scholarly journals Propagation of BOLD Activity Reveals Task-dependent Directed Interactions Across Human Visual Cortex

2020 ◽  
Vol 30 (11) ◽  
pp. 5899-5914 ◽  
Author(s):  
Nicolás Gravel ◽  
Remco J Renken ◽  
Ben M Harvey ◽  
Gustavo Deco ◽  
Frans W Cornelissen ◽  
...  
Keyword(s):  
Visual Field ◽  
Large Scale ◽  
Cortical Excitability ◽  
Effective Connectivity ◽  
Covariance Structure ◽  
Blood Oxygen Level Dependent ◽  
Dependent Manner ◽  
Blood Oxygen Level ◽  
Functional Relevance ◽  
Visual Field Mapping

Abstract It has recently been shown that large-scale propagation of blood-oxygen-level-dependent (BOLD) activity is constrained by anatomical connections and reflects transitions between behavioral states. It remains to be seen, however, if the propagation of BOLD activity can also relate to the brain’s anatomical structure at a more local scale. Here, we hypothesized that BOLD propagation reflects structured neuronal activity across early visual field maps. To explore this hypothesis, we characterize the propagation of BOLD activity across V1, V2, and V3 using a modeling approach that aims to disentangle the contributions of local activity and directed interactions in shaping BOLD propagation. It does so by estimating the effective connectivity (EC) and the excitability of a noise-diffusion network to reproduce the spatiotemporal covariance structure of the data. We apply our approach to 7T fMRI recordings acquired during resting state (RS) and visual field mapping (VFM). Our results reveal different EC interactions and changes in cortical excitability in RS and VFM, and point to a reconfiguration of feedforward and feedback interactions across the visual system. We conclude that the propagation of BOLD activity has functional relevance, as it reveals directed interactions and changes in cortical excitability in a task-dependent manner.

scholarly journals Propagation of BOLD activity reveals task-dependent directed interactions across human visual cortex

2017 ◽  
Author(s):  
Nicolás Gravel ◽  
Remco J. Renken ◽  
Ben M. Harvey ◽  
Gustavo Deco ◽  
Frans W. Cornelissen ◽  
...  
Keyword(s):  
Visual Field ◽  
Large Scale ◽  
Cortical Excitability ◽  
Effective Connectivity ◽  
Covariance Structure ◽  
Blood Oxygen Level Dependent ◽  
Dependent Manner ◽  
Blood Oxygen Level ◽  
Functional Relevance ◽  
Visual Field Mapping

AbstractIt has recently been shown that large-scale propagation of blood-oxygen level dependent (BOLD) activity is constrained by anatomical connections and reflects transitions between behavioral states. It remains to be seen, however, if the propagation of BOLD activity can also relate to the brain anatomical structure at a more local scale. Here, we hypothesized that BOLD propagation reflects structured neuronal activity across early visual field maps. To explore this hypothesis, we characterize the propagation of BOLD activity across V1, V2 and V3 using a modeling approach that aims to disentangle the contributions of local activity and directed interactions in shaping BOLD propagation. It does so by estimating the effective connectivity (EC) and the excitability of a noise-diffusion network to reproduce the spatiotemporal covariance structure of the data. We apply our approach to 7T fMRI recordings acquired during resting state (RS) and visual field mapping (VFM). Our results reveal different EC interactions and changes in cortical excitability in RS and VFM, and point to a reconfiguration of feedforward and feedback interactions across the visual system. We conclude that the propagation of BOLD activity has functional relevance, as it reveals directed interactions and changes in cortical excitability in a task-dependent manner.

Equal Degrees of Object Selectivity for Upper and Lower Visual Field Stimuli

2010 ◽  
Vol 104 (4) ◽  
pp. 2075-2081 ◽  
Author(s):  
Lars Strother ◽  
Adrian Aldcroft ◽  
Cheryl Lavell ◽  
Tutis Vilis
Keyword(s):  
Visual Field ◽  
Occipital Cortex ◽  
Recognition System ◽  
Blood Oxygen Level Dependent ◽  
Lower Visual Field ◽  
Blood Oxygen Level ◽  
Visual Areas ◽  
Bold Responses ◽  
Cortical Regions ◽  
Lateral Occipital Cortex

