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    Home > Active Ingredient News > Study of Nervous System > SCI Adv-He Xiaosong et al. reveal the physiological basis of network control theory applied to brain science research

    SCI Adv-He Xiaosong et al. reveal the physiological basis of network control theory applied to brain science research

    • Last Update: 2023-01-01
    • Source: Internet
    • Author: User
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    Written by He Xiaosong - Wang Sizhen, Fang Yiyi edited - The dynamic neural activity in Wang Sizhen's
    brain all the time is the physiological basis
    of all human psychology and behavior.
    In recent years, network control theory developed
    in the field of systems engineering has been widely used in brain science research, exploring the network mechanism of transmission of neurodynamic activities across brain regions by treating the brain as a complex system
    [1-3].

    。 Based on the characteristics of the brain's structural connection network, network control theory can not only identify which brain regions are more likely to influence other brain regions, but also explore the brain's energy consumption, also known as control energy, in these dynamic processes by simulating the transition between brain states

    .
    As an engineering concept, control energy refers to the inputs required to drive a change in the state of a system; When applied to simulate brain dynamics, there has been no answer
    to what kind of brain physiological activity this "input" corresponds to.
    The lack of physiological foundation will inevitably question the adaptability of network control theory in brain science research and hinder the development of
    its further application.

    Recently, He Xiaosong, a special researcher in the Department of Psychology of the University of Science and Technology of China, published a title entitled " Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy" By using unilateral temporal lobe epilepsy as an injury model, combined with multimodal imaging techniques such as diffusion-weighted imaging (dMRI) and positron emission tomography (PET), the association between abnormal control energy consumption and glucose metabolism abnormalities in the patient's brain was revealed, which provided a potential physiological basis
    for the application of network control theory to brain science research.


    As a human organ that accounts for only 2% by weight, the brain needs to consume more than 20% of the body's daily energy consumption to drive its internal dynamic processes and perform daily functions.

    So, is this biological form of energy expenditure, such as glucose metabolism, linked to "controlled energy" in the engineering sense? In order to answer this question, the team drew on neuropsychological research ideas to explore whether pathological damage associated with brain diseases can bring about covariant perturbations that control energy and glucose metabolism
    .
    As a pathological disorder of transient brain dynamic processes, seizures can bring long-term damage to the structure and function of the brain of patients, especially those with refractory epilepsy, and can be detected
    by neuroimaging technology even during the interictal period.
    Based on this feature, the team selected unilateral temporal lobe epilepsy, the most typical of refractory epilepsy, as the injury model in this project
    .

    Figure 1 Schematic diagram
    of research methods.
    (Source: He X, et al.
    , Sci Adv, 2022)

    Based on the structural connection network of patients and healthy controls, the team simulated two representative brain dynamic processes through network control theory.
    The amount of control energy required by the brain during these processes was estimated
    (Figure 1).

    To this end, based on previous research, the team defined
    8 representative brain states, in each state, one and only one brain functional network (intrinsic connectivity network) was activated
    .
    The first representative brain dynamic process studied by the team simulates the process from baseline level to the independent activation of specific brain function networks, which can be compared to the scene when the
    brain exercises specific cognitive functions.
    It was found that the brain of patients with temporal lobe epilepsy as a whole did not significantly differ
    in the level of control energy required to activate most brain functional networks compared with healthy controls.
    However, when the team simulated activating the limbic system network, it found that the control energy consumed by the patient group was significantly higher than that of the healthy control group
    .
    The limbic system network, which includes structures such as the hippocampus and amygdala, is the core area of temporal lobe seizures and transmission, and most often has structural and functional impairment, and additional energy resources are required to maintain the same level of activation as healthy controls, consistent with the research hypothesis
    .
    Subsequently, the team simulated and estimated the control energy required to activate the left and right limbic system networks, further verifying that this energy efficiency anomaly was highly consistent with the eccentricity of epileptogenic foci in patients,
    illustrating that pathological damage associated with unilateral temporal lobe epilepsy as a damage model can bring specific changes in controlling energy expenditure (Figure 2)

    Figure 2 By simulating brain dynamic processes through network control theory, it is found that patients with temporal lobe epilepsy have reduced energy efficiency in both global and local areas, and require higher control energy to achieve the same brain state transformation
    than healthy controls.
    (Source: He X, et al.
    , Sci Adv, 2022)

