Fundamentación conceptual del ambiente de aprendizaje

Data analysis was performed using MATLAB (The Mathworks, Aachen, Germany, program version: 7.8.0.347 (R2009a)). Graphs were layouted using Prism (Graph Pad Software, La Jolla, USA, program version: 5.03).

2.2.7.1 Semi-automatic mEPSC detection

The available tools for mEPSC detection and analysis (e.g. the template search in the Clamp- fit program (Axon Instruments)) were inconvenient to use, prone to user errors and detected many false positive events. Therefore, a MATLAB-based analysis tool for semi-automated mEPSC detection and analysis was developed. mEPSCs were detected by analyzing on- set slope(differential), amplitude threshold, and mEPSC decay kinetics to identify potential

mEPSC events. All events were manually evaluated (accept/reject) by the user to enable complete control of the analysis process. Statistical analysis of event properties is imple- mented in MATLAB and does not require the error-prone manual transfer of the aquired data to other programs for analysis.

Subsequent to mEPSC evaluation, the time between individual events (interevent in- terval), the amplitudes of the individual events, the decay constant and other mEPSC pa- rameters are statistically analyzed and plotted as cumulative histograms. Histograms of all cells of the same conditions were averaged and data are reported as mean and SEM, which are also presented as error bars in the figures. Distributions of different datasets are tested for difference using the Kolmogorov-Smirnov significance test.

2.2.7.2 Synaptic plasticity

Manual analysis of plasticity experiments is inflexible to modification of the analysis criteria (e.g. changing bin size), very monotonous (which make it prone to user errors), and can never be as objective as a routine with clearly defined analysis parameters. Hence, a MATLAB based program was developed to ensure maximum precision and complete user control in analysis of long-term plasticity experiments.

This ”PlasticityAnalysis” tool determines the slope of the dendritic field between 20 and 80% of the maximum field amlitude. The slopes can be binned over time and the time- course of all individual experiments is plotted. All recordings of one experimental condition are subsequently averaged, and data are reported as mean and SEM, which are also presented as error bars in the figures. Differences between experimental conditions were analyzed by comparing the means at 55-60 min after the induction of plasticity between experimental conditions.

3.1 SynCAM1 and SynCAM2 overexpression induces excitatory

synapse formation in neuronal cultures

SynCAM family proteins have been known to induce the formation of functional presynap- tic specializations in co-culture systems (Biederer et al., 2002). Whether SynCAM family members would only exert this effect in heterologous systems or also induce the formation of functional synaptic contacts in neurons remained elusive. To elucidate the role of Syn- CAMs in interneuronal contact formation, SynCAM1 and SynCAM2 were overexpressed in dissociated hippocampal neurons using a Semliki Forest virus expression system.

Based on previous findings, it was hypothesized that SynCAM overexpressing neurons could form more synaptic contacts. Postsynaptic neurons overexpressing SynCAM proteins would therefore receive more synaptic inputs than non-overexpressing control neurons. Ex- perimentally, the number of functional synapses onto a cell can be analyzed by recording miniature postsynaptic currents. This approach exploits the fact that functional synapses exhibit action potential independent vesicle release. At glutamatergic synapses, the trans- mitter elicits miniature excitatory postsynaptic currents (mEPSCs), which can be measured by whole cell recordings. The frequency of mEPSC events is a measure for the number of synapses onto the respective neuron.

Dissociated hippocampal neurons were transfected with SynCAM1 or SynCAM2 using a Semliki Forest virus. All transfected cells coexpressed soluble GFP with control neurons only expressing GFP. mEPSCs of GFP positive neurons were recorded 12-24 h post infection. mEPSC recordings from SynCAM1 and SynCAM2 overexpressing neurons revealed significant increases in mEPSC frequencies compared to control neurons that only expressed GFP (GFP controls n=15, 0.10 ± 0.02 Hz; SynCAM1 n=11, 0.21 ± 0.04 Hz; SynCAM2

0 10 20 30

mean amplitude (pA)

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mEPSC amplitude (pA)

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mEPSC interevent interval (s)

fraction of events 0 0.1 0.2 0.3 0.4 0.5 mean frequency (Hz) GFP control SynCAM1 SynCAM2 1s 10 pA

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a

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Figure 3.1: a, Representative whole cell recordings of mEPSCs from dissociated hippocampal neurons at 8-10 DIV. Neurons overexpressed GFP as a control (black; n=15 cells), SynCAM1 (purple; n=11 cells), or SynCAM2 (green; n=9 cells). Legend and color scheme in panel (a) also apply to (b) and (c). b, Cumulative distribution of mEPSC interevent intervals. The bar graph inset depicts mean mEPSC frequencies. c, Cumulative distribution of mEPSC amplitudes. The bar graph inset depicts mean mEPSC amplitudes. Experimental design, experiments and analyses by AK.

n=9, 0.3 ± 0.11 Hz; Kolmogorov-Smirnov p < 0.005 for SynCAM1 vs. GFP control, and p < 0.001 for SynCAM2 vs. GFP control). This result confirms the hypothethis that SynCAM1 and SynCAM2 induce excitatory synapse formation in neurons. In contrast to mEPSC frequency, mEPSC amplitude is a measure of receptor density (Raghavachari and Lisman, 2004). Overexpression of SynCAM1 and SynCAM2, caused an increase in mEPSC amplitude (GFP controls n=15, 12±1.2 pA; SynCAM1 n=11, 14±1.0 pA; SynCAM2 n=9, 21 ±3.4 pA; Kolmogorov-Smirnov p< 0.01 for SynCAM1 vs. GFP control, and p<0.005 for SynCAM2 vs. GFP control), suggesting a higher receptor density. However, the effect on mEPSC amplitude did not occur upon overexpression of SynCAM1flagin the intact brain (Fig. 3.4) and might be specific for cultured neurons. Taken together, these results confirm

the hypothesis that SynCAM1 and SynCAM2 overexpression in neurons induces excitatory synapse formation.