Self-regulation of frontal-midline theta facilitates memory updating and mental set shifting

Frontal-midline (fm) theta oscillations as measured via the electroencephalogram (EEG) have been suggested as neural “working language” of executive functioning. Their power has been shown to increase when cognitive processing or task performance is enhanced. Thus, the question arises whether learning to increase fm-theta amplitudes would functionally impact the behavioral performance in tasks probing executive functions (EFs). Here, the effects of neurofeedback (NF), a learning method to self-up-regulate fm-theta over fm electrodes, on the four most representative EFs, memory updating, set shifting, conflict monitoring, and motor inhibition are presented. Before beginning and after completing an individualized, eight-session gap-spaced NF intervention, the three-back, letter/number task-switching, Stroop, and stop-signal tasks were tested while measuring the EEG. Self-determined up-regulation of fm-theta and its putative role for executive functioning were compared to an active control group, the so-called pseudo-neurofeedback group. Task-related fm-theta activity after training differed significantly between groups. More importantly, though, after NF significantly enhanced behavioral performance was observed. The training group showed higher accuracy scores in the three-back task and reduced mixing and shifting costs in letter/number task-switching. However, this specific protocol type did not affect performance in tasks probing conflict monitoring and motor inhibition. Thus, our results suggest a modulation of proactive but not reactive mechanisms of cognitive control. Furthermore, task-related EEG changes show a distinct pattern for fm-theta after training between the NF and the pseudo-neurofeedback group, which indicates that NF training indeed tackles EFs-networks. In sum, the modulation of fm-theta via NF may serve as potent treatment approach for executive dysfunctions.

[1]  A. Fingelkurts,et al.  EEG Oscillatory States: Universality, Uniqueness and Specificity across Healthy-Normal, Altered and Pathological Brain Conditions , 2014, PloS one.

[2]  B. Stankoff,et al.  Induction of myelination in the central nervous system by electrical activity. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[3]  M. J. Emerson,et al.  The Unity and Diversity of Executive Functions and Their Contributions to Complex “Frontal Lobe” Tasks: A Latent Variable Analysis , 2000, Cognitive Psychology.

[4]  A. Mecklinger,et al.  Separating intra-modal and across-modal training effects in visual working memory: an fMRI investigation. , 2011, Cerebral cortex.

[5]  H. Kraemer,et al.  A Decade of EEG Theta/Beta Ratio Research in ADHD , 2013, Journal of attention disorders.

[6]  K. Grill-Spector,et al.  Repetition and the brain: neural models of stimulus-specific effects , 2006, Trends in Cognitive Sciences.

[7]  A. Miyake,et al.  The Nature and Organization of Individual Differences in Executive Functions , 2012, Current directions in psychological science.

[8]  Ruth Stevens,et al.  Improving children's working memory and classroom performance , 2010 .

[9]  M B Sterman,et al.  Facilitation of Spindle-Burst Sleep by Conditioning of Electroencephalographic Activity While Awake , 1970, Science.

[10]  Brent A. Vogt,et al.  Cingulate Neurobiology and Disease , 2009 .

[11]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[12]  N. McNaughton,et al.  Frontal-midline theta from the perspective of hippocampal “theta” , 2008, Progress in Neurobiology.

[13]  P. J. Basser,et al.  Role of myelin plasticity in oscillations and synchrony of neuronal activity , 2014, Neuroscience.

[14]  M. Molnár,et al.  Age-related changes of frontal-midline theta is predictive of efficient memory maintenance , 2014, Neuroscience.

[15]  Benedikt Zoefel,et al.  Neurofeedback training of the upper alpha frequency band in EEG improves cognitive performance , 2011, NeuroImage.

[16]  G. Logan,et al.  Impulsivity and Inhibitory Control , 1997 .

[17]  Michael X. Cohen,et al.  Midfrontal conflict-related theta-band power reflects neural oscillations that predict behavior. , 2013, Journal of neurophysiology.

[18]  Rebecca Elliott,et al.  Executive functions and their disorders. , 2003, British medical bulletin.

[19]  B. Oken,et al.  Expectancy effect: Impact of pill administration on cognitive performance in healthy seniors , 2008, Journal of clinical and experimental neuropsychology.

[20]  M. Rushworth,et al.  Behavioral / Systems / Cognitive Connectivity-Based Parcellation of Human Cingulate Cortex and Its Relation to Functional Specialization , 2008 .

[21]  M. Arns,et al.  Neurofeedback and Basic Learning Theory: Implications for Research and Practice , 2011 .

[22]  J. Rothwell,et al.  Endogenous control of waking brain rhythms induces neuroplasticity in humans , 2010, The European journal of neuroscience.

