scholarly journals From Topological Analyses to Functional Modeling: The Case of Hippocampus

2021 ◽  
Vol 14 ◽  
Author(s):  
Yuri Dabaghian
Keyword(s):  
Spatial Learning ◽  
Functional Model ◽  
Cognitive Maps ◽  
Functional Modeling ◽  
Memory Processing ◽  
Neuronal Ensembles ◽  
Brain Waves ◽  
Data Analyses ◽  
Brain Part ◽  
Different Levels

Topological data analyses are widely used for describing and conceptualizing large volumes of neurobiological data, e.g., for quantifying spiking outputs of large neuronal ensembles and thus understanding the functions of the corresponding networks. Below we discuss an approach in which convergent topological analyses produce insights into how information may be processed in mammalian hippocampus—a brain part that plays a key role in learning and memory. The resulting functional model provides a unifying framework for integrating spiking data at different timescales and following the course of spatial learning at different levels of spatiotemporal granularity. This approach allows accounting for contributions from various physiological phenomena into spatial cognition—the neuronal spiking statistics, the effects of spiking synchronization by different brain waves, the roles played by synaptic efficacies and so forth. In particular, it is possible to demonstrate that networks with plastic and transient synaptic architectures can encode stable cognitive maps, revealing the characteristic timescales of memory processing.

Experimental Studies Assessing the Repeatability of a Functional Modeling Derivation Method

2003 ◽  
Vol 125 (4) ◽  
pp. 682-693 ◽  
Author(s):  
Mark A. Kurfman ◽  
Michael E. Stock ◽  
Robert B. Stone ◽  
Jagan Rajan ◽  
Kristin L. Wood
Keyword(s):  
Design Research ◽  
Functional Model ◽  
Experimental Studies ◽  
Testing Procedure ◽  
Research Literature ◽  
Functional Modeling ◽  
Skill Levels ◽  
Functional Models ◽  
Model Derivation ◽  
Derivation Method

This paper presents the results of research attempts to substantiate repeatability and uniqueness claims of a functional model derivation method following a hypothesis generation and testing procedure outlined in design research literature. Three experiments are constructed and carried out with a participant pool that possesses a range of engineering design skill levels. The experiments test the utility of a functional model derivation method to produce repeatable functional models for a given product among different designers. In addition to this, uniqueness of the functional models produced by the participants is examined. Results indicate the method enhances repeatability and leads designers toward a unique functional model of a product. Shortcomings of the method and opportunities for improvement are also identified.

scholarly journals Function modeling combined with physics-based reasoning for assessing design options and supporting innovative ideation

2017 ◽  
Vol 31 (4) ◽  
pp. 476-500 ◽  
Author(s):  
Hossein Mokhtarian ◽  
Eric Coatanéa ◽  
Henri Paris
Keyword(s):  
Functional Model ◽  
Mathematical Framework ◽  
Functional Modeling ◽  
Design Problems ◽  
Academic Communities ◽  
Functional Representations ◽  
Incremental Improvement ◽  
Design Options ◽  
Structural Blocks

AbstractFunctional modeling is an analytical approach to design problems that is widely taught in certain academic communities but not often used by practitioners. This approach can be applied in multiple ways to formalize the understanding of the systems, to support the synthesis of the design in the development of a new product, or to support the analysis and improvement of existing systems incrementally. The type of usage depends on the objectives that are targeted. The objectives can be categorized into two key groups: discovering a totally new solution, or improving an existing one. This article proposes to use the functional modeling approach to achieve three goals: to support the representation of physics-based reasoning, to use this physics-based reasoning to assess design options, and finally to support innovative ideation. The exemplification of the function-based approach is presented via a case study of a glue gun proposed for this Special Issue. A reverse engineering approach is applied, and the authors seek an incremental improvement of the solution. As the physics-based reasoning model presented in this article is heavily dependent on the quality of the functional model, the authors propose a general approach to limit the interpretability of the functional representations by mapping the functional vocabulary with elementary structural blocks derived from bond graph theory. The physics-based reasoning approach is supported by a mathematical framework that is summarized in the article. The physics-based reasoning model is used for discovering the limitations of solutions in the form of internal contradictions and guiding the design ideation effort.

scholarly journals FUNCTIONAL MODELING OF CARBON SORBENTS SYNTHESIS CONTROL

2019 ◽  
Vol 14 (1) ◽  
pp. 39-46
Author(s):  
V. V. Burlyaev ◽  
E. V. Burlyaeva ◽  
A. I. Nikolaev ◽  
B. V. Peshnev
Keyword(s):  
Functional Model ◽  
Carbon Sorbent ◽  
Sorption Properties ◽  
Raw Material ◽  
Synthesis Process ◽  
Phase Method ◽  
General Description ◽  
Functional Modeling ◽  
Technological Parameters ◽  
Carbon Sorbents

