We are working with Prof. Aurel Lazar’s Bionet Lab (http://www.bionet.ee.columbia.edu/) to design, implement and experimentally evaluate an open software framework called the Neurokernel that will enable the isolated and integrated emulation of fly brain model neural ciits and their connectivity patterns (e.g., sensory and locomotion systems) and other parts of the fly’s nervous system on clusters of GPUs, and support the in vivo functional identification of neural circuits. (Note this is NOT the same meaning of “in vivo” as PSL’s In Vivo Testing project.)
The Neurokernel will:
- Enable computational/systems neuroscientists to exploit new connectome data by directing emulation efforts at interoperable local processing units (LPUs), functional subdivisions of the brain that serve as its computational substrate;
- Capitalize on the representation of stimuli in the time domain to enable the development of novel asynchronous algorithms for processing spikes with neural circuits;
- Serve as an extended machine that will provide abstractions and interfaces for scalably leveraging a powerful commodity parallel computing hardware platform to study a tractable neural system;
- Serve as a resource allocator that will enable researchers to transparently take advantage of future improvements in this hardware platform;
- Enable testing of models, both by easing the detection and localization of programming errors and by operationally verifying the models’ designs against time-encoded signals to/from live fly brains in real-time;
- Accelerate the research community’s progress in developing new brain circuit model by facilitating the sharing and refinement of novel and/or improved models of LPUs and their constituent circuits by different groups.
To ease its use by the neuroscience community and enable synergy with existing computational tools and packages, we are developing our software framework in Python, a high-level language that has enjoyed great popularity amongst computational neuroscientists.
As we enhance Neurokernel to model new regions of the fly brain, there may be a negative effect on previous models for other regions. As the fly brain model(s) will be developed in iterative software development cycles, it will be imperative to ensure that each iteration re-verifies the platform and its individual LPUs against the actual fly brain neuropils. We would like these tests on the Python code to be conducted automatically, without requiring the use of our fly interface equipment — which is manually intensive to operate. We are constructing a tool to simulate the fly brain interface for software testing purposes that will capture the stimuli provided to the fly along with its responses. From these sets of inputs and outputs, the tool will automatically generate test cases that recreate the same experiment without the need for repeated interfacing with the fly. This tool will also be used to automatically generate regression tests for the Neurokernel software that depend on other external factors.
Additional information is available on the Bionet website.
Contact Professor Aurel Lazar (email@example.com) for further information.
Former PSL Graduate Students