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Figure 2—figure supplement 2. Robustness of intrinsic STP evoked by 100 Hz train at unitary GC-MLI synapses. ; (A) Functional mapping of synaptic responses recorded during 100 Hz trains in 99 neurons (See Materials and methods). PCA transformation are computed independently for each train (n > 1000) based on the charge value of each EPSC in the train. Consecutive recordings from the same synaptic terminals are represented with the same color code (orange, purples blue or pink points). Note that these recordings are located in a very specific position inside the cloud of points indicating that the profile of STP is conserved during successive stimulation at 100 Hz of the same synaptic input. (B) Normalized EPSC charges plotted against the stimulus number for responses highlighted in A (same color code). Left panel, synaptic responses from synapses with the same behavior during 100 Hz train are clustered nearby inside the PCA transform. Right panel, synaptic responses from synapses with distinct behaviors during 100 Hz trains are positioned at distant positions in the PCA transform. (C) STP profile was not skewed by changes in PF excitability in minimal stimulation experiments. Potentially, high current values can recruit additional PFs during trains and low current values can be associated with failures of PF excitation. These non-synaptic phenomena can induce unexpected changes in the profile of STP. However, neither charges of EPSC at the first stimuli (blue points), PPR (green points), PC1 (purple point) or PC2 (orange points) could be correlated with stimulus intensities. The lack of valid relationships between these parameters and current intensity indicated that in the vast majority of experiments, STP profile was shaped by synaptic mechanisms rather than change in PF excitability.

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Figure 2—figure supplement 1. Details on Principal Component Analysis and k-Mean clustering parameters of minimal stimulation GC-MLI STP data. ; (A) Principal components 1 and 2 (PC1 and PC2) represent over 58.4% of the total variation of GC-MLI STP dataset. PC1 and PC2 explain the highest source of variability within the dataset (see Materials and methods). Thus, these two variables were used to illustrate different categories of GC-MLI STP behavior over a population of 99 synapses. A negative PC1 eigenvalue is correlated with phasic synapses while synapses displaying tonic glutamate release have a positive PC1 eigenvalue. However, PC2 is correlated to a facilitating glutamate release behavior between EPSC #2 and EPSC #4. (B) We determined the number of GC-MLI STP categories by increasing one-by-one the number of clusters obtained by k-Mean clustering method plotted against total variance for all individual observations. Using the ‘elbow method’, we chose a number of clusters ‘by eye’ above which variance of clustered observations does not increase substantially.

2019

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Figure 2. Identification of 4 classes of MC-MLI synapses using PCA followed by k-means clustering analysis of EPSC properties during high-frequency stimulation. ; (A) PCA transformation of GC-MLI STP profiles. Scatter plot of the first two principal components (PC1, PC2) obtained by analyzing EPSC properties during 100 Hz trains at numerous unitary GC-MLI synapses (n = 96). The first two components explain 69.4% of the total variance of STP. Synapses with negative PC1 values sustain glutamate release during the 10 EPSCs of the burst while PC1 with positive values synapses are depressing synapses. Positive PC2 synapses are depressing synapses while negative PC2 synapses are facilitating during EPSC #2 and EPSC #3. (B) Representative traces of the four classes of inputs (C1 to C4) determined by k-means clustering analysis during ten minimal stimulations of unitary inputs at 100 Hz. The corresponding values of averaged EPSC amplitudes plotted versus the stimulus number and normalized again the vector space model (see method) were displayed on the right panels. (C) Box plots of the charge of EPSC recorded at the first stimulus (left panel) and the paired pulse ratio (PPR) (right panel) according to the four categories of input. EPSC charges: C1 = 198.78 fC±23.46 fC, C2 = 124.96 fC±18.78 fC, C3 = 126.52 fC±22.10 fC, C4 = 74.41 fC±9.48 fC. PPR: C1 = 1.39 ± 0.07, C2 = 1.97 ± 0.19, C3 = 1.98 ± 0.19, C4 = 1.82 ± 0.14. Red bars refer to means and white bars to medians. Multiple comparisons were performed using one-way ANOVAs with Tukey post hoc tests. Only statistically significant differences between categories were shown above box plots (D) Mean values of normalized EPSC amplitudes during 100 Hz train according to the four categories of inputs. The circular diagram represents the relative proportion of each category of input from 96 unitary GC-MLI synapses.

