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Googling the Brain: Discovering Hierarchical and Asymmetric Network Structures, with Applications in Neuroscience

Jonathan J. Crofts, Desmond J. Higham
2011 Internet Mathematics  
2011) Googling the brain : discovering hierarchical and asymmetric network structures, with applications in neuroscience. Internet Mathematics, 7 (4). pp. 233-254.  ...  Abstract Hierarchical organisation is a common feature of many directed networks arising in nature and technology.  ...  The adjacency matrix is shown in Figure 3 . Table 3 quantifies the ability of each method to discover hierarchical structure.  ... 
doi:10.1080/15427951.2011.604284 fatcat:mgwnwhpvpbavrabtmfcjhydtdq

The organization of physiological brain networks

C.J. Stam, E.C.W. van Straaten
2012 Clinical Neurophysiology  
Interest in brain network studies has increased strongly with the advent of modern network theory and increasingly powerful investigative techniques such as "highdensity EEG", MEG, functional and structural  ...  In addition to the already established network models, we suggest a heuristic model including hierarchical modularity. a b s t r a c t One of the central questions in neuroscience is how communication  ...  To a large extent, structural and functional studies reveal the same complex and in particular hierarchical network structure of the brain at multiple levels (Bassett et al., 2008) .  ... 
doi:10.1016/j.clinph.2012.01.011 pmid:22356937 fatcat:d6qeu4q46vcmpdnxqgpko3jtga

Evolving Signal Processing for Brain–Computer Interfaces

S. Makeig, C. Kothe, T. Mullen, N. Bigdely-Shamlo, Zhilin Zhang, Kenneth Kreutz-Delgado
2012 Proceedings of the IEEE  
, and contextual data that may in the future be increasingly ubiquitous.  ...  | Because of the increasing portability and wearability of noninvasive electrophysiological systems that record and process electrical signals from the human brain, automated systems for assessing changes  ...  Acknowledgment The authors would like to thank Zeynep Akalin Acar for use of her EEG simulation (Fig. 1) and Jason Palmer and Clemens Brunner for useful discussions.  ... 
doi:10.1109/jproc.2012.2185009 fatcat:ebed3ribeneptnatoxaoyzn4xm

Using big data to map the network organization of the brain

James E. Swain, Chandra Sripada, John D. Swain
2014 Behavioral and Brain Sciences  
AbstractThe past few years have shown a major rise in network analysis of "big data" sets in the social sciences, revealing non-obvious patterns of organization and dynamic principles.  ...  Connectomic neural analyses, informed by social network theory, may be helpful in understanding underlying fundamental principles of brain organization.  ...  In Figure 8 , we have placed in the southeast the diffuse networks that Lieberman et al. (2005) identify with drift and in the northeast the hierarchical networks they associate with selection.  ... 
doi:10.1017/s0140525x13001908 pmid:24572243 pmcid:PMC4327852 fatcat:6buaugmen5d3nkhj6gxpaxrfh4

The Tensor Brain: Semantic Decoding for Perception and Memory [article]

Volker Tresp and Sahand Sharifzadeh and Dario Konopatzki and Yunpu Ma
2020 arXiv   pre-print
and memory in the brain.  ...  We discuss the operations of the four layers and relate them to the global workspace theory. In a Bayesian brain interpretation, semantic memory defines the prior for observable triple statements.  ...  In different brain regions, maps have been discovered that code for visual appearance, sound, and function.  ... 
arXiv:2001.11027v3 fatcat:rruvq42earhljnpw4oxvfunhte

Humanoid Cognitive Robots That Learn by Imitating: Implications for Consciousness Studies

James A. Reggia, Garrett E. Katz, Gregory P. Davis
2018 Frontiers in Robotics and AI  
Based on our initial results, we argue that the top-down cognitive control of working memory, and in particular its gating mechanisms, is an important potential computational correlate of consciousness  ...  In particular, its cognitive components center on top-down control of a working memory that retains the explanatory interpretations that the robot constructs during learning.  ...  The CEG is related to past work in philosophy, neuroscience, and psychology, addressing various aspects of the mind–brain problem.  ... 
doi:10.3389/frobt.2018.00001 pmid:33500888 pmcid:PMC7806019 fatcat:h7ljzgobxvhzpl7fmyh4r54hhy

Mapping collective behavior – beware of looping

Markus Christen, Peter Brugger
2014 Behavioral and Brain Sciences  
AbstractWe discuss ambiguities of the two main dimensions of the map proposed by Bentley and colleagues that relate to the degree of self-reflection the observed agents have upon their behavior.  ...  We outline how this can be understood as a dimension of "height" in the map of Bentley et al.  ...  In Figure 8 , we have placed in the southeast the diffuse networks that Lieberman et al. (2005) identify with drift and in the northeast the hierarchical networks they associate with selection.  ... 
doi:10.1017/s0140525x13001696 pmid:24572221 fatcat:qsfmoow6zvb6xb3u57tgvfwada

Neurocognitive anthropology: What are the options?

