scholarly journals Circuits for integrating learnt and innate valences in the fly brain

2020 ◽  
Author(s):  
Claire Eschbach ◽  
Akira Fushiki ◽  
Michael Winding ◽  
Bruno Afonso ◽  
Ingrid V Andrade ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Functional Imaging ◽  
Animal Behavior ◽  
Mushroom Body ◽  
Individual Experience ◽  
Lateral Horn ◽  
Olfactory Pathways ◽  
Sensory Cue ◽  
Output Neurons ◽  
Direct Input

AbstractAnimal 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.

scholarly journals Circuits for integrating learned and innate valences in the insect brain

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Claire Eschbach ◽  
Akira Fushiki ◽  
Michael Winding ◽  
Bruno Afonso ◽  
Ingrid V Andrade ◽  
...  
Keyword(s):  
Animal Behavior ◽  
Mushroom Body ◽  
Excitatory Input ◽  
Insect Brain ◽  
Inhibitory Input ◽  
Lateral Horn ◽  
Negative Valence ◽  
Output Neurons ◽  
Positive Valence ◽  
Patterns Of Interaction

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all Mushroom Body output neurons (encoding learned valences) and characterized their patterns of interaction with Lateral Horn neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent Mushroom Body and Lateral Horn inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate to modify behavior.

scholarly journals Predictive olfactory learning in Drosophila

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chang Zhao ◽  
Yves F. Widmer ◽  
Sören Diegelmann ◽  
Mihai A. Petrovici ◽  
Simon G. Sprecher ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Dopaminergic Neurons ◽  
Mushroom Body ◽  
Trace Conditioning ◽  
Fruit Fly ◽  
Olfactory Learning ◽  
Shock Strength ◽  
Behavioral Experiments ◽  
Kenyon Cells ◽  
Output Neurons

AbstractOlfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. We present behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and we suggest two alternative models for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offers a framework to dissect MBON circuits and interpret DAN activity during olfactory learning.

scholarly journals Selective dendritic localization of mRNA in Drosophila mushroom body output neurons

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Jessica Mitchell ◽  
Carlas S Smith ◽  
Josh Titlow ◽  
Nils Otto ◽  
Pieter van Velde ◽  
...  
Keyword(s):  
Single Molecule ◽  
Nicotinic Acetylcholine Receptors ◽  
Neuronal Plasticity ◽  
Mushroom Body ◽  
Acetylcholine Receptors ◽  
Behavioural Change ◽  
Before And After ◽  
Specific Mrnas ◽  
Output Neurons ◽  
Subcellular Resolution

Memory-relevant neuronal plasticity is believed to require local translation of new proteins at synapses. Understanding this process requires the visualization of the relevant mRNAs within these neuronal compartments. Here we used single-molecule fluorescence in situ hybridization (smFISH) to localize mRNAs at subcellular resolution in the adult Drosophila brain. mRNAs for subunits of nicotinic acetylcholine receptors and kinases could be detected within the dendrites of co-labelled Mushroom Body Output Neurons (MBONs) and their relative abundance showed cell-specificity. Moreover, aversive olfactory learning produced a transient increase in the level of CaMKII mRNA within the dendritic compartments of the 52a MBONs. Localization of specific mRNAs in MBONs before and after learning represents a critical step towards deciphering the role of dendritic translation in the neuronal plasticity underlying behavioural change in Drosophila.

scholarly journals Long-term memory requires sequential protein synthesis in three subsets of mushroom body output neurons in Drosophila

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Jie-Kai Wu ◽  
Chu-Yi Tai ◽  
Kuan-Lin Feng ◽  
Shiu-Ling Chen ◽  
Chun-Chao Chen ◽  
...  
Keyword(s):  
Protein Synthesis ◽  
Mushroom Body ◽  
Long Term Memory ◽  
Term Memory ◽  
Output Neurons

scholarly journals Multimodal integration and stimulus categorization in putative mushroom body output neurons of the honeybee

2018 ◽  
Vol 5 (2) ◽  
pp. 171785 ◽  
Author(s):  
Martin F. Strube-Bloss ◽  
Wolfgang Rössler
Keyword(s):  
Visual Information ◽  
Mushroom Body ◽  
Visual Cues ◽  
Sensory Modality ◽  
Sensory Information ◽  
Insect Brain ◽  
Pollinating Insects ◽  
Output Neurons ◽  
Electrophysiological Characterization ◽  
Nonlinear Integration

Flowers attract pollinating insects like honeybees by sophisticated compositions of olfactory and visual cues. Using honeybees as a model to study olfactory–visual integration at the neuronal level, we focused on mushroom body (MB) output neurons (MBON). From a neuronal circuit perspective, MBONs represent a prominent level of sensory-modality convergence in the insect brain. We established an experimental design allowing electrophysiological characterization of olfactory, visual, as well as olfactory–visual induced activation of individual MBONs. Despite the obvious convergence of olfactory and visual pathways in the MB, we found numerous unimodal MBONs. However, a substantial proportion of MBONs (32%) responded to both modalities and thus integrated olfactory–visual information across MB input layers. In these neurons, representation of the olfactory–visual compound was significantly increased compared with that of single components, suggesting an additive, but nonlinear integration. Population analyses of olfactory–visual MBONs revealed three categories: (i) olfactory, (ii) visual and (iii) olfactory–visual compound stimuli. Interestingly, no significant differentiation was apparent regarding different stimulus qualities within these categories. We conclude that encoding of stimulus quality within a modality is largely completed at the level of MB input, and information at the MB output is integrated across modalities to efficiently categorize sensory information for downstream behavioural decision processing.

scholarly journals Drosophila ORB protein in two mushroom body output neurons is necessary for long-term memory formation

