Justas Birgiolas

Ronin Institute

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...

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...

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...

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...

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...

Most biological brains, as well as artificial neural networks, are capable of performing multiple tasks [1]. The mechanisms through which simultaneous tasks are performed by the same set of units are not yet entirely clear. Such systems can be modular or mixed selective through some variables such as sensory stimulus [2,3]. Based on simple tasks st...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...