Dynamic neurophysiological correlates of mental processes.

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Neurophysiology

Background:

• Understanding the brain's mechanisms underlying mental states and activities is crucial.
• Previous research has explored various neurophysiological processes, but a comprehensive view of their interplay during cognitive tasks is still developing.
• The concept of a cortical-subcortical functional system with varying link rigidity provides a framework for investigating mental activity.

Purpose of the Study:

• To investigate the neurophysiological correlates of mental activity by recording infraslow physiological processes (ISPP) and neuronal activity (NIA).
• To examine the stability and variability of these correlates across different brain areas during cognitive tasks.
• To explore the quantitative reflection of brain states by specific ISPP types, such as omega-potential.

Main Methods:

• Recording of infraslow physiological processes (ISPP) and neuronal impulse activity (NIA) in neurological patients with implanted electrodes.
• Subjects performed psychological and other trials while neurophysiological data was collected.
• Analysis of reproducible (stable) versus variable correlates of mental activity in different brain regions.

Main Results:

• Correlates of mental activity were found to be reproducible in some brain areas and variable in others, supporting the cortical-subcortical functional system hypothesis.
• Omega-potential, a type of ISPP, was identified as a quantitative indicator of brain area states.
• Neuronal impulse activity (NIA) rearrangements accompanying mental operations were described, highlighting their complementary nature.

Conclusions:

• Mental activity is supported by a cortical-subcortical functional system with varying degrees of link rigidity.
• The dynamic yet stable nature of physiological processes in the brain is fundamental for its informational capacity and the organism's adaptability.
• Investigating the relationship between local and distributed neural rearrangements, alongside combining averaging techniques with single mental act correlates, is highly promising for future research.