Functional MRI (fMRI) studies of the human object recognition system commonly identify object-selective cortical regions by comparing blood oxygen level–dependent (BOLD) responses to objects versus those to scrambled objects. Object selectivity distinguishes human lateral occipital cortex (LO) from earlier visual areas. Recent studies suggest that, in addition to being object selective, LO is retinotopically organized; LO represents both object and location information. Although LO responses to objects have been shown to depend on location, it is not known whether responses to scrambled objects vary similarly. This is important because it would suggest that the degree of object selectivity in LO does not vary with retinal stimulus position. We used a conventional functional localizer to identify human visual area LO by comparing BOLD responses to objects versus scrambled objects presented to either the upper (UVF) or lower (LVF) visual field. In agreement with recent findings, we found evidence of position-dependent responses to objects. However, we observed the same degree of position dependence for scrambled objects and thus object selectivity did not differ for UVF and LVF stimuli. We conclude that, in terms of BOLD response, LO discriminates objects from non-objects equally well in either visual field location, despite stronger responses to objects in the LVF.

Effective Connectivity During an Avoidance-Based Pavlovian-to-Instrumental Transfer Task

2021 ◽  
Author(s):  
Daniel Petrie ◽  
Sy-Miin Chow ◽  
Charles Geier
Keyword(s):  
Effective Connectivity ◽  
A Priori ◽  
Transfer Task ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Response Patterns ◽  
Multiple Model ◽  
Hemodynamic Response Function ◽  
Blood Oxygen Level ◽  
Psychological Phenomena

Pavlovian-to-instrumental transfer (PIT) refers to a phenomenon whereby a classically conditioned stimulus (CS) impacts the motivational salience of instrumental behavior. We examined behavioral response patterns and functional magnetic resonance imaging (fMRI) based effective connectivity during an avoidance-based PIT task. Eleven participants (8 females; Mage = 28.2, SD = 2.8, range = 25-32 years) completed the task. Effective connectivity between a priori brain regions engaged during the task was determined using hemodynamic response function group iterative multiple model estimation (HRF-GIMME). Behaviorally, participants exhibited specific PIT, a CS previously associated with a reinforcing outcome increased instrumental responding directed at the same outcome. We did not find evidence for general PIT; a CS did not significantly increase instrumental responding towards a different but related outcome. Using HRF-GIMME, we recovered effective connectivity maps among corticostriatal circuits engaged during the task. Group-level paths revealed directional effects from left putamen to right insula and from right putamen to right cingulate. Importantly, a direct effect of specific PIT stimuli on blood-oxygen-level-dependent (BOLD) activity in the left putamen was found. Results provide initial evidence of effective connectivity in key brain regions in an avoidance-based PIT task network. This study adds to the literature studying PIT effects in humans and employing GIMME models to understand how psychological phenomena are supported in the brain.

Radial Biases in the Processing of Motion and Motion-Defined Contours by Human Visual Cortex

2009 ◽  
Vol 102 (5) ◽  
pp. 2974-2981 ◽  
Author(s):  
Colin W. G. Clifford ◽  
Damien J. Mannion ◽  
J. Scott McDonald
Keyword(s):  
Visual Cortex ◽  
Visual Field ◽  
Human Subjects ◽  
Temporal Integration ◽  
Blood Oxygen Level Dependent ◽  
Orientation Tuning ◽  
Bold Signal ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Blood Oxygen Level

Luminance gratings reportedly produce a stronger functional magnetic resonance imaging (fMRI) blood oxygen level–dependent (BOLD) signal in those parts of the retinotopic cortical maps where they are oriented radially to the point of fixation. We sought to extend this finding by examining anisotropies in the response of cortical areas V1–V3 to motion-defined contour stimuli. fMRI at 3 Tesla was used to measure the BOLD signal in the visual cortex of six human subjects. Stimuli were composed of strips of spatial white noise texture presented in an annular window. The texture in alternate strips moved in opposite directions (left–right or up–down). The strips themselves were static and tilted 45° left or right from vertical. Comparison with maps of the visual field obtained from phase-encoded retinotopic analysis revealed systematic patterns of radial bias. For motion, a stronger response to horizontal was evident within V1 and along the borders between V2 and V3. For orientation, the response to leftward tilted contours was greater in left dorsal and right ventral V1–V3. Radial bias for the orientation of motion-defined contours analogous to that reported previously for luminance gratings could reflect cue-invariant processing or the operation of distinct mechanisms subject to similar anisotropies in orientation tuning. Radial bias for motion might be related to the phenomenon of “motion streaks,” whereby temporal integration by the visual system introduces oriented blur along the axis of motion. We speculate that the observed forms of radial bias reflect a common underlying anisotropy in the representation of spatiotemporal image structure across the visual field.

