Dynamic Bayesian Network Modeling of Hippocampal Subfields Connectivity with 7T fMRI: A Case Study

Fernando P. Santos; Stephen F. Smagula; Helmet Karim; Tales S. Santini; Howard J. Aizenstein; Tamer S. Ibrahim; Carlos D. Maciel

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

Dynamic Bayesian Network Modeling of Hippocampal Subfields Connectivity with 7T fMRI: A Case Study

Topics: Medical Image Detection, Acquisition, Analysis and Processing; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics

In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSTEC, 178-184, 2017 , Porto, Portugal

Authors: Fernando P. Santos ¹ ; Stephen F. Smagula ² ; Helmet Karim ³ ; Tales S. Santini ³ ; Howard J. Aizenstein ² ; Tamer S. Ibrahim ³ and Carlos D. Maciel ¹

Affiliations: ¹ University of São Paulo, Brazil ; ² University of Pittsburgh School of Medicine, United States ; ³ University of Pittsburgh, United States

Keyword(s): Dynamic Bayesian Networks, fMRI, Network Modelling, Hippocampus.

Abstract: The development of high resolution structural and functional magnetic resonance imaging, along with the new automatic segmentation procedures for identifying brain regions with high precision and level of detail, has made possible new studies on functional connectivity in the medial temporal lobe and hippocampal subfields, with important applications in the understanding of human memory and psychiatric disorders. Many previous analyses using high resolution data have focused on undirected measures between these subfields. Our work expands this by presenting Dynamic Bayesian Network (DBN) models as an useful tool for mapping directed functional connectivity in the hippocampal subfields. Besides revealing directional connections, DBNs use a model-free approach which also exclude indirect connections between nodes of a graph by means of conditional probability distribution. They also relax the constraint of acyclicity imposed by traditional Bayesian networks (BNs) by considering nodes a t different time points through a Markovianity assumption. We apply the GlobalMIT DBN learning algorithm to one subject with fMRI time-series obtained from three regions: the cornu ammonis (CA), dentate gyrus (DG) and entorhinal cortex (ERC), and find an initial network structure, which can be further expanded with the inclusion of new regions and analyzed with a group analysis method. (More)

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 3.140.188.16

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

P. Santos, F.; F. Smagula, S.; Karim, H.; S. Santini, T.; J. Aizenstein, H.; S. Ibrahim, T. and D. Maciel, C. (2017). Dynamic Bayesian Network Modeling of Hippocampal Subfields Connectivity with 7T fMRI: A Case Study. In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - BIOSIGNALS; ISBN 978-989-758-212-7; ISSN 2184-4305, SciTePress, pages 178-184. DOI: 10.5220/0006151601780184

@conference{biosignals17,
author={Fernando {P. Santos}. and Stephen {F. Smagula}. and Helmet Karim. and Tales {S. Santini}. and Howard {J. Aizenstein}. and Tamer {S. Ibrahim}. and Carlos {D. Maciel}.},
title={Dynamic Bayesian Network Modeling of Hippocampal Subfields Connectivity with 7T fMRI: A Case Study},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - BIOSIGNALS},
year={2017},
pages={178-184},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006151601780184},
isbn={978-989-758-212-7},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - BIOSIGNALS
TI - Dynamic Bayesian Network Modeling of Hippocampal Subfields Connectivity with 7T fMRI: A Case Study
SN - 978-989-758-212-7
IS - 2184-4305
AU - P. Santos, F.
AU - F. Smagula, S.
AU - Karim, H.
AU - S. Santini, T.
AU - J. Aizenstein, H.
AU - S. Ibrahim, T.
AU - D. Maciel, C.
PY - 2017
SP - 178
EP - 184
DO - 10.5220/0006151601780184
PB - SciTePress