VII. Our Earthuman Ascent: A Major Evolutionary Transition in Individuality

2. Systems Neuroscience: Multiplex Networks and Critical Function

Treffner, Paul and Scott Kelso. Dynamic Encounters: Long Memory During Functional Stabilization. Ecological Psychology. 11/2, 1999. Human and universe share the same creative agency.

Evidence and theory suggest that the coordination of human perception and action may be understood as a self-organizing complex system that exhibits great flexibility by operating nearby critical points of instability. (103)

Tsuda, Ichiro. Toward an Interpretation of Dynamic Neural Activity in Terms of Chaotic Dynamical Systems. Behavioral and Brain Sciences. 24/6, 2001. The conventional view emphasizes static elements while new insights focus on the fluid, shifting relations between modular components. The active brain is then seen to self-organize by the interplay of retained representation and creative perception.

According to this point of view, a single neuron or neuron assembly is represented by a single code and also by a multiple code; the information representation is realized both by the state of neurons and by the dynamic relation among states. (793)

Van Gelder, Tim. The Dynamical Hypothesis in Cognitive Science. Behavioral and Brain Sciences. 21/5, 1998. An affirmation of an integrative, self-organizing mental activity to supplant the prior digital computational model.

Van Orden, Guy. Nonlinear Dynamics and Psycholinguistics. Ecological Psychology. 14/1-2, 2002. An introduction to a special issue on this topic. While 20th century cognitive psychology was founded on reductionism and linearity, this article recognizes the irreducible, reciprocal relations between agents and environments. These take on the characteristic form of fractally nested self-organizing systems.

Van Pelt, J., et al, eds. The Self-Organizing Brain: From Growth Cones to Functional Networks. Amsterdam: Elsevier, 1994. Proceedings of the 18th International Summer School of Brain Research, University of Amsterdam, August 1993. How the sciences of complexity are bringing a novel understanding of mutually interrelated brain structure and function. Neuronal self-organization is seen to have an epigenetic character beyond molecular programs so as to remove a genetic determination.

Varela, Francisco, et al. The Embodied Mind. Cambridge: MIT Press, 1991. An extraordinary work of bridge building from the expansive self of Madhyamika Buddhist psychology over a computational neuroscience view of a fragmented self toward a novel “enactive” theory drawing on connectionist, self-organizing networks.

Vazquez-Rodriguez, Bertha, et al. Stochastic Resonance at Criticality in a Network Model of the Human Cortex. Nature Scientific Reports. 7/13020, 2017. Universidad Nacional Autónoma de México, Indiana University, and Lausanne University Hospital neuroscientists including Olaf Sporns add significant neuroimage evidence for an innate propensity of human brains to situate cognitive activities in an optimal, critically poised state between noise and content. By so doing, our neural acuity becomes an ultra-complex exemplar of a uniVerse to human evolutionary genesis. See also The Signatures of Conscious Access and its Phenomenology are Consistent with Large-Scale Communication at Criticality by Enzo Tagliazucchi in Consciousness and Cognition (55/136, 2017).

Stochastic resonance is a phenomenon in which noise enhances the response of a system to an input signal. The brain is an example of a system that has to detect and transmit signals in a noisy environment, suggesting that it is a good candidate to take advantage of stochastic resonance. In this work, we aim to identify the optimal levels of noise that promote signal transmission through a simple network model of the human brain (connectome). The optimal noise level is not unique; rather, there is a set of parameter values at which the information is transmitted with greater precision, this set corresponds to the parameter values that place the system in a critical regime. The multiplicity of critical points in our model allows it to adapt to different noise situations and remain at criticality. (Abstract)

Growing evidence supports the hypothesis that the dynamics of the brain resembles the dynamics of a system near a critical point. This suggests that many functionally important features of brain dynamics may be optimized at criticality. Recent work has shown that a discrete state dynamical model implemented on a network of neuroanatomical connections exhibits a phase transition similar to that observed in a percolation model, where the average size of the second biggest cluster of active nodes reaches its maximum value for a
specific activation threshold. (1) In this work we determine quantitatively the amount of noise required for the best transmission of signals through the structural network of the brain’s connectome, and its relationship with the hypothesis of the brain operating near criticality. (2)

