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Article: Horizontal cortical connections shape intrinsic traveling waves into feature-selective motifs that regulate perceptual sensitivity.

Davis, Zachary W / Busch, Alexandria / Stewerd, Christopher / Muller, Lyle / Reynolds, John

Research square

2024

Abstract: Intrinsic, ongoing fluctuations of cortical activity form traveling waves that modulate the gain of sensory-evoked responses and perceptual sensitivity. Several lines of evidence suggest that intrinsic traveling waves (iTWs) may arise, in part, from the ... ...

Abstract	Intrinsic, ongoing fluctuations of cortical activity form traveling waves that modulate the gain of sensory-evoked responses and perceptual sensitivity. Several lines of evidence suggest that intrinsic traveling waves (iTWs) may arise, in part, from the coordination of synaptic activity through the recurrent horizontal connectivity within cortical areas, which include long range patchy connections that link neurons with shared feature preferences. In a spiking network model with anatomical topology that incorporates feature-selective patchy connections, which we call the Balanced Patchy Network (BPN), we observe repeated iTWs, which we refer to as
Language	English
Publishing date	2024-01-09
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-3830199/v1
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Article ; Online: Spontaneous Spiking Is Governed by Broadband Fluctuations.

Davis, Zachary W / Muller, Lyle / Reynolds, John H

The Journal of neuroscience : the official journal of the Society for Neuroscience

2022 Volume 42, Issue 26, Page(s) 5159–5172

Abstract: Populations of cortical neurons generate rhythmic fluctuations in their ongoing spontaneous activity. These fluctuations can be seen in the local field potential (LFP), which reflects summed return currents from synaptic activity in the local population ... ...

Abstract	Populations of cortical neurons generate rhythmic fluctuations in their ongoing spontaneous activity. These fluctuations can be seen in the local field potential (LFP), which reflects summed return currents from synaptic activity in the local population near a recording electrode. The LFP is spectrally broad, and many researchers view this breadth as containing many narrowband oscillatory components that may have distinct functional roles. This view is supported by the observation that the phase of narrowband oscillations is often correlated with cortical excitability and can relate to the timing of spiking activity and the fidelity of sensory evoked responses. Accordingly, researchers commonly tune in to these channels by narrowband filtering the LFP. Alternatively, neural activity may be fundamentally broadband and composed of transient, nonstationary rhythms that are difficult to approximate as oscillations. In this view, the instantaneous state of the broad ensemble relates directly to the excitability of the local population with no particular allegiance to any frequency band. To test between these alternatives, we asked whether the spiking activity of neocortical neurons in marmoset of either sex is better aligned with the phase of the LFP within narrow frequency bands or with a broadband measure. We find that the phase of broadband LFP fluctuations provides a better predictor of spike timing than the phase after filtering in narrow bands. These results challenge the view of the neocortex as a system composed of narrowband oscillators and supports a view in which neural activity fluctuations are intrinsically broadband.
MeSH term(s)	Action Potentials/physiology ; Neocortex/physiology ; Neurons/physiology
Language	English
Publishing date	2022-05-23
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
ZDB-ID	604637-x
ISSN	1529-2401 ; 0270-6474
ISSN (online)	1529-2401
ISSN	0270-6474
DOI	10.1523/JNEUROSCI.1899-21.2022
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Article ; Online: Algebraic approach to the Kuramoto model.

Muller, Lyle / Mináč, Ján / Nguyen, Tung T

Physical review. E

2021 Volume 104, Issue 2, Page(s) L022201

Abstract: We study the Kuramoto model with attractive sine coupling. We introduce a complex-valued matrix formulation whose argument coincides with the original Kuramoto dynamics. We derive an exact solution for the complex-valued model, which permits analytical ... ...

Abstract	We study the Kuramoto model with attractive sine coupling. We introduce a complex-valued matrix formulation whose argument coincides with the original Kuramoto dynamics. We derive an exact solution for the complex-valued model, which permits analytical insight into individual realizations of the Kuramoto model. The existence of a complex-valued form of the Kuramoto model provides a key demonstration that, in some cases, reformulations of nonlinear dynamics in higher-order number fields may provide tractable analytical approaches.
Language	English
Publishing date	2021-09-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	2844562-4
ISSN	2470-0053 ; 2470-0045
ISSN (online)	2470-0053
ISSN	2470-0045
DOI	10.1103/PhysRevE.104.L022201
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Article ; Online: Composed solutions of synchronized patterns in multiplex networks of Kuramoto oscillators.

Jain, Priya B / Nguyen, Tung T / Mináč, Ján / Muller, Lyle E / Budzinski, Roberto C

Chaos (Woodbury, N.Y.)

