Justas Birgiolas

Justas Birgiolas
Arizona State University | ASU · Graduate College

Ph.D., MBA

About

21
Publications
8,998
Reads
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114
Citations
Introduction
After having been trained in computer engineering, psychology, and business administration, and have worked as a software developer for over half-decade, I decided to pursue a PhD in computational neuroscience. Advised by Dr. Sharon Crook at ASU, I'm interested in building biophysically detailed large-scale models of the nervous system to understand how behavior arises from neuronal spiking activity. My long term goal is to understand what is necessary to build a brain emulation machine.
Education
August 2014 - December 2019
Arizona State University
Field of study
  • Neuroscience
August 2012 - May 2014
Carnegie Mellon University
Field of study
  • Business Administration
August 2002 - May 2007
University of Illinois, Urbana-Champaign
Field of study
  • Dual Major in Computer Engineering and Psychology

Publications

Publications (21)
Conference Paper
Full-text available
Objectively evaluating and selecting computational models of biological neurons is an ongoing challenge in the field. Models vary in morphological detail, channel mechanisms, and synaptic transmission implementations. We present the results of an automated method for evaluating computational models against property values obtained from published ce...
Article
Full-text available
We describe SwarmSight (available at https://github.com/justasb/SwarmSight ), a novel, open-source, Microsoft Windows software tool for quantitative assessment of the temporal progression of animal group activity levels from recorded videos. The tool utilizes a background subtraction machine vision algorithm and provides an activity metric that can...
Conference Paper
Full-text available
NeuroML is an extensible markup language for describing complex mathematical models of neurons and neuronal networks. NeuroML is unique in its modular, multi-scale structure -- not only can entire NeuroML models be exchanged, but subcomponents of these models that correspond to neuroscience objects, like channels or synapses, also can be shared and...
Preprint
Full-text available
As researchers develop computational models of neural systems with increasing sophistication and scale, it is often the case that fully de novo model development is impractical and inefficient. Thus arises a critical need to quickly find, evaluate, re-use, and build upon models and model components developed by other researchers. We introduce the N...
Conference Paper
Full-text available
The mammalian olfactory bulb is an intensively investigated system that is important in understanding neurodegenerative diseases. Insights gained from understanding the system also have important agricultural and national security applications. In this work, we developed a large-scale, biophysically, and geometrically realistic model of the mouse o...
Article
Full-text available
The neural circuit linking the basal ganglia, the cerebellum and the cortex through the thalamus plays an essential role in motor and cognitive functions. However, how such functions are realized by multiple loop circuits with neurons of multiple types is still unknown. In order to investigate the dynamic nature of the whole-brain network, we built...
Article
Full-text available
Computational models are powerful tools for exploring the properties of complex biological systems. In neuroscience, data-driven models of neural circuits that span multiple scales are increasingly being used to understand brain function in health and disease. But their adoption and reuse has been limited by the specialist knowledge required to eva...
Preprint
Full-text available
Validating a quantitative scientific model requires comparing its predictions against many experimental observations, ideally from many labs, using transparent, robust, statistical comparisons. Unfortunately, in rapidly-growing fields like neuroscience, this is becoming increasingly untenable, even for the most conscientious scientists. Thus the me...
Poster
Full-text available
Biophysically realistic computational models are ideally suited for simulation of predictions that can be verified experimentally via chemical, surgical, and optogenetic manipulations. NeuroML is a modular, declarative, simulator-independent model language for describing and exchanging such models. NeuroML-DB.org is an online resource for rapidly l...
Article
Full-text available
In ants, bees, and other social Hymenoptera, alarm pheromones are widely employed to coordinate colony nest defense. In that context, alarm pheromones elicit innate species-specific defensive behaviors. Therefore, in terms of classical conditioning, an alarm pheromone could act as an unconditioned stimulus (US). Here, we test this hypothesis by est...
Preprint
Full-text available
Computational models are powerful tools for investigating brain function in health and disease. However, biologically detailed neuronal and circuit models are complex and implemented in a range of specialized languages, making them inaccessible and opaque to many neuroscientists. This has limited critical evaluation of models by the scientific comm...
Chapter
Computational models of the nervous system help researchers discover principles of brain operation and form/function relationships. They can provide a framework for understanding empirical data and serve as an experimental platform to test concepts and intuitions. In practice, the effective use of theoretical, computational, and information theoret...
Article
Full-text available
Many scientifically and agriculturally important insects use antennae to detect the presence of volatile chemical compounds and extend their proboscis during feeding. The ability to rapidly obtain high-resolution measurements of natural antenna and proboscis movements and assess how they change in response to chemical, developmental, and genetic ma...
Preprint
Full-text available
Many scientifically and agriculturally important insects use antennae to detect the presence of volatile chemical compounds and extend their proboscis during feeding. The ability to rapidly obtain high-resolution measurements of natural antenna and proboscis movements and assess how they change in response to chemical, developmental, and genetic ma...
Presentation
Full-text available
Presentation on "25th Annual Computational Neuroscience Meeting: CNS-2016 " BMC Neuroscience 17, 112-113 (2016).
Conference Paper
Full-text available
ICGenealogy: towards a common topology of neuronal ion channel function and genealogy in model and experiment Ion channels are fundamental constituents determining the function of single neurons and neuronal circuits. To understand their complex interactions, the field of computational modeling has proven essential: since its emergence, thousands...
Article
Human observers are able to quickly and efficiently perceive the content of natural scenes (Potter, 1976). Previous studies have examined the time course of this rapid classification (Thorpe et al, 1996) as well as the brain regions activated when subjects categorize natural scenes (Epstein & Higgins, 2006). Using statistical pattern recognition al...

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Projects

Project (1)
Project
I am the lead developer for NeuronUnit (http://neuronunit.scidash.org), a Python library for formally validating computational models of neurons and ion channels against experimental data.