scholarly journals Honeybees solve a multi-comparison ranking task by probability matching

2020 ◽  
Vol 287 (1934) ◽  
pp. 20201525
Author(s):  
HaDi MaBouDi ◽  
James A. R. Marshall ◽  
Andrew B. Barron
Keyword(s):  
Mushroom Body ◽  
Computational Modelling ◽  
Cognitive Strategy ◽  
Choice Task ◽  
Probability Matching ◽  
Input And Output ◽  
Comparison Choice ◽  
History Of ◽  
Ranking Task ◽  
Reward And Punishment

Honeybees forage on diverse flowers which vary in the amount and type of rewards they offer, and bees are challenged with maximizing the resources they gather for their colony. That bees are effective foragers is clear, but how bees solve this type of complex multi-choice task is unknown. Here, we set bees a five-comparison choice task in which five colours differed in their probability of offering reward and punishment. The colours were ranked such that high ranked colours were more likely to offer reward, and the ranking was unambiguous. Bees' choices in unrewarded tests matched their individual experiences of reward and punishment of each colour, indicating bees solved this test not by comparing or ranking colours but by basing their colour choices on their history of reinforcement for each colour. Computational modelling suggests a structure like the honeybee mushroom body with reinforcement-related plasticity at both input and output can be sufficient for this cognitive strategy. We discuss how probability matching enables effective choices to be made without a need to compare any stimuli directly, and the use and limitations of this simple cognitive strategy for foraging animals.

scholarly journals Honey bees solve a multi-comparison ranking task by probability matching

2020 ◽  
Author(s):  
HaDi MaBouDi ◽  
James A.R. Marshall ◽  
Andrew B. Barron
Keyword(s):  
Honey Bee ◽  
Honey Bees ◽  
Cognitive Strategy ◽  
Choice Task ◽  
Probability Matching ◽  
Comparison Choice ◽  
History Of ◽  
Ranking Task ◽  
Matching Strategy ◽  
Reward And Punishment

AbstractHoney bees forage on a range of flowers, all of which can vary unpredictably in the amount and type of rewards they offer. In this environment bees are challenged with maximising the resources they gather for their colony. That bees are effective foragers is clear, but how bees solve this type of complex multi-choice task is unknown. Here we challenged bees with a five-comparison choice task in which five colours differed in their probability of offering reward and punishment. The colours were ranked such that high ranked colours were more likely to offer reward, and the ranking was unambiguous. Bees choices in unrewarded tests matched their individual experiences of reward and punishment of each colour, indicating bees solved this test not by comparing or ranking colours but by matching their preferences to their history of reinforcement for each colour. We used a computational model to explore the feasibility of this probability matching strategy for the honey bee brain. The model suggested a structure like the honey bee mushroom body with reinforcement-related plasticity at both input and output was sufficient for this cognitive strategy. We discuss how probability matching enables effective choices to be made without a need to compare any stimuli directly, and the utility and limitations of this simple cognitive strategy for foraging animals.

scholarly journals What is the role of computational models in Cognitive Science? A quantitative and qualitative analysis of the history of the TRACE model of speech segmentation

2019 ◽  
Author(s):  
Manisha Chawla ◽  
Richard Shillcock
Keyword(s):  
Qualitative Analysis ◽  
Cognitive Science ◽  
Computational Models ◽  
Computational Modelling ◽  
Speech Segmentation ◽  
Cognitive Modelling ◽  
Trace Model ◽  
History Of ◽  
Central Paradigm

Implemented computational models are a central paradigm of Cognitive Science. How do cognitive scientists really use such models? We take the example of one of the most successful and influential cognitive models, TRACE (McClelland & Elman, 1986), and we map its impact on the field in terms of published, electronically available documents that cite the original TRACE paper over a period of 25 years since its publication. We draw conclusions about the general status of computational cognitive modelling and make critical suggestions regarding the nature of abstraction in computational modelling.

Prioritization of Potential Mates’ History of Sexual Fidelity During a Conjoint Ranking Task

2014 ◽  
Vol 40 (7) ◽  
pp. 884-897 ◽  
Author(s):  
Justin K. Mogilski ◽  
T. Joel Wade ◽  
Lisa L. M. Welling
Keyword(s):  
History Of ◽  
Ranking Task

Effects of variety reduction and amplification in circular feedback systems

Kybernetes ◽  
2014 ◽  
Vol 43 (9/10) ◽  
pp. 1330-1337 ◽  
Author(s):  
Thomas Fischer
Keyword(s):  
Optical Feedback ◽  
Computational Modelling ◽  
Feedback System ◽  
Output Channel ◽  
Feedback Systems ◽  
Content Type ◽  
Theoretical Concepts ◽  
Input And Output ◽  
Photo Camera ◽  
Recursive System

