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Intelligent estimation of the structural connectivity of neuronal cultures

Project Description

The vast majority of cognitive theories as well as computational neuroscience models are concentrating on the computational properties of neurons, circuits and systems, effectively reducing intelligence to disembodied information processing engine. However, growing body of evidence suggests that computational properties cannot be disentangled from the biological substrate in which they take place; the cognitive processes are shaped by the bodies which give rise to them. In order to advance our understanding of intelligence it is necessary to start taking forms of embodiment seriously. One characteristics of embodiment is structure. In case of neurons and neural networks, structure corresponds to the shape of the dendritic trees of single neurons, distribution of synaptic contacts across the neuron’s body and to topology of neural connections.
In order to understand how the structure of neural networks contributes to intelligent information processing it is thus necessary to estimate the topology of such networks and start relating topological characteristics to the functions played by the corresponding circuits. Comparing the structural characteristics between in vitro culture models of neurological disorders with controls may shed light on the contributions of structural factors to pathology. This project will focus on creation of intelligent next generation of tools for automated reconstruction of anatomical connectivity from the microscope images of in vitro neural cultures. It will require combination of the intelligent image processing tools with the methods for tracking the curvilinear features and estimating the variability of connectivity patterns and extraction of topological invariants and motifs.

The project will be hosted by the School of Biological Sciences, University of Reading. The University of Reading is one of the UK’s 20 most research-intensive universities and among the top 200 universities in the world. Achievements include the Queen’s Award for Export Achievement (1989) and the Queen’s Anniversary Prize for Higher Education (1998, 2006 and 2009). This project will take place in the Brain Embodiment Lab within Biomedical Engineering Section of the School of Biological Sciences (SBS), which has a strong reputation for its innovative research in cybernetics, and biomedical engineering, including Brain Computer Interfaces, animats - robots controlled by cultures of living neuronal cells and cognitive robotics systems.

For informal inquiries please contact Prof SJ Nasuto, email: .

Funding Notes

Eligibility requirements:

Applicants should have a bachelors (at least 2.1 or equivalent) or masters degree in physics,
applied mathematics, engineering, computing or a strongly related discipline.
Strong analytic and programming skills are preferable.
Experience in image processing and experimental data analysis are desirable.

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