Vernon, David. Artificial Cognitive Systems. Cambridge: MIT Press, 2014. The University of Skovde, Sweden, professor of informatics provides a good update review and synthesis of the field and frontier of Cognitive Science. In this nascent paradigm, a cerebral, and robotic, cognizance is seen as emergent in some self-constructive way. The view can then join connectionist, dynamic systems theory, and enactive approaches, each of which is well explained. A “radical constructionism” is noted which does not deny prior representations but holds that an agent or entity proceeds to adapt and compose their own viable reality. If we might shift from microcosm to macrocosm, could we imagine a radical self-realizing uniVerse, of which peoples are the selves meant to achieve this?

Walter, Nike and Thilo Hinterberge. Determining states of consciousness in the electroencephalogram based on spectral, complexity, and criticality features.. Neuroscience of Consciousness. Volume 1, 2022. University Hospital of Regensburg, Germany systems psychologists advantage the latest neuro-instrument and computational analyses to achieve deeper explanations and proofs of this optimum dynamic poise. Once again, nature’s preferred avail of this best balance is found in how we experience, think, learn and respond.

, This study was based on recent findings that distinct states of consciousness are quantifiable by neural complexities and critical dynamics. To test this, we compared the electrophysiological correlates of meditation states using nonlinear techniques. We used analytical methods from criticality theory (detrended fluctuation analysis, neuronal avalanche), complexity measures (multiscale entropy, Higuchi’s fractal dimension), and power spectral density. The meditation states could be quantified with nonlinear measures by the degree of neuronal complexity, long-range temporal correlations, and power law avalanches. (Excerpt)

In recent years, the hypothesis arose that neural dynamics reside in a self-organized criticality. This premise is based on theoretical and experimental work in physics, which show that the multiscale dynamics of a complex system are distinguished by branching avalanches. These statistics reveal whether the system is in a critical state at the edge between order and disorder. Critical state dynamics as these were associated with optimized network functions of information processing such as input susceptibility, maximized dynamic range, storage capacity as well as computational power. (1)

In conclusion, electrophysiological differences of distinct meditation states were identified and the relationship between non-linear complexity, critical brain dynamics, and spectral features was determined. The meditation states could be discriminated with nonlinear measures and quantified by the degree of neuronal complexity, LRTC, and power law distributions in neuronal avalanches. (8)

Neuroscience of Consciousness is an open access journal which publishes papers on the biological basis of consciousness. We welcome contributions from neuroscience, cognitive science, psychology, philosophy, computer science, and allied disciplines.. As well as the primary phenomenon of consciousness, relevant topics include interactions between conscious and unconscious processes; selfhood; emotion; metacognition and higher-order consciousness; intention, volition, and agency; individual differences in consciousness; altered states of consciousness; and consciousness in infants, non-human animals, and machines.

Wang, Jilin, et al. Non-equilibrium Critical Dynamics of Bursts in θ and δ Rhythms as Fundamental Characteristic of Sleep and Wake Micro-architecture. PLoS Computational Biology. November, 2019. As the 2010s come to a close, in this Public Library of Science journal Boston University and UM Worcester Medical School researchers including Plamen Ivanov describe experiments and theories so as to report that even our daily resting phase is distinguished by independent, universal complex phenomena. Thus nighttime joins daylight wakefulness which, as Systems Neuroscience cites, prefers to be poised between more or less order. A person’s beingness then joins a quantum, universal complementarity which all other phases and site sections lately attest to. Once again microcosmic selves are vital exemplars of a macrocosmic genesis.

