Emergent complex neural dynamics
TL;DR: Viewing the brain in terms of collective dynamics is one approach now yielding some insight.
Abstract: Is the brain on the edge of criticality? Understanding the inner workings of the brain is a task made difficult by the number of elements involved: a hundred billion neurons and a hundred trillion synapses. Viewing the brain in terms of collective dynamics is one approach now yielding some insight.
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28 Jul 2005
TL;DR: PfPMP1）与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。
18,940 citations
TL;DR: It is proposed that brain organization is shaped by an economic trade-off between minimizing costs and allowing the emergence of adaptively valuable topological patterns of anatomical or functional connectivity between multiple neuronal populations.
Abstract: On the basis of data from brain network science, Bullmore and Sporns propose that brain organization is shaped by an economical trade-off between minimizing wiring cost and maximizing the efficiency of information transfer between neuronal populations and discuss this idea in the context of psychiatric and neurological disorders. The brain is expensive, incurring high material and metabolic costs for its size — relative to the size of the body — and many aspects of brain network organization can be mostly explained by a parsimonious drive to minimize these costs. However, brain networks or connectomes also have high topological efficiency, robustness, modularity and a 'rich club' of connector hubs. Many of these and other advantageous topological properties will probably entail a wiring-cost premium. We propose that brain organization is shaped by an economic trade-off between minimizing costs and allowing the emergence of adaptively valuable topological patterns of anatomical or functional connectivity between multiple neuronal populations. This process of negotiating, and re-negotiating, trade-offs between wiring cost and topological value continues over long (decades) and short (millisecond) timescales as brain networks evolve, grow and adapt to changing cognitive demands. An economical analysis of neuropsychiatric disorders highlights the vulnerability of the more costly elements of brain networks to pathological attack or abnormal development.
2,646 citations
TL;DR: A novel model of the posterior cingulate cortex's function is synthesized into a model that influences attentional focus by 'tuning' whole-brain metastability and so adjusts how stable brain network activity is over time, and is tested within the framework of complex dynamic systems theory.
Abstract: The posterior cingulate cortex is a highly connected and metabolically active brain region. Recent studies suggest it has an important cognitive role, although there is no consensus about what this is. The region is typically discussed as having a unitary function because of a common pattern of relative deactivation observed during attentionally demanding tasks. One influential hypothesis is that the posterior cingulate cortex has a central role in supporting internally-directed cognition. It is a key node in the default mode network and shows increased activity when individuals retrieve autobiographical memories or plan for the future, as well as during unconstrained ‘rest’ when activity in the brain is ‘free-wheeling’. However, other evidence suggests that the region is highly heterogeneous and may play a direct role in regulating the focus of attention. In addition, its activity varies with arousal state and its interactions with other brain networks may be important for conscious awareness. Understanding posterior cingulate cortex function is likely to be of clinical importance. It is well protected against ischaemic stroke, and so there is relatively little neuropsychological data about the consequences of focal lesions. However, in other conditions abnormalities in the region are clearly linked to disease. For example, amyloid deposition and reduced metabolism is seen early in Alzheimer’s disease. Functional neuroimaging studies show abnormalities in a range of neurological and psychiatric disorders including Alzheimer’s disease, schizophrenia, autism, depression and attention deficit hyperactivity disorder, as well as ageing. Our own work has consistently shown abnormal posterior cingulate cortex function following traumatic brain injury, which predicts attentional impairments. Here we review the anatomy and physiology of the region and how it is affected in a range of clinical conditions, before discussing its proposed functions. We synthesize key findings into a novel model of the region’s function (the ‘Arousal, Balance and Breadth of Attention’ model). Dorsal and ventral subcomponents are functionally separated and differences in regional activity are explained by considering: (i) arousal state; (ii) whether attention is focused internally or externally; and (iii) the breadth of attentional focus. The predictions of the model can be tested within the framework of complex dynamic systems theory, and we propose that the dorsal posterior cingulate cortex influences attentional focus by ‘tuning’ whole-brain metastability and so adjusts how stable brain network activity is over time.
1,710 citations
Cites background from "Emergent complex neural dynamics"
...This work provides evidence that the PCC integrates the consequences of behaviour over time, and provides a signal for strategic changes in behaviour when the consequences of previous actions are suboptimal (Hayden et al., 2008; Pearson et al., 2009)....
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TL;DR: Current empirical efforts toward generating a network map of the human brain, the human connectome, are reviewed, and how the connectome can provide new insights into the organization of the brain's structural connections and their role in shaping functional dynamics are explored.
