Critical branching neural computation

Kello, Christopher T.; Mayberry, Marshall R.

doi:10.1109/ijcnn.2010.5596813

Cited by 10 publications

(12 citation statements)

References 27 publications

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“…Recent work leading up to the present model began by characterizing spike dynamics as a branching process Kello, Kerster, & Johnson, 2011;Kello & Mayberry, 2010). In any given network, an ancestor spike occurring on neuron / at time t may subsequently "branch" into some number of descendant spikes at times t + T^, where descendant spikes occur on neurons directly connected via axonal synapses, indexed by k. Thus, subsequent spikes triggered downstream do not count as descendants of neuron /, but rather as descendants of their directly connected neurons.…”

Section: Computational Capacity and Critical Branchingmentioning

confidence: 99%

Critical branching neural networks.

Kello

2013

Psychological Review

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It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical branching and, in doing so, simulates observed scaling laws as pervasive to neural and behavioral activity. These scaling laws are related to neural and cognitive functions, in that critical branching is shown to yield spiking activity with maximal memory and encoding capacities when analyzed using reservoir computing techniques. The model is also shown to account for findings of pervasive 1/f scaling in speech and cued response behaviors that are difficult to explain by isolable causes. Issues and questions raised by the model and its results are discussed from the perspectives of physics, neuroscience, computer and information sciences, and psychological and cognitive sciences.

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Section: Computational Capacity and Critical Branchingmentioning

confidence: 99%

Critical branching neural networks.

Kello

2013

Psychological Review

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“…According to Anderson and colleagues, the operation of the brain gives way to these intrinsic dynamics during conscious processing, which can be identified both in waking states and in REM sleep. Kello (under review;Kello et al 2010) has developed a model that suggests that sustained operation of a complex nervous system requires this "echo" of noise, as it reflects the balance between two dangerous equilibria: zero activity in the brain (akin to death) and saturation of activity (akin to debilitating seizure) (cf. self-organized criticality: Bak et al 1987; also its relationship to homeostasis for cognitive function: Parvizi & Damasio 2001).…”

Section: Challenge 1: the Sustained Dynamics Of Phenomenal Experiencementioning

confidence: 99%

“…In other words, the larger/slower scales of human activity make spike patterns and behavioral patterns more than just patterns -recall that traffic jams are patterns too, and such patterns often exhibit the same earmarks of complexity (e.g. scaling laws; Kello et al 2010) as neural and behavioral activity. What traffic jams and many other complex patterns lack, however, is a hierarchical nesting within the dynamics of learning, long-term memory, culture, and evolution.…”

Section: The Hierarchy Of Human Activity: Which Scales?mentioning

confidence: 99%

An integrative pluralistic approach to phenomenal consciousness

Dale¹,

Tollefsen²,

Kello³

2012

Being in Time

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We review theories and empirical research on underlying mechanisms of selfhood, awareness, and conscious experience. The mechanisms that have been identified for these phenomena are many and multifarious, lying at many levels of space and time, and complexity and abstractness. Proposals have included the global workspace for conscious information, action and its centrality to self awareness, the role for social information and narrative, and more. We argue that phenomenal experience, whatever it "really is," is probably dependent upon all of these levels simultaneously. We end with two challenges for consciousness research. Both are couched in terms of the dynamics of phenomenal experience. The first is to investigate the sustained dynamics of phenomenal experience; the second is to unveil the way that multi-scale processes in the cognitive system interact to produce that richness of experience. We do not aim to solve the hard problem, but argue that any solution will require this plural characteristic.

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“…At the same time, I became involved in a project led by IBM to design and build a neurosynaptic computer chip (Arthur et al, 2012). This project spurred me to formulate an algorithm that could selfregulate network activity to maintain critical branching in spike propagation (Kello & Mayberry, 2010). The resulting neural network model of SOC has proven capable of simulating many of the findings that drove Guy and me toward complex dynamic systems (Kello, 2013).…”

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confidence: 99%