You took the words right out of my mouth: Dual-fMRI reveals intra- and inter-personal neural processes supporting verbal interaction.

Verbal communication relies heavily upon mutual understanding, or common ground. Inferring the intentional states of our interaction partners is crucial in achieving this, and social neuroscience has begun elucidating the intra- and inter-personal neural processes supporting such inferences. Typically, however, neuroscientific paradigms lack the reciprocal to-and-fro characteristic of social communication, offering little insight into the way these processes operate online during real-world interaction. In the present study, we overcame this by developing a "hyperscanning" paradigm in which pairs of interactants could communicate verbally with one another in a joint-action task whilst both undergoing functional magnetic resonance imaging simultaneously. Successful performance on this task required both interlocutors to predict their partner's upcoming utterance in order to converge on the same word as each other over recursive exchanges, based only on one another's prior verbal expressions. By applying various levels of analysis to behavioural and neuroimaging data acquired from 20 dyads, three principal findings emerged: First, interlocutors converged frequently within the same semantic space, suggesting that mutual understanding had been established. Second, assessing the brain responses of each interlocutor as they planned their upcoming utterances on the basis of their co-player's previous word revealed the engagement of the temporo-parietal junctional (TPJ), precuneus and dorso-lateral pre-frontal cortex. Moreover, responses in the precuneus were modulated positively by the degree of semantic convergence achieved on each round. Second, effective connectivity among these regions indicates the crucial role of the right TPJ in this process, consistent with the Nexus model. Third, neural signals within certain nodes of this network became aligned between interacting interlocutors. We suggest this reflects an interpersonal neural process through which interactants infer and align to one another's intentional states whilst they establish a common ground.

What can be found in scalp EEG spectrum beyond common frequency bands. EEG-fMRI study.

OBJECTIVE: The scalp EEG spectrum is a frequently used marker of neural activity. Commonly, the preprocessing of EEG utilizes constraints, e.g. dealing with a predefined subset of electrodes or a predefined frequency band of interest. Such treatment of the EEG spectrum neglects the fact that particular neural processes may be reflected in several frequency bands and/or several electrodes concurrently, and can overlook the complexity of the structure of the EEG spectrum. APPROACH: We showed that the EEG spectrum structure can be described by parallel factor analysis (PARAFAC), a method which blindly uncovers the spatial-temporal-spectral patterns of EEG. We used an algorithm based on variational Bayesian statistics to reveal nine patterns from the EEG of 38 healthy subjects, acquired during a semantic decision task. The patterns reflected neural activity synchronized across theta, alpha, beta and gamma bands and spread over many electrodes, as well as various EEG artifacts. MAIN RESULTS: Specifically, one of the patterns showed significant correlation with the stimuli timing. The correlation was higher when compared to commonly used models of neural activity (power fluctuations in distinct frequency band averaged across a subset of electrodes) and we found significantly correlated hemodynamic fluctuations in simultaneously acquired fMRI data in regions known to be involved in speech processing. Further, we show that the pattern also occurs in EEG data which were acquired outside the MR machine. Two other patterns reflected brain rhythms linked to the attentional and basal ganglia large scale networks. The other patterns were related to various EEG artifacts. SIGNIFICANCE: These results show that PARAFAC blindly identifies neural activity in the EEG spectrum and that it naturally handles the correlations among frequency bands and electrodes. We conclude that PARAFAC seems to be a powerful tool for analysis of the EEG spectrum and might bring novel insight to the relationships between EEG activity and brain hemodynamics.

Sensitivity of PPI analysis to differences in noise reduction strategies.

BACKGROUND: In some fields of fMRI data analysis, using correct methods for dealing with noise is crucial for achieving meaningful results. This paper provides a quantitative assessment of the effects of different preprocessing and noise filtering strategies on psychophysiological interactions (PPI) methods for analyzing fMRI data where noise management has not yet been established. METHODS: Both real and simulated fMRI data were used to assess these effects. Four regions of interest (ROIs) were chosen for the PPI analysis on the basis of their engagement during two tasks. PPI analysis was performed for 32 different preprocessing and analysis settings, which included data filtering with RETROICOR or no such filtering; different filtering of the ROI "seed" signal with a nuisance data-driven time series; and the involvement of these data-driven time series in the subsequent PPI GLM analysis. The extent of the statistically significant results was quantified at the group level using simple descriptive statistics. Simulated data were generated to assess statistical improvement of different filtering strategies. RESULTS: We observed that different approaches for dealing with noise in PPI analysis yield differing results in real data. In simulated data, we found RETROICOR, seed signal filtering and the addition of data-driven covariates to the PPI design matrix significantly improves results. CONCLUSIONS: We recommend the use of RETROICOR, and data-driven filtering of the whole data, or alternatively, seed signal filtering with data-driven signals and the addition of data-driven covariates to the PPI design matrix.

Default mode network and extrastriate visual resting state network in patients with Parkinson's disease dementia.

AIMS: Using fMRI, we evaluated the default mode network (DMN) and the extrastriate visual resting state network (ESV-RSN) in 14 patients with Parkinson's disease dementia (PDD) as compared with 18 patients with Parkinson's disease (PD) without dementia and 18 healthy controls (HC). METHODS: We analyzed the seed-based functional connectivity of both resting state data and deactivations during a visual complex scene-encoding task. RESULTS: Using the posterior cingulate cortex/precuneus as a seed for the DMN analysis, we observed significant decreases of connectivity in the right inferior frontal gyrus in PDD as compared to PD and HC. Using the caudate nucleus as a seed for the ESV-RSN analysis, we found significant decreases of connectivity in the left and right inferior occipital gyrus in PDD as compared to HC. CONCLUSION: Differences in functional connectivity patterns between PDD and PD/HC were observed in areas known to be engaged in stimulus-driven reorienting of attention and in visual processing.

