02094nas a2200169   4500008004100000022001400041245008200055210006900137260000800206300001200214490000700226520151500233100002001748700002101768700002301789856011201812       2024                        eng d  a1072-050200aNetwork motifs exhibiting a differential response to spaced and massed inputs0 aNetwork motifs exhibiting a differential response to spaced and   cJUL  aa0540120 v313 a<p>
	One characteristic of long-term memory is the existence of an inverted U-shaped response to increasing intervals between training sessions, and consequently, an optimal spacing that maximizes memory formation. Current models of this spacing effect focus on specific molecular components and their interactions. Here, we computationally study the underlying network architecture, in particular, the potential of motif dynamics in qualitatively capturing the spacing effect in a manner that is independent of the animal model, biomolecular components, and the timescales involved. We define a common training and test protocol, and computationally identify network topologies that can qualitatively replicate the experimentally observed characteristics of the spacing effect. For 41 motifs derived from fundamental network architectures such as autoregulation, feedback, and feedforward motifs, we tested their capacity to manifest the spacing effect in terms of an inverted U-shaped response curve, using different combinations of stimulation protocols, response metrics, and kinetic parameters. Our findings indicate that positive feedback motifs where the stimulus enhances conversion reaction in the loop replicate the spacing effect across all response metrics, while feedforward motifs exhibit a metric-specific spacing effect. For some parameter combinations, linear cascades of activation and conversion reactions were found sufficient to qualitatively exhibit spacing effect characteristics.</p>
1 aSreejan, Ashley1 aSaxena, Priyanka1 aGadgil, Chetan, J.  uhttps://library.ncl.res.in/content/network-motifs-exhibiting-differential-response-spaced-and-massed-inputs