Metastability of cortical BOLD signals in maturation and senescence

Naik, Shruti; Subbareddy, Oota; Banerjee, Arpan; Roy, Dipanjan; Bapi, Raju S.

doi:10.1109/ijcnn.2017.7966435

Cited by 7 publications

(6 citation statements)

References 29 publications

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“…This model posits that childhood autism is characterized by brain hyperconnectivity, whereas adolescent and adulthood autism is characterized by brain hypoconnectivity (B. Chen et al, 2020 ; Delmonte et al, 2013 ; Guo et al, 2017 ; Guo et al, 2019 ; Harlalka et al, 2018 ; Henry et al, 2018 ; Huang et al, 2015 ; Nomi & Uddin, 2015 ). These findings suggest atypical cortical developmental trajectories across the life span, and highlight the importance of taking different developmental stages into account when exploring the potential neural mechanisms of ASD (Gollo et al, 2017 ; Hahamy et al, 2015 ; Henry et al, 2018 ; Naik, Banerjee, Bapi, Deco, & Roy, 2017 ; Naik, Subbareddy, Banerjee, Roy, & Bapi, 2017 ).…”

Section: Introductionmentioning

confidence: 91%

Atypical core-periphery brain dynamics in autism

Roy

Uddin

2021

Network Neuroscience

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The intrinsic function of the human brain is dynamic, giving rise to numerous behavioral subtypes that fluctuate distinctively at multiple timescales. One of the key dynamical processes that takes place in the brain is the interaction between core-periphery brain regions, which undergoes constant fluctuations associated with developmental time frames. Core-periphery dynamical changes associated with macroscale brain network dynamics span multiple timescales and may lead to atypical behavior and clinical symptoms. For example, recent evidence suggests that brain regions with shorter intrinsic timescales are located at the periphery of brain networks (e.g. sensorimotor hand, face areas) and are implicated in perception and movement. On the contrary, brain regions with longer timescales are core hub regions. These hubs are important for regulating interactions between the brain and the body during self-related cognition and emotion. In this review, we summarize a large body of converging evidence derived from timeresolved fMRI studies in autism to characterize atypical core-periphery brain dynamics and how they relate to core and contextual sensory and cognitive profiles.

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Section: Introductionmentioning

confidence: 91%

Atypical core-periphery brain dynamics in autism

Roy

Uddin

2021

Network Neuroscience

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“…In recent years, there has been increasing research on the measurement of synchrony and metastability in functional magnetic resonance imaging (fMRI) signals [ 25 , 27 , 28 , 29 , 30 ]. Additionally, it is well-verified by a variety of studies that these indexes not only provide a mechanistic explanation of the origin of functional organization of the brain [ 28 , 31 , 32 , 33 , 34 ], but also help us understand the mechanistic causes of diseases [ 18 , 25 , 35 ], and as a significant predictor of diseases.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, there is also a published study that describes that some of these changes in metastability are associated with the suppression of a given network during task completion [ 26 ]. Moreover, a recent study by Naik et al assesses the changes in metastability to characterize age-effects on the dynamic repertoire of the functional networks at rest [ 29 ]. In a word, these two neurodynamic indexes facilitate the exploration of a larger dynamical repertoire of the brain and allow for the all-around visitation of functional states and dynamic responses to the external world [ 36 ].…”

Section: Introductionmentioning

confidence: 99%

Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI

Yang

Wei

et al. 2021

Brain Sciences

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In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much research has studied the analysis of neurodynamic indices, few have investigated its reliability. In this paper, the datasets from the Human Connectome Project have been used to explore the test–retest reliabilities of synchrony and metastability from multiple angles through intra-class correlation (ICC). The results showed that both of these indexes had fair test–retest reliability, but they are strongly affected by the field strength, the spatial resolution, and scanning interval, less affected by the temporal resolution. Denoising processing can help improve their ICC values. In addition, the reliability of neurodynamic indexes was affected by the node definition strategy, but these effects were not apparent. In particular, by comparing the test–retest reliability of different resting-state networks, we found that synchrony of different networks was basically stable, but the metastability varied considerably. Among these, DMN and LIM had a relatively higher test–retest reliability of metastability than other networks. This paper provides a methodological reference for exploring the brain dynamic neural activity by using synchrony and metastability in fMRI signals.

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“…Hence, any conceptual framework relating to the empirical observations of brain structure and function must be constrained to brain states that maximize metastability. Interestingly, we report that metastability is preserved across young and elderly (Fig 1); however, if the intermediate age range is taken into consideration, the relationship may be more U-shaped [Naik et al, 2017a, Naik et al, 2017b].…”

Section: Introductionmentioning

confidence: 99%

Neuromolecular interactions guiding homeostatic mechanisms underlying healthy ageing: A view from computational microscope

Saha

Chakraborty

Naskar

et al. 2023

Preprint

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Ageing brain is associated with a slow drift in structural network properties over the lifespan accompanied by reorganization in neuromolecular interactions giving rise to changes in global functional markers. What are the guiding principles of the homeostatic mechanisms that maintain the desired performance of functional neural circuits and preserve brain health during healthy ageing? We hypothesize that an ageing brain alters two primary neurotransmitters, glutamate and γ -aminobutyric acid (GABA), responsible for excitation-inhibition regulation, concomitant with anatomical demyelination to preserve critical neural dynamics that are necessary to uphold optimal network performance. Thus, often observed reorganized functional connectivity with age by several investigations is a byproduct of this adaptive process. We demonstrate that the adaptive mechanism is driven by the tuning of glutamate and GABA concentration over a very slow time scale (lifespan) that can be estimated by tracking criticality from coordinated neural dynamics at a resting state via a biophysically driven computational framework, introduced as a computational microscope. We validate several empirical observations and model predictions across three independent aging cohorts using this computational microscope. One of the key mechanisms we discover is the reduction in local glutamate levels employed by brain regions to maintain a homeostatic balance with aging. This is further supported by the invariance of measures of global functional integration during the healthy ageing process.

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Metastability of cortical BOLD signals in maturation and senescence

Cited by 7 publications

References 29 publications

Atypical core-periphery brain dynamics in autism

Atypical core-periphery brain dynamics in autism

Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI

Neuromolecular interactions guiding homeostatic mechanisms underlying healthy ageing: A view from computational microscope

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