The effective connectivity of the default mode network following moderate traumatic brain injury

Rahman, Muhammad Riddha Abdul; Hamid, Aini Ismafairus Abd; Noh, Nor Azila; Idris, Zamzuri; Abdullah, J M

doi:10.1088/1742-6596/1497/1/012008

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…Moreover, the TBI group displayed more inhibitory connectivity compared to HC. This finding is in line with our previous study, which found more negative ECs in the TBI group with higher strength ( Abdul Rahman et al, 2020 ). The extrinsic inhibitory connections are the negative influence exerted by one region to another, also known as the baseline inhibition ( Stephan and Friston, 2010 ), due to the population of inhibitory neurons.…”

Section: Discussionsupporting

confidence: 94%

Alteration in the Functional Organization of the Default Mode Network Following Closed Non-severe Traumatic Brain Injury

et al. 2022

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The debilitating effect of traumatic brain injury (TBI) extends years after the initial injury and hampers the recovery process and quality of life. In this study, we explore the functional reorganization of the default mode network (DMN) of those affected with non-severe TBI. Traumatic brain injury (TBI) is a wide-spectrum disease that has heterogeneous effects on its victims and impacts everyday functioning. The functional disruption of the default mode network (DMN) after TBI has been established, but its link to causal effective connectivity remains to be explored. This study investigated the differences in the DMN between healthy participants and mild and moderate TBI, in terms of functional and effective connectivity using resting-state functional magnetic resonance imaging (fMRI). Nineteen non-severe TBI (mean age 30.84 ± 14.56) and twenty-two healthy (HC; mean age 27.23 ± 6.32) participants were recruited for this study. Resting-state fMRI data were obtained at the subacute phase (mean days 40.63 ± 10.14) and analyzed for functional activation and connectivity, independent component analysis, and effective connectivity within and between the DMN. Neuropsychological tests were also performed to assess the cognitive and memory domains. Compared to the HC, the TBI group exhibited lower activation in the thalamus, as well as significant functional hypoconnectivity between DMN and LN. Within the DMN nodes, decreased activations were detected in the left inferior parietal lobule, precuneus, and right superior frontal gyrus. Altered effective connectivities were also observed in the TBI group and were linked to the diminished activation in the left parietal region and precuneus. With regard to intra-DMN connectivity within the TBI group, positive correlations were found in verbal and visual memory with the language network, while a negative correlation was found in the cognitive domain with the visual network. Our results suggested that aberrant activities and functional connectivities within the DMN and with other RSNs were accompanied by the altered effective connectivities in the TBI group. These alterations were associated with impaired cognitive and memory domains in the TBI group, in particular within the language domain. These findings may provide insight for future TBI observational and interventional research.

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Section: Discussionsupporting

confidence: 94%

Alteration in the Functional Organization of the Default Mode Network Following Closed Non-severe Traumatic Brain Injury

et al. 2022

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Stimulation-mediated reverse engineering of silent neural networks

Ren

Hai

2021

Preprint

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Stimulation-mediated reverse engineering of silent neural networks

Ren

Bok

Vareberg

et al. 2023

Journal of Neurophysiology

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Reconstructing connectivity of neuronal networks from single cell activity is essential to understanding brain function, but the challenge of deciphering connections from populations of silent neurons has been largely unmet. We use a simple feedforward toy network to demonstrate a protocol for deriving connectivity of simulated silent neuronal networks using stimulation combined with a supervised learning algorithm. We show that asynchronous stimulation is favorable for inferring connection weights with high fidelity and predicting spike trains at the single-spike and single-cell level with high accuracy. We then apply our method on rat cortical recordings fed through a hybrid circuit of heterogeneously connected leaky integrate-and-fire neurons firing at typical lognormal distributions, and demonstrate significant degrees of improved performance during stimulation for multiple subpopulations. These testable predictions about the number and protocol of the required stimulations are expected to enhance future efforts for deriving neuronal connectivity and drive new experiments to better understand brain function.

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The effective connectivity of the default mode network following moderate traumatic brain injury

Cited by 3 publications

References 11 publications

Alteration in the Functional Organization of the Default Mode Network Following Closed Non-severe Traumatic Brain Injury

Alteration in the Functional Organization of the Default Mode Network Following Closed Non-severe Traumatic Brain Injury

Stimulation-mediated reverse engineering of silent neural networks

Stimulation-mediated reverse engineering of silent neural networks

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