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Wang K, Chen K, Wei Z, Wang T, Wei A, Gao X, Qin Y, Zhu Y, Ge Y, Cui B, Zhu M. Visual light flicker stimulation: enhancing alertness in sleep-deprived rats. Front Neurosci 2024; 18:1415614. [PMID: 38903600 PMCID: PMC11188382 DOI: 10.3389/fnins.2024.1415614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 05/24/2024] [Indexed: 06/22/2024] Open
Abstract
Introduction In the evolving field of neurophysiological research, visual light flicker stimulation is recognized as a promising non-invasive intervention for cognitive enhancement, particularly in sleep-deprived conditions. Methods This study explored the effects of specific flicker frequencies (40 Hz and 20-30 Hz random flicker) on alertness recovery in sleep-deprived rats. We employed a multidisciplinary approach that included behavioral assessments with the Y-maze, in vivo electrophysiological recordings, and molecular analyses such as c-FOS immunohistochemistry and hormone level measurements. Results Both 40 Hz and 20-30 Hz flicker significantly enhanced behavioral performance in the Y-maze test, suggesting an improvement in alertness. Neurophysiological data indicated activation of neural circuits in key brain areas like the thalamus and hippocampus. Additionally, flicker exposure normalized cortisol and serotonin levels, essential for stress response and mood regulation. Notably, increased c-FOS expression in brain regions related to alertness and cognitive functions suggested heightened neural activity. Discussion These findings underscore the potential of light flicker stimulation not only to mitigate the effects of sleep deprivation but also to enhance cognitive functions. The results pave the way for future translational research into light-based therapies in human subjects, with possible implications for occupational health and cognitive ergonomics.
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Affiliation(s)
- Kun Wang
- Military Medical Sciences Academy, Tianjin, China
- Medical Support Technology Research Department, Systems Engineering Institute, Tianjin, China
| | - Kang Chen
- Military Medical Sciences Academy, Tianjin, China
- Tianjin Key Lab of Exercise Physiology and Sports Medicine, Tianjin University of Sport, Tianjin, China
| | - Zilin Wei
- Military Medical Sciences Academy, Tianjin, China
| | - Tianhui Wang
- Military Medical Sciences Academy, Tianjin, China
| | - Aili Wei
- Military Medical Sciences Academy, Tianjin, China
| | - Xiujie Gao
- Military Medical Sciences Academy, Tianjin, China
| | - Yingkai Qin
- Military Medical Sciences Academy, Tianjin, China
| | - Yingwen Zhu
- Military Medical Sciences Academy, Tianjin, China
| | - Yi Ge
- Logistic Support Department of Central Military Commission, Beijing, China
| | - Bo Cui
- Military Medical Sciences Academy, Tianjin, China
| | - Mengfu Zhu
- Medical Support Technology Research Department, Systems Engineering Institute, Tianjin, China
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Thalamic control of sensory processing and spindles in a biophysical somatosensory thalamoreticular circuit model of wakefulness and sleep. Cell Rep 2023; 42:112200. [PMID: 36867532 PMCID: PMC10066598 DOI: 10.1016/j.celrep.2023.112200] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 01/04/2023] [Accepted: 02/15/2023] [Indexed: 03/04/2023] Open
Abstract
Thalamoreticular circuitry plays a key role in arousal, attention, cognition, and sleep spindles, and is linked to several brain disorders. A detailed computational model of mouse somatosensory thalamus and thalamic reticular nucleus has been developed to capture the properties of over 14,000 neurons connected by 6 million synapses. The model recreates the biological connectivity of these neurons, and simulations of the model reproduce multiple experimental findings in different brain states. The model shows that inhibitory rebound produces frequency-selective enhancement of thalamic responses during wakefulness. We find that thalamic interactions are responsible for the characteristic waxing and waning of spindle oscillations. In addition, we find that changes in thalamic excitability control spindle frequency and their incidence. The model is made openly available to provide a new tool for studying the function and dysfunction of the thalamoreticular circuitry in various brain states.
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Wang K, Wei A, Fu Y, Wang T, Gao X, Fu B, Zhu Y, Cui B, Zhu M. State-dependent modulation of thalamocortical oscillations by gamma light flicker with different frequencies, intensities, and duty cycles. Front Neuroinform 2022; 16:968907. [PMID: 36081653 PMCID: PMC9445583 DOI: 10.3389/fninf.2022.968907] [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: 06/14/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
Rhythmic light flickers have emerged as useful tools to modulate cognition and rescue pathological oscillations related to neurological disorders by entrainment. However, a mechanistic understanding of the entrainment for different brain oscillatory states and light flicker parameters is lacking. To address this issue, we proposed a biophysical neural network model for thalamocortical oscillations (TCOs) and explored the stimulation effects depending on the thalamocortical oscillatory states and stimulation parameters (frequency, intensity, and duty cycle) using the proposed model and electrophysiology experiments. The proposed model generated alpha, beta, and gamma oscillatory states (with main oscillation frequences at 9, 25, and 35 Hz, respectively), which were successfully transmitted from the thalamus to the cortex. By applying light flicker stimulation, we found that the entrainment was state-dependent and it was more prone to induce entrainment if the flicker perturbation frequency was closer to the endogenous oscillatory frequency. In addition, endogenous oscillation would be accelerated, whereas low-frequency oscillatory power would be suppressed by gamma (30–50 Hz) flickers. Notably, the effects of intensity and duty cycle on entrainment were complex; a high intensity of light flicker did not mean high entrainment possibility, and duty cycles below 50% could induce entrainment easier than those above 50%. Further, we observed entrainment discontinuity during gamma flicker stimulations with different frequencies, attributable to the non-linear characteristics of the network oscillations. These results provide support for the experimental design and clinical applications of the modulation of TCOs by gamma (30–50 Hz) light flicker.
