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Gonzales DL, Khan HF, Keri HVS, Yadav S, Steward C, Muller LE, Pluta SR, Jayant K. A Translaminar Spacetime Code Supports Touch-Evoked Traveling Waves. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.09.593381. [PMID: 38766232 PMCID: PMC11100787 DOI: 10.1101/2024.05.09.593381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Linking sensory-evoked traveling waves to underlying circuit patterns is critical to understanding the neural basis of sensory perception. To form this link, we performed simultaneous electrophysiology and two-photon calcium imaging through transparent NeuroGrids and mapped touch-evoked cortical traveling waves and their underlying microcircuit dynamics. In awake mice, both passive and active whisker touch elicited traveling waves within and across barrels, with a fast early component followed by a variable late wave that lasted hundreds of milliseconds post-stimulus. Strikingly, late-wave dynamics were modulated by stimulus value and correlated with task performance. Mechanistically, the late wave component was i) modulated by motor feedback, ii) complemented by a sparse ensemble pattern across layer 2/3, which a balanced-state network model reconciled via inhibitory stabilization, and iii) aligned to regenerative Layer-5 apical dendritic Ca 2+ events. Our results reveal a translaminar spacetime pattern organized by cortical feedback in the sensory cortex that supports touch-evoked traveling waves. GRAPHICAL ABSTRACT AND HIGHLIGHTS Whisker touch evokes both early- and late-traveling waves in the barrel cortex over 100's of millisecondsReward reinforcement modulates wave dynamics Late wave emergence coincides with network sparsity in L23 and time-locked L5 dendritic Ca 2+ spikes Experimental and computational results link motor feedback to distinct translaminar spacetime patterns.
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2
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Alamia A, VanRullen R. A Traveling Waves Perspective on Temporal Binding. J Cogn Neurosci 2024; 36:721-729. [PMID: 37172133 DOI: 10.1162/jocn_a_02004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Brain oscillations are involved in many cognitive processes, and several studies have investigated their role in cognition. In particular, the phase of certain oscillations has been related to temporal binding and integration processes, with some authors arguing that perception could be an inherently rhythmic process. However, previous research on oscillations mostly overlooked their spatial component: how oscillations propagate through the brain as traveling waves, with systematic phase delays between brain regions. Here, we argue that interpreting oscillations as traveling waves is a useful paradigm shift to understand their role in temporal binding and address controversial results. After a brief definition of traveling waves, we propose an original view on temporal integration that considers this new perspective. We first focus on cortical dynamics, then speculate about the role of thalamic nuclei in modulating the waves, and on the possible consequences for rhythmic temporal binding. In conclusion, we highlight the importance of considering oscillations as traveling waves when investigating their role in cognitive functions.
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Affiliation(s)
- Andrea Alamia
- CNRS Centre de Recherche Cerveau et Cognition (CERCO, UMR 5549), Toulouse, France
| | - Rufin VanRullen
- CNRS Centre de Recherche Cerveau et Cognition (CERCO, UMR 5549), Toulouse, France
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3
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Mohan UR, Zhang H, Ermentrout B, Jacobs J. The direction of theta and alpha travelling waves modulates human memory processing. Nat Hum Behav 2024:10.1038/s41562-024-01838-3. [PMID: 38459263 DOI: 10.1038/s41562-024-01838-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 01/24/2024] [Indexed: 03/10/2024]
Abstract
To support a range of behaviours, the brain must flexibly coordinate neural activity across widespread brain regions. One potential mechanism for this coordination is a travelling wave, in which a neural oscillation propagates across the brain while organizing the order and timing of activity across regions. Although travelling waves are present across the brain in various species, their potential functional relevance has remained unknown. Here, using rare direct human brain recordings, we demonstrate a distinct functional role for travelling waves of theta- and alpha-band (2-13 Hz) oscillations in the cortex. Travelling waves propagate in different directions during separate cognitive processes. In episodic memory, travelling waves tended to propagate in a posterior-to-anterior direction during successful memory encoding and in an anterior-to-posterior direction during recall. Because travelling waves of oscillations correspond to local neuronal spiking, these patterns indicate that rhythmic pulses of activity move across the brain in different directions for separate behaviours. More broadly, our results suggest a fundamental role for travelling waves and oscillations in dynamically coordinating neural connectivity, by flexibly organizing the timing and directionality of network interactions across the cortex to support cognition and behaviour.
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Affiliation(s)
- Uma R Mohan
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD, USA
| | | | - Bard Ermentrout
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University, New York City, NY, USA.
- Department of Neurological Surgery, Columbia University, New York City, NY, USA.
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4
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Orsher Y, Rom A, Perel R, Lahini Y, Blinder P, Shein-Idelson M. Sequentially activated discrete modules appear as traveling waves in neuronal measurements with limited spatiotemporal sampling. eLife 2024; 12:RP92254. [PMID: 38451063 PMCID: PMC10942589 DOI: 10.7554/elife.92254] [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] [Indexed: 03/08/2024] Open
Abstract
Numerous studies have identified traveling waves in the cortex and suggested they play important roles in brain processing. These waves are most often measured using macroscopic methods that are unable to assess the local spiking activity underlying wave dynamics. Here, we investigated the possibility that waves may not be traveling at the single neuron scale. We first show that sequentially activating two discrete brain areas can appear as traveling waves in EEG simulations. We next reproduce these results using an analytical model of two sequentially activated regions. Using this model, we were able to generate wave-like activity with variable directions, velocities, and spatial patterns, and to map the discriminability limits between traveling waves and modular sequential activations. Finally, we investigated the link between field potentials and single neuron excitability using large-scale measurements from turtle cortex ex vivo. We found that while field potentials exhibit wave-like dynamics, the underlying spiking activity was better described by consecutively activated spatially adjacent groups of neurons. Taken together, this study suggests caution when interpreting phase delay measurements as continuously propagating wavefronts in two different spatial scales. A careful distinction between modular and wave excitability profiles across scales will be critical for understanding the nature of cortical computations.
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Affiliation(s)
- Yuval Orsher
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- School of Physics & Astronomy, Faculty of Exact Sciences, Tel Aviv UniversityTel AvivIsrael
| | - Ariel Rom
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
| | - Rotem Perel
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
| | - Yoav Lahini
- School of Physics & Astronomy, Faculty of Exact Sciences, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
| | - Pablo Blinder
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
| | - Mark Shein-Idelson
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
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5
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Cortes N, Ladret HJ, Abbas-Farishta R, Casanova C. The pulvinar as a hub of visual processing and cortical integration. Trends Neurosci 2024; 47:120-134. [PMID: 38143202 DOI: 10.1016/j.tins.2023.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 10/26/2023] [Accepted: 11/26/2023] [Indexed: 12/26/2023]
Abstract
The pulvinar nucleus of the thalamus is a crucial component of the visual system and plays significant roles in sensory processing and cognitive integration. The pulvinar's extensive connectivity with cortical regions allows for bidirectional communication, contributing to the integration of sensory information across the visual hierarchy. Recent findings underscore the pulvinar's involvement in attentional modulation, feature binding, and predictive coding. In this review, we highlight recent advances in clarifying the pulvinar's circuitry and function. We discuss the contributions of the pulvinar to signal modulation across the global cortical network and place these findings within theoretical frameworks of cortical processing, particularly the global neuronal workspace (GNW) theory and predictive coding.
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Affiliation(s)
- Nelson Cortes
- Visual Neuroscience Laboratory, School of Optometry, Université de Montréal, Montreal, QC, Canada
| | - Hugo J Ladret
- Visual Neuroscience Laboratory, School of Optometry, Université de Montréal, Montreal, QC, Canada; Institut de Neurosciences de la Timone, UMR 7289, CNRS and Aix-Marseille Université, Marseille, 13005, France
| | - Reza Abbas-Farishta
- Visual Neuroscience Laboratory, School of Optometry, Université de Montréal, Montreal, QC, Canada
| | - Christian Casanova
- Visual Neuroscience Laboratory, School of Optometry, Université de Montréal, Montreal, QC, Canada.
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6
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Turner W, Sexton C, Hogendoorn H. Neural mechanisms of visual motion extrapolation. Neurosci Biobehav Rev 2024; 156:105484. [PMID: 38036162 DOI: 10.1016/j.neubiorev.2023.105484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 11/21/2023] [Accepted: 11/25/2023] [Indexed: 12/02/2023]
Abstract
Because neural processing takes time, the brain only has delayed access to sensory information. When localising moving objects this is problematic, as an object will have moved on by the time its position has been determined. Here, we consider predictive motion extrapolation as a fundamental delay-compensation strategy. From a population-coding perspective, we outline how extrapolation can be achieved by a forwards shift in the population-level activity distribution. We identify general mechanisms underlying such shifts, involving various asymmetries which facilitate the targeted 'enhancement' and/or 'dampening' of population-level activity. We classify these on the basis of their potential implementation (intra- vs inter-regional processes) and consider specific examples in different visual regions. We consider how motion extrapolation can be achieved during inter-regional signaling, and how asymmetric connectivity patterns which support extrapolation can emerge spontaneously from local synaptic learning rules. Finally, we consider how more abstract 'model-based' predictive strategies might be implemented. Overall, we present an integrative framework for understanding how the brain determines the real-time position of moving objects, despite neural delays.
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Affiliation(s)
- William Turner
- Queensland University of Technology, Brisbane 4059, Australia; The University of Melbourne, Melbourne 3010, Australia.
| | | | - Hinze Hogendoorn
- Queensland University of Technology, Brisbane 4059, Australia; The University of Melbourne, Melbourne 3010, Australia
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7
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Fakche C, Dugué L. Perceptual Cycles Travel Across Retinotopic Space. J Cogn Neurosci 2024; 36:200-216. [PMID: 37902594 DOI: 10.1162/jocn_a_02075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
Visual perception waxes and wanes periodically over time at low frequencies (theta: 4-7 Hz; alpha: 8-13 Hz), creating "perceptual cycles." These perceptual cycles can be induced when stimulating the brain with a flickering visual stimulus at the theta or alpha frequency. Here, we took advantage of the well-known organization of the visual system into retinotopic maps (topographic correspondence between visual and cortical spaces) to assess the spatial organization of induced perceptual cycles. Specifically, we tested the hypothesis that they can propagate across the retinotopic space. A disk oscillating in luminance (inducer) at 4, 6, 8, or 10 Hz was presented in the periphery of the visual field to induce perceptual cycles at specific frequencies. EEG recordings verified that the brain responded at the corresponding inducer frequencies and their first harmonics. Perceptual cycles were assessed with a concurrent detection task-target stimuli were displayed at threshold contrast (50% detection) at random times during the inducer. Behavioral results confirmed that perceptual performance was modulated periodically by the inducer at each frequency. We additionally manipulated the distance between the target and the inducer (three possible positions) and showed that the optimal phase, that is, moment of highest target detection, shifted across target distance to the inducer, specifically when its flicker frequency was in the alpha range (8 and 10 Hz). These results demonstrate that induced alpha perceptual cycles travel across the retinotopic space in humans at a propagation speed of 0.3-0.5 m/sec, consistent with the speed of unmyelinated horizontal connections in the visual cortex.
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Affiliation(s)
- Camille Fakche
- Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
| | - Laura Dugué
- Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
- Institut Universitaire de France
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8
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Shinn M. Phantom oscillations in principal component analysis. Proc Natl Acad Sci U S A 2023; 120:e2311420120. [PMID: 37988465 PMCID: PMC10691246 DOI: 10.1073/pnas.2311420120] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/18/2023] [Indexed: 11/23/2023] Open
Abstract
Principal component analysis (PCA) is a dimensionality reduction method that is known for being simple and easy to interpret. Principal components are often interpreted as low-dimensional patterns in high-dimensional space. However, this simple interpretation fails for timeseries, spatial maps, and other continuous data. In these cases, nonoscillatory data may have oscillatory principal components. Here, we show that two common properties of data cause oscillatory principal components: smoothness and shifts in time or space. These two properties implicate almost all neuroscience data. We show how the oscillations produced by PCA, which we call "phantom oscillations," impact data analysis. We also show that traditional cross-validation does not detect phantom oscillations, so we suggest procedures that do. Our findings are supported by a collection of mathematical proofs. Collectively, our work demonstrates that patterns which emerge from high-dimensional data analysis may not faithfully represent the underlying data.