[23]  J. Kray,et al.  How useful is executive control training? Age differences in near and far transfer of task-switching training. , 2009, Developmental science.

[24]  M. Hautzinger,et al.  Slow cortical potential and theta/beta neurofeedback training in adults: effects on attentional processes and motor system excitability , 2014, Front. Hum. Neurosci..

[25]  S. Petersen,et al.  A dual-networks architecture of top-down control , 2008, Trends in Cognitive Sciences.

[26]  R. Fields,et al.  Astrocytes Promote Myelination in Response to Electrical Impulses , 2006, Neuron.

[27]  J. Gruzelier EEG-neurofeedback for optimising performance. I: A review of cognitive and affective outcome in healthy participants , 2014, Neuroscience & Biobehavioral Reviews.

[28]  N. Landrø,et al.  Executive functions are impaired in adolescents engaging in non-suicidal self-injury , 2010, Psychological Medicine.

[29]  R. Chabot,et al.  Quantitative electroencephalographic profiles of children with attention deficit disorder , 1996, Biological Psychiatry.

[30]  Jacob Cohen Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[31]  Daniel J. Miller,et al.  Prolonged myelination in human neocortical evolution , 2012, Proceedings of the National Academy of Sciences.

[32]  R. Nigbur,et al.  Theta power as a marker for cognitive interference , 2011, Clinical Neurophysiology.

[33]  R. Fields Change in the Brain's White Matter , 2010, Science.

[34]  Wolfgang Klimesch,et al.  Instrumental conditioning of human sensorimotor rhythm (12-15 Hz) and its impact on sleep as well as declarative learning. , 2008, Sleep.

[35]  A. Engel,et al.  Cognitive functions of gamma-band activity: memory match and utilization , 2004, Trends in Cognitive Sciences.

[36]  Marc W Howard,et al.  Theta and Gamma Oscillations during Encoding Predict Subsequent Recall , 2003, The Journal of Neuroscience.

[37]  N. Birbaumer,et al.  Learned regulation of brain metabolism , 2013, Trends in Cognitive Sciences.

[38]  S. Makeig,et al.  Mining event-related brain dynamics , 2004, Trends in Cognitive Sciences.

[39]  E. Basar,et al.  A review of brain oscillations in cognitive disorders and the role of neurotransmitters , 2008, Brain Research.

[40]  René J. Huster,et al.  Modulation of frontal-midline theta by neurofeedback , 2014, Biological Psychology.

[41]  John J. B. Allen,et al.  Theta lingua franca: a common mid-frontal substrate for action monitoring processes. , 2012, Psychophysiology.

[42]  T. Braver The variable nature of cognitive control: a dual mechanisms framework , 2012, Trends in Cognitive Sciences.

[43]  Jonathan D. Cohen,et al.  Conflict monitoring and anterior cingulate cortex: an update , 2004, Trends in Cognitive Sciences.

[44]  K. Young,et al.  Adult myelination: wrapping up neuronal plasticity , 2014, Neural regeneration research.

[45]  L. Vaughan,et al.  Executive function in daily life: Age-related influences of executive processes on instrumental activities of daily living. , 2010, Psychology and aging.

[46]  R. C. Oldfield The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[47]  S. Hsieh,et al.  Neurofeedback training improves attention and working memory performance , 2013, Clinical Neurophysiology.

[48]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[49]  G. Buzsáki Rhythms of the brain , 2006 .

[50]  K. Kubota,et al.  Neurofeedback Using Real-Time Near-Infrared Spectroscopy Enhances Motor Imagery Related Cortical Activation , 2012, PloS one.

[51]  W. Klimesch EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis , 1999, Brain Research Reviews.

[52]  M. Molnár,et al.  Frontal midline theta connectivity is related to efficiency of WM maintenance and is affected by aging , 2014, Neurobiology of Learning and Memory.

[53]  Niels Birbaumer,et al.  Neurofeedback and brain-computer interface clinical applications. , 2009, International review of neurobiology.

[54]  Christina F. Lavallee,et al.  Electroencephalography of response inhibition tasks: functional networks and cognitive contributions. , 2013, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[55]  Kimberly L. Ray,et al.  Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions , 2012, Cognitive, affective & behavioral neuroscience.

[56]  A. Belger,et al.  Impaired Neural Synchrony in the Theta Frequency Range in Adolescents at Familial Risk for Schizophrenia , 2011, Front. Psychiatry.

[57]  V. Menon Large-scale brain networks and psychopathology: a unifying triple network model , 2011, Trends in Cognitive Sciences.

