The Study on Brain Regions in Patients With Depression Based on Co-Activation Patterns and fMRI

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.

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The Relationship between BOLD and Neural Activity Arises from Temporally Sparse Events

10.1101/644419 ◽

2019 ◽

Author(s):

Xiaodi Zhang ◽

Wen-Ju Pan ◽

Shella Dawn Keilholz

Keyword(s):

Neural Activity ◽

Field Potential ◽

High Amplitude ◽

Brain Regions ◽

Functional Networks ◽

Time Varying ◽

Bold Signal ◽

Activation Patterns ◽

Amplitude Data ◽

Co Activation

Resting state functional magnetic resonance (rs-fMRI) imaging offers insights into how different brain regions are connected into functional networks. It was recently shown that networks that are almost identical to the ones created from conventional correlation analysis can be obtained from a subset of high-amplitude data, suggesting that the functional networks may be driven by instantaneous co-activations of multiple brain regions rather than ongoing oscillatory processes. The rs-fMRI studies, however, rely on the blood oxygen level dependent (BOLD) signal, which is only indirectly sensitive to neural activity through neurovascular coupling. To provide more direct evidence that the neuronal co-activation events produce the time-varying network patterns seen in rs-fMRI studies, we examined the simultaneous rs-fMRI and local field potential (LFP) recordings in rats performed in our lab over the past several years. We developed complementary analysis methods that focus on either the temporal or spatial domain, and found evidence that the interaction between LFP and BOLD may be driven by instantaneous co-activation events as well. BOLD maps triggered on high-amplitude LFP events resemble co-activation patterns created from rs-fMRI data alone, though the co-activation time points are defined differently in the two cases. Moreover, only LFP events that fall into the highest or lowest thirds of the amplitude distribution result in a BOLD signal that can be distinguished from noise. These findings provide evidence of an electrophysiological basis for the time-varying co-activation patterns observed in previous studies.

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Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed

Frontiers in Neuroscience ◽

10.3389/fnins.2021.700171 ◽

2021 ◽

Vol 15 ◽

Author(s):

Ignacio Cifre ◽

Maria T. Miller Flores ◽

Lucia Penalba ◽

Jeremi K. Ochab ◽

Dante R. Chialvo

Keyword(s):

Functional Connectivity ◽

Brain Regions ◽

Significant Loss ◽

Subsequent Work ◽

Activation Patterns ◽

Nonlinear Functional ◽

Co Activation ◽

Neuro Imaging ◽

Experimental Findings ◽

Correlation Properties

The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations.

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Beyond Consensus: Embracing Heterogeneity in Curated Neuroimaging Meta-Analysis

10.1101/149567 ◽

2017 ◽

Author(s):

Gia H. Ngo ◽

Simon B. Eickhoff ◽

Minh Nguyen ◽

Gunes Sevinc ◽

Peter T. Fox ◽

...

Keyword(s):

Mental Disorder ◽

Topic Model ◽

Meta Analysis ◽

Brain Regions ◽

Small Scale ◽

Functional Domain ◽

Seed Region ◽

Activation Patterns ◽

Co Activation ◽

Meta Analyses

AbstractCoordinate-based meta-analysis can provide important insights into mind-brain relationships. A popular approach for curated small-scale meta-analysis is activation likelihood estimation (ALE), which identifies brain regions consistently activated across a selected set of experiments, such as within a functional domain or mental disorder. ALE can also be utilized in meta-analytic co-activation modeling (MACM) to identify brain regions consistently co-activated with a seed region. Therefore, ALE aims to find consensus across experiments, treating heterogeneity across experiments as noise. However, heterogeneity within an ALE analysis of a functional domain might indicate the presence of functional sub-domains. Similarly, heterogeneity within a MACM analysis might indicate the involvement of a seed region in multiple co-activation patterns that are dependent on task contexts. Here, we demonstrate the use of the author-topic model to automatically determine if heterogeneities within ALE-type meta-analyses can be robustly explained by a small number of latent patterns. In the first application, the author-topic modeling of experiments involving self-generated thought (N = 179) revealed cognitive components fractionating the default network. In the second application, the author-topic model revealed that the left inferior frontal junction (IFJ) participated in multiple task-dependent co-activation patterns (N = 323). Furthermore, the author-topic model estimates compared favorably with spatial independent component analysis in both simulation and real data. Overall, the results suggest that the author-topic model is a flexible tool for exploring heterogeneity in ALE-type meta-analyses that might arise from functional sub-domains, mental disorder subtypes or task-dependent co-activation patterns. Code for this study is publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/meta-analysis/Ngo2019_AuthorTopic).