2019

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Figure 2. Intrinsically disordered regions with similar evolutionary signatures can rescue wildtype phenotypes, while those with different evolutionary signatures cannot. ; (A) Multiple sequence alignment of Ste50 IDR (a.a. 152–250), Pex5 IDR (a.a. 77–161), Stp4 (a.a. 144–256), and Rad26 IDR (a.a. 163–239) shows negligible similarity when their primary amino acid sequences are aligned, while evolutionary signatures show that the Pex5 and Stp4 IDRs are more similar to the Ste50 IDR than the Rad26 IDR. While the Ste50 IDR has five consensus phosphorylation sites that are implicated in its function (Hao et al., 2008; Yamamoto et al., 2010; Zarin et al., 2017), the Pex5 IDR and Rad26 IDR have none, and the Stp4 IDR has 4. IDRs are presented in order of increasing Euclidian distance between their evolutionary signatures, though we do not recommend using this measure to quantitate similarity between evolutionary signatures independently (see Discussion). The Ste50 IDR is located between the Sterile Alpha Motif (SAM) and Ras Association (RA) domains in the Ste50 protein. (B) Boxplots show distribution of values corresponding to basal Fus1pr-GFP activity in an S. cerevisiae strain with the wildtype Ste50 IDR compared to strains with the Pex5, Stp4, or Rad26 IDR swapped to replace the Ste50 IDR in the genome. Boxplot boxes represent the 25th-75th percentile of the data, the black line represents the median, and whiskers represent 1.5*the interquartile range. Outliers fall outside the 1.5*interquartile range, and are represented by unfilled circles. Distribution of GFP activity is based on quantification of GFP intensity in single cells pooled from four colonies (which we define as biological replicates) for each strain; sample sizes for each distribution are as follows: WT n = 588 cells, Pex5 IDR n = 196 cells, Stp4 IDR n = 228 cells, Rad26 IDR n = 271 cells. (C) Brightfield micrographs showing each strain from part B following exposure to pheromone. Shmooing cells are those which have elongated cell shape, representing mating projections.

2019

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Figure 3—figure supplement 1. STP profile at compound GC-MLI synapses is not determined by the target cell upon. ; (A) Right, schematic of the experimental design used to probe STP profiles on a single MLI following compound stimulations of GC-MLI synapses. In this example, synaptic responses in a BC were recorded upon stimulations (10 pulses at 100 Hz) of three different clusters of GCs (stimulation in GCL, green symbols) and two different beams of PFs (red symbols). Left, Corresponding compound EPSC responses recorded in the BC following stimulations of the five different locations showed on the schematic. Depending of the location of the stimulation pipette, compound EPSC responses either facilitated or depressed. (B) Mean EPSC responses recorded in BC (triangles) or in SC (circles) following compound stimulations of beams of PFs (pink triangle for BCs, n = 9 and pink circles for SCs, n = 6) or clusters of GC soma (blue triangles for BCs, n = 11 and blue circles for SCs, n = 9).

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Figure 1. Heterogeneous profile of STP at unitary GC-MLI synapses. ; (A) Typical experiment showing the profile of STP during 100 trains at three unitary inputs recruited by local stimulation of PF at two different locations (Z1 to Z3). Figure shows post-hoc reconstruction of a recorded MLI. The left and right dashed lines represent the location of the Purkinje cell layer (PCL) and the pia, respectively. (B) Superimposed traces correspond to EPSCs recorded during trains of 10 stimuli at 100 Hz after minimal stimulation at Z1, Z2 and Z3 locations. Averaged traces from 10 successive stimulations are represented in purple (Z1), green (Z2) and blue (Z3). (C) Corresponding EPSC charges versus stimulus number at Z1, Z2 and Z3 locations.

