Functional Mesh Model with Temporal Measurements for Brain Decoding

Date

2015-08-29

Author

Onal, Itir
Ozay, Mete
Yarman Vural, Fatoş Tunay

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

140
views

0
downloads

We propose a method called Functional Mesh Model with Temporal Measurements (FMM-TM) to estimate a functional relationship among voxels using temporal data, and employ these relationships for brain decoding. For each sample, we measure Blood Oxygenation Level Dependent (BOLD) responses from each voxel, and construct a functional mesh around each voxel (called seed voxel) with its nearest neighbors selected using distance metrics namely Pearson correlation, cosine similarity and Euclidean distance. Then, we represent the BOLD response of a seed voxel in terms of linear combination of BOLD responses of its p-nearest neighbors. The relationship between the seed voxel and its neighbors is represented using a set of weights which are estimated by employing linear regression. We train Support Vector Machine and k-Nearest Neighbor classifiers using the estimated weights as features. We test our model in an event-related design experiment, namely object recognition, and observe that our features perform better than raw voxel intensity values, features obtained using various pairwise distance metrics, and local mesh model features extracted using stationary and temporal measurements.

Subject Keywords

STATES

URI

https://hdl.handle.net/11511/53372

Conference Name

37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Recent results on Bayesian Cramér-Rao bounds for jump Markov systems Fritsche, Carsten; Orguner, Umut; Svensson, Lennart; Gustafsson, Fredrik (2016-07-08) In this paper, recent results on the evaluation of the Bayesian Cramer-Rao bound for jump Markov systems are presented. In particular, previous work is extended to jump Markov systems where the discrete mode variable enters into both the process and measurement equation, as well as where it enters exclusively into the measurement equation. Recursive approximations are derived with finite memory requirements as well as algorithms for checking the validity of these approximations are established. The tightnes...
EQUIVALENT ELASTIC PROPERTIES OF LATTICES USING NON-UNIFORMLY DISTRIBUTED POINT CLOUD Yormaz, Engin Ege; Tuncay, Kağan; Department of Civil Engineering (2022-11-22) A method based on the equivalency of strain energy density is proposed for finding the elastic parameters of non-uniformly distributed lattice models in 2D with a Poisson’s ratio of 1/3. Lattice members are assumed to carry only normal force. Hence, the elasticity modulus times the area is the only defining parameter for each lattice member. The method is implemented in MATLAB and it is tested with regularly structured lattices whose solutions can be calculated exactly. A “User-Friendly Lattice Model P...
Expectation propagation for state estimation with discrete-valued hidden random variables Sarıtaş, Elif; Orguner, Umut; Department of Electrical and Electronics Engineering (2023-2-21) In this thesis, the expectation propagation (EP) approach of Minka is considered for the estimation problems in dynamical systems with discrete hidden random variables where optimal posteriors are usually intractable. The concept of context adjustment is introduced to avoid/alleviate indefinite covariance problems encountered in standard EP implementations in a systematic way. Additionally, the moment projection (Mprojection) problem involving pseudo-Gaussian likelihoods as factors is solved to be used in t...
Quantum decoherence and quantum state diffusion formalism Dumlu, Cesim Kadri; Turgut, Sadi; Department of Physics (2007) Foundational problems of quantum theory, regarding the appearance of classicality and the measurement problem are stated and their link to studies of open quantum systems is discussed. This study's main aim is to analyze the main approaches that are employed in the context of open quantum systems. The general form of Markovian master equations are derived by a constructive approach. The Quantum State Diffusion (QSD) formalism is stressed upon as an alternative method to the master equations. Using the Calde...
Fuzzy neural network learning method for time series analysis using multivariate autoregression Sisman, NA; Alpaslan, Ferda Nur (1998-11-13) This paper describes how temporal fuzzy neural network model proposed in [4] can be applied to time series analysis when a multivariate autoregressive model is constructed. The fuzzy multivariate autoregression procedure is described first, then the temporal fuzzy neural network model using this procedure is presented.

Citation Formats

I. Onal, M. Ozay, and F. T. Yarman Vural, “Functional Mesh Model with Temporal Measurements for Brain Decoding,” presented at the 37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Milan, ITALY, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53372.