Methylphenidate does not affect convergent and divergent creative processes in healthy adults Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Matthijs Baas, Nathalie Boot, Simon van Gaal, Carsten K.W. de Dreu, Roshan Cools Abstract An increasing number of healthy people use methylphenidate, a psychostimulant that increases dopamine and noradrenaline transmission in the brain, to help them focus over extended periods of time. While methylphenidate has been shown to facilitate some cognitive functions, like focus and distractor-resistance, the same drug might also contribute to cognitive impairment, for example, in creativity. In this study, we investigated whether acute administration of a low oral dose (20 mg) of methylphenidate affected convergent and divergent creative processes in a sample of young healthy participants. Also, we explored whether such effects depended on individual differences in ADHD symptoms and working memory capacity. Contrary to our expectations, methylphenidate did not affect participants’ creative performance on any of the tasks. Also, methylphenidate effects did not depend on individual differences in trait hyperactivity–impulsivity or baseline working memory capacity. Thus, although the effects of methylphenidate on creativity might be underestimated in our study due to several methodological factors, our findings do not suggest that methylphenidate impairs people’s ability to be creative.

Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Claudio Toro-Serey, Sean M. Tobyne, Joseph T. McGuire Abstract Regions of human medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) are part of the default network (DN), and additionally are implicated in diverse cognitive functions ranging from autobiographical memory to subjective valuation. Our ability to interpret the apparent co-localization of task-related effects with DN-regions is constrained by a limited understanding of the individual-level heterogeneity in mPFC/PCC functional organization. Here we used cortical surface-based meta-analysis to identify a parcel in human PCC that was more strongly associated with the DN than with valuation effects. We then used resting-state fMRI data and a data-driven network analysis algorithm, spectral partitioning, to partition mPFC and PCC into “DN” and “non-DN” subdivisions in individual participants (n = 100 from the Human Connectome Project). The spectral partitioning algorithm identified individual-level cortical subdivisions that varied markedly across individuals, especially in mPFC, and were reliable across test/retest datasets. Our results point toward new strategies for assessing whether distinct cognitive functions engage common or distinct mPFC subregions at the individual level. Graphical abstract

Decomposing alpha and 1/f brain activities reveals their differential associations with cognitive processing speed Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Guang Ouyang, Andrea Hildebrandt, Florian Schmitz, Christoph S. Herrmann Abstract Research in cognitive neuroscience has extensively demonstrated that the temporal dynamics of brain activity are associated with cognitive functioning. The temporal dynamics mainly include oscillatory and 1/f noise-like, non-oscillatory brain activities that coexist in many forms of brain activity and confound each other’s variability. As such, observed functional associations of narrowband oscillations might have been confounded with the broadband 1/f component. Here, we investigated the relationship between resting-state EEG activity and the efficiency of cognitive functioning in N = 180 individuals. We show that 1/f brain activity plays an essential role in accounting for between-person variability in cognitive speed – a relationship that can be mistaken as originating from brain oscillations using conventional power spectrum analysis. At first glance, the power of alpha oscillations appeared to be predictive of cognitive speed. However, when dissociating pure alpha oscillations from 1/f brain activity, only the 1/f predicted cognitive speed, whereas the predictive power of alpha vanished. With this highly powered study, we disambiguate the functional relevance of the 1/f power law pattern in resting state neural activities and substantiate the necessity of isolating the 1/f component from oscillatory activities when studying the functional relevance of spontaneous brain activities.

Theta and alpha oscillations as signatures of internal and external attention to delayed intentions: A magnetoencephalography (MEG) study Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Giorgia Cona, Francesco Chiossi, Silvia Di Tomasso, Giovanni Pellegrino, Francesco Piccione, Patrizia Bisiacchi, Giorgio Arcara Abstract Background Remembering to execute delayed intentions (i.e., prospective memory, PM) entails the allocation of internal and external attention. These processes are crucial for rehearsing PM intentions in memory and for monitoring the presence of the PM cue in the environment, respectively. Aim The study took advantage of the excellent spatial and temporal resolution of magnetoencephalography (MEG) to delineate the neural mechanisms of the memory and monitoring processes underlying PM. Method The spatio-temporal dynamic of theta and alpha oscillations were explored in 21 participants in two PM tasks compared to a baseline condition (i.e., a lexical decision task with no PM instruction). The PM tasks varied for the load of internally-directed attention (Retrospective-load task) vs externally-directed attention (Monitoring-load task). Results Increase in theta activity was observed in the Retrospective-load task, and was particularly expressed in the regions of the Default Mode Network, such as in medial temporal regions, precuneus, posterior cingulate cortex and medial prefrontal cortex. Alpha decrease was the most relevant feature of the Monitoring-load task, and it was expressed over bilateral occipital, occipito-parietal and fronto-temporal regions, as well as over left dorsal fronto-parietal regions. Conclusions Theta and alpha oscillations are strictly associated with the direction of attention during the PM tasks. In particular, theta increase is linked to internal attention necessary for maintaining the intention active in working memory, whereas alpha decrease supports the external attention for detecting the PM cue in the environment.

