UH Biocomputation Group - Neuronhttp://biocomputation.herts.ac.uk/2018-02-12T14:36:04+00:00Olfactory coding in the turbulent realm2018-02-12T14:36:04+00:002018-02-12T14:36:04+00:00Rebecca Mikotag:biocomputation.herts.ac.uk,2018-02-12:/2018/02/12/olfactory-coding-in-the-turbulent-realm.html<p class="first last">Rebecca Miko's journal club session on 'Olfactory coding in the turbulent realm' by Jacob et al.</p>
<p>Long-distance olfactory search behaviors depend on odor detection dynamics. Due to turbulence, olfactory signals travel as bursts of variable concentration and spacing and are characterized by long-tail distributions of odor/no-odor events, challenging the computing capacities of olfactory systems. How animals encode complex olfactory scenes to track the plume far from the source remains unclear. Here we focus on the coding of the plume temporal dynamics in moths. We compare responses of olfactory receptor neurons (ORNs) and antennal lobe projection neurons (PNs) to sequences of pheromone stimuli either with white-noise patterns or with realistic turbulent temporal structures simulating a large range of distances (8 to 64 m) from the odor source. For the first time, we analyze what information is extracted by the olfactory system at large distances from the source. Neuronal responses are analyzed using linear–nonlinear models fitted with white-noise stimuli and used for predicting responses to turbulent stimuli.</p>
<p><strong>Date:</strong> 16/02/2018 <br />
<strong>Time:</strong> 16:00 <br />
<strong>Location</strong>: LB252</p>
How the Olfactory Bulb processes naturalistic time-varying inputs2017-10-11T18:31:43+01:002017-10-11T18:31:43+01:00Rebecca Mikotag:biocomputation.herts.ac.uk,2017-10-11:/2017/10/11/how-the-olfactory-bulb-processes-naturalistic-time-varying-inputs.html<p class="first last">Rebecca will be presenting the work she conducted for her masters thesis titled 'How the Olfactory Bulb processes naturalistic time-varying inputs'.</p>
<p>Rebecca will be presenting the work she conducted for her master's thesis titled 'How the Olfactory Bulb processes naturalistic time-varying inputs'.</p>
<p>Abstract is below:</p>
<hr class="docutils" />
<p>The olfactory bulb in mammals is responsible for receiving, processing and relaying olfactory
information (odours). This project investigates how naturalistic temporally fluctuating odour signals are
processed and which neurons or neural mechanisms are able to extract information from these signals.
Multiple computation models were created to represent different OB circuits between periglomerular
cells and mitral cells using NEURON (Hines and Carnevale, 2006, 2001). The results show that the
strength and frequency of these odour signals can be determined by looking at a combination of the
latency and the firing rates of the output from the mitral cells.</p>
<p><strong>Date:</strong> 20/10/2017 <br />
<strong>Time:</strong> 16:00 <br />
<strong>Location</strong>: LB252</p>
An introduction to NEURON2017-05-11T10:05:33+01:002017-05-11T10:05:33+01:00Maria Psarroutag:biocomputation.herts.ac.uk,2017-05-11:/2017/05/11/an-introduction-to-neuron.html<p class="first last">Maria Psarrou's journal club session where she introduces the NEURON simulator.</p>
<p>Biological computational modelling is a powerful tool to simulate a system and draw conclusions regarding its function. It also allows to make predictions for processes that still haven’t been investigated in the laboratory. NEURON [1, 2] is an simulation environment, where empirical data are combined with analytic mathematical expressions, in order to model single neurons or neural networks. Neuronal cells are created as a series of connected sections, able to form realistic morphologies, and where different membrane properties (ionic, synaptic and passive) can be inserted. The interface and programming syntax are designed to offer an intuitive environment and emphasise on the biological functions in detail, rather than the the programming or numerical methods.
The purpose of this workshop is to give an introduction to the NEURON software and how it could be used, by building a simple neuronal cell model and testing its behaviour under different conditions.</p>
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<ol class="arabic simple">
<li>Carnevale, N.T. and Hines, M.L. The NEURON Book. Cambridge, UK: Cambridge University Press, 2006.</li>
<li>NEURON for empirically-based simulations of neurons and networks of neurons (2017). [online] Available at: <a class="reference external" href="https://www.neuron.yale.edu/">https://www.neuron.yale.edu/</a></li>
</ol>
<p><strong>Date:</strong> 12/05/2017 <br />
<strong>Time:</strong> 16:00 <br />
<strong>Location</strong>: LB252</p>