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Affiliation(s)
- Maxwell Shinn
- University College London (UCL) Queen Square Institute of Neurology, University College London, LondonWC1E 6BT, United Kingdom
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9
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Zabeh E, Foley NC, Jacobs J, Gottlieb JP. Beta traveling waves in monkey frontal and parietal areas encode recent reward history. Nat Commun 2023; 14:5428. [PMID: 37669966 PMCID: PMC10480436 DOI: 10.1038/s41467-023-41125-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 08/22/2023] [Indexed: 09/07/2023] Open
Abstract
Brain function depends on neural communication, but the mechanisms of this communication are not well understood. Recent studies suggest that one form of neural communication is through traveling waves (TWs)-patterns of neural oscillations that propagate within and between brain areas. We show that TWs are robust in microarray recordings in frontal and parietal cortex and encode recent reward history. Two adult male monkeys made saccades to obtain probabilistic rewards and were sensitive to the (statistically irrelevant) reward on the previous trial. TWs in frontal and parietal areas were stronger in trials that followed a prior reward versus a lack of reward and, in the frontal lobe, correlated with the monkeys' behavioral sensitivity to the prior reward. The findings suggest that neural communication mediated by TWs within the frontal and parietal lobes contribute to maintaining information about recent reward history and mediating the impact of this history on the monkeys' expectations.
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Affiliation(s)
- Erfan Zabeh
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Nicholas C Foley
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University, New York, NY, USA.
- Department of Neurological Surgery, Columbia University, New York, NY, USA.
| | - Jacqueline P Gottlieb
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
- Department of Neuroscience, Columbia University, New York, NY, USA.
- Kavli Institute for Brain Science, Columbia University, New York, NY, USA.
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10
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Lillis KP. Rogue Waves: A Unifying Model of Human Seizure Propagation. Epilepsy Curr 2023; 23:265-267. [PMID: 37662458 PMCID: PMC10470098 DOI: 10.1177/15357597231176345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2023] Open
Abstract
Multiple Sources of Fast Traveling Waves During Human Seizures: Resolving a Controversy Schlafly ED, Marshall FA, Merricks EM, Eden UT, Cash SS, Schevon CA, Kramer MA. J Neurosci . 2022;42(36):6966-6982. doi:10.1523/JNEUROSCI.0338-22.2022 During human seizures organized waves of voltage activity rapidly sweep across the cortex. Two contradictory theories describe the source of these fast traveling waves: either a slowly advancing narrow region of multiunit activity (an ictal wavefront) or a fixed cortical location. Limited observations and different analyses prevent resolution of these incompatible theories. Here we address this disagreement by combining the methods and microelectrode array recordings (N = 11 patients, 2 females, N = 31 seizures) from previous human studies to analyze the traveling wave source. We find—inconsistent with both existing theories—a transient relationship between the ictal wavefront and traveling waves, and multiple stable directions of traveling waves in many seizures. Using a computational model that combines elements of both existing theories, we show that interactions between an ictal wavefront and fixed source reproduce the traveling wave dynamics observed in vivo. We conclude that combining both existing theories can generate the diversity of ictal traveling waves. Significance Statement: The source of voltage discharges that propagate across cortex during human seizures remains unknown. Two candidate theories exist, each proposing a different discharge source. Support for each theory consists of observations from a small number of human subject recordings, analyzed with separately developed methods. How the different, limited data and different analysis methods impact the evidence for each theory is unclear. To resolve these differences, we combine the unique, human microelectrode array recordings collected separately for each theory and analyze these combined data with a unified approach. We show that neither existing theory adequately describes the data. We then propose a new theory that unifies existing proposals and successfully reproduces the voltage discharge dynamics observed in vivo.
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11
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Benigno GB, Budzinski RC, Davis ZW, Reynolds JH, Muller L. Waves traveling over a map of visual space can ignite short-term predictions of sensory input. Nat Commun 2023; 14:3409. [PMID: 37296131 PMCID: PMC10256723 DOI: 10.1038/s41467-023-39076-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 05/25/2023] [Indexed: 06/12/2023] Open
Abstract
Recent analyses have found waves of neural activity traveling across entire visual cortical areas in awake animals. These traveling waves modulate the excitability of local networks and perceptual sensitivity. The general computational role of these spatiotemporal patterns in the visual system, however, remains unclear. Here, we hypothesize that traveling waves endow the visual system with the capacity to predict complex and naturalistic inputs. We present a network model whose connections can be rapidly and efficiently trained to predict individual natural movies. After training, a few input frames from a movie trigger complex wave patterns that drive accurate predictions many frames into the future solely from the network's connections. When the recurrent connections that drive waves are randomly shuffled, both traveling waves and the ability to predict are eliminated. These results suggest traveling waves may play an essential computational role in the visual system by embedding continuous spatiotemporal structures over spatial maps.
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Affiliation(s)
- Gabriel B Benigno
- Department of Mathematics, Western University, London, ON, Canada
- Brain and Mind Institute, Western University, London, ON, Canada
- Western Academy for Advanced Research, Western University, London, ON, Canada
| | - Roberto C Budzinski
- Department of Mathematics, Western University, London, ON, Canada
- Brain and Mind Institute, Western University, London, ON, Canada
- Western Academy for Advanced Research, Western University, London, ON, Canada
| | - Zachary W Davis
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - John H Reynolds
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Lyle Muller
- Department of Mathematics, Western University, London, ON, Canada.
- Brain and Mind Institute, Western University, London, ON, Canada.
- Western Academy for Advanced Research, Western University, London, ON, Canada.
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12
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Zhigalov A, Jensen O. Perceptual echoes as travelling waves may arise from two discrete neuronal sources. Neuroimage 2023; 272:120047. [PMID: 37001836 PMCID: PMC7615062 DOI: 10.1016/j.neuroimage.2023.120047] [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: 10/10/2022] [Revised: 01/26/2023] [Accepted: 03/20/2023] [Indexed: 03/31/2023] Open
Abstract
Growing evidence suggests that travelling waves are functionally relevant for cognitive operations in the brain. Several electroencephalography (EEG) studies report on a perceptual alpha-echo, representing the brain response to a random visual flicker, propagating as a travelling wave across the cortical surface. In this study, we ask if the propagating activity of the alpha-echo is best explained by a set of discrete sources mixing at the sensor level rather than a cortical travelling wave. To this end, we presented participants with gratings modulated by random noise and simultaneously acquired the ongoing MEG. The perceptual alpha-echo was estimated using the temporal response function linking the visual input to the brain response. At the group level, we observed a spatial decay of the amplitude of the alpha-echo with respect to the sensor where the alpha-echo was the largest. Importantly, the propagation latencies consistently increased with the distance. Interestingly, the propagation of the alpha-echoes was predominantly centro-lateral, while EEG studies reported mainly posterior-frontal propagation. Moreover, the propagation speed of the alpha-echoes derived from the MEG data was around 10 m/s, which is higher compared to the 2 m/s reported in EEG studies. Using source modelling, we found an early component in the primary visual cortex and a phase-lagged late component in the parietal cortex, which may underlie the travelling alpha-echoes at the sensor level. We then simulated the alpha-echoes using realistic EEG and MEG forward models by placing two sources in the parietal and occipital cortices in accordance with our empirical findings. The two-source model could account for both the direction and speed of the observed alpha-echoes in the EEG and MEG data. Our results demonstrate that the propagation of the perceptual echoes observed in EEG and MEG data can be explained by two sources mixing at the scalp level equally well as by a cortical travelling wave. Importantly, these findings should not be directly extrapolated to intracortical recordings, where travelling waves gradually propagate at a sub-millimetre scale.
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Affiliation(s)
- Alexander Zhigalov
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, United Kingdom.
| | - Ole Jensen
- Centre for Human Brain Health, University of Birmingham, United Kingdom
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13
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Tovar DA, Westerberg JA, Cox MA, Dougherty K, Wallace MT, Bastos AM, Maier A. Near-field potentials index local neural computations more accurately than population spiking. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.11.540026. [PMID: 37214905 PMCID: PMC10197629 DOI: 10.1101/2023.05.11.540026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Local field potentials (LFP) are low-frequency extracellular voltage fluctuations thought to primarily arise from synaptic activity. However, unlike highly localized neuronal spiking, LFP is spatially less specific. LFP measured at one location is not entirely generated there due to far-field contributions that are passively conducted across volumes of neural tissue. We sought to quantify how much information within the locally generated, near-field low-frequency activity (nfLFP) is masked by volume-conducted far-field signals. To do so, we measured laminar neural activity in primary visual cortex (V1) of monkeys viewing sequences of multifeatured stimuli. We compared information content of regular LFP and nfLFP that was mathematically stripped of volume-conducted far-field contributions. Information content was estimated by decoding stimulus properties from neural responses via spatiotemporal multivariate pattern analysis. Volume-conducted information differed from locally generated information in two important ways: (1) for stimulus features relevant to V1 processing (orientation and eye-of-origin), nfLFP contained more information. (2) in contrast, the volume-conducted signal was more informative regarding temporal context (relative stimulus position in a sequence), a signal likely to be coming from elsewhere. Moreover, LFP and nfLFP differed both spectrally as well as spatially, urging caution regarding the interpretations of individual frequency bands and/or laminar patterns of LFP. Most importantly, we found that population spiking of local neurons was less informative than either the LFP or nfLFP, with nfLFP containing most of the relevant information regarding local stimulus processing. These findings suggest that the optimal way to read out local computational processing from neural activity is to decode the local contributions to LFP, with significant information loss hampering both regular LFP and local spiking. Author’s Contributions Conceptualization, D.A.T., J.A.W, and A.M.; Data Collection, J.A.W., M.A.C., K.D.; Formal Analysis, D.A.T. and J.A.W.; Data Visualization, D.A.T. and J.A.W.; Original Draft, D.A.T., J.A.W., and A.M.; Revisions and Final Draft, D.A.T., J.A.W., M.A.C., K.D., M.T.W., A.M.B., and A.M. Competing Interests The authors declare no conflicts of interest.
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14
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Eisenkolb VM, Held LM, Utzschmid A, Lin XX, Krieg SM, Meyer B, Gempt J, Jacob SN. Human acute microelectrode array recordings with broad cortical access, single-unit resolution, and parallel behavioral monitoring. Cell Rep 2023; 42:112467. [PMID: 37141095 DOI: 10.1016/j.celrep.2023.112467] [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: 11/19/2022] [Revised: 01/06/2023] [Accepted: 04/18/2023] [Indexed: 05/05/2023] Open
Abstract
There are vast gaps in our understanding of the organization and operation of the human nervous system at the level of individual neurons and their networks. Here, we report reliable and robust acute multichannel recordings using planar microelectrode arrays (MEAs) implanted intracortically in awake brain surgery with open craniotomies that grant access to large parts of the cortical hemisphere. We obtained high-quality extracellular neuronal activity at the microcircuit, local field potential level and at the cellular, single-unit level. Recording from the parietal association cortex, a region rarely explored in human single-unit studies, we demonstrate applications on these complementary spatial scales and describe traveling waves of oscillatory activity as well as single-neuron and neuronal population responses during numerical cognition, including operations with uniquely human number symbols. Intraoperative MEA recordings are practicable and can be scaled up to explore cellular and microcircuit mechanisms of a wide range of human brain functions.
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Affiliation(s)
- Viktor M Eisenkolb
- Translational Neurotechnology Laboratory, Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany; Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Lisa M Held
- Translational Neurotechnology Laboratory, Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Alexander Utzschmid
- Translational Neurotechnology Laboratory, Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Xiao-Xiong Lin
- Translational Neurotechnology Laboratory, Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany; Graduate School of Systemic Neurosciences, Ludwig Maximilians University Munich, Großhaderner Straße 2, 82152 Planegg-Martinsried, Germany
| | - Sandro M Krieg
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Jens Gempt
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Simon N Jacob
- Translational Neurotechnology Laboratory, Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany; Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany.
