Biomedical subjects

B A Huberman

Publications and source records attributed to B A Huberman.

10 recordsLinked to original sources

PubMed2001

Portfolios of quantum algorithms.

Quantum computation holds promise for the solution of many intractable problems. However, since many quantum algorithms are stochastic in nature they can find the solution of hard problems only probabilistically. Thus the efficiency of the algorithms has to be characterized by both the expected time to completion and the associated variance. In order to minimize both the running time and its uncertainty, we show that portfolios of quantum algorithms analogous to those of finance can outperform single algorithms when applied to the NP-complete problems such as 3-satisfiability.

Journal Article↗

PubMed2001

Search in power-law networks.

Many communication and social networks have power-law link distributions, containing a few nodes that have a very high degree and many with low degree. The high connectivity nodes play the important role of hubs in communication and networking, a fact that can be exploited when designing efficient search algorithms. We introduce a number of local search strategies that utilize high degree nodes in power-law graphs and that have costs scaling sublinearly with the size of the graph. We also demonstrate the utility of these strategies on the GNUTELLA peer-to-peer network.

Journal Article↗

PubMed1993

Evolutionary games and computer simulations.

The Prisoner's Dilemma has long been considered the paradigm for studying the emergence of cooperation among selfish individuals. Because of its importance, it has been studied through computer experiments as well as in the laboratory and by analytical means. However, there are important differences between the way a system composed of many interacting elements is simulated by a digital machine and the manner in which it behaves when studied in real experiments. In some instances, these disparities can be marked enough so as to cast doubt on the implications of cellular automata-type simulations for the study of cooperation in social systems. In particular, if such a simulation imposes space-time granularity, then its ability to describe the real world may be compromised. Indeed, we show that the results of digital simulations regarding territoriality and cooperation differ greatly when time is discrete as opposed to continuous.

Animals↗

PubMed1992

Gaucher's disease: case report of mandibular trauma.

Gaucher's disease is a disturbance of lipid storage that results in the accumulation of histiocytes filled with glucosyl ceramide in various organs and bones. Clinical features include history of epistaxis, hemoptysis, and spontaneous gingival hemorrhage. This article reviews Gaucher's disease with reference to its importance to dental practitioners and a case involving mandibular trauma is presented.

Accidents, Traffic↗

PubMed1992

An associationist model of the paranoid process: application of phase transitions in spreading activation networks.

We propose an associationist model of the paranoid process in which the initial paranoid state is characterized by the formation of cognitive associations among temporally contiguous perceptions, an internally generated explanatory schema is produced to give meaning to the associations, and the schema then becomes learned and perpetuated as a crystallized delusion. We suggest that the genesis of the initial paranoid state can be modeled by a spreading activation network of learning and memory whose parameters of activation spread, including connectivity and relaxation rate, are varying over time. Moreover, recently demonstrated abrupt phase transitions that occur in such networks as a function of connectivity provide a particularly useful means for understanding the process by which an initial paranoid state becomes crystallized into a fixed delusion.

Association Learning↗

PubMed1989

The stability of ecosystems.

Stability criteria and phase boundaries for complex ecosystems are obtained and contrasted with previously studied scenarios. The stability of such systems is determined by the behaviour of the largest eigenvalue of matrices governing the response of the system to small perturbations. As a result we show that ecosystems with unstructured cooperative interactions between arbitary species can be less stable than had been previously determined. We also examine hierarchical ecologies, and demonstrate their increased stability under certain conditions.

Animals↗

PubMed1988

A graph-dynamic model of the power law of practice and the problem-solving fan-effect.

Numerous human learning phenomena have been observed and captured by individual laws, but no unified theory of learning has succeeded in accounting for these observations. A theory and model are proposed that account for two of these phenomena: the power law of practice and the problem-solving fan-effect. The power law of practice states that the speed of performance of a task will improve as a power of the number of times that the task is performed. The power law resulting from two sorts of problem-solving changes, addition of operators to the problem-space graph and alterations in the decision procedure used to decide which operator to apply at a particular state, is empirically demonstrated. The model provides an analytic account for both of these sources of the power law. The model also predicts a problem-solving fan-effect, slowdown during practice caused by an increase in the difficulty of making useful decisions between possible paths, which is also found empirically.

Decision Making↗

PubMed1987

A model for dysfunctions in smooth pursuit eye movement.

In this paper, I have introduced and solved a simple deterministic model of eye tracking that produces rich dynamical behavior. Some of its main features, notably the existence of a chaotic regime, are reminiscent of the anomalies reported in smooth pursuit eye tracking experiments with schizophrenia patients. By obtaining the state diagram of such a model as a function of target frequency and amplitude, we showed the existence of a chaotic regime characterized by a strange attractor in phase-space and associated random velocity arrests in the eye dynamics. Moreover, the power spectrum contains features similar to those reported in the literature. The correctness of this model could in principle be determined by performing experiments where the target parameters (i.e., amplitude and frequency) could be varied in a systematic manner and by taking Poincaré maps from the corresponding time series. Although the present status of such experiments prevents us from verifying the validity of the model, the available data does not seem to contradict the main predictions. Furthermore, we showed that the inevitable noise expected to be present in actual experiments would only enhance the observability of our predictions. If this model were proven incorrect, then the focus of research into mechanisms will have to shift into a search for an intrinsic source of the fluctuations. If, on the other hand, this deterministic theory has any validity, it will point to the nonlinearities in eye tracking mechanisms as the main culprits for the observed anomalies.

Eye Movements↗

PubMed1984

Understanding biological computation: reliable learning and recognition.

We experimentally examine the consequences of the hypothesis that the brain operates reliably, even though individual components may intermittently fail, by computing with dynamical attractors. Specifically, such a mechanism exploits dynamic collective behavior of a system with attractive fixed points in its phase space. In contrast to the usual methods of reliable computation involving a large number of redundant elements, this technique of self-repair only requires collective computation with a few units, and it is amenable to quantitative investigation. Experiments on parallel computing arrays show that this mechanism leads naturally to rapid self-repair, adaptation to the environment, recognition and discrimination of fuzzy inputs, and conditional learning, properties that are commonly associated with biological computation.

Adaptation, Physiological↗

PubMed1984

Chaotic behavior in dopamine neurodynamics.

We report the results of the dynamics of a model of the central dopaminergic neuronal system. In particular, for certain values of a parameter k, which monitors the efficacy of dopamine at the postsynaptic receptor, chaotic solutions of the dynamical equations appear--a prediction that correlates with the observed increased variability in behavior among schizophrenics, the rapid fluctuations in motor activity among Parkinsonian patients treated chronically with L-dopa, and the lability of mood in some patients with an affective disorder. Moreover our hypothesis offers specific results concerning the appearance or disappearance of erratic solutions as a function of k and the external input to the dopamine neuronal system.

Brain↗