Abstract
Neural complexity and brain entropy (BEN) have gained greater interest in recent years. The dynamics of neural signals and their relations with information processing continue to be investigated through different measures in a variety of noteworthy studies. The BEN of spontaneous neural activity decreases during states of reduced consciousness. This evidence has been showed in primary consciousness states, such as psychedelic states, under the name of “the entropic brain hypothesis.” In this manuscript we propose an extension of this hypothesis to physiological and pathological aging. We review this particular facet of the complexity of the brain, mentioning studies that have investigated BEN in primary consciousness states, and extending this view to the field of neuroaging with a focus on resting-state functional Magnetic Resonance Imaging. We first introduce historic and conceptual ideas about entropy and neural complexity, treating the mindbrain as a complex nonlinear dynamic adaptive system, in light of the free energy principle. Then, we review the studies in this field, analyzing the idea that the aim of the neurocognitive system is to maintain a dynamic state of balance between order and chaos, both in terms of dynamics of neural signals and functional connectivity. In our exploration we will review studies both on acute psychedelic states and more chronic psychotic states and traits, such as those in schizophrenia, in order to show the increase of entropy in those states. Then we extend our exploration to physiological and pathological aging, where BEN is reduced. Finally, we propose an interpretation of these results, defining a general trend of BEN in primary states and cognitive aging.
Highlights
Several factors characterize the human brain as one of the most complex organs in nature
As we address in more details in the forthcoming sections, the complexity becomes super-critical in case of primary states
Sample Entropy (SampEn) avoids the problem of vector selfmatching, not including it in the analysis. This technique has been recently used (Jia et al, 2017) to show that brain entropy (BEN) of the amygdalacortical connectivity decreases with advancing age, but this effect disappears in patients with schizophrenia
Summary
Several factors characterize the human brain as one of the most complex organs in nature. This technique has been recently used (Jia et al, 2017) to show that BEN of the amygdalacortical connectivity decreases with advancing age, but this effect disappears in patients with schizophrenia In other words, these authors have shown the general loss of brain complexity (in terms of FC) related to neuroaging, which will be explored in depth but they added the evidence. During the neurocognitive aging process (especially in its pathological vein) the system seems to lose its general “goodness” to receive information and apply an efficient perceptual synthesis, good factorization of the putative causes of sensations, losing the ability to update, interpret and predict the reality Associate to this factor there is the progressive loss to anticorrelate specific networks during cognitive task and resting state. We focus our attention to the BEN in physiological and pathological aging, investigated through the rs-fMRI approach (Table 1)
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