Desynchronizing to be faster? Perceptual- and attentional-modulation of brain rhythms at the sub-millisecond scale
Introduction
Many studies suggest that neural oscillatory signals could serve various important functions in the brain. Unit-cell recordings on animals showed that changes in amplitude and coherence of gamma-band oscillation are strongly linked to cognitive processes such as feature integration and attention (Engel et al., 2001; Fries, 2009), while oscillations in theta-band plays a key role in memory (Buzsaki and Moser, 2013; Knyazev, 2007). The close relationships between oscillatory signals and cognitive functions have been also demonstrated in the human brain (Jensen et al., 2007; Palva and Palva, 2011). In electroencephalography (EEG) and magnetoencephalography (MEG), an increase in power of a given frequency band is called the event-related synchronization (ERS), which reflects cooperative or synchronized behaviors of a large number of neurons (Pfurtscheller and Lopes da Silva, 1999) that would facilitate the information transfer across neuronal groups (Fries, 2005). Consistent with this view, a spatial allocation of attention induced the gamma-band ERS in the sensory cortex of a contralateral hemisphere (Bauer et al., 2006), and stronger theta-band ERS in a memory encoding stage predicted better performances in later retrieval stage (Osipova et al., 2006).
In contrast to the ERS, a decrease in power of oscillatory signals is called the event-related desynchronization or ERD (Pfurtscheller and Lopes da Silva, 1999), being associated with uncorrelated (irregular) behaviors of neural population. Paradoxically, many studies have reported the ERD in brain regions that would play a central role in a given task (task-relevant regions). A well-known example is the alpha ERD over the occipital cortex in response to visual inputs (Berger, 1929). Recent studies showed that not only the alpha rhythm (8–12 Hz) but also the beta rhythm (13–30 Hz) showed prominent ERD to visual (Kulashekhar et al., 2016; Minami et al., 2014; Wyart and Tallon-Baudry, 2009), auditory (Cirelli et al., 2014; de Pesters et al., 2016; Fujioka et al., 2015), and somatosensory (Bauer et al., 2006; Fransen et al., 2016) stimuli. The alpha/beta ERD in the sensory areas was also induced by attention (van Ede et al., 2012). A voluntary allocation of attention to a visual hemifield reduced alpha/beta power in the contralateral visual cortex (Bauer et al., 2014; Worden et al., 2000; Wyart and Tallon-Baudry, 2009).
Why was the ERD, a neural signature of uncorrelated activities, observed in task-relevant regions? Previous studies resolved this issue by assuming an inhibitory role of alpha oscillation on neural processing (Jensen and Mazaheri, 2010; Klimesch, 2012). For example, Jensen and Mazaheri (2010) argued that alpha activity provides pulsed inhibition reducing the processing capabilities of a given area. A recent study also reported the inhibitory role of beta rhythm on neural processing (Shin et al., 2017). The alpha/beta ERD observed in task-relevant regions thus would reflect a release from this periodic (regular) inhibition, representing the active processing of sensory information in a contra-stimulus and contra-attention hemisphere.
Although this release-from-inhibition (disinhibition) hypothesis of alpha/beta ERD is widely accepted, here we explore a new role of ERD other than the disinhibition. Specifically, we focused on changes in frequency (Cohen, 2014) and regularity (Fransen et al., 2015) of neural rhythms caused by the ERD. Regularity (or periodicity) is one of the most fundamental information in oscillatory signals. Indeed, previous studies reported altered regularity of neural oscillations in patients with mental disorders such as Alzheimer's disease (Gomez et al., 2007; Poza et al., 2012). We hypothesized that, if the alpha/beta ERD represents weakened (less-regulated) pulses of inhibition, this would be associated with decreased regularity of oscillations in the same frequency band.
Basic procedures of our MEG experiment are shown in Fig. 1. Participants performed the standard Posner task in which their attention was directed to either a left or right visual field (Fig. 1A). A central cue (arrow) and a peripheral task stimulus (Gabor patch) would induce a decrease in alpha/beta power in a contralateral (contra-attention and contra-stimulus) hemisphere. To quantify the regularity, we measured inter-peak intervals (IPIs) of oscillatory signals (Fig. 1B), depicting a distribution of their occurrences (Fig. 1C). For example, an IPI distribution of alpha rhythm (8–12 Hz) would be centered on 100 ms, because its central frequency is 10 Hz. When the alpha rhythm is highly regular, most IPIs would be located around the mean (100 ms), which results in a smaller variance of the distribution (Fig. 1C, top). In contrast, an irregular alpha wave would be indexed by a large variance because such irregular rhythm produces IPIs distant from 100 ms (Fig. 1C, bottom). One advantage of our method is that it can measure various types of changes in oscillatory signals simultaneously. For example, if the decreased alpha/beta power causes an overall increase in an oscillation frequency, this would be detected as a decrease in a mean (rather than variance) of IPIs.
