Connectionists: Scientist I – Neural Connectivity and Consciousness

[Stefan Mihalas]

Scientist I – Neural Connectivity and Consciousness

The Allen Institute for Brain Science is looking to add a Scientist I to our Modeling & Theory team. This scientist will work under the supervision of Stefan Mihalas and will be part of a larger team led by Christof Koch which includes both experimental, theoretical and modeling work aimed at measuring the neural correlates of consciousness.

The mouse brain has an intricate anatomical connectivity, which we have mapped in detail ( http://connectivity.brain-map.org/ ). Connectivity patterns have important consequences for synchronization between areas. Specifically, a small number of strong, long range connections can shift the synchronization from local to global. Additionally, in the cortex we have characterized multiple types of inter-areal connections.

How does this observed structure support conscious perception? More specifically, what elements of network connectivity are important to generate activity which is sufficiently complex and integrated to support consciousness? We seek to hire a scientist to help us make progress towards answering this question.

Position Summary

The Scientist will work on coarse-grained models of cortical networks aiming to understand how the structure of inter-areal connections influences the complexity of the activity simulated on such networks and the synchronization between different nodes, and if any features of the observed mesoscopic connectivity are particularly important.

We use mouse as a model system and this position will focus on using coupled oscillator models with multiple types of long-range interactions and population statistics models and simulation tools (http://alleninstitute.github.io/dipde/).

More specifically, the scientist will work to: (i) Simulate coupled oscillator models parameterized by mesoscopic connectivity measurements and analyze the complexity of localized perturbations to the model (“Zap and Zip”). (ii) Simulate the cortical activity using population statistic methods and simplified area models. (iii) Analyze the importance of both the strength and type of connections between areas to these results, and the importance of specific nodes (for example claustrum).

While modeling work is essential for this position, the capacity of the applicant to work in parallel on theoretical understanding of the obtained results is highly desired.

Job Responsibilities

·         Simulate cortical networks parameterized from experimental data coupled oscillator models as well as population statistics model.
·         Analyze how different measures of activity (e.g. the complexity of perturbations, the relation between local and long-range correlations, and other measures of activity shown to be relevant for consciousness) relate to graph theoretical measures based on strength of connections, and multigraph measures relating to types of connections.
·         Compare the results of the simulations with theoretical models with a focus on integrated information theory (IIT).
·         Interact and collaborate with experimental and computational team members that are investigating complementary aspects of the neuronal correlates of consciousness.
·         Maintain clear and accurate communication with supervisor and team members.
·         Publish/present findings in peer-reviewed journals/scientific conferences.


Required Qualifications

·         PhD degree in computational neuroscience, physics, mathematics, applied mathematics or related field.
·         Strong background in scientific computing.
·         Strong publication record.
·         Experience in pursuing research projects in collaborative fashion.
·         Proven independent thinking and flexibility.
·         Strong written and verbal communication skills.


Preferred Qualifications

·         Experience in computational neuroscience is preferred.
·         Ability to meet aggressive timelines and deliverables in a collaborative environment

It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities.



Stefan Mihalas
Associate Investigator
Allen Institute for Brain Science
www.alleninstitute.org<http://www.alleninstitute.org/>

Affiliate Professor
Department of Applied Mathematics
University of Washington

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