Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients ...extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface—and are precisely equidistant—from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input.
Cortical connectivity conforms to a series of organizing principles that are common across species. Spatial proximity, similar cortical type, and similar connectional profile all constitute factors ...for determining the connectivity between cortical regions. We previously demonstrated another principle of connectivity that is closely related to the spatial layout of the cerebral cortex. Using functional connectivity from resting-state fMRI in the human cortex, we found that the further a region is located from primary cortex, the more distant are its functional connections with the other areas of the cortex. However, it remains unknown whether this relationship between cortical layout and connectivity extends to other primate species. Here, we investigated this relationship using both resting-state functional connectivity as well as gold-standard tract-tracing connectivity in the macaque monkey cortex. For both measures of connectivity, we found a gradient of connectivity distance extending between primary and frontoparietal regions. In the human cortex, the further a region is located from primary areas, the stronger its connections to distant portions of the cortex, with connectivity distance highest in frontal and parietal regions. The similarity between the human and macaque findings provides evidence for a phylogenetically conserved relationship between the spatial layout of cortical areas and connectivity.
Deception has always been a part of human communication as it helps to promote self-presentation. Although both men and women are equally prone to try to manage their appearance, their strategies, ...motivation and eagerness may be different. Here, we asked if lying could be influenced by gender on both the behavioral and neural levels. To test whether the hypothesized gender differences in brain activity related to deceptive responses were caused by differential socialization in men and women, we administered the Gender Identity Inventory probing the participants' subjective social sex role. In an fMRI session, participants were instructed either to lie or to tell the truth while answering a questionnaire focusing on general and personal information. Only for personal information, we found differences in neural responses during instructed deception in men and women. The women vs. men direct contrast revealed no significant differences in areas of activation, but men showed higher BOLD signal compared to women in the left middle frontal gyrus (MFG). Moreover, this effect remained unchanged when self-reported psychological gender was controlled for. Thus, our study showed that gender differences in the neural processes engaged during falsifying personal information might be independent from socialization.
The dataset enables exploration of higher-order cognitive faculties, self-generated mental experience, and personality features in relation to the intrinsic functional architecture of the brain. We ...provide multimodal magnetic resonance imaging (MRI) data and a broad set of state and trait phenotypic assessments: mind-wandering, personality traits, and cognitive abilities. Specifically, 194 healthy participants (between 20 and 75 years of age) filled out 31 questionnaires, performed 7 tasks, and reported 4 probes of in-scanner mind-wandering. The scanning session included four 15.5-min resting-state functional MRI runs using a multiband EPI sequence and a hig h-resolution structural scan using a 3D MP2RAGE sequence. This dataset constitutes one part of the MPI-Leipzig Mind-Brain-Body database.
Ciało migdałowate jest parzystą strukturą podkorową zlokalizowaną w płatach skroniowych mózgu. Struktura ta wzbudza zainteresowanie badaczy ze względu na jej związek z emocjami i procesami ...uczenia się. Badania z udziałem zwierząt sugerują, że grupy jąder znajdujące się w różnych częściach ciała migdałowatego są elementami odrębnych sieci neuronowych i mogą pełnić odmienne funkcje w procesach emocjonalnych i poznawczych. Część autorów dochodzi wręcz do wniosku, że ciało migdałowate zostało uznane za jedną strukturę wyłącznie z powodu bliskiego położenia grup jąder. Zweryfikowanie tej hipotezy w odniesieniu do ludzi jest bardzo trudne, ponieważ do niedawna wyodrębnienie części ciała migdałowatego w ludzkim mózgu było możliwe jedynie dzięki badaniom anatomicznym wykonywanym pośmiertnie. Dopiero w ostatnich latach, za pomocą technik rezonansu magnetycznego, podjęto próby określenia części ciała migdałowatego na podstawie strukturalnych i funkcjonalnych połączeń z innymi obszarami mózgu. Dotychczas przeprowadzono nieliczne badania dotyczące tego zagadnienia, jednak ich wyniki nie są spójne – ani pod względem liczby wyodrębnionych części, ani pod względem ich lokalizacji. Przyczyn otrzymywania niejednoznacznych wyników można upatrywać w stosowaniu różnych metod określania połączeń, w różnych parametrach akwizycji danych oraz w posługiwaniu się różnymi technikami analizy, przede wszystkim zaś w wykorzystywaniu różnych algorytmów grupujących. Przyszłe badania powinny zatem koncentrować się na opracowaniu jak najbardziej wiarygodnego sposobu wyróżniania części ciała migdałowatego, który pozwoliłby na jednoznaczne ich zidentyfikowanie. Tylko wtedy możliwe będzie pełne poznanie funkcjonalnej organizacji ciała migdałowatego u ludzi.
