scholarly journals Biased competition in the absence of input bias: predictions from corticostriatal computation

2018 ◽  
Author(s):  
Salva Ardid ◽  
Jason S. Sherfey ◽  
Michelle M. McCarthy ◽  
Joachim Hass ◽  
Benjamin R. Pittman-Polletta ◽  
...  
Keyword(s):  
Decision Making ◽  
Rhythmic Activity ◽  
High Strength ◽  
Downstream Processing ◽  
Biased Competition ◽  
Rule Based ◽  
Cortical Input ◽  
Neuronal Ensembles ◽  
Input Strength ◽  
Selection Of

Classical accounts of biased competition (BC) require an input bias to resolve the competition between neuronal ensembles driving downstream processing. However, flexible and reliable selection of behaviorally-relevant ensembles can occur with unbiased stimulation: striatal D1 and D2 spiny projecting neurons (SPNs) receive balanced cortical input, yet their activity determines the choice between GO and NO-GO pathways in the basal ganglia. We present a corticostriatal model identifying three mechanisms that rely on physiological asymmetries to effect rate- and time-coded BC in the presence of balanced inputs. First, tonic input strength determines which SPN phenotype exhibit higher mean firing rate (FR). Second, low strength oscillatory inputs induce higher FR in D2 SPNs but higher coherence between D1 SPNs. Third, high strength inputs oscillating at distinct frequencies preferentially activate D1 or D2 SPN populations. Of these mechanisms, the latter accommodates observed rhythmic activity supporting rule-based decision making in prefrontal cortex.

scholarly journals Biased competition in the absence of input bias revealed through corticostriatal computation

2019 ◽  
Vol 116 (17) ◽  
pp. 8564-8569 ◽  
Author(s):  
Salva Ardid ◽  
Jason S. Sherfey ◽  
Michelle M. McCarthy ◽  
Joachim Hass ◽  
Benjamin R. Pittman-Polletta ◽  
...  
Keyword(s):  
Firing Rate ◽  
Rhythmic Activity ◽  
High Strength ◽  
Downstream Processing ◽  
Projection Neurons ◽  
Biased Competition ◽  
Cortical Input ◽  
Neuronal Ensembles ◽  
Input Strength ◽  
Selection Of

Classical accounts of biased competition require an input bias to resolve the competition between neuronal ensembles driving downstream processing. However, flexible and reliable selection of behaviorally relevant ensembles can occur with unbiased stimulation: striatal D1 and D2 spiny projection neurons (SPNs) receive balanced cortical input, yet their activity determines the choice between GO and NO-GO pathways in the basal ganglia. We here present a corticostriatal model identifying three mechanisms that rely on physiological asymmetries to effect rate- and time-coded biased competition in the presence of balanced inputs. First, tonic input strength determines which one of the two SPN phenotypes exhibits a higher mean firing rate. Second, low-strength oscillatory inputs induce higher firing rate in D2 SPNs but higher coherence between D1 SPNs. Third, high-strength inputs oscillating at distinct frequencies can preferentially activate D1 or D2 SPN populations. Of these mechanisms, only the latter accommodates observed rhythmic activity supporting rule-based decision making in prefrontal cortex.

scholarly journals Critical Analysis of the Selection of Non-Conventional Machining Processes

2021 ◽  
pp. 132-139
Author(s):  
Jesang Hutchinson
Keyword(s):  
Decision Making ◽  
Stainless Steels ◽  
Critical Analysis ◽  
High Strength ◽  
Machining Processes ◽  
Resistant Alloy ◽  
Complex Shapes ◽  
High Strength Fiber ◽  
Conventional Machining ◽  
Selection Of

Non-Convectional Machining (NCM) processes are used widely to produce accurate and intricate material shape such as titanium, stainless steels and resistant alloy that are of high strength, fiber-based composite, refractories and ceramics. The production of more complex shapes of materials using convectional machining processes is considered to be challenging. This research paper focusses on the section of the most effective NCM process. The ‘choice’ of the most considerable NCM process for a particular application could be seen as a multi-technique for making proper choices for diverse or conflicting approaches. To aid the process of choosing, various NCM techniques have been proposed in this research. This contribution focuses on the usage of unexplored NCM and Multi-Feature Decision-Making (MFDM) ‘choice’ issues.

Selection of Contractor Using Multi-Criteria Decision Making Tools

2011 ◽  
Vol 4 (4) ◽  
pp. 139-142
Author(s):  
S.PUSHPARANI S.PUSHPARANI ◽  
◽  
Dr.S.SENTHAMILKUMAR Dr.S.SENTHAMILKUMAR
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Selection Of

Sistem Pendukung Keputusan SNMPTN Jalur Undangan Dengan Metode Electre

2018 ◽  
Vol 3 ◽  
pp. 14
Author(s):  
Lidia K Simanjuntak ◽  
Tessa Y M Sihite ◽  
Mesran Mesran ◽  
Nuning Kurniasih ◽  
Yuhandri Yuhandri
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Action Selection ◽  
Multi Criteria Decision Making ◽  
Prospective Students ◽  
College Entrance ◽  
Electre Method ◽  
Selection Of

All colleges each year organize the selection of new admissions. Acceptance of prospective students in universities as education providers is done by selecting prospective students based on achievement in school and college entrance selection. To select the best student candidates based on predetermined criteria, then use Multi-Criteria Decision Making (MCDM) or commonly called decision support system. One method in MCDM is the Elimination Et Choix Traduisant la Reality (ELECTRE). The ELECTRE method is the best method of action selection. The ELECTRE method to obtain the best alternative by eliminating alternative that do not fit the criteria and can be applied to the decision SNMPTN invitation path.