[58]  I. Higginson,et al.  Experimental and quasi-experimental designs , 2011 .

[59]  Bernhard Hommel,et al.  Enhancing cognitive control through neurofeedback: A role of gamma-band activity in managing episodic retrieval , 2010, NeuroImage.

[60]  Petra Kaufmann,et al.  Experimental And Quasi Experimental Designs For Research , 2016 .

[61]  L. Hedges,et al.  Statistical Methods for Meta-Analysis , 1987 .

[62]  Cihan Gani,et al.  Long term effects after feedback of slow cortical potentials and of theta-beta-amplitudes in children with attention-deficit/hyperactivity disorder (ADHD) , 2009 .

[63]  Marc Wildi,et al.  Test–retest reliability of EEG spectra during a working memory task , 2008, NeuroImage.

[64]  T. Egner,et al.  EEG Biofeedback of low beta band components: frequency-specific effects on variables of attention and event-related brain potentials , 2004, Clinical Neurophysiology.

[65]  C. Neuper,et al.  Near-infrared spectroscopy based neurofeedback training increases specific motor imagery related cortical activation compared to sham feedback , 2014, Biological Psychology.

[66]  K. Miller Executive functions. , 2005, Pediatric annals.

[67]  Manuel Schabus,et al.  Increasing Individual Upper Alpha Power by Neurofeedback Improves Cognitive Performance in Human Subjects , 2005, Applied psychophysiology and biofeedback.

[68]  Stephen P. Hinshaw,et al.  Childhood Executive Function Continues to Predict Outcomes in Young Adult Females with and Without Childhood-Diagnosed ADHD , 2012, Journal of abnormal child psychology.

[69]  Mirka Pesonen,et al.  Brain oscillatory 4–30 Hz responses during a visual n-back memory task with varying memory load , 2007, Brain Research.

[70]  Mathias Benedek,et al.  Neural efficiency as a function of task demands , 2014, Intelligence.

[71]  T. Egner,et al.  Learned self-regulation of EEG frequency components affects attention and event-related brain potentials in humans , 2001, Neuroreport.

[72]  Simon Hanslmayr,et al.  Neural Communication Patterns Underlying Conflict Detection, Resolution, and Adaptation , 2014, The Journal of Neuroscience.

[73]  M. Berger,et al.  High Gamma Power Is Phase-Locked to Theta Oscillations in Human Neocortex , 2006, Science.

[74]  Alan Tucholka,et al.  Neurofeedback Training Induces Changes in White and Gray Matter , 2013, Clinical EEG and neuroscience.

[75]  R. Douglas Fields,et al.  Control of Local Protein Synthesis and Initial Events in Myelination by Action Potentials , 2011, Science.

[76]  René J. Huster,et al.  Brain-computer interfaces for EEG neurofeedback: peculiarities and solutions. , 2014, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[77]  Niels Birbaumer,et al.  Neurofeedback and brain-computer interface clinical applications. , 2009, International review of neurobiology.

[78]  Michael X. Cohen,et al.  Single-Trial Regression Elucidates the Role of Prefrontal Theta Oscillations in Response Conflict , 2011, Front. Psychology.

[79]  Carles Escera,et al.  EEG delta oscillations index inhibitory control of contextual novelty to both irrelevant distracters and relevant task-switch cues. , 2014, Psychophysiology.

[80]  Tilo Kircher,et al.  Acquired self‐control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia , 2013, Human brain mapping.

[81]  Robert J Barry,et al.  EEG-defined subtypes of children with attention-deficit/hyperactivity disorder , 2001, Clinical Neurophysiology.

[82]  Xiao-Hua Zhou,et al.  Statistical Methods for Meta‐Analysis , 2008 .

[83]  N. Logothetis,et al.  Scaling Brain Size, Keeping Timing: Evolutionary Preservation of Brain Rhythms , 2013, Neuron.

[84]  M. Frank,et al.  Frontal theta as a mechanism for cognitive control , 2014, Trends in Cognitive Sciences.

[85]  M. Just,et al.  Exploring the neural dynamics underpinning individual differences in sentence comprehension. , 2011, Cerebral cortex.

[86]  Vince D. Calhoun,et al.  Mind over chatter: Plastic up-regulation of the fMRI salience network directly after EEG neurofeedback , 2013, NeuroImage.

[87]  G. Buzsáki,et al.  Neuronal Oscillations in Cortical Networks , 2004, Science.

[88]  Wei Wang,et al.  rtMEG: A Real-Time Software Interface for Magnetoencephalography , 2011, Comput. Intell. Neurosci..

[89]  K. Young,et al.  White matter plasticity in adulthood , 2014, Neuroscience.