scholarly journals Stochastic resonance mediates the state-dependent effect of periodic stimulation on cortical alpha oscillations

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Jérémie Lefebvre ◽  
Axel Hutt ◽  
Flavio Frohlich
Keyword(s):  
Stochastic Resonance ◽  
Brain Stimulation ◽  
Brain Activity ◽  
Rhythmic Activity ◽  
Oscillatory Activity ◽  
Alpha Oscillations ◽  
State Dependent ◽  
Periodic Stimulation ◽  
Brain States ◽  
Cortical System

Brain stimulation can be used to engage and modulate rhythmic activity in brain networks. However, the outcomes of brain stimulation are shaped by behavioral states and endogenous fluctuations in brain activity. To better understand how this intrinsic oscillatory activity controls the susceptibility of the brain to stimulation, we analyzed a computational model of the thalamo-cortical system in two distinct states (rest and task-engaged) to identify the mechanisms by which endogenous alpha oscillations (8Hz–12Hz) are modulated by periodic stimulation. Our analysis shows that the different responses to stimulation observed experimentally in these brain states can be explained by a passage through a bifurcation combined with stochastic resonance — a mechanism by which irregular fluctuations amplify the response of a nonlinear system to weak periodic signals. Indeed, our findings suggest that modulation of brain oscillations is best achieved in states of low endogenous rhythmic activity, and that irregular state-dependent fluctuations in thalamic inputs shape the susceptibility of cortical population to periodic stimulation.

scholarly journals Stochastic Resonance Mediates the State-Dependent Effect of Periodic Stimulation on Cortical Alpha Oscillations

2017 ◽  
Author(s):  
Jérémie Lefebvre ◽  
Flavio Frohlich ◽  
Axel Hutt
Keyword(s):  
Stochastic Resonance ◽  
Rhythmic Activity ◽  
Oscillatory Activity ◽  
Alpha Oscillations ◽  
State Dependent ◽  
Periodic Stimulation ◽  
Brain States ◽  
Behavioral States ◽  
Thalamocortical System ◽  
And Task

ABSTRACTBrain stimulation can be used to engage and modulate rhythmic activity in cortical networks. However, the outcomes have been shown to be impacted by behavioral states and endogenous brain fluctuations. To better understand how this intrinsic oscillatory activity controls the brain’s susceptibility to stimulation, we analyzed a computational model of the thalamocortical system in both the rest and task states, to identify the mechanisms by which endogenous alpha oscillations (8Hz-12Hz) are impacted by periodic stimulation. Our analysis shows that the differences between different brain states can be explained by a passage through a bifurcation combined to stochastic resonance - a mechanism whereby irregular fluctuations amplify the response of a nonlinear system to weak signals. Indeed, our findings suggest that modulating brain oscillations is best achieved in states of low endogenous rhythmic activity, and that irregular state-dependent fluctuations in thalamic inputs shape the susceptibility of cortical population to periodic stimulation.

scholarly journals A connectome-based, corticothalamic model of state- and stimulation-dependent modulation of rhythmic neural activity and connectivity

2019 ◽  
Author(s):  
John D Griffiths ◽  
Anthony Randal McIntosh ◽  
Jeremie Lefebvre
Keyword(s):  
Functional Connectivity ◽  
Brain Stimulation ◽  
Brain Activity ◽  
Low Frequency ◽  
Rhythmic Activity ◽  
Clinical Applications ◽  
Oscillatory Activity ◽  
Neural Mass Model ◽  
Brain Connectome ◽  
The Impact

