On the Physiological Modulation and Potential Mechanisms Underlying Parieto-Occipital Alpha Oscillations

Abstract

The parieto-occipital alpha (8-13 Hz) rhythm is by far the strongest spectral fingerprint in the human brain. Almost 90 years later, its physiological origin is still far from clear. In this Research Topic I review human pharmacological studies using electroencephalography (EEG) and magnetoencephalography (MEG) that investigated the physiological mechanisms behind posterior alpha. Based on results from classical and recent experimental studies, I find a wide spectrum of drugs that modulate parieto-occipital alpha power. Alpha frequency is rarely affected, but this might be due to the range of drug dosages employed. Animal and human pharmacological findings suggest that both GABA enhancers and NMDA blockers systematically decrease posterior alpha power. Surprisingly, most of the theoretical frameworks do not seem to embrace these empirical findings and the debate on the functional role of alpha oscillations has been polarized between the inhibition vs. active poles hypotheses. Here, I speculate that the functional role of alpha might depend on physiological excitation as much as on physiological inhibition. This is supported by animal and human pharmacological work showing that GABAergic, glutamatergic, cholinergic, and serotonergic receptors in the thalamus and the cortex play a key role in the regulation of alpha power and frequency. This myriad of physiological modulations fit with the view that the alpha rhythm is a complex rhythm with multiple sources supported by both thalamo-cortical and cortico-cortical loops. Finally, I briefly discuss how future research combining experimental measurements derived from theoretical predictions based of biophysically realistic computational models will be crucial to the reconciliation of these disparate findings.

Keywords: brain oscillations; cognitive processes; electroencephalography; magnetoencephalography; pharmacology.

Figure 1

Physiological modulations of parieto-occipital alpha oscillations. (a) Lorazepam (GABAergic enhancer) parametrically reduces both tonic and attentional alpha power modulations during the delay interval of a visuo-spatial working memory task. The figure shows the topographic distribution of alpha power and the time and frequency dynamics of ipsilateral and contralateral sensors of interest under Placebo (A) 0.5 mg (B) and (C) 1.5 mg of Lorazepam. (D,E) show the delay-specific interaction between drug dosage and sensors meaning that Lorazepam caused a strong reduction in the ipsilateral relative to the contralateral sensors. Reproduced from Lozano-Soldevilla et al. (2014) with the permission from Elsevier. (b) Relationship between posterior alpha frequency and EEG amplitude. The x-axis represents the alpha cycles preceding the single trial P1 evoked potential produced in a semantic-judgement task. The left y-axis represents the period of the alpha band (red) and the right y-axis represents the amplitude of the EEG measured at the time point of the positive alpha peak (blue). The EEG raw amplitude correlates positively with alpha frequency. Reproduced from Himmelstoss et al. (2015) with the permission from Frontiers S.A. (c) Physostigmine (cholinergic enhancer) increases the attentional alpha power modulations in parieto-occipital cortices relative to placebo during the cue interval of a visuo-spatial attention task. (A) Time and frequency representation of the left minus right attention contrast during the placebo session of significant parieto-occipital voxels (B). Physostigmine attention contrast and interaction are represented in (C,D) and (E,F), respectively. Reproduced from Bauer et al. (2012) with the permission from Elsevier. (d) LSD (serotonergic enhancer) reduces posterior alpha power during resting state conditions (A). The LSD-induced alpha power reduction correlates with increase of simple hallucination and ego-dissolution ratings (B). LSD produced a robust increase of posterior alpha peak frequency (C). Reproduced from Carhart-Harris et al. (2016) with the permission from Proceedings of the National Academy of Sciences of the United States of America.

Figure 2

Effect of common denominator when comparing normalized power differences. (A) Simulated alpha power dynamics of a hypothetical MEG sensor from left hemisphere in a visuo-spatial attention task. Red (blue) lines represent the alpha oscillations during attention to the right (left) conditions. The left column illustrated the alpha attentional power modulations during Placebo and the right column during an experimental session where a hypothetical Drug exclusively produces a tonic power reduction ànd leaves the attentional power modulation intact. The power differences between attention to the left (blue) vs. attention to the right conditions (red) is the same for Placebo and Drug. (B) Time-resolved alpha modulation index (AMI) for Placebo and Drug sessions. AMI is defined as the normalized power difference between attentional conditions: (attention to the left – attention to the right)./ (attention to the left + attention to the right). AMI is compared between treatments using different denominator (green vs. purple) or using the same, in this case Placebo (green vs. black). (C) Time-resolved power differences due to attentional (phasic) alpha power modulations (numerator) vs. total (tonic) alpha power (denominator) for each treatment separately. In this simulated example, it is clear that the Drug decreased the total or tonic alpha power (denominator) without interacting with attention (numerator). As the tonic power during Drug is lower relative to Placebo, having the same attentional modulation, the AMI is clearly enhanced using different denominator relative to common denominator (see B).

Figure 3

Minimizing head movements during MEG experiments. Measurement of the MEG chair inclination of the CTF275 system in two specific positions (A,B). The height of the chair in two different positions (C,D). Example of a sponge neck-collar (E).