(RRJoCB)

ISSN 2349-3720

Research & Reviews Journal of

Computational Biology

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(ISSN: 2349-3720)

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Industrial Tribology Machine Dynamics & Maintenance

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Indian Institute of Technology Delhi, India

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Alternative Energy Technology Laboratory,

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Indian Institute of Technology Madras, India.

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Engineering department, PEC University of Technology,

Chandigarh, India.

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Dr. Jagadeesha MaharudraiahInstitute of Bioinformatics,

Bangalore, India.

Dr. Khushhali MenariaDepartment of Bioinformatics, Maulana Azad National Institute of Technology,

Bhopal (M.P.), India.

P. ChellapandiDepartment of Bioinformatics, Centre

for Excellence in School of Life Sciences, Bharathidasan University,

Tiruchirappalli, India.

Dr. Amutha RamaswamyCentre for Bioinformatics, Pondicherry University Campus, Pondicherry, India.

Dr. Ayaluru MuraliBioinformatics Centre, Pondicherry

University, India.

Joseph SelvinDrug Discovery and Development

Research Unit (DDRU),Dept. of Bioinformatics, India.

Prof.(Dr.) Jugal KishoreDepartment of Community Medicine,

Maulana Azad Medical College, New Delhi 110002, India.

Dr. Kumud SarinEducational Consultant, New Delhi, India

I take the privilege to present the hard copy compilation for the Volume 3 Issue (2) of Research &

Reviews: Journal of Computational Biology (RRJoCB). The intension of RRJoCB is to create an

atmosphere that stimulates creativeness, research and growth in the area of Computational Biology.

The development and growth of the mankind is the consequence of brilliant Research done by

eminent Scientists and Engineers in every field. RRJoCB provides an outlet for Research findings

and reviews in areas of Computational Biology found to be relevant for National and International

recent developments & research initiative.

The aim and scope of the Journal is to provide an academic medium and an important reference for

the advancement and dissemination of Research results that support high level learning, teaching and

research in the domain of Computational Biology.

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their continued support and invaluable contributions and suggestions in the form of authoring write-

ups/ reviewing and providing constructive comments for the advancement of the journals. With

regards to their due continuous support and co-operation, we have been able to publish quality

Research/Reviesw findings for our customers base.

I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra

Director

STM Journals

Director's Desk

STM JOURNALS

1. Characterizing Face Encoding Mechanism by Selective Object Pattern in Brains using Synthetic Intelligence and Its Simultaneous Replication of Visual System That Encode Faces Ankush Rai 1

2. Computational Modeling Study of Synfire Chains from Multiple Plasticity Mechanisms for Model Development at Neural Level: Introducing an Evolving Digital Micro-Brain

Ankush Rai 9

3. Arterial Stiffness and Parameters for Its Assessment Pankti Brar, Sharda Vashisth 16

ContentsResearch & Reviews : Journal of Computational Biology

RRJoCB (2014)© STM Journals 2014. All Rights Reserved

Research & Reviews: Journal of Computational Biology ISSN: 2319-3433 (online), ISSN: 2349-3720 (print)

Volume 3, Issue 2

www.stmjournals.com

Characterizing Face Encoding Mechanism by Selective

Object Pattern in Brains using Synthetic Intelligence and

Its Simultaneous Replication of Visual System

That Encode Faces

Ankush Rai* Department of Applied Science, CRIAD Laboratories, Smiriti Nagar, Bhilai 490020, India

Abstract Various aspects of facial recognition information for identifying individuals are still

remained unknown. Our goal in the research papers is to identify factors from

parahippocampal place area (PPA)with means of computational method that trigger the

recognition process and what constitutes facial encoding by measuring the selectively

responses in PPA to images of objects. We use synthetic intelligent computer model to

help categories the feature selectivity in brain patterns and simultaneously training it as a building block for visual system which mimics and categorized shape selective responses

in PPA.

Keywords: Face perception; FMRI; Neural representation; Face recognition;

Parahippocampal activity; Computational neuroscience

RRJoCB (2014)© STM Journals 2014. All Rights Reserved

Research & Reviews: Journal of Computational Biology ISSN: 2319-3433 (online), ISSN: 2349-3720 (print)

Volume 3, Issue 2

www.stmjournals.com

Computational Modeling Study of Synfire Chains from

Multiple Plasticity Mechanisms for Model Development at

Neural Level: Introducing an Evolving Digital

Micro-Brain

Ankush Rai* Department of Applied Science, CRIAD Laboratories, Smiriti Nagar, Bhilai 490020, India

Abstract In a biological specimen with evolved brain the interconnected neural networks by

plasticity mechanisms bring out intelligence, consciousness, and emotions by a collective

firing of a sets of neurons operating at different time delays and oscillations. Therefore,

the nature of our study is to computationally test a mathematical model to mimic

neurological events in general and provides a theoretical and experimental framework

that links neural function to model-based learning and theory of cognitive control; which in turn will bridge the junction of biology and computer science. This will allow us to

sculpt such neural networks into effective data processor.

Keywords: synfire chain, recurrent neural network, self-organization network, spike-

timing-dependent plasticity

RRJoCB (2014)© STM Journals 2014. All Rights Reserved

Research & Reviews: Journal of Computational Biology ISSN: 2319-3433 (online), ISSN: 2349-3720 (print)

Volume 3, Issue 2

www.stmjournals.com

Arterial Stiffness and Parameters for Its Assessment

Pankti Brar1*, Sharda Vashisth

2

1ECE Department, Dronacharya College of Engineering, Gurgaon, India

2EECE Department, ITM University, Gurgaon, India

Abstract In this paper, we have presented a review of the changes that occur in the vasculature

with age. These all lead to increased central arterial stiffness. Arterial stiffness lead to

variation in the blood flow physics, which inturn causes the reflected pressure wave to reach the aortic root in the systole. This leads to increase in the systolic blood pressure

and ultimately the pulse pressure increases. The article further reviews that vascular

damage can be assessed by pulse wave velocity (PWV) and the augmentation index (AI).

Both these parameters can be easily determined noninvasively and are reproducible.

Keywords: Arterial stiffness, Augmentation index, Pulse wave velocity, Forward

arterial wave, Reflected arterial wave