Although fear memory formation is essential for survival and fear-related mental disorders, the neural circuitry and mechanism are incompletely understood. Here, we utilized trace fear conditioning to study the formation of trace fear memory in mice. We identified the entorhinal cortex (EC) as a critical component of sensory signaling to the amygdala. We adopted both loss-of-function and gain-of-function experiments to demonstrate that release of the cholecystokinin (CCK) from the EC is required for trace fear memory formation. We discovered that CCK-positive neurons project from the EC to the lateral nuclei of the amygdala (LA), and inhibition of CCK-dependent signaling in the EC prevented long-term potentiation of the auditory response in the LA and formation of trace fear memory. In summary, high-frequency activation of EC neurons triggers the release of CCK in their projection terminals in the LA, potentiating auditory response in LA neurons. The neural plasticity in the LA leads to trace fear memory formation.
Data for this submission has been uploaded to the Dryad Digital Repository,available once published: doi:10.5061/dryad.0p2ngf217
The entorhinal cortex modulates trace fear memory formation and neuroplasticity in the lateral amygdala via cholecystokininDryad Digital Repository, doi:10.5061/dryad.0p2ngf217.
- Jufang He
- Jufang He
- Jufang He
- Jufang He
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Animal experimentation: All experimental procedures were approved by the Animal Subjects Ethics Sub-Committee of the City University of Hong Kong (Reference number of animal ethics review: A-0529 and A-0282)
- Joshua Johansen, RIKEN Center for Brain Science, Japan
© 2021, Feng et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Deciphering patterns of connectivity between neurons in the brain is a critical step toward understanding brain function. Imaging-based neuroanatomical tracing identifies area-to-area or sparse neuron-to-neuron connectivity patterns, but with limited throughput. Barcode-based connectomics maps large numbers of single-neuron projections, but remains a challenge for jointly analyzing single-cell transcriptomics. Here, we established a rAAV2-retro barcode-based multiplexed tracing method that simultaneously characterizes the projectome and transcriptome at the single neuron level. We uncovered dedicated and collateral projection patterns of ventromedial prefrontal cortex (vmPFC) neurons to five downstream targets and found that projection-defined vmPFC neurons are molecularly heterogeneous. We identified transcriptional signatures of projection-specific vmPFC neurons, and verified Pou3f1 as a marker gene enriched in neurons projecting to the lateral hypothalamus, denoting a distinct subset with collateral projections to both dorsomedial striatum and lateral hypothalamus. In summary, we have developed a new multiplexed technique whose paired connectome and gene expression data can help reveal organizational principles that form neural circuits and process information.
Blindness affects millions of people around the world. A promising solution to restoring a form of vision for some individuals are cortical visual prostheses, which bypass part of the impaired visual pathway by converting camera input to electrical stimulation of the visual system. The artificially induced visual percept (a pattern of localized light flashes, or ‘phosphenes’) has limited resolution, and a great portion of the field’s research is devoted to optimizing the efficacy, efficiency, and practical usefulness of the encoding of visual information. A commonly exploited method is non-invasive functional evaluation in sighted subjects or with computational models by using simulated prosthetic vision (SPV) pipelines. An important challenge in this approach is to balance enhanced perceptual realism, biologically plausibility, and real-time performance in the simulation of cortical prosthetic vision. We present a biologically plausible, PyTorch-based phosphene simulator that can run in real-time and uses differentiable operations to allow for gradient-based computational optimization of phosphene encoding models. The simulator integrates a wide range of clinical results with neurophysiological evidence in humans and non-human primates. The pipeline includes a model of the retinotopic organization and cortical magnification of the visual cortex. Moreover, the quantitative effects of stimulation parameters and temporal dynamics on phosphene characteristics are incorporated. Our results demonstrate the simulator’s suitability for both computational applications such as end-to-end deep learning-based prosthetic vision optimization as well as behavioral experiments. The modular and open-source software provides a flexible simulation framework for computational, clinical, and behavioral neuroscientists working on visual neuroprosthetics.