The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Alumit Ishai - One of the best experts on this subject based on the ideXlab platform.
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Let's face it: it's a Cortical Network.
NeuroImage, 2008Co-Authors: Alumit IshaiAbstract:Face perception elicits activation within a distributed Cortical Network in the human brain. The Network includes visual ("core") regions, which process invariant facial features, as well as limbic and prefrontal ("extended") regions that process changeable aspects of faces. Analysis of effective connectivity reveals that the major entry node in the "face Network" is the lateral fusiform gyrus and that the functional coupling between the core and the extended systems is content-dependent. A model for face perception is proposed, in which the flow of information through the Network is shaped by cognitive demands.
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effective connectivity within the distributed Cortical Network for face perception
Cerebral Cortex, 2007Co-Authors: Scott L Fairhall, Alumit IshaiAbstract:Face perception elicits activation within a distributed Cortical Network in the human brain. The Network includes visual ("core") regions, as well as limbic and prefrontal ("extended") regions, which process invariant facial features and changeable aspects of faces, respectively. We used functional Magnetic Resonance Imaging and Dynamic Causal Modeling to investigate effective connectivity and functional organization between and within the core and the extended systems. We predicted a ventral rather than dorsal connection between the core and the extended systems during face viewing and tested whether valence and fame would alter functional coupling within the Network. We found that the core system is hierarchically organized in a predominantly feed-forward fashion, and that the fusiform gyrus (FG) exerts the dominant influence on the extended system. Moreover, emotional faces increased the coupling between the FG and the amygdala, whereas famous faces increased the coupling between the FG and the orbitofrontal cortex. Our results demonstrate content-specific dynamic alterations in the functional coupling between visual-limbic and visual-prefrontal face-responsive pathways.
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Face perception is mediated by a distributed Cortical Network.
Brain Research Bulletin, 2005Co-Authors: Alumit Ishai, Conny F Schmidt, Peter BoesigerAbstract:The neural system associated with face perception in the human brain was investigated using functional magnetic resonance imaging (fMRI). In contrast to many studies that focused on discreet face-responsive regions, the objective of the current study was to demonstrate that regardless of stimulus format, emotional valence, or task demands, face perception evokes activation in a distributed Cortical Network. Subjects viewed various stimuli (line drawings of unfamiliar faces and photographs of unfamiliar, famous, and emotional faces) and their phase scrambled versions. A Network of face-responsive regions was identified that included the inferior occipital gyrus, fusiform gyrus, superior temporal sulcus, hippocampus, amygdala, inferior frontal gyrus, and orbitofrontal cortex. Although bilateral activation was found in all regions, the response in the right hemisphere was stronger. This hemispheric asymmetry was manifested by larger and more significant clusters of activation and larger number of subjects who showed the effect. A region of interest analysis revealed that while all face stimuli evoked activation within all regions, viewing famous and emotional faces resulted in larger spatial extents of activation and higher amplitudes of the fMRI signal. These results indicate that a mere percept of a face is sufficient to localize activation within the distributed Cortical Network that mediates the visual analysis of facial identity and expression.
Paul B. Fitzgerald - One of the best experts on this subject based on the ideXlab platform.
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assessing Cortical Network properties using tms eeg
Human Brain Mapping, 2013Co-Authors: Nigel C. Rogasch, Paul B. FitzgeraldAbstract:The past decade has seen significant developments in the concurrent use of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to directly assess Cortical Network properties such as excitability and connectivity in humans. New hardware solutions, improved EEG amplifier technology, and advanced data processing techniques have allowed substantial reduction of the TMS-induced artifact, which had previously rendered concurrent TMS–EEG impossible. Various physiological artifacts resulting from TMS have also been identified, and methods are being developed to either minimize or remove these sources of artifact. With these developments, TMS–EEG has unlocked regions of the cortex to researchers that were previously inaccessible to TMS. By recording the TMS-evoked response directly from the cortex, TMS–EEG provides information on the excitability, effective connectivity, and oscillatory tuning of a given Cortical area, removing the need to infer such measurements from indirect measures. In the following review, we investigate the different online and offline methods for reducing artifacts in TMS–EEG recordings and the physiological information contained within the TMS-evoked Cortical response. We then address the use of TMS–EEG to assess different Cortical mechanisms such as Cortical inhibition and neural plasticity, before briefly reviewing studies that have utilized TMS–EEG to explore Cortical Network properties at rest and during different functional brain states. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.