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How (not) to cross a boundary: Crosslinguistic influence in simultaneous bilingual children's event construal

Bilingualism Language and Cognition ◽

10.1017/s1366728921000298 ◽

2021 ◽

pp. 1-13

Author(s):

Helen Engemann

Keyword(s):

Production Process ◽

Age Groups ◽

Boundary Crossing ◽

Bilingual Children ◽

Activation Patterns ◽

Motion Event ◽

Co Activation ◽

Crosslinguistic Influence ◽

Event Construal ◽

Two Age Groups

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.

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A rigorous approach for testing the constructionist hypotheses of brain function

Behavioral and Brain Sciences ◽

10.1017/s0140525x1100149x ◽

2012 ◽

Vol 35 (3) ◽

pp. 148-149 ◽

Cited By ~ 11

Author(s):

Gopikrishna Deshpande ◽

K. Sathian ◽

Xiaoping Hu ◽

Joseph A. Buckhalt

Keyword(s):

Granger Causality ◽

Strong Evidence ◽

Bayesian Modeling ◽

Brain Function ◽

Brain Regions ◽

Causal Modeling ◽

Dynamic Causal Modeling ◽

Rigorous Approach ◽

Target Article ◽

Co Activation

AbstractAlthough the target article provides strong evidence against the locationist view, evidence for the constructionist view is inconclusive, because co-activation of brain regions does not necessarily imply connectivity between them. We propose a rigorous approach wherein connectivity between co-activated regions is first modeled using exploratory Granger causality, and then confirmed using dynamic causal modeling or Bayesian modeling.

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Mapping the common and distinct neural correlates of visual, rule and motor conflict

10.1101/2020.11.19.388231 ◽

2020 ◽

Author(s):

Bryony Goulding Mew ◽

Darije Custovic ◽

Eyal Soreq ◽

Romy Lorenz ◽

Ines Violante ◽

...

Keyword(s):

Region Of Interest ◽

Neural Correlates ◽

Brain Regions ◽

Control Mechanisms ◽

Activation Patterns ◽

The Common ◽

Full Factorial ◽

The Brain ◽

Categorical Scale ◽

Conflict Types

AbstractFlexible behaviour requires cognitive-control mechanisms to efficiently resolve conflict between competing information and alternative actions. Whether a global neural resource mediates all forms of conflict or this is achieved within domainspecific systems remains debated. We use a novel fMRI paradigm to orthogonally manipulate rule, response and stimulus-based conflict within a full-factorial design. Whole-brain voxelwise analyses show that activation patterns associated with these conflict types are distinct but partially overlapping within Multiple Demand Cortex (MDC), the brain regions that are most commonly active during cognitive tasks. Region of interest analysis shows that most MDC sub-regions are activated for all conflict types, but to significantly varying levels. We propose that conflict resolution is an emergent property of distributed brain networks, the functional-anatomical components of which place on a continuous, not categorical, scale from domain-specialised to domain general. MDC brain regions place towards one end of that scale but display considerable functional heterogeneity.

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Rest-task Modulation of fMRI-derived Global Signal Topography is Mediated by Transient Co-activation Patterns

10.1101/798819 ◽

2019 ◽

Cited By ~ 1

Author(s):

Jianfeng Zhang ◽

Zirui Huang ◽

Shankar Tumati ◽

Georg Northoff

Keyword(s):

Resting State ◽

Resting State Fmri ◽

Peak Period ◽

Physiological Noise ◽

Activation Patterns ◽

Global Signal ◽

Co Activation ◽

Human Connectome Project ◽

Partial Dissociation ◽

Signal Correlation

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.

