and rivalry is identified with time periodic states that have periods of dominance of different patterns. Here, we show that these networks can also support patterns that were not learned, which we call derived. This is important because there is evidence for perception of derived patterns in the binocular rivalry experiments of Kovács, Papathomas, Yang, and Fehér. We construct modified Wilson networks for these experiments and use symmetry breaking to make predictions regarding states that a subject might perceive. Specifically, we modify the networks to include lateral coupling, which is inspired by the known structure of the primary visual cortex. The modified network models make expected the surprising outcomes observed in these experiments.
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Affiliation(s)
- Casey O Diekman
- Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, 43210, USA
| | - Martin Golubitsky
- Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, 43210, USA
| | - Yunjiao Wang
- Department of Mathematics, Texas Southern University, Houston, TX, 77004, USA
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29
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Pastukhov A, García-Rodríguez PE, Haenicke J, Guillamon A, Deco G, Braun J. Multi-stable perception balances stability and sensitivity. Front Comput Neurosci 2013; 7:17. [PMID: 23518509 PMCID: PMC3602966 DOI: 10.3389/fncom.2013.00017] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2012] [Accepted: 03/04/2013] [Indexed: 11/13/2022] Open
Abstract
We report that multi-stable perception operates in a consistent, dynamical regime, balancing the conflicting goals of stability and sensitivity. When a multi-stable visual display is viewed continuously, its phenomenal appearance reverses spontaneously at irregular intervals. We characterized the perceptual dynamics of individual observers in terms of four statistical measures: the distribution of dominance times (mean and variance) and the novel, subtle dependence on prior history (correlation and time-constant). The dynamics of multi-stable perception is known to reflect several stabilizing and destabilizing factors. Phenomenologically, its main aspects are captured by a simplistic computational model with competition, adaptation, and noise. We identified small parameter volumes (~3% of the possible volume) in which the model reproduced both dominance distribution and history-dependence of each observer. For 21 of 24 data sets, the identified volumes clustered tightly (~15% of the possible volume), revealing a consistent "operating regime" of multi-stable perception. The "operating regime" turned out to be marginally stable or, equivalently, near the brink of an oscillatory instability. The chance probability of the observed clustering was <0.02. To understand the functional significance of this empirical "operating regime," we compared it to the theoretical "sweet spot" of the model. We computed this "sweet spot" as the intersection of the parameter volumes in which the model produced stable perceptual outcomes and in which it was sensitive to input modulations. Remarkably, the empirical "operating regime" proved to be largely coextensive with the theoretical "sweet spot." This demonstrated that perceptual dynamics was not merely consistent but also functionally optimized (in that it balances stability with sensitivity). Our results imply that multi-stable perception is not a laboratory curiosity, but reflects a functional optimization of perceptual dynamics for visual inference.
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Affiliation(s)
- Alexander Pastukhov
- Center for Behavioral Brain SciencesMagdeburg, Germany
- Department of Cognitive Biology, Otto-von-Guericke UniversitätMagdeburg, Germany
| | | | - Joachim Haenicke
- Center for Behavioral Brain SciencesMagdeburg, Germany
- Department of Cognitive Biology, Otto-von-Guericke UniversitätMagdeburg, Germany
| | - Antoni Guillamon
- Department de Matemàtica Aplicada I, Universitat Politècnica de CatalunyaBarcelona, Spain
| | - Gustavo Deco
- Institució Catalana de Recerca i Estudis AvançatsBarcelona, Spain
| | - Jochen Braun
- Center for Behavioral Brain SciencesMagdeburg, Germany
- Department of Cognitive Biology, Otto-von-Guericke UniversitätMagdeburg, Germany
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30
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Zhang C, Lewis TJ. Phase response properties of half-center oscillators. J Comput Neurosci 2013; 35:55-74. [PMID: 23456595 DOI: 10.1007/s10827-013-0440-1] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2012] [Revised: 12/18/2012] [Accepted: 01/14/2013] [Indexed: 11/30/2022]
Abstract
We examine the phase response properties of half-center oscillators (HCOs) that are modeled by a pair of Morris-Lecar-type neurons connected by strong fast inhibitory synapses. We find that the two basic mechanisms for half-center oscillations, "release" and "escape", give rise to strikingly different phase response curves (PRCs). Release-type HCOs are most sensitive to perturbations delivered to cells at times when they are about to transition from the active to the suppressed state, and PRCs are dominated by a large negative peak (phase delays) at corresponding phases. On the other hand, escape-type HCOs are most sensitive to perturbations delivered to cells at times when they are about to transition from the suppressed to the active state, and PRCs are dominated by a large positive peak (phase advances) at corresponding phases. By analyzing the phase space structure of Morris-Lecar-type HCO models with fast synaptic dynamics, we identify the dynamical mechanisms underlying the shapes of the PRCs. To demonstrate the significance of the different shapes of the PRCs for the release-type and escape-type HCOs, we link the shapes of the PRCs to the different frequency modulation properties of release-type and escape-type HCOs, and we show that the different shapes of the PRCs for the release-type and escape-type HCOs can lead to fundamentally different phase-locking dynamics.