2023 Volume 33, Issue 10

Abstract: Networks with different levels of interactions, including multilayer and multiplex networks, can display a rich diversity of dynamical behaviors and can be used to model and study a wide range of systems. Despite numerous efforts to investigate these ... ...

Abstract	Networks with different levels of interactions, including multilayer and multiplex networks, can display a rich diversity of dynamical behaviors and can be used to model and study a wide range of systems. Despite numerous efforts to investigate these networks, obtaining mathematical descriptions for the dynamics of multilayer and multiplex systems is still an open problem. Here, we combine ideas and concepts from linear algebra and graph theory with nonlinear dynamics to offer a novel approach to study multiplex networks of Kuramoto oscillators. Our approach allows us to study the dynamics of a large, multiplex network by decomposing it into two smaller systems: one representing the connection scheme within layers (intra-layer), and the other representing the connections between layers (inter-layer). Particularly, we use this approach to compose solutions for multiplex networks of Kuramoto oscillators. These solutions are given by a combination of solutions for the smaller systems given by the intra- and inter-layer systems, and in addition, our approach allows us to study the linear stability of these solutions.
Language	English
Publishing date	2023-10-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	1472677-4
ISSN	1089-7682 ; 1054-1500
ISSN (online)	1089-7682
ISSN	1054-1500
DOI	10.1063/5.0161399
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Article ; Online: Waves traveling over a map of visual space can ignite short-term predictions of sensory input.

Benigno, Gabriel B / Budzinski, Roberto C / Davis, Zachary W / Reynolds, John H / Muller, Lyle

Nature communications

2023 Volume 14, Issue 1, Page(s) 3409

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 ... ...

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.
MeSH term(s)	Animals ; Wakefulness ; Visual Cortex/physiology
Language	English
Publishing date	2023-06-09
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-39076-2
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Article ; Online: Waves traveling over a map of visual space can ignite short-term predictions of sensory input

Gabriel B. Benigno / Roberto C. Budzinski / Zachary W. Davis / John H. Reynolds / Lyle Muller

Nature Communications, Vol 14, Iss 1, Pp 1-

2023 Volume 14

Abstract: 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 ... ...

Abstract	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.
Keywords	Science ; Q
Subject code	535
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Spike-phase coupling patterns reveal laminar identity in primate cortex.

Davis, Zachary W / Dotson, Nicholas M / Franken, Tom P / Muller, Lyle / Reynolds, John H

eLife

2023 Volume 12

Abstract: The cortical column is one of the fundamental computational circuits in the brain. In order to understand the role neurons in different layers of this circuit play in cortical function it is necessary to identify the boundaries that separate the laminar ... ...

Abstract	The cortical column is one of the fundamental computational circuits in the brain. In order to understand the role neurons in different layers of this circuit play in cortical function it is necessary to identify the boundaries that separate the laminar compartments. While histological approaches can reveal ground truth they are not a practical means of identifying cortical layers in vivo. The gold standard for identifying laminar compartments in electrophysiological recordings is current-source density (CSD) analysis. However, laminar CSD analysis requires averaging across reliably evoked responses that target the input layer in cortex, which may be difficult to generate in less well-studied cortical regions. Further, the analysis can be susceptible to noise on individual channels resulting in errors in assigning laminar boundaries. Here, we have analyzed linear array recordings in multiple cortical areas in both the common marmoset and the rhesus macaque. We describe a pattern of laminar spike-field phase relationships that reliably identifies the transition between input and deep layers in cortical recordings from multiple cortical areas in two different non-human primate species. This measure corresponds well to estimates of the location of the input layer using CSDs, but does not require averaging or specific evoked activity. Laminar identity can be estimated rapidly with as little as a minute of ongoing data and is invariant to many experimental parameters. This method may serve to validate CSD measurements that might otherwise be unreliable or to estimate laminar boundaries when other methods are not practical.
MeSH term(s)	Animals ; Macaca mulatta ; Brain ; Electrophysiological Phenomena
Language	English
Publishing date	2023-04-17
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.84512
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Article ; Online: Algebraic approach to spike-time neural codes in the hippocampus.

Pasini, Federico W / Busch, Alexandra N / Mináč, Ján / Padmanabhan, Krishnan / Muller, Lyle

Physical review. E

2023 Volume 108, Issue 5-1, Page(s) 54404

Abstract: Although temporal coding through spike-time patterns has long been of interest in neuroscience, the specific structures that could be useful for spike-time codes remain highly unclear. Here, we introduce an analytical approach, using techniques from ... ...

