Search bioRxivSearch

bioRxiv · 10.1101/188839

Cholecystokinin release triggered by presynaptic NMDA receptors produces LTP and sound-sound associative memory formation

Abstract

Memory is stored in neural networks via changes in synaptic strength mediated in part by NMDA-dependent long-term potentiation (LTP). There is evidence that entorhinal cortex enables neocortical neuroplasticity through cholecystokinin (CCK)-containing neocortical projections. Here we show that a CCKB antagonist blocks high-frequency stimulation (HFS)-induced LTP in the auditory cortex, whereas local infusion of CCK induces LTP. CCK-/- mice lacked neocortical LTP and showed deficits in a cue-cue associative learning paradigm; administration of CCK rescued associative learning. HFS of CCK-containing entorhino-neocortical projection neurons in anesthetized mice enabled cue-cue associative learning. Furthermore, when one cue was pre-conditioned to footshock, the mouse showed a freezing response to the other cue, indicating that the mice had formed an association. HFS-induced neocortical LTP was completely blocked by either NMDA antagonist or CCK-BR antagonist, while application of either NMDA or CCK induced LTP after low-frequency stimulation (LFS). Moreover, in the presence of CCK LTP was still induced, even after blockade of NMDA receptors. Local application of NMDA induced CCK release in the neocortex. To identify how NMDA receptor switches LTP, a stimulation protocol of 25 pulse-pairs was adopted to replace HFS; NMDA-dependent LTP was induced with the inter-pulse intervals between 10 and 100 ms, but not with those of 5 and 200 ms. LTP-mediated plasticity was linked to localization of the NMDA receptor subunit NR2a on cortical CCK terminals originating in the entorhinal cortex. These novel findings suggest that presynaptic NMDA receptors on CCK terminals control the release of CCK, which enables neocortical LTP and formation of cue-cue associative memory.\n\nOne Sentence SummaryPresynaptic NMDA receptors switches the release of CCK from entorhinal neurons, which enables neocortical LTP and formation of sound-sound associative memory.

Explore related subjects

Keep this discovery

BibTeXRIS

Li, X., Xi, C., Wong, Y. T., Wang, H., Feng, H., Zheng, X., Feng, J., Baibado, J. T., Jesky, R., Peng, Y., Wang, Z., Xie, H., Sun, W., Zhang, Z., Zhang, X., He, L., Zhang, N., Tang, P., Su, J.-F., Hu, L.-L., Liu, Q., He, X.-B., Tan, A., Sun, X., Li, M., Wong, K., Wang, X., Guo, Y. P., Xu, F., He, J.. 2017-09-14. Cholecystokinin release triggered by presynaptic NMDA receptors produces LTP and sound-sound associative memory formation. https://doi.org/10.1101/188839

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

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience