Escitalopram enhances synchrony of brain responses during emotional narratives in patients with major depressive disorder

One-week treatment with escitalopram decreases amygdala responses to fearful facial expressions in depressed patients, but it remains unknown whether it also modulates processing of complex and freely processed emotional stimuli resembling daily life emotional situations. Inter-subject correlation (ISC) offers a means to track brain activity during complex, dynamic stimuli in a model-free manner. Twenty-nine treatment-seeking patients with major depressive disorder were randomized in a double-blind study design to receive either escitalopram or placebo for one week, after which functional magnetic resonance imaging (fMRI) was performed. During fMRI the participants listened to spoken emotional narratives. Level of ISC between the escitalopram and the placebo group was compared across all the narratives and separately for the episodes with positive and negative valence. Across all the narratives, the escitalopram group had higher ISC in the default mode network of the brain as well as in the fronto-temporal narrative processing regions, whereas lower ISC was seen in the middle temporal cortex, hippocampus and occipital cortex. Escitalopram increased ISC during positive parts of the narratives in the precuneus, medial prefrontal cortex, anterior cingulate and fronto-insular cortex, whereas there was no significant synchronization in brain responses to positive vs negative events in the placebo group. Increased ISC may imply improved emotional synchronization with others, particularly during observation of positive events. Further studies are needed to test whether this contributes to the later therapeutic effect of escitalopram.Peer reviewe

Effects of spatial smoothing on functional brain networks

Graph-theoretical methods have rapidly become a standard tool in studies of the structure and function of the human brain. Whereas the structural connectome can be fairly straightforwardly mapped onto a complex network, there are more degrees of freedom in constructing networks that represent functional connections between brain areas. For functional magnetic resonance imaging (fMRI) data, such networks are typically built by aggregating the blood-oxygen-level dependent signal time series of voxels into larger entities (such as Regions of Interest in some brain atlas) and determining their connection strengths from some measure of time-series correlations. Although it is evident that the outcome must be affected by how the voxel-level time series are treated at the preprocessing stage, there is a lack of systematic studies of the effects of preprocessing on network structure. Here, we focus on the effects of spatial  smoothing, a standard preprocessing method for fMRI. We apply various levels of spatial smoothing to resting-state fMRI data and measure the changes induced in functional networks. We show that the level of spatial smoothing clearly affects the degrees and other centrality measures of functional network nodes; these changes are non-uniform, systematic, and depend on the geometry of the brain. The composition of the largest connected network component is also affected in a way that artificially increases the similarity of the networks of different subjects. Our conclusion is that wherever possible, spatial smoothing should be avoided when preprocessing fMRI data for network analysis.</p

Regions of Interest as nodes of dynamic functional brain networks

The properties of functional brain networks strongly depend on how their nodes are chosen. Commonly, nodes are defined by Regions of Interest (ROIs), predetermined groupings of fMRI measurement voxels. Earlier, we demonstrated that the functional homogeneity of ROIs, captured by their spatial consistency, varies widely across ROIs in commonly used brain atlases. Here, we ask how ROIs behave as nodes of dynamic brain networks. To this end, we use two measures: spatiotemporal consistency measures changes in spatial consistency across time and network turnover quantifies the changes in the local network structure around an ROI. We find that spatial consistency varies non-uniformly in space and time, which is reflected in the variation of spatiotemporal consistency across ROIs. Furthermore, we see time-dependent changes in the network neighborhoods of the ROIs, reflected in high network turnover. Network turnover is nonuniformly distributed across ROIs: ROIs with high spatiotemporal consistency have low network turnover. Finally, we reveal that there is rich voxel-level correlation structure inside ROIs. Because the internal structure and the connectivity of ROIs vary in time, the common approach of using static node definitions may be surprisingly inaccurate. Therefore, network neuroscience would greatly benefit from node definition strategies tailored for dynamical networks

Inferior parietal lobule and early visual areas support elicitation of individualized meanings during narrative listening

Introduction: When listening to a narrative, the verbal expressions translate into meanings and flow of mental imagery. However, the same narrative can be heard quite differently based on differences in listeners' previous experiences and knowledge. We capitalized on such differences to disclose brain regions that support transformation of narrative into individualized propositional meanings and associated mental imagery by analyzing brain activity associated with behaviorally assessed individual meanings elicited by a narrative. Methods: Sixteen right-handed female subjects were instructed to list words that best described what had come to their minds while listening to an eight-minute narrative during functional magnetic resonance imaging (fMRI). The fMRI data were analyzed by calculating voxel-wise intersubject correlation (ISC) values. We used latent semantic analysis (LSA) enhanced with Wordnet knowledge to measure semantic similarity of the produced words between subjects. Finally, we predicted the ISC with the semantic similarity using representational similarity analysis. Results: We found that semantic similarity in these word listings between subjects, estimated using LSA combined with WordNet knowledge, predicting similarities in brain hemodynamic activity. Subject pairs whose individual semantics were similar also exhibited similar brain activity in the bilateral supramarginal and angular gyrus of the inferior parietal lobe, and in the occipital pole. Conclusions: Our results demonstrate, using a novel method to measure interindividual differences in semantics, brain mechanisms giving rise to semantics and associated imagery during narrative listening. During listening to a captivating narrative, the inferior parietal lobe and early visual cortical areas seem, thus, to support elicitation of individual meanings and flow of mental imagery.Peer reviewe

