The anterior paired lateral neuron normalizes odour-evoked activity in the Drosophila mushroom body calyx

To identify and memorize discrete but similar environmental inputs, the brain needs to distinguish between subtle differences of activity patterns in defined neuronal populations. The Kenyon cells of the Drosophila adult mushroom body (MB) respond sparsely to complex olfactory input, a property that is thought to support stimuli discrimination in the MB. To understand how this property emerges, we investigated the role of the inhibitory anterior paired lateral neuron (APL) in the input circuit of the MB, the calyx. Within the calyx, presynaptic boutons of projection neurons (PNs) form large synaptic microglomeruli (MGs) with dendrites of postsynaptic Kenyon cells (KCs). Combining EM data analysis and in vivo calcium imaging, we show that APL, via inhibitory and reciprocal synapses targeting both PN boutons and KC dendrites, normalizes odour-evoked representations in MGs of the calyx. APL response scales with the PN input strength and is regionalized around PN input distribution. Our data indicate that the formation of a sparse code by the Kenyon cells requires APL-driven normalization of their MG postsynaptic responses. This work provides experimental insights on how inhibition shapes sensory information representation in a higher brain centre, thereby supporting stimuli discrimination and allowing for efficient associative memory formation.

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The anterior paired lateral neuron normalizes odour-evoked activity at the mushroom body calyx

10.1101/2021.09.20.461071 ◽

2021 ◽

Author(s):

Luigi Prisco ◽

Stephan Hubertus Deimel ◽

Hanna Yeliseyeva ◽

Andre Fiala ◽

Gaia Tavosanis

Keyword(s):

Mushroom Body ◽

Activity Patterns ◽

Sensory Information ◽

Input Circuit ◽

Projection Neurons ◽

Neuronal Populations ◽

Kenyon Cells ◽

Presynaptic Boutons ◽

Evoked Activity

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Mushroom body input connections form independently of sensory activity in Drosophila melanogaster

10.1101/2021.11.06.467552 ◽

2021 ◽

Author(s):

Tatsuya Hayashi ◽

Alexander John MacKenzie ◽

Ishani Ganguly ◽

Hayley Smihula ◽

Miles Solomon Jacob ◽

...

Keyword(s):

Drosophila Melanogaster ◽

Mushroom Body ◽

Activity Patterns ◽

Sensory Information ◽

Population Level ◽

Connectivity Pattern ◽

Projection Neurons ◽

Efficient Manner ◽

Kenyon Cells ◽

Sensory Activity

Associative brain centers, such as the insect mushroom body, need to represent sensory information in an efficient manner. In Drosophila melanogaster, the Kenyon cells of the mushroom body integrate inputs from a random set of olfactory projection neurons, but some projection neurons, namely those activated by a few ethologically meaningful odors, connect to Kenyon cells more frequently than others. This biased and random connectivity pattern is conceivably advantageous, as it enables the mushroom body to represent a large number of odors as unique activity patterns while prioritizing the representation of a few specific odors. How this connectivity pattern is established remains largely unknown. Here, we test whether the mechanisms patterning the connections between Kenyon cells and projection neurons depend on sensory activity or whether they are hardwired. We mapped a large number of mushroom body input connections in anosmic flies, flies lacking the obligate odorant co-receptor Orco, and in wildtype flies. Statistical analyses of these datasets reveal that the random and biased connectivity pattern observed between Kenyon cells and projection neurons forms normally in the absence of most olfactory sensory activity. This finding supports the idea that even comparatively subtle, population-level patterns of neuronal connectivity can be encoded by fixed genetic programs and are likely to be the result of evolved prioritization of ecologically and ethologically salient stimuli.