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Figure 7. The diverse profiles of STP of GC boutons differentially shape the spike output pattern in the target MLI. ; (A) Left panel, schematic representing the design of photostimulation in the granule cell layer. Open circles represent the sites where RuBi-glutamate was uncaged and the blue circles represent the locations where photostimulation elicited responses in the recorded MLI. In this example, 2 GCs localized at distal positions in the granule cell layer contact the recorded MLI. Right panels, representative experiment showing the spike output pattern recorded in loose-patch configuration and EPSCs recording in whole cell configuration in the same MLI following photostimulation of two different locations in the granule cell layer. The white arrowheads and dashed lines represent the onset of photostimulation. Note that the onset of firing is time-locked to the first peak of EPSC charge for photostimulations in location #1 (upper panels) while the onset of firing was more variable for photostimulation in location #2 (lower panels). (B) PCA transformation of the evoked charge time course for 63 unitary contacts (see Materials and methods). The EPSC bursts could be differentiated depending on their tonic or phasic component into three different clusters using k-Means clustering analysis. (C) Representative traces of EPSCs and of the corresponding firing profiles recorded in singles MLI following stimulation of C1’, C2’ and C3’ connections. (D) The delays separating the onset of photostimulation and the time the recorded MLIs were firing at their maximum frequency (referred as delay to frequency peak, recorded in loose-patch configuration) and the delays separating the onset of photostimulation and the time EPSCs are reaching their maximum value (referred as delay to EPSC peak, recorded in voltage-clamp configuration) were measured for 12 GC-MLI synapses for which we were able to correlate the spike output pattern with STP profile (C1’, C2’ or C3’). Upper panel, the bar plot shows that stimulation of C1’ connections led to faster accelerations of MLI firing rate than stimulation of C2’ and C3’ connections. Lower panel, the scatter plot shows a clear correlation between the delay to EPSC peak and the delay to frequency peak recorded. Each experimental point was associated with its STP profile by using the same color code for categories than in the upper graph.

2019

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Figure 7—figure supplement 2. The profile of STP is not determined by the target cell in photostimulation experiments. ; Unitary synaptic responses from three different GCs recruited by photostimulation were recorded on 2 BCs (left and middle graphs) and 1 SC (right graph). MLI subtype and position in the molecular layer were determined by post hoc reconstruction. The corresponding STP profile of each synaptic input was classified using PCA transformation of synaptic responses followed by k-mean clustering analysis. Our results show that either BCs or SCs were contacted by connections belonging to different classes. Photostimulation experiments confirm that the behavioral heterogeneity of excitatory synaptic inputs contacting same MLIs.

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Figure 5. Short-term dynamics of mouse recurrent connections by Cre-line and layer (n in Table 1 ‘STP’). ; (A) Schematic of STP and STP recovery stimuli. (B) Sim1-Cre EPSPs in response to a 50 Hz stimulus train (top; eight induction pulses and four recovery pulses delayed 250 ms; individual connection: gray traces; blue: Sim1-Cre average EPSP at 50 Hz). Exponential deconvolution followed by lowpass filter of EPSPs above (middle, filled circles: pulse amplitudes in C). Exponential deconvolution of 50 Hz stimulus with all five recovery time points in A (bottom, filled circles: pulse amplitudes in C). (C) The mean normalized amplitude of deconvolved response versus pulse number at multiple stimulation frequencies for Sim1-Cre (top). Normalized amplitude of the deconvolved response at 50 Hz with first recovery pulse at each interval for each Cre-line and L2/3 connections (bottom). (D) The depth of depression during 50 Hz induction (left) as measured by the amplitude ratio of the 8th to 1st pulse for each Cre-line and layer (small circles) and grand mean (large circles). Amount of recovery at 250 ms latency (right) for each Cre-line and layer (small circles) and grand mean (large circles). See Figure 5—figure supplement 1 for results of STP at different EGTA concentrations and Figure 1—figure supplement 1 for data analysis diagram.

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Figure 1. Genetic lineage tracing of neck muscle progenitors. ; Whole-mount X-gal stainings of Mef2c-AHFCre;R26R, Islet1Cre;Pax7GPL, Mesp1Cre;Pax7GPL and Pax3Cre;Pax7GPL mice at E10.5 (A–D), E11.75 (E–H) and E18.5 (I–L’) (n = 3 for each condition). See associated Figure 1—supplements 1–3. (A–H) Note labeling of mesodermal core of pharyngeal arches (PAs) and cucullaris anlage (ccl) by Mef2c-AHF, Islet1 and Mesp1 lineage reporters; β-gal+ cells in anterior somites of Mesp1Cre embryos and in the clp anlagen of Islet1Cre embryos. Pax3 lineage marked somitic mesoderm. (I–L’) Mef2c-AHF, Islet1 and Mesp1 lineages marked branchiomeric (mas, tpr, dg) and cucullaris muscles (stm, atp and stp). Pax3Cre and Mesp1Cre labeled somitic epaxial neck muscles (epm). atp, acromiotrapezius; ccl, cucullaris anlage; clp, cutaneous maximus/latissimus dorsi precursor; dg, digastric; epm, epaxial musculature; h, heart; hc, hypoglossal cord; lbm, limb muscle anlagen and limb muscles; ltd, latissimus dorsi; mas, masseter; nc, nasal capsule; nt, neural tube; PA1-2, pharyngeal arches 1–2; S3, somite 3; stm, sternocleidomastoid; stp, spinotrapezius; tpr; temporal. Scale bars: in D for A-D and in H for E-H, 1000 µm; in L for I-L’, 2000 µm.

