Volume 2 Issue 1 (April 2023)
Michael J. Spivey
T.W. Nichols, M.H. Berman and J.A. Tuszynski
The etiology of Alzheimer's dementia is, at best multifactorial. Before the emergence of cognitive impairment, symptoms such as thinning of the cortex, accumulation of β-amyloid, and decreased hippocampal volume are common. Hence, the accumulation of β-amyloid and hyperphosphorylated tau fibrillary tangles are two pathological hallmarks in Alzheimer's disease brains, but antibody therapy aimed to decrease β-amyloid has been a failure and, in most optimistic opinions, may delay somewhat disease progression. However, 31-38 % of subjects develop cerebral micro-hemorrhages in aducanumab therapy, an antibody to the amyloid beta plaque by Biogen. Genetics such as Apo E3/E3 have demonstrated defects in the blood-brain barrier in early-onset dementia...more
E. Alemdar, R. R. Poznanski, L.A. Cacha, G. Leisman and E. J. Brändas
This pioneering research on how specific molecules deep inside our brains form a dynamic information holarchy in phase space, linking mind and consciousness, is not only provocative but also revolutionary. Holonomic is a dynamic encapsulation of the holonic view that originates from the word “holon” and designates a holarchical rather than a hierarchical, dynamic brain organization to encompass multiscale effects. The unitary nature of consciousness being interconnected stems from a multiscalar organization of the brain. We aim to give a holonomic modification of the thermodynamic approach to the problem of consciousness using spatiotemporal intermittency...more
J. B. Falandays, R. O. Kaaronen, C. Moser, W. Rorot, J. Tan, V. Varma, T. Williams, and M. Youngblood
Collective intelligence, broadly conceived, refers to the adaptive behavior achieved by groups through the interactions of their members, often involving phenomena such as consensus building, cooperation, and competition. The standard view of collective intelligence is that it is a distinct phenomenon from supposed individual intelligence. In this position piece, we argue that a more parsimonious stance is to consider all intelligent adaptive behavior as being driven by similar abstract principles of collective dynamics. To illustrate this point, we highlight how similar principles are at work in the intelligent behavior of groups of non-human animals, multicellular organisms, brains, small groups of humans, cultures, more
S. F. Corbin, C.H. Moore, T. Davis, K. Shockley and T. Lorenz
Human motion contains rich contextual information about not only action, but action intention. In two experiments, we investigated whether the multiscale kinematic information that differentiates intentional actions is the same information to which observers attend when asked to observe an actor’s intended movement. To do so, we first recorded an actor’s movement kinematics while performing four different intentional sit-to-stand actions. Analyzing the differences in movement kinematics, we then identified the joints that contributed to differentiating the actions using principal components analysis and multinomial regression. Observers were then shown point-light displays of these movements and given a forced-choice task to select which action the actor...more
Tadhg Waddington and Ramesh Balasubramaniam
A wide body of research is currently being devoted to investigating the multiscale processes across the brain and body, and the nature of their interactions. The purpose of this paper is to supplement these analyses of brain and body dynamics by providing a comprehensive account of the multiscale organisations also found in music, and ways in which these systems interact. We proceed in identifying scaling laws as a signature for multiscale features of a system and make the methodological choice of distinguishing 1) scale free structure from 2) scale free dynamics. We follow these distinctions in demonstrating how specifically i.) hierarchical temporal structures, ii.) long-range temporal correlations, and iii.) musical information as scale free structures...more
Luis H. Favela
Neuroscience has become a big data enterprise. This is due in large part to the rapidly growing quantity and quality of data and increased appreciation of non-neuronal physiology and environments in explaining behavior, cognition, and consciousness. One way neuroscience is dealing with this embarrassment of riches is by appealing to investigative frameworks that put the multiscale nature of neural systems at the forefront. The current work offers one such approach: Nested dynamical modeling, a strategy for creating models of phenomena comprised of multiple spatial and/or temporal scales for purposes of exploration, explanation, and understanding. Building from dynamical systems theory and synergetics, nested dynamical modeling applies a methodological approach aimed at nesting models at one scale of inquiry within models at other scales without compromising biological realism. This strategy is demonstrated via a proof of concept. Some consequences this approach has for the epistemological and theoretical commitments of neuroscience are discussed.
There is growing evidence that brain processes involve multiscale overlapping networks and that the mapping between such neural processes and cognitive functions is many-to-many. So, the answer to the question what spatiotemporal scales in the brain are most relevant for cognition, action, experience, etc., is that several inextricably interconnected and integrated scales are relevant. There is also growing evidence that brains and embodied agents (people) are part of “larger” distributed “bio-psycho-social networks.” One cannot fully appreciate what brains do and how they work in isolation from these larger multiscale, multi-level, and multi-faceted “4E” networks (embodied, embedded, extended, and enactive). Nor can one explain
Benjamin Nguyen and Michael J. Spivey
By juxtaposing time series analyses of activity measured from a fully recurrent network undergoing disrupted processing and of activity measured from a continuous meta-cognitive report of disruption in real-time language comprehension, we present an opportunity to compare the temporal statistics of the state-space trajectories inherent to both systems. Both the recurrent network and the human language comprehension process appear to exhibit long-range temporal correlations and low entropy when processing is undisrupted and coordinated. However, when processing is disrupted and discoordinated, they both exhibit more short-range temporal correlations and higher entropy. We conclude that by measuring human language comprehension in a dense-sampling manner similar to how we analyze the networks, and analyzing the resulting data stream with nonlinear time series analysis techniques, we can obtain more insight into the temporal character of these discoordination phases than by simply marking the points in time at which they peak.
Michael J. Spivey
This brief report provides an overview of the Special Issue on The Mind and The Brain: A Multiscale Interpretation of Cognitive Brain Functionality. It serves as a concise guide for the initial motivation for the special issue and for how best to read the articles inside it and identify their connections. This special issue combines experts from the philosophy of complex systems, ecological perception, embodied cognition, dynamical systems theory and comparative cognition to enable a widened perspective on cognition that is both multiscale and multidimensional. By looking at the mutual overlap between perception, action, and cognition, and the multiscale methods that allow novel insights into the interactive processes that underly them, this special issue provides a unique assemblage of methods, findings, and theoretical advances. The reader should expect to come out of it with a slightly different understanding of what cognition is made of.