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Olfactory Representations by Drosophila Mushroom Body Neurons

Journal of Neurophysiology ◽

10.1152/jn.01283.2007 ◽

2008 ◽

Vol 99 (2) ◽

pp. 734-746 ◽

Cited By ~ 205

Author(s):

Glenn C. Turner ◽

Maxim Bazhenov ◽

Gilles Laurent

Keyword(s):

Olfactory Receptor ◽

Mushroom Body ◽

Temporal Integration ◽

Activity Patterns ◽

Olfactory Receptor Neurons ◽

Projection Neurons ◽

Contributing Factors ◽

Receptor Neurons ◽

Whole Cell Recordings

Learning and memory has been studied extensively in Drosophila using behavioral, molecular, and genetic approaches. These studies have identified the mushroom body as essential for the formation and retrieval of olfactory memories. We investigated odor responses of the principal neurons of the mushroom body, the Kenyon cells (KCs), in Drosophila using whole cell recordings in vivo. KC responses to odors were highly selective and, thus sparse, compared with those of their direct inputs, the antennal lobe projection neurons (PNs). We examined the mechanisms that might underlie this transformation and identified at least three contributing factors: excitatory synaptic potentials (from PNs) decay rapidly, curtailing temporal integration, PN convergence onto individual KCs is low (∼10 PNs per KC on average), and KC firing thresholds are high. Sparse activity is thought to be useful in structures involved in memory in part because sparseness tends to reduce representation overlaps. By comparing activity patterns evoked by the same odors across olfactory receptor neurons and across KCs, we show that representations of different odors do indeed become less correlated as they progress through the olfactory system.

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Sparsening and Temporal Sharpening of Olfactory Representations in the Honeybee Mushroom Bodies

Journal of Neurophysiology ◽

10.1152/jn.00397.2005 ◽

2005 ◽

Vol 94 (5) ◽

pp. 3303-3313 ◽

Cited By ~ 107

Author(s):

Paul Szyszka ◽

Mathias Ditzen ◽

Alexander Galkin ◽

C. Giovanni Galizia ◽

Randolf Menzel

Keyword(s):

Mushroom Body ◽

Antennal Lobe ◽

Activity Patterns ◽

Projection Neuron ◽

Insect Brain ◽

Projection Neurons ◽

Similar Response ◽

Kenyon Cell ◽

Cell Responses ◽

Kenyon Cells

We explored the transformations accompanying the transmission of odor information from the first-order processing area, the antennal lobe, to the mushroom body, a higher-order integration center in the insect brain. Using Ca2+ imaging, we recorded activity in the dendrites of the projection neurons that connect the antennal lobe with the mushroom body. Next, we recorded the presynaptic terminals of these projection neurons. Finally, we characterized their postsynaptic partners, the intrinsic neurons of the mushroom body, the clawed Kenyon cells. We found fundamental differences in odor coding between the antennal lobe and the mushroom body. Odors evoked combinatorial activity patterns at all three processing stages, but the spatial patterns became progressively sparser along this path. Projection neuron dendrites and boutons showed similar response profiles, but the boutons were more narrowly tuned to odors. The transmission from projection neuron boutons to Kenyon cells was accompanied by a further sparsening of the population code. Activated Kenyon cells were highly odor specific. Furthermore, the onset of Kenyon cell responses to projection neurons occurred within the first 200 ms and complex temporal patterns were transformed into brief phasic responses. Thus two types of transformations occurred within the MB: sparsening of a combinatorial code, mediated by pre- and postsynaptic processing within the mushroom body microcircuits, and temporal sharpening of postsynaptic Kenyon cell responses, probably involving a broader loop of inhibitory recurrent neurons.

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Mechanisms underlying homeostatic plasticity in theDrosophilamushroom body in vivo

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1921294117 ◽

2020 ◽

Vol 117 (28) ◽

pp. 16606-16615 ◽

Cited By ~ 1

Author(s):

Anthi A. Apostolopoulou ◽

Andrew C. Lin

Keyword(s):

Mushroom Body ◽

Feedback Inhibition ◽

Homeostatic Plasticity ◽

Projection Neurons ◽

Kenyon Cell ◽

Network Function ◽

Kenyon Cells ◽

Central Brain ◽

Artificial Activation

Neural network function requires an appropriate balance of excitation and inhibition to be maintained by homeostatic plasticity. However, little is known about homeostatic mechanisms in the intact central brain in vivo. Here, we study homeostatic plasticity in theDrosophilamushroom body, where Kenyon cells receive feedforward excitation from olfactory projection neurons and feedback inhibition from the anterior paired lateral neuron (APL). We show that prolonged (4-d) artificial activation of the inhibitory APL causes increased Kenyon cell odor responses after the artificial inhibition is removed, suggesting that the mushroom body compensates for excess inhibition. In contrast, there is little compensation for lack of inhibition (blockade of APL). The compensation occurs through a combination of increased excitation of Kenyon cells and decreased activation of APL, with differing relative contributions for different Kenyon cell subtypes. Our findings establish the fly mushroom body as a model for homeostatic plasticity in vivo.