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assessing Cortical Network properties using tms eeg
Human Brain Mapping, 2013Co-Authors: Nigel C. Rogasch, Paul B. FitzgeraldAbstract:The past decade has seen significant developments in the concurrent use of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to directly assess Cortical Network properties such as excitability and connectivity in humans. New hardware solutions, improved EEG amplifier technology, and advanced data processing techniques have allowed substantial reduction of the TMS-induced artifact, which had previously rendered concurrent TMS-EEG impossible. Various physiological artifacts resulting from TMS have also been identified, and methods are being developed to either minimize or remove these sources of artifact. With these developments, TMS-EEG has unlocked regions of the cortex to researchers that were previously inaccessible to TMS. By recording the TMS-evoked response directly from the cortex, TMS-EEG provides information on the excitability, effective connectivity, and oscillatory tuning of a given Cortical area, removing the need to infer such measurements from indirect measures. In the following review, we investigate the different online and offline methods for reducing artifacts in TMS-EEG recordings and the physiological information contained within the TMS-evoked Cortical response. We then address the use of TMS-EEG to assess different Cortical mechanisms such as Cortical inhibition and neural plasticity, before briefly reviewing studies that have utilized TMS-EEG to explore Cortical Network properties at rest and during different functional brain states.
Stanislas Dehaene - One of the best experts on this subject based on the ideXlab platform.
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a distinct Cortical Network for mathematical knowledge in the human brain
NeuroImage, 2019Co-Authors: Marie Amalric, Stanislas DehaeneAbstract:How does the brain represent and manipulate abstract mathematical concepts? Recent evidence suggests that mathematical processing relies on specific brain areas and dissociates from language. Here, we investigate this dissociation in two fMRI experiments in which professional mathematicians had to judge the truth value of mathematical and nonmathematical spoken statements. Sentences with mathematical content systematically activated bilateral intraparietal sulci and inferior temporal regions, regardless of math domain, problem difficulty, and strategy for judging truth value (memory retrieval, calculation or mental imagery). Second, classical language areas were only involved in the parsing of both nonmathematical and mathematical statements, and their activation correlated with syntactic complexity, not mathematical content. Third, the mere presence, within a sentence, of elementary logical operators such as quantifiers or negation did not suffice to activate math-responsive areas. Instead, quantifiers and negation impacted on activity in right angular gyrus and left inferior frontal gyrus, respectively. Overall, these results support the existence of a distinct, non-linguistic Cortical Network for mathematical knowledge in the human brain.
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probing the Cortical Network underlying the psychological refractory period a combined eeg fmri study
NeuroImage, 2011Co-Authors: Guido Hesselmann, Stanislas Dehaene, Guillaume FlandinAbstract:Abstract Human performance exhibits strong multi-tasking limitations in simple response time tasks. In the psychological refractory period (PRP) paradigm, where two tasks have to be performed in brief succession, central processing of the second task is delayed when the two tasks are performed at short time intervals. Here, we aimed to probe the Cortical Network underlying this postponement of central processing by simultaneously recording electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data while 12 subjects performed two simple number-comparison tasks. Behavioral data showed a significant slowing of response times to the second target stimulus at short stimulus-onset asynchronies, together with significant correlations between response times to the first and second target stimulus, i.e., the hallmarks of the PRP effect. The analysis of EEG data showed a significant delay of the post-perceptual P3 component evoked by the second target, which was of similar magnitude as the effect on response times. fMRI data revealed an involvement of parietal and prefrontal regions in dual-task processing. The combined analysis of fMRI and EEG data—based on the trial-by-trial variability of the P3—revealed that BOLD signals in two bilateral regions in the inferior parietal lobe and precentral gyrus significantly covaried with P3 related activity. Our results show that combining neuroimaging methods of high spatial and temporal resolutions can help to identify Cortical regions underlying the central bottleneck of information processing, and strengthen the conclusion that fronto-parietal Cortical regions participate in a distributed “global neuronal workspace” system that underlies the generation of the P3 component and may be one of the key cerebral underpinnings of the PRP bottleneck.
Rick C S Lin - One of the best experts on this subject based on the ideXlab platform.
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behavioral training reverses global Cortical Network dysfunction induced by perinatal antidepressant exposure
Proceedings of the National Academy of Sciences of the United States of America, 2015Co-Authors: Kimberly L Simpson, Michael M Merzenich, Xiaoming Zhou, Ryan D Darling, Xiaoqing Zhu, Fang Wang, Xinde Sun, Rick C S LinAbstract:Abnormal Cortical circuitry and function as well as distortions in the modulatory neurological processes controlling Cortical plasticity have been argued to underlie the origin of autism. Here, we chemically distorted those processes using an antidepressant drug-exposure model to generate developmental neurological distortions like those characteristics expressed in autism, and then intensively trained altered young rodents to evaluate the potential for neuroplasticity-driven renormalization. We found that young rats that were injected s.c. with the antidepressant citalopram from postnatal d 1–10 displayed impaired neuronal repetition-rate following capacity in the primary auditory cortex (A1). With a focus on recovering grossly degraded auditory system processing in this model, we showed that targeted temporal processing deficits induced by early-life antidepressant exposure within the A1 were almost completely reversed through implementation of a simple behavioral training strategy (i.e., a modified go/no-go repetition-rate discrimination task). Degraded parvalbumin inhibitory GABAergic neurons and the fast inhibitory actions that they control were also renormalized by training. Importantly, antidepressant-induced degradation of serotonergic and dopaminergic neuromodulatory systems regulating Cortical neuroplasticity was sharply reversed. These findings bear important implications for neuroplasticity-based therapeutics in autistic patients.