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15
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Bouhadjar Y, Wouters DJ, Diesmann M, Tetzlaff T. Coherent noise enables probabilistic sequence replay in spiking neuronal networks. PLoS Comput Biol 2023; 19:e1010989. [PMID: 37130121 PMCID: PMC10153753 DOI: 10.1371/journal.pcbi.1010989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 03/02/2023] [Indexed: 05/03/2023] Open
Abstract
Animals rely on different decision strategies when faced with ambiguous or uncertain cues. Depending on the context, decisions may be biased towards events that were most frequently experienced in the past, or be more explorative. A particular type of decision making central to cognition is sequential memory recall in response to ambiguous cues. A previously developed spiking neuronal network implementation of sequence prediction and recall learns complex, high-order sequences in an unsupervised manner by local, biologically inspired plasticity rules. In response to an ambiguous cue, the model deterministically recalls the sequence shown most frequently during training. Here, we present an extension of the model enabling a range of different decision strategies. In this model, explorative behavior is generated by supplying neurons with noise. As the model relies on population encoding, uncorrelated noise averages out, and the recall dynamics remain effectively deterministic. In the presence of locally correlated noise, the averaging effect is avoided without impairing the model performance, and without the need for large noise amplitudes. We investigate two forms of correlated noise occurring in nature: shared synaptic background inputs, and random locking of the stimulus to spatiotemporal oscillations in the network activity. Depending on the noise characteristics, the network adopts various recall strategies. This study thereby provides potential mechanisms explaining how the statistics of learned sequences affect decision making, and how decision strategies can be adjusted after learning.
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Affiliation(s)
- Younes Bouhadjar
- Institute of Neuroscience and Medicine (INM-6), & Institute for Advanced Simulation (IAS-6), & JARA BRAIN Institute Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
- Peter Grünberg Institute (PGI-7,10), Jülich Research Centre and JARA, Jülich, Germany
- RWTH Aachen University, Aachen, Germany
| | - Dirk J Wouters
- Institute of Electronic Materials (IWE 2) & JARA-FIT, RWTH Aachen University, Aachen, Germany
| | - Markus Diesmann
- Institute of Neuroscience and Medicine (INM-6), & Institute for Advanced Simulation (IAS-6), & JARA BRAIN Institute Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
- Department of Physics, Faculty 1, & Department of Psychiatry, Psychotherapy, and Psychosomatics, Medical School, RWTH Aachen University, Aachen, Germany
| | - Tom Tetzlaff
- Institute of Neuroscience and Medicine (INM-6), & Institute for Advanced Simulation (IAS-6), & JARA BRAIN Institute Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
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16
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Volpert V, Xu B, Tchechmedjiev A, Harispe S, Aksenov A, Mesnildrey Q, Beuter A. Characterization of spatiotemporal dynamics in EEG data during picture naming with optical flow patterns. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:11429-11463. [PMID: 37322989 DOI: 10.3934/mbe.2023507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
In this study, we investigate the spatiotemporal dynamics of the neural oscillations by analyzing the electric potential that arises from neural activity. We identify two types of dynamics based on the frequency and phase of oscillations: standing waves or as out-of-phase and modulated waves, which represent a combination of standing and moving waves. To characterize these dynamics, we use optical flow patterns such as sources, sinks, spirals and saddles. We compare analytical and numerical solutions with real EEG data acquired during a picture-naming task. Analytical approximation of standing waves helps us to establish some properties of pattern location and number. Specifically, sources and sinks are mainly located in the same location, while saddles are positioned between them. The number of saddles correlates with the sum of all the other patterns. These properties are confirmed in both the simulated and real EEG data. In particular, source and sink clusters in the EEG data overlap with each other with median percentages around 60%, and hence have high spatial correlation, while source/sink clusters overlap with saddle clusters in less than 1%, and have different locations. Our statistical analysis showed that saddles account for about 45% of all patterns, while the remaining patterns are present in similar proportions.
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Affiliation(s)
- V Volpert
- Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, 69622 Villeurbanne, France
| | - B Xu
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Ales, France
| | - A Tchechmedjiev
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Ales, France
| | - S Harispe
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Ales, France
| | | | | | - A Beuter
- CorStim SAS, Montpellier, France
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17
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Pines A, Keller AS, Larsen B, Bertolero M, Ashourvan A, Bassett DS, Cieslak M, Covitz S, Fan Y, Feczko E, Houghton A, Rueter AR, Saggar M, Shafiei G, Tapera TM, Vogel J, Weinstein SM, Shinohara RT, Williams LM, Fair DA, Satterthwaite TD. Development of top-down cortical propagations in youth. Neuron 2023; 111:1316-1330.e5. [PMID: 36803653 PMCID: PMC10121821 DOI: 10.1016/j.neuron.2023.01.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 12/08/2022] [Accepted: 01/18/2023] [Indexed: 02/19/2023]
Abstract
Hierarchical processing requires activity propagating between higher- and lower-order cortical areas. However, functional neuroimaging studies have chiefly quantified fluctuations within regions over time rather than propagations occurring over space. Here, we leverage advances in neuroimaging and computer vision to track cortical activity propagations in a large sample of youth (n = 388). We delineate cortical propagations that systematically ascend and descend a cortical hierarchy in all individuals in our developmental cohort, as well as in an independent dataset of densely sampled adults. Further, we demonstrate that top-down, descending hierarchical propagations become more prevalent with greater demands for cognitive control as well as with development in youth. These findings emphasize that hierarchical processing is reflected in the directionality of propagating cortical activity and suggest top-down propagations as a potential mechanism of neurocognitive maturation in youth.
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Affiliation(s)
- Adam Pines
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94304, USA; The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Arielle S Keller
- The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Bart Larsen
- The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Maxwell Bertolero
- The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Arian Ashourvan
- Department of Psychology, The University of Kansas, Lawrence, KS 66045, USA
| | - Dani S Bassett
- Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA; Departments of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Physics & Astronomy, The University of Pennsylvania, Philadelphia, PA 19104, USA; Santa Fe Institute, Santa Fe, NM 87051, USA
| | - Matthew Cieslak
- The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Sydney Covitz
- The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Yong Fan
- Department of Radiology, The University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Eric Feczko
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Audrey Houghton
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Amanda R Rueter
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Manish Saggar
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94304, USA
| | - Golia Shafiei
- The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Tinashe M Tapera
- The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Jacob Vogel
- The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Sarah M Weinstein
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94304, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Theodore D Satterthwaite
- The Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA.
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18
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Ono H, Sonoda M, Sakakura K, Kitazawa Y, Mitsuhashi T, Firestone E, Jeong JW, Luat AF, Marupudi NI, Sood S, Asano E. Dynamic cortical and tractography atlases of proactive and reactive alpha and high-gamma activities. Brain Commun 2023; 5:fcad111. [PMID: 37228850 PMCID: PMC10204271 DOI: 10.1093/braincomms/fcad111] [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: 07/08/2022] [Revised: 10/15/2022] [Accepted: 04/03/2023] [Indexed: 05/27/2023] Open
Abstract
Alpha waves-posterior dominant rhythms at 8-12 Hz reactive to eye opening and closure-are among the most fundamental EEG findings in clinical practice and research since Hans Berger first documented them in the early 20th century. Yet, the exact network dynamics of alpha waves in regard to eye movements remains unknown. High-gamma activity at 70-110 Hz is also reactive to eye movements and a summary measure of local cortical activation supporting sensorimotor or cognitive function. We aimed to build the first-ever brain atlases directly visualizing the network dynamics of eye movement-related alpha and high-gamma modulations, at cortical and white matter levels. We studied 28 patients (age: 5-20 years) who underwent intracranial EEG and electro-oculography recordings. We measured alpha and high-gamma modulations at 2167 electrode sites outside the seizure onset zone, interictal spike-generating areas and MRI-visible structural lesions. Dynamic tractography animated white matter streamlines modulated significantly and simultaneously beyond chance, on a millisecond scale. Before eye-closure onset, significant alpha augmentation occurred at the occipital and frontal cortices. After eye-closure onset, alpha-based functional connectivity was strengthened, while high gamma-based connectivity was weakened extensively in both intra-hemispheric and inter-hemispheric pathways involving the central visual areas. The inferior fronto-occipital fasciculus supported the strengthened alpha co-augmentation-based functional connectivity between occipital and frontal lobe regions, whereas the posterior corpus callosum supported the inter-hemispheric functional connectivity between the occipital lobes. After eye-opening offset, significant high-gamma augmentation and alpha attenuation occurred at occipital, fusiform and inferior parietal cortices. High gamma co-augmentation-based functional connectivity was strengthened, whereas alpha-based connectivity was weakened in the posterior inter-hemispheric and intra-hemispheric white matter pathways involving central and peripheral visual areas. Our results do not support the notion that eye closure-related alpha augmentation uniformly reflects feedforward or feedback rhythms propagating from lower to higher order visual cortex, or vice versa. Rather, proactive and reactive alpha waves involve extensive, distinct white matter networks that include the frontal lobe cortices, along with low- and high-order visual areas. High-gamma co-attenuation coupled to alpha co-augmentation in shared brain circuitry after eye closure supports the notion of an idling role for alpha waves during eye closure. These normative dynamic tractography atlases may improve understanding of the significance of EEG alpha waves in assessing the functional integrity of brain networks in clinical practice; they also may help elucidate the effects of eye movements on task-related brain network measures observed in cognitive neuroscience research.
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Affiliation(s)
- Hiroya Ono
- Department of Pediatrics, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
- Department of Pediatric Neurology, National Center of Neurology and Psychiatry, Joint Graduate School of Tohoku University, Tokyo 1878551, Japan
- Department of Pediatrics, UCLA Mattel Children’s Hospital, David Geffen School of Medicine, Los Angeles, CA 90095, USA
| | - Masaki Sonoda
- Department of Pediatrics, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
- Department of Neurosurgery, Graduate School of Medicine, Yokohama City University, Yokohama 2360004, Japan
| | - Kazuki Sakakura
- Department of Pediatrics, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
- Department of Neurosurgery, University of Tsukuba, Tsukuba 3058575, Japan
| | - Yu Kitazawa
- Department of Pediatrics, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
- Department of Neurology and Stroke Medicine, Yokohama City University, Yokohama, Kanagawa 2360004, Japan
| | - Takumi Mitsuhashi
- Department of Pediatrics, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
- Department of Neurosurgery, Juntendo University, School of Medicine, Tokyo 1138421, Japan
| | - Ethan Firestone
- Department of Physiology, Wayne State University, Detroit, MI 48201, USA
| | - Jeong-Won Jeong
- Department of Pediatrics, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
- Department of Neurology, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
| | - Aimee F Luat
- Department of Pediatrics, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
- Department of Neurology, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
- Department of Pediatrics, Central Michigan University, Mount Pleasant, MI 48858, USA
| | - Neena I Marupudi
- Department of Neurosurgery, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
| | - Sandeep Sood
- Department of Neurosurgery, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
| | - Eishi Asano
- Department of Pediatrics, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
- Department of Neurology, Children’s Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
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19
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Campbell JM, Davis TS, Anderson DN, Arain A, Inman CS, Smith EH, Rolston JD. Subsets of cortico-cortical evoked potentials propagate as traveling waves. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.27.534002. [PMID: 37034691 PMCID: PMC10081214 DOI: 10.1101/2023.03.27.534002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Emerging evidence suggests that the temporal dynamics of cortico-cortical evoked potentials (CCEPs) may be used to characterize the patterns of information flow between and within brain networks. At present, however, the spatiotemporal dynamics of CCEP propagation cortically and subcortically are incompletely understood. We hypothesized that CCEPs propagate as an evoked traveling wave emanating from the site of stimulation. To elicit CCEPs, we applied single-pulse stimulation to stereoelectroencephalography (SEEG) electrodes implanted in 21 adult patients with intractable epilepsy. For each robust CCEP, we measured the timing of the maximal descent in evoked local field potentials and broadband high-gamma power (70-150 Hz) envelopes relative to the distance between the recording and stimulation contacts using three different metrics (i.e., Euclidean distance, path length, geodesic distance), representing direct, subcortical, and transcortical propagation, respectively. Many evoked responses to single-pulse electrical stimulation appear to propagate as traveling waves (~17-30%), even in the sparsely sampled, three-dimensional SEEG space. These results provide new insights into the spatiotemporal dynamics of CCEP propagation.
