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The solver is based on the Spike framework, applying Givens rotations and QR factorization without pivoting.
Based on the spike rate, ictal, inter-ictal, and pre-ictal states can be identified through comparison with a certain threshold.
According to the review studies, the methods are classified into different categories based on the spike detection criterion, while many approaches use a combination of methods in a multi-stage framework.
Some studies have categorized extracellularly recorded neurons into pyramidal and interneurons based on the spike shape [21], [22], [23], [24], [25].
In this paper we examine methods for categorical classification of discrete stimuli or episodic events based on the spike series responses they induce in a population of neurons.
Then, for multi-session epochs in which these parameters were stable, we evaluated the stability of the stimulus selectivity by computing two standard indices, depth of selectivity [32] and sparseness[33], based on the spike rates across stimuli (see Supplementary Methods S1).
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A detailed analysis for selected targets comparing this normalization strategy with the one recommended by Luminex™ (based on the spike-in controls) showed that for individual microRNAs expression patterns depend on the normalization strategy.
Fig. 3 (A) ( b, I ) -parameter sweep of the Hindmarsh-Rose model based on the spike-counting approach.
Its architecture is based on the spiking winner-take-all (WTA): There are lateral excitatory connections between the WTAs and lateral inhibitory connections between the neurons of a WTA.
Location and trial type were estimated based on the spiking activity (bottom, spike raster) enclosed by the red lines in the replay.
Pyramidal neurons were identified by their morphological appearance and based on the spiking profile in response to step depolarizations (Fig. 1 A1 ).
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CEO of Professional Science Editing for Scientists @ prosciediting.com