Transparallel processing by hyperstrings

Helm, Peter A. van der

doi:10.1073/pnas.0403402101

Cited by 24 publications

(28 citation statements)

References 41 publications

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“…3). However, these are actually the relatively easy parts of the problem-they can be solved by traditional computing methods (van der Helm 2004(van der Helm , 2012(van der Helm , 2014. Therefore, here, I focus not so much on the entire minimal coding problem, but rather on its hard part, namely, the problem that the argument of every detected symmetry or alternation has to be hierarchically recoded before a simplest code may be selected (repetition does not pose this problem).…”

Section: Hyperstringsmentioning

confidence: 98%

Transparallel mind: classical computing with quantum power

Helm

2015

Artif Intell Rev

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Inspired by the extraordinary computing power promised by quantum computers, the quantum mind hypothesis postulated that quantum mechanical phenomena are the source of neuronal synchronization, which, in turn, might underlie consciousness. Here, I present an alternative inspired by a classical computing method with quantum power. This method relies on special distributed representations called hyperstrings. Hyperstrings are superpositions of up to an exponential number of strings, which-by a single-processor classical computercan be evaluated in a transparallel fashion, that is, simultaneously as if only one string were concerned. Building on a neurally plausible model of human visual perceptual organization, in which hyperstrings are formal counterparts of transient neural assemblies, I postulate that synchronization in such assemblies is a manifestation of transparallel information processing. This accounts for the high combinatorial capacity and speed of human visual perceptual organization and strengthens ideas that self-organizing cognitive architecture bridges the gap between neurons and consciousness.

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Section: Hyperstringsmentioning

confidence: 98%

Transparallel mind: classical computing with quantum power

Helm

2015

Artif Intell Rev

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“…Actually, it is already feasible on single-processor classical computers, and structural coding implemented it in PISA, which is a minimal coding algorithm for strings (van der Helm, 2004(van der Helm, , 2015a. Notably, to compute guaranteed simplest codes of strings, PISA employs formal counterparts of the three perceptual subprocesses in Fig.…”

Section: Transparallel Processingmentioning

confidence: 99%

“…6. Through exploiting visual regularities such as repetition and symmetry, such codes specify strings by a minimum number of descriptive parameters (for formal and empirical underpinnings of the choice of employed regularities, see , 2004. Notice that a string gives rise to a superexponential number of candidate codes (i.e., hypotheses), so that the simplest one is probably not tractable by traditional forms of processing.…”

Section: Transparallel Processingmentioning

confidence: 99%

“…The first version of PISA (van der Helm & Leeuwenberg, 1986) already employed what Lee and Mumford (2003) called particle filtering, but then, with particle updating guided by propagation of the Occamian simplicity belief. The second version (van der Helm, 1988) added the basics of what van der Helm (2004) formalized as transparallel processing by hyperstrings. The latter is fully implemented in the latest version, which is available in the Supplemental Material of van der Helm (2015a).…”

Section: Transparallel Processingmentioning

confidence: 99%

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Structural coding versus free-energy predictive coding

Helm

2015

Psychon Bull Rev

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Focusing on visual perceptual organization, this article contrasts the free-energy (FE) version of predictive coding (a recent Bayesian approach) to structural coding (a long-standing representational approach). Both use freeenergy minimization as metaphor for processing in the brain, but their formal elaborations of this metaphor are fundamentally different. FE predictive coding formalizes it by minimization of prediction errors, whereas structural coding formalizes it by minimization of the descriptive complexity of predictions. Here, both sides are evaluated. A conclusion regarding competence is that FE predictive coding uses a powerful modeling technique, but that structural coding has more explanatory power. A conclusion regarding performance is that FE predictive coding-though more detailed in its account of neurophysiological data-provides a less compelling cognitive architecture than that of structural coding, which, for instance, supplies formal support for the computationally powerful role it attributes to neuronal synchronization.

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“…Transparallel processing with hyperstrings [6] arises in the context of Stuctural Information Theory (SIT) [7]. Like CHAINS, SIT was originally motivated by the idea that perceptual coding involves finding the shortest description to describe the sensory input (in that case, visual input), and it proceeds by discovering alternative regularities in a string.…”

Section: Modelling Sequencesmentioning

confidence: 99%

CHAINS: Competition and cooperation between fragmentary event predictors in a Model of Auditory Scene Analysis

Mill

Bőhm²,

Bendixen

et al. 2011

2011 45th Annual Conference on Information Sciences and Systems

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Abstract-This paper presents an algorithm called CHAINS for separating temporal patterns of events that are mixed together. The algorithm is motivated by the task the auditory system faces when it attempts to analyse an acoustic mixture to determine the sources that contribute to it, and in particular, sources that emit regular sequences. The task is complicated by the fact that a mixture can be interpreted in several ways. For example, a complex pattern may issue from a complex source; or, alternatively, it may arise from the interaction of many simple sources. The idea pursued here is that the brain attempts to account for an incoming sequence in terms of short, fragmentary sequences, called chains. Chains are built as the input arrives and, once built, are used to predict inputs. A group of chains can coalesce to form an organisation, in which the member chains alternately generate predictions. A chain fails upon making an incorrect prediction, and any organisation it belongs to collapses. Several incompatible organisations can exist in parallel. The CHAINS algorithm thus remains open to multiple interpretations of a sequence. Perceptual multistability, in which the perceptual experience of an ambiguous stimulus switches spontaneously from one interpretation to another, seems to require a similar flexibility of representation.

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Transparallel processing by hyperstrings

Cited by 24 publications

References 41 publications

Transparallel mind: classical computing with quantum power

Transparallel mind: classical computing with quantum power

Structural coding versus free-energy predictive coding

CHAINS: Competition and cooperation between fragmentary event predictors in a Model of Auditory Scene Analysis

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