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Affiliation(s)
- Justin M. Campbell
- MD-PhD Program, School of Medicine, University of Utah, Salt Lake City, UT, USA
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Tyler S. Davis
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Daria Nesterovich Anderson
- School of Biomedical Engineering, Faculty of Engineering, University of Sydney, Sydney, New South Wales, Australia
| | - Amir Arain
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
| | - Cory S. Inman
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Psychology, University of Utah, Salt Lake City, UT, USA
| | - Elliot H. Smith
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - John D. Rolston
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
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20
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Boucher-Routhier M, Thivierge JP. A deep generative adversarial network capturing complex spiral waves in disinhibited circuits of the cerebral cortex. BMC Neurosci 2023; 24:22. [PMID: 36964493 PMCID: PMC10039524 DOI: 10.1186/s12868-023-00792-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/17/2023] [Indexed: 03/26/2023] Open
Abstract
BACKGROUND In the cerebral cortex, disinhibited activity is characterized by propagating waves that spread across neural tissue. In this pathological state, a widely reported form of activity are spiral waves that travel in a circular pattern around a fixed spatial locus termed the center of mass. Spiral waves exhibit stereotypical activity and involve broad patterns of co-fluctuations, suggesting that they may be of lower complexity than healthy activity. RESULTS To evaluate this hypothesis, we performed dense multi-electrode recordings of cortical networks where disinhibition was induced by perfusing a pro-epileptiform solution containing 4-Aminopyridine as well as increased potassium and decreased magnesium. Spiral waves were identified based on a spatially delimited center of mass and a broad distribution of instantaneous phases across electrodes. Individual waves were decomposed into "snapshots" that captured instantaneous neural activation across the entire network. The complexity of these snapshots was examined using a measure termed the participation ratio. Contrary to our expectations, an eigenspectrum analysis of these snapshots revealed a broad distribution of eigenvalues and an increase in complexity compared to baseline networks. A deep generative adversarial network was trained to generate novel exemplars of snapshots that closely captured cortical spiral waves. These synthetic waves replicated key features of experimental data including a tight center of mass, a broad eigenvalue distribution, spatially-dependent correlations, and a high complexity. By adjusting the input to the model, new samples were generated that deviated in systematic ways from the experimental data, thus allowing the exploration of a broad range of states from healthy to pathologically disinhibited neural networks. CONCLUSIONS Together, results show that the complexity of population activity serves as a marker along a continuum from healthy to disinhibited brain states. The proposed generative adversarial network opens avenues for replicating the dynamics of cortical seizures and accelerating the design of optimal neurostimulation aimed at suppressing pathological brain activity.
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Affiliation(s)
- Megan Boucher-Routhier
- School of Psychology, University of Ottawa, 156 Jean-Jacques Lussier, Ottawa, ON, K1N 6N5, Canada
| | - Jean-Philippe Thivierge
- School of Psychology, University of Ottawa, 156 Jean-Jacques Lussier, Ottawa, ON, K1N 6N5, Canada.
- University of Ottawa Brain and Mind Research Institute, 451 Smyth Rd., Ottawa, ON, K1H 8M5, Canada.
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21
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Complexity of cortical wave patterns of the wake mouse cortex. Nat Commun 2023; 14:1434. [PMID: 36918572 PMCID: PMC10015011 DOI: 10.1038/s41467-023-37088-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 03/02/2023] [Indexed: 03/16/2023] Open
Abstract
Rich spatiotemporal dynamics of cortical activity, including complex and diverse wave patterns, have been identified during unconscious and conscious brain states. Yet, how these activity patterns emerge across different levels of wakefulness remain unclear. Here we study the evolution of wave patterns utilizing data from high spatiotemporal resolution optical voltage imaging of mice transitioning from barbiturate-induced anesthesia to wakefulness (N = 5) and awake mice (N = 4). We find that, as the brain transitions into wakefulness, there is a reduction in hemisphere-scale voltage waves, and an increase in local wave events and complexity. A neural mass model recapitulates the essential cellular-level features and shows how the dynamical competition between global and local spatiotemporal patterns and long-range connections can explain the experimental observations. These mechanisms possibly endow the awake cortex with enhanced integrative processing capabilities.
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22
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Erazo-Toscano R, Osan R. Synaptic propagation in neuronal networks with finite-support space-dependent coupling. Phys Rev E 2023; 107:034403. [PMID: 37073055 DOI: 10.1103/physreve.107.034403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 12/16/2022] [Indexed: 04/20/2023]
Abstract
Traveling waves of electrical activity are ubiquitous in biological neuronal networks. Traveling waves in the brain are associated with sensory processing, phase coding, and sleep. The neuron and network parameters that determine traveling waves' evolution are the synaptic space constant, synaptic conductance, membrane time constant, and synaptic decay time constant. We used an abstract neuron model in a one-dimensional network to investigate the propagation characteristics of traveling wave activity. We formulate a set of evolution equations based on the network connectivity parameters. Using a combination of numerical and analytical approaches, we show that these traveling waves are stable to a series of perturbations with biological relevance.
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Affiliation(s)
- Ricardo Erazo-Toscano
- Neuroscience Institute, College of Arts and Sciences, Georgia State University, Atlanta, Georgia 30303, USA
| | - Remus Osan
- Neuroscience Institute, College of Arts and Sciences, Georgia State University, Atlanta, Georgia 30303, USA
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23
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Liu M, Liang Y, Song C, Knöpfel T, Zhou C. Cortex-wide spontaneous activity non-linearly steers propagating sensory-evoked activity in awake mice. Cell Rep 2022; 41:111740. [PMID: 36476858 DOI: 10.1016/j.celrep.2022.111740] [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: 04/13/2022] [Revised: 08/27/2022] [Accepted: 11/07/2022] [Indexed: 12/12/2022] Open
Abstract
The brain responds highly variably to identical sensory inputs, but there is no consensus on the nature of this variability. We explore this question using cortex-wide optical voltage imaging and whisker stimulation in awake mice. Clustering analysis reveals that the sensory-evoked activity propagates over the cortex via distinct pathways associated with distinct behavioral states. The pathway taken by each trial is independent of the level of primary sensory-evoked activation but is partially predictable by the spatiotemporal features of the preceding cortical spontaneous activity patterns. The sensory inputs reduce trial-to-trial variability in brain activity and alter temporal autocorrelation in spatial activity pattern evolutions, suggesting non-linear interactions between evoked activities and spontaneous activities. Further, evoked activities and spontaneous activities occupy different positions in the state space, suggesting that sensory inputs can intricately interact with the internal state to generate large-scale evoked activity patterns not frequented by spontaneous brain states.
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Affiliation(s)
- Mianxin Liu
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Yuqi Liang
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Chenchen Song
- Laboratory for Neuronal Circuit Dynamics, Imperial College London, London, UK
| | - Thomas Knöpfel
- Laboratory for Neuronal Circuit Dynamics, Imperial College London, London, UK.
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong; Research Centre, HKBU Institute of Research and Continuing Education, Virtual University Park Building, South Area Hi-tech Industrial Park, Shenzhen, China.
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24
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Racicot I, Muslimov E, Chemla S, Blaize K, Ferrari M, Chavane F. High resolution, wide field optical imaging of macaque visual cortex with a curved detector. J Neural Eng 2022; 19. [PMID: 36347038 DOI: 10.1088/1741-2552/aca123] [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: 09/20/2022] [Accepted: 11/08/2022] [Indexed: 11/09/2022]
Abstract
Objective. Cortical activity can be recorded using a variety of tools, ranging in scale from the single neuron (microscopic) to the whole brain (macroscopic). There is usually a trade-off between scale and resolution; optical imaging techniques, with their high spatio-temporal resolution and wide field of view, are best suited to study brain activity at the mesoscale. Optical imaging of cortical areas is however in practice limited by the curvature of the brain, which causes the image quality to deteriorate significantly away from the center of the image.Approach. To address this issue and harness the full potential of optical cortical imaging techniques, we developed a new wide-field optical imaging system adapted to the macaque brain. Our system is composed of a curved detector, an aspherical lens and a ring composed of light emitting diodes providing uniform illumination at wavelengths relevant for the different optical imaging methods, including intrinsic and fluorescence imaging.Main results. The system was characterized and compared with the standard macroscope used for cortical imaging, and a three-fold increase of the area in focus was measured as well as a four-fold increase in the evenness of the optical qualityin vivo.Significance. This new instrument, which is to the best of our knowledge the first use of a curved detector for cortical imaging, should facilitate the observation of wide mesoscale phenomena such as dynamic propagating waves within and between cortical maps, which are otherwise difficult to observe due to technical limitations of the currently available recording tools.
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Affiliation(s)
- Isabelle Racicot
- Laboratoire d'Astrophysique de Marseille: Aix-Marseille Univ, CNRS, CNES, LAM, Marseille, France.,Institut de Neurosciences de la Timone: Aix-Marseille Univ, CNRS, INT, Marseille, France
| | - Eduard Muslimov
- Laboratoire d'Astrophysique de Marseille: Aix-Marseille Univ, CNRS, CNES, LAM, Marseille, France.,Kazan National Research Technical University named after A.N. Tupolev KAI, 10 K. Marx, Kazan 420111, Russia.,NOVA Optical IR Instrumentation Group at ASTRON Oude Hoogeveensedijk 4, 7991 PD Dwingeloo, The Netherlands
| | - Sandrine Chemla
- Institut de Neurosciences de la Timone: Aix-Marseille Univ, CNRS, INT, Marseille, France
| | - Kévin Blaize
- Institut de Neurosciences de la Timone: Aix-Marseille Univ, CNRS, INT, Marseille, France
| | - Marc Ferrari
- Laboratoire d'Astrophysique de Marseille: Aix-Marseille Univ, CNRS, CNES, LAM, Marseille, France
| | - Frédéric Chavane
- Institut de Neurosciences de la Timone: Aix-Marseille Univ, CNRS, INT, Marseille, France
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Lee JH, Tsunada J, Vijayan S, Cohen YE. Cortical circuit-based lossless neural integrator for perceptual decision-making: A computational modeling study. Front Comput Neurosci 2022; 16:979830. [DOI: 10.3389/fncom.2022.979830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 10/17/2022] [Indexed: 11/05/2022] Open
Abstract
The intrinsic uncertainty of sensory information (i.e., evidence) does not necessarily deter an observer from making a reliable decision. Indeed, uncertainty can be reduced by integrating (accumulating) incoming sensory evidence. It is widely thought that this accumulation is instantiated via recurrent rate-code neural networks. Yet, these networks do not fully explain important aspects of perceptual decision-making, such as a subject’s ability to retain accumulated evidence during temporal gaps in the sensory evidence. Here, we utilized computational models to show that cortical circuits can switch flexibly between “retention” and “integration” modes during perceptual decision-making. Further, we found that, depending on how the sensory evidence was readout, we could simulate “stepping” and “ramping” activity patterns, which may be analogous to those seen in different studies of decision-making in the primate parietal cortex. This finding may reconcile these previous empirical studies because it suggests these two activity patterns emerge from the same mechanism.