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Affiliation(s)
- Kun Wang
- Institute of Medical Support Technology, Academy of Military Science of Chinese PLA, Tianjin, China
- Department of Occupational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Aili Wei
- Department of Occupational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Yu Fu
- Department of Occupational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Tianhui Wang
- Department of Occupational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Xiujie Gao
- Department of Occupational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Bo Fu
- Department of Occupational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Yingwen Zhu
- Department of Occupational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
| | - Bo Cui
- Department of Occupational Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China
- *Correspondence: Bo Cui,
| | - Mengfu Zhu
- Institute of Medical Support Technology, Academy of Military Science of Chinese PLA, Tianjin, China
- Mengfu Zhu,
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4
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Maness EB, Burk JA, McKenna JT, Schiffino FL, Strecker RE, McCoy JG. Role of the locus coeruleus and basal forebrain in arousal and attention. Brain Res Bull 2022; 188:47-58. [PMID: 35878679 DOI: 10.1016/j.brainresbull.2022.07.014] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 07/11/2022] [Accepted: 07/20/2022] [Indexed: 12/11/2022]
Abstract
Experimental evidence has implicated multiple neurotransmitter systems in either the direct or indirect modulation of cortical arousal and attention circuitry. In this review, we selectively focus on three such systems: 1) norepinephrine (NE)-containing neurons of the locus coeruleus (LC), 2) acetylcholine (ACh)-containing neurons of the basal forebrain (BF), and 3) parvalbumin (PV)-containing gamma-aminobutyric acid neurons of the BF. Whereas BF-PV neurons serve as a rapid and transient arousal system, LC-NE and BF-ACh neuromodulation are typically activated on slower but longer-lasting timescales. Recent findings suggest that the BF-PV system serves to rapidly respond to even subtle sensory stimuli with a microarousal. We posit that salient sensory stimuli, such as those that are threatening or predict the need for a response, will quickly activate the BF-PV system and subsequently activate both the BF-ACh and LC-NE systems if the circumstances require longer periods of arousal and vigilance. We suggest that NE and ACh have overlapping psychological functions with the main difference being the precise internal/environmental sensory situations/contexts that recruit each neurotransmitter system - a goal for future research to determine. Implications of dysfunction of each of these three attentional systems for our understanding of neuropsychiatric conditions are considered. Finally, the contemporary availability of research tools to selectively manipulate and measure the activity of these distinctive neuronal populations promises to answer longstanding questions, such as how various arousal systems influence downstream decision-making and motor responding.
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Affiliation(s)
- Eden B Maness
- VA Boston Healthcare System and Department of Psychiatry, Harvard Medical School, West Roxbury, MA 02132, USA.
| | - Joshua A Burk
- Department of Psychological Sciences, College of William and Mary, Williamsburg, VA 23187, USA
| | - James T McKenna
- VA Boston Healthcare System and Department of Psychiatry, Harvard Medical School, West Roxbury, MA 02132, USA
| | - Felipe L Schiffino
- VA Boston Healthcare System and Department of Psychiatry, Harvard Medical School, West Roxbury, MA 02132, USA; Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Robert E Strecker
- VA Boston Healthcare System and Department of Psychiatry, Harvard Medical School, West Roxbury, MA 02132, USA.
| | - John G McCoy
- Department of Psychology, Stonehill College, Easton, MA 02357, USA.
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5
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State-dependent effects of neural stimulation on brain function and cognition. Nat Rev Neurosci 2022; 23:459-475. [PMID: 35577959 DOI: 10.1038/s41583-022-00598-1] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/20/2022] [Indexed: 01/02/2023]
Abstract
Invasive and non-invasive brain stimulation methods are widely used in neuroscience to establish causal relationships between distinct brain regions and the sensory, cognitive and motor functions they subserve. When combined with concurrent brain imaging, such stimulation methods can reveal patterns of neuronal activity responsible for regulating simple and complex behaviours at the level of local circuits and across widespread networks. Understanding how fluctuations in physiological states and task demands might influence the effects of brain stimulation on neural activity and behaviour is at the heart of how we use these tools to understand cognition. Here we review the concept of such 'state-dependent' changes in brain activity in response to neural stimulation, and consider examples from research on altered states of consciousness (for example, sleep and anaesthesia) and from task-based manipulations of selective attention and working memory. We relate relevant findings from non-invasive methods used in humans to those obtained from direct electrical and optogenetic stimulation of neuronal ensembles in animal models. Given the widespread use of brain stimulation as a research tool in the laboratory and as a means of augmenting or restoring brain function, consideration of the influence of changing physiological and cognitive states is crucial for increasing the reliability of these interventions.
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Li G, Liu Y, Zheng Y, Wu Y, Li D, Liang X, Chen Y, Cui Y, Yap PT, Qiu S, Zhang H, Shen D. Multiscale neural modeling of resting-state fMRI reveals executive-limbic malfunction as a core mechanism in major depressive disorder. Neuroimage Clin 2021; 31:102758. [PMID: 34284335 PMCID: PMC8313604 DOI: 10.1016/j.nicl.2021.102758] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 06/30/2021] [Accepted: 07/03/2021] [Indexed: 11/15/2022]
Abstract
Major depressive disorder (MDD) represents a grand challenge to human health and society, but the underlying pathophysiological mechanisms remain elusive. Previous neuroimaging studies have suggested that MDD is associated with abnormal interactions and dynamics in two major neural systems including the default mode - salience (DMN-SAL) network and the executive - limbic (EXE-LIM) network, but it is not clear which network plays a central role and which network plays a subordinate role in MDD pathophysiology. To address this question, we refined a newly developed Multiscale Neural Model Inversion (MNMI) framework and applied it to test whether MDD is more affected by impaired circuit interactions in the DMN-SAL network or the EXE-LIM network. The model estimates the directed connection strengths between different neural populations both within and between brain regions based on resting-state fMRI data collected from normal healthy subjects and patients with MDD. Results show that MDD is primarily characterized by abnormal circuit interactions in the EXE-LIM network rather than the DMN-SAL network. Specifically, we observe reduced frontoparietal effective connectivity that potentially contributes to hypoactivity in the dorsolateral prefrontal cortex (dlPFC), and decreased intrinsic inhibition combined with increased excitation from the superior parietal cortex (SPC) that potentially lead to amygdala hyperactivity, together resulting in activation imbalance in the PFC-amygdala circuit that pervades in MDD. Moreover, the model reveals reduced PFC-to-hippocampus excitation but decreased SPC-to-thalamus inhibition in MDD population that potentially lead to hypoactivity in the hippocampus and hyperactivity in the thalamus, consistent with previous experimental data. Overall, our findings provide strong support for the long-standing limbic-cortical dysregulation model in major depression but also offer novel insights into the multiscale pathophysiology of this debilitating disease.
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Affiliation(s)
- Guoshi Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Yujie Liu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA; The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Yanting Zheng
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA; The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Ye Wu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Danian Li
- Cerebropathy Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Xinyu Liang
- The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Yaoping Chen
- The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China; Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Ying Cui
- Cerebropathy Center, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Pew-Thian Yap
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
| | - Han Zhang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA.
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC USA.
