Transport Coefficients from Large Deviation Functions

We describe a method for computing transport coefficients from the direct evaluation of large deviation function. This method is general, relying on only equilibrium fluctuations, and is statistically efficient, employing trajectory based importance sampling. Equilibrium fluctuations of molecular currents are characterized by their large deviation functions, which is a scaled cumulant generating function analogous to the free energy. A diffusion Monte Carlo algorithm is used to evaluate the large deviation functions, from which arbitrary transport coefficients are derivable. We find significant statistical improvement over traditional Green-Kubo based calculations. The systematic and statistical errors of this method are analyzed in the context of specific transport coefficient calculations, including the shear viscosity, interfacial friction coefficient, and thermal conductivity.Comment: 11 pages, 5 figure

Visualization 2: Multiphoton in vivo imaging with a femtosecond semiconductor disk laser

In vivo two-photon imaging of blood vessels filled with Texas Red Dextran using the ultrafast SDL. Originally published in Biomedical Optics Express on 01 July 2017 (boe-8-7-3213

Layer-specific R-CaMP1.07 expression and calcium transients in vivo.

<p><b>A,</b> Large field-of-view two-photon images in S1 cortex for the four different mouse lines expressing R-CaMP1.07. In L4-R-CaMP1.07 mice the barrels and septa in S1 cortex are clearly discernible. <b>B,</b> Example spontaneous R-CaMP1.07 calcium transients measured in awake mice of the corresponding mouse lines. Traces for three example cells (marked) are shown for each imaging field.</p

Characterization of layer-specific R-CaMP1.07 expression in triple transgenic mice.

<p><b>A</b>, Schematic diagram of intersectional control by Cre and tTA, driven by different promoters, of the doubly regulated TITL-R-CaMP1.07 reporter line. tTA is driven by a CamK2a promoter, whereas layer-specificity is achieved by Cre expressed under the control of layer-specific promoters (p2: Rasgrf2-2A for L2/3, Nr5a1 for L4, Rbp4 for L5 and Ntsr1 for L6). <b>B</b>, Confocal images of coronal sections of fixed brains from the different mice, illustrating layer-specific labelling in neocortex of the respective mouse lines. <b>C</b>, High-resolution close-ups of the regions indicated in B, showing the R-CaMP1.07 expression patterns across cortical layers.</p

R-CaMP1.07 sensitivity for reporting APs in vivo.

<p><b>A,</b> Left: Cell body of an R-CaMP1.07-expressing L2/3 neuron and recording pipette. Right: Simultaneous fluorescence measurement and juxtacellular AP recording from this neuron. The number of spikes per burst is indicated below the voltage trace. <b>B,</b> Average Δ<i>F</i>/<i>F</i> calcium transient for R-CaMP1.07 in response to a single AP in red (± S.E.M as grey traces; n = 63 transients from 8 cells, 3 mice). <b>C,</b> Peak amplitudes of Δ<i>F</i>/<i>F</i> calcium transients (red data points) as a function of the number of APs within short AP bursts (300-ms time window; mean ± S.E.M.). For comparison R-CaMP1.07 performance for AAV-mediated expression (same as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179460#pone.0179460.g001" target="_blank">Fig 1E</a>) is overlaid (grey data points). <b>D,</b> Efficiency of AP detection in vivo was determined by estimating the distribution of the signal-to-noise ratio (SNR) under noise conditions and fitting with a Gaussian. From the fit, we determined the SNR cutoff at which less than 5% of baseline traces would be classified as false positives (SNR = 2.28). Using this threshold, 60% (38/63) of single APs, 97% of doublets (38/39) and 100% of triplets (30/30) were correctly detected (see ref. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179460#pone.0179460.ref053" target="_blank">53</a>]).</p

Long-term stability of L2/3 R-CaMP1.07 calcium signals.

<p><b>A,</b> Longitudinal two-photon imaging of the same group of cells in L2/3 of S1 cortex in an example mouse, at 22, 45, 65 and 100 days post-induction (DPI). For a spectrally unmixed version of the image at 65 DPI see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179460#pone.0179460.s003" target="_blank">S3 Fig</a>. <b>B,</b> Two-photon images of L2/3 neurons within the same tissue volume, for which R-CaMP1.07 calcium transients were measured across days. In the imaging sessions 65 DPI and 100 DPI the very same neurons were measured (same cells as in A). For each imaging area three example Δ<i>F</i>/<i>F</i> traces with spontaneous calcium transients are shown for the cells marked in the images above. <b>C</b>, Pooled analysis of stability of R-CaMP1.07 calcium transients. Recordings were made in 2 mice from a total of 18, 15, 15, and 38 active cells at 22, 45, 65, and 100 DPI, respectively. Data points and box plots of peak amplitudes of calcium transient events did not show significant variation across sessions. <b>D</b>, Data points and box plots of decay time constants (τ) of exponentially fitted calcium transients (see inset), which also did not show a significant change across imaging sessions. <b>E</b>, Cumulative distribution of calcium transient amplitudes for L2/3 neurons that were measured twice at 65 and 100 DPI, respectively. A non-parametric, Wilcoxon rank sum test was used to compute <i>P</i>-values.</p