AbstractRhythmic activity in the brain fluctuates with behaviour and cognitive state, through a combination of coexisting and interacting frequencies. At large spatial scales such as those studied in human M/EEG, measured oscillatory dynamics are believed to arise primarily from a combination of cortical (intracolumnar) and corticothalamic rhythmogenic mechanisms. Whilst considerable progress has been made in characterizing these two types of neural circuit separately, relatively little work has been done that attempts to unify them into a single consistent picture. This is the aim of the present paper. We present and examine a whole-brain, connectome-based neural mass model with detailed long-range cortico-cortical connectivity and strong, recurrent corticothalamic circuitry. This system reproduces a variety of known features of human M/EEG recordings, including a 1/f spectral profile, spectral peaks at canonical frequencies, and functional connectivity structure that is shaped by the underlying anatomical connectivity. Importantly, our model is able to capture state-(e.g. idling/active) dependent fluctuations in oscillatory activity and the coexistence of multiple oscillatory phenomena, as well as frequency-specific modulation of functional connectivity. We find that increasing the level of sensory or neuromodulatory drive to the thalamus triggers a suppression of the dominant low frequency rhythms generated by corticothalamic loops, and subsequent disinhibition of higher frequency endogenous rhythmic behaviour of intra-columnar microcircuits. These combine to yield simultaneous decreases in lower frequency and increases in higher frequency components of the M/EEG power spectrum during states of high sensory or cognitive drive. Building on this, we also explored the effect of pulsatile brain stimulation on ongoing oscillatory activity, and evaluated the impact of coexistent frequencies and state-dependent fluctuations on the response of cortical networks. Our results provide new insight into the role played by cortical and corticothalamic circuits in shaping intrinsic brain rhythms, and suggest new directions for brain stimulation therapies aimed at state-and frequency-specific control of oscillatory brain activity.Author SummaryOne of the most distinctive features of brain activity is that it is highly rhythmic. Developing a better understanding of how these rhythms are generated, and how they can be controlled in clinical applications, is a central goal of modern neuroscience. Here we have developed a computational model that succinctly captures several key aspects of the rhythmic brain activity most easily measurable in human subjects. In particular, it provides both a conceptual and a concrete mathematical framework for understanding the well-established experimental observation of antagonism between high- and low-frequency oscillations in human brain recordings. This dynamic has important implications for how we understand the modulation of rhythmic activity in diverse cognitive states relating to arousal, attention, and cognitive processing. As we demonstrate, our model also provides a tool for investigating and improving the use of rhythmic brain stimulation in clinical applications.

scholarly journals Do Brain Oscillations Orchestrate Memory?

2018 ◽  
Vol 4 (1) ◽  
pp. 16-33 ◽  
Author(s):  
Wenhan Luo ◽  
Ji-Song Guan
Keyword(s):  
Brain Activity ◽  
Large Population ◽  
Rhythmic Activity ◽  
Brain Oscillations ◽  
Strongly Coupled ◽  
Specific Memory ◽  
State Dependent ◽  
Neural Communication ◽  
The Brain ◽  
Oscillatory Waves

Rhythmicity and oscillations are common features in nature, and can be seen in phenomena such as seasons, breathing, and brain activity. Despite the fact that a single neuron transmits its activity to its neighbor through a transient pulse, rhythmic activity emerges from large population-wide activity in the brain, and such rhythms are strongly coupled with the state and cognitive functions of the brain. However, it is still debated whether the oscillations of brain activity actually carry information. Here, we briefly introduce the biological findings of brain oscillations, and summarize the recent progress in understanding how oscillations mediate brain function. Finally, we examine the possible relationship between brain cognitive function and oscillation, focusing on how oscillation is related to memory, particularly with respect to state-dependent memory formation and memory retrieval under specific brain waves. We propose that oscillatory waves in the neocortex contribute to the synchronization and activation of specific memory trace ensembles in the neocortex by promoting long-range neural communication.

scholarly journals State Dependent Beta Oscillations in the Cortico-Basal Ganglia Circuit and their Neuromodulation under Phase-Locked Inputs

2020 ◽  
Author(s):  
Timothy O. West ◽  
Simon F. Farmer ◽  
Peter J. Magill ◽  
Andrew Sharott ◽  
Vladimir Litvak ◽  
...  
Keyword(s):  
Basal Ganglia ◽  
Brain Stimulation ◽  
Open Loop ◽  
List Type ◽  
Beta Band ◽  
Beta Oscillations ◽  
Disease States ◽  
State Dependent ◽  
Brain Rhythm ◽  
Brain States