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Figure 1—figure supplement 1. Potentiation of reverse propagation in 1-D recurrent network with accumulation of afterdepolarization (ADP). ; In this simulation, we show that ADP can generate direction-selective synaptic potentiation similar to those for STP. Here, Hebbian plasticity is modulated by ADP, but not by STP (Experimental Procedure). (A) Weight modifications were induced by a firing sequence in a 1-D recurrent network (at time 0 s), and the effects of these changes on sequence propagation were examined at time 3 s. Recurrent synaptic weights were modified by the revised Hebbian plasticity rule in which the contribution of postsynaptic activities were determined by ADP accumulated through time. (B) Weights of outgoing synapses from neuron #250 to other neurons are shown at time 0 s (black) and 3 s (red) of the simulations in (A) (top). Lower panels show the weight changes (blue). (C) Neural activity and accumulated effects of ADP are shown at 300 ms of the simulation in (A).

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Figure 3—figure supplement 2. STP is not determined by the position of MLI in the molecular layer or by the position of inputs in MLI dendritic trees. ; (A) Left panel, schematic showing how the relative depth of cell’s soma in the molecular layer was measured. Right panels, scatter plots showing the lack of correlation between PC1 or PC2 with the relative depth of cell’s soma for all recorded MLIs. (B) Left panel, schematic showing how the relative depth of stimulated inputs in the molecular layer was measured. Right panels, scatter plots showing the lack of correlation between PC1 or PC2 with the relative depth of inputs. (C) Left panel, schematic showing how the distance of stimulated inputs from MLI soma was measured. Right panels, scatter plots showing the lack of correlation between PC1 with distance of stimulated inputs from the soma.

2019

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Figure 11. New signaling proteins that are developmentally regulated in M. xanthus identified in this study. ; Code used to distinguish among types of regulators is indicated in the upper part, where OCS indicates one-component systems; HK, histidine kinase: hyHK, hybrid histidine kinase; CheY, CheY-likeresponse regulator; RR, response regulator; ECF, ECF sigma factor; STPK, active Ser/Thr protein kinase; PseudoK, pseudokinase. Numbers inside each symbol indicate the number of each type of regulator that have not been previously identified as being developmentally regulated. Information about proteins depicted here is shown in Figure 11—source data 1.

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Figure 8. Synapse-specific expression of Syn II diversifies the profile of excitatory drives on MLIs and expands the coding range of MLIs. ; (A) Left panels, representative traces of superimposed EPSCs recorded in WT and Syn II KO mice after photostimulations in the GCL (same experimental design than in Figure 7A). Right panel, averaged values of EPSC charges versus the time following photorelease of RuBi-glutamate recorded in WT and Syn II KO mice (black and red traces respectively). Note the strong reduction in the peak of charge in Syn II KO mice. (B) PCA transformation of EPSC properties obtained in WT (green, purple and blue points, same dataset than in Figure 7B) and Syn II KO mice (red points). (C) Line plots display the normalized release time course from GC-MLI synapses belonging to clusters C1’, C2’, C3’ (WT mice, same color code as in B) and GC-MLI synapses from Syn II KO mice (red line). (D) The pie chart shows a partial reduction of STP heterogeneity in Syn II KO condition with a strong reduction of phasic profiles (C1’). (E) Typical raster plots and peristimulus time histogram obtained in WT and Syn II KO mice following photostimulation of unitary GC-MLI synapses. The onsets of photostimulation are represented with white arrowheads and dashed lines. (F) Means values of the firing frequency (upper graph) and the firing probability (lower graph) of MLIs following photostimulation of unitary GC-MLI synapses in WT and Syn II KO mice (black and red lines, respectively).

2019

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Figure 3. The profile of STP is not determined by the target cell. ; (A) Post-hoc reconstruction of 2 recorded MLI using a two-photon microscope. SCs were identified by the absence of neuronal process reaching the PCL (left MLI) and by the absence of cut processes (transection of neuronal processes could be clearly identified by swelling at the tip end portion of processes). At the opposite, BCs were identified by the presence of processes entering in the PCL (right MLI). (B) Circular diagrams of the relative proportion of each category of input (determined by k-means clustering analysis during ten minimal stimulation of GC unitary inputs at 100 Hz) contacting BCs and SCs.

