MACHINE INTELLIGENCE AND COGNITIVE INTELLIGENCE FOR HUMAN BRAIN ANALYSIS (HBA)

Divya

Intelligence can be integrating via a number of cognitive processes such as sensory observations, responsiveness, memory and language perception.  Cognitive Intelligence refers to a general mental ability for problem-solving, learning and cognitive aptitude. Standardized tests can measure intelligence correctly, and the results can be used to predict a variety of broad social outcomes, such as academic success, work performance, health, and lifespan. A complete understanding of the neural mechanisms behind this basic mental capacity could have significant positive effects on people.

A Fronto-Parietal Network (FPN) associated with intelligence has typically been validated by structural and functional neuroimaging research. The same neural network enables language, short-term memory, and sensory cognitive activities. The study of the connections between anatomical and functional networks, with a focus on the communication across distant brain regions, is entering a crucial new phase. An extensive examination of the composition of human intellect is required to investigate the relationships between it and the brain. Before making a definitive statement regarding the measured performance, the precise proportion of the “ingredients” for the examined human intelligence must be determined. This necessitates the use of multiple tests such as Standard Progressive Matrices Test (SPM) in research like functional imaging investigations of intelligence. Human intelligence includes reasoning, problem-solving, and learning, among other things. People can acquire both simple and incredibly complex behavioural repertoires throughout their lives. The ability of humans to handle challenging situations varies significantly depending on individual differences in thinking, problem-solving, and learning. These differences are (i) more noticeable when the situation’s cognitive complexity increases, (ii) persistent over time, and (iii) largely driven by hereditary variables. Any variance in performance on a certain set of mental or cognitive tasks is referred to as a cognitive ability. A person’s abilities are visible variations in how well they perform on certain activity or other tasks. However, this performance entails the synthesis of a number of talents.  The challenge of defining the underlying concepts and describing their structure is the challenge of categorizing and assessing intelligence using techniques such as semantic web, model-based information processing for semantics (ontology mining), problem-solving using Modelling and Simulation for Clinical or Biomedical text mining, Support Vector Machines, and traditional neural networks for Analysis, detection and diagnosis of various disease.