Elsevier

NeuroImage

Volume 89, 1 April 2014, Pages 235-243
NeuroImage

Alpha activity reflects individual abilities to adapt to the environment

https://doi.org/10.1016/j.neuroimage.2013.12.018Get rights and content

Abstract

Recent findings suggest that oscillatory alpha activity (7–13 Hz) is associated with functional inhibition of sensory regions by filtering incoming information. Accordingly the alpha power in visual regions varies in anticipation of upcoming, predictable stimuli which has consequences for visual processing and subsequent behavior. In covert spatial attention studies it has been demonstrated that performance correlates with the adaptation of alpha power in response to explicit spatial cueing. However it remains unknown whether such an adaptation also occurs in response to implicit statistical properties of a task. In a covert attention switching paradigm, we here show evidence that individuals differ on how they adapt to implicit statistical properties of the task. Subjects whose behavioral performance reflects the implicit change in switch trial likelihood show strong adjustment of anticipatory alpha power lateralization. Most importantly, the stronger the behavioral adjustment to the switch trial likelihood was, the stronger the adjustment of anticipatory posterior alpha lateralization. We conclude that anticipatory spatial attention is reflected in the distribution of posterior alpha band power which is predictive of individual detection performance in response to the implicit statistical properties of the task.

Introduction

When driving down a long and lonesome road, you can probably attend to the road while also talking to your passenger. As you head towards a crowded crossing, you will gradually focus your attention to the traffic and eventually stop talking to your passenger. After having passed the crossing you can allow yourself to again attend to your passenger.

This example illustrates our ability to gradually adjust our attentional resources according to the surrounding. This process is likely to be associated with a gradual engagement and disengagement of brain regions processing respectively relevant or irrelevant for the task at hand. We hypothesize that this redistribution of resources is partly reflected by a differential adjustment of neural oscillations in various brain regions. Recent findings suggest that oscillatory alpha activity (7–13 Hz) plays a role in the distribution of attention resources by functional inhibition of sensory regions. This allows for filtering incoming information (reviewed in Bonnefond and Jensen, 2012, Foxe and Snyder, 2011, Jensen and Mazaheri, 2010, Jensen et al., 2012, Klimesch, 1999, Klimesch, 2012). The main idea is that alpha activity increases in sensory regions associated with suppression of task-irrelevant information, while alpha activity decreases in regions processing the task-relevant information. For instance, recent studies on visual covert attention have demonstrated that alpha power decreases in the parieto-occipital regions contralateral to the anticipated stimuli whereas alpha activity increases relatively in ipsilateral parieto-occipital regions (Worden et al., 2000). In a visuo-spatial detection task, Thut et al. (2006) demonstrated that the degree of prestimulus hemispheric alpha lateralization correlated with faster target detections. Kelly et al. (2009) and Händel et al. (2011) showed that the strength of prestimulus alpha lateralization is predictive of target discriminability. These studies indicate that hemispheric alpha lateralization correlates with enhanced performance in spatial attention tasks. Finally, Romei et al. (2010) demonstrated that TMS can be applied to entrain alpha oscillations over the parietal cortex ipsi-lateral to the attended direction. Since this entrainment had positive consequences for performance in a spatial attention task, one can argue for a causal inhibitory role of the alpha oscillations.

Two recent studies provided strong evidence for alpha power being under top-down control by demonstrating that prestimulus hemispheric alpha lateralization is influenced by explicit manipulation of the reliability of the spatial cue (i.e. a cue indicating the visual hemifield to covertly attend to). Haegens et al. (2011) conducted a spatial somatosensory discrimination task in which subjects were explicitly informed about the cue reliability. They found that the reliability of the cue correlated with the prestimulus alpha power lateralization in sensorimotor regions. A related study was performed by Gould et al. (2011) in the visual domain. They found a linear increase in alpha lateralization in visual regions with cue reliability. Furthermore, subjects with a stronger alpha power decrease contralateral to the cue also showed a stronger behavioral cueing effect as reflected in faster reaction times. These two studies show that alpha power in both visual and somatosensory regions is modulated by expectations about the likelihood of external events.

In these paradigms attention biasing was manipulated using explicit cues. In real life, however, attention biasing is often modulated by statistical properties of events in the environment. The aim of our current study was to assess whether biases in the allocation of attention due to statistical properties in the environment are reflected in anticipatory alpha-band lateralization. In a visual covert attention paradigm subjects were instructed to detect a stream of targets occurring in one hemifield. However, they had to switch attention to the unattended hemifield when a stimulus change occurred in the unattended side. The likelihood of an attention-switch-stimulus (indicating an attention switch trial) increased with the number of trials following the previous switch; however, the subjects were not explicitly informed about this statistical property. We assessed the individual change in alpha lateralization and switch-trial detection rate with switch-trial likelihood. Our study provides evidence that subjects who adapted their behavior (i.e. switch trial detection rate) according to the statistical properties of the task (switch-trial likelihood) also were the ones who adjusted their hemispheric alpha lateralization accordingly.

Section snippets

Participants

Twenty healthy subjects with normal or corrected-to-normal vision (mean age: 24 ± (SD) 4 years) participated in the experiment after providing written informed consent according to the Declaration of Helsinki and the local Ethics board. The subjects did not have neurological or psychiatric disorders. The study was approved by the local ethics committee (CMO region Arnhem/Nijmegen).