Guy Vingerhoets
2012 Behavioral and Brain Sciences  
AbstractInvestigation of the cerebral organization of cognition in modern humans may serve as a tool for a better understanding of the evolutionary origins of our unique cognitive abilities.  ...  This commentary suggests three approaches that may serve this purpose: (1) cross-task neural overlap, referred to by Vaesen; but also (2) co-lateralization of asymmetric cognitive functions and (3) cross-functional  ...  Selection favored the cognitive structures dependent on brain organization and social structure which resulted in both language and toolmaking.  ... 
doi:10.1017/s0140525x11002111 pmid:22697608 fatcat:ybwz6ns3jfa5rkta3s5jucuw4m

Big data in the new media environment

Matthew Brook O'Donnell, Emily B. Falk, Sara Konrath
2014 Behavioral and Brain Sciences  
., socially motivated versus independently motivated) decision-making dimension in light of findings from social psychology and neuroscience.  ...  AbstractBentley et al. argue for the social scientific contextualization of "big data" by proposing a four-quadrant model.  ...  In Figure 8 , we have placed in the southeast the diffuse networks that Lieberman et al. (2005) identify with drift and in the northeast the hierarchical networks they associate with selection.  ... 
doi:10.1017/s0140525x13001672 pmid:24572235 fatcat:hrck375xfvcirb5qt5uifx766y

Adding network structure onto the map of collective behavior

Santo Fortunato, Jari Saramäki, Jukka-Pekka Onnela
2014 Behavioral and Brain Sciences  
This dimension, which captures a feature of network community structure, is known both from theory and from experiments to be relevant for decision-making processes.  ...  AbstractWe propose an extension to the map of Bentley et al. by incorporating an aspect of underlying network structure that is likely relevant for many modes of collective behavior.  ...  In Figure 8 , we have placed in the southeast the diffuse networks that Lieberman et al. (2005) identify with drift and in the northeast the hierarchical networks they associate with selection.  ... 
doi:10.1017/s0140525x13001726 pmid:24572224 fatcat:bgko434cvng4lnrayuitysm6om

Mapping collective behavior in the big-data era

R. Alexander Bentley, Michael J. O'Brien, William A. Brock
2014 Behavioral and Brain Sciences  
the degree to which there is transparency in the payoffs and risks associated with the decisions agents make.  ...  In the online age, however, social phenomena can occur with unprecedented scale and unpredictability, and individuals have access to social connections never before possible.  ...  In Figure 8 , we have placed in the southeast the diffuse networks that Lieberman et al. (2005) identify with drift and in the northeast the hierarchical networks they associate with selection.  ... 
doi:10.1017/s0140525x13000289 pmid:24572217 fatcat:qrajnq2fine7ddjtbjzkk6weea

"Big data" needs an analysis of decision processes

Pantelis P. Analytis, Mehdi Moussaïd, Florian Artinger, Juliane E. Kämmer, Gerd Gigerenzer
2014 Behavioral and Brain Sciences  
Within the same environment, two decision processes can generate strikingly different collective behavior; in two environments that fundamentally differ in transparency, a single process gives rise to  ...  AbstractWe demonstrate by means of a simulation that the conceptual map presented by Bentley et al. is incomplete without taking into account people's decision processes.  ...  In Figure 8 , we have placed in the southeast the diffuse networks that Lieberman et al. (2005) identify with drift and in the northeast the hierarchical networks they associate with selection.  ... 
doi:10.1017/s0140525x13001659 pmid:24572218 fatcat:hia3dthrdzdk5ig2ggqwxtbt4e

The cognitive bases of human tool use

Krist Vaesen
2012 Behavioral and Brain Sciences  
The first is to assess, in the face of accruing reports on the ingenuity of great ape tool use, whether and in what sense human tool use still evidences unique, higher cognitive ability.  ...  In particular, I show how the cognitive traits reviewed help to explain why technological accumulation evolved so markedly in humans, and so modestly in apes.  ...  Selection favored the cognitive structures dependent on brain organization and social structure which resulted in both language and toolmaking.  ... 
doi:10.1017/s0140525x11001452 pmid:22697258 fatcat:yfvrgqa6gzenhkcsmrl5x5edle

Cultural evolution in more than two dimensions: Distinguishing social learning biases and identifying payoff structures

Alex Mesoudi
2014 Behavioral and Brain Sciences  
Here, I qualify their scheme by arguing that different social learning biases should be treated distinctly, and that the transparency of decisions is sometimes conflated with the actual underlying payoff  ...  structure of those decisions.  ...  In Figure 8 , we have placed in the southeast the diffuse networks that Lieberman et al. (2005) identify with drift and in the northeast the hierarchical networks they associate with selection.  ... 
doi:10.1017/s0140525x13001805 pmid:24572232 fatcat:kh45ncgbpfcqnaa6fxm3nsm2ne

Keeping conceptual boundaries distinct between decision making and learning is necessary to understand social influence

Gaël Le Mens
2014 Behavioral and Brain Sciences  
AbstractBentley et al. make the deliberate choice to blur the distinction between learning and decision making.  ...  This obscures the social influence mechanisms that operate in the various empirical settings that their map aims to categorize.  ...  In Figure 8 , we have placed in the southeast the diffuse networks that Lieberman et al. (2005) identify with drift and in the northeast the hierarchical networks they associate with selection.  ... 
doi:10.1017/s0140525x13001775 pmid:24572229 fatcat:rcxn7aypjvabraowo4y7njxia4
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