scholarly journals Cytoarchitectonic mapping of the human brain cerebellar nuclei in stereotaxic space and delineation of their co-activation patterns

2015 ◽  
Vol 09 ◽  
Author(s):  
Stefanie Tellmann ◽  
Sebastian Bludau ◽  
Simon Eickhoff ◽  
Hartmut Mohlberg ◽  
Martina Minnerop ◽  
...  
Author(s):  
Helen Engemann

Abstract Simultaneous bilingual children sometimes display crosslinguistic influence (CLI), widely attested in the domain of morphosyntax. It remains less clear whether CLI affects bilinguals’ event construal, what motivates its occurrence and directionality, and how developmentally persistent it is. The present study tested predictions generated by the structural overlap hypothesis and the co-activation account in the motion event domain. 96 English–French bilingual children of two age groups and 96 age-matched monolingual English and French controls were asked to describe animated videos displaying voluntary motion events. Semantic encoding in main verbs showed bidirectional CLI. Unidirectional CLI affected French path encoding in the verbal periphery and was predicted by the presence of boundary-crossing, despite the absence of structural overlap. Furthermore, CLI increased developmentally in the French data. It is argued that these findings reflect highly dynamic co-activation patterns sensitive to the requirements of the task and to language-specific challenges in the online production process.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Arian Ashourvan ◽  
Preya Shah ◽  
Adam Pines ◽  
Shi Gu ◽  
Christopher W. Lynn ◽  
...  

AbstractA major challenge in neuroscience is determining a quantitative relationship between the brain’s white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes’ activation patterns’ probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM’s interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions’ distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain’s structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.


2007 ◽  
Vol 118 (4) ◽  
pp. e34-e35
Author(s):  
R. Gobbelé ◽  
U. Stegelmeyer ◽  
T.D. Waberski ◽  
K.E. Stephan ◽  
K. Rache ◽  
...  

2019 ◽  
Author(s):  
Jianfeng Zhang ◽  
Zirui Huang ◽  
Shankar Tumati ◽  
Georg Northoff

AbstractRecent resting-state fMRI studies have revealed that the global signal (GS) exhibits a non-uniform spatial distribution across the gray matter. Whether this topography is informative remains largely unknown. We therefore tested rest-task modulation of global signal topography by analyzing static global signal correlation and dynamic co-activation patterns in a large sample of fMRI dataset (n=837) from the Human Connectome Project. The GS topography in the resting-state and in seven different tasks was first measured by correlating the global signal with the local timeseries (GSCORR). In the resting state, high GSCORR was observed mainly in the primary sensory and motor regions, while low GSCORR was seen in the association brain areas. This pattern changed during the seven tasks, with mainly decreased GSCORR in sensorimotor cortex. Importantly, this rest-task modulation of GSCORR could be traced to transient co-activation patterns at the peak period of global signal (GS-peak). By comparing the topography of GSCORR and respiration effects, we observed that the topography of respiration mimicked the topography of global signal in the resting-state whereas both differed during the task states; due to such partial dissociation, we assume that GSCORR could not be equated with a respiration effect. Finally, rest-task modulation of GS topography could not be exclusively explained by other sources of physiological noise. Together, we here demonstrate the informative nature of global signal topography by showing its rest-task modulation, the underlying dynamic co-activation patterns, and its partial dissociation from respiration effects during task states.


Author(s):  
Payel Das ◽  
Brian Quanz ◽  
Pin-Yu Chen ◽  
Jae-wook Ahn ◽  
Dhruv Shah

Creativity, a process that generates novel and meaningful ideas, involves increased association between task-positive (control) and task-negative (default) networks in the human brain. Inspired by this seminal finding, in this study we propose a creative decoder within a deep generative framework, which involves direct modulation of the neuronal activation pattern after sampling from the learned latent space. The proposed approach is fully unsupervised and can be used off- the-shelf. Several novelty metrics and human evaluation were used to evaluate the creative capacity of the deep decoder. Our experiments on different image datasets (MNIST, FMNIST, MNIST+FMNIST, WikiArt and CelebA) reveal that atypical co-activation of highly activated and weakly activated neurons in a deep decoder promotes generation of novel and meaningful artifacts.


2017 ◽  
pp. 3-12
Author(s):  
Riitta Hari ◽  
Aina Puce

Neuronal communication in the brain is associated with minute electrical currents that give rise to both electrical potentials on the scalp (measurable by means of electroencephalography [EEG]) and magnetic fields outside the head (measurable by magnetoencephalography [MEG]). Both MEG and EEG are noninvasive neurophysiological methods used to study brain dynamics, that is temporal changes in the activation patterns, and sequences in signal progression. Differences between MEG and EEG mainly reflect differences in the spread of electric and magnetic fields generated by the same electric currents in the human brain. This chapter provides an overall description of the main principles of MEG and EEG and provides background for the following chapters in this and subsequent sections.


2008 ◽  
Vol 1205 ◽  
pp. 81-90 ◽  
Author(s):  
René Gobbelé ◽  
Kathrin Lamberty ◽  
Klaas E. Stephan ◽  
Ulrike Stegelmeyer ◽  
Helmut Buchner ◽  
...  

NeuroImage ◽  
2014 ◽  
Vol 90 ◽  
pp. 390-402 ◽  
Author(s):  
Julian Caspers ◽  
Karl Zilles ◽  
Christoph Beierle ◽  
Claudia Rottschy ◽  
Simon B. Eickhoff

2021 ◽  
Author(s):  
Moataz Assem ◽  
Sneha Shashidhara ◽  
Matthew F. Glasser ◽  
John Duncan

AbstractRecent functional MRI studies identified sensory-biased regions across much of the association cortices and cerebellum. However, their anatomical relationship to multiple-demand (MD) regions, characterized as domain-general due to their co-activation during multiple cognitive demands, remains unclear. For a better anatomical delineation, we used multimodal MRI techniques of the Human Connectome Project to scan subjects performing visual and auditory versions of a working memory (WM) task. The contrast between hard and easy WM showed strong domain generality, with essentially identical patterns of MD activity for visual and auditory materials. In contrast, modality preferences were shown by contrasting easy WM with baseline; most MD regions showed visual preference while immediately adjacent to cortical MD regions, there were interleaved regions of both visual and auditory preference. The results may exemplify a general motif whereby domain-specific regions feed information into and out of an adjacent, integrative MD core.


2017 ◽  
Author(s):  
Selen Atasoy ◽  
Leor Roseman ◽  
Mendel Kaelen ◽  
Morten L. Kringelbach ◽  
Gustavo Deco ◽  
...  

ABSTRACTRecent studies have started to elucidate the effects of lysergic acid diethylamide (LSD) on the human brain but the underlying dynamics are not yet fully understood. Here we used ‘connectome-harmonic decomposition’, a novel method to investigate the dynamical changes in brain states. We found that LSD alters the energy and the power of individual harmonic brain states in a frequency-selective manner. Remarkably, this leads to an expansion of the repertoire of active brain states, suggestive of a general re-organization of brain dynamics given the non-random increase in co-activation across frequencies. Interestingly, the frequency distribution of the active repertoire of brain states under LSD closely follows power-laws indicating a re-organization of the dynamics at the edge of criticality. Beyond the present findings, these methods open up for a better understanding of the complex brain dynamics in health and disease.


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