Section snippets
Participants
Twenty-two healthy human subjects (13 females, age: 20–54) participated in the present study. Informed consent was received from each participant after the nature of the study had been explained. All experiments were carried out in accordance with guidelines and regulations approved by the ethics committee of Kobe University, Japan.
Stimuli and task
We used the Matlab Psychophysics Toolbox (Brainard, 1997; Pelli, 1997) to generate visual stimuli (refresh rate: 60 Hz) and to record button-press responses by
Behavioral data
Hit and false-alarm (FA) rates in all types of trials (mean ± SE across participants) are shown in Fig. 2. Participants correctly pressed a button when a grating with a target orientation (target grating) appeared in an attended visual field (hit rates: 95.2% in LL target and 94.8% in RR target trials). Reactions times measured from an onset of a grating were 665.9 ± 23.6 ms (LL) and 665.7 ± 22.2 ms (RR). No difference in hit rates (t(21) = 0.30, p = 0.77, Cohen's d = 0.029) or reaction times (t
Discussion
In contrast to the prediction in Introduction, we presently found that the decreased alpha-to-beta power in task-relevant regions was associated with the increased regularity of oscillatory signals. Although regularity (periodicity) of neural oscillation has been measured using autocorrelation analysis (Red'ka and Mayorov, 2015), spectral entropy (Gomez-Pilar et al., 2016; Poza et al., 2012), sample entropy (Gomez and Hornero, 2010), auto-mutual information analysis (Gomez et al., 2007), Q
Acknowledgments
This work was supported by KAKENHI Grants Number 22680022 and 26700011 from the Japan Society for the Promotion of Science for Young Scientists to Y.N. We thank Mr. Y. Takeshima (National Institute for Physiological Sciences, Japan) for his technical supports. The authors declare no competing financial interest. All data supporting the findings of this study are available from Y.N. upon reasonable request.
References (57)
- et al.
Interareal oscillatory synchronization in top-down neocortical processing
Curr. Opin. Neurobiol.
(2015) - et al.
Alpha power indexes task-related networks on large and small scales: a multimodal ECoG study in humans and a non-human primate
Neuroimage
(2016) - et al.
Toward a computational theory of conscious processing
Curr. Opin. Neurobiol.
(2014) - et al.
Beta-band oscillations--signalling the status quo?
Curr. Opin. Neurobiol.
(2010) - et al.
Identifying neuronal oscillations using rhythmicity
Neuroimage
(2015) A mechanism for cognitive dynamics: neuronal communication through neuronal coherence
Trends Cognit. Sci.
(2005)- et al.
Analysis of the magnetoencephalogram background activity in Alzheimer's disease patients with auto-mutual information
Comput. Methods Progr. Biomed.
(2007) - et al.
New insights into the relationship between dopamine, beta oscillations and motor function
Trends Neurosci.
(2011) - et al.
Human gamma-frequency oscillations associated with attention and memory
Trends Neurosci.
(2007) alpha-band oscillations, attention, and controlled access to stored information
Trends Cognit. Sci.
(2012)
Motivation, emotion, and their inhibitory control mirrored in brain oscillations
Neurosci. Biobehav. Rev.
Aberrant alpha and gamma oscillations ex vivo after single application of the NMDA receptor antagonist MK-801
Schizophr. Res.
EEG spectral dynamics during discrimination of auditory and visual targets
Brain Res Cogn Brain Res
State-dependent alpha peak frequency shifts: experimental evidence, potential mechanisms and functional implications
Neuroscience
Decreased beta-band activity is correlated with disambiguation of hidden figures
Neuropsychologia
Linking ADHD to the neural circuitry of attention
Trends Cognit. Sci.
Viewing lip forms: cortical dynamics
Neuron
Direct behavioral and neural evidence for an offset-triggered conscious perception
Cortex
Event-related EEG/MEG synchronization and desynchronization: basic principles
Clin. Neurophysiol.
Temporal dynamics of neural activity underlying unconscious processing of manipulable objects
Cortex
Tactile spatial attention enhances gamma-band activity in somatosensory cortex and reduces low-frequency activity in parieto-occipital areas
J. Neurosci.
Attentional modulation of alpha/beta and gamma oscillations reflect functionally distinct processes
J. Neurosci.
Sensory coding accuracy and perceptual performance are improved during the desynchronized cortical state
Nat. Commun.
Controlling the false discovery rate - a practical and powerful approach to multiple testing
J. Roy. Stat. Soc. B
Uber das Elektrenkephalogramm des Menschen
Arch Psychiat Nervenkr
The neural basis of visual attention
J. Physiol.
The psychophysics toolbox
Spatial Vis.
Memory, navigation and theta rhythm in the hippocampal-entorhinal system
Nat. Neurosci.
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