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26
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Jia X, Shao W, Hu N, Shi J, Fan X, Chen C, Wang Y, Chen L, Qiao H, Li X. Learning populations with hubs govern the initiation and propagation of spontaneous bursts in neuronal networks after learning. Front Neurosci 2022; 16:854199. [PMID: 36061604 PMCID: PMC9433803 DOI: 10.3389/fnins.2022.854199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 07/29/2022] [Indexed: 11/13/2022] Open
Abstract
Spontaneous bursts in neuronal networks with propagation involving a large number of synchronously firing neurons are considered to be a crucial feature of these networks both in vivo and in vitro. Recently, learning has been shown to improve the association and synchronization of spontaneous events in neuronal networks by promoting the firing of spontaneous bursts. However, little is known about the relationship between the learning phase and spontaneous bursts. By combining high-resolution measurement with a 4,096-channel complementary metal-oxide-semiconductor (CMOS) microelectrode array (MEA) and graph theory, we studied how the learning phase influenced the initiation of spontaneous bursts in cultured networks of rat cortical neurons in vitro. We found that a small number of selected populations carried most of the stimulus information and contributed to learning. Moreover, several new burst propagation patterns appeared in spontaneous firing after learning. Importantly, these "learning populations" had more hubs in the functional network that governed the initiation of spontaneous burst activity. These results suggest that changes in the functional structure of learning populations may be the key mechanism underlying increased bursts after learning. Our findings could increase understanding of the important role that synaptic plasticity plays in the regulation of spontaneous activity.
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Affiliation(s)
- Xiaoli Jia
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Wenwei Shao
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Nan Hu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Jianxin Shi
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Xiu Fan
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Chong Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Youwei Wang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Liqun Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Huanhuan Qiao
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Xiaohong Li
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
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27
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Visual evoked feedforward-feedback traveling waves organize neural activity across the cortical hierarchy in mice. Nat Commun 2022; 13:4754. [PMID: 35963850 PMCID: PMC9376099 DOI: 10.1038/s41467-022-32378-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 07/27/2022] [Indexed: 12/26/2022] Open
Abstract
Sensory processing is distributed among many brain regions that interact via feedforward and feedback signaling. Neuronal oscillations have been shown to mediate intercortical feedforward and feedback interactions. Yet, the macroscopic structure of the multitude of such oscillations remains unclear. Here, we show that simple visual stimuli reliably evoke two traveling waves with spatial wavelengths that cover much of the cerebral hemisphere in awake mice. 30-50 Hz feedforward waves arise in primary visual cortex (V1) and propagate rostrally, while 3-6 Hz feedback waves originate in the association cortex and flow caudally. The phase of the feedback wave modulates the amplitude of the feedforward wave and synchronizes firing between V1 and parietal cortex. Altogether, these results provide direct experimental evidence that visual evoked traveling waves percolate through the cerebral cortex and coordinate neuronal activity across broadly distributed networks mediating visual processing.
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28
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Dai L, Xu Q, Xiong X, Yu Y, Wang X, Dai H, Zhao H, Ke J. Propagation Structure of Intrinsic Brain Activity in Migraine without Aura. Brain Sci 2022; 12:brainsci12070903. [PMID: 35884710 PMCID: PMC9313295 DOI: 10.3390/brainsci12070903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 07/03/2022] [Accepted: 07/07/2022] [Indexed: 12/02/2022] Open
Abstract
Previous studies have revealed highly reproducible patterns of temporally lagged brain activity in healthy human adults. However, it is unknown whether temporal organization of intrinsic activity is altered in migraines or if it relates to migraine chronification. In this resting-state functional magnetic resonance imaging study, temporal features of intrinsic activity were investigated using resting-state lag analysis, and 39 episodic migraine patients, 17 chronic migraine patients, and 35 healthy controls were assessed. Temporally earlier intrinsic activity in the hippocampal complex was revealed in the chronic migraine group relative to the other two groups. We also found earlier intrinsic activity in the medial prefrontal cortex in chronic compared with episodic migraines. Both migraine groups showed earlier intrinsic activity in the lateral temporal cortex and sensorimotor cortex compared with the healthy control group. Across all patients, headache frequency negatively correlated with temporal lag of the medial prefrontal cortex and hippocampal complex. Disrupted propagation of intrinsic activity in regions involved in sensory, cognitive and affective processing of pain may contribute to abnormal brain function during migraines. Decreased time latency in the lateral temporal cortex and sensorimotor cortex may be common manifestations in episodic and chronic migraines. The temporal features of the medial prefrontal cortex and hippocampal complex were associated with migraine chronification.
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Affiliation(s)
- Lingling Dai
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou 215000, China; (L.D.); (X.X.); (Y.Y.); (X.W.); (H.D.)
- Institute of Medical Imaging, Soochow University, Suzhou 215000, China
| | - Qiang Xu
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China;
| | - Xing Xiong
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou 215000, China; (L.D.); (X.X.); (Y.Y.); (X.W.); (H.D.)
- Institute of Medical Imaging, Soochow University, Suzhou 215000, China
| | - Yang Yu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou 215000, China; (L.D.); (X.X.); (Y.Y.); (X.W.); (H.D.)
- Institute of Medical Imaging, Soochow University, Suzhou 215000, China
| | - Ximing Wang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou 215000, China; (L.D.); (X.X.); (Y.Y.); (X.W.); (H.D.)
- Institute of Medical Imaging, Soochow University, Suzhou 215000, China
| | - Hui Dai
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou 215000, China; (L.D.); (X.X.); (Y.Y.); (X.W.); (H.D.)
- Institute of Medical Imaging, Soochow University, Suzhou 215000, China
| | - Hongru Zhao
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou 215000, China
- Correspondence: (H.Z.); (J.K.)
| | - Jun Ke
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou 215000, China; (L.D.); (X.X.); (Y.Y.); (X.W.); (H.D.)
- Institute of Medical Imaging, Soochow University, Suzhou 215000, China
- Correspondence: (H.Z.); (J.K.)
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29
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Le Bec B, Troncoso XG, Desbois C, Passarelli Y, Baudot P, Monier C, Pananceau M, Frégnac Y. Horizontal connectivity in V1: Prediction of coherence in contour and motion integration. PLoS One 2022; 17:e0268351. [PMID: 35802625 PMCID: PMC9269411 DOI: 10.1371/journal.pone.0268351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 04/26/2022] [Indexed: 11/30/2022] Open
Abstract
This study demonstrates the functional importance of the Surround context relayed laterally in V1 by the horizontal connectivity, in controlling the latency and the gain of the cortical response to the feedforward visual drive. We report here four main findings: 1) a centripetal apparent motion sequence results in a shortening of the spiking latency of V1 cells, when the orientation of the local inducer and the global motion axis are both co-aligned with the RF orientation preference; 2) this contextual effects grows with visual flow speed, peaking at 150–250°/s when it matches the propagation speed of horizontal connectivity (0.15–0.25 mm/ms); 3) For this speed range, the axial sensitivity of V1 cells is tilted by 90° to become co-aligned with the orientation preference axis; 4) the strength of modulation by the surround context correlates with the spatiotemporal coherence of the apparent motion flow. Our results suggest an internally-generated binding process, linking local (orientation /position) and global (motion/direction) features as early as V1. This long-range diffusion process constitutes a plausible substrate in V1 of the human psychophysical bias in speed estimation for collinear motion. Since it is demonstrated in the anesthetized cat, this novel form of contextual control of the cortical gain and phase is a built-in property in V1, whose expression does not require behavioral attention and top-down control from higher cortical areas. We propose that horizontal connectivity participates in the propagation of an internal “prediction” wave, shaped by visual experience, which links contour co-alignment and global axial motion at an apparent speed in the range of saccade-like eye movements.
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Affiliation(s)
- Benoit Le Bec
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Xoana G. Troncoso
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Christophe Desbois
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
- Ecole Nationale Vétérinaire d’Alfort, Maisons-Alfort, France
| | - Yannick Passarelli
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Pierre Baudot
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Cyril Monier
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Marc Pananceau
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
| | - Yves Frégnac
- NeuroPSI-UNIC, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, Gif-sur-Yvette, France
- * E-mail:
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30
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Powell H, Winkel M, Hopp AV, Linde H. A hybrid biological neural network model for solving problems in cognitive planning. Sci Rep 2022; 12:10628. [PMID: 35739285 PMCID: PMC9226121 DOI: 10.1038/s41598-022-11567-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 04/12/2022] [Indexed: 11/09/2022] Open
Abstract
A variety of behaviors, like spatial navigation or bodily motion, can be formulated as graph traversal problems through cognitive maps. We present a neural network model which can solve such tasks and is compatible with a broad range of empirical findings about the mammalian neocortex and hippocampus. The neurons and synaptic connections in the model represent structures that can result from self-organization into a cognitive map via Hebbian learning, i.e. into a graph in which each neuron represents a point of some abstract task-relevant manifold and the recurrent connections encode a distance metric on the manifold. Graph traversal problems are solved by wave-like activation patterns which travel through the recurrent network and guide a localized peak of activity onto a path from some starting position to a target state.
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Affiliation(s)
- Henry Powell
- Merck KGaA, Darmstadt, Germany. .,University of Glasgow, Glasgow, Scotland, UK.
| | | | | | - Helmut Linde
- Merck KGaA, Darmstadt, Germany.,Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
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31
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Woolnough O, Forseth KJ, Rollo PS, Roccaforte ZJ, Tandon N. Event-Related Phase Synchronization Propagates Rapidly across Human Ventral Visual Cortex. Neuroimage 2022; 256:119262. [PMID: 35504563 PMCID: PMC9382906 DOI: 10.1016/j.neuroimage.2022.119262] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 03/31/2022] [Accepted: 04/27/2022] [Indexed: 11/01/2022] Open
Abstract
Visual inputs to early visual cortex integrate with semantic, linguistic and memory inputs in higher visual cortex, in a manner that is rapid and accurate, and enables complex computations such as face recognition and word reading. This implies the existence of fundamental organizational principles that enable such efficiency. To elaborate on this, we performed intracranial recordings in 82 individuals while they performed tasks of varying visual and cognitive complexity. We discovered that visual inputs induce highly organized posterior-to-anterior propagating patterns of phase modulation across the ventral occipitotemporal cortex. At individual electrodes there was a stereotyped temporal pattern of phase progression following both stimulus onset and offset, consistent across trials and tasks. The phase of low frequency activity in anterior regions was predicted by the prior phase in posterior cortical regions. This spatiotemporal propagation of phase likely serves as a feed-forward organizational influence enabling the integration of information across the ventral visual stream. This phase modulation manifests as the early components of the event related potential; one of the most commonly used measures in human electrophysiology. These findings illuminate fundamental organizational principles of the higher order visual system that enable the rapid recognition and characterization of a variety of inputs.
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Affiliation(s)
- Oscar Woolnough
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, 77030, United States of America; Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, United States of America
| | - Kiefer J Forseth
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, 77030, United States of America; Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, United States of America
| | - Patrick S Rollo
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, 77030, United States of America; Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, United States of America
| | - Zachary J Roccaforte
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, 77030, United States of America; Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, United States of America
| | - Nitin Tandon
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, 77030, United States of America; Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, United States of America; Memorial Hermann Hospital, Texas Medical Center, Houston, TX, 77030, United States of America.
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32
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Bhattacharya S, Donoghue JA, Mahnke M, Brincat SL, Brown EN, Miller EK. Propofol Anesthesia Alters Cortical Traveling Waves. J Cogn Neurosci 2022; 34:1274-1286. [PMID: 35468201 DOI: 10.1162/jocn_a_01856] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Oscillatory dynamics in cortex seem to organize into traveling waves that serve a variety of functions. Recent studies show that propofol, a widely used anesthetic, dramatically alters cortical oscillations by increasing slow-delta oscillatory power and coherence. It is not known how this affects traveling waves. We compared traveling waves across the cortex of non-human primates before, during, and after propofol-induced loss of consciousness (LOC). After LOC, traveling waves in the slow-delta (∼1 Hz) range increased, grew more organized, and traveled in different directions relative to the awake state. Higher frequency (8-30 Hz) traveling waves, by contrast, decreased, lost structure, and switched to directions where the slow-delta waves were less frequent. The results suggest that LOC may be due, in part, to increases in the strength and direction of slow-delta traveling waves that, in turn, alter and disrupt traveling waves in the higher frequencies associated with cognition.
