Endogenous Neuromodulation at Infralow Frequencies

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Neuromodulation in the bioelectrical domain is an attractive option for the remediation of functionally based deficits. Most of the interest to date has focused on exogenous methods, such as repetitive transcranial magnetic stimulation, transient direct current stimulation, vagus nerve stimulation, and deep brain stimulation. Much less attention has been given to endogenous methods of exploiting latent brain plasticity. These have reached a level of sophistication and maturity that invites attention. Over the last 7 years, the domain of infralow frequencies has been exploited productively for the enhancement of neuroregulation. The principal mechanism is putatively the renormalization of functional connectivity of our resting-state networks. The endogeneous techniques are particularly attractive for the pediatric population, where they can be utilized before dysfunctional patterns of brain behavior become consolidated and further elaborated into clinical syndromes.

Section snippets

The Clinical Method

The clinical approach is based entirely on inviting the brain to engage with information derived from the low-frequency EEG. Typically the signal is presented in the form of a video display, often accompanied by tactile feedback. A bipolar montage is used exclusively. This informs the brain as to the time course of the differential activation at two cortical sites.36 It also serves the usual purpose of suppressing common-mode signals, such as nonneuronal influences on the signal.37 The spectral

The Hierarchy of Regulation

If the brain is regarded as a control system, its fundamental responsibility is to assure its own unconditional stability.38, 39 This is a particular challenge because to function in a real-time environment, the brain is also constrained to work in a critical state, poised for rapid, macroscopic state change.40, 41 This maintains the brain far from an equilibrium state. This implies a narrow parameter space for both optimum responsiveness and stability in the vulnerable brain. Ultimately we

The Protocols in the Spatial Domain

Protocol development has proceeded largely empirically, informed at all times by considerations of functional neuroanatomy. The critical drivers in this development were instability and severe dysregulation. A broad generalization has been consolidated over the years that brain stability is best promoted with interhemispheric placements.49, 50 The placement offering the strongest effects and greatest breadth of clinical effect is T3-T4. The most severe cases of dysregulation observed in

The Protocols in the Frequency Domain

The unstable brain is the most sensitive to the parameters of the training, in particular, the target frequency. Because of the extreme sensitivity to target frequency, the right-hemisphere issues drove the agenda for the deepening penetration of the ILF region. The most difficult and intractable cases tended to require the lowest target frequencies. Whereas the initial thrust into the lowest frequency region was mandated by our most challenging clients, by now it is clear that nearly everyone

Assessment

Assessment covers a broad range of observables that can capture the quality of system functioning and characterize the nature of the particular dysregulation at issue. Client history is extensively explored, with emphasis on early developmental issues. Brain stability and arousal regulation are probed with a continuous performance test (CPT) with everyone capable of taking the test. The expectation for successful training is that the CPT measures normalize or at least improve. The test tracks

Discrimination of the Slow Cortical Potential

It has been convenient to describe the brain’s engagement with its own EEG in anthropomorphic terms. It is necessary to demonstrate, however, that translation of the simplistic model into a viable neurophysiological model is in prospect. An analogy may be helpful. The driver on a Los Angeles freeway is likely to have turned over the job of steering the car to his brain while his mind is engaged on higher matters. And even if his mind were to turn to thoughts of suicide, the brain would still

Feedback on Spectral Properties of the EEG

The roots of frequency-based neurofeedback go back to animal research performed in the 1960s. In the course of sleep research on cats, a bursting rhythm was identified in sensorimotor cortex while the cats were motorically idle.10 Termed the sensorimotor rhythm (SMR), the spindle bursts occurred at the same frequency as the sleep spindle and thus were identified with it. Operant conditioning to promote the appearance of SMR bursts altered both the waking and sleep behavior of the cats.63, 64

Disorders of Sleep Regulation

As the quality of sleep is a good index to the quality of arousal regulation, it is an appropriate starting point for a discussion of clinical effects.85 Remediation of insomnia was originally reported for SMR training for cases involving an anxiety condition.74 ILF training has been found to be more generally helpful with ordinary insomnia—delayed sleep onset, frequent waking, failure to return to sleep after early wakening, etc. The effects are often felt after a single session. Given the

An Appraisal and a Projection

Understanding and treating the brain in the perspective of its functioning as a dynamically regulated, hierarchical control system has turned out to be highly fruitful, and portends significant implications for clinical neurology and psychiatry, and for all the neurosciences. Stimulating and promoting endogenous mechanisms of recovery allows for a level of subtlety, refinement, and comprehensiveness in clinical practice that is not available with existing exogenous therapies.

The potential is

References (108)

  • A.F.T. Arnsten et al.

    Dynamic Network Connectivity: A new form of neuroplasticity

    Trends Cogn Sci

    (2010)
  • G. Werner

    Metastability, criticality and phase transitions in brain and its models

    Biosystems

    (2007)
  • P. Halász

    Hierarchy of micro-arousals and the microstructure of sleep

    Neurophysiol Clin

    (1998)
  • E. Sforza et al.

    Cardiac activation during arousal in humans: Further evidence for hierarchy in the arousal response

    Clin Neurophysiol

    (2000)
  • E.J.S. Sonuga-Barke et al.