Abstract	Although temporal coding through spike-time patterns has long been of interest in neuroscience, the specific structures that could be useful for spike-time codes remain highly unclear. Here, we introduce an analytical approach, using techniques from discrete mathematics, to study spike-time codes. As an initial example, we focus on the phenomenon of "phase precession" in the rodent hippocampus. During navigation and learning on a physical track, specific cells in a rodent's brain form a highly structured pattern relative to the oscillation of population activity in this region. Studies of phase precession largely focus on its role in precisely ordering spike times for synaptic plasticity, as the role of phase precession in memory formation is well established. Comparatively less attention has been paid to the fact that phase precession represents one of the best candidates for a spike-time neural code. The precise nature of this code remains an open question. Here, we derive an analytical expression for a function mapping points in physical space to complex-valued spikes by representing individual spike times as complex numbers. The properties of this function make explicit a specific relationship between past and future in spike patterns of the hippocampus. Importantly, this mathematical approach generalizes beyond the specific phenomenon studied here, providing a technique to study the neural codes within precise spike-time sequences found during sensory coding and motor behavior. We then introduce a spike-based decoding algorithm, based on this function, that successfully decodes a simulated animal's trajectory using only the animal's initial position and a pattern of spike times. This decoder is robust to noise in spike times and works on a timescale almost an order of magnitude shorter than typically used with decoders that work on average firing rate. These results illustrate the utility of a discrete approach, based on the structure and symmetries in spike patterns across finite sets of cells, to provide insight into the structure and function of neural systems.
MeSH term(s)	Animals ; Action Potentials ; Hippocampus ; Brain ; Algorithms ; Models, Neurological
Language	English
Publishing date	2023-12-20
Publishing country	United States
Document type	Journal Article
ZDB-ID	2844562-4
ISSN	2470-0053 ; 2470-0045
ISSN (online)	2470-0053
ISSN	2470-0045
DOI	10.1103/PhysRevE.108.054404
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Article ; Online: Geometry unites synchrony, chimeras, and waves in nonlinear oscillator networks.

Budzinski, Roberto C / Nguyen, Tung T / Đoàn, Jacqueline / Mináč, Ján / Sejnowski, Terrence J / Muller, Lyle E

Chaos (Woodbury, N.Y.)

2022 Volume 32, Issue 3, Page(s) 31104

Abstract: One of the simplest mathematical models in the study of nonlinear systems is the Kuramoto model, which describes synchronization in systems from swarms of insects to superconductors. We have recently found a connection between the original, real-valued ... ...

Abstract	One of the simplest mathematical models in the study of nonlinear systems is the Kuramoto model, which describes synchronization in systems from swarms of insects to superconductors. We have recently found a connection between the original, real-valued nonlinear Kuramoto model and a corresponding complex-valued system that permits describing the system in terms of a linear operator and iterative update rule. We now use this description to investigate three major synchronization phenomena in Kuramoto networks (phase synchronization, chimera states, and traveling waves), not only in terms of steady state solutions but also in terms of transient dynamics and individual simulations. These results provide new mathematical insight into how sophisticated behaviors arise from connection patterns in nonlinear networked systems.
MeSH term(s)	Chimera ; Models, Theoretical ; Nonlinear Dynamics
Language	English
Publishing date	2022-04-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	1472677-4
ISSN	1089-7682 ; 1054-1500
ISSN (online)	1089-7682
ISSN	1054-1500
DOI	10.1063/5.0078791
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Article ; Online: State-dependent activity dynamics of hypothalamic stress effector neurons.

Ichiyama, Aoi / Mestern, Samuel / Benigno, Gabriel B / Scott, Kaela E / Allman, Brian L / Muller, Lyle / Inoue, Wataru

eLife

2022 Volume 11

Abstract: The stress response necessitates an immediate boost in vital physiological functions from their homeostatic operation to an elevated emergency response. However, the neural mechanisms underlying this state-dependent change remain largely unknown. Using a ...

Abstract	The stress response necessitates an immediate boost in vital physiological functions from their homeostatic operation to an elevated emergency response. However, the neural mechanisms underlying this state-dependent change remain largely unknown. Using a combination of in vivo and ex vivo electrophysiology with computational modeling, we report that corticotropin releasing hormone (CRH) neurons in the paraventricular nucleus of the hypothalamus (PVN), the effector neurons of hormonal stress response, rapidly transition between distinct activity states through recurrent inhibition. Specifically, in vivo optrode recording shows that under non-stress conditions, CRH
MeSH term(s)	Corticotropin-Releasing Hormone/metabolism ; Hypothalamus/metabolism ; Neurons/physiology ; Paraventricular Hypothalamic Nucleus/metabolism
Chemical Substances	Corticotropin-Releasing Hormone (9015-71-8)
Language	English
Publishing date	2022-06-30
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.76832
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