Search bioRxiv⌕ Search

bioRxiv · 10.1101/2021.07.15.452391

Tuned to Learn: An anticipatory hippocampal convergence state conducive to memory formation revealed during midbrain activation

Abstract

The hippocampus has been a focus of memory research since H.Ms surgery in 1953 abolished his ability to form new memories, yet its mechanistic role in memory is still debated. Here, we identify a novel, systems-level candidate memory mechanism: an anticipatory hippocampal "convergence state", observed while awaiting valuable information, that both predicts later memory, and accounts for the relationship between midbrain activation and enhanced learning. To reveal this state, we leveraged endogenous neuromodulation associated with motivation: During fMRI, participants viewed trivia questions eliciting high or low curiosity, each followed seconds later by its answer. We reasoned that memory encoding success requires a convergence of factors, and as such, hippocampal states associated with remembered trials would be less variable than forgotten ones. Using a novel multivariate approach, we measured convergence by quantifying the typicality of spatially distributed patterns. We found that during anticipation of trivia answers, hippocampal states showed greater convergence under high than low curiosity. Crucially, convergence in the hippocampus increased with greater midbrain activation and uniquely accounted for the association between midbrain activation and subsequent memory recall. We propose that this novel convergence state in the hippocampus reflects a mechanism of its contribution to long term memory formation and that engagement of this convergence state completes the cascade from motivation to midbrain activity to memory enhancement.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Poh, J.-H., Vu, M.-A. T., Stanek, J. K., Hsiung, A., Egner, T., Adcock, R. A.. 2021-07-15. Tuned to Learn: An anticipatory hippocampal convergence state conducive to memory formation revealed during midbrain activation. https://doi.org/10.1101/2021.07.15.452391

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Complex Spatial and Temporal Organization of Functional Brain Networks

Recent research exploring brain-behavior associations has relied on the language of complex systems to understand how stable behavioral individual differences emerge from brain function. At the same time, advances in neuroimaging have provided greater insight into both the topological and temporal properties of macroscale cortical networks. These new approaches offer a potential avenue for understanding how functional activity in the brain might behave in a manner that aligns with complex-systems interpretations of psychological traits. The present study used resting-state data from the Human Connectome project (N = 994) to explore associations between the spatial and temporal features of functional brain networks. Using an adaptive frequency approach to explore brain function at different timescales together with a family of methods from complex systems theory, we identified patterns of brain state organization reflecting a state-trait continuum, with more stable trait-like dynamics and greater functional coupling between networks in lower frequency oscillations. Additionally, we found evidence of greater coupling across timescales in brain networks associated with higher-order cognition. This research supports interpretations of brain organization as a spatiotemporal hierarchy and provides future avenues for exploring brain-behavior associations from a complex system perspective.

neuroscience↗

A Mechanistic Account of Dedifferentiation in the Aging Visual System

To uncover the mechanisms of age-related dedifferentiation, we simulated neural degradation in a computational model of the ventral visual stream. Severing connections or adding noise, whether in inferotemporal cortex (IT) or upstream, reduced IT differentiation, indicating that dedifferentiation need not originate locally. Degrading peripheral V1, which preferentially drove place-selective IT neurons, selectively reduced place differentiation, a candidate mechanism for the stronger place dedifferentiation reported in aging.

neuroscience↗

Reusing pipettes in Patch-seq: a foundation for automated multimodal profiling

Patch-seq is a technique for single-cell multimodal characterization. It combines whole-cell electrophysiology, single-cell transcriptomics, and morphological reconstruction in single neurons. Patch-seq morphologies are a critical bridge among cell types, genes, physiology, and large-scale connectivity platforms such as EM connectomes and single-cell-resolution projectomes. However, patch-seq experimental complexity and operator dependence limit throughput. Automation could enable scalable Patch-seq but requires procedural adaptations, including detergent-based pipette cleaning, robotic nucleus extraction and collection. The impact of these automations on Patch-seq quality has not been systematically evaluated. Here, we show that each of these modifications preserves or improves key Patch-seq outcomes. Automated nucleus extraction performs comparably to, or better than, expert manual operation, preserving key RNA and morphological metrics. Detergent-cleaned, reused pipettes supported a viable sealing success rate across multiple cleaning cycles and preserved electrophysiological quality and transcriptomic yield without introducing excess contamination. Sonication effectively allows collection of nuclear material without damaging RNA and supports subsequent pipette cleaning and reuse. Enhanced automated sealing and break-in procedures increased throughput regardless of brain region, cell type or species. Together, these results validate the core procedural adaptations required for automated Patch-seq and establish a foundation for high-throughput, standardized multimodal single-cell characterization.

neuroscience↗