Fluid intelligence is a critical factor in learning and instruction. It also influences performance at school and in the workplace. There have been many attempts to directly and indirectly improve ...general fluid intelligence by training its underlying cognitive functions, such as working memory, cognitive control, or attention. The aim of the present study was to determine the extent to which school-age children's scores on intelligence tests could be improved by attention training. After training sessions, which consisted of four computerized cognitive tasks that practiced various aspects of attention, the children's scores on an attention test improved, with fewer false alarms and increased performance speed. This improvement partially persisted over an extended period of time. However, this effect was not associated with higher intelligence test scores. These results suggest that attention is possible to develop through short-term interventions but general intelligence is not. We interpret our findings in terms of the three-stratum theory of human intelligence. Key words: attention, intelligence, cognitive training
Human interaction often requires the precise yet flexible interpersonal coordination of rhythmic behavior, as in group music making. The present fMRI study investigates the functional brain networks ...that may facilitate such behavior by enabling temporal adaptation (error correction), prediction, and the monitoring and integration of information about ‘self’ and the external environment. Participants were required to synchronize finger taps with computer-controlled auditory sequences that were presented either at a globally steady tempo with local adaptations to the participants' tap timing (Virtual Partner task) or with gradual tempo accelerations and decelerations but without adaptation (Tempo Change task). Connectome-based predictive modelling was used to examine patterns of brain functional connectivity related to individual differences in behavioral performance and parameter estimates from the adaptation and anticipation model (ADAM) of sensorimotor synchronization for these two tasks under conditions of varying cognitive load. Results revealed distinct but overlapping brain networks associated with ADAM-derived estimates of temporal adaptation, anticipation, and the integration of self-controlled and externally controlled processes across task conditions. The partial overlap between ADAM networks suggests common hub regions that modulate functional connectivity within and between the brain's resting-state networks and additional sensory-motor regions and subcortical structures in a manner reflecting coordination skill. Such network reconfiguration might facilitate sensorimotor synchronization by enabling shifts in focus on internal and external information, and, in social contexts requiring interpersonal coordination, variations in the degree of simultaneous integration and segregation of these information sources in internal models that support self, other, and joint action planning and prediction.
•Brain functional connectivity reflects variation in rhythmic coordination skills•Connectome-based modelling reveals mutliple audio-motor synchronization networks•Resting-state and sensory-motor network reconfiguration supports temporal precision•Network overlap links predictive timing, error correction, and self-other processing
Autism is a developmental condition associated with altered functional connectivity. We propose to re-frame the functional connectivity alterations in terms of gradients that capture the functional ...hierarchy of cortical processing from sensory to default-mode network regions. We hypothesized that this hierarchy will be altered in ASD. To test that, we compared the scale of gradients in people with autism and healthy controls. The present results do not support our hypothesis. There are two alternative implications: either the processing hierarchies are preserved in autism or the scale of the gradients does not capture them. In the future we will attempt to settle which alternative is more likely.