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Affiliation(s)
| | | | | | | | - Emery N Brown
- Massachusetts Institute of Technology, Cambridge.,Massachusetts General Hospital/Harvard Medical School, Boston
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33
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Drewes J, Muschter E, Zhu W, Melcher D. Individual resting-state alpha peak frequency and within-trial changes in alpha peak frequency both predict visual dual-pulse segregation performance. Cereb Cortex 2022; 32:5455-5466. [PMID: 35137008 PMCID: PMC9712717 DOI: 10.1093/cercor/bhac026] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 01/13/2022] [Accepted: 01/14/2022] [Indexed: 12/27/2022] Open
Abstract
Although sensory input is continuous, information must be combined over time to guide action and cognition, leading to the proposal of temporal sampling windows. A number of studies have suggested that a 10-Hz sampling window might be involved in the "frame rate" of visual processing. To investigate this, we tested the ability of participants to localize and enumerate 1 or 2 visual flashes presented either at near-threshold or full-contrast intensities, while recording magnetoencephalography. The inter-stimulus interval (ISI) between the 2 flashes was varied across trials. Performance in distinguishing between 1 and 2 flashes was linked to the alpha frequency, both at the individual level and trial-by-trial. Participants with a higher resting-state alpha peak frequency showed the greatest improvement in performance as a function of ISI within a 100-ms time window, while those with slower alpha improved more when ISI exceeded 100 ms. On each trial, correct enumeration (1 vs. 2) performance was paired with faster pre-stimulus instantaneous alpha frequency. Our results suggest that visual sampling/processing speed, linked to peak alpha frequency, is both an individual trait and can vary in a state-dependent manner.
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Affiliation(s)
- Jan Drewes
- Corresponding author: Institute of Brain and Psychological Sciences, Lion Hill Campus, Sichuan Normal University, 5 Jing'an Road, Chengdu 610066, Sichuan, China.
| | - Evelyn Muschter
- Department of Psychology and Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto, Italy,Centre for Tactile Internet with Human-in-the-Loop (CeTI), Technische Universität Dresden, 01069 Dresden, Germany
| | - Weina Zhu
- Department of Psychology and Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto, Italy,School of Information Science, Yunnan University, 650091 Kunming, China
| | - David Melcher
- Department of Psychology and Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto, Italy,Psychology Program, Division of Science, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
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34
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Cortical traveling waves reflect state-dependent hierarchical sequencing of local regions in the human connectome network. Sci Rep 2022; 12:334. [PMID: 35013416 PMCID: PMC8748796 DOI: 10.1038/s41598-021-04169-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 12/14/2021] [Indexed: 11/08/2022] Open
Abstract
Recent human studies using electrocorticography have demonstrated that alpha and theta band oscillations form traveling waves on the cortical surface. According to neural synchronization theories, the cortical traveling waves may group local cortical regions and sequence them by phase synchronization; however these contributions have not yet been assessed. This study aimed to evaluate the functional contributions of traveling waves using connectome-based network modeling. In the simulation, we observed stable traveling waves on the entire cortical surface wherein the topographical pattern of these phases was substantially correlated with the empirically obtained resting-state networks, and local radial waves also appeared within the size of the empirical networks (< 50 mm). Importantly, individual regions in the entire network were instantaneously sequenced by their internal frequencies, and regions with higher intrinsic frequency were seen in the earlier phases of the traveling waves. Based on the communication-through-coherence theory, this phase configuration produced a hierarchical organization of each region by unidirectional communication between the arbitrarily paired regions. In conclusion, cortical traveling waves reflect the intrinsic frequency-dependent hierarchical sequencing of local regions, global traveling waves sequence the set of large-scale cortical networks, and local traveling waves sequence local regions within individual cortical networks.
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35
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Orczyk JJ, Kajikawa Y. Magnifying Traveling Waves on the Scalp. Brain Topogr 2022; 35:162-168. [PMID: 34086189 PMCID: PMC8759578 DOI: 10.1007/s10548-021-00853-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Accepted: 05/26/2021] [Indexed: 01/03/2023]
Abstract
Traveling waves appear in various signals that measure neuronal activity. Some signals measured in animals have singles-cell resolution and directly point to neuronal activity. In those cases, activation of distributed neurons forms a wave front, and the front propagates across the cortical surface. Other signals are variants of neuroelectric potentials, i.e. electroencephalography, electrocorticography and field potentials. Instead of having fine spatial resolution, these signals reflect the activity of neuronal populations via volume conduction (VC). Sources of traveling waves in neuroelectric potentials have not been well addressed so far. As animal studies show propagating activation of neurons that spread in measured areas, it is often considered that neuronal activations during scalp waves have similar trajectories of activation, spreading like scalp waves. However, traveling waves on the scalp differ from those found directly on the cortical surface in several dimensions: traveling velocity, traveling distance and areal size occupied by single polarity. We describe that the simplest sources can produce scalp waves with perceived spatial dimensions which are actually a magnification of neuronal activity emanating from local sources due to VC. This viewpoint is not a rigorous proof of our magnification concept. However, we suggest the possibility that the actual dimensions of neuronal activity producing traveling waves is not as large as the dimension of the traveling waves.
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Affiliation(s)
- John J. Orczyk
- Translational Neuroscience Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY
| | - Yoshinao Kajikawa
- Translational Neuroscience Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY,Department of Psychiatry, New York University School of Medicine, New York, NY
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36
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Martínez-Cañada P, Noei S, Panzeri S. Methods for inferring neural circuit interactions and neuromodulation from local field potential and electroencephalogram measures. Brain Inform 2021; 8:27. [PMID: 34910260 PMCID: PMC8674171 DOI: 10.1186/s40708-021-00148-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 11/29/2021] [Indexed: 11/10/2022] Open
Abstract
Electrical recordings of neural mass activity, such as local field potentials (LFPs) and electroencephalograms (EEGs), have been instrumental in studying brain function. However, these aggregate signals lack cellular resolution and thus are not easy to be interpreted directly in terms of parameters of neural microcircuits. Developing tools for a reliable estimation of key neural parameters from these signals, such as the interaction between excitation and inhibition or the level of neuromodulation, is important for both neuroscientific and clinical applications. Over the years, we have developed tools based on neural network modeling and computational analysis of empirical data to estimate neural parameters from aggregate neural signals. This review article gives an overview of the main computational tools that we have developed and employed to invert LFPs and EEGs in terms of circuit-level neural phenomena, and outlines future challenges and directions for future research.
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Affiliation(s)
- Pablo Martínez-Cañada
- Neural Computation Laboratory, Istituto Italiano Di Tecnologia, Genova and Rovereto, Italy
- Optical Approaches To Brain Function Laboratory, Istituto Italiano Di Tecnologia, Genova, Italy
| | - Shahryar Noei
- Neural Computation Laboratory, Istituto Italiano Di Tecnologia, Genova and Rovereto, Italy
- CIMeC, University of Trento, Rovereto, Italy
| | - Stefano Panzeri
- Neural Computation Laboratory, Istituto Italiano Di Tecnologia, Genova and Rovereto, Italy.
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
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37
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Afrashteh N, Inayat S, Bermudez-Contreras E, Luczak A, McNaughton BL, Mohajerani MH. Spatiotemporal structure of sensory-evoked and spontaneous activity revealed by mesoscale imaging in anesthetized and awake mice. Cell Rep 2021; 37:110081. [PMID: 34879278 DOI: 10.1016/j.celrep.2021.110081] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 05/25/2021] [Accepted: 11/10/2021] [Indexed: 11/22/2022] Open
Abstract
Stimuli-evoked and spontaneous brain activity propagates across the cortex in diverse spatiotemporal patterns. Despite extensive studies, the relationship between spontaneous and evoked activity is poorly understood. We investigate this relationship by comparing the amplitude, speed, direction, and complexity of propagation trajectories of spontaneous and evoked activity elicited with visual, auditory, and tactile stimuli using mesoscale wide-field imaging in mice. For both spontaneous and evoked activity, the speed and direction of propagation is modulated by the amplitude. However, spontaneous activity has a higher complexity of the propagation trajectories. For low stimulus strengths, evoked activity amplitude and speed is similar to that of spontaneous activity but becomes dissimilar at higher stimulus strengths. These findings are consistent with observations that primary sensory areas receive widespread inputs from other cortical regions, and during rest, the cortex tends to reactivate traces of complex multisensory experiences that might have occurred in exhibition of different behaviors.
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Affiliation(s)
- Navvab Afrashteh
- University of Lethbridge, Faculty of Arts and Sciences, Department of Neuroscience, 4401 University Dr. W., Lethbridge, Alberta T1K 3M4, Canada
| | - Samsoon Inayat
- University of Lethbridge, Faculty of Arts and Sciences, Department of Neuroscience, 4401 University Dr. W., Lethbridge, Alberta T1K 3M4, Canada
| | - Edgar Bermudez-Contreras
- University of Lethbridge, Faculty of Arts and Sciences, Department of Neuroscience, 4401 University Dr. W., Lethbridge, Alberta T1K 3M4, Canada
| | - Artur Luczak
- University of Lethbridge, Faculty of Arts and Sciences, Department of Neuroscience, 4401 University Dr. W., Lethbridge, Alberta T1K 3M4, Canada
| | - Bruce L McNaughton
- University of Lethbridge, Faculty of Arts and Sciences, Department of Neuroscience, 4401 University Dr. W., Lethbridge, Alberta T1K 3M4, Canada; Center for Neurobiology of Learning and Memory, Department of Neurobiology and Behavior, University of California, Irvine, CA 92603, USA
| | - Majid H Mohajerani
- University of Lethbridge, Faculty of Arts and Sciences, Department of Neuroscience, 4401 University Dr. W., Lethbridge, Alberta T1K 3M4, Canada.
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Baker V, Cruz L. Traveling Waves in Quasi-One-Dimensional Neuronal Minicolumns. Neural Comput 2021; 34:78-103. [PMID: 34758481 DOI: 10.1162/neco_a_01451] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 07/03/2021] [Indexed: 11/04/2022]
Abstract
Traveling waves of neuronal activity in the cortex have been observed in vivo. These traveling waves have been correlated to various features of observed cortical dynamics, including spike timing variability and correlated fluctuations in neuron membrane potential. Although traveling waves are typically studied as either strictly one-dimensional or two-dimensional excitations, here we investigate the conditions for the existence of quasi-one-dimensional traveling waves that could be sustainable in parts of the brain containing cortical minicolumns. For that, we explore a quasi-one-dimensional network of heterogeneous neurons with a biologically influenced computational model of neuron dynamics and connectivity. We find that background stimulus reliably evokes traveling waves in networks with local connectivity between neurons. We also observe traveling waves in fully connected networks when a model for action potential propagation speed is incorporated. The biological properties of the neurons influence the generation and propagation of the traveling waves. Our quasi-one-dimensional model is not only useful for studying the basic properties of traveling waves in neuronal networks; it also provides a simplified representation of possible wave propagation in columnar or minicolumnar networks found in the cortex.
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Affiliation(s)
- Vincent Baker
- Department of Physics, Drexel University, Philadelphia, PA 19104, U.S.A.
| | - Luis Cruz
- Department of Physics, Drexel University, Philadelphia, PA 19104, U.S.A.
