Oscillatory coupling between sensory and frontal control areas. Is it relevant for behaviour?

Selective attention is one of the cognitive abilities that allows primates to be goal-directed in an environment that is cluttered with both task-relevant stimuli and distracters. One of the most robust findings in systems neuroscience is the attentional modulation of neural oscillations over primary sensory areas. This modulation pertains to the alpha band (8-14 Hz) oscillations over posterior (occipito-parietal) areas and the alpha- and beta band (15-25 Hz) oscillations over sensorimotor areas. The attentional modulation of these oscillations is typically observed in tasks that manipulate spatial attention (mostly, attend-left versus attend-right). Specifically, this modulation involves that the amplitude of these oscillations over some cortical area is smaller when attention is deployed to the corresponding part of the sensory input space (e.g., left visual field for the right visual cortex, or the right side of the body for the left somatosensory cortex) as compared to when attention is deployed to another part of the sensory input space (i.c., the right visual field and the left side of the body). This attentional modulation can be due to two factors: (1) a decrease in the amplitude over the attended cortical areas, and/or (2) an increase in the amplitude over the non-attended cortical areas. Especially the first factor has received strong empirical support (e.g., van Ede et al, 2013).

These observations have lead to the view that low amplitude neuronal oscillations allow the sensory input to be transferred to their downstream targets whereas high amplitude neural oscillations block the sensory input. The question now is, via which mechanism this gating of sensory input is controlled. The dominant view here is that frontal cortical areas are responsible for this, and this view is consistent with the fact that fMRI studies of attentional control show a robust involvement of these frontal cortical areas. Compared to fMRI studies, there is only limited evidence from electrophysiological studies showing the involvement of frontal cortical areas in the modulation of neural oscillations over sensory input areas. Two recent magnetoencephalography studies are exceptions to this rule (Baldauf & Desimone, 2014; Sacchet et al, 2015), and both found evidence for oscillatory coupling between the right inferior frontal cortex (rIFG) and different sensory areas (S1 in Sacchet et al, 2015; fusiform face area and parahippocampal place area in Baldauf & Desimone, 2014).

As yet, it has not been shown that oscillatory coupling with frontal areas is also behaviourally relevant. Specifically, it still has to be shown that the strength of this coupling predicts behaviour, and the objective of this project is to demonstrate this. This project requires requires data that are appropriate for this purpose, as well as an analysis methods with which the between-area coupling can be quantified. With respect the former, we will analyse data from two experiments in which there was a substantial variability across trials in behavioural performance, as this is a requirement for a regression on neural parameters to make sense. The data of the first experiment have been used in a publication that addressed a different question (regressing behavioural performance on oscillatory amplitude, see van Ede et al, 2012), and the data of the second experiment are novel (see The function of neuronal oscillations over sensory cortices; collecting evidence from a combined behavioural-electrophysiological study. With respect to the required analysis methods, we will use a novel data analysis method that improves on existing methods, such as ones used by Sacchet et al (2015) and Baldauf & Desimone (2014). More specifically, we will use a source reconstruction method that is capable of (1) estimating the frequency content of the oscillations involved in the coupling, (2) separating the target oscillation from other signal components in the same frequency band, and (3) imposing biophysically plausible spatial continuity constraints. All of these aspects drastically improve performance.

This project will be supervised by Eric Maris and Luca Ambrogioni.