Abstract: The human brain is a complex network. An important first step toward understanding the function of such a network is to map its elements and connections, to create a comprehensive structural description of the network architecture. This paper reviews current empirical efforts toward generating a network map of the human brain, the human connectome, and explores how the connectome can provide new insights into the organization of the brain's structural connections and their role in shaping functional dynamics. Network studies of structural connectivity obtained from noninvasive neuroimaging have revealed a number of highly nonrandom network attributes, including high clustering and modularity combined with high efficiency and short path length. The combination of these attributes simultaneously promotes high specialization and high integration within a modular small-world architecture. Structural and functional networks share some of the same characteristics, although their relationship is complex and nonlinear. Future studies of the human connectome will greatly expand our knowledge of network topology and dynamics in the healthy, developing, aging, and diseased brain.
1,173 citations
TL;DR: The method allows, for the first time, to define a theoretical framework in terms of an order and control parameter derived from fMRI data, where the dynamical regime can be interpreted as one corresponding to a system close to the critical point of a second order phase transition.
Abstract: Functional magnetic resonance imaging (fMRI) techniques have contributed significantly to our understanding of brain function. Current methods are based on the analysis of gradual and continuous changes in the brain blood oxygenated level dependent (BOLD) signal. Departing from that approach, recent work has shown that equivalent results can be obtained by inspecting only the relatively large amplitude BOLD signal peaks, suggesting that relevant information can be condensed in discrete events. This idea is further explored here to demonstrate how brain dynamics at resting state can be captured just by the timing and location of such events, i.e., in terms of a spatiotemporal point process. The method allows, for the first time, to define a theoretical framework in terms of an order and control parameter derived from fMRI data, where the dynamical regime can be interpreted as one corresponding to a system close to the critical point of a second order phase transition. The analysis demonstrates that the resting brain spends most of the time near the critical point of such transition and exhibits avalanches of activity ruled by the same dynamical and statistical properties described previously for neuronal events at smaller scales. Given the demonstrated functional relevance of the resting state brain dynamics, its representation as a discrete process might facilitate large-scale analysis of brain function both in health and disease.
671 citations
Cites background or methods or result from "Emergent complex neural dynamics"
...with sizes up to 103 and have no preferred scale, a behavior very similar to that of neuronal avalanches described previously in smaller scales (Beggs and Plenz, 2003; Petermann et al., 2009; Chialvo, 2010)....
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...The spatiotemporal statistics are then considered, revealing novel aspects of the brain dynamics which are scale-invariant, consistent with that shown for other systems at the critical state (Bak, 1996; Jensen, 1998; Chialvo, 2010; Expert et al., 2011)....
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...At the same time, similar efforts are dedicated to place brain phenomenology in the context of statistical physics theory (Chialvo, 2010; Rolls and Deco, 2010; Sporns, 2010; Steyn-Rose and Steyn-Rose, 2010)....
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...In addition to uncover new dynamical properties for the activated clusters, the method exposed scale-invariant features conjectured in the past (Chialvo, 2010) which are identical to those seen at smaller scales (Beggs and Plenz, 2003; Petermann et al....
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...…length of the activity measured with fMRI diverges as predicted by the theory of phase transitions (Fraiman and Chialvo, 2010), supporting the hypothesis that brain dynamics operates at a critical point of a second order phase transition (Bak, 1996; Chialvo, 2010; Tagliazucchi and Chialvo, 2011)....
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References
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TL;DR: This study’s findings can provide practical guidelines to steer partnership programs within the academic and clinical bodies, with the aim of providing a collaborative partnership approach to clinical education.
Abstract: The aim of our systematic review was to retrieve and integrate relevant evidence related to the process of formation and implementation of the academic–service partnership, with the aim of reformin...
41,134 citations
28 Jul 2005
TL;DR: PfPMP1）与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。
18,940 citations
TL;DR: A model of a system having a large number of simple equivalent components, based on aspects of neurobiology but readily adapted to integrated circuits, produces a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size.
Abstract: Computational properties of use of biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices.
16,652 citations
TL;DR: This article reviews studies investigating complex brain networks in diverse experimental modalities and provides an accessible introduction to the basic principles of graph theory and highlights the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
Abstract: Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
9,700 citations
"Emergent complex neural dynamics" refers background in this paper
...Extensive reviews [57, 58] cover the statistical physics approaches that are increasingly being use to analyze this large body of complex data....
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TL;DR: It is shown that dynamical systems with spatial degrees of freedom naturally evolve into a self-organized critical point, and flicker noise, or 1/f noise, can be identified with the dynamics of the critical state.
Abstract: We show that dynamical systems with spatial degrees of freedom naturally evolve into a self-organized critical point. Flicker noise, or 1/f noise, can be identified with the dynamics of the critical state. This picture also yields insight into the origin of fractal objects.
6,486 citations
"Emergent complex neural dynamics" refers background in this paper
...In other words, animals need a brain because the world is critical [1, 15, 31, 37]....
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...The most significant efforts were those aimed at discovering the conditions in which something complex emerges from the interaction of the constituting non-complex elements [1, 31]....
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