Cognitive Regime Shift I - When the Brain Breaks
Category: Application Area Application Area: Infectious Diseases
Date/Time: July 23, 2018 - July 25, 2018
Location: Santa Fe Institute
Audio files
Cognitive Regime Shift I organizer interview converted.mp3 (x)
In this inaugural working group on Cognitive Regime Shift, complexity tools and models developed to understand network phenomena in physiological, sociological, ecological, and financial realms will be applied to better understand the loss of cognitive function. The central goal is to achieve synthesis and integration between neurology and several areas of complexity science bearing on network failure, such that interventions for increasing long-term adaptability of the brain might be found. Critical questions that will be raised during the working group include relationship between network failure, adaptation and robustness to system aging, early indicators for risk factors, application of criticality, long-range order, and collective dynamic to the aging brain, and specific aspects of the above to Alzheimer’s. Some questions that will be discussed during this working group are: 1. What is the relationship between network, failure, adaptation, and robustness to system aging? 2. What are the early indicators and risk factors that are predictive of loss of functions? 3. Can ideas from the study of criticality, long-range order, and collective dynamics inform our understanding and suggest restorative intervention in the aging brain? 4. How can neurodegenerative disease such as Alzheimer’s be better characterized as atrophy on large-scale, distributed function-critical neural networks?
David Krakauer (SFI) - "Prion dynamics and latency"[edit source]
A large number of neurodegenerative diseases feature the accumulation of mis-folded proteins. These include prion diseases, Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease. In all of these cases several different scales of organization are associated with disease progression or onset to include genetic, epigenetic, neural circuits, brain modules, and behavior. How should we best integrate data from each of these levels and what models and theories allow us to span levels? I shall discuss a few dynamical models of polymerization, protein accumulation, and protein diffusion through neural connections, that provide insights into disease progression at a number of different time and space scales. An ongoing challenge is a criterion for fixing thresholds that define an observable cognitive regime shift.
George Mashour (Univ. Michigan) - Consciousness, Cognition, and the Prefrontal Cortex[edit source]
The goal of my talk was to inform the group on the current controversies in identifying the neural correlates of consciousness, to distinguish phenomenal vs. access consciousness, and to highlight the potential role of recurrent processing (also known as reafferent, reentrant, reverberant or feedback processing) in conscious experience. I also wanted to show that anesthesia can be a reversible, functional model of a "broken brain" and demonstrate interventions (in this case, cholinergic stimulation of prefrontal cortex) that might reverse phenotypes of brokenness.
Gagan Wig (UT Dallas) - Large-scale Brain Network Changes Across the Healthy Adult Human Lifespan: Relations to Cognition and First Steps toward Identifying Potential Risk Factors of Brain Decline[edit source]
-Human brain areas are organized into a large-scale functional network, which can be measured at rest using non-invasive brain imaging (functional MRI)
-The brain network contains segregated sub-networks that correspond to functionally specialized brain systems
-The segregation of brain systems declines with increasing age, across the healthy adult lifespan
-System segregation relates to cognitive function in individuals (greater system segregation is associated with better long--term memory ability)
-Certain health risk factors (e.g., lower socioeconomic status) are related to lower system segregation
-My working hypothesis is that gradual and sudden cognitive decline is related to changes in system segregation as an individual ages, and that individual differences in rate and risk of decline are a consequence of the capacity of the functional brain network to tolerate and adapt to damage (neurodegeneration)
Sidney Redner (SFI) - Network Breakdown Phenomena[edit source]
I gave a basic review of percolation theory on lattices and outlined the behavior of physical observables, such as the correlation length, the mean cluster size, and the percolation probability on the bond occupation probability. I then discussed the analogous percolation transition on complex networks, where the degree distribution can be broad. The basic new feature of complex networks is that they are relatively robust to random removal of nodes or links and quite vulnerable to the removal of the highest-degree nodes.
Finally, I presented two examples of network breakdown phenomena: the electrical failure of electrical networks of fuse elements and the external voltage is increased, and the clogging of fluid networks during the process of filtration.
Dietmar Plenz (NIH) - Neuronal Avalanches[edit source]
Jacopo Grilli (ICTP) - On the Stability of Large Ecological Communities[edit source]
Ecological communities (more generally, non-linear systems) often showmultiple regimes, which are separated by a sharp and rapid transition. I will discuss the scenario when the driver of the transition is the structure of interactions. Random matrix theory has a powerful set of tools that can be used to unveil the relation between interaction structure and dynamics.