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Davis ZW, Benigno GB, Fletterman C, Desbordes T, Steward C, Sejnowski TJ, H Reynolds J, Muller L. Spontaneous traveling waves naturally emerge from horizontal fiber time delays and travel through locally asynchronous-irregular states. Nat Commun 2021; 12:6057. [PMID: 34663796 PMCID: PMC8523565 DOI: 10.1038/s41467-021-26175-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 09/17/2021] [Indexed: 11/25/2022] Open
Abstract
Studies of sensory-evoked neuronal responses often focus on mean spike rates, with fluctuations treated as internally-generated noise. However, fluctuations of spontaneous activity, often organized as traveling waves, shape stimulus-evoked responses and perceptual sensitivity. The mechanisms underlying these waves are unknown. Further, it is unclear whether waves are consistent with the low rate and weakly correlated “asynchronous-irregular” dynamics observed in cortical recordings. Here, we describe a large-scale computational model with topographically-organized connectivity and conduction delays relevant to biological scales. We find that spontaneous traveling waves are a general property of these networks. The traveling waves that occur in the model are sparse, with only a small fraction of neurons participating in any individual wave. Consequently, they do not induce measurable spike correlations and remain consistent with locally asynchronous irregular states. Further, by modulating local network state, they can shape responses to incoming inputs as observed in vivo. Spontaneous traveling cortical waves shape neural responses. Using a large-scale computational model, the authors show that transmission delays shape locally asynchronous spiking dynamics into traveling waves without inducing correlations and boost responses to external input, as observed in vivo.
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Affiliation(s)
- Zachary W Davis
- The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Gabriel B Benigno
- Department of Applied Mathematics, Western University, London, ON, Canada.,Brain and Mind Institute, Western University, London, ON, Canada
| | | | - Theo Desbordes
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | | | - John H Reynolds
- The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Lyle Muller
- Department of Applied Mathematics, Western University, London, ON, Canada. .,Brain and Mind Institute, Western University, London, ON, Canada.
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40
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Tu Y, Ta D, Lu ZL, Wang Y. Topological Receptive Field Model for Human Retinotopic Mapping. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2021; 12907:639-649. [PMID: 34746937 PMCID: PMC8570543 DOI: 10.1007/978-3-030-87234-2_60] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The mapping between visual inputs on the retina and neuronal activations in the visual cortex, i.e., retinotopic map, is an essential topic in vision science and neuroscience. Human retinotopic maps can be revealed by analyzing the functional magnetic resonance imaging (fMRI) signal responses to designed visual stimuli in vivo. Neurophysiology studies summarized that visual areas are topological (i.e., nearby neurons have receptive fields at nearby locations in the image). However, conventional fMRI-based analyses frequently generate non-topological results because they process fMRI signals on a voxel-wise basis, without considering the neighbor relations on the surface. Here we propose a topological receptive field (tRF) model which imposes the topological condition when decoding retinotopic fMRI signals. More specifically, we parametrized the cortical surface to a unit disk, characterized the topological condition by tRF, and employed an efficient scheme to solve the tRF model. We tested our framework on both synthetic and human fMRI data. Experimental results showed that the tRF model could remove the topological violations, improve model explaining power, and generate biologically plausible retinotopic maps. The proposed framework is general and can be applied to other sensory maps.
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Affiliation(s)
- Yanshuai Tu
- Arizona State University, Tempe AZ 85201, USA
| | - Duyan Ta
- Arizona State University, Tempe AZ 85201, USA
| | - Zhong-Lin Lu
- New York University, New York, NY
- NYU Shanghai, Shanghai, China
| | - Yalin Wang
- Arizona State University, Tempe AZ 85201, USA
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41
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Orczyk JJ, Barczak A, Costa-Faidella J, Kajikawa Y. Cross Laminar Traveling Components of Field Potentials due to Volume Conduction of Non-Traveling Neuronal Activity in Macaque Sensory Cortices. J Neurosci 2021; 41:7578-7590. [PMID: 34321312 PMCID: PMC8425975 DOI: 10.1523/jneurosci.3225-20.2021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 06/25/2021] [Accepted: 06/29/2021] [Indexed: 11/21/2022] Open
Abstract
Field potentials (FPs) reflect neuronal activities in the brain, and often exhibit traveling peaks across recording sites. While traveling FPs are interpreted as propagation of neuronal activity, not all studies directly reveal such propagating patterns of neuronal activation. Neuronal activity is associated with transmembrane currents that form dipoles and produce negative and positive fields. Thereby, FP components reverse polarity between those fields and have minimal amplitudes at the center of dipoles. Although their amplitudes could be smaller, FPs are never flat even around these reversals. What occurs around the reversal has not been addressed explicitly, although those are rationally in the middle of active neurons. We show that sensory FPs around the reversal appeared with peaks traveling across cortical laminae in macaque sensory cortices. Interestingly, analyses of current source density did not depict traveling patterns but lamina-delimited current sinks and sources. We simulated FPs produced by volume conduction of a simplified 2 dipoles' model mimicking sensory cortical laminar current source density components. While FPs generated by single dipoles followed the temporal patterns of the dipole moments without traveling peaks, FPs generated by concurrently active dipole moments appeared with traveling components in the vicinity of dipoles by superimposition of individually non-traveling FPs generated by single dipoles. These results indicate that not all traveling FP are generated by traveling neuronal activity, and that recording positions need to be taken into account to describe FP peak components around active neuronal populations.SIGNIFICANCE STATEMENT Field potentials (FPs) generated by neuronal activity in the brain occur with fields of opposite polarity. Likewise, in the cerebral cortices, they have mirror-imaged waveforms in upper and lower layers. We show that FPs appear like traveling across the cortical layers. Interestingly, the traveling FPs occur without traveling components of current source density, which represents transmembrane currents associated with neuronal activity. These seemingly odd findings are explained using current source density models of multiple dipoles. Concurrently active, non-traveling dipoles produce FPs as mixtures of FPs produced by individual dipoles, and result in traveling FP waveforms as the mixing ratio depends on the distances from those dipoles. The results suggest that not all traveling FP components are associated with propagating neuronal activity.
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Affiliation(s)
- John J Orczyk
- Translational Neuroscience Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York 10962
| | - Annamaria Barczak
- Translational Neuroscience Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York 10962
| | - Jordi Costa-Faidella
- Translational Neuroscience Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York 10962
- Brainlab - Cognitive Neuroscience Research Group, Department of Clinical Psychology and Psychobiology, University of Barcelona, Barcelona, Catalonia 08035, Spain
- Institute of Neurosciences, University of Barcelona, Barcelona, Catalonia 08035, Spain
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain, Barcelona, Catalonia 08950
| | - Yoshinao Kajikawa
- Translational Neuroscience Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York 10962
- Department of Psychiatry, New York University School of Medicine, New York, New York 10016
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42
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Linden NJ, Tabuena DR, Steinmetz NA, Moody WJ, Brunton SL, Brunton BW. Go with the FLOW: visualizing spatiotemporal dynamics in optical widefield calcium imaging. J R Soc Interface 2021; 18:20210523. [PMID: 34428947 PMCID: PMC8385384 DOI: 10.1098/rsif.2021.0523] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 08/02/2021] [Indexed: 12/11/2022] Open
Abstract
Widefield calcium imaging has recently emerged as a powerful experimental technique to record coordinated large-scale brain activity. These measurements present a unique opportunity to characterize spatiotemporally coherent structures that underlie neural activity across many regions of the brain. In this work, we leverage analytic techniques from fluid dynamics to develop a visualization framework that highlights features of flow across the cortex, mapping wavefronts that may be correlated with behavioural events. First, we transform the time series of widefield calcium images into time-varying vector fields using optic flow. Next, we extract concise diagrams summarizing the dynamics, which we refer to as FLOW (flow lines in optical widefield imaging) portraits. These FLOW portraits provide an intuitive map of dynamic calcium activity, including regions of initiation and termination, as well as the direction and extent of activity spread. To extract these structures, we use the finite-time Lyapunov exponent technique developed to analyse time-varying manifolds in unsteady fluids. Importantly, our approach captures coherent structures that are poorly represented by traditional modal decomposition techniques. We demonstrate the application of FLOW portraits on three simple synthetic datasets and two widefield calcium imaging datasets, including cortical waves in the developing mouse and spontaneous cortical activity in an adult mouse.
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Affiliation(s)
- Nathaniel J. Linden
- Department of Bioengineering, University of Washington, Seattle, WA 98195-0005, USA
- Department of Biology, University of Washington, Seattle, WA 98195-0005, USA
| | - Dennis R. Tabuena
- Department of Biology, University of Washington, Seattle, WA 98195-0005, USA
- Graduate Program in Neuroscience, University of Washington, Seattle, WA 98195-0005, USA
| | - Nicholas A. Steinmetz
- Department of Biological Structure, University of Washington, Seattle, WA 98195-0005, USA
| | - William J. Moody
- Department of Biology, University of Washington, Seattle, WA 98195-0005, USA
| | - Steven L. Brunton
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195-0005, USA
| | - Bingni W. Brunton
- Department of Biology, University of Washington, Seattle, WA 98195-0005, USA
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43
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Bhattacharya S, Cauchois MBL, Iglesias PA, Chen ZS. The impact of a closed-loop thalamocortical model on the spatiotemporal dynamics of cortical and thalamic traveling waves. Sci Rep 2021; 11:14359. [PMID: 34257333 PMCID: PMC8277909 DOI: 10.1038/s41598-021-93618-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 06/21/2021] [Indexed: 12/23/2022] Open
Abstract
Propagation of activity in spatially structured neuronal networks has been observed in awake, anesthetized, and sleeping brains. How these wave patterns emerge and organize across brain structures, and how network connectivity affects spatiotemporal neural activity remains unclear. Here, we develop a computational model of a two-dimensional thalamocortical network, which gives rise to emergent traveling waves similar to those observed experimentally. We illustrate how spontaneous and evoked oscillatory activity in space and time emerge using a closed-loop thalamocortical architecture, sustaining smooth waves in the cortex and staggered waves in the thalamus. We further show that intracortical and thalamocortical network connectivity, cortical excitation/inhibition balance, and thalamocortical or corticothalamic delay can independently or jointly change the spatiotemporal patterns (radial, planar and rotating waves) and characteristics (speed, direction, and frequency) of cortical and thalamic traveling waves. Computer simulations predict that increased thalamic inhibition induces slower cortical frequencies and that enhanced cortical excitation increases traveling wave speed and frequency. Overall, our results provide insight into the genesis and sustainability of thalamocortical spatiotemporal patterns, showing how simple synaptic alterations cause varied spontaneous and evoked wave patterns. Our model and simulations highlight the need for spatially spread neural recordings to uncover critical circuit mechanisms for brain functions.
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Affiliation(s)
- Sayak Bhattacharya
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Matthieu B L Cauchois
- Department of Mechanical Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Pablo A Iglesias
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
| | - Zhe Sage Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, 10016, USA.
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44
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Salamanca-Giron RF, Raffin E, Zandvliet SB, Seeber M, Michel CM, Sauseng P, Huxlin KR, Hummel FC. Enhancing visual motion discrimination by desynchronizing bifocal oscillatory activity. Neuroimage 2021; 240:118299. [PMID: 34171500 DOI: 10.1016/j.neuroimage.2021.118299] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 06/11/2021] [Accepted: 06/20/2021] [Indexed: 11/17/2022] Open
Abstract
Visual motion discrimination involves reciprocal interactions in the alpha band between the primary visual cortex (V1) and mediotemporal areas (V5/MT). We investigated whether modulating alpha phase synchronization using individualized multisite transcranial alternating current stimulation (tACS) over V5 and V1 regions would improve motion discrimination. We tested 3 groups of healthy subjects with the following conditions: (1) individualized In-Phase V1alpha-V5alpha tACS (0° lag), (2) individualized Anti-Phase V1alpha-V5alpha tACS (180° lag) and (3) sham tACS. Motion discrimination and EEG activity were recorded before, during and after tACS. Performance significantly improved in the Anti-Phase group compared to the In-Phase group 10 and 30 min after stimulation. This result was explained by decreases in bottom-up alpha-V1 gamma-V5 phase-amplitude coupling. One possible explanation of these results is that Anti-Phase V1alpha-V5alpha tACS might impose an optimal phase lag between stimulation sites due to the inherent speed of wave propagation, hereby supporting optimized neuronal communication.