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Nasal Chemosensory-Stimulation Evoked Activity Patterns in the Rat Trigeminal Ganglion Visualized by In Vivo Voltage-Sensitive Dye Imaging

PLoS ONE ◽

10.1371/journal.pone.0026158 ◽

2011 ◽

Vol 6 (10) ◽

pp. e26158 ◽

Cited By ~ 8

Author(s):

Markus Rothermel ◽

Benedict Shien Wei Ng ◽

Agnieszka Grabska-Barwińska ◽

Hanns Hatt ◽

Dirk Jancke

Keyword(s):

Trigeminal Ganglion ◽

Activity Patterns ◽

Voltage Sensitive Dye ◽

Evoked Activity ◽

Voltage Sensitive Dye Imaging

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Reinforcement Learning of Two-Joint Virtual Arm Reaching in a Computer Model of Sensorimotor Cortex

Neural Computation ◽

10.1162/neco_a_00521 ◽

2013 ◽

Vol 25 (12) ◽

pp. 3263-3293 ◽

Cited By ~ 23

Author(s):

Samuel A. Neymotin ◽

George L. Chadderdon ◽

Cliff C. Kerr ◽

Joseph T. Francis ◽

William W. Lytton

Keyword(s):

Reinforcement Learning ◽

Information Flow ◽

Sensory Information ◽

Relevant Information ◽

Spike Timing ◽

Proprioceptive Information ◽

Learning Networks ◽

Neuronal Populations ◽

Arm Reaching

Neocortical mechanisms of learning sensorimotor control involve a complex series of interactions at multiple levels, from synaptic mechanisms to cellular dynamics to network connectomics. We developed a model of sensory and motor neocortex consisting of 704 spiking model neurons. Sensory and motor populations included excitatory cells and two types of interneurons. Neurons were interconnected with AMPA/NMDA and GABAA synapses. We trained our model using spike-timing-dependent reinforcement learning to control a two-joint virtual arm to reach to a fixed target. For each of 125 trained networks, we used 200 training sessions, each involving 15 s reaches to the target from 16 starting positions. Learning altered network dynamics, with enhancements to neuronal synchrony and behaviorally relevant information flow between neurons. After learning, networks demonstrated retention of behaviorally relevant memories by using proprioceptive information to perform reach-to-target from multiple starting positions. Networks dynamically controlled which joint rotations to use to reach a target, depending on current arm position. Learning-dependent network reorganization was evident in both sensory and motor populations: learned synaptic weights showed target-specific patterning optimized for particular reach movements. Our model embodies an integrative hypothesis of sensorimotor cortical learning that could be used to interpret future electrophysiological data recorded in vivo from sensorimotor learning experiments. We used our model to make the following predictions: learning enhances synchrony in neuronal populations and behaviorally relevant information flow across neuronal populations, enhanced sensory processing aids task-relevant motor performance and the relative ease of a particular movement in vivo depends on the amount of sensory information required to complete the movement.

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Connectivity patterns shape sensory representation in a cerebellum-like network

10.1101/2021.02.10.430647 ◽

2021 ◽

Author(s):

Daniel Zavitz ◽

Elom A. Amematsro ◽

Alla Borisyuk ◽

Sophie J.C. Caron

Keyword(s):