AbstractState-of-the-art therapeutic brain stimulation strategies are delivered open loop, using fixed parameters. However, brain states exhibit spontaneous fluctuations dependent upon different behavioural or disease states. Here, we use a model of the cortico-basal ganglia-thalamic circuit to demonstrate how connectivity underpins changes in subcortical beta oscillations – a commonly used control parameter for deep brain stimulation in Parkinson’s disease. We show that recurrent cortical-subcortical loops involving either the cortico-subthalamic or pallido-subthalamic pathways can act in antagonism to modulate the expression of beta band activity (14-30 Hz). These pathways alter the relative timing of intermittent activity across the network, with increased pallido-subthalamic connectivity increasing the propensity of the circuit to enter a state of autonomous oscillation. We demonstrate that phase-locked stimulation can modulate these oscillations, with an efficacy that ultimately depends upon the connectivity across the circuit. This work outlines critical factors required to implement state-adaptive closed-loop brain stimulation.HighlightsConverging inputs to the subthalamic nucleus arriving via the external segment of globus pallidus and cortex act in antagonism and promote different beta rhythms.Phase locked stimulation has the capacity to selectively enhance or suppress a brain rhythm depending on the stimulation timing.The efficacy of stimulation and the parameters required to deliver it, e.g. stimulation timing, effective sensing and stimulation locations, are functions of network state.

scholarly journals Oscillations, criticality and responsiveness in complex brain networks

2019 ◽  
Author(s):  
MinKyung Kim ◽  
UnCheol Lee
Keyword(s):  
Large Scale ◽  
Brain Activity ◽  
Conscious State ◽  
Brain Network ◽  
State Dependent ◽  
Model Study ◽  
Brain States ◽  
Specific Stimulation ◽  
The Brain ◽  
Oscillation Properties

AbstractBrain networks during unconscious states resulting from sleep, anesthesia, or traumatic injuries are associated with a limited capacity for complex responses to stimulation. Even during the conscious resting state, responsiveness to stimulus is highly dependent on spontaneous brain activities. Many empirical findings have been suggested that the brain responsiveness is determined mainly by the ongoing brain activity when a stimulus is given. However, there has been no systematic study exploring how such various brain activities with high or low synchronization, amplitude, and phase response to stimuli. In this model study, we simulated large-scale brain network dynamics in three brain states (below, near, and above the critical state) and investigated a relationship between ongoing oscillation properties and a stimulus decomposing the brain activity into fundamental oscillation properties (instantaneous global synchronization, amplitude, and phase). We identified specific stimulation conditions that produce varying levels of brain responsiveness. When a single pulsatile stimulus was applied to globally desynchronized low amplitude of oscillation, the network generated a large response. By contrast, when a stimulus was applied to specific phases of oscillation that were globally synchronized with high amplitude activity, the response was inhibited. This study proposes the oscillatory conditions to induce specific stimulation outcomes in the brain that can be systematically derived from networked oscillator properties, and reveals the presence of state-dependent temporal windows for optimal brain stimulation. The identified relationship will help advance understanding of the small/large responsiveness of the brain in different states of consciousness and suggest state-dependent methods to modulate responsiveness.Author SummaryA responsiveness of the brain network to external stimulus is different across brain states such as wakefulness, sleep, anesthesia, and traumatic injuries. It has been shown that responsiveness of the brain during conscious state also varies due to the diverse transient states of the brain characterized by different global and local oscillation properties. In this computational model study using large-scale brain network, we hypothesized that the brain responsiveness is determined by the interactions of networked oscillators when a stimulus is applied to the brain. We examined relationships between responsiveness of the brain network, global synchronization levels, and instantaneous oscillation properties such as amplitude and phase in different brain states. We found specific stimulation conditions of the brain that produce large or small levels of responsiveness. The identified relationship suggests the existence of temporal windows that periodically inhibit sensory information processing during conscious state and develops state-dependent methods to modulate brain responsiveness considering dynamically changed functional brain network.

Rhythmic Constraints on Hippocampal Processing: State and Phase-Related Fluctuations of Synaptic Excitability During Theta and the Slow Oscillation

2008 ◽  
Vol 99 (2) ◽  
pp. 888-899 ◽  
Author(s):  
Kurt P. Schall ◽  
Jon Kerber ◽  
Clayton T. Dickson
Keyword(s):  
Medial Temporal Lobe ◽  
Evoked Potential ◽  
Rhythmic Activity ◽  
Slow Oscillation ◽  
Perforant Path ◽  
Oscillatory Activity ◽  
Deep Sleep ◽  
Differential Effects ◽  
Input Processing ◽  
State Dependent

