Review
Frontal theta as a mechanism for cognitive control

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Highlights

  • Frontal theta is a candidate biophysical mechanism for cognitive control.

  • Frontal midline theta reflects a canonical computation of the need for control.

  • The implementation of control may emerge from intersite theta-phase synchrony.

  • The information content of frontal theta can be derived using computational models.

Recent advancements in cognitive neuroscience have afforded a description of neural responses in terms of latent algorithmic operations. However, the adoption of this approach to human scalp electroencephalography (EEG) has been more limited, despite the ability of this methodology to quantify canonical neuronal processes. Here, we provide evidence that theta band activities over the midfrontal cortex appear to reflect a common computation used for realizing the need for cognitive control. Moreover, by virtue of inherent properties of field oscillations, these theta band processes may be used to communicate this need and subsequently implement such control across disparate brain regions. Thus, frontal theta is a compelling candidate mechanism by which emergent processes, such as ‘cognitive control’, may be biophysically realized.

Section snippets

Frontal computations are revealed by theta band activities

The prefrontal cortex allows us to transcend routines and habits to make better decisions. However, how does it actually ‘do’ this? As cognitive neuroscientists, we need to aim to move beyond descriptive findings and psychological correlates for a better understanding of how the brain underlies the mind. A mechanistic perspective is ideal for addressing how latent neural features underlie emergent psychological constructs.

Although the marriage of cognitive neuroscience and formal computational

Theta reflects active cortical functioning

Primate theta band (approximately 4–8 Hz) activities reflect a more discrete range of activities than the similarly named ‘theta’ observed in rat hippocampus (approximately 4–12 Hz). In primates, theta is broadly distributed across the brain [6] and appears to reflect active operations of the generative cortex, particularly during high-level cognitive processes, such as memory encoding and retrieval, working memory retention, novelty detection, and realizing the need for top-down control 7, 8, 9,

Frontal midline theta and the realization of the need for control

The realization of the need for control appears to be conveyed by frontal midline theta (FMθ) activities recorded from sensors overlying medial prefrontal cortex (mPFC). These FMθ activities have largely been quantified as event-related potential (ERP) components that reflect mPFC-related control processes elicited by novel information, conflicting stimulus–response requirements, punishing feedback, and the realization of errors. These potentials are known by varied and sometimes overlapping

Theta phase is a biologically plausible candidate for neuronal computation and communication

We propose that these theta-band similarities not only suggest that these phenomena are aspects of a common high-level process, but also may indicate how the need for control is biophysically realized and communicated. Time-varying changes in the phase angle reflect population-wide oscillations of neuronal membrane potentials [37]. This synchronization can create temporal windows for segregating cortical populations [38], which can separate information intake and transfer processes 39, 40.

Potential roles of theta in the instantiation of control

It is becoming increasingly clear that these FMθ activities reflect uncertainty in varied circumstances (Box 1). Given that the mPFC is sensitive to varied circumstances indicating a need for control [49], it should be expected that this system commonly reacts to novelty, conflict, punishment, and error, each of which indicate a need for enhanced control processes to change behavior adaptively. Thus, it is important to consider whether this theta signal acts to communicate specific information

What to do with a surprise signal?

Here, we describe some ways by which mPFC-generated surprise signals lead to task-specific adjustments in control (Figure 4). FMθ is sensitive to both unexpected uncertainty (volatility) and expected uncertainty (risk) [13], suggesting that it serves as both a teaching signal and an alarm of the need for control. This observation suggests that the information content of the signal, at least as measured on the human scalp, is minimal. Yet, even a simple signal of uncertainty can lead to a

Caveats for such a broad description

Any description of mPFC processes is bound to be complicated by the high base rate of activation in areas such as MCC across experimental demands [79]. It should be expected that some mPFC processes are not reflected by FMΘ, and that some FMΘ processes do not necessarily involve a phasic response to uncertainty. Moreover, other frequency bands have been shown to have a role in the implementation of control 19, 22, 74. It remains an important goal to specify the role of frontal theta in relation

Concluding remarks

Even a simple surprise signal can be used to communicate many different things. If the mPFC responds to unsigned prediction errors using a theta-band process capable of intersite entrainment, this would provide a plausible mechanism by which surprise could influence action selection, shift attention, cautiously adjust behavior, and enhance sensory precision. Most compellingly, such seemingly complex interactions may emerge simply by virtue of the connectivity and timing of biophysical processes

Acknowledgments

The authors thank Alex Shackman for his helpful discussions on these topics. This report was supported by NIH RO1 MH080066-01 and NSF 1125788.

References (99)

  • P.J. Uhlhaas

    Neural synchrony and the development of cortical networks

    Trends Cogn. Sci.

    (2010)
  • K. Benchenane

    Coherent theta oscillations and reorganization of spike timing in the hippocampal-prefrontal network upon learning

    Neuron

    (2010)
  • M. Remondes et al.

