Hattori, D. | Search bioRxiv

bioRxiv2023

A rapid and bidirectional reporter of neural activity reveals neural correlates of social behaviors in Drosophila

Neural activity is modulated over different timescales encompassing sub-seconds to days reflecting changes in external environment, internal state, and behavior. Using Drosophila as a model, we have developed a rapid and bidirectional reporter that provides a robust cellular readout of recent neural activity. This reporter utilizes nuclear vs cytoplasmic distribution of CREB-regulated transcriptional coactivator, CRTC. Subcellular distribution of GFP-tagged CRTC (CRTC::GFP) bidirectionally changes on the order of minutes and reflects both increases and decreases in neural activity. We establish an automated machine-learning-based routine for efficient quantification of reporter signal. Using this reporter, we demonstrate acute mating- evoked activation of peptidergic neurons. We further investigate the functional role of the master courtship regulator gene, fruitless, and show that fruitless is necessary to ensure activation of male arousal neurons by female cues. Together, our results establish CRTC::GFP as a bidirectional reporter of recent neural activity suitable for examining neural correlates in behavioral contexts.

neuroscience↗

bioRxiv2022

A neural theory for counting memories

"Ive never smelled anything like this." "Ive seen you once before." "Ive heard this song many times." Keeping track of the number of times different stimuli have been experienced is a critical computation for behavior. This computation occurs ubiquitously across sensory modalities, and naturally without reward or punishment. However, the neural circuitry that mediates this computation remains unknown. Here, we propose a theoretical two-layer neural circuit that can store counts of stimulus occurrence frequencies. This circuit implements a data structure, called a count sketch, that is commonly used in computer science to maintain item frequencies in streaming data. Our first model implements the count sketch data structure using Hebbian synapses and outputs stimulus-specific frequencies. Our second model uses anti-Hebbian plasticity and only tracks frequencies within four count categories ("1-2-3-many"), which we suggest makes a better trade-off between the number of categories that need to be distinguished and the potential ethological value of those categories. Using real-world datasets, we show how both models can closely track the frequencies of different stimuli experienced, while being robust to noise, thus expanding the traditional novelty-familiarity memory axis from binary to continuous. Finally, we show that an implementation of the "1-2-3-many" count sketch -- including network architecture, synaptic plasticity rule, and output neuron that encodes count categories -- exists in a novelty detection circuit in the insect mushroom body, and we argue that similar circuit motifs also appear in mammals, suggesting that basic memory counting machinery may be broadly conserved.

neuroscience↗