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Dosha brain-types: A neural model of individual differences
by
Wallace, RobertKeith
, Travis, FrederickT
in
Ayurveda
/ Ayurvedic medicine
/ brain-types
/ Health aspects
/ Kapha
/ nervous system
/ Pitta
/ Vata
2015
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Dosha brain-types: A neural model of individual differences
by
Wallace, RobertKeith
, Travis, FrederickT
in
Ayurveda
/ Ayurvedic medicine
/ brain-types
/ Health aspects
/ Kapha
/ nervous system
/ Pitta
/ Vata
2015
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Dosha brain-types: A neural model of individual differences
Journal Article
Dosha brain-types: A neural model of individual differences
2015
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Overview
This paper explores brain patterns associated with the three categories of regulatory principles of the body, mind, and behavior in Ayurveda, called Vata, Pitta, and Kapha dosha. A growing body of research has reported patterns of blood chemistry, genetic expression, physiological states, and chronic diseases associated with each dosha type. Since metabolic and growth factors are controlled by the nervous system, each dosha type should be associated with patterns of functioning of six major areas of the nervous system: The prefrontal cortex, the reticular activating system, the autonomic nervous system, the enteric nervous system, the limbic system, and the hypothalamus. For instance, the prefrontal cortex, which includes the anterior cingulate, ventral medial, and the dorsal lateral cortices, would exhibit a high range of functioning in the Vata brain-type leading to the possibility of being easily overstimulated. The Vata brain-type performs activity quickly. Learns quickly and forgets quickly. Their fast mind gives them an edge in creative problem solving. The Pitta brain-type reacts strongly to all challenges leading to purposeful and resolute actions. They never give up and are very dynamic and goal oriented. The Kapha brain-type is slow and steady leading to methodical thinking and action. They prefer routine and needs stimulation to get going. A model of dosha brain-types could provide a physiological foundation to understand individual differences. This model could help individualize treatment modalities to address different mental and physical dysfunctions. It also could explain differences in behavior seen in clinical as well as in normal populations.
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