Previous studies showed that both healthy and pathological aging are associated with changes in brain structure and function of the mature human brain. The most prominent anatomical alteration are changes in prefrontal cortex morphology, volume loss and reduced white-matter integrity and hippocampal atrophy. Cognitive decline affects mainly the performance of episodic memory, speed of sensory information processing, working memory, inhibitory function and long-term memory. It has been also proposed that due to the aforementioned changes the aging brain engages in compensatory brain mechanism such as a broader activation of cortical regions (mainly frontal) rather than specialized activation. Evidence suggests that similar changes occur with pathological aging but to a greater extent. In this case information flow is disrupted due to neurodegeneration, functional activation of posterior (occipito-temporal) regions is decreased and as a consequence the brain fails to process sensorial input in the ventral pathway and cognitive deficits appear.
In the last years, functional alterations associated with aging have been studied using the mathematical notion of graph theory that offers an integrative approach since it examines different properties of the brain network: 1) Organization level 2) amount of local information processing, 3) information flow 4) cortical community structure and 5) identification of functional / anatomical hubs. So, graph theory offers an attractive way to model brain networks organization and to quantify their pathological deviations.
Previous studies have already employed this mathematical notion and demonstrated that age-related neurodegeneration is often accompanied by loss of optimal network organization either due to diminished local information processing or due to progressive isolation of distant brain regions. They have also found that changes in network properties may be present even in the preclinical phase, which could be taken as a biological marker of disease.
Despite the great envisaged impact and the importance of such studies, there is scarce research aiming to quantify whether still great lack of literature aiming to quantify whether the decrease of network performance with age follows a linear trajectory. In this sense, an outstanding question is whether this trajectory could be changed via non-invasive intervention such as cognitive and physical training, which are thought to induce brain plasticity changes. The present research topic aims at hosting studies that propose new brain network models, or validate existing ones for healthy and pathological aging and studies that test or propose contemporary techniques derived from graph theory or other methods, to assess the efficacy of non-pharmacological interventions in aging or age-related neurodegenerative disorders Therefore, we welcome studies that answer fundamental neuroscientific questions like (but not limited to) the following:
1. Is there a linear decrease of brain network performance across the life span?
2. What are the age-related changes in the brain (hubs) and how these changes may be related to pathological neurodegeneration?
3. How can we detect/quantify compensatory mechanisms through brain network properties?
4. How do we establish evaluation models for quantifying the impact of interventions in terms of brain network properties?
5. What is the optimal identification of network states and how do they evolve during aging?
Previous studies showed that both healthy and pathological aging are associated with changes in brain structure and function of the mature human brain. The most prominent anatomical alteration are changes in prefrontal cortex morphology, volume loss and reduced white-matter integrity and hippocampal atrophy. Cognitive decline affects mainly the performance of episodic memory, speed of sensory information processing, working memory, inhibitory function and long-term memory. It has been also proposed that due to the aforementioned changes the aging brain engages in compensatory brain mechanism such as a broader activation of cortical regions (mainly frontal) rather than specialized activation. Evidence suggests that similar changes occur with pathological aging but to a greater extent. In this case information flow is disrupted due to neurodegeneration, functional activation of posterior (occipito-temporal) regions is decreased and as a consequence the brain fails to process sensorial input in the ventral pathway and cognitive deficits appear.
In the last years, functional alterations associated with aging have been studied using the mathematical notion of graph theory that offers an integrative approach since it examines different properties of the brain network: 1) Organization level 2) amount of local information processing, 3) information flow 4) cortical community structure and 5) identification of functional / anatomical hubs. So, graph theory offers an attractive way to model brain networks organization and to quantify their pathological deviations.
Previous studies have already employed this mathematical notion and demonstrated that age-related neurodegeneration is often accompanied by loss of optimal network organization either due to diminished local information processing or due to progressive isolation of distant brain regions. They have also found that changes in network properties may be present even in the preclinical phase, which could be taken as a biological marker of disease.
Despite the great envisaged impact and the importance of such studies, there is scarce research aiming to quantify whether still great lack of literature aiming to quantify whether the decrease of network performance with age follows a linear trajectory. In this sense, an outstanding question is whether this trajectory could be changed via non-invasive intervention such as cognitive and physical training, which are thought to induce brain plasticity changes. The present research topic aims at hosting studies that propose new brain network models, or validate existing ones for healthy and pathological aging and studies that test or propose contemporary techniques derived from graph theory or other methods, to assess the efficacy of non-pharmacological interventions in aging or age-related neurodegenerative disorders Therefore, we welcome studies that answer fundamental neuroscientific questions like (but not limited to) the following:
1. Is there a linear decrease of brain network performance across the life span?
2. What are the age-related changes in the brain (hubs) and how these changes may be related to pathological neurodegeneration?
3. How can we detect/quantify compensatory mechanisms through brain network properties?
4. How do we establish evaluation models for quantifying the impact of interventions in terms of brain network properties?
5. What is the optimal identification of network states and how do they evolve during aging?