Differentiating ADHD subtypes and simulation of in silico therapeutic neuronal excitation in a whole-brain nonlinear dynamic modelling frame-work

ABSTRACTRecent advances in non-linear computational and dynamical modelling have opened up the possibility to parametrize dynamic neural mechanisms that drive complex behavior. Importantly, building models of neuronal processes is of key importance to fully understand disorders of the brain as it may provide a quantitative platform that is capable of binding multiple neurophysiological processes to phenotype profiles. In this study, we apply a newly developed adaptive frequency-based model of whole-brain oscillations to resting-state fMRI data acquired from healthy controls and a cohort of attention deficit hyperactivity disorder (ADHD) subjects. As expected, we found that healthy control subjects differed from ADHD in terms of attractor dynamics. However, we also found a marked dichotomy in neural dynamics within the ADHD cohort. Next, we classified the ADHD subgroup according to the level of distance of each individual’s empirical network from the two model-based simulated networks. Critically, the model was mirrored in the empirical behavior data with the two ADHD subgroups displaying distinct behavioral phenotypes related to emotional instability (i.e., depression and hypomanic personality traits). Finally, we investigated the applicability and feasibility of our whole-brain model in a therapeutic setting by conducting in silico excitatory stimulations to mimic clinical transcranial magnetic stimulation paradigms in ADHD. We tested the effect of stimulating any individual brain region on key network measures and its contribution in rectifying the brain dynamics to that of the healthy brain, separately for each ADHD subgroup. This showed that this was indeed possible for both subgroups. However, the current effect sizes were small suggesting that the stimulation protocol needs to be tailored at the individual level. These findings demonstrate the potential of this new modelling framework to unveil hidden neurophysiological profiles and establish tailored clinical interventions.

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The effect of external stimulation on functional networks in the aging healthy human brain

10.1101/2021.11.19.469206 ◽

2021 ◽

Author(s):

Anira Escrichs ◽

Yonatan Sanz Perl ◽

Noelia Martinez-Molina ◽

Carles Biarnes ◽

Josep Garre ◽

...

Keyword(s):

In Silico ◽

Brain Area ◽

Resting State Fmri ◽

Brain Dynamics ◽

Healthy Human ◽

Whole Brain ◽

External Stimulation ◽

Rich Club ◽

Brain States ◽

The Brain

Understanding the brain changes occurring during aging can provide new insights for developing treatments that alleviate or reverse cognitive decline. Neurostimulation techniques have emerged as potential treatments for brain disorders and to improve cognitive functions. Nevertheless, given the ethical restrictions of neurostimulation approaches, in silico perturbation protocols based on causal whole-brain models are fundamental to gaining a mechanistic understanding of brain dynamics. Furthermore, this strategy could serve as a more specific biomarker relating local activity with global brain dynamics. Here, we used a large resting-state fMRI dataset divided into middle-aged (N=310, aged < 65 years) and older adults (N=310, aged >= 65) to characterize brain states in each group as a probabilistic metastable substate (PMS) space, each with a probabilistic occurrence and frequency. Then, we fitted the PMS to a whole-brain model and applied in silico stimulations with different intensities in each node to force transitions from the brain states of the older group to the middle-age group. We found that the precuneus, a brain area belonging to the default mode network and the rich club, was the best stimulation target. These findings might have important implications for designing neurostimulation interventions to revert the effects of aging on whole-brain dynamics.