Take home messages:
- universality: when many components interact many details do not matter (e.g. the distribution of interaction coefficients) and few global properties of the interactions determine the relevant dynamical properties
- the effect of the structure (whether a given network structure is stabilizing or destabilizing compared to the null/random case) *depends* on the interaction strengths properties
Caterina Gratton (Northwestern Univ.) - States and Stability in Human Functional Brain Networks[edit source]
In my talk, I went over two main empirical studies. In the first, we used a dataset that highly-sampled 10 individual subjects, across different days and tasks. We asked how functional brain networks vary over different timescales, and found that these network measurements are primarily stable, with only moderate/minor state-based effects. In the second experiment, we looked at how Parkinson’s disease affect functional brain networks. We found that PD selectively impacts blocks of network-to-network connections, remote from primary pathophysiology. I also described initial findings from a recent initiative into how we might characterize individual variation in brain networks, showing that individual network “variants” are stable and systematic. From these findings, I concluded:
- Functional network measures are well-suited to tracking slow, stable brain processes
- These measures can provide detailed images of individual differences
- Functional network effects can be complex, occurring at locations remote from primary pathology
Graham H. Creasey (Stanford) - The Brain and other Networks[edit source]
The brain, whether considered as a network or a complex adaptive system, is obviously linked to other networks and complex adaptive systems, both technical and social. These links are usually mediated by inputs and outputs corresponding to sensors (visual, auditory, tactile, etc) and actuators (muscles, glands, etc) but it is also possible to create direct electrical interfaces to the nervous system. Study of these inputs and outputs gives insights into the internal function of the brain as a network.
How do the brain and other networks adapt/learn/grow in parallel or collaboratively? How can this knowledge be used to defer or prevent network failure, especially with aging?
Reference Materials by Presenting Attendees[edit source]
General Meeting Reference Material[edit source]
Title | Author name | Source name | Year | Citation count From Scopus. Refreshed every 5 days. | Page views | Related file |
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Aging and measures of processing speed | Timothy A. Salthouse | Biological Psychology | 2000 | 672 | 59 | |
Open questions in artificial life | Mark A. Bedau, John S. McCaskill, Norman H. Packard, Steen Rasmussen, Chris Adami, David G. Green, Takashi Ikegami, Kunihiko Kaneko, Thomas S. Ray | Artificial Life | 2000 | 159 | 17 | |
High performance communication by people with paralysis using an intracortical brain-computer interface | Chethan Pandarinath, Paul Nuyujukian, Christine H. Blabe, Brittany L. Sorice, Jad Saab, Francis R. Willett, Leigh R. Hochberg, Krishna V. Shenoy, Jaimie M. Henderson | eLife | 2017 | 152 | 6 | |
Review - Segregated Systems of Human Brain Networks | Gagan S. Wig | Trends in Cognitive Sciences | 2017 | 89 | 7 | |
Critical networks exhibit maximal information diversity in structure-dynamics relationships | Matti Nykter, Nathan D. Price, Antti Larjo, Tommi Aho, Stuart A. Kauffman, Olli Yli-Harja, Ilya Shmulevich | Physical Review Letters | 2008 | 66 | 11 | |
Irregular spiking of pyramidal neurons organizes as scale-invariant neuronal avalanches in the awake state | Timothy Bellay, Andreas Klaus, Saurav Seshadri, Dietmar Plenz | eLife | 2015 | 63 | 9 | |
Predicting the stability of large structured food webs | Stefano Allesina, Jacopo Grilli, György Barabás, Si Tang, Johnatan Aljadeff, Amos Maritan | Nature Communications | 2015 | 57 | 8 | |
Coordinated reset vibrotactile stimulation shows prolonged improvement in Parkinson's disease | Judy Syrkin-Nikolau, Raumin Neuville, Johanna O'Day, Chioma Anidi, Mandy Miller Koop, Talora Martin, Peter A. Tass, Helen Bronte-Stewart | Movement Disorders | 2018 | 11 | 15 | |
Voltage imaging of waking mouse cortex reveals emergence of critical neuronal dynamics | 0 | 13 | ||||
Socioeconomic status moderates age-related differences in the brain’s functional network organization and anatomy across the adult lifespan | 0 | 10 | ||||
Editorial overview: Neurobiology of cognitive behavior: Complexity of neural computation and cognition | Alla Karpova, Roozbeh Kiani | Current Opinion in Neurobiology | 2016 | 0 | 5 | |
Loss of Consciousness Is Associated with Stabilization of Cortical Activity2 | 0 | 3 |