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Figure 6. Modeling of short-term depression in recurrent Rorb, Sim1, and Tlx3 connections (n in Table 1 ‘STP’). ; (A) Sim1 average dynamic response; Same data as in Figure 5C, top plotted on a log-X time scale with modeling fits overlaid. (B) Results of model for parameters P0 and 𝜏r0. Values are means with standard error of the covariance matrix. Paired Z-scores (Equation 6) in Table 5.

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Figure 4—figure supplement 2. Prx1 lineage contribution to neck and limbs. ; (A–C) Immunostainings on coronal cryosections (n = 2). Note Prx1-derived cells contributing to a great extent to form MCT, tendons and skeletal components of limb and shoulder (A–B); less β-gal+ cells are seen in acromiotrapezius (B); no contribution in neck epaxial muscles (C). (D–D”) Some Prx1-derived cells contribute to MCT fibroblasts of spinotrapezius, but not to myofibres. acp, scapular acromion process; atp, acromiotrapezius; ccl, cucullaris; epm, epaxial neck musculature; lbm; limb muscles; scp, scapular musculature; stp, spinotrapezius; uln, ulna. Scale bars: in C for A-C 200 µm, for D’ for D-D’ 50 µm.

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Figure 1—figure supplement 1. Ontogenetic analysis of Myf5 muscle progenitors at the head-trunk interface. ; (A–F’) Temporal X-gal stainings of Myf5Cre;Pax7GPL embryos (n = 2–4 each condition). (G–G’’) Immunostaining for GFP and Tuj1 in E10.5 Myf5Cre;R26mTmG embryo (n = 2). Ventral 3D projection of cranial region (G) and two sections 60 µm apart (dorso-ventral direction) in region indicated in (G) are shown. The cucullaris is innervated by the accessory nerve XI. V, trigeminal nerve; VII, facial nerve; IX, glossopharyngeal nerve; X, vagal nerve; XI, accessory nerve; XII, hypoglossal nerve; atp, acromiotrapezius; ccl, cucullaris anlage; clp, cutaneous maximus/latissimus dorsi precursor; dg, digastric muscles; epm, epaxial neck musculature; fmp, facial muscle precursors; h, heart; hc, hypoglossal cord; ifh, infrahyoid muscles; lb, limb bud; lbm, limb muscle anlagen and limb muscles; ltd, latissimus dorsi; lvs, levator scapula; mas, masseter; mmp, masticatory muscle precursor; nlb, nasolabialis muscles; oca, occipito/cervico-auricularis anlagen and muscles; PA1-6, pharyngeal arches 1–6; ptm, pectoralis muscles; S3-S4, somites 3–4; stm, sternocleidomastoid; stp, spinotrapezius; tgp, tongue primordia; tpr; temporal. Scale bars: in A-E’, 1000 µm; in F-F’, 2000 µm, in G for G, 400 µm for G-G’, 200 µm.

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Figure 2. Potentiation of reverse propagation in 1-D recurrent network of spiking neurons. ; (A, C) Simulations similar to those shown in Figure 1 were performed in a 1-D spiking neural network. Recurrent synaptic weights were changed by symmetric STDP. In (A) the plasticity rules were not modulated by STP whereas in (C) the rules were modulated. (B, D) The weights of outgoing synapses from neuron #250 (top) are shown at time 0 s (black) and 3 s (red) of the simulation settings shown in (A) and (C), respectively. Lower panels display the weight changes (blue).

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Figure 1. Potentiation of reverse propagation in 1-D recurrent network of rate neurons. ; (A, C) Weight modifications were induced by a firing sequence in a 1-D recurrent network (at time 0 s), and the effects of these changes on sequence propagation were examined at time 3 s. Recurrent synaptic weights were modified by the standard Hebbian plasticity rule (A) or the revised Hebbian plasticity rule, where the latter was modulated by STP. (B, D) Weights of outgoing synapses from neuron #250 to other neurons are shown at time 0 s (black) and 3 s (red) of the simulations in (A) and (C), respectively (top). Lower panels show the weight changes (blue). (E) Neural activity, presynaptic outputs (top) and the amount of neurotransmitters at presynaptic terminals (bottom) are shown at 300 ms of the simulation in (C). (F) Activity packet traveling on the 1-D recurrent network and the resultant weight changes by the revised Hebbian plasticity rule are schematically illustrated. (G) Distributions of synaptic weights are schematically shown before and after a sequence propagation.

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