Scaling in topological properties of brain networks

Singh, Soibam Shyamchand; Khundrakpam, Budhachandra; Reid, Andrew; Lewis, John D.; Evans, Alan C.; Ishrat, Romana; Sharma, Bharat; Singh, R. K. Brojen

doi:10.1038/srep24926

Cited by 24 publications

(15 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, speaking about “hierarchical organization” of the brain, we here do not refer to a qualitative representation of psychic functions, but to the anatomical and functional architecture of the brain. This functional neuroanatomy displays features of a fractal organization: parallel elements account for different functional domains [15]. They are coupled through multiple organizational levels to systems with increasing complexity but with recurrent principles such as mutual inhibitory control, forming balanced loops.…”

Section: Outline Of Synopsismentioning

confidence: 99%

Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems

et al. 2017

View full text Add to dashboard Cite

Schizophrenia research has been in a deadlock for many decades. Despite important advances in clinical treatment, there are still major concerns regarding long-term psychosocial reintegration and disease management, biological heterogeneity, unsatisfactory predictors of individual course and treatment strategies, and a confusing variety of controversial theories about its etiology and pathophysiological mechanisms. In the present perspective on schizophrenia research, we first discuss a methodological pitfall in contemporary schizophrenia research inherent in the attempt to link mental phenomena with the brain: we claim that the time-honored phenomenological method of defining mental symptoms should not be contaminated with the naturalistic approach of modern neuroscience. We then describe our Systems Neuroscience of Psychosis (SyNoPsis) project, which aims to overcome this intrinsic problem of psychiatric research. Considering schizophrenia primarily as a disorder of interindividual communication, we developed a neurobiologically informed semiotics of psychotic disorders, as well as an operational clinical rating scale. The novel psychopathology allows disentangling the clinical manifestations of schizophrenia into behavioral domains matching the functions of three well-described higher-order corticobasal brain systems involved in interindividual human communication, namely, the limbic, associative, and motor loops, including their corticocortical sensorimotor connections. The results of several empirical studies support the hypothesis that the proposed three-dimensional symptom structure, segregated into the affective, the language, and the motor domain, can be specifically mapped onto structural and functional abnormalities of the respective brain systems. New pathophysiological hypotheses derived from this brain system-oriented approach have helped to develop and improve novel treatment strategies with noninvasive brain stimulation and practicable clinical parameters. In clinical practice, the novel psychopathology allows confining the communication deficits of the individual patient, shifting attention from the symptoms to the intact resources. We have studied this approach and observed important advantages for therapeutic alliances, personalized treatment, and de-escalation strategies. Future studies will further conjoin clinical definitions of psychotic symptoms with brain structures and functions, and disentangle structural and functional deficit patterns within these systems to identify neurobiologically distinct subsyndromes. Neurobiologically homogeneous patient groups may provide new momentum for treatment research. Finally, lessons learned from schizophrenia research may contribute to developing a comprehensive perspective on human experience and behavior that integrates methodologically distinct, but internally consistent, insights from humanities and neuroscience.

show abstract

Section: Outline Of Synopsismentioning

confidence: 99%

Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems

et al. 2017

View full text Add to dashboard Cite

show abstract

“…C. elegans' neuronal network, consisting of N = 277 nodes, is one such type which have hierarchical organization of communities/sub-communities at various levels of organization ( Fig. 1), and similar nature of topological organization was obtained in cat (N = 52) and macaque monkey (N = 71) brain networks also [8]. If such a network is defined by G(L, N ), then network at level-2 is organized by a set of m communities defined by a set of sub-graphs {G [2] i }, i = 1, 2, ..., m constructed from level-1, i.e., the whole network.…”

Section: Properties Of Hamiltonian Function In Complex Brain Networkmentioning

confidence: 53%

“…These distributions of connectivities, in brain networks constructed from functional magnetic resonance imaging, diffusion tensor imaging, electroencephalogram, electrooculogram, etc., may be fundamentally related to energy distributions in brain. We have studied the energy distribution in the brain networks of three species [8] using simple but efficient CPM approach [12][13][14]. The edge distributions at various levels of organization are found to be different which are reflected in the energy distributions calculated via CPM, and also the Hamiltonian calculated as a function of levels of organization is found to follow power-law or fractal behavior which is a signature of self-organization red in the system.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Organization in complex brain networks: energy distributions and phase shift

Sharma

Singh²,

Haobijam

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

The Hamiltonian function of a network, derived from the intrinsic distributions of nodes and edges, magnified by resolution parameter has information on the distribution of energy in the network. In brain networks, the Hamiltonian function follows hierarchical features reflecting a power-law behavior which can be a signature of self-organization. Further, the transition of three distinct phases driven by resolution parameter is observed which could correspond to various important brain states. This resolution parameter could thus reflect a key parameter that controls and balances the energy distribution in the brain network.

show abstract

“…Hierarchically organized networks generally qualify most of the features of self-organization, namely, fractal behaviours of topological parameters, system level organization of modules and absence of central control mechanism (removal of hubs do not cause network breakdown)4142. However, neighborhood connectivity in these networks constructed from the dynamical states of stress p53 driven by either nutlin or Axin follows, C n ( k ) ~ k β , which is power law of positive exponent (Figs 2G and 3G).…”

Section: Resultsmentioning

confidence: 99%

Dynamical states, possibilities and propagation of stress signal

Malik

Ali

Ishrat

2017

Sci Rep

Self Cite

View full text Add to dashboard Cite

The stress driven dynamics of Notch-Wnt-p53 cross-talk is subjected to a few possible dynamical states governed by simple fractal rules, and allowed to decide its own fate by choosing one of these states which are contributed from long range correlation with varied fluctuations due to active molecular interaction. The topological properties of the networks corresponding to these dynamical states have hierarchical features with assortive structure. The stress signal driven by nutlin and modulated by mediator GSK3 acts as anti-apoptotic signal in this system, whereas, the stress signal driven by Axin and modulated by GSK3 behaves as anti-apoptotic for a certain range of Axin and GSK3 interaction, and beyond which the signal acts as favor-apoptotic signal. However, this stress system prefers to stay in an active dynamical state whose counterpart complex network is closest to hierarchical topology with exhibited roles of few interacting hubs. During the propagation of stress signal, the system allows the propagator pathway to inherit all possible properties of the state to the receiver pathway/pathways with slight modifications, indicating efficient information processing and democratic sharing of responsibilities in the system via cross-talk. The increase in the number of cross-talk pathways in the system favors to establish self-organization.

show abstract

Scaling in topological properties of brain networks

Cited by 24 publications

References 68 publications

Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems

Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems

Organization in complex brain networks: energy distributions and phase shift

Dynamical states, possibilities and propagation of stress signal

Contact Info

Product

Resources

About