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7
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Barbero-Castillo A, Mateos-Aparicio P, Dalla Porta L, Camassa A, Perez-Mendez L, Sanchez-Vives MV. Impact of GABA A and GABA B Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States. J Neurosci 2021; 41:5029-5044. [PMID: 33906901 PMCID: PMC8197642 DOI: 10.1523/jneurosci.1837-20.2021] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 03/20/2021] [Accepted: 04/01/2021] [Indexed: 11/21/2022] Open
Abstract
Quantitative estimations of spatiotemporal complexity of cortical activity patterns are used in the clinic as a measure of consciousness levels, but the cortical mechanisms involved are not fully understood. We used a version of the perturbational complexity index (PCI) adapted to multisite recordings from the ferret (either sex) cerebral cortex in vitro (sPCI) to investigate the role of GABAergic inhibition in cortical complexity. We studied two dynamical states: slow-wave activity (synchronous state) and desynchronized activity, that express low and high causal complexity respectively. Progressive blockade of GABAergic inhibition during both regimes revealed its impact on the emergent cortical activity and on sPCI. Gradual GABAA receptor blockade resulted in higher synchronization, being able to drive the network from a desynchronized to a synchronous state, with a progressive decrease of complexity (sPCI). Blocking GABAB receptors also resulted in a reduced sPCI, in particular when in a synchronous, slow wave state. Our findings demonstrate that physiological levels of inhibition contribute to the generation of dynamical richness and spatiotemporal complexity. However, if inhibition is diminished or enhanced, cortical complexity decreases. Using a computational model, we explored a larger parameter space in this relationship and demonstrate a link between excitatory/inhibitory balance and the complexity expressed by the cortical network.SIGNIFICANCE STATEMENT The spatiotemporal complexity of the activity expressed by the cerebral cortex is a highly revealing feature of the underlying network's state. Complexity varies with physiological brain states: it is higher during awake than during sleep states. But it also informs about pathologic states: in disorders of consciousness, complexity is lower in an unresponsive wakefulness syndrome than in a minimally conscious state. What are the network parameters that modulate complexity? Here we investigate how inhibition, mediated by either GABAA or GABAA receptors, influences cortical complexity. And we do this departing from two extreme functional states: a highly synchronous, slow-wave state, and a desynchronized one that mimics wakefulness. We find that there is an optimal level of inhibition in which complexity is highest.
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Affiliation(s)
- Almudena Barbero-Castillo
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Pedro Mateos-Aparicio
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Leonardo Dalla Porta
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Alessandra Camassa
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Lorena Perez-Mendez
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Maria V Sanchez-Vives
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain 08010
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Saponati M, Garcia-Ojalvo J, Cataldo E, Mazzoni A. Thalamocortical Spectral Transmission Relies on Balanced Input Strengths. Brain Topogr 2021; 35:4-18. [PMID: 34089121 PMCID: PMC8813837 DOI: 10.1007/s10548-021-00851-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 05/05/2021] [Indexed: 12/27/2022]
Abstract
The thalamus is a key element of sensory transmission in the brain, as it gates and selects sensory streams through a modulation of its internal activity. A preponderant role in these functions is played by its internal activity in the alpha range ([8–14] Hz), but the mechanism underlying this process is not completely understood. In particular, how do thalamocortical connections convey stimulus driven information selectively over the back-ground of thalamic internally generated activity? Here we investigate this issue with a spiking network model of feedforward connectivity between thalamus and primary sensory cortex reproducing the local field potential of both areas. We found that in a feedforward network, thalamic oscillations in the alpha range do not entrain cortical activity for two reasons: (i) alpha range oscillations are weaker in neurons projecting to the cortex, (ii) the gamma resonance dynamics of cortical networks hampers oscillations over the 10–20 Hz range thus weakening alpha range oscillations. This latter mechanism depends on the balance of the strength of thalamocortical connections toward excitatory and inhibitory neurons in the cortex. Our results highlight the relevance of corticothalamic feedback to sustain alpha range oscillations and pave the way toward an integrated understanding of the sensory streams traveling between the periphery and the cortex.
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Affiliation(s)
- Matteo Saponati
- The Biorobotics Institute, Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025, Pontedera, IT, Italy.,Dipartimento di Fisica "E. Fermi", Largo Bruno Pontecorvo 3, 56127, Pisa, IT, Italy
| | - Jordi Garcia-Ojalvo
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park Dr. Aiguader 88, 08003, Barcelona, ES, Spain
| | - Enrico Cataldo
- Dipartimento di Fisica "E. Fermi", Largo Bruno Pontecorvo 3, 56127, Pisa, IT, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025, Pontedera, IT, Italy.
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Huang WA, Stitt IM, Negahbani E, Passey DJ, Ahn S, Davey M, Dannhauer M, Doan TT, Hoover AC, Peterchev AV, Radtke-Schuller S, Fröhlich F. Transcranial alternating current stimulation entrains alpha oscillations by preferential phase synchronization of fast-spiking cortical neurons to stimulation waveform. Nat Commun 2021; 12:3151. [PMID: 34035240 PMCID: PMC8149416 DOI: 10.1038/s41467-021-23021-2] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 03/24/2021] [Indexed: 12/12/2022] Open
Abstract
Computational modeling and human studies suggest that transcranial alternating current stimulation (tACS) modulates alpha oscillations by entrainment. Yet, a direct examination of how tACS interacts with neuronal spiking activity that gives rise to the alpha oscillation in the thalamo-cortical system has been lacking. Here, we demonstrate how tACS entrains endogenous alpha oscillations in head-fixed awake ferrets. We first show that endogenous alpha oscillations in the posterior parietal cortex drive the primary visual cortex and the higher-order visual thalamus. Spike-field coherence is largest for the alpha frequency band, and presumed fast-spiking inhibitory interneurons exhibit strongest coupling to this oscillation. We then apply alpha-tACS that results in a field strength comparable to what is commonly used in humans (<0.5 mV/mm). Both in these ferret experiments and in a computational model of the thalamo-cortical system, tACS entrains alpha oscillations by following the theoretically predicted Arnold tongue. Intriguingly, the fast-spiking inhibitory interneurons exhibit a stronger entrainment response to tACS in both the ferret experiments and the computational model, likely due to their stronger endogenous coupling to the alpha oscillation. Our findings demonstrate the in vivo mechanism of action for the modulation of the alpha oscillation by tACS.
