scholarly journals The Situational Structure of Primate Beliefs

Perspectives ◽  
2016 ◽  
Vol 6 (1) ◽  
pp. 50-57
Author(s):  
Tony Cheng
Keyword(s):  
Working Memory ◽  
A Priori ◽  
Analytic Tradition ◽  
Model Based ◽  
Situational Model ◽  
Empirical Argument ◽  
State Of Affairs ◽  
Referential Opacity

Abstract This paper develops the situational model of primate beliefs from the Prior-Lurz line of thought. There is a strong skepticism concerning primate beliefs in the analytic tradition which holds that beliefs have to be propositional and non-human animals do not have them (e.g., Davidson 1975, 1982). The response offered in this paper is twofold. First, two arguments against the propositional model as applied to other animals are put forward: an a priori argument from referential opacity and an empirical argument from varieties of working memory. Second, the Prior-Lurz situational model based on state of affairs as opposed to propositions is introduced and defended with two significant modifications. With this model of primate beliefs we can make progress in understanding how other primates can have certain mindreading capacity.

scholarly journals A working memory model based on excitatory-inhibitory interactions and calcium dynamics

2010 ◽  
Vol 11 (S1) ◽  
Author(s):  
Kyle Lyman ◽  
Robert McDougal ◽  
Brian Myers ◽  
Joseph Tien ◽  
Mustafa Zeki ◽  
...  
Keyword(s):  
Working Memory ◽  
Memory Model ◽  
Calcium Dynamics ◽  
Model Based ◽  
Inhibitory Interactions ◽  
Working Memory Model

Functional and structural MRI correlates of executive functions in multiple sclerosis

2021 ◽  
pp. 135245852110331
Author(s):  
Olga Marchesi ◽  
Raffaello Bonacchi ◽  
Paola Valsasina ◽  
Paolo Preziosa ◽  
Elisabetta Pagani ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Working Memory ◽  
A Priori ◽  
Structural Mri ◽  
Wisconsin Card Sorting Test ◽  
Cognitive Networks ◽  
Superior Cerebellar Peduncle ◽  
Card Sorting ◽  
Cerebellar Peduncle ◽  
Magnetic Resonance Imaging Mri

Background: Executive dysfunctions, including difficulties in attention, working memory, planning, and inhibition affect 15%–28% of multiple sclerosis (MS) patients. Objectives: To investigate structural and functional magnetic resonance imaging (MRI) abnormalities underlying executive function (EF) in MS patients. Methods: A total 116 MS patients and 65 controls underwent resting-state (RS) and diffusion-weighted sequences and neuropsychological examination, including Wisconsin Card Sorting Test (WCST) to test EF. Brain RS cognitive networks and fractional anisotropy (FA) from a priori selected white matter tracts were derived. Associations of WCST scores with RS functional connectivity (FC) and FA abnormalities were investigated. Results: In MS patients, predictors of working memory/updating were: lower corpus callosum (CC) FA, lower left working-memory network (WMN), right WMN RS FC for worse performance; lower executive control network (ECN), higher default-mode network (DMN), and salience network (SN) RS FC for better performance ( R2 = 0.35). Predictors of attention were lower CC genu FA, lower left WMN, and DMN RS FC for worse performance; higher left WMN and ECN RS FC for better performance ( R2 = 0.24). Predictors of worse shifting/inhibition were lower CC genu and superior cerebellar peduncle (SCP) FA, lower left WMN RS FC for worse performance; and higher ECN RS FC for better performance ( R2 = 0.24). Conclusions: CC and SCP microstructural damage and RS FC abnormalities in cognitive networks underlie EF frailty in MS.

Parameter Identification for Model-Based Control of Hydraulically Actuated Open-Chain Manipulators

2019 ◽  
Author(s):  
Lionel Hulttinen ◽  
Janne Koivumäki ◽  
Jouni Mattila
Keyword(s):  
Parameter Identification ◽  
Nonlinear Model ◽  
A Priori ◽  
Chamber Pressure ◽  
Hydraulic Actuator ◽  
Open Chain ◽  
Model Based Control ◽  
Model Based ◽  
Inertial Parameters ◽  
Manipulator Link

Abstract In this paper, a nonlinear model-based controller with parameter identification is designed for a rigid open-chain manipulator arm actuated by servovalve-controlled hydraulic cylinders. The arising problem in adopting model-based controllers is how to acquire accurate estimates of system parameters, with limited available information about either the hydraulic actuator parameters or manipulator link inertial parameters. The objective of this study is to identify both the rigid-body parameters of the links and the hydraulic actuator parameters from collected cylinder chamber pressure and joint angle data, while no a priori knowledge of these parameters is available. Same physical plant models are used for control design as well as for parameter identification. Experimental results show that the proposed nonlinear model-based control scheme results in acceptable Cartesian position tracking performance in free-space motion when using the identified parameters.

scholarly journals Quantitative assessment of near-infrared spectroscopy time course under hypercapnia using an a priori model-based fitting

2020 ◽  
Vol 118 ◽  
pp. 103638
Author(s):  
Victor Vagné ◽  
Emmanuelle Le Bars ◽  
Jérémy Deverdun ◽  
Olivier Rossel ◽  
Stéphane Perrey ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Quantitative Assessment ◽  
Time Course ◽  
Near Infrared ◽  
A Priori ◽  
Model Based

A physics-based approach to flow control using system identification

2012 ◽  
Vol 702 ◽  
pp. 26-58 ◽  
Author(s):  
Aurelien Hervé ◽  
Denis Sipp ◽  
Peter J. Schmid ◽  
Manuel Samuelides
Keyword(s):  
System Identification ◽  
Control Strategies ◽  
A Priori ◽  
Operating Conditions ◽  
Noise Sources ◽  
Subsequent Performance ◽  
Model Based ◽  
Noise Characteristics ◽  
Identification Technique ◽  
Auto Regressive

AbstractControl of amplifier flows poses a great challenge, since the influence of environmental noise sources and measurement contamination is a crucial component in the design of models and the subsequent performance of the controller. A model-based approach that makes a priori assumptions on the noise characteristics often yields unsatisfactory results when the true noise environment is different from the assumed one. An alternative approach is proposed that consists of a data-based system-identification technique for modelling the flow; it avoids the model-based shortcomings by directly incorporating noise influences into an auto-regressive (ARMAX) design. This technique is applied to flow over a backward-facing step, a typical example of a noise-amplifier flow. Physical insight into the specifics of the flow is used to interpret and tailor the various terms of the auto-regressive model. The designed compensator shows an impressive performance as well as a remarkable robustness to increased noise levels and to off-design operating conditions. Owing to its reliance on only time-sequences of observable data, the proposed technique should be attractive in the design of control strategies directly from experimental data and should result in effective compensators that maintain performance in a realistic disturbance environment.

2205 – Working memory dependent prefrontal-parietal connectivity and model-based diagnostic classification in schizophrenia

2013 ◽  
Vol 28 ◽  
pp. 1
Author(s):  
L. Deserno ◽  
K. Brodersen ◽  
Z. Lin ◽  
W.D. Penny ◽  
A. Heinz ◽  
...  
Keyword(s):  
Working Memory ◽  
Diagnostic Classification ◽  
Model Based
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