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Brain networks refer to the interconnected neural circuits that facilitate communication and coordination across different regions of the brain, enabling complex cognitive, sensory, and motor functions. Understanding these networks is crucial for deciphering how the brain processes information and how disruptions can lead to neurological and psychiatric disorders.
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Functional connectivity refers to the statistical dependencies or correlations between different regions of the brain, suggesting that these areas are working together during specific cognitive tasks or resting states. It is a crucial aspect of understanding brain networks and is often studied using techniques like functional MRI to map out these interactions and their role in various neurological conditions.
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Structural connectivity refers to the anatomical connections between different regions of the brain, typically assessed through neuroimaging techniques like diffusion tensor imaging (DTI) which maps the white matter pathways. It is crucial for understanding how brain regions communicate and can be altered in neurological disorders, affecting cognitive and behavioral functions.
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Neural circuits are networks of interconnected neurons that process specific types of information and generate responses in the nervous system. They are fundamental to understanding how the brain functions, influencing everything from sensory perception to complex behaviors.
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Resting-State Networks (RSNs) are patterns of brain activity that occur when a person is not focused on the outside world, reflecting the brain's intrinsic functional architecture. These networks are crucial for understanding brain connectivity and have implications for various neurological and psychiatric conditions.
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The default mode network (DMN) is a group of interconnected brain regions that show increased activity during rest and mind-wandering, playing a crucial role in self-referential thought, memory, and future planning. Disruptions in the DMN are linked to various neurological and psychiatric disorders, highlighting its importance in understanding brain function and mental health.
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The salience network is a collection of brain regions that determines which stimuli are deserving of our attention by filtering and prioritizing sensory information. It plays a crucial role in switching between the brain's default mode network and central executive network, thereby influencing cognitive control and emotional regulation.
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The central executive network (CEN) is a brain network that is crucial for high-level cognitive functions such as decision-making, problem-solving, and goal-directed behavior. It primarily involves the dorsolateral prefrontal cortex and the posterior parietal cortex, functioning to maintain and manipulate information in working memory and to exert top-down control over attention.
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Neuroplasticity refers to the brain's remarkable ability to reorganize itself by forming new neural connections throughout life, allowing it to adapt to new experiences, learn new information, and recover from injuries. This dynamic process underscores the brain's capacity for change and adaptation, challenging the long-held belief that brain development is static after a certain age.
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Graph theory is a branch of mathematics that studies the properties and applications of graphs, which are structures made up of nodes (vertices) connected by edges. It is fundamental in computer science, network analysis, and combinatorics for solving problems related to connectivity, flow, and optimization.
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Connectomics is the comprehensive study of neural connections within the brain, aiming to map the intricate web of neurons and synapses that define neural pathways. This field leverages advanced imaging techniques and computational models to understand brain function, development, and disorders at a network level.
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Neural synchronization refers to the process by which neurons in different regions of the brain coordinate their activity to produce coherent patterns of oscillations, which are crucial for cognitive functions such as perception, attention, and memory. This synchronization is often achieved through mechanisms like phase locking and can be measured using techniques such as electroencephalography (EEG) and magnetoencephalography (MEG).
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Seed-Based Analysis is a neuroimaging technique used to explore functional connectivity in the brain by selecting a 'seed' region and examining its correlation with other brain areas. This method is essential for understanding brain networks and identifying regions associated with specific cognitive or clinical conditions.
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The 'resting state' refers to a condition in which a system, often biological or neural, is not actively engaged in a task but still exhibits intrinsic activity. This state is crucial for understanding baseline functioning and connectivity within systems, providing insights into their default operational modes and potential disruptions in various conditions or disorders.
Seed-Based Correlation Analysis is a neuroimaging technique used to identify functional connectivity by selecting a seed region and examining the correlation of its activity with other regions in the brain. This method helps in understanding how different brain areas interact during various cognitive states or tasks, providing insights into brain network organization and dysfunctions in neurological disorders.
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Intrinsic brain activity refers to the spontaneous, ongoing neural activity that occurs in the brain even in the absence of external stimuli or tasks, reflecting the brain's default mode of operation. It is crucial for maintaining baseline brain function, supporting cognitive processes, and is often studied through resting-state functional MRI to understand brain networks and disorders.
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