2015 Brainhack Proceedings Craddock, R. Cameron; Bellec, Pierre; Margules, Daniel S. ...
Gigascience,
11/2016, Letnik:
5, Številka:
S1
Journal Article
Recenzirano
Odprti dostop
I1 Introduction to the 2015 Brainhack Proceedings
R. Cameron Craddock, Pierre Bellec, Daniel S. Margules, B. Nolan Nichols, Jörg P. Pfannmöller
A1 Distributed collaboration: the case for the ...enhancement of Brainspell’s interface
AmanPreet Badhwar, David Kennedy, Jean-Baptiste Poline, Roberto Toro
A2 Advancing open science through NiData
Ben Cipollini, Ariel Rokem
A3 Integrating the Brain Imaging Data Structure (BIDS) standard into C-PAC
Daniel Clark, Krzysztof J. Gorgolewski, R. Cameron Craddock
A4 Optimized implementations of voxel-wise degree centrality and local functional connectivity density mapping in AFNI
R. Cameron Craddock, Daniel J. Clark
A5 LORIS: DICOM anonymizer
Samir Das, Cécile Madjar, Ayan Sengupta, Zia Mohades
A6 Automatic extraction of academic collaborations in neuroimaging
Sebastien Dery
A7 NiftyView: a zero-footprint web application for viewing DICOM and NIfTI files
Weiran Deng
A8 Human Connectome Project Minimal Preprocessing Pipelines to Nipype
Eric Earl, Damion V. Demeter, Kate Mills, Glad Mihai, Luka Ruzic, Nick Ketz, Andrew Reineberg, Marianne C. Reddan, Anne-Lise Goddings, Javier Gonzalez-Castillo, Krzysztof J. Gorgolewski
A9 Generating music with resting-state fMRI data
Caroline Froehlich, Gil Dekel, Daniel S. Margulies, R. Cameron Craddock
A10 Highly comparable time-series analysis in Nitime
Ben D. Fulcher
A11 Nipype interfaces in CBRAIN
Tristan Glatard, Samir Das, Reza Adalat, Natacha Beck, Rémi Bernard, Najmeh Khalili-Mahani, Pierre Rioux, Marc-Étienne Rousseau, Alan C. Evans
A12 DueCredit: automated collection of citations for software, methods, and data
Yaroslav O. Halchenko, Matteo Visconti di Oleggio Castello
A13 Open source low-cost device to register dog’s heart rate and tail movement
Raúl Hernández-Pérez, Edgar A. Morales, Laura V. Cuaya
A14 Calculating the Laterality Index Using FSL for Stroke Neuroimaging Data
Kaori L. Ito, Sook-Lei Liew
A15 Wrapping FreeSurfer 6 for use in high-performance computing environments
Hans J. Johnson
A16 Facilitating big data meta-analyses for clinical neuroimaging through ENIGMA wrapper scripts
Erik Kan, Julia Anglin, Michael Borich, Neda Jahanshad, Paul Thompson, Sook-Lei Liew
A17 A cortical surface-based geodesic distance package for Python
Daniel S Margulies, Marcel Falkiewicz, Julia M Huntenburg
A18 Sharing data in the cloud
David O’Connor, Daniel J. Clark, Michael P. Milham, R. Cameron Craddock
A19 Detecting task-based fMRI compliance using plan abandonment techniques
Ramon Fraga Pereira, Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi
A20 Self-organization and brain function
Jörg P. Pfannmöller, Rickson Mesquita, Luis C.T. Herrera, Daniela Dentico
A21 The Neuroimaging Data Model (NIDM) API
Vanessa Sochat, B Nolan Nichols
A22 NeuroView: a customizable browser-base utility
Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi
A23 DIPY: Brain tissue classification
Julio E. Villalon-Reina, Eleftherios Garyfallidis
Impulsive behavior often occurs without forethought and can be driven by strong emotions or sudden impulses, leading to problems in cognition and behavior across a wide range of situations. Although ...neuroimaging studies have explored the neurocognitive indicators of impulsivity, the large-scale functional networks that contribute to different aspects of impulsive cognition remain unclear. In particular, we lack a coherent account of why impulsivity is associated with such a broad range of different psychological features. Here, we use resting state functional connectivity, acquired in two independent samples, to investigate the neural substrates underlying different aspects of self-reported impulsivity. Based on the involvement of the anterior cingulate cortex (ACC) in cognitive but also affective processes, five seed regions were placed along the caudal to rostral gradient of the ACC. We found that positive urgency was related to functional connectivity between subgenual ACC and bilateral parietal regions such as retrosplenial cortex potentially highlighting this connection as being important in the modulation of the non-prospective, hastiness – related aspects of impulsivity. Further, two impulsivity dimensions were associated with significant alterations in functional connectivity of the supragenual ACC: (i) lack of perseverance was positively correlated to connectivity with the bilateral dorsolateral prefrontal cortex and right inferior frontal gyrus and (ii) lack of premeditation was inversely associated with functional connectivity with clusters within bilateral occipital cortex. Further analysis revealed that these connectivity patterns overlapped with bilateral dorsolateral prefrontal and bilateral occipital regions of the multiple demand network, a large-scale neural system implicated in the general control of thought and action. Together these results demonstrate that different forms of impulsivity have different neural correlates, which are linked to the functional connectivity of a region of anterior cingulate cortex. This suggests that poor perseveration and premeditation might be linked to dysfunctions in how the rostral zone of the ACC interacts with the multiple demand network that allows cognition to proceed in a controlled way.
•Functional connectivity of the ACC relates to impulsivity in 2 independent samples.•Positive urgency predicts connectivity from subgenual cingulate to bilateral parietal.•Perseverance predicts connectivity from rostral cingulate to dorsolateral prefrontal.•Premeditation predicts connectivity from rostral cingulate to occipital/parietal.•Regions from perseverance and premeditation overlapped with multiple demand network.
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