Purpose – The purpose of this paper is to present the result of an experiment examining the effects of changing input and output channel variety in an optical feedback system and their potential to give rise to novelty, as some non-trivial systems do. Design/methodology/approach – The experimental design is based on a digital computer connected to a digital photo camera (input channel), and to a monitor screen (output channel). The camera is pointed at the monitor to form a circular feedback system. Monitor and camera resolutions constitute the variable input and output variety of the system, allowing the visual investigation of effects of variety reduction and variety amplification in circular feedback systems. Findings – Results suggest that variety amplification in input and/or output channels promotes the emergence of discernible novelty in the apparent absence of a creative/generative capability or agenda within the recursive system. Research limitations/implications – An analogy between an optical feedback system and human novelty generation is shown, while generalisability of observations made beyond the described experiment remains to be established. Originality/value – A new approach to the computational modelling of aspects of human creativity is presented. Photographic investigation of variety reduction and variety amplification is new, and hoped to be of value to those wishing to examine these theoretical concepts in concrete terms.

Determination of Gear Ratios

1982 ◽  
Vol 104 (4) ◽  
pp. 775-777 ◽  
Author(s):  
W. C. Orthwein
Keyword(s):  
Angular Velocity ◽  
Direct Method ◽  
Gear Train ◽  
Pocket Calculator ◽  
Input And Output ◽  
Number Of Teeth ◽  
History Of ◽  
A Direct Method

Finding the number of teeth for each gear in a gear train required to provide a specified noninteger ratio (or its inverse) of angular velocity between input and output shafts has been a troublesome problem throughout the history of gearing. A direct method for finding the required number of teeth is presented, along with a program for its implementation on a programmable pocket calculator.

scholarly journals МЕТОД УМЕНЬШЕНИЯ КОЛИЧЕСТВА ВЗАИМОПРОВЕРОК ПРИ САМОТЕСТИРОВАНИИ МНОГОПРОЦЕССОРНЫХ СИСТЕМ

2018 ◽  
pp. 61-66
Author(s):  
Виталий Алексеевич Романкевич ◽  
Алексей Витальевич Романкевич ◽  
Дарина Натиговна Ахмедова
Keyword(s):  
Control Systems ◽  
Fault Tolerant ◽  
Regular Structure ◽  
The Other ◽  
Multiprocessor Systems ◽  
Circulant Graph ◽  
Input And Output ◽  
Self Testing ◽  
History Of ◽  
The Subject

The subject matter of this article is the testing processes in multiprocessor systems, first of all - fault-tolerant control systems, when the number m of allowed failures from n processors is known in advance and is limited. The topology of interprocessor communications can be represented as a directed graph of the circulant type, where the number of input and output channels between each one processor and the other processors in the system is not less than m. The goal is to minimize the number of mutual checks in the system when performing its self-testing. Tasks: develop an effective method for organizing the mutual testing of processors in multiprocessor systems and algorithm for its implementation, estimate the number of elementary checks and prove its rightness. The following results were obtained. Based on the known method of diagnosis of multiprocessor systems with a regular structure, and m≤4, with parallel and independent testing, the task of organizing of testing process for any m <(n ⁄ 2) was formulated. In this process, only one pair of processors participate in testing in one moment of time, thus it was called sequential. what special about this organization is that the choice of the next pair is based on the analysis of the history of the process. An algorithm for performing the method has been proposed. The Preparata-Metz-Chen model was chosen as the model of faults, as the closest one to reality. Conclusions. The scientific novelty of the results is as follows: The method for organizing of self-testing of multiprocessor systems with a connection topology described by a circulant graph (with at least m input and m output edges) has been proposed, and this method allows reducing the number of mutual tests in the system. It has been proved that the state (serviceable/faulty) of all processors of the system can be determined after performing no more than n + 2m checks. Practical value - the method allows to reduce the time spent by system on self-testing, and, therefore, to increase its performance, since the system performs this task constantly in the process of exploitation. The advantages of the selected topology: it is suitable for any integer values of n

scholarly journals SSRIs modulate asymmetric learning from reward and punishment

2020 ◽  
Author(s):  
Jochen Michely ◽  
Eran Eldar ◽  
Alon Erdman ◽  
Ingrid M. Martin ◽  
Raymond J. Dolan
Keyword(s):  
Temporal Evolution ◽  
Instrumental Learning ◽  
Reward Learning ◽  
Antidepressant Effects ◽  
History Of ◽  
Asymmetric Learning ◽  
Serotonergic Antidepressant ◽  
Negative Expectations ◽  
Reward And Punishment

AbstractHuman instrumental learning is driven by a history of outcome success and failure. We demonstrate that week-long treatment with a serotonergic antidepressant modulates a valence-dependent asymmetry in learning from reinforcement. In particular, we show that prolonged boosting of central serotonin reduces reward learning, and enhances punishment learning. This treatment induced learning asymmetry can result in lowered positive and enhanced negative expectations. A consequential effect is more rewarding, and less disappointing, experiences and this may, in part, explain the slow temporal evolution of serotonin’s well-established antidepressant effects.

