scholarly journals Theta and alpha oscillations are traveling waves in the human neocortex

2017 ◽  
Author(s):  
Honghui Zhang ◽  
Andrew J. Watrous ◽  
Ansh Patel ◽  
Joshua Jacobs
Keyword(s):  
Traveling Waves ◽  
Neural Activity ◽  
Coupled Oscillators ◽  
Large Scale ◽  
Brain Connectivity ◽  
Memory Task ◽  
Human Cognition ◽  
Alpha Oscillations ◽  
Neural Processes ◽  
Neurosurgical Patients

SummaryHuman cognition requires the coordination of neural activity across widespread brain networks. Here we describe a new mechanism for large-scale coordination in the human brain: traveling waves of theta and alpha oscillations. Examining direct brain recordings from neurosurgical patients performing a memory task, we found contiguous clusters of cortex in individual patients with oscillations at specific frequencies between 2 to 15 Hz. These clusters displayed spatial phase gradients, indicating that the oscillations were traveling waves that propagated across the cortex at ∼0.25-0.75 m/s. Traveling waves were relevant behaviorally because their propagation correlated with task events and was more consistent when subjects performed the task well. Our findings suggest that traveling waves can be modeled by a network of coupled oscillators because the direction of wave propagation correlated with the spatial orientation of local frequency gradients. These findings suggest a role for traveling waves in supporting brain connectivity by organizing neural processes across space and time.

Explaining How Brain Stimulation Can Evoke Memories

2012 ◽  
Vol 24 (3) ◽  
pp. 553-563 ◽  
Author(s):  
Joshua Jacobs ◽  
Bradley Lega ◽  
Christopher Anderson
Keyword(s):  
High School ◽  
Temporal Lobe ◽  
Brain Stimulation ◽  
Neural Activity ◽  
Memory Retrieval ◽  
Memory Task ◽  
Cognitive State ◽  
Normal Brain ◽  
Neural Basis ◽  
Neurosurgical Patients

An unexplained phenomenon in neuroscience is the discovery that electrical stimulation in temporal neocortex can cause neurosurgical patients to spontaneously experience memory retrieval. Here we provide the first detailed examination of the neural basis of stimulation-induced memory retrieval by probing brain activity in a patient who reliably recalled memories of his high school (HS) after stimulation at a site in his left temporal lobe. After stimulation, this patient performed a customized memory task in which he was prompted to retrieve information from HS and non-HS topics. At the one site where stimulation evoked HS memories, remembering HS information caused a distinctive pattern of neural activity compared with retrieving non-HS information. Together, these findings suggest that the patient had a cluster of neurons in his temporal lobe that help represent the “high school-ness” of the current cognitive state. We believe that stimulation here evoked HS memories because it altered local neural activity in a way that partially mimicked the normal brain state for HS memories. More broadly, our findings suggest that brain stimulation can evoke memories by recreating neural patterns from normal cognition.

scholarly journals Redefining the role of Broca’s area in speech

2015 ◽  
Vol 112 (9) ◽  
pp. 2871-2875 ◽  
Author(s):  
Adeen Flinker ◽  
Anna Korzeniewska ◽  
Avgusta Y. Shestyuk ◽  
Piotr J. Franaszczuk ◽  
Nina F. Dronkers ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Neural Activity ◽  
Large Scale ◽  
Inferior Frontal Gyrus ◽  
Temporal Cortex ◽  
Word Production ◽  
Broca’S Area ◽  
Broca's Area ◽  
Neurosurgical Patients

For over a century neuroscientists have debated the dynamics by which human cortical language networks allow words to be spoken. Although it is widely accepted that Broca’s area in the left inferior frontal gyrus plays an important role in this process, it was not possible, until recently, to detail the timing of its recruitment relative to other language areas, nor how it interacts with these areas during word production. Using direct cortical surface recordings in neurosurgical patients, we studied the evolution of activity in cortical neuronal populations, as well as the Granger causal interactions between them. We found that, during the cued production of words, a temporal cascade of neural activity proceeds from sensory representations of words in temporal cortex to their corresponding articulatory gestures in motor cortex. Broca’s area mediates this cascade through reciprocal interactions with temporal and frontal motor regions. Contrary to classic notions of the role of Broca’s area in speech, while motor cortex is activated during spoken responses, Broca’s area is surprisingly silent. Moreover, when novel strings of articulatory gestures must be produced in response to nonword stimuli, neural activity is enhanced in Broca’s area, but not in motor cortex. These unique data provide evidence that Broca’s area coordinates the transformation of information across large-scale cortical networks involved in spoken word production. In this role, Broca’s area formulates an appropriate articulatory code to be implemented by motor cortex.

