The influence of emotion on temporal context models

ABSTRACT

Temporal context models (TCMs) have been influential in understanding episodic memory and its neural underpinnings. Recently, TCMs have been extended to explain emotional memory effects, one of the most clinically important findings in the field of memory research. This review covers recent advances in hypotheses for the neural representation of spatiotemporal context through the lens of TCMs, including their ability to explain the influence of emotion on episodic and temporal memory. In recent years, simplifying assumptions of “classical” TCMs – with exponential trace decay and the mechanism by which temporal context is recovered – have become increasingly clear. The review also outlines how recent advances could be incorporated into a future TCM, beyond classical assumptions, to integrate emotional modulation.

KEYWORDS:

• Temporal context
• free recall
• computational modelling
• temporal memory
• episodic memory

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 This is because Hebbian learning implies that the weight matrix is symmetric. Symmetric matrices have orthogonal eigenvectors.

2 To find the time horizon defined by $\rho$, set ${\rho }^t=e^{-\mathrm{st}}$. We find that the rate constant of the exponential decay $s=-\log \rho$, so the time constant goes like $\tau =1/s=(-\log \rho {)}^{-1}$.

Additional information

Funding

The funding was from National Institutes of Health R01MH132171 to Marc W. Howard.