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Neural tracking of subjective value under riskand ambiguity in adolescence

Cognitive Affective & Behavioral Neuroscience ◽

10.3758/s13415-019-00749-5 ◽

2019 ◽

Vol 19 (6) ◽

pp. 1364-1378 ◽

Cited By ~ 1

Author(s):

Neeltje E. Blankenstein ◽

Anna C. K. van Duijvenvoorde

Keyword(s):

Brain Activation ◽

Superior Temporal Gyrus ◽

Building Blocks ◽

Brain Regions ◽

Activation Patterns ◽

Subjective Value ◽

Adolescent Risk ◽

Dorsolateral Prefrontal ◽

Adolescent Sample ◽

Superior Parietal Cortex

Abstract Although many neuroimaging studies on adolescent risk taking have focused on brain activation during outcome valuation, less attention has been paid to the neural correlates of choice valuation. Subjective choice valuation may be particularly influenced by whether a choice presents risk (known probabilities) or ambiguity (unknown probabilities), which has rarely been studied in developmental samples. Therefore, we examined the neural tracking of subjective value during choice under risk and ambiguity in a large sample of adolescents (N = 188, 12–22 years). Specifically, we investigated which brain regions tracked subjective value coding under risk and ambiguity. A model-based approach to estimate individuals’ risk and ambiguity attitudes showed prominent variation in individuals’ aversions to risk and ambiguity. Furthermore, participants subjectively experienced the ambiguous options as being riskier than the risky options. Subjective value tracking under risk was coded by activation in ventral striatum and superior parietal cortex. Subjective value tracking under ambiguity was coded by dorsolateral prefrontal cortex (PFC) and superior temporal gyrus activation. Finally, overlapping activation in the dorsomedial PFC was observed for subjective value under both conditions. Overall, this is the first study to chart brain activation patterns for subjective choice valuation under risk and ambiguity in an adolescent sample, which shows that the building blocks for risk and ambiguity processing are already present in early adolescence. Finally, we highlight the potential of combining behavioral modeling with fMRI for investigating choice valuation in adolescence, which may ultimately aid in understanding who takes risks and why.

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Functional brain organization for visual search in ASD

Journal of the International Neuropsychological Society ◽

10.1017/s1355617708081356 ◽

2008 ◽

Vol 14 (6) ◽

pp. 990-1003 ◽

Cited By ~ 33

Author(s):

BRANDON KEEHN ◽

LAURIE BRENNER ◽

ERICA PALMER ◽

ALAN J. LINCOLN ◽

RALPH-AXEL MÜLLER

Keyword(s):

Visual Search ◽

Brain Regions ◽

Autism Spectrum ◽

Neural Mechanisms ◽

Search Efficiency ◽

Typically Developing ◽

Brain Organization ◽

Activation Patterns ◽

Set Size ◽

Functional Brain Organization

AbstractAlthough previous studies have shown that individuals with autism spectrum disorder (ASD) excel at visual search, underlying neural mechanisms remain unknown. This study investigated the neurofunctional correlates of visual search in children with ASD and matched typically developing (TD) children, using an event-related functional magnetic resonance imaging design. We used a visual search paradigm, manipulating search difficulty by varying set size (6, 12, or 24 items), distractor composition (heterogeneous or homogeneous) and target presence to identify brain regions associated with efficient and inefficient search. While the ASD group did not evidence accelerated response time (RT) compared with the TD group, they did demonstrate increased search efficiency, as measured by RT by set size slopes. Activation patterns also showed differences between ASD group, which recruited a network including frontal, parietal, and occipital cortices, and the TD group, which showed less extensive activation mostly limited to occipito-temporal regions. Direct comparisons (for both homogeneous and heterogeneous search conditions) revealed greater activation in occipital and frontoparietal regions in ASD than in TD participants. These results suggest that search efficiency in ASD may be related to enhanced discrimination (reflected in occipital activation) and increased top-down modulation of visual attention (associated with frontoparietal activation). (JINS, 2008, 14, 990–1003.)

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