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Affiliation(s)
- Wei A Huang
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC, USA
- Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA
| | - Iain M Stitt
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC, USA
| | - Ehsan Negahbani
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC, USA
| | - D J Passey
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC, USA
- Department of Mathematics, University of North Carolina, Chapel Hill, NC, USA
| | - Sangtae Ahn
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC, USA
- School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea
| | - Marshall Davey
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
- Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA
| | - Moritz Dannhauer
- Department of Psychiatry and Behavioral Science, Duke University, Durham, NC, USA
| | - Thien T Doan
- Department of Psychiatry and Behavioral Science, Duke University, Durham, NC, USA
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Anna C Hoover
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Angel V Peterchev
- Department of Psychiatry and Behavioral Science, Duke University, Durham, NC, USA
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, Duke University, Durham, NC, USA
| | - Susanne Radtke-Schuller
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC, USA
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC, USA.
- Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA.
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, USA.
- Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC, USA.
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA.
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Chiang S, Khambhati AN, Wang ET, Vannucci M, Chang EF, Rao VR. Evidence of state-dependence in the effectiveness of responsive neurostimulation for seizure modulation. Brain Stimul 2021; 14:366-375. [PMID: 33556620 PMCID: PMC8083819 DOI: 10.1016/j.brs.2021.01.023] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 01/25/2021] [Accepted: 01/31/2021] [Indexed: 11/28/2022] Open
Abstract
Background: An implanted device for brain-responsive neurostimulation (RNS® System) is approved as an effective treatment to reduce seizures in adults with medically-refractory focal epilepsy. Clinical trials of the RNS System demonstrate population-level reduction in average seizure frequency, but therapeutic response is highly variable. Hypothesis: Recent evidence links seizures to cyclical fluctuations in underlying risk. We tested the hypothesis that effectiveness of responsive neurostimulation varies based on current state within cyclical risk fluctuations. Methods: We analyzed retrospective data from 25 adults with medically-refractory focal epilepsy implanted with the RNS System. Chronic electrocorticography was used to record electrographic seizures, and hidden Markov models decoded seizures into fluctuations in underlying risk. State-dependent associations of RNS System stimulation parameters with changes in risk were estimated. Results: Higher charge density was associated with improved outcomes, both for remaining in a low seizure risk state and for transitioning from a high to a low seizure risk state. The effect of stimulation frequency depended on initial seizure risk state: when starting in a low risk state, higher stimulation frequencies were associated with remaining in a low risk state, but when starting in a high risk state, lower stimulation frequencies were associated with transition to a low risk state. Findings were consistent across bipolar and monopolar stimulation configurations. Conclusion: The impact of RNS on seizure frequency exhibits state-dependence, such that stimulation parameters which are effective in one seizure risk state may not be effective in another. These findings represent conceptual advances in understanding the therapeutic mechanism of RNS, and directly inform current practices of RNS tuning and the development of next-generation neurostimulation systems.
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Affiliation(s)
- Sharon Chiang
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States.
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Emily T Wang
- Department of Statistics, Rice University, Houston, TX, United States
| | - Marina Vannucci
- Department of Statistics, Rice University, Houston, TX, United States
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Vikram R Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
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11
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Yamakawa H. Revealing the Computational Meaning of Neocortical Interarea Signals. Front Comput Neurosci 2020; 14:74. [PMID: 33013340 PMCID: PMC7461790 DOI: 10.3389/fncom.2020.00074] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 07/13/2020] [Indexed: 11/13/2022] Open
Abstract
To understand the function of the neocortex, which is a hierarchical distributed network, it is useful giving meaning to the signals transmitted between these areas from the computational viewpoint. The overall anatomical structure or organs related to this network, including the neocortex, thalamus, and basal ganglia, has been roughly revealed, and much physiological knowledge, though often fragmentary, is being accumulated. The computational theories involving the neocortex have also been developed considerably. By introducing the assumption “The signals transmitted by interarea axonal projections of pyramidal cells in the neocortex carry different meanings for each cell type, common to all areas,” derived from its nature as a distributed network in the neocortex, allows us to specify the computational meanings of interarea signals. In this paper, first, the types of signals exchanged between neocortical areas are investigated, taking into account biological constraints, and employing theories such as predictive coding, reinforcement learning, representation emulation theory, and BDI logic as theoretical starting points, two types of feedforward signals (observation and deviation) and three types of feedback signals (prediction, plan, and intention) are identified. Next, based on the anatomical knowledge of the neocortex and thalamus, the pathways connecting the areas are organized and summarized as three corticocortical pathways and two thalamocortical pathways. Using this summation as preparation, this paper proposes a hypothesis that gives meaning to each type of signals transmitted in the different pathways in the neocortex, from the viewpoint of their functions. This hypothesis reckons that the feedforward corticocortical pathway transmits observation signals, the feedback corticocortical pathway transmits prediction signals, and the corticothalamic pathway mediated by core relay cells transmits deviation signals. The thalamocortical pathway, which is mediated by matrix relay cells, would be responsible for transmitting the signals that activate a part of prediction signals as intentions, due to the reason that the nature of the other available feedback pathways are not sufficient for conveying plans and intentions as signals. The corticocortical pathway, which is projected from various IT cells to the first layer, would be responsible for transmitting signals that activate a part of prediction signals as plans.
