Theoretical and experimental studies are piecing together how the brain creates a temporal context for ordering memories — a kind of trailing timeline that gets blurrier for events receding into the past. quanta 
A second can last forever. Days can vanish. It’s this coding by parsing episodes that makes a very neat explanation for the way we see time. We’re processing things that happen in sequences, and what happens in those sequences can determine the subjective estimate for how much time passes.
That timeline could be of use not just to episodic memory in the hippocampus, but to working memory in the prefrontal cortex and conditioning responses in the striatum.
As sensory neurons fire in response to an unfolding event, the brain maps the temporal component of that activity to some intermediate representation of the experience — a Laplace transform, in mathematical terms. That representation allows the brain to preserve information about the event as a function of some variable it can encode rather than as a function of time (which it can’t).
The brain can then map the intermediate representation back into other activity for a temporal experience — an inverse Laplace transform — to reconstruct a compressed record of what happened when.
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The researchers suggest Laplace transform creates an intermediate representation of experience. A transformation of experience seems likely but Laplace? Let me refresh my memory.
YOUTUBE n2y7n6jw5d0 Published Nov 3, 2019.
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Boston University Psychological & Brain Sciences, Theoretical Cognitive Neuroscience Lab. site
A growing body of neural data suggests that neural representations in several
brain regions have qualitative properties predicted by the representation of temporal history. Taken
together, these results suggest that a scale-invariant representation of temporal history may serve as a
cornerstone of a physical model of cognition in learning and memory. pdf
We propose a principled way to construct an internal representation of the temporal stimulus history leading up to the present moment. A set of leaky integrators performs a Laplace transform on the stimulus function, and a linear operator approximates the inversion of the Laplace transform. pdf