The formalized model of carbon sorbent synthesis control based on the methodology for functional modeling is constructed. The correlations between the directions of use and the properties of carbon sorbents are revealed. The characteristics that are essential regardless of the direction of use of the sorbent, in particular, sorption properties and strength are identified. The technologies based on the gas-phase method of obtaining carbon material are considered, the analysis of individual stages of the process of obtaining carbon sorbents is carried out. The analysis of the influence of the technological parameters of the synthesis on the properties of sorbents is carried out. On the basis of the established relationships, a functional model has been built that provides a hierarchically ordered, structured, visual description of the management of carbon sorbent synthesis. The simulation is performed “from top to bottom” from the most general description to the detail. The resulting model is a set of interrelated graphical diagrams. At the initial stage, the synthesis of carbon sorbent is considered as a single process, the input parameters of which are hydrocarbon gas, the activating agent and the material form factor, the output - carbon sorbent, and the control parameters are the requirements for strength and sorption properties. Then the synthesis process is decomposed. The control processes (analysis of raw material properties and matrix selection), technological processes (raw material preparation) and mixed processes are distinguished as a result of decomposition. The model includes a consistent description of the technological parameters selection (temperature, gas flow and time) for both stages of the synthesis process. The model is the base for information support providing for the production of carbon sorbents with the required properties.

scholarly journals On the use of the structural and functional modeling of a system analysis of the company financial statements

2016 ◽  
Vol 12 (2) ◽  
pp. 49-53
Author(s):  
Daria S Orlova ◽  
Andrey V Kutyshkin
Keyword(s):  
Economic Analysis ◽  
Data Model ◽  
System Analysis ◽  
Functional Model ◽  
Financial Statements ◽  
Functional Modeling ◽  
Semantic Data ◽  
Complex Models ◽  
Semantic Data Model ◽  
The Impact

The article discusses the construction of complex models consisting of a structural-functional model, information model and semantic data model, which is the basis for the design of soft-ware that implements the method of calculating the dynamic standard. Dynamic specification of linear and non-linear form is intended for financial and economic analysis of the performance of the enterprise. Dynamic standard to some extent reduces the impact on the results of financial and economic analysis of the experience and skills of the analyst conducting this analysis.

scholarly journals That which is not form: The practical challenges in using functional concepts in design

2013 ◽  
Vol 27 (3) ◽  
pp. 217-231 ◽  
Author(s):  
Claudia Eckert
Keyword(s):  
Functional Model ◽  
Significant Part ◽  
Functional Modeling ◽  
Modeling Approaches ◽  
Design Methodologies

AbstractFunctional modeling is a very significant part of many different well-known design methodologies. This paper investigates the questions of what functional modeling approaches people use in industry and how they conceptualize functions. Using interviews and the findings from an experiment where 20 individual designers were asked to generate a functional model of a product, the paper highlights the different notions designers associate with the wordfunction. Difficulties associated with functional modeling arise from varied and inconsistent notions of functions as well as wider challenges associated with modeling and the introduction of methods in industry.

Multilevel Modeling and its Application in Counseling Psychology Research

1999 ◽  
Vol 27 (4) ◽  
pp. 528-551 ◽  
Author(s):  
Steven P. Reise ◽  
Naihua Duan
Keyword(s):  
Multilevel Modeling ◽  
Counseling Psychology ◽  
Predictor Variables ◽  
Outcome Variable ◽  
Hierarchical Data ◽  
Psychology Research ◽  
Data Set ◽  
Data Analyses ◽  
Different Levels ◽  
Group Effects

Multilevel modeling (MLM) should be used when a researcher has collected hierarchical data. For example, when a researcher investigates an outcome variable (e.g., depression) with several clients drawn from different clinicians, the data set has a hierarchical structure. Herein, we describe the use of MLM in counseling research. The goals include the following: (a) to specify research contexts where MLM may be applied, (b) to describe how to conduct data analyses using MLM, and (c) to highlight key statistical and design issues encountered when analyzing hierarchical data. We also highlight how MLM can be used (a) to provide valid statistical inference in the presence of hierarchical data structure, (b) to separate the within-group effects from between-group effects for predictor variables, and (c) to study the interactions among predictor variables drawn from different levels (e.g., variables drawn from both clients and their clinicians).

CREB phosphorylation as a molecular marker of memory processing in the hippocampus for spatial learning

2002 ◽  
Vol 133 (2) ◽  
pp. 135-141 ◽  
Author(s):  
Makoto Mizuno ◽  
Kiyofumi Yamada ◽  
Naoya Maekawa ◽  
Kuniaki Saito ◽  
Mitsuru Seishima ◽  
...  
Keyword(s):  
Molecular Marker ◽  
Spatial Learning ◽  
Creb Phosphorylation ◽  
Memory Processing

EEG Frequency and Phase Coupling during Human Information Processing

2001 ◽  
Vol 40 (02) ◽  
pp. 106-111 ◽  
Author(s):  
P. Rappelsberger ◽  
N. Vath ◽  
S. Weiss ◽  
E. Möller ◽  
G. Grießbach ◽  
...  
Keyword(s):  
Information Processing ◽  
Information Transfer ◽  
Network Activity ◽  
Single Frequency ◽  
Human Information Processing ◽  
Phase Coupling ◽  
Memory Processing ◽  
Neuronal Ensembles ◽  
Non Linear ◽  
Oscillatory Network

AbstractNeuronal activity during information processing is represented by oscillations within local or widespread neuronal networks. These oscillations may be recorded by the EEG (electroencephalogram). The oscillatory interaction between neuronal ensembles may be at one single frequency or at different frequencies due to non-linear coupling. The investigation of momentary coherence and phase enables the examination of synchronized oscillatory network activity during fast-changing cognitive processes. On this basis information transfer from occipital areas towards frontal areas could be described during processing of visual presented words. Non-linear phase coupling between oscillations with different frequencies during memory processing was detected by means of cross-bicoherence.

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