Model-based physiological noise removal in fast fMRI Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Uday Agrawal, Emery N. Brown, Laura D. Lewis Abstract Recent improvements in the speed and sensitivity of fMRI acquisition techniques suggest that fast fMRI can be used to detect and precisely localize sub-second neural dynamics. This enhanced temporal resolution has enormous potential for neuroscientists. However, physiological noise poses a major challenge for the analysis of fast fMRI data. Physiological noise scales with sensitivity, and its autocorrelation structure is altered in rapidly sampled data, suggesting that new approaches are needed for physiological noise removal in fast fMRI. Existing strategies either rely on external physiological recordings, which can be noisy or difficult to collect, or employ data-driven approaches which make assumptions that may not hold true in fast fMRI. We created a statistical model of harmonic regression with autoregressive noise (HRAN) to estimate and remove cardiac and respiratory noise from the fMRI signal directly. This technique exploits the fact that cardiac and respiratory noise signals are fully sampled (rather than aliasing) when imaging at fast rates, allowing us to track and model physiology over time without requiring external physiological measurements. We then created a joint model of neural hemodynamics, and physiological and autocorrelated noise to more accurately remove noise. We first verified that HRAN accurately estimates cardiac and respiratory dynamics and that our model demonstrates goodness-of-fit in fast fMRI data. In task-driven data, we then demonstrated that HRAN is able to remove physiological noise while leaving the neural signal intact, thereby increasing detection of task-driven voxels. Finally, we established that in both simulations and fast fMRI data HRAN is able to improve statistical inferences as compared with gold-standard physiological noise removal techniques. In conclusion, we created a tool that harnesses the novel information in fast fMRI to remove physiological noise, enabling broader use of the technology to study human brain function.

Combining fMRI during resting state and an attention bias task in children Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Anita Harrewijn, Rany Abend, Julia Linke, Melissa A. Brotman, Nathan A. Fox, Ellen Leibenluft, Anderson M. Winkler, Daniel S. Pine Abstract Neuroimaging studies typically focus on either resting state or task-based fMRI data. Prior research has shown that similarity in functional connectivity between rest and cognitive tasks, interpreted as reconfiguration efficiency, is related to task performance and IQ. Here, we extend this approach from adults to children, and from cognitive tasks to a threat-based attention task. The goal of the current study was to examine whether similarity in functional connectivity during rest and an attention bias task relates to threat bias, IQ, anxiety symptoms, and social reticence. fMRI was measured during resting state and during the dot-probe task in 41 children (M = 13.44, SD = 0.70). Functional connectivity during rest and dot-probe was positively correlated, suggesting that functional hierarchies in the brain are stable. Similarity in functional connectivity between rest and the dot-probe task only related to threat bias (puncorr < .03). This effect did not survive correction for multiple testing. Overall, children who allocate more attention towards threat also may possess greater reconfiguration efficiency in switching from intrinsic to threat-related attention states. Finally, functional connectivity correlated negatively across the two conditions of the dot-probe task. Opposing patterns of modulation of functional connectivity by threat-congruent and threat-incongruent trials may reflect task-specific network changes during two different attentional processes.

Monotonic Gaussian Process for spatio-temporal disease progression modeling in brain imaging data Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Clément Abi Nader, Nicholas Ayache, Philippe Robert, Marco Lorenzi, Alzheimer’s Disease Neuroimaging Initiative Abstract We introduce a probabilistic generative model for disentangling spatio-temporal disease trajectories from collections of high-dimensional brain images. The model is based on spatio-temporal matrix factorization, where inference on the sources is constrained by anatomically plausible statistical priors. To model realistic trajectories, the temporal sources are defined as monotonic and time-reparameterized Gaussian Processes. To account for the non-stationarity of brain images, we model the spatial sources as sparse codes convolved at multiple scales. The method was tested on synthetic data favourably comparing with standard blind source separation approaches. The application on large-scale imaging data from a clinical study allows to disentangle differential temporal progression patterns mapping brain regions key to neurodegeneration, while revealing a disease-specific time scale associated to the clinical diagnosis.