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Affiliation(s)
- Calvin Zhang
- Department of Mathematics, University of California, Davis, Davis, CA 95616, USA
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31
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Effects of time-dependent stimuli in a competitive neural network model of perceptual rivalry. Bull Math Biol 2012; 74:1396-1426. [PMID: 22314546 DOI: 10.1007/s11538-012-9718-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2011] [Accepted: 01/16/2012] [Indexed: 10/14/2022]
Abstract
We analyze a competitive neural network model of perceptual rivalry that receives time-varying inputs. Time-dependence of inputs can be discrete or smooth. Spike frequency adaptation provides negative feedback that generates network oscillations when inputs are constant in time. Oscillations that resemble perceptual rivalry involve only one population being “ON” at a time, which represents the dominance of a single percept at a time. As shown in Laing and Chow (J. Comput. Neurosci. 12(1):39–53, 2002), for sufficiently high contrast, one can derive relationships between dominance times and contrast that agree with Levelt’s propositions (Levelt in On binocular rivalry, 1965). Time-dependent stimuli give rise to novel network oscillations where both, one, or neither populations are “ON” at any given time. When a single population receives an interrupted stimulus, the fundamental mode of behavior we find is phase-locking, where the temporally driven population locks its state to the stimulus. Other behaviors are analyzed as bifurcations from this forced oscillation, using fast/slow analysis that exploits the slow timescale of adaptation. When both populations receive time-varying input, we find mixtures of fusion and sole population dominance, and we partition parameter space into particular oscillation types. Finally, when a single population’s input contrast is smoothly varied in time, 1:n mode-locked states arise through period-adding bifurcations beyond phase-locking. Our results provide several testable predictions for future psychophysical experiments on perceptual rivalry.
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Theodoni P, Panagiotaropoulos TI, Kapoor V, Logothetis NK, Deco G. Cortical microcircuit dynamics mediating binocular rivalry: the role of adaptation in inhibition. Front Hum Neurosci 2011; 5:145. [PMID: 22164140 PMCID: PMC3224982 DOI: 10.3389/fnhum.2011.00145] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2011] [Accepted: 11/05/2011] [Indexed: 11/25/2022] Open
Abstract
Perceptual bistability arises when two conflicting interpretations of an ambiguous stimulus or images in binocular rivalry (BR) compete for perceptual dominance. From a computational point of view, competition models based on cross-inhibition and adaptation have shown that noise is a crucial force for rivalry, and operates in balance with adaptation. In particular, noise-driven transitions and adaptation-driven oscillations define two dynamical regimes and the system explains the observed alternations in perception when it operates near their boundary. In order to gain insights into the microcircuit dynamics mediating spontaneous perceptual alternations, we used a reduced recurrent attractor-based biophysically realistic spiking network, well known for working memory, attention, and decision making, where a spike-frequency adaptation mechanism is implemented to account for perceptual bistability. We thus derived a consistently reduced four-variable population rate model using mean-field techniques, and we tested it on BR data collected from human subjects. Our model accounts for experimental data parameters such as mean time dominance, coefficient of variation, and gamma distribution fit. In addition, we show that our model operates near the bifurcation that separates the noise-driven transitions regime from the adaptation-driven oscillations regime, and agrees with Levelt's second revised and fourth propositions. These results demonstrate for the first time that a consistent reduction of a biophysically realistic spiking network of leaky integrate-and-fire neurons with spike-frequency adaptation could account for BR. Moreover, we demonstrate that BR can be explained only through the dynamics of competing neuronal pools, without taking into account the adaptation of inhibitory interneurons. However, the adaptation of interneurons affects the optimal parametric space of the system by decreasing the overall adaptation necessary for the bifurcation to occur, and introduces oscillations in the spontaneous state.
