task-related information and form functional networks encode both sensory input and behavioral choice.

Cortical processing of task-relevant information enables recognition of behaviorally meaningful sensory events. How task-related information is represented within cortical networks by the activity of individual neurons and their functional interactions was investigates. A subset of neurons transiently encode sensory information used to inform behavioral choice.
These neurons form functional networks in which information transmits sequentially. Network structures differ for target versus non-target tones, encode behavioral choice, and differ between correct versus incorrect behavioral choices. Correct behavioral choices are associated with shorter communication timescales, larger functional correlations, and greater information redundancy.
In summary, specialized neurons in primary auditory cortex integrate task-related information and form functional networks whose structures encode both sensory input and behavioral choice.

• Aberrant attentional gain in auditory cortex reflects incorrect decision making
• Task-relevant information is transiently encoded by individual neurons
• Neuronal network structures with task-relevant information encode behavioral choice
• Networked neurons communicate task-relevant information redundantly

In an earlier post, I already mentioned the work of Ulanowicz whereby the “window of viability” & ascendency was defined (as a non-conservative, macroscopic variable which ecosystems were to optimize as self-organizing, dissipative systems). A healthy balance of resilience and efficiency can be measured using Ulanowicz’ Window of Vitality metric.

Also on my blog – a while ago – is a reference on how during their lives humans constantly interact with the physical environment, as well as with themselves and others.
World model learning and inference are crucial concepts in brain and cognitive science, as well as in AI and robotics. The outstanding challenges of building a generalpurpose AI needs world modelling and probabilistic inference, needed to realise a brain-like artificial intelligence that can interact naturally with the real world and our society. The interaction mentioned, is modeled based on the priciples of Free Energy & Active Inference