Fear generalization of implicit conditioned facial features – Behavioral and magnetoencephalographic correlates Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Kati Roesmann, Nele Wiens, Constantin Winker, Maimu Alissa Rehbein, Ida Wessing, Markus Junghoefer Abstract Acquired fear responses often generalize from conditioned stimuli (CS) towards perceptually similar, but harmless generalization stimuli (GS). Knowledge on similarities between CS and GS may be explicit or implicit. Employing behavioral measures and whole-head magnetoencephalography, we here investigated the neurocognitive mechanisms underpinning implicit fear generalization. Twenty-nine participants underwent a classical conditioning procedure in which 32 different faces were either paired with an aversive scream (16 CS+) or remained unpaired (16 CS-). CS+ and CS- faces systematically differed from each other regarding their ratio of eye distance and mouth width. High versus low values on this “threat-related feature (TF)” implicitly predicted the presence or absence of the aversive scream. In pre- and post-conditioning phases, all CS and 32 novel GS faces were presented. 16 GS+ ​faces shared the TF of the 16 CS+ ​faces, while 16 ​GS- faces shared the TF of the 16 CS- faces. Behavioral tests confirmed that participants were fully unaware of TF-US contingencies. CS+ ​compared to CS- faces revealed higher unpleasantness, arousal and US-expectancy ratings. A generalization of these behavioral fear responses to GS+ ​compared to GS- faces was observed by trend only. Source-estimations of event-related fields showed stronger neural responses to both CS+ and GS+ ​compared to CS- and GS- in anterior temporal (<100 ​ms) and temporo-occipital (<150 ​ms; 553–587 ​ms) ventral brain regions. Reverse effects were found in dorsal frontal areas (<100 ​ms; 173–203 ​ms; 257–290 ​ms). Neural data also revealed selectively enhanced responses to CS+ ​but not GS+ ​stimuli in occipital regions (110–167 ​ms; 330–413 ​ms), indicating perceptual discrimination. Our data suggest that the prioritized perceptual analysis of threat-associated conditioned faces in ventral networks rapidly generalizes to novel faces sharing threat-related features. This generalization process occurs in absence of contingency awareness and may thus contribute to implicit attentional biases. The coexisting perceptual discrimination suggests that fear generalization is not a mere consequence of insufficient stimulus discrimination but rather an active, integrative process.

Mapping critical cortical hubs and white matter pathways by direct electrical stimulation: an original functional atlas of the human brain Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Silvio Sarubbo, Matthew Tate, Alessandro De Benedictis, Stefano Merler, Sylvie Moritz-Gasser, Guillaume Herbet, Hugues Duffau Abstract Objective The structural and functional organization of brain networks subserving basic daily activities (i.e. language, visuo-spatial cognition, movement, semantics, etc.) are not completely understood to date. Here, we report the first probabilistic cortical and subcortical atlas of critical structures mediating human brain functions based on direct electrical stimulation (DES), a well-validated tool for the exploration of cerebral processing and for performing safe surgical interventions in eloquent areas. Methods We collected 1162 cortical and 659 subcortical DES responses during testing of 16 functional domains in 256 patients undergoing awake surgery. Spatial coordinates for each functional response were calculated, and probability distributions for the entire patient cohort were mapped onto a standardized three-dimensional brain template using a multinomial statistical analysis. In addition, matching analyses were performed against prior established anatomy-based cortical and white matter (WM) atlases. Results The probabilistic maps for each functional domain were provided. The topographical analysis demonstrated a wide spatial distribution of cortical functional responses, while subcortical responses were more restricted, localizing to known WM pathways. These DES-derived data showed reliable matching with existing cortical and WM atlases as well as recent neuroimaging and neurophysiological data. Conclusions We present the first integrated and comprehensive cortical-subcortical atlas of structures essential for humans’ neural functions based on highly-specific DES mapping during real-time neuropsychological testing. This novel atlas can serve as a complementary tool for neuroscientists, along with data obtained from other modalities, to improve and refine our understanding of the functional anatomy of critical brain networks.

Inter-subject P300 variability relates to the efficiency of brain networks reconfigured from resting- to task-state: Evidence from a simultaneous event-related EEG-fMRI study Publication date: 15 January 2020 Source: NeuroImage, Volume 205 Author(s): Fali Li, Qin Tao, Wenjing Peng, Tao Zhang, Yajing Si, Yangsong Zhang, Chanlin Yi, Bharat Biswal, Dezhong Yao, Peng Xu Abstract The P300 event-related potential (ERP) varies across individuals, and exploring this variability deepens our knowledge of the event, and scope for its potential applications. Previous studies exploring the P300 have relied on either electroencephalography (EEG) or functional magnetic resonance imaging (fMRI). We applied simultaneous event-related EEG-fMRI to investigate how the network structure is updated from rest to the P300 task so as to guarantee information processing in the oddball task. We first identified 14 widely distributed regions of interest (ROIs) that were task-associated, including the inferior frontal gyrus and the middle frontal gyrus, etc. The task-activated network was found to closely relate to the concurrent P300 amplitude, and moreover, the individuals with optimized resting-state brain architectures experienced the pruning of network architecture, i.e. decreasing connectivity, when the brain switched from rest to P300 task. Our present simultaneous EEG-fMRI study explored the brain reconfigurations governing the variability in P300 across individuals, which provided the possibility to uncover new biomarkers to predict the potential for personalized control of brain-computer interfaces.