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Affiliation(s)
- Panagiota Theodoni
- Computational Neuroscience, Department of Technology, Universitat Pompeu FabraBarcelona, Spain
| | | | - Vishal Kapoor
- Department of Physiology of Cognitive Processes, Max-Planck-Institute for Biological CyberneticsTübingen, Germany
| | - Nikos K. Logothetis
- Department of Physiology of Cognitive Processes, Max-Planck-Institute for Biological CyberneticsTübingen, Germany
- Imaging Science and Biomedical Engineering, University of ManchesterManchester, UK
| | - Gustavo Deco
- Computational Neuroscience, Department of Technology, Universitat Pompeu FabraBarcelona, Spain
- Institució Catalana de Recerca i Estudis AvançatsBarcelona, Spain
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Abstract
Binocular rivalry is a phenomenon that occurs when a different image is presented to each eye. The observer generally perceives just one image at a time, with perceptual switches occurring every few seconds. A natural assumption is that this perceptual mutual exclusivity is achieved via mutual inhibition between populations of neurons that encode for either percept. Theoretical models that incorporate mutual inhibition have been largely successful at capturing experimental features of rivalry, including Levelt's propositions, which characterize perceptual dominance durations as a function of image contrasts. However, basic mutual inhibition models do not fully comply with Levelt's fourth proposition, which states that percepts alternate faster as the stimulus contrasts to both eyes are increased simultaneously. This theory-experiment discrepancy has been taken as evidence against the role of mutual inhibition for binocular rivalry. Here, we show how various biophysically plausible modifications to mutual inhibition models can resolve this problem.
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Affiliation(s)
- Jeffrey Seely
- Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA
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Daun S, Rubin JE, Rybak IA. Control of oscillation periods and phase durations in half-center central pattern generators: a comparative mechanistic analysis. J Comput Neurosci 2009; 27:3-36. [PMID: 19130197 PMCID: PMC2844522 DOI: 10.1007/s10827-008-0124-4] [Citation(s) in RCA: 68] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2008] [Revised: 10/29/2008] [Accepted: 11/04/2008] [Indexed: 10/21/2022]
Abstract
Central pattern generators (CPGs) consisting of interacting groups of neurons drive a variety of repetitive, rhythmic behaviors in invertebrates and vertebrates, such as arise in locomotion, respiration, mastication, scratching, and so on. These CPGs are able to generate rhythmic activity in the absence of afferent feedback or rhythmic inputs. However, functionally relevant CPGs must adaptively respond to changing demands, manifested as changes in oscillation period or in relative phase durations in response to variations in non-patterned inputs or drives. Although many half-center CPG models, composed of symmetric units linked by reciprocal inhibition yet varying in their intrinsic cellular properties, have been proposed, the precise oscillatory mechanisms operating in most biological CPGs remain unknown. Using numerical simulations and phase-plane analysis, we comparatively investigated how the intrinsic cellular features incorporated in different CPG models, such as subthreshold activation based on a slowly inactivating persistent sodium current, adaptation based on slowly activating calcium-dependent potassium current, or post-inhibitory rebound excitation, can contribute to the control of oscillation period and phase durations in response to changes in excitatory external drive to one or both half-centers. Our analysis shows that both the sensitivity of oscillation period to alterations of excitatory drive and the degree to which the duration of each phase can be separately controlled depend strongly on the intrinsic cellular mechanisms involved in rhythm generation and phase transitions. In particular, the CPG formed from units incorporating a slowly inactivating persistent sodium current shows the greatest range of oscillation periods and the greatest degree of independence in phase duration control by asymmetric inputs. These results are explained based on geometric analysis of the phase plane structures corresponding to the dynamics for each CPG type, which in particular helps pinpoint the roles of escape and release from synaptic inhibition in the effects we find.