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Modelling cultural systems and selective filters

10.31219/osf.io/hzmqg ◽

2020 ◽

Author(s):

Fredrik Jansson ◽

Elliot Aguilar ◽

Alberto Acerbi ◽

Magnus Enquist

Keyword(s):

Cultural Change ◽

Cultural Evolution ◽

Selection Process ◽

Change Models ◽

Individual Level ◽

Modelling Framework ◽

Structure Changes ◽

Cultural Systems ◽

Cultural Domain ◽

The Individual

A specific goal of the field of cultural evolution is to understand how processes of transmission and selection at the individual level lead to population-wide patterns of cultural diversity and change. Models of cultural evolution have typically assumed that traits are independent of one another and essentially exchangeable. But culture has a structure: traits bear relationships to one another that affect the transmission and selection process itself. Here we introduce a modelling framework to explore the effect of cultural structure on the process of learning. Through simulations, we find that introducing this simple structure changes the cultural dynamics. Based on a basic filtering mechanism for parsing these relationships, more elaborate cultural filters emerge. In a mostly incompatible cultural domain of traits, these filters organise culture into mostly (but not fully) consistent and stable systems. Incompatible domains produce small homogeneous cultures, while more compatibility increases size, diversity, and group divergence. When individuals copy based on a trait's features (here, its compatibility relationships) they produce more homogeneous cultures than when they copy based on the agent carrying the cultural trait. We discuss the implications of considering cultural systems and filters in the dynamics of cultural change.

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Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

10.1101/2021.02.08.430334 ◽

2021 ◽

Author(s):

Takashi Nakano ◽

Masahiro Takamura ◽

Haruki Nishimura ◽

Maro Machizawa ◽

Naho Ichikawa ◽

...

Keyword(s):

Resting State ◽

Brain Connectivity ◽

Brain Activity ◽

Resting State Fmri ◽

Brain Regions ◽

Posterior Cingulate Cortex ◽

Fmri Data ◽

Independent Test ◽

The Individual ◽

The Brain

AbstractNeurofeedback (NF) aptitude, which refers to an individual’s ability to change its brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical NF applications. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude independent of NF-targeting brain regions. We combined the data in fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect the resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Next we validated the prediction model using independent test data from another site. The result showed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting NF aptitude may be involved in the attentional mode-orientation modulation system’s characteristics in task-free resting-state brain activity.

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Coupling between cerebrovascular oscillations and CSF flow fluctuations during wakefulness: An fMRI study

Journal of Cerebral Blood Flow & Metabolism ◽

10.1177/0271678x221074639 ◽

2022 ◽

pp. 0271678X2210746

Author(s):

Ho-Ching (Shawn) Yang ◽

Ben Inglis ◽

Thomas M Talavage ◽

Vidhya Vijayakrishnan Nair ◽

Jinxia (Fiona) Yao ◽

...

Keyword(s):

Time Delays ◽

Cerebral Blood Volume ◽

Low Frequency ◽

Nrem Sleep ◽

Resting State Fmri ◽

Csf Flow ◽

Flow Fluctuations ◽

Fmri Study ◽

The Individual ◽

The Brain

It is commonly believed that cerebrospinal fluid (CSF) movement is facilitated by blood vessel wall movements (i.e., hemodynamic oscillations) in the brain. A coherent pattern of low frequency hemodynamic oscillations and CSF movement was recently found during non-rapid eye movement (NREM) sleep via functional MRI. This finding raises other fundamental questions: 1) the explanation of coupling between hemodynamic oscillations and CSF movement from fMRI signals; 2) the existence of the coupling during wakefulness; 3) the direction of CSF movement. In this resting state fMRI study, we proposed a mechanical model to explain the coupling between hemodynamics and CSF movement through the lens of fMRI. Time delays between CSF movement and global hemodynamics were calculated. The observed delays between hemodynamics and CSF movement match those predicted by the model. Moreover, by conducting separate fMRI scans of the brain and neck, we confirmed the low frequency CSF movement at the fourth ventricle is bidirectional. Our finding also demonstrates that CSF movement is facilitated by changes in cerebral blood volume mainly in the low frequency range, even when the individual is awake.

