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ZDB-FIG-210209-2

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Triplett et al., 2020 - Model-based decoupling of evoked and spontaneous neural activity in calcium imaging data

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Fig. 2

Fig 2. Overview of the CILVA approach for decoupling stimulus-evoked responses and latent sources of SA. (A) Proposed generative architecture underlying multivariate calcium imaging data. Neurons are driven by sensory stimuli (red) and latent sources of SA (blue). These two sources are combined additively to define the underlying rate of calcium influx (λn), before being convolved with a GCaMP kernel. Calcium levels are subsequently reported through noisy fluorescence intensities. (B) The intensity of calcium influx λn encoding stimuli and shared SA is convolved with a GCaMP kernel k to generate observed calcium levels. (C) The learned encoding model provides a method for decoupling evoked responses from common patterns of SA.

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