    The second representative brain dynamic process studied by the team, It simulates the transition of the brain between the activation states of different brain functional networks, which can be analogous to the brain switching
    between various cognitive tasks.
    By estimating the average controlled energy expenditure of each brain region in support of these state transitions, the team compared and identified which brain regions with epilepsy had energy efficiency abnormalities
    .
    The results showed that compared with the healthy control, the patients in
    the temporal lobe brain region of the seven limbic systems such as hippocampus and amygdala on the affected side needed to consume more control energy to maintain the predetermined brain dynamic process
    .
    To verify that this result is independent of the selection of brain activation states, the team further simulated and estimated the average energy consumption of each brain region under dynamic transitions between 100,000 random brain activation states, and finally observed consistent results
    (Figure 2).

    As a result, the team was able to focus specific changes in temporal lobe epilepsy that control energy expenditure to specific brain regions and lay the groundwork
    for subsequent analysis.

    Finally, the team analyzed whether seven affected brain regions with abnormal energy efficiency, such as hippocampus and amygdala, also had abnormal
    glucose metabolism.
    To this end, the team collected the PET
    imaging data of 18F-fluorodeoxyglucose in the patient's interictal period, and found that these brain regions did have hypometabolism relative to their contralateral mirror region by calculating the biasing coefficient of glucose metabolism, suggesting that the baseline metabolic level of these brain regions was abnormally low
    。 Through correlation analysis, the team confirmed that there is a negative correlation between glucose metabolism and control of energy lateralization coefficients in multiple brain regions such as hippocampus, amygdala, parahippocampal gyrus, and temporoparietal, which also means that in order to achieve the same level of activation, a lower metabolic baseline may lead to higher energy demand, which can be quantified by controlling energy
    Especially in the hippocampus, higher structural atrophy is associated with lower baseline glucose metabolism and higher controlled energy expenditure, and glucose metabolism levels can completely mediate the link
    between structural atrophy and controlled energy expenditure.
    This suggests that damage to hippocampal structure may lead to a decrease in baseline glucose metabolism and ultimately higher energy costs in sustaining dynamic brain processes
    (Figure 3).


    Figure 3 Baseline glucose metabolism levels are negatively correlated
    with controlled energy expenditure.
    (Source: He X, et al.
    , Sci Adv, 2022)

    Article conclusion and discussion, inspiration and prospects

    In summary, this paper uses unilateral temporal lobe epilepsy as an injury model to provide a unified theoretical framework for the relationship between brain structural integrity, glucose metabolism baseline, and the control energy required to maintain brain dynamic processes, and for the first time provides a potential physiological explanation
    for "energy control" 。 It is worth pointing out that this damage model-based research method, which explores the correlation between glucose metabolism and energy control at the individual level, is not enough to explain the direct causal link
    between the two.
    In future studies, it is necessary to explore, at the individual level, whether the controlled energy required by the brain to perform specific state transitions in the task state is related
    to the level of glucose metabolism at the same time.
    In particular, it is necessary to modulate cognitive load by setting different task difficulty and record whether there are covariability changes
    between the two.
    This series of work will lay the foundation for the further widespread application of network control theory in the
    field of brain science.


    Original link: Dr.
    style="outline: 0px;font-size: 12px;color: rgb(172, 57, 255);" _mstmutation="1" _istranslated="1">
    He Xiaosong (Photo courtesy of He Xiaosong Laboratory, Department of Psychology, University of Science and Technology of China)
    About the author (swipe up and down to read).

    Dr.
    Xiaosong He is a specially appointed researcher and doctoral supervisor of the Department of Psychology, University of Science and Technology of China, and a member of the Working Group of the Epilepsy Surgery Network of
    the International Union Against Epilepsy.
    Mainly engaged in clinical related research in cognitive psychology, using cognitive assessment and multimodal magnetic resonance imaging technology, combined with network science analysis methods, to explore the pathogenesis and prognosis
    of epilepsy and other neurological diseases.
    As first author and co-author in
    Science Advances, Brain, Neurology, Nature Methods, Nature Communications and other international mainstream academic journals published 36 research papers, and served as Epilepsia, Reviewer
    for journals such as Network Neuroscience, NeuroImage, and Neurology 。 He has received many grants and awards such as the National Natural Science Foundation of China, the China Postdoctoral Science Foundation, the American Epilepsy Association Postdoctoral Research Fellowship and the Young Investigator Award




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