Matthias Moosmann

Rolandic alpha and beta EEG rhythms' strengths are inversely related to fMRI-BOLD signal in primary somatosensory and motor cortex

Similar to the posterior alpha rhythm, pericentral (Rolandic) EEG rhythms in the alpha and beta frequency range are referred to as “idle rhythms” indicating a “resting state” of the respective system. The precise function of these rhythms is not clear. We used simultaneous EEG‐fMRI during a bimanual motor task to localize brain areas involved in Rolandic alpha and beta EEG rhythms. The identification of these rhythms in the MR environment was achieved by a blind source separation algorithm. Rhythm “strength”, i.e. spectral power determined by wavelet analysis, inversely correlated most strongly with the fMRI‐BOLD signal in the postcentral cortex for the Rolandic alpha (mu) rhythm and in the precentral cortex for the Rolandic beta rhythm. FMRI correlates of Rolandic alpha and beta rhythms were distinct from those associated with the posterior “classical” alpha rhythm, which correlated inversely with the BOLD signal in the occipital cortex. An inverse correlation with the BOLD signal in the respective sensory area seems to be a general feature of “idle rhythms”. Hum Brain Mapp 2009.

Single-trial coupling of EEG and fMRI reveals the involvement of early anterior cingulate cortex activation in effortful decision making.

While the precise role of the anterior cingulate cortex (ACC) is still being discussed, it has been suggested that ACC activity might reflect the amount of mental effort associated with cognitive processing. So far, not much is known about the temporal dynamics of ACC activity in effort-related decision making or auditory attention, because fMRI is limited concerning its temporal resolution and electroencephalography (EEG) is limited concerning its spatial resolution. Single-trial coupling of EEG and fMRI can be used to predict the BOLD signal specifically related to amplitude variations of electrophysiological components. The striking feature of single-trial coupling is its ability to separate different aspects of the BOLD signal according to their specific relationship to a distinct neural process. In the present study we investigated 10 healthy subjects with a forced choice reaction task under both low and high effort conditions and a control condition (passive listening) using simultaneous EEG and fMRI. We detected a significant effect of mental effort only for the N1 potential, but not for the P300 potential. In the fMRI analysis, ACC activation was present only in the high effort condition. We used single-trial coupling of EEG and fMRI in order to separate information specific to N1-amplitude variations from the unrelated BOLD response. Under high effort conditions we were able to detect circumscribed BOLD activations specific to the N1 potential in the ACC (t=4.7) and the auditory cortex (t=6.1). Comparing the N1-specific BOLD activity of the high effort condition versus the control condition we found only activation of the ACC (random effects analysis, corrected for multiple comparisons, t=4.4). These findings suggest a role of early ACC activation in effort-related decision making and provide a direct link between the N1 component and its corresponding BOLD signal.

Identification of attention and cognitive control networks in a parametric auditory fMRI study.

In the competition for limited processing resources, top-down attention and cognitive control processes are needed to separate relevant from irrelevant sensory information and to interact with the environment in a meaningful way. The demands for the recruitment of top-down control processes depend on the relative salience of the competing stimuli. In the present event-related functional magnetic resonance imaging (fMRI) study we investigated the dynamics of neuronal networks during varying degrees of top-down control demands. We tested 20 participants with a dichotic auditory discrimination task in which the relative perceptual salience of two simultaneously presented syllables was parametrically varied by manipulating the inter-aural intensity differences (IIDs) and instructing the subjects to selectively attend to either the louder or weaker of the two stimuli. A significant interaction of IID manipulation and attentional instruction was detected bilaterally in the inferior parietal lobe and pre-supplementary motor area, and in the precentral gyrus, anterior cingulate cortex, and inferior frontal gyrus of the right hemisphere. The post hoc analysis of the interaction pattern allowed for an assignment of these regions to either of two sets of regions which can be interpreted to constitute two different brain networks: a fronto-parietal attention control network, involved in the integration of saliency-based and instruction-based processing preferences, and a medial-lateral frontal cognitive control network, involved in the processing of the conflicts arising in the attempt to follow the attentional instruction in face of the varying inter-aural stimulus salience.

Realignment parameter-informed artefact correction for simultaneous EEG–fMRI recordings ☆

In this work we introduce a new algorithm to correct the imaging artefacts in the EEG signal measured during fMRI acquisition. The correction techniques proposed so far cannot optimally represent transitions, i.e. when abrupt changes of the artefact properties due to head movements occur. The algorithm developed here takes the head movement parameters from the fMRI signal into account to calculate adequate EEG artefact templates and subsequently correct the distorted EEG data. The data reported in this work demonstrate that the realignment parameter-informed algorithm outperforms the commonly used moving average algorithm if head movements occur. The superiority is reflected by comparing the residual variance after artefact correction with either method. The residual variance is lower around head-movements that exceed head deflections of about 1 mm when applying the realignment parameter-informed algorithm. Additionally, the signal to noise ratio of a surrogate event-related potential (ERP) increased by 10-40% for head displacements larger than 1 mm. The algorithm developed here is particularly suited for studies where head movements of the subject cannot be prevented as in studies with patients, children, or during sleep. Furthermore, the enhanced signal to noise ratio of a single trial ERP indicates the power of the presented algorithm for single trial ERP-fMRI studies in which EEG signal quality is a critical factor.

Top-down and bottom-up interaction: manipulating the dichotic listening ear advantage.

The aim of the study was to investigate interactions between top-down and bottom-up information processing in the auditory domain. For this purpose, thirty-five right-handed participants with normal hearing acuity were tested with consonant-vowel dichotic stimulus pairs. Bottom-up stimulus characteristics were manipulated by gradually varying interaural intensity difference from -21 dB in favor of the left ear to +21 dB in favor of the right ear (including a no difference baseline condition). Top-down manipulation consisted of three conditions with different attention instructions: one free report condition, and each one condition requiring the participants to focus their attention on the right ear and on the left ear, respectively. The results showed a significant interaction of bottom-up and top-down manipulations with respect to the modulation of the ear advantage. Post-hoc analysis showed that the effect of directing attention was reduced when the intensity difference favored the to-be-attended ear. Thus, bottom-up intensity and top-down attention manipulations should not be regarded as independent but rather interacting factors when it comes to the manipulation of the ear advantage in a dichotic listening situation.

The effects of background noise on dichotic listening to consonant-vowel syllables: An fMRI study

The present fMRI study attempts to identify brain areas that may underlie the effect of different background noises on functional brain asymmetry in a dichotic listening task. Previous studies have shown that the prominent right ear advantage in dichotic listening to consonant-vowel syllables is affected by background noise. To explore the underlying neuronal processes, haemodynamic brain responses using fMRI were recorded while participants performed the dichotic listening task in two different noisy backgrounds (conversational “babble” and traffic noise). The behavioural results showed a reduction of the right ear advantage in the background noise conditions, especially in the traffic noise condition. The behavioural results are discussed in terms of alertness-attentional mechanisms. The effects of background noise on brain activation involved significant activations in a speech-processing network. Specifically the changes in activations in the peri-Sylvian region of the superior temporal gyrus and in the temporo-parietal junction part in the left hemisphere, as well as in the superior temporal gyrus/sulcus area in the right hemisphere may mirror the effects of noise on behavioural performance. The effects of noise on brain activation are discussed with regard to pre-activation mechanisms.