    Spontaneous attentional fluctuations in impaired states and pathological conditions: A neurobiological hypothesis

    Neurosci Biobehav Rev

    (2007)
  • S.J. Broyd et al.

    Default-mode brain dysfunction in mental disorders: A systematic review

    Neurosci Biobehav Rev

    (2009)
  • M.B. Sterman et al.

    Effects of sensorimotor EEG feedback training on seizure susceptibility in the Rhesus monkey

    Exp Neurol

    (1978)
  • U. Strehl et al.

    Predictors of seizure reduction after self-regulation of slow cortical potentials as a treatment of drug-resistant epilepsy

    Epilepsy Behav

    (2005)
  • J. Gruzelier et al.

    Learned control of interhemispheric slow potential negativity in schizophrenia

    Int J Psychophysiol

    (1999)
  • C.H. Moritz et al.

    Functional MR imaging assessment of a non-responsive brain injured patient

    Magn Reson Imaging

    (2001)
  • K.E. Thornton et al.

    Electroencephalogram biofeedback for reading disability and traumatic brain injury

    Child Adolesc Psychiatr Clin N Am

    (2005)
  • J.A. Pineda et al.

    Positive behavioral and electrophysiological changes following neurofeedback training in children with autism

    Res Autism Spectr Disord

    (2008)
  • G. Tan et al.

    Meta-analysis of EEG biofeedback in treating epilepsy

    Clin EEG Neurosci

    (2009)
  • R.C. deCharms et al.

    Control over brain activation and pain learned by using real-time functional MRI

    Proc Natl Acad Sci U S A

    (2005)
  • T. Harmelech et al.

    The day-after effect: Long term, Hebbian-like restructuring of resting-state fMRI patterns induced by a single epoch of cortical activation

    J Neurosci

    (2013)
  • G. Zhang et al.

    Functional alteration of the DMN by learned regulation of the PCC using real-time fMRI

    IEEE Trans Neural Syst Rehabil Eng

    (2013)
  • D. Scheinost et al.

    Orbitofrontal cortex neurofeedback produces lasting changes in contamination anxiety and resting-state connectivity

    Transl Psychiatry

    (2013)
  • D.P. Nowlis et al.

    The control of electroencephalographic alpha rhythms through auditory feedback and the associated mental activity

    Psychophysiology

    (1970)
  • D. Mantini et al.

    Electrophysiological signatures of resting state networks in the human brain

    Proc Natl Acad Sci U S A

    (2007)
  • A.L. Ko et al.

    Quasi-periodic fluctuations in default mode network electrophysiology

    J Neurosci

    (2011)
  • M.H. Lee et al.

    Clustering of resting state networks

    PLoS One

    (2012)
  • Othmer S, Othmer SF, Legarda SB: Clinical neurofeedback: Training brain behavior. Treatment Strategies—Pediatric...
  • F.X. Castellanos et al.

    Connectivity

    Curr Top Behav Neurosci

    (2013)
  • B.S. Khundrakpam et al.

    Developmental changes in organization of structural brain networks

    Cereb Cortex

    (2013)
  • K. Supekar et al.

    Development of large-scale functional brain networks in children

    PLoS Biol

    (2009)
  • J.B. Watson et al.

    Conditioned emotional reactions

    J Exp Psychol

    (1920)
  • H.E. Scharfman

    Epilepsy as an example of neural plasticity

    Neuroscientist

    (2002)
  • Othmer SF: Protocol Guide for Neurofeedback Clinicians. Los Angeles, CA, EEG Info Publications, 2006-2013 ((ed 1),...
  • F. Travis et al.

    A self-referential default brain state: Patterns of coherence, power, and eLORETA sources during eyes-closed rest and transcendental meditation practice

    Cogn Process

    (2010)
  • G. Pagnoni

    Dynamical properties of BOLD activity from the ventral posteromedial cortex associated with meditation and attentional skills

    J Neurosci

    (2012)
  • V.A. Taylor et al.

    Impact of meditation training on the default mode network during a restful state

    Soc Cogn Affect Neurosci

    (2013)
  • D. Sliz et al.

    Neural correlates of a single-session massage treatment

    Brain Imaging Behav

    (2012)
  • C.J. Vaidya et al.

    Phenotypic variability in resting-state functional connectivity: Current status

    Brain Connectivity

    (2013)
  • H. Benson

    The Relaxation Response

    (1975)
  • M.W. Muesse

    Practicing Mindfulness: An Introduction to Meditation

    (2011)
  • M.P. Jensen et al.

    Neurofeedback treatment for pain associated with complex regional pain syndrome type I

    J Neurother

    (2007)
  • A Proposal for Standard Montages to Be Used in Clinical EEG

    (2006)
  • J. Voipio et al.

    Millivolt-Scale DC Shift in the Human Scalp EEG: Evidence for a Nonneuronal Generator

    J Neurophysiol

    (2003)
  • A. Fingelkurts et al.

    Making complexity simpler: Multivariability and metastability in the brain

    Int J Neurosci

    (2004)
  • J.M. Beggs et al.

    Neuronal avalanches in neocortical circuits

    J Neurosci

    (2003)
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