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perinatal antidepressant exposure alters Cortical Network function in rodents
Proceedings of the National Academy of Sciences of the United States of America, 2011Co-Authors: Kimberly L Simpson, Kristin J Weaver, Etienne De Villerssidani, Zhengwei Cai, Yi Pang, Federico Rodriguezporcel, Ian A Paul, Michael M Merzenich, Rick C S LinAbstract:Serotonin (5-HT) plays a key role in early brain development, and manipulation of 5-HT levels during this period can have lasting neurobiological and behavioral consequences. It is unclear how perinatal exposure to drugs, such as selective serotonin reuptake inhibitors (SSRIs), impacts Cortical neural Network function and what mechanism(s) may elicit the disruption of normal neuronal connections/interactions. In this article, we report on Cortical wiring organization after pre- and postnatal exposure to the SSRI citalopram. We show that manipulation of 5-HT during early development in both in vitro and in vivo models disturbs characteristic chemoarchitectural and electrophysiological brain features, including changes in raphe and callosal connections, sensory processing, and myelin sheath formation. Also, drug-exposed rat pups exhibit neophobia and disrupted juvenile play behavior. These findings indicate that 5-HT homeostasis is required for proper brain maturation and that fetal/infant exposure to SSRIs should be examined in humans, particularly those with developmental dysfunction, such as autism.
Avram J Holmes - One of the best experts on this subject based on the ideXlab platform.
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heritability of individualized Cortical Network topography
Proceedings of the National Academy of Sciences of the United States of America, 2021Co-Authors: Kevin M Anderson, Ru Kong, Lauren M Patrick, Nathan R Spreng, Mert R Sabuncu, B Thomas T Yeo, Avram J HolmesAbstract:Human cortex is patterned by a complex and interdigitated web of large-scale functional Networks. Recent methodological breakthroughs reveal variation in the size, shape, and spatial topography of Cortical Networks across individuals. While spatial Network organization emerges across development, is stable over time, and is predictive of behavior, it is not yet clear to what extent genetic factors underlie interindividual differences in Network topography. Here, leveraging a nonlinear multidimensional estimation of heritability, we provide evidence that individual variability in the size and topographic organization of Cortical Networks are under genetic control. Using twin and family data from the Human Connectome Project (n = 1,023), we find increased variability and reduced heritability in the size of heteromodal association Networks (h 2 : M = 0.34, SD = 0.070), relative to unimodal sensory/motor cortex (h 2 : M = 0.40, SD = 0.097). We then demonstrate that the spatial layout of Cortical Networks is influenced by genetics, using our multidimensional estimation of heritability (h 2 -multi; M = 0.14, SD = 0.015). However, topographic heritability did not differ between heteromodal and unimodal Networks. Genetic factors had a regionally variable influence on brain organization, such that the heritability of Network topography was greatest in prefrontal, precuneus, and posterior parietal cortex. Taken together, these data are consistent with relaxed genetic control of association cortices relative to primary sensory/motor regions and have implications for understanding population-level variability in brain functioning, guiding both individualized prediction and the interpretation of analyses that integrate genetics and neuroimaging.
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anxious attachment is associated with heightened responsivity of a parietofrontal Cortical Network that monitors peri personal space
NeuroImage: Clinical, 2021Co-Authors: Zahra Nasiriavanaki, Avram J Holmes, Tracy Barbour, Amy Farabaugh, Maurizio Fava, Roger B H Tootell, Daphne J HoltAbstract:Abstract Background Attachment, or affiliative bonding among conspecifics, is thought to involve neural mechanisms underlying behavioral responses to threat and reward -related social signals. However, attachment-oriented responses may also rely on basic sensorimotor processes. One sensorimotor system that may play a role in attachment is the parietofrontal Cortical Network that responds to stimuli that are near or approaching the body, the peripersonal space (PPS) monitoring system. We hypothesized that this Network may vary in responsivity to such potentially harmful stimuli, particularly those with social salience, based on individual differences in attachment styles. Methods Young adults viewed images of human faces or cars that appeared to move towards or away from them, while functional magnetic resonance imaging data were collected. Correlations between each of four adult attachment styles, measured using the Relationship Questionnaire, and responses of the PPS Network to approaching (versus withdrawing) stimuli were measured. Results A region-of-interest (ROI) analysis, focused on six Cortical regions of the PPS Network that showed significant responses to approaching versus withdrawing face stimuli in an independent sample (n = 80), revealed that anxious attachment style (but not the other 3 attachment styles) was significantly positively correlated with responses to faces (but not to cars) in all six ROIs (r = 0.36 - 0.52, p = 0.01- 0.0001, n = 50). Conclusions These findings suggest that anxious attachment is associated with over-responsivity of a sensorimotor Network involved in attending to social stimuli near the body.
