Principles for coding associative memories in a compact neural network

Abstract

A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how four types of associative memories (short- and long-term memories, each as positive and negative associations) are encoded within the compact neural network of Caenorhabditis elegans worms. Interestingly, sensory neurons were primarily involved in coding short-term, but not long-term, memories, and individual sensory neurons could be assigned to coding either the conditioned stimulus or the experience valence (or both). Moreover, when considering the collective activity of the sensory neurons, the specific training experiences could be decoded. Interneurons integrated the modulated sensory inputs and a simple linear combination model identified the experience-specific modulated communication routes. The widely distributed memory suggests that integrated network plasticity, rather than changes to individual neurons, underlies the fine behavioral plasticity. This comprehensive study reveals basic memory-coding principles and highlights the central roles of sensory neurons in memory formation.

Intricate response dynamics enhances stimulus discrimination in the resource-limitedC. eleganschemosensory system

“… (A) A confocal image of the right side of the amphid organ. Imaging was done using the strain azrIs280 [ osm-6 ::GCaMP3, osm-6 ::mCherry-NLS] (Iwanir et al 2019; Pritz et al 2023). Red, nuclear mCherry; Green, cytoplasmic GCaMP.…”

“…To simultaneously image all of the neurons, we used a confocal system equipped with a fast-resonating scanner that allowed imaging the entire brain volume at 2 Hz (30-40 slices, at a 0.6-0.7 µm Z-resolution), providing the necessary spatio-temporal resolution to reliably extract activity from individual sensory neurons (Schrödel et al 2013; Nguyen et al 2016; Randi and Leifer 2020; Iwanir et al 2019; Yemini et al 2021; Pritz et al 2023; Lin et al 2023). These acquisition settings, coupled with our analysis pipeline (see Methods) allowed tracking and measuring activity of all chemosensory neurons from both the right and left lateral sides (22 in total), excluding only AFDL/R which were often below detection levels ( Figure 1A-B ).…”

Disposition of the chemosensory neurons in the neurotransmitter-release mutantunc-13

“…For imaging, we used a confocal microscope capturing z-stack images at a resolution of 0.6 µm apart, sufficient for cellular resolution detection of individual neurons. Using our previously developed image analysis pipeline (Iwanir et al, 2019;Pritz et al, 2023), we segmented and identified individual neurons based on nuclear expression of mCherry. Notably, mCherry nuclear localization is crucial as it provides the cellular resolution required for accurate identification of individual neurons.…”

Adapting and optimizing GCaMP8f for use inCaenorhabditis elegans

“…In C. elegans, GCaMP usage has been widespread and enabled discoveries about stimulus encoding of sensory neurons using single-cell imaging (Clark et al 2006;Kato et al 2014;Larsch et al 2015;Itskovits et al 2018;Katta et al 2019) and multi-neuron imaging in chemosensory cells (Itskovits et al 2018;Pritz et al 2023). In addition, GCaMP was essential for detecting the compartment-specific activity in interneurons (Hendricks et al 2012), and global effects of single neurons on activity and sleep (Turek et al 2013).…”