Bridging Brain and Educational Sciences: An Optical Brain Imaging Study of Visuospatial Reasoning

Date

2011-10-22

Author

Çakır, Murat Perit
Izzetoglu, Meltem
Shewokis, Patricia A.
Izzetoglu, Kurtulus
Onaral, Banu

Metadata

Show full item record

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

Item Usage Stats

209
views

0
downloads

In this paper we present an experimental study where we investigated neural correlates of visuospatial reasoning during math problem solving in a computer-based environment to exemplify the potential for conducting interdisciplinary research that incorporates insights from educational research and cognitive neuroscience. Functional near-infrared spectroscopy (fNIRS) technology is used to measure changes in blood oxygenation in the dorsolateral and inferior prefrontal cortex while subjects attempt to solve tangram puzzles. The study aimed to identify which areas in the frontal cortex are responsive to geometric reasoning elicited by tangram puzzles and explored how the activation patterns change in response to problem types and difficulty levels. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Dr. Zafer Bekirogullari.

Subject Keywords

Optical brain imaging, Dorsolateral prefrontal cortex, Visuospatial reasoning, fNIR

URI

https://hdl.handle.net/11511/30160

DOI

https://doi.org/10.1016/j.sbspro.2011.11.243

Collections

Graduate School of Informatics, Conference / Seminar

Suggestions

OpenMETU
Core

Neural correlates of purchasing behavior in the prefrontal cortex an optical brain imaging study Çakır, Murat Perit; Çakar, Tuna (null; 2015-07-23) Existing neuroimaging studies in decision making predominantly employ the fMRI method. Despite its superior spatial resolution, fMRI is an expensive and impractical neuroimaging technology for purchasing behavior studies in the field. This study aims to explore the role of prefrontal cortex during purchasing behavior by utilizing functional near-infrared (fNIR) spectroscopy; a low-cost, non-invasive and portable optical brain imaging methodology. The findings suggest that fNIRS can be effectively used for d...
Representation of human brain by mesh networks Önal Ertuğrul, Itır; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2017) In this thesis, we propose novel representations to extract discriminative information in functional Magnetic Resonance Imaging (fMRI) data for cognitive state and gender classification. First, we model the local relationship among a set of fMRI time series within a neighborhood by considering temporal information obtained from all measurements in time series. The estimated local relationships, called Mesh Arc Descriptors (MADs), are employed to represent information in fMRI data. Second, we adapt encoding ...
A philosophical analysis of computational modeling in cognitive science Ürgen, Burcu Ayşen; Bağçe, Samet; Department of Cognitive Sciences (2007) This study analyses the methodology of computational cognitive modeling as one of the ways of conducting research in cognitive science. The aim of the study is to provide an understanding of the place of computational cognitive models in understanding human cognition. Considering the vast number of computational cognitive models which have been just given to account for some cognitive phenomenon by solely simulating some experimental study and fitting to empirical data, a practice-oriented approach is adopt...
Fault detection and diagnosis in nonlinear dynamical systems Kılıç, Erdal; Leblebicioğlu, Mehmet Kemal; Department of Electrical and Electronics Engineering (2005) The aim of this study is to solve Fault Detection and Diagnosis (FDD) problems occurring in nonlinear dynamical systems by using model and knowledge-based FDD methods and to give a priority and a degree about faults. For this purpose, three model-based FDD approaches, called FDD by utilizing principal component analysis (PCA), system identification based FDD and inverse model based FDD are introduced. Performances of these approaches are tested on different nonlinear dynamical systems starting from simple t...
A Hierarchical representation and decoding of fMRI data by partitioning a brain network Moğultay, Hazal; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2017) In this study, we propose a hierarchical network representation of human brain extracted from fMRI data. This representation consists of two levels. In the first level, we form a network among the voxels, smallest building block of fMRI data. In the second level, we define a set of supervoxels by partitioning the first level network into a set of subgraphs, which are assu med to represent homogeneous brain regions with respect to a predefined criteria. For this purpose, we develop a novel brain parcellation...

Citation Formats

M. P. Çakır, M. Izzetoglu, P. A. Shewokis, K. Izzetoglu, and B. Onaral, “Bridging Brain and Educational Sciences: An Optical Brain Imaging Study of Visuospatial Reasoning,” 2011, vol. 29, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/30160.