Origin and functions of intermittent transitions among sleep stages, including short awakenings and arousals, challenge the current homeostatic framework for sleep regulation. Here we propose that a complex micro-architecture characterizing the sleep-wake cycle results from an underlying non-equilibrium critical dynamics, bridging collective behaviors across spatio-temporal scales. We demonstrate that intermittent bursts in θ and δ rhythms exhibit a complex temporal organization, with long-range power-law correlations and a robust duality of θ-bursts (active phase) and exponential-like δ-bursts (quiescent phase) durations, which are typical features of non-equilibrium systems self-organizing at criticality. Importantly, such temporal organization relates to anti-correlated coupling between θ- and δ-bursts, and is independent of the dominant physiologic state, a solid indication of a basic principle in sleep dynamics. (Abstract excerpt)

The results demonstrate that critical dynamics underlie cortical activation during sleep and wake, and lay the foundation for a new paradigm, considering sleep micro-architecture as a non-equilibrium process and self-organization among neuronal assemblies to maintain a critical state, in contrast to the homeostasis paradigm of sleep regulation at large time scales. (Author Summary)

Power-law distributions are the statistical hallmark of scale invariance, and are typical features of physical systems at the critical point of a second order phase transition in equilibrium thermodynamics. At criticality systems exhibit high sensitivity to interactions among elements, leading to emergent collective behavior across scales, and thus, power laws. The critical point is located at the border between an ordered and a disordered phase, and can be reached by fine tuning external parameters. In contrast to this scenario, in non-equilibrium systems the dynamics can be spontaneously driven at criticality, where an active phase characterized by bursts/avalanches with power-law distributed sizes and durations coexists with a quiescent phase with exponential-like statistics. (3-4)

Wang, Yujiang et al. Neuro-evolutionary Evidence for a Universal Fractal Primate Brain Shape. . Eight neuro-researchers from Newcastle University, UK, University of Iowa, and University of Nottingham including Bruno Mota describe a frontier, multi-species study of cortex anatomies whose empirical sophistication are now found to be distinguished by a deep self-similar invariance. We then turn to a planatural philoSophia view to observe how a global brain faculty, as it continues these personal topologies and abilities, can be seen to reconstruct the hominid and animal brains that it altogether arose from.

The primate cerebral cortex can take on a wide diversity of shapes and sizes within species, whilst maintaining common qualities that make it a "brain". Here we present a new way to express the cortical shape as a structural hierarchy across spatial scales. In computational studies, as one removes sulci and gyri smaller than a specified scale, the cortices of 11 primate species are coarse-grained into less folded modes. As a result these cortices take on an archetypal fractal frame which implies a single universal gyrification on all folds. (Abstract)

Ultimately, we hope this new framework for expressing and analyzing cortical morphology, besides revealing a hitherto hidden regularity of nature, can become a powerful tool to characterize and compare cortices of different species and individuals, across development and aging, and across health and disease. (18)

Werner, Gerhard. Brain Dynamics across Levels of Organization. Journal of Physiology-Paris. 101/4-6, 2007. A University of Texas, Austin, physician employs “dynamic core” and “global neuronal workspace” models, with their dual “computational, connectivity spaces” of particular, subcortical processors and widespread, long range nets, to propose that these fluid neural phenomena are signatures of a robust self-organized criticality. As per the quote, a novel merging with statistical physics is advanced, which, one might add, can root which our exemplary cerebral cogitations into an implicate cosmos.

After initially presenting evidence that the electrical activity recorded from the brain surface can reflect metastable state transitions of neuronal configurations at the mesoscopic level, I will suggest that their patterns may correspond to the distinctive spatio-temporal activity in the dynamic core (DC) and the global neuronal workspace (GNW), respectively, in the models of the Edelman group on the one hand, and of Dehaene–Changeux, on the other. Reasons will be given for viewing the temporal characteristics of this activity flow as signature of self-organized criticality (SOC), notably in reference to the dynamics of neuronal avalanches. This point of view enables the use of statistical physics approaches for exploring phase transitions, scaling and universality properties of DC and GNW, with relevance to the macroscopic electrical activity in EEG and EMG. (273)

[Prev Pages]   Previous   | 11 | 12 | 13 | 14 | 15 | 16 | 17  Next