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Affiliation(s)
- Hiroshi Yamakawa
- University of Tokyo, Tokyo, Japan.,The Whole Brain Architecture Initiative, Edogawa-ku, Japan
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12
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Papadopoulos L, Lynn CW, Battaglia D, Bassett DS. Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical state. PLoS Comput Biol 2020; 16:e1008144. [PMID: 32886673 PMCID: PMC7537889 DOI: 10.1371/journal.pcbi.1008144] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Revised: 10/06/2020] [Accepted: 07/12/2020] [Indexed: 01/09/2023] Open
Abstract
At the macroscale, the brain operates as a network of interconnected neuronal populations, which display coordinated rhythmic dynamics that support interareal communication. Understanding how stimulation of different brain areas impacts such activity is important for gaining basic insights into brain function and for further developing therapeutic neurmodulation. However, the complexity of brain structure and dynamics hinders predictions regarding the downstream effects of focal stimulation. More specifically, little is known about how the collective oscillatory regime of brain network activity—in concert with network structure—affects the outcomes of perturbations. Here, we combine human connectome data and biophysical modeling to begin filling these gaps. By tuning parameters that control collective system dynamics, we identify distinct states of simulated brain activity and investigate how the distributed effects of stimulation manifest at different dynamical working points. When baseline oscillations are weak, the stimulated area exhibits enhanced power and frequency, and due to network interactions, activity in this excited frequency band propagates to nearby regions. Notably, beyond these linear effects, we further find that focal stimulation causes more distributed modifications to interareal coherence in a band containing regions’ baseline oscillation frequencies. Importantly, depending on the dynamical state of the system, these broadband effects can be better predicted by functional rather than structural connectivity, emphasizing a complex interplay between anatomical organization, dynamics, and response to perturbation. In contrast, when the network operates in a regime of strong regional oscillations, stimulation causes only slight shifts in power and frequency, and structural connectivity becomes most predictive of stimulation-induced changes in network activity patterns. In sum, this work builds upon and extends previous computational studies investigating the impacts of stimulation, and underscores the fact that both the stimulation site, and, crucially, the regime of brain network dynamics, can influence the network-wide responses to local perturbations. Stimulation can be used to alter brain activity and is a therapeutic option for certain neurological conditions. However, predicting the distributed effects of local perturbations is difficult. Previous studies show that responses to stimulation depend on anatomical (or structural) coupling. In addition to structure, here we consider how stimulation effects also depend on the brain’s collective dynamical (or functional) state, arising from the coordination of rhythmic activity across large-scale networks. In a whole-brain computational model, we show that global responses to regional stimulation can indeed be contingent upon and differ across various dynamical working points. Notably, depending on the network’s oscillatory regime, stimulation can accelerate the activity of the stimulated site, and lead to widespread effects at both the new, excited frequency, as well as in a much broader frequency range including areas’ baseline frequencies. While structural connectivity is a good predictor of “excited band” changes, in some states “baseline band” effects can be better predicted by functional connectivity, which depends upon the system’s oscillatory regime. By integrating and extending past efforts, our results thus indicate that dynamical—in additional to structural—brain organization plays a role in governing how focal stimulation modulates interactions between distributed network elements.
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Affiliation(s)
- Lia Papadopoulos
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Christopher W. Lynn
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Demian Battaglia
- Université Aix-Marseille, INSERM UMR 1106, Institut de Neurosciences des Systèmes, F-13005, Marseille, France
| | - Danielle S. Bassett
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Santa Fe Institute, Santa Fe, New Mexico, United States of America
- * E-mail:
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13
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Bennett M. An Attempt at a Unified Theory of the Neocortical Microcircuit in Sensory Cortex. Front Neural Circuits 2020; 14:40. [PMID: 32848632 PMCID: PMC7416357 DOI: 10.3389/fncir.2020.00040] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 06/15/2020] [Indexed: 11/13/2022] Open
Abstract
The neocortex performs a wide range of functions, including working memory, sensory perception, and motor planning. Despite this diversity in function, evidence suggests that the neocortex is made up of repeating subunits ("macrocolumns"), each of which is largely identical in circuitry. As such, the specific computations performed by these macrocolumns are of great interest to neuroscientists and AI researchers. Leading theories of this microcircuit include models of predictive coding, hierarchical temporal memory (HTM), and Adaptive Resonance Theory (ART). However, these models have not yet explained: (1) how microcircuits learn sequences input with delay (i.e., working memory); (2) how networks of columns coordinate processing on precise timescales; or (3) how top-down attention modulates sensory processing. I provide a theory of the neocortical microcircuit that extends prior models in all three ways. Additionally, this theory provides a novel working memory circuit that extends prior models to support simultaneous multi-item storage without disrupting ongoing sensory processing. I then use this theory to explain the functional origin of a diverse set of experimental findings, such as cortical oscillations.
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Affiliation(s)
- Max Bennett
- Independent Researcher, New York, NY, United States
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14
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Baroni F, Morillon B, Trébuchon A, Liégeois-Chauvel C, Olasagasti I, Giraud AL. Converging intracortical signatures of two separated processing timescales in human early auditory cortex. Neuroimage 2020; 218:116882. [PMID: 32439539 DOI: 10.1016/j.neuroimage.2020.116882] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 03/30/2020] [Accepted: 04/23/2020] [Indexed: 11/15/2022] Open
Abstract
Neural oscillations in auditory cortex are argued to support parsing and representing speech constituents at their corresponding temporal scales. Yet, how incoming sensory information interacts with ongoing spontaneous brain activity, what features of the neuronal microcircuitry underlie spontaneous and stimulus-evoked spectral fingerprints, and what these fingerprints entail for stimulus encoding, remain largely open questions. We used a combination of human invasive electrophysiology, computational modeling and decoding techniques to assess the information encoding properties of brain activity and to relate them to a plausible underlying neuronal microarchitecture. We analyzed intracortical auditory EEG activity from 10 patients while they were listening to short sentences. Pre-stimulus neural activity in early auditory cortical regions often exhibited power spectra with a shoulder in the delta range and a small bump in the beta range. Speech decreased power in the beta range, and increased power in the delta-theta and gamma ranges. Using multivariate machine learning techniques, we assessed the spectral profile of information content for two aspects of speech processing: detection and discrimination. We obtained better phase than power information decoding, and a bimodal spectral profile of information content with better decoding at low (delta-theta) and high (gamma) frequencies than at intermediate (beta) frequencies. These experimental data were reproduced by a simple rate model made of two subnetworks with different timescales, each composed of coupled excitatory and inhibitory units, and connected via a negative feedback loop. Modeling and experimental results were similar in terms of pre-stimulus spectral profile (except for the iEEG beta bump), spectral modulations with speech, and spectral profile of information content. Altogether, we provide converging evidence from both univariate spectral analysis and decoding approaches for a dual timescale processing infrastructure in human auditory cortex, and show that it is consistent with the dynamics of a simple rate model.