2013 ◽  
Vol 110 (19) ◽  
pp. 7898-7903 ◽  
Author(s):  
T.-P. Pai ◽  
C.-C. Chen ◽  
H.-H. Lin ◽  
A.-L. Chin ◽  
J. S.-Y. Lai ◽  
...  
Keyword(s):  
Mushroom Body ◽  
Memory Formation ◽  
Long Term Memory ◽  
Term Memory ◽  
Output Neurons

scholarly journals Predictive olfactory learning in Drosophila

2019 ◽  
Author(s):  
Chang Zhao ◽  
Yves F Widmer ◽  
Soeren Diegelmann ◽  
Mihai Petrovici ◽  
Simon G Sprecher ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Dopaminergic Neurons ◽  
Mushroom Body ◽  
Trace Conditioning ◽  
Fruit Fly ◽  
Olfactory Learning ◽  
Shock Strength ◽  
Behavioral Experiments ◽  
Kenyon Cells ◽  
Output Neurons

AbstractOlfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. We present behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and we suggest two alternative models for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offer a framework to dissect MBON circuits and interpret DAN activity during olfactory learning.

scholarly journals The connectome of the adult Drosophila mushroom body: implications for function

2020 ◽  
Author(s):  
Feng Li ◽  
Jack Lindsey ◽  
Elizabeth C. Marin ◽  
Nils Otto ◽  
Marisa Dreher ◽  
...  
Keyword(s):  
Dopaminergic Neurons ◽  
Mushroom Body ◽  
Experimental Studies ◽  
Central Complex ◽  
Sensory Inputs ◽  
Descending Neurons ◽  
Sensory Modalities ◽  
Output Neurons ◽  
Transfer Of Information ◽  
Adult Drosophila

AbstractMaking inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory and activity regulation. Here we identify new components of the MB circuit in Drosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

scholarly journals Input connectivity reveals additional heterogeneity of dopaminergic reinforcement in Drosophila

2020 ◽  
Author(s):  
Nils Otto ◽  
Markus W. Pleijzier ◽  
Isabel C. Morgan ◽  
Amelia J. Edmondson-Stait ◽  
Konrad J. Heinz ◽  
...  
Keyword(s):  
Dopaminergic Neurons ◽  
Mushroom Body ◽  
List Type ◽  
Behavioral Experiments ◽  
State Dependent ◽  
Memory Extinction ◽  
Level Function ◽  
Output Neurons ◽  
Functional Relevance ◽  
Dendritic Branches

SummaryDifferent types of Drosophila dopaminergic neurons (DANs) reinforce memories of unique valence and provide state-dependent motivational control [1]. Prior studies suggest that the compartment architecture of the mushroom body (MB) is the relevant resolution for distinct DAN functions [2, 3]. Here we used a recent electron microscope volume of the fly brain [4] to reconstruct the fine anatomy of individual DANs within three MB compartments. We find the 20 DANs of the γ5 compartment, at least some of which provide reward teaching signals, can be clustered into 5 anatomical subtypes that innervate different regions within γ5. Reconstructing 821 upstream neurons reveals input selectivity, supporting the functional relevance of DAN sub-classification. Only one PAM-γ5 DAN subtype γ5(fb) receives direct recurrent input from γ5β’2a mushroom body output neurons (MBONs) and behavioral experiments distinguish a role for these DANs in memory revaluation from those reinforcing sugar memory. Other DAN subtypes receive major, and potentially reinforcing, inputs from putative gustatory interneurons or lateral horn neurons, which can also relay indirect feedback from MBONs. We similarly reconstructed the single aversively reinforcing PPL1-γ1pedc DAN. The γ1pedc DAN inputs mostly differ from those of γ5 DANs and they cluster onto distinct dendritic branches, presumably separating its established roles in aversive reinforcement and appetitive motivation [5, 6]. Tracing also identified neurons that provide broad input to γ5, β’2a and γ1pedc DANs suggesting that distributed DAN populations can be coordinately regulated. These connectomic and behavioral analyses therefore reveal further complexity of dopaminergic reinforcement circuits between and within MB compartments.HighlightsNanoscale anatomy reveals additional subtypes of rewarding dopaminergic neurons.Connectomics reveals extensive input specificity to subtypes of dopaminergic neurons.Axon morphology implies dopaminergic neurons provide subcompartment-level function.Unique dopaminergic subtypes serve aversive memory extinction and sugar learning.

scholarly journals Neurogenetic dissection of the Drosophila lateral horn reveals major outputs, diverse behavioural functions, and interactions with the mushroom body

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Michael-John Dolan ◽  
Shahar Frechter ◽  
Alexander Shakeel Bates ◽  
Chuntao Dan ◽  
Paavo Huoviala ◽  
...  
Keyword(s):  
Mushroom Body ◽  
Cell Types ◽  
Olfactory Cues ◽  
Body Site ◽  
Olfactory Behavior ◽  
Gal4 Driver ◽  
Sensory Stimuli ◽  
Lateral Horn ◽  
Functional Understanding ◽  
Innate Behaviour

Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In Drosophila, one higher olfactory centre, the lateral horn (LH), is implicated in innate behaviour. However, our structural and functional understanding of the LH is scant, in large part due to a lack of sparse neurogenetic tools for this region. We generate a collection of split-GAL4 driver lines providing genetic access to 82 LH cell types. We use these to create an anatomical and neurotransmitter map of the LH and link this to EM connectomics data. We find ~30% of LH projections converge with outputs from the mushroom body, site of olfactory learning and memory. Using optogenetic activation, we identify LH cell types that drive changes in valence behavior or specific locomotor programs. In summary, we have generated a resource for manipulating and mapping LH neurons, providing new insights into the circuit basis of innate and learned olfactory behavior.

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