    Cingulate-hippocampus coherence and trajectory coding in a sequential choice task

    Neuron

    (2013)
  • L.H. Arnal et al.

    Cortical oscillations and sensory predictions

    Trends Cogn. Sci.

    (2012)
  • O. Jensen et al.

    Hippocampal sequence-encoding driven by a cortical multi-item working memory buffer

    Trends Neurosci.

    (2005)
  • M. Medalla et al.

    Synapses with inhibitory neurons differentiate anterior cingulate from dorsolateral prefrontal pathways associated with cognitive control

    Neuron

    (2009)
  • W. Singer

    Cortical dynamics revisited

    Trends Cogn. Sci.

    (2013)
  • W. Notebaert

    Post-error slowing: an orienting account

    Cognition

    (2009)
  • K. Johnston

    Top-down control-signal dynamics in anterior cingulate and prefrontal cortex neurons following task switching

    Neuron

    (2007)
  • K. Friston

    Learning and inference in the brain

    Neural Netw.

    (2003)
  • O. David

    Modelling event-related responses in the brain

    Neuroimage

    (2005)
  • M.J. Frank

    Error-related negativity predicts reinforcement learning and conflict biases

    Neuron

    (2005)
  • A. Caplin et al.

    Axiomatic methods, dopamine and reward prediction error

    Curr. Opin. Neurobiol.

    (2008)
  • W. Klimesch

    Event-related phase reorganization may explain evoked neural dynamics

    Neurosci. Biobehav. Rev.

    (2007)
  • M.F. Rushworth et al.

    Choice, uncertainty and value in prefrontal and cingulate cortex

    Nat. Neurosci.

    (2008)
  • J.I. Gold et al.

    The neural basis of decision making

    Annu. Rev. Neurosci.

    (2007)
  • P. Fries

    Neuronal gamma-band synchronization as a fundamental process in cortical computation

    Annu. Rev. Neurosci.

    (2009)
  • M. Siegel

    Spectral fingerprints of large-scale neuronal interactions

    Nat. Rev. Neurosci.

    (2012)
  • S. Raghavachari

    Theta oscillations in human cortex during a working-memory task: evidence for local generators

    J. Neurophysiol.

    (2006)
  • S. Itthipuripat

    Frontal theta is a signature of successful working memory manipulation

    Exp. Brain Res.

    (2013)
  • J.F. Cavanagh

    Theta lingua franca: a common mid-frontal substrate for action monitoring processes

    Psychophysiology

    (2012)
  • U. Rutishauser

    Human memory strength is predicted by theta-frequency phase-locking of single neurons

    Nature

    (2010)
  • W.J. Gehring

    The error-related negativity (ERN/Ne)

  • J.R. Folstein et al.

    Influence of cognitive control and mismatch on the N2 component of the ERP: a review

    Psychophysiology

    (2008)
  • S. Hanslmayr

    The electrophysiological dynamics of interference during the Stroop task

    J. Cogn. Neurosci.

    (2008)
  • J.F. Cavanagh

    Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring

    J. Neurosci.

    (2009)
  • M.X. Cohen

    Unconscious errors enhance prefrontal-occipital oscillatory synchrony

    Front. Hum. Neurosci.

    (2009)
  • M.X. Cohen et al.

    Single-trial regression elucidates the role of prefrontal theta oscillations in response conflict

    Front. Psychol.

    (2011)
  • M.X. Cohen et al.

    Dynamic interactions between large-scale brain networks predict behavioral adaptation after perceptual errors

    Cereb. Cortex

    (2013)
  • R. Nigbur

    Theta dynamics reveal domain-specific control over stimulus and response conflict

    J. Cogn. Neurosci.

    (2012)
  • I. Van de Vijver

    Frontal oscillatory dynamics predict feedback learning and action adjustment

    J. Cogn. Neurosci.

    (2011)
  • J. Van Driel

    Not all errors are alike: theta and alpha EEG dynamics relate to differences in error-processing dynamics

    J. Neurosci.

    (2012)
  • N.S. Narayanan

    Common medial frontal mechanisms of adaptive control in humans and rodents

    Nat. Neurosci.

    (2013)
  • J. Anguera et al.

    Video game training enhances cognitive control in older adults

    Nature

    (2013)
  • W.J. Gehring

    A neural system for error-detection and compensation

    Psychol. Sci.

    (1993)
  • M.M. Walsh et al.

    Learning from delayed feedback: neural responses in temporal credit assignment

    Cogn. Affect. Behav. Neurosci.

    (2011)
  • N. Yeung

    The neural basis of error detection: conflict monitoring and the error-related negativity

    Psychol. Rev.

    (2004)
  • M.X. Cohen et al.

    Reinforcement learning signals predict future decisions

    J. Neurosci.

    (2007)
  • S. Debener

    Trial-by-trial coupling of concurrent electroencephalogram and functional magnetic resonance imaging identifies the dynamics of performance monitoring

    J. Neurosci.

    (2005)
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