Back close

Amrita School of Biotechnology Shines at Bangalore’s ICACCI ‘18 International Conference

November 27, 2018 - 11:54
Amrita School of Biotechnology Shines at Bangalore’s ICACCI ‘18 International Conference

In another stellar display of its academic excellence, 42 students and young researchers from the Amrita School of Biotechnology (ASBT) have presented 11 peer-reviewed papers at the International Conference on Advances in Computing, Communications and Informatics (ICACCI) held between 11th and 15th of September, 2018 at PES University, Bengaluru, India. The academicians from the computational neuroscience and neurophysiology laboratory submitted themes on computational neuroscience (6 papers), biomedical device technology and methods (3 papers) and ICT-driven virtual labs and digital tools (2 papers) to the prestigious forum.

The focus of Amrita’s computational neuroscience modeling has been on reconstructing biological activity and function in order to study neural changes attributed to behavior and specifically, to understand or predict how brain disorders may happen. The institute has been focusing on using such models for building new tools for helping with diagnosis, for treatment and education requirements.

The multi-school team was led by Dr. Shyam Diwakar of ASBT and involved 31 M. Sc. students, 5 B. Sc. students, 5 Ph. D. students and 2 faculty members from ASBT, along with 4 MCA students from Amrita School of Arts and Sciences.

Papers on computational neuroscience

  1. ‘Modeling Nitric oxide-induced Neural Activity and Neurovascular Coupling in a Cerebellum Circuit’
    In this study, the effect of cerebellar blood flow and neural activity were correlated through a model of nitric oxide (NO) in the cerebellar granular layer. An estimate of nitric oxide-induced activity and corresponding fMRI BOLD response was taken and the volume and flow were also measured.
  2. ‘Reproducing the Firing Properties of a Cerebellum Deep Cerebellar Nucleus with a Multi-compartmental, Morphologically Realistic Biophysical Model’
    A multi-compartmental morphologically realistic model of a DCN neuron was mathematically reconstructed with active ion channels as part of this study.
  3. ‘Modeling of Glutamate Pathway in Alzheimer’s Disease using Biochemical Systems Theory’
    This study made use of computational models to simulate the glutamate pathway to relate molecular mechanisms of how glutamate links to neural activity and predict the involvement in Alzheimer’s disease.
  4. ‘Spectral Correlations in Speaker-listener Behavior during a Focused Duo Conversation using EEG’
    The main goal of this paper was to analyze speaker-listener synchrony during verbal and nonverbal communication within EEG spectra.
  5. ‘Design and Implementation of an Open-source Browser-based Laboratory Platform for EEG Data Analysis’
    We have developed an easy to use online platform to perform EEG data analysis and to verify recorded data. The data analysis platform was implemented with Jinja and MNE-Python tools, which allowed scalable and reasonably fast browser-based access to processing EEG datasets.
  6. ‘Experimental Recording and Computational Analysis of EEG Signals for a Squeeze Task: Assessments and Impacts for Applications’
    For interpreting the difference between brain functions in healthy subjects and motor dysfunctions patients, a motor-related squeeze task, a simple daily task was employed in this study.

Papers on biomedical devices and technology

  1. ‘Experimental Recording and Assessing Gait Phases using Mobile Phone Sensors and EEG’
    n this study, low-cost sensors have been used to collect gait signals and identify the features responsible for differentiating the gait phases.
  2. ‘Torque Analysis of Male-female Gait and Identification using Machine Learning’
    Here, we have used 6 low-cost, wearable mobile phone sensors to extract gait data. Classification and inverse dynamic analysis were performed to identify gait changes for distinctly identifying gender-specific characteristics as relevant classification biomarkers.
  3. ‘Trajectory Tracking using a Bio-inspired Neural Network for a Low- cost Robotic Articulator’
    We have applied the Kalman filter models to train neural networks and used the same to model hand motion and correlate the same to neural spiking activity, in order to generate a biologically realistic model for haptic motion planning activity.

Papers on virtual labs and education tools

  1. ‘Virtual Laboratories in Biotechnology are Significant Educational Informatics Tools’
    This paper reviews the impact of virtual laboratories as an adaptive learning tool and its role in knowledge transfer, in a blended classroom environment using cell biology and molecular biology virtual tools.
  2. ‘Mathematical Models as Bio-science Educational Informatics Tools’
    Listing common simulations used in the demonstration of classroom topics in undergraduate and postgraduate bioscience education in India, this paper reviewed of the effectiveness of virtual labs in blended classroom education.

For complete author information and citations, visit website.

Admissions Apply Now