We simulated 6 patterns with Poisson noise surrounding the pattern on the left and right. The onset of the pattern (i.e., Δtw) was randomly assigned between 0 and 0.8 with a window length of Tw = 0.2s for the patterns. The analysis window used here is 1 s, i.e. the entire period. SpikeShip correctly detects the 6 different patterns, but also SpikeShip can decompose the spike patterns to make it invariant to changes in global shifts. VP distance drastically depends on the global shift applied to the spikes. SpikeShip can retrieve the global shift from the spike sequences and reconstruct the random global shifts applied to the spike trains. (PDF)</p
Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional n...
A) Pairwise comparison of epochs and clustering performance of metrics (one session). Top: Dissimila...
(A) Multiple bimodal activation patterns and examples of realizations for each pattern (N = 50 neuro...
Two different temporal patterns with different firing rates. Each temporal pattern can occur in a lo...
A) Example of single spike trains for two epochs for 10 neurons. Patterns were generated as uniform ...
Simulations of spike trains with same number of spikes (i.e., n = 20). Top: Comparison of distances ...
A) Example of two epochs with spike times tk = (10, 10, 10, 10, 10, 10) and tm = (25, 40, 45, 55, 60...
A) Global scaling. Same simulations as in S8 Fig. Victor-Purpura distance (VP) was used with differe...
A) Sensitivity to spike timing and spike count for different measures for an example of three synthe...
Two different temporal patterns with different firing rates. Each temporal pattern could occur in on...
A) Global scaling. SPIKE and RI-SPIKE computations for globally scaled sequences. Top: dissimilarity...
In order to detect significant spatio-temporal spike patterns (STPs) at ms-precision, we developed t...
(Top) Example of two epochs with spike times for two active neurons N0 and N1 (i.e., Akm = 2): tk = ...
We designed the statistical method SPADE [1,2,3] to detect ms-precise significant spatio-temporal sp...
(A) Each pattern has a length of 300 samples, and is embedded in a larger window starting from -300 ...
Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional n...
A) Pairwise comparison of epochs and clustering performance of metrics (one session). Top: Dissimila...
(A) Multiple bimodal activation patterns and examples of realizations for each pattern (N = 50 neuro...
Two different temporal patterns with different firing rates. Each temporal pattern can occur in a lo...
A) Example of single spike trains for two epochs for 10 neurons. Patterns were generated as uniform ...
Simulations of spike trains with same number of spikes (i.e., n = 20). Top: Comparison of distances ...
A) Example of two epochs with spike times tk = (10, 10, 10, 10, 10, 10) and tm = (25, 40, 45, 55, 60...
A) Global scaling. Same simulations as in S8 Fig. Victor-Purpura distance (VP) was used with differe...
A) Sensitivity to spike timing and spike count for different measures for an example of three synthe...
Two different temporal patterns with different firing rates. Each temporal pattern could occur in on...
A) Global scaling. SPIKE and RI-SPIKE computations for globally scaled sequences. Top: dissimilarity...
In order to detect significant spatio-temporal spike patterns (STPs) at ms-precision, we developed t...
(Top) Example of two epochs with spike times for two active neurons N0 and N1 (i.e., Akm = 2): tk = ...
We designed the statistical method SPADE [1,2,3] to detect ms-precise significant spatio-temporal sp...
(A) Each pattern has a length of 300 samples, and is embedded in a larger window starting from -300 ...
Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional n...
A) Pairwise comparison of epochs and clustering performance of metrics (one session). Top: Dissimila...
(A) Multiple bimodal activation patterns and examples of realizations for each pattern (N = 50 neuro...