Traveling Waves of Excitation in Neural Field Models: Equivalence of Rate Descriptions and Integrate-and-Fire Dynamics

2002 ◽  
Vol 14 (7) ◽  
pp. 1651-1667 ◽  
Author(s):  
Daniel Cremers ◽  
Andreas V. M. Herz
Keyword(s):  
Traveling Waves ◽  
Neural Activity ◽  
Large Scale ◽  
Plane Waves ◽  
Network Connectivity ◽  
Microscopic Level ◽  
Mathematical Framework ◽  
Fire Dynamics ◽  
Integrate And Fire ◽  
Quantitative Results

Field models provide an elegant mathematical framework to analyze large-scale patterns of neural activity. On the microscopic level, these models are usually based on either a firing-rate picture or integrate-andfire dynamics. This article shows that in spite of the large conceptual differences between the two types of dynamics, both generate closely related plane-wave solutions. Furthermore, for a large group of models, estimates about the network connectivity derived from the speed of these plane waves only marginally depend on the assumed class of microscopic dynamics. We derive quantitative results about this phenomenon and discuss consequences for the interpretation of experimental data.

scholarly journals Global waves synchronize the brain’s functional systems with fluctuating arousal

2021 ◽  
Vol 7 (30) ◽  
pp. eabf2709
Author(s):  
Ryan V. Raut ◽  
Abraham Z. Snyder ◽  
Anish Mitra ◽  
Dov Yellin ◽  
Naotaka Fujii ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Functional Connectivity ◽  
Traveling Waves ◽  
Neural Activity ◽  
Large Scale ◽  
Functional Organization ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Fmri Signal ◽  
The Brain

We propose and empirically support a parsimonious account of intrinsic, brain-wide spatiotemporal organization arising from traveling waves linked to arousal. We hypothesize that these waves are the predominant physiological process reflected in spontaneous functional magnetic resonance imaging (fMRI) signal fluctuations. The correlation structure (“functional connectivity”) of these fluctuations recapitulates the large-scale functional organization of the brain. However, a unifying physiological account of this structure has so far been lacking. Here, using fMRI in humans, we show that ongoing arousal fluctuations are associated with global waves of activity that slowly propagate in parallel throughout the neocortex, thalamus, striatum, and cerebellum. We show that these waves can parsimoniously account for many features of spontaneous fMRI signal fluctuations, including topographically organized functional connectivity. Last, we demonstrate similar, cortex-wide propagation of neural activity measured with electrocorticography in macaques. These findings suggest that traveling waves spatiotemporally pattern brain-wide excitability in relation to arousal.

scholarly journals Rich-club circuitry: function, evolution and vulnerability

2018 ◽  
Vol 20 (2) ◽  
pp. 121-131 ◽  
Keyword(s):  
Large Scale ◽  
Brain Connectivity ◽  
Interesting Property ◽  
Human Cognition ◽  
Brain Disorders ◽  
Nervous Systems ◽  
Rich Club ◽  
The Past ◽  
And Behavior ◽  
Insight Into

Over the past decades, network neuroscience has played a fundamental role in the understanding of large-scale brain connectivity architecture. Brains, and more generally nervous systems, can be modeled as sets of elements (neurons, assemblies, or cortical chunks) that dynamically interact through a highly structured and adaptive neurocircuitry. An interesting property of neural networks is that elements rich in connections are central to the network organization and tend to interconnect strongly with each other, forming so-called rich clubs. The ubiquity of rich-club organization across different species and scales of investigation suggests that this topology could be a distinctive feature of biological systems with information processing capabilities. This review surveys recent neuroimaging, computational, and cross-species comparative literature to offer an insight into the function and origin of rich-club architecture in nervous systems, discussing its relevance to human cognition and behavior, and vulnerability to brain disorders.

scholarly journals Dynamic relationships between spontaneous and evoked electrophysiological activity

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Soren Wainio-Theberge ◽  
Annemarie Wolff ◽  
Georg Northoff
Keyword(s):  
Neural Activity ◽  
Large Scale ◽  
Behavioral Outcomes ◽  
Low Frequencies ◽  
Scale Free ◽  
Non Invasive ◽  
Spontaneous Neural Activity ◽  
Electrophysiological Signals ◽  
Evoked Activity ◽  
Dynamic Relationships

AbstractSpontaneous neural activity fluctuations have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioral outcomes. However, the complex electrophysiological mechanisms by which these fluctuations shape stimulus-evoked neural activity remain largely to be explored. Employing a large-scale magnetoencephalographic dataset and an electroencephalographic replication dataset, we investigate the relationship between spontaneous and evoked neural activity across a range of electrophysiological variables. We observe that for high-frequency activity, high pre-stimulus amplitudes lead to greater evoked desynchronization, while for low frequencies, high pre-stimulus amplitudes induce larger degrees of event-related synchronization. We further decompose electrophysiological power into oscillatory and scale-free components, demonstrating different patterns of spontaneous-evoked correlation for each component. Finally, we find correlations between spontaneous and evoked time-domain electrophysiological signals. Overall, we demonstrate that the dynamics of multiple electrophysiological variables exhibit distinct relationships between their spontaneous and evoked activity, a result which carries implications for experimental design and analysis in non-invasive electrophysiology.

