Towards real-time neuronal connectivity assessment: A scalable pipelined parallel generalized partial directed coherence engine

Georgios Georgis; Georgios Menoutis; Dionysios Reisis; Konstantinos Tsakalis; Ashfaque Bin Shafique

doi:10.1109/ICECS.2015.7440237

Towards real-time neuronal connectivity assessment: A scalable pipelined parallel generalized partial directed coherence engine

Georgios Georgis, Georgios Menoutis, Dionysios Reisis, Konstantinos Tsakalis, Ashfaque Bin Shafique

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The current paper introduces a real-time architecture for the computation of the Generalized Partial Directed Coherence (GPDC) of multiple signals. The motivating application is the localization and control of epileptic seizures where hitherto published results shown the effectiveness of exploiting Generalized Partial Directed Coherence to quantify and analyse connectivity and interaction of brain structures. To speed up GPDC computations we develop first, a parallelizing strategy leading to the high performance scalable architecture and second, a low-complexity fixed-point reciprocal square root module. We show that a real-time computation is feasible at a speed of 0.027ms for 16 channels and 1.637ms for 128 channels. Furthermore, the implementation results on Xilinx 7A35T, KC705, VC707, KU115 show that the power requirements are quite modest and allow for the embedded application of the engine.

Original language	English (US)
Title of host publication	2015 IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	13-16
Number of pages	4
ISBN (Electronic)	9781509002467
DOIs	https://doi.org/10.1109/ICECS.2015.7440237
State	Published - Mar 23 2016
Event	IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015 - Cairo, Egypt Duration: Dec 6 2015 → Dec 9 2015

Publication series

Name	Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems
Volume	2016-March

Other

Other	IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015
Country/Territory	Egypt
City	Cairo
Period	12/6/15 → 12/9/15

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/ICECS.2015.7440237

Cite this

Georgis, G., Menoutis, G., Reisis, D., Tsakalis, K., & Shafique, A. B. (2016). Towards real-time neuronal connectivity assessment: A scalable pipelined parallel generalized partial directed coherence engine. In 2015 IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015 (pp. 13-16). Article 7440237 (Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems; Vol. 2016-March). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICECS.2015.7440237

Towards real-time neuronal connectivity assessment: A scalable pipelined parallel generalized partial directed coherence engine. / Georgis, Georgios; Menoutis, Georgios; Reisis, Dionysios et al.
2015 IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 13-16 7440237 (Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems; Vol. 2016-March).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Georgis, G, Menoutis, G, Reisis, D, Tsakalis, K & Shafique, AB 2016, Towards real-time neuronal connectivity assessment: A scalable pipelined parallel generalized partial directed coherence engine. in 2015 IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015., 7440237, Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems, vol. 2016-March, Institute of Electrical and Electronics Engineers Inc., pp. 13-16, IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015, Cairo, Egypt, 12/6/15. https://doi.org/10.1109/ICECS.2015.7440237

Georgis G, Menoutis G, Reisis D, Tsakalis K, Shafique AB. Towards real-time neuronal connectivity assessment: A scalable pipelined parallel generalized partial directed coherence engine. In 2015 IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 13-16. 7440237. (Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems). doi: 10.1109/ICECS.2015.7440237

Georgis, Georgios ; Menoutis, Georgios ; Reisis, Dionysios et al. / Towards real-time neuronal connectivity assessment : A scalable pipelined parallel generalized partial directed coherence engine. 2015 IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 13-16 (Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems).

@inproceedings{d80b80dc400c466e8b9b1e90c276c47d,

title = "Towards real-time neuronal connectivity assessment: A scalable pipelined parallel generalized partial directed coherence engine",

abstract = "The current paper introduces a real-time architecture for the computation of the Generalized Partial Directed Coherence (GPDC) of multiple signals. The motivating application is the localization and control of epileptic seizures where hitherto published results shown the effectiveness of exploiting Generalized Partial Directed Coherence to quantify and analyse connectivity and interaction of brain structures. To speed up GPDC computations we develop first, a parallelizing strategy leading to the high performance scalable architecture and second, a low-complexity fixed-point reciprocal square root module. We show that a real-time computation is feasible at a speed of 0.027ms for 16 channels and 1.637ms for 128 channels. Furthermore, the implementation results on Xilinx 7A35T, KC705, VC707, KU115 show that the power requirements are quite modest and allow for the embedded application of the engine.",

author = "Georgios Georgis and Georgios Menoutis and Dionysios Reisis and Konstantinos Tsakalis and Shafique, {Ashfaque Bin}",

note = "Funding Information: The authors' work has been supported by the National Science Foundation, under Grant ECCS-1102390. Publisher Copyright: {\textcopyright} 2015 IEEE. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.; IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015 ; Conference date: 06-12-2015 Through 09-12-2015",

year = "2016",

month = mar,

day = "23",

doi = "10.1109/ICECS.2015.7440237",

language = "English (US)",

series = "Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "13--16",

booktitle = "2015 IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015",

}

TY - GEN

T1 - Towards real-time neuronal connectivity assessment

T2 - IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015

AU - Georgis, Georgios

AU - Menoutis, Georgios

AU - Reisis, Dionysios

AU - Tsakalis, Konstantinos

AU - Shafique, Ashfaque Bin

N1 - Funding Information: The authors' work has been supported by the National Science Foundation, under Grant ECCS-1102390. Publisher Copyright: © 2015 IEEE. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.

PY - 2016/3/23

Y1 - 2016/3/23

N2 - The current paper introduces a real-time architecture for the computation of the Generalized Partial Directed Coherence (GPDC) of multiple signals. The motivating application is the localization and control of epileptic seizures where hitherto published results shown the effectiveness of exploiting Generalized Partial Directed Coherence to quantify and analyse connectivity and interaction of brain structures. To speed up GPDC computations we develop first, a parallelizing strategy leading to the high performance scalable architecture and second, a low-complexity fixed-point reciprocal square root module. We show that a real-time computation is feasible at a speed of 0.027ms for 16 channels and 1.637ms for 128 channels. Furthermore, the implementation results on Xilinx 7A35T, KC705, VC707, KU115 show that the power requirements are quite modest and allow for the embedded application of the engine.

AB - The current paper introduces a real-time architecture for the computation of the Generalized Partial Directed Coherence (GPDC) of multiple signals. The motivating application is the localization and control of epileptic seizures where hitherto published results shown the effectiveness of exploiting Generalized Partial Directed Coherence to quantify and analyse connectivity and interaction of brain structures. To speed up GPDC computations we develop first, a parallelizing strategy leading to the high performance scalable architecture and second, a low-complexity fixed-point reciprocal square root module. We show that a real-time computation is feasible at a speed of 0.027ms for 16 channels and 1.637ms for 128 channels. Furthermore, the implementation results on Xilinx 7A35T, KC705, VC707, KU115 show that the power requirements are quite modest and allow for the embedded application of the engine.

UR - http://www.scopus.com/inward/record.url?scp=84964845224&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84964845224&partnerID=8YFLogxK

U2 - 10.1109/ICECS.2015.7440237

DO - 10.1109/ICECS.2015.7440237

M3 - Conference contribution

AN - SCOPUS:84964845224

T3 - Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems

SP - 13

EP - 16

BT - 2015 IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2015

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 6 December 2015 through 9 December 2015

ER -

Towards real-time neuronal connectivity assessment: A scalable pipelined parallel generalized partial directed coherence engine

Abstract

Publication series

Other

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this