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Affiliation(s)
- Fabiano Baroni
- Department of Fundamental Neuroscience, University of Geneva, Geneva, Switzerland; School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
| | - Benjamin Morillon
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Neurosciences des Systémes (INS), Marseille, France
| | - Agnès Trébuchon
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Neurosciences des Systémes (INS), Marseille, France; Clinical Neurophysiology and Epileptology Department, Timone Hospital, Assistance Publique Hôpitaux de Marseille, Marseille, France
| | - Catherine Liégeois-Chauvel
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Neurosciences des Systémes (INS), Marseille, France; Department of Neurological Surgery, University of Pittsburgh, PA, 15213, USA
| | - Itsaso Olasagasti
- Department of Fundamental Neuroscience, University of Geneva, Geneva, Switzerland
| | - Anne-Lise Giraud
- Department of Fundamental Neuroscience, University of Geneva, Geneva, Switzerland
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15
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Li Q, Song JL, Li SH, Westover MB, Zhang R. Effects of Cholinergic Neuromodulation on Thalamocortical Rhythms During NREM Sleep: A Model Study. Front Comput Neurosci 2020; 13:100. [PMID: 32038215 PMCID: PMC6990259 DOI: 10.3389/fncom.2019.00100] [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: 09/09/2019] [Accepted: 12/30/2019] [Indexed: 11/13/2022] Open
Abstract
It has been suggested that cholinergic neurons shape the oscillatory activity of the thalamocortical (TC) network in behavioral and electrophysiological experiments. However, theoretical modeling demonstrating how cholinergic neuromodulation of thalamocortical rhythms during non-rapid eye movement (NREM) sleep might occur has been lacking. In this paper, we first develop a novel computational model (TC-ACH) by incorporating a cholinergic neuron population (CH) into the classical thalamo-cortical circuitry, where connections between populations are modeled in accordance with existing knowledge. The neurotransmitter acetylcholine (ACH) released by neurons in CH, which is able to change the discharge activity of thalamocortical neurons, is the primary focus of our work. Simulation results with our TC-ACH model reveal that the cholinergic projection activity is a key factor in modulating oscillation patterns in three ways: (1) transitions between different patterns of thalamocortical oscillations are dramatically modulated through diverse projection pathways; (2) the model expresses a stable spindle oscillation state with certain parameter settings for the cholinergic projection from CH to thalamus, and more spindles appear when the strength of cholinergic input from CH to thalamocortical neurons increases; (3) the duration of oscillation patterns during NREM sleep including K-complexes, spindles, and slow oscillations is longer when cholinergic input from CH to thalamocortical neurons becomes stronger. Our modeling results provide insights into the mechanisms by which the sleep state is controlled, and provide a theoretical basis for future experimental and clinical studies.
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Affiliation(s)
- Qiang Li
- Medical Big Data Research Center, Northwest University, Xi'an, China
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Jiang-Ling Song
- Medical Big Data Research Center, Northwest University, Xi'an, China
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Si-Hui Li
- Medical Big Data Research Center, Northwest University, Xi'an, China
| | - M. Brandon Westover
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Rui Zhang
- Medical Big Data Research Center, Northwest University, Xi'an, China
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16
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Sritharan SY, Contreras-Hernández E, Richardson AG, Lucas TH. Primate somatosensory cortical neurons are entrained to both spontaneous and peripherally evoked spindle oscillations. J Neurophysiol 2019; 123:300-307. [PMID: 31800329 DOI: 10.1152/jn.00471.2019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Recurrent thalamocortical circuits produce a number of rhythms critical to brain function. In slow-wave sleep, spindles (7-16 Hz) are a prominent spontaneous oscillation generated by thalamic circuits and triggered by cortical slow waves. In wakefulness and under anesthesia, brief peripheral sensory stimuli can evoke 10-Hz reverberations due potentially to similar thalamic mechanisms. Functionally, sleep spindles and peripherally evoked spindles may play a role in memory consolidation and perception, respectively. Yet, rarely have the circuits involved in these two rhythms been compared in the same animals and never in primates. Here, we investigated the entrainment of primary somatosensory cortex (S1) neurons to both rhythms in ketamine-sedated macaques. First, we compared spontaneous spindles in sedation and natural sleep to validate the model. Then, we quantified entrainment with spike-field coherence and phase-locking statistics. We found that S1 neurons entrained to spontaneous sleep spindles were also entrained to the evoked spindles, although entrainment strength and phase systematically differed. Our results indicate that the spindle oscillations triggered by top-down spontaneous cortical activity and bottom-up peripheral input share a common cortical substrate.NEW & NOTEWORTHY Brief sensory stimuli evoke 10-Hz oscillations in thalamocortical neuronal activity and in perceptual thresholds. The mechanisms underlying this evoked rhythm are not well understood but are thought to be similar to those generating sleep spindles. We directly compared the entrainment of cortical neurons to both spontaneous spindles and peripherally evoked oscillations in sedated monkeys. We found that the entrainment strengths to each rhythm were positively correlated, although with differing entrainment phases, implying involvement of similar networks.
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Affiliation(s)
- Srihari Y Sritharan
- Department of Neurosurgery, Center for Neuroengineering and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Enrique Contreras-Hernández
- Department of Neurosurgery, Center for Neuroengineering and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Andrew G Richardson
- Department of Neurosurgery, Center for Neuroengineering and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Timothy H Lucas
- Department of Neurosurgery, Center for Neuroengineering and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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17
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Torres-Russotto D, Elble RJ. Slow Orthostatic Tremor and the Case for Routine Electrophysiological Evaluation of All Tremors. Tremor Other Hyperkinet Mov (N Y) 2019; 9:tre-09-740. [PMID: 31832264 PMCID: PMC6886495 DOI: 10.7916/tohm.v0.740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Accepted: 10/23/2019] [Indexed: 12/01/2022] Open
Affiliation(s)
- Diego Torres-Russotto
- Movement Disorders Division, Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, USA
| | - Rodger J. Elble
- Department of Neurology, Southern Illinois University School of Medicine, Springfield, IL, USA
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18
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Li G, Liu Y, Zheng Y, Wu Y, Yap PT, Qiu S, Zhang H, Shen D. Identification of Abnormal Circuit Dynamics in Major Depressive Disorder via Multiscale Neural Modeling of Resting-State fMRI. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2019; 11766:682-690. [PMID: 34734214 PMCID: PMC8562763 DOI: 10.1007/978-3-030-32248-9_76] [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
Resting-state functional magnetic resonance imaging (rs-fMRI) studies have focused primarily on characterizing functional or effective connectivity of discrete brain regions. A major drawback of this approach is that it does not provide a mechanistic understanding of brain cognitive function or dysfunction at cellular and circuit levels. To overcome this limitation, we combined the methods of computational neuroscience with traditional macroscale connectomic analysis and developed a Multiscale Neural Model Inversion (MNMI) framework that links microscale circuit interaction with macroscale network dynamics and estimates both local coupling and inter-regional connections via stochastic optimization based on blood oxygen-level dependent (BOLD) rs-fMRI. We applied this method to the rs-fMRI data of 66 normal healthy subjects and 66 individuals with major depressive disorder (MDD) to identify potential biomarkers at both local circuit and global network level. Results suggest that the recurrent excitation and inhibition within the dorsal lateral prefrontal cortex (dlPFC) might be disrupted in MDD, consistent with the commonly accepted hypothetical model of MDD. In addition, recurrent excitation in the thalamus was found to be abnormally elevated, which may be responsible to abnormal thalamocortical oscillations often observed in MDD. Overall, our modeling approach holds the promise to overcome the limitation of traditional large-scale connectome modeling by providing hidden mechanistic insights into neuroanatomy, circuit dynamics and pathophysiology.
