Antennal Lobe Processing Increases Separability of Odor Mixture Representations in the Honeybee

Deisig, Nina; Giurfa, Martín; Sandoz, Jean‐Christophe

doi:10.1152/jn.00342.2009

Cited by 98 publications

(130 citation statements)

References 43 publications

Supporting

Mentioning

119

Contrasting

Order By: Relevance

“…Please note that the 'model responses' correspond to firing rate, which may not map directly to Ca 2+ imaging data. Figure 4 (right) shows that the correlation between our model ORN and PN response patterns to different odours centred around 0.7, which agrees with experimental data [14], which shows that the correlation between ORN and AL activity is around 0.6-0.7. …”

Section: Response To Continuous Stimulisupporting

confidence: 86%

“…Biologically, responses of a sensory unit to a stimulus may differ greatly among individual animals due to factors like genetic heterogeneity and past learning experience. Moreover, many coding strategies are believed to be based on ensemble behaviours [2,3,14]. Therefore, we believe that reproducing the statistics of observed data, rather than detailed measurements of individual cells, is more useful when modelling sensory systems of animals in most circumstances.…”

Section: Discussionmentioning

confidence: 99%

“…In Section 2, we describe in details how our model was built. In Section 3, we show that our model reproduces key features of ORN and PN responses to continuous stimuli (3.1) and short pulses (3.2) observed in experimental work that was not considered when building the model [9,10,13,14]. In Section 4, we discuss the strength and limitations of our model and our plans for future work.…”

Section: Introductionmentioning

confidence: 88%

See 2 more Smart Citations

A Biophysical Model of the Early Olfactory System of Honeybees

Chan

Nowotny

2017

Neural Information Processing

View full text Add to dashboard Cite

Abstract. Experimental measurements often can only provide limited data from an animal's sensory system. In addition, they exhibit large trial-to-trial and animal-to-animal variability. These limitations pose challenges to building mathematical models intended to make biologically relevant predictions. Here, we present a mathematical model of the early olfactory system of honeybees aiming to overcome these limitations. The model generates olfactory response patterns which conform to the statistics derived from experimental data for a variety of their properties. This allows considering the full dimensionality of the sensory input space as well as avoiding overfitting the underlying data sets. Several known biological mechanisms, including processes of chemical binding and activation of receptors, and spike generation and transmission in the antennal lobe network, are incorporated in the model at a minimal level. It can therefore be used to study how experimentally observed phenomena are shaped by these underlying biophysical processes. We verified that our model can replicate some key experimental findings that were not used when building it. Given appropriate data, our model can be generalized to the early olfactory systems of other insects. It hence provides a possible framework for future numerical and analytical studies of olfactory processing in insects.

show abstract

Section: Response To Continuous Stimulisupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 88%

See 1 more Smart Citation

A Biophysical Model of the Early Olfactory System of Honeybees

Chan

Nowotny

2017

Neural Information Processing

View full text Add to dashboard Cite

show abstract

“…In the honey bee, the configural representation of odor compounds has been analyzed in calcium imaging studies of neural activity at different stages of the olfactory circuit (63,64). At the input to the AL (olfactory receptor neurons), olfactory compound representation is linear so that a compound is encoded as the sum of the representations of its odor components (63).…”

Section: Discussionmentioning

confidence: 99%

Neural substrate for higher-order learning in an insect: Mushroom bodies are necessary for configural discriminations

Devaud

Papouin

Carcaud

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

116

View full text Add to dashboard Cite

Learning theories distinguish elemental from configural learning based on their different complexity. Although the former relies on simple and unambiguous links between the learned events, the latter deals with ambiguous discriminations in which conjunctive representations of events are learned as being different from their elements. In mammals, configural learning is mediated by brain areas that are either dispensable or partially involved in elemental learning. We studied whether the insect brain follows the same principles and addressed this question in the honey bee, the only insect in which configural learning has been demonstrated. We used a combination of conditioning protocols, disruption of neural activity, and optophysiological recording of olfactory circuits in the bee brain to determine whether mushroom bodies (MBs), brain structures that are essential for memory storage and retrieval, are equally necessary for configural and elemental olfactory learning. We show that bees with anesthetized MBs distinguish odors and learn elemental olfactory discriminations but not configural ones, such as positive and negative patterning. Inhibition of GABAergic signaling in the MB calyces, but not in the lobes, impairs patterning discrimination, thus suggesting a requirement of GABAergic feedback neurons from the lobes to the calyces for nonelemental learning. These results uncover a previously unidentified role for MBs besides memory storage and retrieval: namely, their implication in the acquisition of ambiguous discrimination problems. Thus, in insects as in mammals, specific brain regions are recruited when the ambiguity of learning tasks increases, a fact that reveals similarities in the neural processes underlying the elucidation of ambiguous tasks across species.learning | configural learning | mushroom bodies | honey bee | Apis mellifera

show abstract

“…For in vivo optophysiological recordings (Joerges et al, 1997;Sachse and Galizia, 2002;Deisig et al, 2010), bees were immobilized individually in an opaque plastic chamber (see Fig. 8 A).…”

Section: Methodsmentioning

confidence: 99%

Neural Organization and Visual Processing in the Anterior Optic Tubercle of the Honeybee Brain

Mota¹,

Yamagata²,

Giurfa³

et al. 2011

J. Neurosci.

View full text Add to dashboard Cite

The honeybee Apis mellifera represents a valuable model for studying the neural segregation and integration of visual information. Vision in honeybees has been extensively studied at the behavioral level and, to a lesser degree, at the physiological level using intracellular electrophysiological recordings of single neurons. However, our knowledge of visual processing in honeybees is still limited by the lack of functional studies of visual processing at the circuit level. Here we contribute to filling this gap by providing a neuroanatomical and neurophysiological characterization at the circuit level of a practically unstudied visual area of the bee brain, the anterior optic tubercle (AOTu). First, we analyzed the internal organization and neuronal connections of the AOTu. Second, we established a novel protocol for performing optophysiological recordings of visual circuit activity in the honeybee brain and studied the responses of AOTu interneurons during stimulation of distinct eye regions. Our neuroanatomical data show an intricate compartmentalization and connectivity of the AOTu, revealing a dorsoventral segregation of the visual input to the AOTu. Light stimuli presented in different parts of the visual field (dorsal, lateral, or ventral) induce distinct patterns of activation in AOTu output interneurons, retaining to some extent the dorsoventral input segregation revealed by our neuroanatomical data. In particular, activity patterns evoked by dorsal and ventral eye stimulation are clearly segregated into distinct AOTu subunits. Our results therefore suggest an involvement of the AOTu in the processing of dorsoventrally segregated visual information in the honeybee brain.

show abstract

Antennal Lobe Processing Increases Separability of Odor Mixture Representations in the Honeybee

Cited by 98 publications

References 43 publications

A Biophysical Model of the Early Olfactory System of Honeybees

A Biophysical Model of the Early Olfactory System of Honeybees

Neural substrate for higher-order learning in an insect: Mushroom bodies are necessary for configural discriminations

Neural Organization and Visual Processing in the Anterior Optic Tubercle of the Honeybee Brain

Contact Info

Product

Resources

About