Stimulus presentation and experimental paradigm

Stimulus presentation was performed using Presentation (Neurobehavioural Systems, Inc.) and a liquid crystal display

Behavioral performance

The subjects were asked to perform the task described in Fig. 1. We recorded 1018 ± 98 (mean ± standard deviation) trials per subject and 722 ± 122 trials were left after artifact rejection; 151 ± 21 of them were switch trials, i.e. trials which include a switch stimulus (see Section 2.2). We expected the detection of switch trials to be more difficult than the detection of repeat trials, i.e. to be associated with longer reaction times and more errors (van Schouwenburg, 2010). Figs. 3A and D provide

Discussion

In a covert attention switching paradigm, we have investigated how subjects adapt to statistical properties of the environment; here a linear increase in the likelihood of stimuli prompting a switch in spatial attention. We found individual differences in how subjects adjusted behaviorally to the increase in switch trial likelihood. Interestingly, the individual degree of adjustment of posterior alpha band lateralization to switch trials likelihood predicted how well subjects adjusted their

Acknowledgments

M.B. is supported by the Fyssen Foundation. R.C. was supported by a Human Frontiers Science Program grant to Kae Nakamura, Nathaniel Daw and R.C. under grant number RGP0036/2009-c, as well as a VIDI grant from the Innovational Research Incentives Scheme of the Netherlands Organisation for Scientific Research (NWO) under grant number 016-095-340 and a James McDonnell scholar award. She has been a consultant to Abbott Laboratories and Pfizer, but she is not an employee or a stock shareholder.

References (41)

  • A. Stolk et al.

    Online and offline tools for head movement compensation in MEG

    Neuroimage

    (2013)
  • N. ter Huurne et al.

    Behavioral consequences of aberrant alpha lateralization in attention deficit/hyperactivity disorder

    Biol. Psychiatry

    (2013)
  • P. Capotosto et al.

    Fronto-parietal cortex controls spatial attention through modulation of anticipatory alpha rhythms

    J. Neurosci.

    (2009)
  • P. Capotosto et al.

    Differential contribution of right and left parietal cortex to the control of spatial attention: a simultaneous EEG-rTMS study

    Cereb. Cortex

    (2012)
  • E. Comoli et al.

    A direction projection from superior colliculus to substantia nigra for detecting salient visual events

    Nat. Neurosci.

    (2003)
  • M. Corbetta et al.

    Control of goal-directed and stimulus-driven attention in the brain

    Nat. Rev. Neurosci.

    (2002)
  • J.J. Foxe et al.

    The role of alpha-band brain oscillations as a sensory suppression mechanism during selective attention

    Front. Psychol.

    (2011)
  • I.C. Gould et al.

    Indexing the graded allocation of visuospatial attention using anticipatory alpha oscillations

    JN Physiol.

    (2011)
  • J. Gross et al.

    Dynamic imaging of coherent sources: studying neural interactions in the human brain

    Proc. Natl. Acad. Sci. U. S. A.

    (2001)
  • S. Haegens et al.

    Top-down controlled alpha band activity in somatosensory areas determines behavioural performance in a discrimination task

    J. Neurosci.

    (2011)
  • Cited by (25)

    • Alpha power during task performance predicts individual language comprehension

      2022, NeuroImage
      Citation Excerpt :

      After artifact rejection, the median value of number of valid trials was 34, ranging from a minimum of 6 to a maximum of 35. The characteristics of the alpha peak (e.g., frequency and power) are specific for each individual (Furman et al., 2018; Grabot and Kayser, 2020; Gulbinaite et al., 2017; Horschig et al., 2014; Katyal et al., 2019; Migliorati et al., 2020; Minami et al., 2020; Sadaghiani and Kleinschmidt, 2016; Smit et al., 2006). Hence, the somewhat non-univocal picture regarding the relationship between individual alpha power dynamics and task performance might also be rooted in the insufficient capture of the individual oscillations by using the classical broad frequency band (about 8–12 Hz).

    • Abnormal alpha modulation in response to human eye gaze predicts inattention severity in children with ADHD

      2019, Developmental Cognitive Neuroscience
      Citation Excerpt :

      Previous studies have shown that alpha synchronization is closely related to behavioral performance in visual attention tasks (Romei et al., 2010; Handel et al., 2011). For instance, anticipatory alpha lateralization could predict the performance of the experimental switch (Horschig et al., 2014). As problems in sustaining directed attention is one of the most marked clinical features in ADHD patients, posterior alpha modulation is an important aspect in ADHD studies.

    • Real-time MEG neurofeedback training of posterior alpha activity modulates subsequent visual detection performance

      2015, NeuroImage
      Citation Excerpt :

      During covert attention, concurrent increased alpha power in the ipsilateral hemisphere and decreased alpha power in the contralateral hemisphere with respect to the attended direction have been found (Kelly et al., 2006; Rihs et al., 2007; van Gerven and Jensen, 2009; Worden et al., 2000; Yamagishi et al., 2003). As hypothesized, the strength of the hemispheric alpha lateralization correlates with participants' performance, in terms of both reaction times and accuracy (Horschig et al., 2014a; Kelly et al., 2009; Thut et al., 2006). This correlation between alpha lateralization and perception implies that perceptual sensitivity might change if alpha lateralization can be increased by training covert visual spatial attention.

    View all citing articles on Scopus
    View full text