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The Lamellar Structure of the Brain Fiber Pathways

Neural Computation ◽

10.1162/neco_a_00896 ◽

2016 ◽

Vol 28 (11) ◽

pp. 2533-2556 ◽

Cited By ~ 8

Author(s):

Vitaly L. Galinsky ◽

Lawrence R. Frank

Keyword(s):

Angular Distribution ◽

Vector Field ◽

Lamellar Structure ◽

Structural Connectivity ◽

High Confidence ◽

Whole Brain ◽

Fiber Tracts ◽

The Individual ◽

The Brain

We present a quantitative statistical analysis of pairwise crossings for all fibers obtained from whole brain tractography that confirms with high confidence that the brain grid theory (Wedeen et al., 2012a ) is not supported by the evidence. The overall fiber tracts structure appears to be more consistent with small angle treelike branching of tracts rather than with near-orthogonal gridlike crossing of fiber sheets. The analysis uses our new method for high-resolution whole brain tractography that is capable of resolving fibers crossing of less than 10 degrees and correctly following a continuous angular distribution of fibers even when the individual fiber directions are not resolved. This analysis also allows us to demonstrate that the whole brain fiber pathway system is very well approximated by a lamellar vector field, providing a concise and quantitative mathematical characterization of the structural connectivity of the human brain.

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Whole-brain dynamics in aging: disruptions in functional connectivity and the role of the rich club

10.1101/2020.06.29.164343 ◽

2020 ◽

Author(s):

Anira Escrichs ◽

Carles Biarnes ◽

Josep Garre-Olmo ◽

José Manuel Fernández-Real ◽

Rafel Ramos ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Resting State Fmri ◽

Brain Dynamics ◽

Whole Brain ◽

Rich Club ◽

Brain Functional Network ◽

Age Related ◽

Age Range ◽

The Brain

AbstractNormal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state fMRI studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent (BOLD) signals to analyze resting-state fMRI data from 620 subjects divided into two groups (‘middle-age group’ (n=310); age range, 50-65 years vs. ‘older group’ (n=310); age range, 66-91 years). Applying the Intrinsic-Ignition Framework to assess the effect of spontaneous local activation events on local-global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.

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Lost in translation

F1000Research ◽

10.12688/f1000research.15020.2 ◽

2019 ◽

Vol 7 ◽

pp. 620 ◽

Cited By ~ 1

Author(s):

Parashkev Nachev ◽

Geraint Rees ◽

Richard Frackowiak

Keyword(s):

High Performance ◽

Large Scale ◽

Explanatory Models ◽

Neural Systems ◽

Individual Level ◽

Large Scale Data ◽

The Individual ◽

Adaptive Nature ◽

Lost In Translation ◽

The Brain

Translation in cognitive neuroscience remains beyond the horizon, brought no closer by supposed major advances in our understanding of the brain. Unless our explanatory models descend to the individual level—a cardinal requirement for any intervention—their real-world applications will always be limited. Drawing on an analysis of the informational properties of the brain, here we argue that adequate individualisation needs models of far greater dimensionality than has been usual in the field. This necessity arises from the widely distributed causality of neural systems, a consequence of the fundamentally adaptive nature of their developmental and physiological mechanisms. We discuss how recent advances in high-performance computing, combined with collections of large-scale data, enable the high-dimensional modelling we argue is critical to successful translation, and urge its adoption if the ultimate goal of impact on the lives of patients is to be achieved.

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Mapping of Whole-Brain Resting-State Networks with Half-Millimetre Resolution

10.1101/2021.03.09.434629 ◽

2021 ◽

Author(s):

Seong Dae Yun ◽

Patricia Pais-Roldán ◽

Nicola Palomero-Gallagher ◽

N. Jon Shah

Keyword(s):