Application of projection-based model reduction to finite-element plate models for two-dimensional traveling waves

2016 ◽  
Vol 28 (14) ◽  
pp. 1886-1904 ◽  
Author(s):  
Vijaya VN Sriram Malladi ◽  
Mohammad I Albakri ◽  
Serkan Gugercin ◽  
Pablo A Tarazaga
Keyword(s):  
Finite Element ◽  
Model Reduction ◽  
Traveling Waves ◽  
Large Scale ◽  
Fe Model ◽  
Plate Model ◽  
Reduction Techniques ◽  
State Frequency ◽  
Scale Down ◽  
The Stability

A finite element (FE) model simulates an unconstrained aluminum thin plate to which four macro-fiber composites are bonded. This plate model is experimentally validated for single and multiple inputs. While a single input excitation results in the frequency response functions and operational deflection shapes, two input excitations under prescribed conditions result in tailored traveling waves. The emphasis of this article is the application of projection-based model reduction techniques to scale-down the large-scale FE plate model. Four model reduction techniques are applied and their performances are studied. This article also discusses the stability issues associated with the rigid-body modes. Furthermore, the reduced-order models are utilized to simulate the steady-state frequency and time response of the plate. The results are in agreement with the experimental and the full-scale FE model results.

scholarly journals Functional Brain Connectivity Revealed by Sparse Coding of Large-Scale Local Field Potential Dynamics

2018 ◽  
Vol 32 (2) ◽  
pp. 255-270 ◽  
Author(s):  
Han Wang ◽  
Kun Xie ◽  
Li Xie ◽  
Xiang Li ◽  
Meng Li ◽  
...  
Keyword(s):  
Local Field ◽  
Sparse Coding ◽  
Local Field Potential ◽  
Large Scale ◽  
Brain Connectivity ◽  
Field Potential ◽  
Functional Brain

Attentional load modulates large-scale functional brain connectivity beyond the core attention networks

NeuroImage ◽  
2015 ◽  
Vol 109 ◽  
pp. 260-272 ◽  
Author(s):  
Dag Alnæs ◽  
Tobias Kaufmann ◽  
Geneviève Richard ◽  
Eugene P. Duff ◽  
Markus H. Sneve ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Connectivity ◽  
Attention Networks ◽  
Functional Brain ◽  
The Core ◽  
Attentional Load

Rhythmic Activity and Individual Variability in Recognition Memory: Theta Oscillations Correlate with Performance whereas Alpha Oscillations Correlate with ERPs

2017 ◽  
Vol 29 (1) ◽  
pp. 183-202 ◽  
Author(s):  
Yvonne Y. Chen ◽  
Jeremy B. Caplan
Keyword(s):  
Individual Differences ◽  
Recognition Memory ◽  
Memory Task ◽  
Rhythmic Activity ◽  
Individual Variability ◽  
Theta Oscillations ◽  
Alpha Oscillations ◽  
Alpha Oscillation ◽  
Familiarity And Recollection ◽  
Visual Inattention

During study trials of a recognition memory task, alpha (∼10 Hz) oscillations decrease, and concurrently, theta (4–8 Hz) oscillations increase when later memory is successful versus unsuccessful (subsequent memory effect). Likewise, at test, reduced alpha and increased theta activity are associated with successful memory (retrieval success effect). Here we take an individual-differences approach to test three hypotheses about theta and alpha oscillations in verbal, old/new recognition, measuring the difference in oscillations between hit trials and miss trials. First, we test the hypothesis that theta and alpha oscillations have a moderately mutually exclusive relationship; but no support for this hypothesis was found. Second, we test the hypothesis that theta oscillations explain not only memory effects within participants, but also individual differences. Supporting this prediction, durations of theta (but not alpha) oscillations at study and at test correlated significantly with d′ across participants. Third, we test the hypothesis that theta and alpha oscillations reflect familiarity and recollection processes by comparing oscillation measures to ERPs that are implicated in familiarity and recollection. The alpha-oscillation effects correlated with some ERP measures, but inversely, suggesting that the actions of alpha oscillations on memory processes are distinct from the roles of familiarity- and recollection-linked ERP signals. The theta-oscillation measures, despite differentiating hits from misses, did not correlate with any ERP measure; thus, theta oscillations may reflect elaborative processes not tapped by recollection-related ERPs. Our findings are consistent with alpha oscillations reflecting visual inattention, which can modulate memory, and with theta oscillations supporting recognition memory in ways that complement the most commonly studied ERPs.

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