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Affiliation(s)
- Guoshi Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Yujie Liu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
- The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yanting Zheng
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
- The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ye Wu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Pew-Thian Yap
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Han Zhang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
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19
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Pizarro D, Ilyas A, Chaitanya G, Toth E, Irannejad A, Romeo A, Riley KO, Iasemidis L, Pati S. Spectral organization of focal seizures within the thalamotemporal network. Ann Clin Transl Neurol 2019; 6:1836-1848. [PMID: 31468745 PMCID: PMC6764631 DOI: 10.1002/acn3.50880] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 08/02/2019] [Accepted: 08/06/2019] [Indexed: 01/08/2023] Open
Abstract
Objective To investigate dynamic changes in neural activity between the anterior nucleus of the thalamus (ANT) and the seizure onset zone (SOZ) in patients with drug‐resistant temporal lobe epilepsy (TLE) based on anatomic location, seizure subtype, and state of vigilance (SOV). Methods Eleven patients undergoing stereoelectroencephalography for seizure localization were recruited prospectively for local field potential (LFP) recording directly from the ANT. The SOZ was identified using line length and epileptogenicity index. Changes in power spectral density (PSD) were compared between the two anatomic sites as seizures (N = 53) transitioned from interictal baseline to the posttermination stage. Results At baseline, the thalamic LFPs were significantly lower and distinct from the SOZ with the presence of higher power in the fast ripple band (P < 0.001). Temporal changes in ictal power of neural activity within ANT mimic those of the SOZ, are increased significantly at seizure onset (P < 0.05), and are distinct for seizures that impaired awareness or that secondarily generalized (P < 0.05). The onset of seizure was preceded by a decrease in the mean power spectral density (PSD) in ANT and SOZ (P < 0.05). Neural activity correlated with different states of vigilance at seizure onset within the ANT but not in the SOZ (P = 0.005). Interpretation The ANT can be recruited at the onset of mesial temporal lobe seizures, and the recruitment pattern differs with seizure subtypes. Furthermore, changes in neural dynamics precede seizure onset and are widespread to involve temporo‐thalamic regions, thereby providing an opportunity to intervene early with closed‐loop DBS.
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Affiliation(s)
- Diana Pizarro
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama.,Epilepsy and Cognitive Neurophysiology Laboratory, University of Alabama at Birmingham, Birmingham, Alabama
| | - Adeel Ilyas
- Epilepsy and Cognitive Neurophysiology Laboratory, University of Alabama at Birmingham, Birmingham, Alabama.,Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, Alabama
| | - Ganne Chaitanya
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama.,Epilepsy and Cognitive Neurophysiology Laboratory, University of Alabama at Birmingham, Birmingham, Alabama
| | - Emilia Toth
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama.,Epilepsy and Cognitive Neurophysiology Laboratory, University of Alabama at Birmingham, Birmingham, Alabama
| | - Auriana Irannejad
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama.,Epilepsy and Cognitive Neurophysiology Laboratory, University of Alabama at Birmingham, Birmingham, Alabama
| | - Andrew Romeo
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, Alabama
| | - Kristen O Riley
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, Alabama
| | - Leonidas Iasemidis
- Center for Biomedical Engineering and Rehabilitation Science, Louisiana Tech University, Ruston, Louisiana
| | - Sandipan Pati
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama.,Epilepsy and Cognitive Neurophysiology Laboratory, University of Alabama at Birmingham, Birmingham, Alabama
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20
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Alagapan S, Lustenberger C, Hadar E, Shin HW, Frӧhlich F. Low-frequency direct cortical stimulation of left superior frontal gyrus enhances working memory performance. Neuroimage 2019; 184:697-706. [PMID: 30268847 PMCID: PMC6240347 DOI: 10.1016/j.neuroimage.2018.09.064] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 08/02/2018] [Accepted: 09/21/2018] [Indexed: 02/02/2023] Open
Abstract
The neural substrates of working memory are spread across prefrontal, parietal and cingulate cortices and are thought to be coordinated through low frequency cortical oscillations in the theta (3-8 Hz) and alpha (8-12 Hz) frequency bands. While the functional role of many subregions have been elucidated using neuroimaging studies, the role of superior frontal gyrus (SFG) is not yet clear. Here, we combined electrocorticography and direct cortical stimulation in three patients implanted with subdural electrodes to assess if superior frontal gyrus is indeed involved in working memory. We found left SFG exhibited task-related modulation of oscillations in the theta and alpha frequency bands specifically during the encoding epoch. Stimulation at the frequency matched to the endogenous oscillations resulted in reduced reaction times in all three participants. Our results provide evidence for SFG playing a functional role in working memory and suggest that SFG may coordinate working memory through low-frequency oscillations thus bolstering the feasibility of using intracranial electric stimulation for restoring cognitive function.
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Affiliation(s)
- Sankaraleengam Alagapan
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Caroline Lustenberger
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Eldad Hadar
- Department of Neurosurgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Hae Won Shin
- Department of Neurosurgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Flavio Frӧhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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21
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Negahbani E, Schmidt SL, Mishal N, Fröhlich F. Neuromodulation-dependent effect of gated high-frequency, LFMS-like electric field stimulation in mouse cortical slices. Eur J Neurosci 2018; 49:1288-1297. [PMID: 30450622 DOI: 10.1111/ejn.14273] [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: 02/20/2018] [Revised: 10/29/2018] [Accepted: 10/30/2018] [Indexed: 11/27/2022]
Abstract
Low-field magnetic stimulation (LFMS) is a gated high-frequency non-invasive brain stimulation method (500 Hz gated at 2 Hz) with a proposed antidepressant effect. However, it has remained unknown how such stimulation paradigms modulate neuronal network activity and how the induced changes depend on network state. Here we examined the immediate and outlasting effects of the gated high-frequency electric field associated with LFMS on the cortical activity as a function of neuromodulatory tone that defines network state. We used a sham-controlled study design to investigate effects of stimulation (20 min of 0.5 s trains of 500 Hz charge-balanced pulse stimulation patterned at 0.5 Hz) on neural activity in mouse medial prefrontal cortex in vitro. Bath application of cholinergic and noradrenergic agents enabled us to examine the stimulation effects as a function of neuromodulatory tone. The stimulation attenuated the increase in firing rate of layer V cortical neurons during the post-stimulation period in the presence of cholinergic activation. The same stimulation had no significant immediate or outlasting effect in the absence of exogenous neuromodulators or in the presence of noradrenergic activation. These results provide electrophysiological insights into the neuromodulatory-dependent effects of gated high-frequency stimulation. More broadly, our results are the first to provide a mechanistic demonstration of how behavioral states and arousal levels may modify the effects of non-invasive brain stimulation.