Coordinated patterns of state-dependent synchronized oscillatory activity have been suggested to play differential roles in both the encoding and consolidation phases of hippocampal-dependent memories. Previous studies have concentrated on the mutually exclusive patterns of theta and sharp-wave/ripple activity because these were thought to be the only collective oscillatory patterns expressed in the hippocampus. Recently we (and others) have described a novel rhythmic activity expressed during anesthesia and deep sleep, the hippocampal slow oscillation (SO). In an attempt to describe the differential effects of theta and the SO on processing in the hippocampal circuit, we performed evoked potential analysis of two major pathways (the commissural and perforant) in urethan-anesthetized rats across spontaneously expressed theta and SO states. We show that synaptic excitability was significantly enhanced in all pathways during the SO as compared with theta with the exception of the medial perforant path to the dentate gyrus, which showed greater excitability during theta. Furthermore, within each ongoing rhythm, there was a phase-dependent modulation of synaptic excitability. This occurred across all sites and similarly favored the falling phase (positive to negative) of both theta and the SO. Differential effects on the input, processing, and output circuitries of the hippocampus across mutually exclusive coordinated oscillatory patterns expressed during different states may be relevant for the staging of memory processes in the medial temporal lobe.

scholarly journals EEG Oscillatory Phase-Dependent Markers of Corticospinal Excitability in the Resting Brain

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Barbara Berger ◽  
Tamas Minarik ◽  
Gianpiero Liuzzi ◽  
Friedhelm C. Hummel ◽  
Paul Sauseng
Keyword(s):  
Cortical Excitability ◽  
Brain Activity ◽  
Motor Evoked Potential ◽  
Corticospinal Excitability ◽  
Neuronal Firing ◽  
Oscillatory Activity ◽  
Brain Oscillations ◽  
Frequency Bands ◽  
Instantaneous Phase ◽  
Brain States

Functional meaning of oscillatory brain activity in various frequency bands in the human electroencephalogram (EEG) is increasingly researched. While most research focuses on event-related changes of brain activity in response to external events there is also increasing interest in internal brain states influencing information processing. Several studies suggest amplitude changes of EEG oscillatory activity selectively influencing cortical excitability, and more recently it was shown that phase of EEG activity (instantaneous phase) conveys additional meaning. Here we review this field with many conflicting findings and further investigate whether corticospinal excitability in the resting brain is dependent on a specific spontaneously occurring brain state reflected by amplitude and instantaneous phase of EEG oscillations. We applied single pulse transcranial magnetic stimulation (TMS) over the left sensorimotor cortex, while simultaneously recording ongoing oscillatory activity with EEG. Results indicate that brain oscillations reflect rapid, spontaneous fluctuations of cortical excitability. Instantaneous phase but not amplitude of oscillations at various frequency bands at stimulation site at the time of TMS-pulse is indicative for brain states associated with different levels of excitability (defined by size of the elicited motor evoked potential). These results are further evidence that ongoing brain oscillations directly influence neural excitability which puts further emphasis on their role in orchestrating neuronal firing in the brain.

scholarly journals Arousal impacts distributed hubs modulating the integration of brain functional connectivity

2021 ◽  
Author(s):  
Kangjoo Lee ◽  
Corey Horien ◽  
David O'Connor ◽  
Bronwen Garand-Sheridan ◽  
Fuyuze Tokoglu ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain State ◽  
Network Integration ◽  
State Dependent ◽  
Show Evidence ◽  
Brain States ◽  
High Level ◽  
The Impact

Even when subjects are at rest, it is thought that brain activity is organized into distinct brain states during which reproducible patterns are observable. Yet, it is unclear how to define or distinguish different brain states. A potential source of brain state variation is arousal, which may play a role in modulating functional interactions between brain regions. Here, we use simultaneous resting state functional magnetic resonance imaging and pupillometry to study the impact of arousal levels indexed by pupil area on the integration of large-scale brain networks. We employ a novel sparse dictionary learning-based method to identify hub regions participating in between-network integration stratified by arousal, by measuring k-hubness, the number (k) of functionally overlapping networks in each brain region. We show evidence of a brain-wide decrease in between-network integration and inter-subject variability at low relative to high arousal, with differences emerging across regions of the frontoparietal, default mode, motor, limbic, and cerebellum networks. State-dependent changes in k-hubness relate to the actual patterns of network integration within these hubs, suggesting a brain state transition from high to low arousal characterized by global synchronization and reduced network overlaps. We demonstrate that arousal is not limited to specific brain areas known to be directly associated with arousal regulation, but instead has a brain-wide impact that involves high-level between-network communications.

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