The default mode network integrity in patients with Parkinson's disease is levodopa equivalent dose-dependent.

Disturbances in the default mode network (DMN) have been described in many neurological and psychiatric disorders including Parkinson's disease (PD). The DMN is characterized by basal activity that increases during rest or passive visual fixation and decreases ("deactivates") during cognitive tasks. The network is believed to be involved in cognitive processes. We examined the DMN in PD patients on dopaminergic medication with normal cognitive performance compared to age- and gender-matched healthy controls (HC) using fMRI and three methodological procedures: independent component analysis of resting-state data, analysis of deactivation during a complex visual scene-encoding task, and seed-based functional connectivity analysis. In the PD group, we also studied the effect of dopaminergic medication on the DMN integrity. We did not find any difference between the PD and HC groups in the DMN, but using the daily levodopa equivalent dose as a covariate, we observed an enhanced functional connectivity of the DMN in the posterior cingulate cortex and decreased activation in the left parahippocampal gyrus during the cognitive task. We conclude that dopaminergic therapy has a specific effect on both the DMN integrity and task-related brain activations in cognitively unimpaired PD patients, and these effects seem to be dose-dependent.

Functional neuroanatomy of vocalization in patients with Parkinson's disease.

UNLABELLED: In Parkinson's disease (PD) both speech production and self-monitoring of voiced speech are altered. METHODS: In our previous study we used functional magnetic resonance imaging (fMRI) to examine which brain areas are involved in overt reading in nine female PD patients (mean age 66.0 ± 11.6 years) compared with eight age-matched healthy female controls (mean age 62.2 years ± 12.3). Here we performed the post-hoc seed-based functional connectivity analysis of our data to assess the functional connectivity between the periaqueductal gray matter (PAG; i.e. the core subcortical structure involved in human vocalization) and other brain regions in the same groups of PD patients and controls. RESULTS: In PD patients as compared with controls we observed increased connectivity between PAG and basal ganglia, posterior superior temporal gyrus, supramarginal and fusiform gyri and inferior parietal lobule on the right side. In the PD group, the connectivity strength in the right putamen and the right sypramarginal gyrus was correlated with variability of pitch while the connectivity strength in the right posterior superior temporal gyrus and in the right inferior parietal lobule was correlated with speech loudness. CONCLUSION: We observed functional reorganization in PD patients as compared with controls in both the motor basal ganglia-thalamo-cortical circuitry and cortical areas known to be engaged in-auditory and somatosensory feedback control of voiced speech. These changes were hemisphere-specific and might either reflect effects of dopaminergic treatment or at least partially successful compensatory mechanisms involved in early-stage PD.

An event-related fMRI study of self-paced alphabetically ordered writing of single letters.

The spatial location of activation for writing individual letters and for writing simple dots was studied using event-related functional MRI. Ten healthy right-handed subjects were scanned while performing two different protocols with self-paced repetitive movement. In the first protocol with self-paced dot writing, we observed significant activation in regions known to participate in motor control: contralateral to the movement in the primary sensorimotor and supramarginal cortices, the supplementary motor area (SMA) with the underlying cingulate, in the thalamus and, to a lesser extent, in the ipsilateral inferior parietal and occipital cortices. In the second protocol, we investigated an elemental writing feature--writing single letters. We observed statistically significant changes in the premotor, sensorimotor and supramarginal cortices, the SMA and the thalamus with left predominance, and in the bilateral premotor and inferior/superior parietal cortices. The parietal region that was active during the writing of single letters spanned the border between the parietal superior and inferior lobuli Brodmann area (BA 2, 40), deep in the intraparietal sulcus, with a surprising right-sided dominance. The direct comparison of the results of the two protocols was not significant with a confidence level of P<0.05 corrected for whole brain volume. Thus, the ROI approach was used, and we tried to find significant differences within the two predefined regions of interest (ROI) (BA 7, BA 37). The differences were found with a confidence level of P<0.05 corrected for the volume of these predicted areas. The ROI were located in the posterior parts of hemispheres, in the ventral and in the dorsal visual pathway. The right-sided posterior cortices may play a role in the elemental mechanisms of writing. It is possible that activation of this region is linked with the spatial dimension of the writing.

Reorganization of language-related neuronal networks in patients with left temporal lobe epilepsy - an fMRI study.

To investigate the inter- and intrahemispheric reorganization of the language cortex in left temporal lobe epilepsy (TLE) with left-sided hippocampal sclerosis. A functional magnetic resonance imaging was performed on 13 right-handed patients suffering from medically intractable left TLE, and in 13 sex- and age-matched healthy controls. The activation paradigm used was a silent word generation task. A language laterality index (LI) was calculated from the number of activated voxels in the right and left anterior two-thirds of the hemispheres. Significant differences between the patients and the controls were observed in the activation of the left-sided inferior frontal gyrus. Less consistent findings in this region, as well as the relative protection of Broca's area from the activation, were revealed in the patients. In addition, different patterns of activation were proven in the cerebellum and other cortical as well as subcortical brain structures within both hemispheres. Significant differences were also found in the values of the language LIs between the investigated groups: these values suggested a more bihemispheric language representation in the patients. As anticipated, lateralization of the language functions in the epileptics significantly decreased in connection with an earlier age of initial insult. Our results support the hypothesis of a significant intra- and interhemispheric functional reorganization of language-related neuronal networks in left TLE.