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**How to keep cool in hot situations: temperature **

compensation in grasshopper auditory neurons Susanne Schreiber Humboldt-Universität and Bernstein Center Berlin Tübingen, July 7th 2012

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**Acoustic communication in grasshoppers**

Susanne Schreiber, BCCN Berlin

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**Reliable mate recognition**

... in warm and cold environments. Susanne Schreiber, BCCN Berlin

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**The grasshopper auditory periphery**

The auditory periphery consists of a simple feed-forward network: Susanne Schreiber, BCCN Berlin

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**Temperature-dependence in the receiver**

Ion-channel dynamics depend on temperature. Neuronal activity is hence likely to depend on temperature too. Susanne Schreiber, BCCN Berlin

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**Quantifying temperature-dependence**

Relative firing-rate change: (RMS) Susanne Schreiber, BCCN Berlin

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**Experimental findings (receptor neurons):**

Relative change in firing rate: Monika Eberhard relative change (spike rate) cell count cell count Q10-value (spike rate) Receptor neurons are surprisingly temperature invariant. Given the feedforward structure of the network, invariance must arise from cell-intrinsic properties. Susanne Schreiber, BCCN Berlin

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**Can temperature invariance be cell-intrinsic?**

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**Study of single-neuron models**

Connor-Stevens model with 9 temperature-dependent parameters (peak conductances and rates). Susanne Schreiber, BCCN Berlin

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**Model analysis Introduce temperature dependence for**

peak conductances and transition rates. Simulate parameter combinations in the physiological range. Question: Can temperature invariance of the firing rate arise? Susanne Schreiber, BCCN Berlin

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**Results of the model analysis**

Frederic Römschied Distribution of firing rate changes across all models: relative change (spike rate) model count Temperature invariance as observed experimentally (about 30%) is possible. But what are the mechanisms? Susanne Schreiber, BCCN Berlin

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**Relative firing-rate change as a function of all parameters**

Visualization: Dimensional stacking. Different parameters are represented on different scales of the image. relative change (spike rate) Impact of parameters: Susanne Schreiber, BCCN Berlin

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**Is temperature invariance metabolically expensive?**

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**Quantification of energy-efficiency**

1. Total Na current (total energy consumption). 2. Overlap between Na and K currents (separability). Susanne Schreiber, BCCN Berlin

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**Energy-efficiency is possible**

Distribution of changes in energy consumption across: firing-rate invariant models: (relative change < 40%) relative consumption count not firing-rate invariant models: (relative change > 40%) relative consumption count Susanne Schreiber, BCCN Berlin

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**Parameters influencing energy consumption**

relative energy consumption Sodium channel temperature-dependence has a large influence on neural energy-efficiency. Susanne Schreiber, BCCN Berlin

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**Two examples Two models with similar temperature invariance ...**

... but different energy efficiency. Susanne Schreiber, BCCN Berlin

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**Key players for temperature invariance and **

energy efficiency are not the same Largely different parameters determine temperature invariance and energy efficiency. Temperature-invariant models can be energy efficient! Susanne Schreiber, BCCN Berlin

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**Summary Grasshopper receptor neurons are surprisingly invariant to**

changes in temperature. This temperature invariance must be cell-intrinsic (no network input). Some ion channels are particularly suited to mediate temperature invariance (potassium channels). Energy-efficiency and temperature invariance of spike rate are not incompatible (mechanisms are largely independent). Susanne Schreiber, BCCN Berlin

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**The computational neurophysiology group**

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**Thanks to The lab: Sven Blankenburg Katharina Glomb, Janina Hesse,**

Eric Reifenstein, Michiel Remme, Frederic Roemschied, Fabian Santi, Katharina Wilmes, Wei Wu, Dmitry Zarubin, Ekaterina Zhuchkova Collaborators: Bernhard Ronacher (Humboldt-University) Monika Eberhard (Humboldt-University) Dietmar Schmitz (Charite Berlin) Richard Kempter (Humboldt-University) Ines Samengo (Bariloche, Argentina) Andreas Herz (LMU Munich), Irina Erchova (University of Edinburgh, UK), Tania Engel (Stanford University) BMBF: Bernstein Center for Computational Neuroscience Berlin, BPCN, BFNL DFG: SFB 618, GK1589

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**Further improvement by mechanotransduction**

+ Susanne Schreiber, BCCN Berlin

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**Other projects in the group Insects:**

Entorhinal cortex: subthreshold resonance: - spatial dependence, - information transfer phase precession in grid cells population coding in the auditory periphery of the grasshopper: summed population versus labeled line insect cellular morphology Heart: ion channel cooperativity Susanne Schreiber, BCCN Berlin

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**Temperature affects grasshopper communication**

Susanne Schreiber, BCCN Berlin

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**Receptor neurons are most temperature-invariant**

Given the feedforward structure of the network, temperature robustness in receptor neurons must arise from cell-intrinsic properties. Susanne Schreiber, BCCN Berlin

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