UH Biocomputation Group - mushroom bodyhttp://biocomputation.herts.ac.uk/2021-06-23T11:28:03+01:00A Spiking Neural Program for Sensorimotor Control during Foraging in Flying Insects2021-06-23T11:28:03+01:002021-06-23T11:28:03+01:00Shavika Rastogitag:biocomputation.herts.ac.uk,2021-06-23:/2021/06/23/a-spiking-neural-program-for-sensorimotor-control-during-foraging-in-flying-insects.html<p class="first last">Shavika Rastogi's Journal Club session where she will talk about a paper "A Spiking Neural Program for Sensorimotor Control during Foraging in Flying Insects"</p>
<p>This week on Journal Club session Shavika Rastogi will talk about a paper "A Spiking Neural Program for Sensorimotor Control during Foraging in Flying Insects".</p>
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<p>Foraging is a vital behavioral task for living organisms. Behavioral
strategies and abstract mathematical models thereof have been
described in detail for various species. To explore the link between
underlying neural circuits and computational principles, we present
how a biologically detailed neural circuit model of the insect
mushroom body implements sensory processing, learning, and motor
control. We focus on cast and surge strategies employed by flying
insects when foraging within turbulent odor plumes. Using a spike-
based plasticity rule, the model rapidly learns to associate
individual olfactory sensory cues paired with food in a classical
conditioning paradigm. We show that, without retraining, the system
dynamically recalls memories to detect relevant cues in complex
sensory scenes. Accumulation of this sensory evidence on short time
scales generates cast-and-surge motor commands. Our generic systems
approach predicts that population sparseness facilitates learning,
while temporal sparseness is required for dynamic memory recall and
precise behavioral control. Our work successfully combines biological
computational principles with spike-based machine learning. It shows
how knowledge transfer from static to arbitrary complex dynamic
conditions can be achieved by foraging insects and may serve as
inspiration for agent-based machine learning.</p>
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<p>Papers:</p>
<ul class="simple">
<li>H. Rapp, M. Nawrot, <a class="reference external" href="https://doi.org/10.1073/pnas.2009821117">"A Spiking Neural Program for Sensorimotor Control during Foraging in Flying Insects"</a>, 2020, Proceedings of the National Academy of Sciences, 117, 28412--28421</li>
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<p><strong>Date:</strong> 2021/06/25 <br />
<strong>Time:</strong> 14:00 <br />
<strong>Location</strong>: online</p>