(A) Example of a timeseries. Dashed lines represent sampling timepoints. Sampling was performed during the perturbation (t1 = green, t2 = yellow, t3 = blue and t4 = grey) and at equilibrium (t5 = dark blue). Alternatively, sampling was performed randomly between t = 100 and t = 1000 (random = pink). (B) Results (F1-scores) of network inference for sampling at various timepoints. After a perturbation all species grow back to their original equilibrium. The bars of the boxplots indicate the variability outside the middle 50% (i.e., the lower 25% of scores and the upper 25% of scores). Dashed lines represent median results of sampling during equilibrium.</p
<p>Scatter plots of population hit rate and response time in the first versus last segment of trials...
<p>(A) Network response (PSTH) for identical stimulation of 30 different subpopulations of 250 neuro...
<p>Analysis on simulated spike data of 40 neurons. <b>A</b> Top: Simultaneous spiking activity of 40...
For the different scenario’s we show the precision, recall and the F1-score. (A) The base case model...
We study the dynamics of on-line learning with time-correlated patterns. In this, we make a distinct...
<p>Part A depicts how the PER mRNA population count grows approximately linearly when observed over ...
<p>A: Examples of distributions for which the variability is mostly along the diagonal direction (bl...
<p>In this experiment, a 90° grating on a screen was presented to the monkey for 2s (light gray shad...
<p>(A) ANN model sketch. Connectivity parameters can shape the dynamical regime of the network. (B) ...
<p>A, Percentages of neurons that showed significant main effect of schedule level and reward amount...
<p>Each neuron in population receives randomly drawn excitatory inputs with weight , randomly dra...
The panels show the time course of average population performance over the last 100 generations of s...
<p>A) The power law exponent <i>λ</i> was estimated during network evolution for a sliding time-wind...
<p><b>A:</b> The number of unique complexes in independent simulations as a function of time: each c...
<p>(A) Response kernels of input neurons to external events (left) and cross-correlation among input...
<p>Scatter plots of population hit rate and response time in the first versus last segment of trials...
<p>(A) Network response (PSTH) for identical stimulation of 30 different subpopulations of 250 neuro...
<p>Analysis on simulated spike data of 40 neurons. <b>A</b> Top: Simultaneous spiking activity of 40...
For the different scenario’s we show the precision, recall and the F1-score. (A) The base case model...
We study the dynamics of on-line learning with time-correlated patterns. In this, we make a distinct...
<p>Part A depicts how the PER mRNA population count grows approximately linearly when observed over ...
<p>A: Examples of distributions for which the variability is mostly along the diagonal direction (bl...
<p>In this experiment, a 90° grating on a screen was presented to the monkey for 2s (light gray shad...
<p>(A) ANN model sketch. Connectivity parameters can shape the dynamical regime of the network. (B) ...
<p>A, Percentages of neurons that showed significant main effect of schedule level and reward amount...
<p>Each neuron in population receives randomly drawn excitatory inputs with weight , randomly dra...
The panels show the time course of average population performance over the last 100 generations of s...
<p>A) The power law exponent <i>λ</i> was estimated during network evolution for a sliding time-wind...
<p><b>A:</b> The number of unique complexes in independent simulations as a function of time: each c...
<p>(A) Response kernels of input neurons to external events (left) and cross-correlation among input...
<p>Scatter plots of population hit rate and response time in the first versus last segment of trials...
<p>(A) Network response (PSTH) for identical stimulation of 30 different subpopulations of 250 neuro...
<p>Analysis on simulated spike data of 40 neurons. <b>A</b> Top: Simultaneous spiking activity of 40...