**Links to**: [[Multiscale systems]], [[Brain]], [[Entropy]], [[Entropofagia]], [[Entropic Brain]], [[Entropomorfismo]], [[Entropicalia]], [[Energy]], [[Negentropy]], [[Thermodynamics]], [[Reversibility]], [[Evolution]], [[Cognition]], [[Metabolism]], [[Digestion]]. <small>Notes from Jil Meier lecture.</small> Nothing more than the measuring of entropy at **different timescales**. The idea here is that it can be used to overview many different dynamics—different types of system complexity—of the brain as one plot, as one snapshot. The clinical applications of this abstract measure are wide and promising: measuring brain dynamics as they relate to performance, aging, etc. In order to get the measures, like with everything else: we have to coarse grain, by creating a time series (e.g., taking a measure per second). We can measure different time scales then: take the entropy of a region/wave every second, every three seconds, every minute, etc. What we are interested in looking at are relevant brain patterns, not just “randomness”, but interesting textures we can read, analyze and interpret for the sake of diagnosis, prognosis, etc. Signals with different types of noise revealed (e.g., white noise) can be ignored or singled out, because we recognize its determined pattern. IT entropy (H), as we know, is a measure of (dis)order. We quantify the predictability of a signal (which depends, of course, on what we characterize as a signal). Noise = lots of info = high entropy. 0 entropy = total predictability, like a plain and simple sine wave. When we have tons of waves interacting, we can also measure their mutual information, where they overlap.^[Joint entropy (H) between X and Y is then: H(X, Y) = H(Y | X) + H(Y | X) + I(X ; Y).] # Local entropy and global entropy It seems that in healthy aging we observe an increase in specialization: more local interactions and less global ones. So, information processing happens in specific regions rather than the system spending energy on doing very global transitions. We could speculate, not so far-fetched: this is biasing, learning. Apparently, this shift, coupled with a healthy lifestyle, has been associated with better cognitive performance. If an individual does not have this shift, during adulthood, from global processing to more local processing, this seems to be indicative of the development of a neurodegenerative diseases such as dementia. Aging means that we get better at local dynamics. But global dynamics decrease. Apparently: multiscale entropy increases from childhood to adulthood. The young brain is less complex than the adult brain, which processes many dynamics at the same time (most likely an effect of the phenomenon we call *memory*). Multiscale entropy can be used to detect the onset of, e.g., dementia. As we age, complexity seems to decrease, too.^[We can read this as going from baby-stubborn to viejx-stubborn.] At a young age we carry very basal priors, we sponge-up culture, and we settle into the priors that kind of worked out for us. %% Link to mention of how youth produces most interesting stuff because of perceiving things anew, fresh, without filtering biases. Aging mindscape podcast Aging https://www.nature.com/articles/d41586-024-01370-4 Mindscape podcast %% ### Footnotes