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Affiliation(s)
- Silvia Daun
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA 15260, USA,
| | - Jonathan E. Rubin
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Ilya A. Rybak
- Department of Neurobiology and Anatomy, Drexel University, College of Medicine, Philadelphia, PA 19129, USA
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Rubin JE, Shevtsova NA, Ermentrout GB, Smith JC, Rybak IA. Multiple rhythmic states in a model of the respiratory central pattern generator. J Neurophysiol 2009; 101:2146-65. [PMID: 19193773 DOI: 10.1152/jn.90958.2008] [Citation(s) in RCA: 79] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The three-phase respiratory pattern observed during normal breathing changes with alterations in metabolic or physiological conditions. A recent study using in situ perfused rat brain preparations demonstrated a reorganization of the respiratory pattern with sequential reduction of the brain stem respiratory network. Specifically, with removal of the pons, the normal three-phase pattern transformed to a two-phase inspiratory-expiratory pattern and, with more caudal transections, to one-phase, intrinsically generated inspiratory oscillations. A minimal neural network proposed to reproduce these transformations includes 1) a ringlike mutually inhibitory network composed of the postinspiratory, augmenting expiratory, and early-inspiratory neurons and 2) an excitatory preinspiratory neuron, with persistent sodium current (I(NaP))-dependent intrinsic bursting properties, that dynamically participates in the expiratory-inspiratory phase transition and inspiratory phase generation. We used activity-based single-neuron models and applied numerical simulations, bifurcation methods, and fast-slow decomposition to describe the behavior of this network in the functional states corresponding to the three-, two-, and one-phase oscillatory regimes, as well as to analyze the transitions between states and between respiratory phases within each state. We demonstrate that, although I(NaP) is not necessary for the generation of three- and two-phase oscillations, it contributes to control of the oscillation period in each state. We also show that the transitions between states can be produced by progressive changes of drives to particular neurons and proceed through intermediate regimes, featuring high-amplitude late-expiratory and biphasic-expiratory activities or ectopic burst generation. Our results provide important insights for understanding the state-dependent mechanisms for respiratory rhythm generation and control.
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Balance between noise and adaptation in competition models of perceptual bistability. J Comput Neurosci 2009; 27:37-54. [PMID: 19125318 DOI: 10.1007/s10827-008-0125-3] [Citation(s) in RCA: 108] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2008] [Revised: 10/23/2008] [Accepted: 11/04/2008] [Indexed: 10/21/2022]
Abstract
Perceptual bistability occurs when a physical stimulus gives rise to two distinct interpretations that alternate irregularly. Noise and adaptation processes are two possible mechanisms for switching in neuronal competition models that describe the alternating behaviors. Either of these processes, if strong enough, could alone cause the alternations in dominance. We examined their relative role in producing alternations by studying models where by smoothly varying the parameters, one can change the rhythmogenesis mechanism from being adaptation-driven to noise-driven. In consideration of the experimental constraints on the statistics of the alternations (mean and shape of the dominance duration distribution and correlations between successive durations) we ask whether we can rule out one of the mechanisms. We conclude that in order to comply with the observed mean of the dominance durations and their coefficient of variation, the models must operate within a balance between the noise and adaptation strength-both mechanisms are involved in producing alternations, in such a way that the system operates near the boundary between being adaptation-driven and noise-driven.
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