title: Shaping Intrinsic Neural Oscillations with Periodic Stimulation.
abstract: Rhythmic brain activity plays an important role in neural processing and behavior. Features of these oscillations, including amplitude, phase, and spectrum, can be influenced by internal states (e.g., shifts in arousal, attention or cognitive ability) or external stimulation. Electromagnetic stimulation techniques such as transcranial magnetic stimulation, transcranial direct current stimulation, and transcranial alternating current stimulation are used increasingly in both research and clinical settings. Currently, the mechanisms whereby time-dependent external stimuli influence population-scale oscillations remain poorly understood. Here, we provide computational insights regarding the mapping between periodic pulsatile stimulation parameters such as amplitude and frequency and the response dynamics of recurrent, nonlinear spiking neural networks. Using a cortical model built of excitatory and inhibitory neurons, we explored a wide range of stimulation intensities and frequencies systematically. Our results suggest that rhythmic stimulation can form the basis of a control paradigm in which one can manipulate the intrinsic oscillatory properties of driven networks via a plurality of input-driven mechanisms. Our results show that, in addition to resonance and entrainment, nonlinear acceleration is involved in shaping the rhythmic response of our modeled network. Such nonlinear acceleration of spontaneous and synchronous oscillatory activity in a neural network occurs in regimes of intense, high-frequency rhythmic stimulation. These results open new perspectives on the manipulation of synchronous neural activity for basic and clinical research.
  
  
  
  Oscillatory activity is widely recognized as a core mechanism for information transmission within and between brain circuits. Noninvasive stimulation methods can shape this activity, something that is increasingly capitalized upon in basic research and clinical practice. Here, we provide computational insights on the mechanistic bases for such effects. Our results show that rhythmic stimulation forms the basis of a control paradigm in which one can manipulate the intrinsic oscillatory properties of driven networks via a plurality of input-driven mechanisms. In addition to resonance and entrainment, nonlinear acceleration is involved in shaping the rhythmic response of our modeled network, particularly in regimes of high-frequency rhythmic stimulation. These results open new perspectives on the manipulation of synchronous neural activity for basic and clinical research.
authors.affiliation: Experimental Psychology Laboratory, Department of Psychology, Cluster of Excellence Hearing4all and European Medical School and Research Center Neurosensory Science, Carl-von-Ossietzky University Oldenburg, 26111 Oldenburg, Germany.
authors.forename: Christoph S
authors.identifier: 0000-0003-0323-2272
authors.initials: CS
authors.lastname: Herrmann
authors.affiliation: The Laboratory for Investigative Neurophysiology (The LINE), Department of Clinical Neurosciences and Department of Radiology, University Hospital Center and University of Lausanne, Lausanne 1011, Switzerland, Electroencephalography Brain Mapping Core, Center for Biomedical Imaging (CIBM), Lausanne 1011, Switzerland, Department of Ophthalmology, University of Lausanne, Jules-Gonin Eye Hospital, Lausanne 1000, Switzerland.
authors.forename: Micah M
authors.identifier: 0000-0002-7821-117X
authors.initials: MM
authors.lastname: Murray
authors.affiliation: The Laboratory for Investigative Neurophysiology (The LINE), Department of Clinical Neurosciences and Department of Radiology, University Hospital Center and University of Lausanne, Lausanne 1011, Switzerland, Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zürich, 8092 Zürich, Switzerland.
authors.forename: Silvio
authors.initials: S
authors.lastname: Ionta
authors.affiliation: Deutscher Wetterdienst, Section FE12 Data Assimilation, 63067 Offenbach am Main, Germany.
authors.forename: Axel
authors.initials: A
authors.lastname: Hutt
authors.affiliation: The Laboratory for Investigative Neurophysiology (The LINE), Department of Clinical Neurosciences and Department of Radiology, University Hospital Center and University of Lausanne, Lausanne 1011, Switzerland, Krembil Research Institute, University Health Network, Toronto, Ontario M5T 2S8, Canada, and Department of Mathematics, University of Toronto, Toronto, Ontario M5S 3G3, Canada jeremie.lefebvre@uhnresearch.ca.
authors.forename: Jérémie
authors.initials: J
authors.lastname: Lefebvre
mesh_terms: D000200:Action Potentials; D001921:Brain / Q000166:cytology / Q000502:physiology*; D004558:Electric Stimulation; D004569:Electroencephalography; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology; D010507:Periodicity; D055366:Synaptic Potentials
keywords: dynamics; networks; oscillations; spectrum; stimulation; synchrony