Cellular-resolution population imaging reveals robust sparse coding in the Drosophila Mushroom Body

By Kyle S. Honegger, Robert A. A. Campbell, Glenn C. Turner. 2011

257 citations recorded by the source corpus.

Sensory stimuli are represented in the brain by the activity of populations of neurons. In most biological systems, studying population coding is challenging since only a tiny proportion of cells can be recorded simultaneously. Here we used two-photon imaging to record neural activity in the relatively simple Drosophila mushroom body (MB), an area involved in olfactory learning and memory. Using the highly sensitive calcium indicator GCaMP3, we simultaneously monitored the activity of >100 MB neurons in vivo (∼5% of the total population). The MB is thought to encode odors in sparse patterns of activity, but the code has yet to be explored either on a population level or with a wide variety of stimuli. We therefore imaged responses to odors chosen to evaluate the robustness of sparse representations. Different odors activated distinct patterns of MB neurons; however, we found no evidence for spatial organization of neurons by either response probability or odor tuning within the cell body layer. The degree of sparseness was consistent across a wide range of stimuli, from monomolecular odors to artificial blends and even complex natural smells. Sparseness was mainly invariant across concentrations, largely because of the influence of recent odor experience. Finally, in contrast to sensory processing in other systems, no response features distinguished natural stimuli from monomolecular odors. Our results indicate that the fundamental feature of odor processing in the MB is to create sparse stimulus representations in a format that facilitates arbitrary associations between odor and punishment or reward.

Subfields: Cellular and Molecular Neuroscience, Genetics, Sensory Systems

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Citations in the corpus

Re-evaluating circuit mechanisms underlying pattern separation (2019, positive): “Considerable evidence has now accumulated that the mushroom body employs ultrasparse coding, as studies using a variety of methods, including whole-cell recordings, tetrode recordings, and calcium imaging, all found that only around 5-10% of Kenyon cells were active upon odour presentation (Figure 3”
The neuronal architecture of the mushroom body provides a logic for associative learning (2014, background): “Odors activate sparse subpopulations of KCs distributed across the MB without spatial preference (Turner et al., 2008; Honegger et al., 2011; Campbell et al., 2013).”
Optimal degrees of synaptic connectivity (2017, unknown): “Although we chose the mixed-layer coding level based on available experimental estimates (Chadderton et al., 2004; Honegger et al., 2011), our conclusions do not depend strongly on this parameter (Figures 3C and 3D).”
Activity of Defined Mushroom Body Output Neurons Underlies Learned Olfactory Behavior in Drosophila (2015, background): “Each MB is comprised of 2,000 intrinsic Kenyon cells (KCs), and an individual odor is represented as activity in a sparse sub- set of these cells (Wang et al., 2004; Honegger et al., 2011).”
γ neurons mediate dopaminergic input during aversive olfactory memory formation in Drosophila (2012, unknown): “Because perception of pure chemical odors is thought to be represented as sparse responses in populations of KCs [29, 30], we wondered whether the sufficiency of g lobes as a site of DopR input could derive from odor choice if OCT and MCH by chance triggered mostly g lobes responses.”
Sparse, Decorrelated Odor Coding in the Mushroom Body Enhances Learned Odor Discrimination (2014, unknown): “n, left to right, given as number of brain hemispheres [number of flies]: 7 [5], 12 [8], 11 [10], 15 [12], 7, 6, 6, 6.”
A connectome of a learning and memory center in the adult Drosophila brain (2017, background): “Thus, only a small subset of KCs respond to a given sensory stimulus (Perez-Orive et al., 2002; Turner et al., 2008; Honegger et al., 2011; Murthy et al., 2008).”
Three Dopamine Pathways Induce Aversive Odor Memories with Different Stability (2012, background): “represented by a small subset of Kenyon cells [10,11,12], which are major intrinsic neurons of the MB and categorized into the a/ b, a’/b’ and c neurons (Figure 1A) [13].”
Neuronal mechanisms underlying innate and learned olfactory processing in Drosophila. (2019, background): “While PN 167 inputs to KCs respond broadly to odors [8], only 5-10% of KCs respond to each odor [51].”
The Drosophila Mushroom Body: From Architecture to Algorithm in a Learning Circuit. (2020, background): “In fact, it is possible to train animals by pairing the odor cue with direct activation of DANs (Aso et al. 2010, 2012; Burke & Waddell 2011; Claridge-Chang et al. 2009; Huetteroth et al. 2015; Liu et al. 2012; Schroll et al. 2006, Yamagata et al. 2015).”
Functional analysis of a higher olfactory center, the lateral horn (2012, background): “In sharp contrast to the sparse spiking observed in KCs, which are targets of the PNs in the MB (Perez-Orive et al., 2002; Stopfer et al., 2003; Ito et al., 2008; Turner et al., 2008; Honegger et al., 2011), LHNs typically fired spontaneously and showed strong responses to odors (Fig.”
Reward signal in a recurrent circuit drives appetitive long-term memory formation (2015, unknown): “The MB represents odors using a sparse subset of ∼2000 intrinsic neurons, Kenyon cells (KCs) (Turner et al., 2008; Aso et al., 2009; Honegger et al., 2011; Campbell et al., 2013).”