Spatial Resolution ◽

Resting State ◽

Granular Layer ◽

Resting State Fmri ◽

Resting State Networks ◽

Whole Brain ◽

Anatomical Structures ◽

Functional Image ◽

Fmri Session ◽

The Brain

AbstractResting-state fMRI has been used in numerous studies to map networks in the brain that employ spatially disparate regions. However, attempts to map networks with high spatial resolution have been hampered by conflicting technical demands and associated problems. Results from recent fMRI studies have shown that spatial resolution remains around 0.7 × 0.7 × 0.7 mm3, with only partial brain coverage. This work presents a novel fMRI method, TR-external EPI with keyhole (TR-external EPIK), which can provide a nominal spatial resolution of 0.51 × 0.51 × 1.00 mm3 (0.26 mm3 voxel) with whole-brain coverage. TR-external EPIK enabled the identification of various resting-state networks distributed throughout the brain from a single fMRI session, with mapping fidelity onto the grey matter at 7T. The high-resolution functional image further revealed mesoscale anatomical structures, such as small cerebral vessels and the internal granular layer of the cortex within the postcentral gyrus.

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Coupling brain cerebrovascular oscillations and CSF flow during wakefulness: An fMRI study

10.1101/2021.03.29.437406 ◽

2021 ◽

Author(s):

Ho-Ching Shawn Yang ◽

Ben Inglis ◽

Tom M Talavage ◽

Vidhya Vijayakrishnan Nair ◽

Jinxia Fiona Yao ◽

...

Keyword(s):

Driving Forces ◽

Low Frequency ◽

Nrem Sleep ◽

Resting State Fmri ◽

Csf Flow ◽

Waste Products ◽

Fmri Study ◽

Flow Through ◽

The Individual ◽

The Brain

Cerebral spinal fluid (CSF) plays an important role in the clearance of metabolic waste products from the brain, yet the driving forces of CSF flow are not fully understood. It is commonly believed that CSF flow is facilitated by the blood vessel wall movements (i.e., hemodynamic oscillations) in the brain. A coherent pattern of low frequency hemodynamic oscillations and CSF flow was found recently during non-rapid eye movement sleep (NREM) sleep via functional MRI. However, questions remain regarding 1) the explanation of coupling between hemodynamic oscillations and CSF flow using fMRI signals; 2) the existence of the coupling during wakefulness; 3) the direction of CSF flow. In this resting state fMRI study, we proposed a mechanical model to explain the coupling between hemodynamics and CSF flow through the lens of fMRI. We found that the observed delays between these two signals match those predicted by the model. Moreover, by conducting separated fMRI scans of the brain and neck, we confirmed the low frequency CSF flow at the fourth ventricle is bidirectional. Our finding also demonstrates that CSF flow is facilitated by hemodynamic oscillations mainly in the low frequency range, even when the individual is awake.

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Addressing the reliability fallacy: Similar group effects may arise from unreliable individual effects

10.1101/215053 ◽

2017 ◽

Author(s):

Juliane H. Fröhner ◽

Vanessa Teckentrup ◽

Michael N. Smolka ◽

Nils B. Kroemer

Keyword(s):

Large Scale ◽

Intertemporal Choice ◽

Subjective Evaluation ◽

Brain Activation ◽

Activation Patterns ◽

Individual Level ◽

The Individual ◽

Global And Local ◽

Main Effects ◽

The Brain

AbstractTo cast valid predictions of future behavior or diagnose disorders, the reliable measurement of a “biomarker” such as the brain activation to prospective reward is a prerequisite. Surprisingly, only a small fraction of functional magnetic resonance imaging (fMRI) studies report or cite the reliability of brain activation maps involved in group analyses. Here, using simulations and exemplary longitudinal data of 126 healthy adolescents performing an intertemporal choice task, we demonstrate that reproducing a group activation map over time is not a sufficient indication of reliable measurements at the individual level. Instead, selecting regions based on significant main effects at the group level may yield estimates that fail to reliably capture individual variance in the subjective evaluation of an offer. Collectively, our results call for more attention on the reliability of supposed biomarkers at the level of the individual. Thus, caution is warranted in employing brain activation patterns prematurely for clinical applications such as diagnosis or tailored interventions before their reliability has been conclusively established by large-scale studies. To facilitate assessing and reporting of the reliability of fMRI contrasts in future studies, we provide a toolbox that incorporates common measures of global and local reliability.

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