Lipreading a naturalistic narrative in a female population : Neural characteristics shared with listening and reading

Publisher Copyright: © 2022 The Authors. Brain and Behavior published by Wiley Periodicals LLC.Introduction: Few of us are skilled lipreaders while most struggle with the task. Neural substrates that enable comprehension of connected natural speech via lipreading are not yet well understood. Methods: We used a data-driven approach to identify brain areas underlying the lipreading of an 8-min narrative with participants whose lipreading skills varied extensively (range 6–100%, mean = 50.7%). The participants also listened to and read the same narrative. The similarity between individual participants’ brain activity during the whole narrative, within and between conditions, was estimated by a voxel-wise comparison of the Blood Oxygenation Level Dependent (BOLD) signal time courses. Results: Inter-subject correlation (ISC) of the time courses revealed that lipreading, listening to, and reading the narrative were largely supported by the same brain areas in the temporal, parietal and frontal cortices, precuneus, and cerebellum. Additionally, listening to and reading connected naturalistic speech particularly activated higher-level linguistic processing in the parietal and frontal cortices more consistently than lipreading, probably paralleling the limited understanding obtained via lip-reading. Importantly, higher lipreading test score and subjective estimate of comprehension of the lipread narrative was associated with activity in the superior and middle temporal cortex. Conclusions: Our new data illustrates that findings from prior studies using well-controlled repetitive speech stimuli and stimulus-driven data analyses are also valid for naturalistic connected speech. Our results might suggest an efficient use of brain areas dealing with phonological processing in skilled lipreaders.Peer reviewe

Classification of emotion categories based on functional connectivity patterns of the human brain

Neurophysiological and psychological models posit that emotions depend on connections across wide-spread corticolimbic circuits. While previous studies using pattern recognition on neuroimaging data have shown differences between various discrete emotions in brain activity patterns, less is known about the differences in functional connectivity. Thus, we employed multivariate pattern analysis on functional magnetic resonance imaging data (i) to develop a pipeline for applying pattern recognition in functional connectivity data, and (ii) to test whether connectivity patterns differ across emotion categories. Six emotions (anger, fear, disgust, happiness, sadness, and surprise) and a neutral state were induced in 16 participants using one-minute-long emotional narratives with natural prosody while brain activity was measured with functional magnetic resonance imaging (fMRI). We computed emotion-wise connectivity matrices both for whole-brain connections and for 10 previously defined functionally connected brain subnetworks and trained an across-participant classifier to categorize the emotional states based on whole-brain data and for each subnetwork separately. The whole-brain classifier performed above chance level with all emotions except sadness, suggesting that different emotions are characterized by differences in large-scale connectivity patterns. When focusing on the connectivity within the 10 subnetworks, classification was successful within the default mode system and for all emotions. We thus show preliminary evidence for consistently different sustained functional connectivity patterns for instances of emotion categories particularly within the default mode system

Contextual knowledge provided by a movie biases implicit perception of the protagonist

We are constantly categorizing other people as belonging to our in-group (one of us') or out-group (one of them'). Such grouping occurs fast and automatically and can be based on others' visible characteristics such as skin color or clothing style. Here we studied neural underpinnings of implicit social grouping not often visible on the face, male sexual orientation. A total of 14 homosexuals and 15 heterosexual males were scanned in functional magnetic resonance imaging while watching a movie about a homosexual man, whose face was also presented subliminally before (subjects did not know about the character's sexual orientation) and after the movie. We discovered significantly stronger activation to the man's face after seeing the movie in homosexual but not heterosexual subjects in medial prefrontal cortex, frontal pole, anterior cingulate cortex, right temporal parietal junction and bilateral superior frontal gyrus. In previous research, these brain areas have been connected to social perception, self-referential thinking, empathy, theory of mind and in-group perception. In line with previous studies showing biased perception of in-/out-group faces to be context dependent, our novel approach further demonstrates how complex contextual knowledge gained under naturalistic viewing can bias implicit social perception.Peer reviewe