scholarly journals A Theoretical Investigation of the Relationship between Structural Equation Modeling and Partial Correlation in Functional MRI Effective Connectivity

2009 ◽  
Vol 2009 ◽  
pp. 1-9 ◽  
Author(s):  
Guillaume Marrelec ◽  
Habib Benali
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Partial Correlation ◽  
Effective Connectivity ◽  
Real Data ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Equation Modeling ◽  
Blood Oxygen Level ◽  
Partial Correlations

An important field of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) is the investigation of effective connectivity, that is, the actions that a given set of regions exert on one another. We recently proposed a data-driven method based on the partial correlation matrix that could provide some insight regarding the pattern of functional interaction between brain regions as represented by structural equation modeling (SEM). So far, the efficiency of this approach was mostly based on empirical evidence. In this paper, we provide theoretical fundaments explaining why and in what measure structural equation modeling and partial correlations are related. This gives better insight regarding what parts of SEM can be retrieved by partial correlation analysis and what remains inaccessible. We illustrate the different results with real data.

scholarly journals The Global Signal and Observed Anticorrelated Resting State Brain Networks

2009 ◽  
Vol 101 (6) ◽  
pp. 3270-3283 ◽  
Author(s):  
Michael D. Fox ◽  
Dongyang Zhang ◽  
Abraham Z. Snyder ◽  
Marcus E. Raichle
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Brain Networks ◽  
Blood Oxygen Level Dependent ◽  
Great Promise ◽  
Blood Oxygen Level ◽  
Whole Brain ◽  
Global Signal ◽  
Global Regression

Resting state studies of spontaneous fluctuations in the functional MRI (fMRI) blood oxygen level dependent (BOLD) signal have shown great promise in mapping the brain's intrinsic, large-scale functional architecture. An important data preprocessing step used to enhance the quality of these observations has been removal of spontaneous BOLD fluctuations common to the whole brain (the so-called global signal). One reproducible consequence of global signal removal has been the finding that spontaneous BOLD fluctuations in the default mode network and an extended dorsal attention system are consistently anticorrelated, a relationship that these two systems exhibit during task performance. The dependence of these resting-state anticorrelations on global signal removal has raised important questions regarding the nature of the global signal, the validity of global signal removal, and the appropriate interpretation of observed anticorrelated brain networks. In this study, we investigate several properties of the global signal and find that it is, indeed, global, not residing preferentially in systems exhibiting anticorrelations. We detail the influence of global signal removal on resting state correlation maps both mathematically and empirically, showing an enhancement in detection of system-specific correlations and improvement in the correspondence between resting-state correlations and anatomy. Finally, we show that several characteristics of anticorrelated networks including their spatial distribution, cross-subject consistency, presence with modified whole brain masks, and existence before global regression are not attributable to global signal removal and therefore suggest a biological basis.

scholarly journals Effective Connectivity during an Avoidance-Based Pavlovian-to-Instrumental Transfer Task

2021 ◽  
Vol 11 (11) ◽  
pp. 1472
Author(s):  
Daniel J. Petrie ◽  
Sy-Miin Chow ◽  
Charles F. Geier
Keyword(s):  
Effective Connectivity ◽  
A Priori ◽  
Transfer Task ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Response Patterns ◽  
Multiple Model ◽  
Hemodynamic Response Function ◽  
Blood Oxygen Level ◽  
Psychological Phenomena

Pavlovian-to-instrumental transfer (PIT) refers to a phenomenon whereby a classically conditioned stimulus (CS) impacts the motivational salience of instrumental behavior. We examined behavioral response patterns and functional magnetic resonance imaging (fMRI) based effective connectivity during an avoidance-based PIT task. Eleven participants (8 females; Mage = 28.2, SD = 2.8, range = 25–32 years) completed the task. Effective connectivity between a priori brain regions engaged during the task was determined using hemodynamic response function group iterative multiple model estimation (HRF-GIMME). Participants exhibited behavior that was suggestive of specific PIT, a CS previously associated with a reinforcing outcome increased instrumental responding directed at the same outcome. We did not find evidence for general PIT; a CS did not significantly increase instrumental responding towards a different but related outcome. Using HRF-GIMME, we recovered effective connectivity maps among corticostriatal circuits engaged during the task. Group-level paths revealed directional effects from left putamen to right insula and from right putamen to right cingulate. Importantly, a direct effect of specific PIT stimuli on blood–oxygen-level-dependent (BOLD) activity in the left putamen was found. Results provide initial evidence of effective connectivity in key brain regions in an avoidance-based PIT task network. This study adds to the literature studying PIT effects in humans and employing GIMME models to understand how psychological phenomena are supported in the brain.