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Affiliation(s)
- Ehsan Negahbani
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina.,Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, North Carolina
| | - Stephen L Schmidt
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina.,Department of Biomedical Engineering, University of North Carolina, Chapel Hill, North Carolina
| | - Nadia Mishal
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina.,Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, North Carolina.,Department of Biomedical Engineering, University of North Carolina, Chapel Hill, North Carolina.,Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina.,Neuroscience Center, University of North Carolina, Chapel Hill, North Carolina.,Department of Neurology, University of North Carolina, Chapel Hill, North Carolina
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22
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Li G, Henriquez CS, Fröhlich F. Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics. J Neural Eng 2018; 16:016013. [PMID: 30524080 DOI: 10.1088/1741-2552/aaeb03] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE Rhythmic brain stimulation has emerged as a powerful tool to modulate cognition and to target pathological oscillations related to neurological and psychiatric disorders. However, we lack a systematic understanding of how periodic stimulation interacts with endogenous neural activity as a function of the brain state and target. APPROACH To address this critical issue, we applied periodic stimulation to a unified biophysical thalamic network model that generates multiple distinct oscillations, and examined thoroughly the impact of rhythmic stimulation on different oscillatory states. MAIN RESULTS We found that rhythmic perturbation induces four basic response mechanisms: entrainment, acceleration, resonance and suppression. Importantly, the appearance and expression of these mechanisms depend highly on the intrinsic cellular dynamics in each state. Specifically, the low-threshold bursting of thalamocortical cells (TCs) in delta (δ) oscillation renders the network relatively insensitive to entrainment; the high-threshold bursting of TCs in alpha (α) oscillation leads to widespread oscillation suppression while the tonic spiking of TC cells in gamma (γ) oscillation results in prominent entrainment and resonance. In addition, we observed entrainment discontinuity during α oscillation that is mediated by firing pattern switching of high-threshold bursting TC cells. Furthermore, we demonstrate that direct excitatory stimulation of the lateral geniculate nucleus (LGN) entrains thalamic oscillations via an asymmetric Arnold tongue that favors higher frequency entrainment and resonance, while stimulation of the inhibitory circuit, the reticular nucleus, induces much weaker and more symmetric entrainment and resonance. These results support the notion that rhythmic stimulation engages brain oscillations in a state- and target-dependent manner. SIGNIFICANCE Overall, our study provides, for the first time, insights into how the biophysics of thalamic oscillations guide the emergence of complex, state-dependent mechanisms of target engagement, which can be leveraged for the future rational design of novel therapeutic stimulation modalities.
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Affiliation(s)
- Guoshi Li
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States of America
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Holmgren Hopkins N, Sanz-Leon P, Roy D, Postnova S. Spiking patterns and synchronization of thalamic neurons along the sleep-wake cycle. CHAOS (WOODBURY, N.Y.) 2018; 28:106314. [PMID: 30384650 DOI: 10.1063/1.5039754] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Accepted: 08/23/2018] [Indexed: 06/08/2023]
Abstract
Spiking patterns and synchronization dynamics of thalamic neurons along the sleep-wake cycle are studied in a minimal model of four coupled conductance-based neurons. The model simulates two thalamic neurons coupled via a gap junction and driven by a synaptic input from a two-neuron model of sleep regulation by the hypothalamus. In accord with experimental data, the model shows that during sleep, when hypothalamic wake-active neurons are silent, the thalamic neurons discharge bursts of spikes. During wake, the excitatory synaptic input from the hypothalamus drives the coupled thalamic neurons to a state of tonic firing (single spikes). In the deterministic case, the thalamic neurons synchronize in-phase in the bursting regime but demonstrate multi-stability of out-of-phase, in-phase, and asynchronous states in the tonic firing. However, along the sleep-wake cycle, once the neurons synchronize in-phase during sleep (bursting), they stay synchronized in wake (tonic firing). It is thus found that noise is needed to reproduce the experimentally observed transitions between synchronized bursting during sleep and asynchronous tonic firing during wake. Overall, synchronization of bursting is found to be more robust to noise than synchronization of tonic firing, where a small disturbance is sufficient to desynchronize the thalamic neurons. The model predicts that the transitions between sleep and wake happen via chaos because a single thalamic neuron exhibits chaos between regular bursting and tonic activity. The results of this study suggest that the sleep- and wake-related dynamics in the thalamus may be generated at a level of gap junction-coupled clusters of thalamic neurons driven from the hypothalamus which would then propagate throughout the thalamus and cortex via axonal long-range connections.
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Affiliation(s)
| | - Paula Sanz-Leon
- School of Physics, University of Sydney, Sydney, New South Wales 2006, Australia
| | - Dibyendu Roy
- School of Physics, University of Sydney, Sydney, New South Wales 2006, Australia
| | - Svetlana Postnova
- School of Physics, University of Sydney, Sydney, New South Wales 2006, Australia
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Kurmann R, Gast H, Schindler K, Fröhlich F. Rational design of transcranial alternating current stimulation. CLINICAL AND TRANSLATIONAL NEUROSCIENCE 2018. [DOI: 10.1177/2514183x18793515] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Affiliation(s)
- Rebekka Kurmann
- Sleep-Wake-Epilepsy-Center, Department of Neurology, InselSpital, University of Bern, Bern, Switzerland
| | - Heidemarie Gast
- Sleep-Wake-Epilepsy-Center, Department of Neurology, InselSpital, University of Bern, Bern, Switzerland
| | - Kaspar Schindler
- Sleep-Wake-Epilepsy-Center, Department of Neurology, InselSpital, University of Bern, Bern, Switzerland
| | - Flavio Fröhlich
- Sleep-Wake-Epilepsy-Center, Department of Neurology, InselSpital, University of Bern, Bern, Switzerland
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Lefebvre J, Hutt A, Frohlich F. Stochastic resonance mediates the state-dependent effect of periodic stimulation on cortical alpha oscillations. eLife 2017; 6:32054. [PMID: 29280733 PMCID: PMC5832422 DOI: 10.7554/elife.32054] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 12/22/2017] [Indexed: 12/14/2022] Open
Abstract
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.
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Affiliation(s)
| | - Axel Hutt
- FE12 - Data Assimilation, Deutscher Wetterdienst, Offenbach am Main, Germany
| | - Flavio Frohlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, United States
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