Computational Modeling and Analysis of Murmurs Generated by Modeled Aortic Stenoses

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Chi Zhu ◽  
Jung-Hee Seo ◽  
Rajat Mittal
Keyword(s):  
Aortic Stenosis ◽  
Numerical Study ◽  
Computational Modelling ◽  
Sound Intensity ◽  
Elliptic Cylinder ◽  
Intensity Pattern ◽  
Modeling And Analysis ◽  
Curved Pipe ◽  
Epidermal Surface ◽  
History Of

In this study, coupled hemodynamic–acoustic simulations are employed to study the generation and propagation of murmurs associated with aortic stenoses where the aorta with a stenosed aortic valve is modeled as a curved pipe with a constriction near the inlet. The hemodynamics of the poststenotic flow is investigated in detail in our previous numerical study (Zhu et al., 2018, “Computational Modelling and Analysis of Haemodynamics in a Simple Model of Aortic Stenosis,” J. Fluid Mech., 851, pp. 23–49). The temporal history of the pressure on the aortic lumen is recorded during the hemodynamic study and used as the murmur source in the acoustic simulations. The thorax is modeled as an elliptic cylinder and the thoracic tissue is assumed to be homogeneous, linear and viscoelastic. A previously developed high-order numerical method that is capable of dealing with immersed bodies is applied in the acoustic simulations. To mimic the clinical practice of auscultation, the sound signals from the epidermal surface are collected. The simulations show that the source of the aortic stenosis murmur is located at the proximal end of the aortic arch and that the sound intensity pattern on the epidermal surface can predict the source location of the murmurs reasonably well. Spectral analysis of the murmur reveals the disconnect between the break frequency obtained from the flow and from the murmur signal. Finally, it is also demonstrated that the source locations can also be predicted by solving an inverse problem using the free-space Green's function. The implications of these results for cardiac auscultation are discussed.

Different classes of input and output neurons reveal new features in microglomeruli of the adult Drosophila mushroom body calyx

2012 ◽  
Vol 520 (10) ◽  
pp. 2185-2201 ◽  
Author(s):  
Nancy J. Butcher ◽  
Anja B. Friedrich ◽  
Zhiyuan Lu ◽  
Hiromu Tanimoto ◽  
Ian A. Meinertzhagen
Keyword(s):  
Mushroom Body ◽  
Input And Output ◽  
Output Neurons ◽  
Mushroom Body Calyx ◽  
Adult Drosophila

scholarly journals Convergence of monosynaptic and polysynaptic sensory paths onto common motor outputs in a Drosophila feeding connectome

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Anton Miroschnikow ◽  
Philipp Schlegel ◽  
Andreas Schoofs ◽  
Sebastian Hueckesfeld ◽  
Feng Li ◽  
...  
Keyword(s):  
Food Intake ◽  
Mushroom Body ◽  
Sensory Inputs ◽  
Input And Output ◽  
Drosophila Larvae ◽  
Output Neurons ◽  
Overlapping Domains ◽  
Motor Outputs ◽  
Neuroendocrine Neurons ◽  
Mushroom Body Calyx

We reconstructed, from a whole CNS EM volume, the synaptic map of input and output neurons that underlie food intake behavior of Drosophila larvae. Input neurons originate from enteric, pharyngeal and external sensory organs and converge onto seven distinct sensory synaptic compartments within the CNS. Output neurons consist of feeding motor, serotonergic modulatory and neuroendocrine neurons. Monosynaptic connections from a set of sensory synaptic compartments cover the motor, modulatory and neuroendocrine targets in overlapping domains. Polysynaptic routes are superimposed on top of monosynaptic connections, resulting in divergent sensory paths that converge on common outputs. A completely different set of sensory compartments is connected to the mushroom body calyx. The mushroom body output neurons are connected to interneurons that directly target the feeding output neurons. Our results illustrate a circuit architecture in which monosynaptic and multisynaptic connections from sensory inputs traverse onto output neurons via a series of converging paths.

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