scholarly journals Transcriptomics-informed large-scale cortical model captures topography of pharmacological neuroimaging effects of LSD

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Joshua B Burt ◽  
Katrin H Preller ◽  
Murat Demirtas ◽  
Jie Lisa Ji ◽  
John H Krystal ◽  
...  
Keyword(s):  
Large Scale ◽  
Physiological State ◽  
Model Fitting ◽  
Blood Oxygen Level Dependent ◽  
Neural Function ◽  
Cortical Model ◽  
Blood Oxygen Level ◽  
Individual Subject ◽  
Brain Physiology ◽  
Serotonin 2A

Psychoactive drugs can transiently perturb brain physiology while preserving brain structure. The role of physiological state in shaping neural function can therefore be investigated through neuroimaging of pharmacologically induced effects. Previously, using pharmacological neuroimaging, we found that neural and experiential effects of lysergic acid diethylamide (LSD) are attributable to agonism of the serotonin-2A receptor (Preller et al., 2018). Here, we integrate brain-wide transcriptomics with biophysically based circuit modeling to simulate acute neuromodulatory effects of LSD on human cortical large-scale spatiotemporal dynamics. Our model captures the inter-areal topography of LSD-induced changes in cortical blood oxygen level-dependent (BOLD) functional connectivity. These findings suggest that serotonin-2A-mediated modulation of pyramidal-neuronal gain is a circuit mechanism through which LSD alters cortical functional topography. Individual-subject model fitting captures patterns of individual neural differences in pharmacological response related to altered states of consciousness. This work establishes a framework for linking molecular-level manipulations to systems-level functional alterations, with implications for precision medicine.

scholarly journals Contribution of Exploratory Methods to the Investigation of Extended Large-Scale Brain Networks in Functional MRI: Methodologies, Results, and Challenges

2008 ◽  
Vol 2008 ◽  
pp. 1-14 ◽  
Author(s):  
V. Perlbarg ◽  
G. Marrelec
Keyword(s):  
Large Scale ◽  
Blood Oxygen Level Dependent ◽  
Brain Network ◽  
Data Driven ◽  
Blood Oxygen ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Blood Oxygen Level ◽  
Functional Interactions ◽  
Efficient Exploration

A large-scale brain network can be defined as a set of segregated and integrated regions, that is, distant regions that share strong anatomical connections and functional interactions. Data-driven investigation of such networks has recently received a great deal of attention in blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI). We here review the rationale for such an investigation, the methods used, the results obtained, and also discuss some issues that have to be faced for an efficient exploration.

scholarly journals Rethinking Measures of Functional Connectivity via Feature Extraction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rosaleena Mohanty ◽  
William A. Sethares ◽  
Veena A. Nair ◽  
Vivek Prabhakaran
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Linear Time ◽  
Adult Population ◽  
Resting State Fmri ◽  
Blood Oxygen Level Dependent ◽  
Blood Oxygen Level ◽  
Pearson’S Correlation ◽  
Functional Connections ◽  
Pearson's Correlation

AbstractFunctional magnetic resonance imaging (fMRI)-based functional connectivity (FC) commonly characterizes the functional connections in the brain. Conventional quantification of FC by Pearson's correlation captures linear, time-domain dependencies among blood-oxygen-level-dependent (BOLD) signals. We examined measures to quantify FC by investigating: (i) Is Pearson's correlation sufficient to characterize FC? (ii) Can alternative measures better quantify FC? (iii) What are the implications of using alternative FC measures? FMRI analysis in healthy adult population suggested that: (i) Pearson's correlation cannot comprehensively capture BOLD inter-dependencies. (ii) Eight alternative FC measures were similarly consistent between task and resting-state fMRI, improved age-based classification and provided better association with behavioral outcomes. (iii) Formulated hypotheses were: first, in lieu of Pearson’s correlation, an augmented, composite and multi-metric definition of FC is more appropriate; second, canonical large-scale brain networks may depend on the chosen FC measure. A thorough notion of FC promises better understanding of variations within a given population.

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