Studies of amnesic patients and animal models support a systems consolidation model, which posits that explicit memories formed in hippocampus are transferred to cortex over time 1-6 . Prelimbic cortex (PL), a subregion of the medial prefrontal cortex, is required for the expression of learned fear memories from hours after learning until weeks later 7-12 . While some studies suggested that prefrontal cortical neurons active during learning are required for memory retrieval 13-15 , others provided evidence for ongoing cortical circuit reorganization during memory consolidation 10,16,17 . It has been difficult to causally relate the activity of cortical neurons during learning or recent memory retrieval to their function in remote memory, in part due to a lack of tools 18 . Here we show that a new version of 'targeted recombination in active populations', TRAP2, has enhanced efficiency over the past version, providing brain-wide access to neurons activated by a particular experience. Using TRAP2, we accessed PL neurons activated during fear conditioning or 1-, 7-, or 14-day memory retrieval, and assessed their contributions to 28-day remote memory. We found that PL neurons TRAPed at later retrieval times were more likely to be reactivated during remote memory retrieval, and more effectively promoted remote memory retrieval. Furthermore, reducing PL activity during learning blunted the ability of TRAPed PL neurons to promote remote memory retrieval. Finally, a series of whole-brain analyses identified a set of cortical regions that were densely innervated by memory-TRAPed PL neurons and preferentially activated by PL neurons TRAPed during 14-day retrieval, and whose activity co-varied with PL and correlated with memory specificity. These findings support a model in which PL ensembles underlying remote memory undergo dynamic changes during the first two weeks after learning, which manifest as increased functional recruitment of cortical targets.Targeted recombination in active populations (TRAP) allows permanent genetic access to neurons activated by a specific experience 19 . The TRAP system uses an immediate early gene locus to drive the expression of tamoxifen-inducible CreER, along with a transgenic or virally-delivered Cre-dependent effector. When a neuron is active in the presence of tamoxifen, CreER can enter the nucleus to catalyze recombination, resulting in permanent expression of the effector (Fig. 1a). Because the original FosTRAP (TRAP1) disrupts endogenous Fos 19 and does not efficiently access many brain regions, we developed a new mouse line, TRAP2 20 , that preserves endogenous Fos, including the highly conserved first intron 21 and the 3' untranslated region critical for mRNA destabilization 22 (Fig. 1b; Extended Data Fig. 1). Further, we replaced the original Cre with a codon-optimized iCre for improved expression 23 .To characterize TRAP2, we first determined the time course of TRAPing and sensitivity of TRAP2 using the tdTomato Cre reporter Ai14 24 . We dark adapted TRAP1;Ai14 and TRAP2;Ai14 dou...

No abstract

Many efforts targeting amyloid-β (Aβ) plaques for the treatment of Alzheimer's Disease thus far have resulted in failures during clinical trials. Regional and temporal heterogeneity of efficacy and dependence on plaque maturity may have contributed to these disappointing outcomes. In this study, we mapped the regional and temporal specificity of various anti-Aβ treatments through high-resolution light-sheet imaging of electrophoretically cleared brains. We assessed the effect on amyloid plaque formation and growth in Thy1-APP/PS1 mice subjected to β-secretase inhibitors, polythiophenes, or anti-Aβ antibodies. Each treatment showed unique spatiotemporal Aβ clearance, with polythiophenes emerging as a potent anti-Aβ compound. Furthermore, aligning with a spatial-transcriptomic atlas revealed transcripts that correlate with the efficacy of each Aβ therapy. As observed in this study, there is a striking dependence of specific treatments on the location and maturity of Aβ plaques. This may also contribute to the clinical trial failures of Aβ-therapies, suggesting that combinatorial regimens may be significantly more effective in clearing amyloid deposition.

Can we construct a model of brain function that enables an understanding of whole-brain circuit mechanisms underlying neurological disease and use it to predict the outcome of therapeutic interventions? How are pathologies in neurological disease, some of which are observed to have spatial spreading mechanisms, associated with circuits and brain function? In this review, we discuss approaches that have been used to date and future directions that can be explored to answer these questions. By combining optogenetic functional magnetic resonance imaging (fMRI) with computational modeling, cell type–specific, large-scale brain circuit function and dysfunction are beginning to be quantitatively parameterized. We envision that these developments will pave the path for future therapeutics developments based on a systems engineering approach aimed at directly restoring brain function.

No abstract