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Affiliation(s)
- Roberto F Salamanca-Giron
- Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Campus Biotech, Room H4.3.132.084, Chemin des Mines 9, Geneva, Switzerland; Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Clinique Romande de Readaptation (CRR), EPFL Valais, Sion, Switzerland
| | - Estelle Raffin
- Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Campus Biotech, Room H4.3.132.084, Chemin des Mines 9, Geneva, Switzerland; Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Clinique Romande de Readaptation (CRR), EPFL Valais, Sion, Switzerland
| | - Sarah B Zandvliet
- Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Campus Biotech, Room H4.3.132.084, Chemin des Mines 9, Geneva, Switzerland; Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Clinique Romande de Readaptation (CRR), EPFL Valais, Sion, Switzerland
| | - Martin Seeber
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland; Lemanic Biomedical Imaging Centre (CIBM), Lausanne, Geneva, Switzerland
| | - Paul Sauseng
- Department of Psychology, LMU Munich, Leopoldstr. 13, Munich 80802, Germany
| | - Krystel R Huxlin
- The Flaum Eye Institute and Center for Visual Science, University of Rochester, Rochester, NY, USA
| | - Friedhelm C Hummel
- Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Campus Biotech, Room H4.3.132.084, Chemin des Mines 9, Geneva, Switzerland; Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Clinique Romande de Readaptation (CRR), EPFL Valais, Sion, Switzerland; Clinical Neuroscience, University of Geneva Medical School, Geneva, Switzerland.
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45
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Byrne Á, Ross J, Nicks R, Coombes S. Mean-Field Models for EEG/MEG: From Oscillations to Waves. Brain Topogr 2021; 35:36-53. [PMID: 33993357 PMCID: PMC8813727 DOI: 10.1007/s10548-021-00842-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 04/21/2021] [Indexed: 11/24/2022]
Abstract
Neural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of within-population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves.
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Affiliation(s)
- Áine Byrne
- School of Mathematics and Statistics, Science Centre, University College Dublin, South Belfield, Dublin 4, Ireland.
| | - James Ross
- School of Mathematical Sciences, Centre for Mathematical Medicine and Biology, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Rachel Nicks
- School of Mathematical Sciences, Centre for Mathematical Medicine and Biology, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Stephen Coombes
- School of Mathematical Sciences, Centre for Mathematical Medicine and Biology, University of Nottingham, Nottingham, NG7 2RD, UK
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46
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Ito Y, Toyoizumi T. Learning poly-synaptic paths with traveling waves. PLoS Comput Biol 2021; 17:e1008700. [PMID: 33561118 PMCID: PMC7928500 DOI: 10.1371/journal.pcbi.1008700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 03/03/2021] [Accepted: 01/11/2021] [Indexed: 11/18/2022] Open
Abstract
Traveling waves are commonly observed across the brain. While previous studies have suggested the role of traveling waves in learning, the mechanism remains unclear. We adopted a computational approach to investigate the effect of traveling waves on synaptic plasticity. Our results indicate that traveling waves facilitate the learning of poly-synaptic network paths when combined with a reward-dependent local synaptic plasticity rule. We also demonstrate that traveling waves expedite finding the shortest paths and learning nonlinear input/output mapping, such as exclusive or (XOR) function. There are approximately 1011 neurons with 1014 connections in the human brain. Information transmission among neurons in this large network is considered crucial for our behavior. To achieve this, multiple synaptic connections along a poly-synaptic network path must be adjusted coherently during learning. Because the previously proposed reward-dependent synaptic plasticity rule requires coactivation of presynaptic and postsynaptic neurons, learning can fail if a subset of neurons along a distant network path is inactive at the beginning of learning. We suggest that traveling waves that are initiated at an information source can mitigate this problem. We performed computer simulations of spiking neural networks with reward-dependent local synaptic plasticity rules and traveling waves. Our results show that this combination facilitates the learning and refinement of synaptic network paths. We argue that these features are a general biological strategy for maintaining and optimizing our brain function. Our research provides new insights into how complex neural networks in the brain form during learning and memory consolidation.
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Affiliation(s)
- Yoshiki Ito
- Graduate School of Information and Technology, the Department of Mechano-Informatics, the University of Tokyo, Tokyo, Japan
- * E-mail: (YI); (TT)
| | - Taro Toyoizumi
- Lab for Neural Computation and Adaptation, RIKEN Center for Brain Science, Saitama, Japan
- Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo, Tokyo, Japan
- * E-mail: (YI); (TT)
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47
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Turning the Stimulus On and Off Changes the Direction of α Traveling Waves. eNeuro 2020; 7:ENEURO.0218-20.2020. [PMID: 33168617 PMCID: PMC7688302 DOI: 10.1523/eneuro.0218-20.2020] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 10/22/2020] [Accepted: 10/23/2020] [Indexed: 12/15/2022] Open
Abstract
Traveling waves have been studied to characterize the complex spatiotemporal dynamics of the brain. Several studies have suggested that the propagation direction of α traveling waves can be task dependent. For example, a recent electroencephalography (EEG) study from our group found that forward waves (i.e., occipital to frontal, FW waves) were observed during visual processing, whereas backward waves (i.e., frontal to occipital, BW waves) mostly occurred in the absence of sensory input. These EEG recordings, however, were obtained from different experimental sessions and different groups of subjects. To further examine how the waves’ direction changes between task conditions, 13 human participants were tested on a target detection task while EEG signals were recorded simultaneously. We alternated visual stimulation (5-s display of visual luminance sequences) and resting state (5 s of black screen) within each single trial, allowing us to monitor the moment-to-moment progression of traveling waves. As expected, the direction of α waves was closely linked with task conditions. First, FW waves from occipital to frontal regions, absent during rest, emerged as a result of visual processing, while BW waves in the opposite direction dominated in the absence of visual inputs, and were reduced (but not eliminated) by external visual inputs. Second, during visual stimulation (but not rest), both waves coexisted on average, but were negatively correlated. In summary, we conclude that the functional role of α traveling waves is closely related with their propagating direction, with stimulus-evoked FW waves supporting visual processing and spontaneous BW waves involved more in top-down control.
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48
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Alamia A, Timmermann C, Nutt DJ, VanRullen R, Carhart-Harris RL. DMT alters cortical travelling waves. eLife 2020; 9:e59784. [PMID: 33043883 PMCID: PMC7577737 DOI: 10.7554/elife.59784] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 10/11/2020] [Indexed: 12/25/2022] Open
Abstract
Psychedelic drugs are potent modulators of conscious states and therefore powerful tools for investigating their neurobiology. N,N, Dimethyltryptamine (DMT) can rapidly induce an extremely immersive state of consciousness characterized by vivid and elaborate visual imagery. Here, we investigated the electrophysiological correlates of the DMT-induced altered state from a pool of participants receiving DMT and (separately) placebo (saline) while instructed to keep their eyes closed. Consistent with our hypotheses, results revealed a spatio-temporal pattern of cortical activation (i.e. travelling waves) similar to that elicited by visual stimulation. Moreover, the typical top-down alpha-band rhythms of closed-eyes rest were significantly decreased, while the bottom-up forward wave was significantly increased. These results support a recent model proposing that psychedelics reduce the 'precision-weighting of priors', thus altering the balance of top-down versus bottom-up information passing. The robust hypothesis-confirming nature of these findings imply the discovery of an important mechanistic principle underpinning psychedelic-induced altered states.
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Affiliation(s)
| | - Christopher Timmermann
- Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Faculty of Medicine, Imperial CollegeLondonUnited Kingdom
- Centre for Psychedelic Research, Division of Psychiatry, Department of Brain Sciences, Imperial College LondonLondonUnited Kingdom
| | - David J Nutt
- Centre for Psychedelic Research, Division of Psychiatry, Department of Brain Sciences, Imperial College LondonLondonUnited Kingdom
| | - Rufin VanRullen
- Cerco, CNRS Université de ToulouseToulouseFrance
- Artificial and Natural Intelligence Toulouse Institute (ANITI)ToulouseFrance
| | - Robin L Carhart-Harris
- Centre for Psychedelic Research, Division of Psychiatry, Department of Brain Sciences, Imperial College LondonLondonUnited Kingdom
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Tu Y, Ta D, Lu ZL, Wang Y. Optimizing Visual Cortex Parameterization with Error-Tolerant Teichmüller Map in Retinotopic Mapping. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2020; 12267:218-227. [PMID: 34291236 PMCID: PMC8291100 DOI: 10.1007/978-3-030-59728-3_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
The mapping between the visual input on the retina to the cortical surface, i.e., retinotopic mapping, is an important topic in vision science and neuroscience. Human retinotopic mapping can be revealed by analyzing cortex functional magnetic resonance imaging (fMRI) signals when the subject is under specific visual stimuli. Conventional methods process, smooth, and analyze the retinotopic mapping based on the parametrization of the (partial) cortical surface. However, the retinotopic maps generated by this approach frequently contradict neuropsychology results. To address this problem, we propose an integrated approach that parameterizes the cortical surface, such that the parametric coordinates linearly relates the visual coordinate. The proposed method helps the smoothing of noisy retinotopic maps and obtains neurophysiological insights in human vision systems. One key element of the approach is the Error-Tolerant Teichmüller Map, which uniforms the angle distortion and maximizes the alignments to self-contradicting landmarks. We validated our overall approach with synthetic and real retinotopic mapping datasets. The experimental results show the proposed approach is superior in accuracy and compatibility. Although we focus on retinotopic mapping, the proposed framework is general and can be applied to process other human sensory maps.
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Affiliation(s)
- Yanshuai Tu
- Arizona State University, Tempe AZ 85201, USA
| | - Duyan Ta
- Arizona State University, Tempe AZ 85201, USA
| | - Zhong-Lin Lu
- New York University, New York, NY
- NYU Shanghai, Shanghai, China
| | - Yalin Wang
- Arizona State University, Tempe AZ 85201, USA
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Heitmann S, Ermentrout GB. Direction-selective motion discrimination by traveling waves in visual cortex. PLoS Comput Biol 2020; 16:e1008164. [PMID: 32877405 PMCID: PMC7467221 DOI: 10.1371/journal.pcbi.1008164] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 07/19/2020] [Indexed: 11/19/2022] Open
Abstract
The majority of neurons in primary visual cortex respond selectively to bars of light that have a specific orientation and move in a specific direction. The spatial and temporal responses of such neurons are non-separable. How neurons accomplish that computational feat without resort to explicit time delays is unknown. We propose a novel neural mechanism whereby visual cortex computes non-separable responses by generating endogenous traveling waves of neural activity that resonate with the space-time signature of the visual stimulus. The spatiotemporal characteristics of the response are defined by the local topology of excitatory and inhibitory lateral connections in the cortex. We simulated the interaction between endogenous traveling waves and the visual stimulus using spatially distributed populations of excitatory and inhibitory neurons with Wilson-Cowan dynamics and inhibitory-surround coupling. Our model reliably detected visual gratings that moved with a given speed and direction provided that we incorporated neural competition to suppress false motion signals in the opposite direction. The findings suggest that endogenous traveling waves in visual cortex can impart direction-selectivity on neural responses without resort to explicit time delays. They also suggest a functional role for motion opponency in eliminating false motion signals. It is well established that the so-called ‘simple cells’ of the primary visual cortex respond preferentially to oriented bars of light that move across the visual field with a particular speed and direction. The spatiotemporal responses of such neurons are said to be non-separable because they cannot be constructed from independent spatial and temporal neural mechanisms. Contemporary theories of how neurons compute non-separable responses typically rely on finely tuned transmission delays between signals from disparate regions of the visual field. However the existence of such delays is controversial. We propose an alternative neural mechanism for computing non-separable responses that does not require transmission delays. It instead relies on the predisposition of the cortical tissue to spontaneously generate spatiotemporal waves of neural activity that travel with a particular speed and direction. We propose that the endogenous wave activity resonates with the visual stimulus to elicit direction-selective neural responses to visual motion. We demonstrate the principle in computer models and show that competition between opposing neurons robustly enhances their ability to discriminate between visual gratings that move in opposite directions.
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Affiliation(s)
- Stewart Heitmann
- Victor Chang Cardiac Research Institute, Sydney, New South Wales, Australia
- * E-mail:
| | - G. Bard Ermentrout
- Department of Mathematics, University of Pittsburgh, Pennsylvania, United Sates of America
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