Periodic Reporting for period 1 - SynEMO (Synaptic dendritic architecture as a determinant for processing emotional information of opposite value in amygdalar-hippocampal subnetworks)
Periodo di rendicontazione: 2022-10-01 al 2024-09-30
Survival depends on the ability to form emotional memories by associating environmental cues with rewarding or aversive stimuli. A critical brain structure in this process is the basolateral amygdala (BLA), where distinct populations of neurons encode positive and negative stimuli. By project to the ventral CA1 region of the hippocampus (vCA1), forming pathways that route information of opposite valence. The specific mechanisms by which these pathways enable vCA1 neurons to process distinct emotional information remain poorly understood.
The SynEMO project investigated how synaptic inputs from the BLA, CA3 pyramidal neurons, and bistratified interneurons (BiS-INs) converge on vCA1 dendrites and contributes to emotional learning and memory.
The project provides a framework that addresses how the spatial organization and clustering of synaptic inputs at the dendritic level influence circuit activity. This is a highly relevant question, expected to enrich the understanding of information processing, by providing a generalizable model that considers synaptic arrangements. SynEMO’s findings advance the development of detailed neuronal models, enriching basic neuroscience research. In addition, such models offer significant implications for addressing mental health disorders such as anxiety and depression, providing a foundation for novel therapeutic strategies.
The SynEMO project investigated how synaptic inputs from the BLA, CA3 pyramidal neurons, and bistratified interneurons (BiS-INs) converge on vCA1 dendrites and contributes to emotional learning and memory.
The project provides a framework that addresses how the spatial organization and clustering of synaptic inputs at the dendritic level influence circuit activity. This is a highly relevant question, expected to enrich the understanding of information processing, by providing a generalizable model that considers synaptic arrangements. SynEMO’s findings advance the development of detailed neuronal models, enriching basic neuroscience research. In addition, such models offer significant implications for addressing mental health disorders such as anxiety and depression, providing a foundation for novel therapeutic strategies.
The SynEMO project carried out extensive experimental and technical development to investigate the synaptic arrangementss underlying emotional learning and memory. Significant progress was made in developing innovative methodologies.
Work Performed: A key achievement was the development of a high-throughput imaging workflow for analyzing dendritic spine calcium activity. This system combined advanced two-photon imaging and patch-clamp with computational pipelines for automated segmentation and classification of calcium traces, exploiting deep learning-based techniques. These tools allowed detailed mapping of synaptic inputs across vCA1 dendrites, providing insights into their spatial organization and clustering.
Custom experimental setups were also established. A behavioral conditioning cage was designed to deliver precise, automated paradigms for aversive and rewarding conditioning.
Main Achievements: The project characterized the spatial distribution of excitatory inputs from the BLA and CA3 on vCA1 dendrites, revealing distinct input patterns. This work advances the understanding of how synaptic architecture supports neural circuit dynamics.
The imaging workflow and behavioral system developed during SynEMO are now available for ongoing and future studies, impacting reproducibility and application to a wide variety of circuits.
Work Performed: A key achievement was the development of a high-throughput imaging workflow for analyzing dendritic spine calcium activity. This system combined advanced two-photon imaging and patch-clamp with computational pipelines for automated segmentation and classification of calcium traces, exploiting deep learning-based techniques. These tools allowed detailed mapping of synaptic inputs across vCA1 dendrites, providing insights into their spatial organization and clustering.
Custom experimental setups were also established. A behavioral conditioning cage was designed to deliver precise, automated paradigms for aversive and rewarding conditioning.
Main Achievements: The project characterized the spatial distribution of excitatory inputs from the BLA and CA3 on vCA1 dendrites, revealing distinct input patterns. This work advances the understanding of how synaptic architecture supports neural circuit dynamics.
The imaging workflow and behavioral system developed during SynEMO are now available for ongoing and future studies, impacting reproducibility and application to a wide variety of circuits.
Results: By performing patch-clamp coupled with calcium imaging of dendrites of vCA1 neurons, comprehensive maps of active synaptic inputs - BLA and CA3 - were built. Overall, spine density of active inputs varies across dendritic branches, with third-degree apical dendrites showing the highest density of both total and activated spines. Specifically, BLA inputs are more evenly distributed between apical and basal dendrites, while CA3 inputs primarily target apical compartments.
SynEMO's findings links dendritic synaptic organization to circuit dynamics, offering a framework for studying information processing. Additional studies are required to validate and expand on SynEMO's findings.
An impact is represented by its potential broader application: disseminating the project’s technical tools and methods to the wider scientific community will foster further research, supporting the workflow integration into other research efforts.
SynEMO's findings links dendritic synaptic organization to circuit dynamics, offering a framework for studying information processing. Additional studies are required to validate and expand on SynEMO's findings.
An impact is represented by its potential broader application: disseminating the project’s technical tools and methods to the wider scientific community will foster further research, supporting the workflow integration into other research efforts.