Learning Outcomes ◽

Network Architecture ◽

Mushroom Body ◽

Structural Features ◽

Projection Neurons ◽

Sensory Representation ◽

Learning Function ◽

Kenyon Cells ◽

Connectivity Patterns ◽

Function Relationship

SUMMARYCerebellum-like structures are found in many brains and share a basic fan-out–fan-in network architecture. How the specific structural features of these networks give rise to their learning function remains largely unknown. To investigate this structure–function relationship, we developed a realistic computational model of an empirically very well-characterized cerebellum-like structure, the Drosophila melanogaster mushroom body. We show how well-defined connectivity patterns between the Kenyon cells, the constituent neurons of the mushroom body, and their input projection neurons enable different functions. First, biases in the likelihoods at which individual projection neurons connect to Kenyon cells allow the mushroom body to prioritize the learning of particular, ethologically meaningful odors. Second, groups of projection neurons connecting preferentially to the same Kenyon cells facilitate the mushroom body generalizing across similar odors. Altogether, our results demonstrate how different connectivity patterns shape the representation space of a cerebellum-like network and impact its learning outcomes.

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Mushroom Body of the Honeybee

Handbook of Brain Microcircuits ◽

10.1093/med/9780190636111.003.0029 ◽

2017 ◽

pp. 353-360

Author(s):

Jürgen Rybak ◽

Randolf Menzel

Keyword(s):

Mushroom Body ◽

Higher Order ◽

Insect Species ◽

Insect Brain ◽

Projection Neurons ◽

Kenyon Cells ◽

Output Neurons ◽

The Brain

The mushroom body (MB) in the insect brain is composed of a large number of densely packed neurons called Kenyon cells (KCs) (Drosophila, 2200; honeybee, 170,000). In most insect species, the MB consists of two caplike dorsal structures, the calyces, which contain the dendrites of KCs, and two to four lobes formed by collaterals of branching KC axons. Although the MB receives input and provides output throughout its whole structure, the neuropil part of the calyx receives predominantly multimodal input from sensory projection neurons (PNs) of second or a higher order, and the lobes send output neurons to many other parts of the brain, including recurrent neurons to the MB calyx. Widely branching, supposedly modulatory neurons (serotonergic, octopaminergic) innervate the MB at all levels (calyx, peduncle, and lobes), including the somata of KCs in the calyx (dopamine).

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Suppression of GABAergic neurons through D2-like receptor secures efficient conditioning in Drosophila aversive olfactory learning

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1812342116 ◽

2019 ◽

Vol 116 (11) ◽

pp. 5118-5125 ◽

Cited By ~ 12

Author(s):

Mingmin Zhou ◽

Nannan Chen ◽

Jingsong Tian ◽

Jianzhi Zeng ◽

Yunpeng Zhang ◽

...

Keyword(s):

Mushroom Body ◽

Olfactory Learning ◽

Gabaergic Inhibition ◽

Synaptic Connections ◽

Inhibitory System ◽

Kenyon Cells ◽

Synaptic Modification ◽

In Vivo Functional Imaging ◽

Negative Modulator

The GABAergic system serves as a vital negative modulator in cognitive functions, such as learning and memory, while the mechanisms governing this inhibitory system remain to be elucidated. In Drosophila, the GABAergic anterior paired lateral (APL) neurons mediate a negative feedback essential for odor discrimination; however, their activity is suppressed by learning via unknown mechanisms. In aversive olfactory learning, a group of dopaminergic (DA) neurons is activated on electric shock (ES) and modulates the Kenyon cells (KCs) in the mushroom body, the center of olfactory learning. Here we find that the same group of DA neurons also form functional synaptic connections with the APL neurons, thereby emitting a suppressive signal to the latter through Drosophila dopamine 2-like receptor (DD2R). Knockdown of either DD2R or its downstream molecules in the APL neurons results in impaired olfactory learning at the behavioral level. Results obtained from in vivo functional imaging experiments indicate that this DD2R-dependent DA-to-APL suppression occurs during odor-ES conditioning and discharges the GABAergic inhibition on the KCs specific to the conditioned odor. Moreover, the decrease in odor response of the APL neurons persists to the postconditioning phase, and this change is also absent in DD2R knockdown flies. Taken together, our findings show that DA-to-GABA suppression is essential for restraining the GABAergic inhibition during conditioning, as well as for inducing synaptic modification in this learning circuit. Such circuit mechanisms may play conserved roles in associative learning across species.

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