PEMILIHAN KEPLING TELADAN MENERAPKAN METODE RANK ORDER CENTROID (ROC) DAN METODE ADDITIVE RATIO ASSESSMENT (ARAS) DI KECAMATAN MEDAN AREA

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Liza Handayani ◽  
Muhammad Syahrizal ◽  
Kennedi Tampubolon
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Rank Order ◽  
Priority Level ◽  
The Village ◽  
Field Area ◽  
Selection Of

The head of the environment is an extension of the head of the village head in assisting or providing services to the community both in the administration of administration in the village and to other problems. It is natural for a kepling to be appreciated for their performance during their special tenure in the kecamatan field area. Previously, the selection of a dipling in a sub-district was very inefficient and seemed unfair for this exemplary selection to use a system to produce an accurate value, and no intentional element. To overcome the process of selecting an exemplary kepling that experiences these obstacles by using an application called a Decision Support System. Decision Support System (SPK) is a system that can solve a problem, and this system is also assisted with several methods, namely the Rank Order Centroid (ROC) method that can assign weight values to each of the criteria based on their priority level. And to do the ranking or determine an exemplary set using the Additive Ratio Assessment (ARAS) method, this method provides decision making that takes decisions based on ranking or the highest value.Keywords: Head of Medan Area Subdistrict, SPK, Centroid Rank Order, Additive Ratio Assessment (ARAS).

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU BERPRESTASI KOTA MEDAN MENERAPKAN METODE PREFERENCES SELECTION INDEX (STUDI KASUS : DINAS PENDIDIKAN KOTA MEDAN)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Fajar Syahputra ◽  
Mesran Mesran ◽  
Ikhwan Lubis ◽  
Agus Perdana Windarto
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Formal Education ◽  
Basic Education ◽  
Selection Index ◽  
Main Task ◽  
Selection Of

The teacher is a major milestone in the world of education, the ability and achievement of students cannot be separated from the role of a teacher in teaching and guiding students. Based on the Law of the Republic of Indonesia No. 14 of 2005 concerning Teachers and Lecturers, in Article 1 explained that teachers are professional educators with the main task of educating, teaching, guiding, directing, training, evaluating, and evaluating students in early childhood education through formal education, basic education and education medium. Whereas in Article 4 of the Act, it is explained that the position of teachers as professionals serves to enhance the dignity and role of teachers as learning agents to function to improve the quality of national education.Decision making is an election process, among various alternatives that aim to meet one or several targets. The decision-making system has 4 phases, namely intelligence, design, choice and implementation. These phases are the basis for decision making, which ends with a recommendation.The Preferences Selection Index (PSI) method is a rarely used decision support system method. This method is a method developed by stevanie and Bhatt (2010) to solve the Multi Criteria Decision Making (MCDM). With the right consideration, this method can be one of the tools to determine policies in decision-making systems, especially the selection of outstanding teachers. Determination of policies taken as a basis for decision making, must use criteria that can be defined clearly and objectively.Keywords: Decision Support System, PSI, Selection of Achieving Teachers

Artikel Strategi tentang Pengambilan Keputusan

2019 ◽  
Author(s):  
Winda Safitri Caniago ◽  
Hade Afriansyah
Keyword(s):  
Decision Making ◽  
Optimization Model ◽  
Heuristic Model ◽  
Selection Of

Decision making is an action with determine the result in solving problem with choose a rule action between alternative through a mental of process, logic of process and etc. This purpose article is to help make it easier to solve a problem. This article explain some strategy decision making such as optimization model, satisfying model, mixed scanning model, heuristic model, and last the selection of certain model.

Pengembangan Aplikasi Pendukung Keputusan Pemilihan Program Studi dengan Metode Fuzzy Logic (Studi Kasus: Universitas Multimedia Nusantara)

2016 ◽  
Vol 7 (1) ◽  
pp. 12-18
Author(s):  
Joko Haryanto ◽  
Seng Hansun
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
System Application ◽  
Prospective Students ◽  
Fuzzy Logic Method ◽  
Index Terms ◽  
Selection Of

This paper describes the development of decision support system application to assist students who want to enter college so that no one choose the majors incorrectly. This application uses fuzzy logic method because fuzzy logic is very flexible in data which are vague and can be represented as a linguistic variable. The purpose of this application is to assist students to choose available majors at University Multimedia Nusantara which are appropriate with his/her capabilities. This application accepts five kinds of input values i.e. Mathematics, Indonesian, English, Physics, and TIK. Received input will be processed by the calculation of the system for decision-making and the application will generate output that shows how great a match for each majors. With this application, prospective students can find out where the majors that match his/her capabilities. This application has ninety nine percentage of match result accuracy. Index Terms—fuzzy logic, decision support system, UMN, selection of major

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