Circuits for integrating learnt and innate valences in the fly brain

Abstract

Animal behavior is shaped both by evolution and by individual experience. In many species parallel brain pathways are thought to encode innate and learnt behavior drives and as a result may link the same sensory cue to different actions if innate and learnt drives are in opposition. How these opposing drives are integrated into a single coherent action is not well understood. In insects, the Mushroom Body Output Neurons (MBONs) and the Lateral Horn Neurons (LHNs) are thought to provide the learnt and innate drives, respectively. However their patterns of convergence and the mechanisms by which their outputs are used to select actions are not well understood. We used electron microscopy reconstruction to comprehensively map the downstream targets of all MBONs in Drosophila larva and characterise their patterns of convergence with LHNs. We discovered convergence neurons that receive direct input from MBONs and LHNs and compare opposite behaviour drives. Functional imaging and optogenetic manipulation suggest these convergence neurons compute the overall predicted value of approaching or avoiding an odor and mediate action selection. Our study describes the circuit mechanisms allowing integration of opposing drives from parallel olfactory pathways.

Synaptic counts approximate synaptic contact area in Drosophila

“…Following the chain of reasoning that synaptic strength correlates with vesicle release probability [32], which in turn correlates with the number of docked vesicles [21, 12], which correlates with the surface area of the EM-dense active zone, our findings suggest that inferring synaptic strength directly from the number of morphological contacts is grounded and generalizable across different edge types. Therefore our findings are consistent with the formulation of computational circuit models directly from morphological synaptic counts per edge, as has been done in previous studies that had implicitly assumed a correlation between counts and synaptic strength [2, 33, 3, 19, 7].…”

Useful road maps: studying Drosophila larva’s central nervous system with the help of connectomics

“…This interpretation also fits the convergence of projection neurons of various modalities onto the two brain structures MB [ 16 ] and LH [ 14 , 15 ] ( Figure 3 ). To comprehensively characterize the circuits that underlie navigational decisions several screens have been conducted for neurons that contribute to these behaviors [ 50 , 69 , 70 , 71 ]. Possible bottleneck targets of navigational circuits are the descending neurons, such as the ‘PDM-DN’ which can trigger stop in a deterministic way [ 35 ] ( Figure 3 iii ).…”

Information flow, cell types and stereotypy in a full olfactory connectome

“…In general, CN2 neurons tend to get inhibitory inputs from naively aversive MBONs and TOONs, and excitatory input from naively appetitive MBONs and TOONs ( Figure S21). Analogous innate-learned integration has been studied in the larva, also in connectome-informed experimentation (Eschbach et al, 2020). The authors investigated a CN2 cell type and found it to be excited by appetitive LHNs and MBONs and inhibited by aversive MBONs.…”

“…After the antennal lobe, information diverges onto two higher olfactory centres, the MB (required for learning) and the lateral horn (LH, principally associated with innate behaviour). We analyse reconvergence downstream of these divergent projections as recent evidence suggests that this is crucial to the expression of learned behaviour (Dolan et al, 2018; Dolan et al, 2019; Bates et al, 2020; Eschbach et al, 2020).…”