3,259 research outputs found
A neurocomputational model for optimal temporal processing
Full text linkHumans can estimate the duration of intervals of time, and psychophysical experiments show that these estimations are subject to timing errors. According to standard theories of timing, these errors increase linearly with the interval to be estimated (Weber’s law), and both at longer and shorter intervals, deviations from linearity are reported. This is not easily reconciled with the accumulation of neuronal noise, which would only lead to an increase with the square root of the interval. Here, we offer a neuronal model which explains the form of the error function as a result of a constrained optimization process. The model consists of a number of synfire chains with different transmission times, which project onto a set of readout neurons. We show that an increase in the transmission time corresponds to a superlinear increase of the timing errors. Under the assumption of a fixed chain length, the experimentally observed error function emerges from optimal selection of chains for each given interval. Furthermore, we show how this optimal selection could be implemented by competitive spike-timing dependent plasticity in the connections from the chains to the readout network, and discuss implications of our model on selective temporal learning and possible neural architectures of interval timing
Nonlinear integration of evidence in a dynamic motor task
Full text linkReaching movements are governed by estimates of sensory and environmental quantities. If performed under uncertainty they are often based on prior expectations that summarise previous relevant information. We study the temporal evolution of the decision priors in a twoalternative forced-choice movement task
Emergence of behavioral primitives in self-organizing control and composition of behavior for autonomous robots
Full text linkA new heuristic for the total tardiness problem with parallel machines
Full text linkBiskup D, Herrmann J. A new heuristic for the total tardiness problem with parallel machines. Discussion paper / Fakultät für Wirtschaftswissenschaften, Universität Bielefeld. Bielefeld: Universität Bielefeld; 2007.Scheduling jobs against due dates is one of the most important and best examined objectives in scheduling theory and practice. In this paper the parallel machine version of the well-known total tardiness problem is considered. The objective is to minimize the total tardiness of the jobs, while for all jobs an individual due date is given. The single machine version has been proven to be NP-hard, hence it is unlikely to find polynomially bounded optimization algorithms. Consequently, we concentrate on developing an efficient heuristic. Our extensive computational results confirm that our new heuristic is capable to deliver near optimal results
Inhibition in the dynamics of selective attention: an integrative model for negative priming
Full text linkWe introduce a computational model of the negative priming (NP) effect that includes perception, memory, attention, decision making, and action. The model is designed to provide a coherent picture across competing theories of NP. The model is formulated in terms of abstract dynamics for the activations of features, their binding into object entities, their semantic categorization as well as related memories and appropriate reactions. The dynamic variables interact in a connectionist network which is shown to be adaptable to a variety of experimental paradigms. We find that selective attention can be modeled by means of inhibitory processes and by a threshold dynamics. From the necessity of quantifying the experimental paradigms, we conclude that the specificity of the experimental paradigm must be taken into account when predicting the nature of the NP effect
Optimal mass distribution for passivity-based bipedal robots
No full textThis paper reports how and to what extent the mass distribution of a passive dynamic walker can be tuned to maximize walking speed and stability. An exploration of the complete parameter space of a bipedal walker is performed by numerical optimization, and optimal manifolds are found in terms of speed, the form of which can be explained by a physical analysis of step periods. Stability, quantified by the minimal basin of attraction, is also shown to be high along these manifolds, but with a maximum at only moderate speeds. Furthermore, it is examined how speed and stability change on different ground slopes. The observed dependence of the stability measure oil the slope is consistent with the interpretation of the walking cycle as a feedback loop, which also provides an explanation for the destabilization of the gait at higher slopes. Regarding speed, an unexpected decrease at higher slopes is observed. This effect reveals another important feature of passive dynamic walking, a swing-back phase of the swing leg near the end of a step, which decreases walking speed on the one hand, but seems to be crucial for the stability of the gait on the other hand. In conclusion, maximal robustness and highest walking speed are shown to be partly conflicting objectives of optimization
Localized activations in a simple neural field model
No full textA quarter of a century ago Amari (Biol. Cybernet. 27 (1977) 77-87) has presented a comprehensive and very elegant solution of the one-dimensional neural field equation. In the two-dimensional case analytical results on localized solutions are available under the assumption of rotational invariance, as numerical evidence indicates that no other stable solutions exist. We present analytic results for a special case of a "tophat" interaction function, which partially justifies the implicit assumption of circular solutions and allows us to discuss the possibility of non-generic deviations from circularity. (c) 2004 Elsevier B.V. All rights reserved
Cross-Modal Distortion of Time Perception: Demerging the Effects of Observed and Performed Motion
Full text linkTemporal information is often contained in multi-sensory stimuli, but it is currently unknown how the brain combines e.g. visual and auditory cues into a coherent percept of time. The existing studies of cross-modal time perception mainly support the ?modality appropriateness hypothesis?, i.e. the domination of auditory temporal cues over visual ones because of the higher precision of audition for time perception. However, these studies suffer from methodical problems and conflicting results. We introduce a novel experimental paradigm to examine cross-modal time perception by combining an auditory time perception task with a visually guided motor task, requiring participants to follow an elliptic movement on a screen with a robotic manipulandum. We find that subjective duration is distorted according to the speed of visually observed movement: The faster the visual motion, the longer the perceived duration. In contrast, the actual execution of the arm movement does not contribute to this effect, but impairs discrimination performance by dual-task interference. We also show that additional training of the motor task attenuates the interference, but does not affect the distortion of subjective duration. The study demonstrates direct influence of visual motion on auditory temporal representations, which is independent of attentional modulation. At the same time, it provides causal support for the notion that time perception and continuous motor timing rely on separate mechanisms, a proposal that was formerly supported by correlational evidence only. The results constitute a counterexample to the modality appropriateness hypothesis and are best explained by Bayesian integration of modality-specific temporal information into a centralized ?temporal hub?.</p
Data Humanities. A Manifesto
No full textHerrmann JB. Data Humanities. A Manifesto. In: Funke D, Körte M, Littschwager M, Michael J, Rottschäfer N, eds. Aufruhr verZeichnen. 26 literaturwissenschaftliche Einsprüche. Düsseldorf: C. W. Leske; 2023: 103-106
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