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  • Review Article
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Spectral fingerprints of large-scale neuronal interactions

Nature Reviews Neuroscience volume 13, pages 121–134 (2012)Cite this article

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Key Points

  • Goal-directed, sensory-guided behaviour relies on both feedforward and feedback interactions between brain regions.

  • Studies of sensorimotor decision-making and top-down attention show that these large-scale interactions are reflected by the phase coherence and amplitude correlation of oscillations between brain regions.

  • Phase coherence and amplitude correlation provide insights into the large-scale neuronal interactions underlying cognition.

  • The frequencies of large-scale coherent oscillations reflect the neuronal circuit mechanisms of the canonical computations underlying cognition.

  • The frequencies of large-scale coherent oscillations may constitute indices, or 'fingerprints', of these canonical computations.

  • 'Spectral fingerprints' provide a level of description situated in between the 'processes' defined by cognitive psychology and the underlying neuronal circuit mechanisms. This level of description may help to identify commonalities and differences between cognitive processes.

Abstract

Cognition results from interactions among functionally specialized but widely distributed brain regions; however, neuroscience has so far largely focused on characterizing the function of individual brain regions and neurons therein. Here we discuss recent studies that have instead investigated the interactions between brain regions during cognitive processes by assessing correlations between neuronal oscillations in different regions of the primate cerebral cortex. These studies have opened a new window onto the large-scale circuit mechanisms underlying sensorimotor decision-making and top-down attention. We propose that frequency-specific neuronal correlations in large-scale cortical networks may be 'fingerprints' of canonical neuronal computations underlying cognitive processes.

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Figure 1: Phase coherence and amplitude correlation of oscillations.
Figure 2: Cortical network dynamics underlying sensorimotor decisions.
Figure 3: Cortical network dynamics underlying top-down attention.
Figure 4: Large-scale spectral fingerprints of cognitive processes.

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Acknowledgements

We thank J. F. Hipp and C. von Nicolai for helpful discussions and comments on the manuscript. This work was supported by grants from the European Union (HEALTH-F2-2008-200728, INFSO-ICT-270212 and ERC-2010-AdG-269716 to A.K.E.) and the German Research Foundation (GRK 1247/1/2 and SFB 936/1 to A.K.E).

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  1. Markus Siegel and Tobias H. Donner: These authors contributed equally.

Authors and Affiliations

  1. Centre for Integrative Neuroscience, University of Tübingen, Tübingen, 72076, Germany

    Markus Siegel

  2. Department of Psychology, University of Amsterdam, Amsterdam, 1018 WB, The Netherlands

    Tobias H. Donner

  3. Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, 20246, Germany

    Andreas K. Engel

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  1. Markus Siegel
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Glossary

Spectral analysis

A general term for analysis techniques (for example, Fourier transform or wavelet transform) that decompose time domain signals into their different frequency components.

Multi-microelectrode recordings

Simultaneous recordings of single- or multi-unit activity from multiple electrodes implanted in the brain.

Blood oxygen level-dependent functional MRI

(BOLD fMRI). Brain imaging technique that measures the haemodynamic response to neural activity based on changes in blood oxygenation.

Sensor level

The level of the sensors, which record neuronal mass activity (for example, electroencephalography electrodes or magnetoencephalography sensors). Each sensor-level signal constitutes a linear mixture of the signals generated by many neuronal sources.

Source reconstruction

Estimation of the sources of neuronal activity that underlie the electromagnetic signals measured at distant electroencephalography or magnetoencephalography sensors.

Effective connectivity

The influence one neuronal system exerts on another; in many studies it is measured by quantifying Granger causality.

1/f spectrum

A spectrum for which the power P is inversely proportional to frequency f: P(f) ∝ 1/fa, a>0.

Posterior parietal cortex

(PPC). An associative brain region that is centrally involved in spatial processing and controlling selective attention.

Area MT

A region in the extrastriate visual cortex of the primate brain that is centrally involved in neuronal processing and perception of visual motion.

Local field potentials

(LFPs). The low-frequency components of the extracellular voltage. The LFP mainly reflects average postsynaptic potentials surrounding the electrode tip.

Frontal eye field

(FEF). A region in the frontal cortex that controls saccadic eye movements and the focus of visuospatial attention in the primate brain.

Granger causality

A statistical measure that quantifies directed and potentially causal interactions between two simultaneous signals based on their mutual predictability.

Attentional blink

The phenomenon that a second target is often missed when presented ∼200–500 ms after a first target in a rapid stream of visual stimuli.

Go/no-go task

A task that requires a subject to perform a behavioural response (for example, button press) when one stimulus type appears, but to withhold a response when another stimulus type appears.

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Siegel, M., Donner, T. & Engel, A. Spectral fingerprints of large-scale neuronal interactions. Nat Rev Neurosci 13, 121–134 (2012). https://doi.org/10.1038/nrn3137

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