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heritability of individualized Cortical Network topography
bioRxiv, 2020Co-Authors: Kevin M Anderson, Ru Kong, Lauren M Patrick, Nathan R Spreng, Mert R Sabuncu, B Thomas T Yeo, Avram J HolmesAbstract:Aim To evaluate service in an English local neonatal unit in regard of capacity issues with high dependency, which represents a lynchpin resource within the Perinatal Network System. Methods. The research was performed in collaboration with a District General Hospital and a University Department of Computer Science. With the consent of the regional Research Ethics Committee, Standardised Electronic Neonatal Database (SEND) data cleaned by local neonatal unit ward clerks was analysed and patient pathways through high dependency modelled. Results The unit configuration was one intensive care and four high dependency cots. During 2009–11, high dependency idle time was 0.14, whilst oversubscription was 0.07. 90% of daily changes in occupancy for high dependency were by up to one cot. The mean Length of Stay (LOS) was 5.5 days. For those patients requiring high dependency care after first being admitted to a different level of care, the mean prior stay on intensive care was 4.7 days and that on special care 2.9 days. In the population needing any high dependency, it represented a backward step in their care pathway in 4.7%. Diagnostic patient groups have differing LOS profiles. Those receiving high dependency for Neonatal Abstinence Syndrome (NAS) or Continuous Positive Airways Pressure for Chronic Lung Disease not only had the longest stays but also iterated between special care and high dependency. NAS accounted for 20% of high dependency work. To achieve a less than even chance of overload in high dependency, spare capacity of two cots is needed. Having one unoccupied cot gives a 70% probability of overload. Up to 63 days per year are normally expected to be short of one or more nurses, assuming full nursing establishment and no absence. Conclusion High dependency cot activity lurched between extremes. Economies of scale are difficult in medium sized local neonatal units. For a patient Network, Game Theory tells us that load balancing of the whole system means running different occupancies in each component unit. We hope that this work contributes to understanding of patient Networks and guides operations management, which is challenged by rota gaps.
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heritability of individualized Cortical Network topography
bioRxiv, 2020Co-Authors: Kevin M Anderson, Ru Kong, Lauren M Patrick, Nathan R Spreng, Mert R Sabuncu, B Thomas T Yeo, Avram J HolmesAbstract:Abstract Human cortex is patterned by a complex and interdigitated web of large-scale functional Networks. Recent methodological breakthroughs reveal variation in the size, shape, and spatial topography of Cortical Networks across individuals. While spatial Network organization emerges across development, is stable over time, and predictive of behavior, it is not yet clear to what extent genetic factors underlie inter-individual differences in Network topography. Here, leveraging a novel non-linear multi-dimensional estimation of heritability, we provide evidence that individual variability in the size and topographic organization of Cortical Networks are under genetic control. Using twin and family data from the Human Connectome Project (n=1,023), we find increased variability and reduced heritability in the size of heteromodal association Networks (h2: M=0.33, SD=0.071), relative to unimodal sensory/motor cortex (h2: M=0.44, SD=0.051). We then demonstrate that the spatial layout of Cortical Networks is influenced by genetics, using our multi-dimensional estimation of heritability (h2-multi; M=0.14, SD=0.015). However, topographic heritability did not differ between heteromodal and unimodal Networks. Genetic factors had a regionally variable influence on brain organization, such that the heritability of Network topography was greatest in prefrontal, precuneus, and posterior parietal cortex. Taken together, these data are consistent with relaxed genetic control of association cortices relative to primary sensory/motor regions, and have implications for understanding population-level variability in brain functioning, guiding both individualized prediction and the interpretation of analyses that integrate genetics and neuroimaging. Significance The widespread use of population-average Cortical parcellations has provided important insights into broad properties of human brain organization. However, the size, location, and spatial arrangement of regions comprising functional brain Networks can vary substantially across individuals. Here, we demonstrate considerable heritability in both the size and spatial organization of individual-specific Network topography across cortex. Genetic factors had a regionally variable influence on brain organization, such that heritability in Network size, but not topography, was greater in unimodal relative to heteromodal cortices. These data suggest individual-specific Network parcellations may provide an avenue to understand the genetic basis of variation in human cognition and behavior.
