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

Szyszka, Paul; Ditzen, Mathias; Galkin, Alexander; Galizia, C. Giovanni; Menzel, Randolf

doi:10.1152/jn.00397.2005

Cited by 187 publications

(244 citation statements)

References 47 publications

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“…Therefore, the activity of the Kenyon cells KCs (see Fig. 2) appears to be heavily regulated and has been shown to generate sparse activity in Honeybees and Locust [94,95,96], which is consistent with the overwhelming predictions of associate memory and pattern recognition models [97,98,99,100,101,102,103,104,105,106,107].…”

Section: The Formation Of Memories In the Mushroom Bodiessupporting

confidence: 73%

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Learning pattern recognition and decision making in the insect brain

Huerta¹

2013

AIP Conference Proceedings

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Abstract. We revise the current model of learning pattern recognition in the Mushroom Bodies of the insects using current experimental knowledge about the location of learning, olfactory coding and connectivity. We show that it is possible to have an efficient pattern recognition device based on the architecture of the Mushroom Bodies, sparse code, mutual inhibition and Hebbian leaning only in the connections from the Kenyon cells to the output neurons. We also show that despite the conventional wisdom that believes that artificial neural networks are the bioinspired model of the brain, the Mushroom Bodies actually resemble very closely Support Vector Machines (SVMs). The derived SVM learning rules are situated in the Mushroom Bodies, are nearly identical to standard Hebbian rules, and require inhibition in the output. A very particular prediction of the model is that random elimination of the Kenyon cells in the Mushroom Bodies do not impair the ability to recognize odorants previously learned.

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Section: The Formation Of Memories In the Mushroom Bodiessupporting

confidence: 73%

“…The evidence of sparse code in the Calyx is found in the locust [95,96] and the honeybee [94,95]. The prevailing theoretical idea to make the code stable over time from the AL to the MB is using forward inhibition [142,106,96].…”

Section: Information Conservation In the Mushroom Bodiesmentioning

confidence: 99%

Learning pattern recognition and decision making in the insect brain

Huerta¹

2013

AIP Conference Proceedings

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“…Thus, generalization can be used as a tool to measure the perceived quality of a CS in relation to other test odors. If trace and delay conditioning engage different brain areas, as is the case in mammals (Woodruff-Pak and Disterhoft, 2008), one would expect differences in the perceived odor quality between trace and delay conditioning, because neural odor representations change over time (Galán et al, 2004) and along different processing levels of the olfactory pathway (Linster et al, 2005;Szyszka et al, 2005). We therefore asked whether the perceived odor quality differs between trace memory and delay conditioning (Fig.…”

Section: Trace and Delay Conditioning Share Basic Propertiesmentioning

confidence: 99%

“…For example, they convey information about the initial PN response only , just as an odor trace does. Normally, Kenyon cells' odor responses are short and go back to baseline within a few seconds, even in the presence of an odor (PerezOrive et al, 2002;Szyszka et al, 2005;Ito et al, 2008;Turner et al, 2008). However, during the pairing of an odor with a US (sucrose), odor-activated Kenyon cells become reactivated .…”

Section: Neural Substrate Of the Odor Trace: A Place For Kenyon Cells?mentioning

confidence: 99%

Mind the Gap: Olfactory Trace Conditioning in Honeybees

Szyszka¹,

Demmler²,

Oemisch³

et al. 2011

J. Neurosci.

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Trace conditioning is a form of classical conditioning, where a neutral stimulus (conditioned stimulus, CS) is associated with a following appetitive or aversive stimulus (unconditioned stimulus, US). Unlike classical delay conditioning, in trace conditioning there is a stimulus-free gap between CS and US, and thus a poststimulus neural representation (trace) of the CS is required to bridge the gap until its association with the US. The properties of such stimulus traces are not well understood, nor are their underlying physiological mechanisms. Using behavioral and physiological approaches, we studied appetitive olfactory trace conditioning in honeybees. We found that single-odor presentation created a trace containing information about odor identity. This trace conveyed odor information about the initial stimulus and was robust against interference by other odors. Memory acquisition decreased with increasing CS-US gap length. The maximum learnable CS-US gap length could be extended by previous trace-conditioning experience. Furthermore, acquisition improved when an additional odor was presented during the CS-US gap. Using calcium imaging, we tested whether projection neurons in the primary olfactory brain area, the antennal lobe, contain a CS trace. We found odor-specific persistent responses after stimulus offset. These post-odor responses, however, did not encode the CS trace, and perceived odor quality could be predicted by the initial but not by the post-odor response. Our data suggest that olfactory trace conditioning is a less reflexive form of learning than classical delay conditioning, indicating that odor traces might involve higher-level cognitive processes.

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“…Taken together these observations support the idea of a combinatorial labelled-line system. Recent studies of olfactory information processing in honey bees, conducted using optical imaging techniques, have provided considerable insight into the combinatorial aspect of odour representation not only in the ALs (Galizia et al 1999b;Joerges et al 1997;Sachse et al 1999), but also at the next level of integration, the Kenyon cells of the mushroom bodies of the brain (Szyszka et al 2005). Generally speaking, however, these studies have described the coding of floral odours rather than pheromones, leaving a large gap in our understanding of the neural bases of pheromoneelicited behaviours in the honey bee.…”

Section: H O W a R E 9 O D A S I G N A L S Processed In The Brain?mentioning

confidence: 99%

Queen mandibular pheromone: questions that remain to be resolved

Jarriault

Mercer

2012

Apidologie

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-The discovery of 'queen substance', and the subsequent identification and synthesis of key components of queen mandibular pheromone, has been of significant importance to beekeepers and to the beekeeping industry. Fifty years on, there is greater appreciation of the importance and complexity of queen pheromones, but many mysteries remain about the mechanisms through which pheromones operate. The discovery of sex pheromone communication in moths occurred within the same time period, but in this case, intense pressure to find better means of pest management resulted in a remarkable focusing of research activity on understanding pheromone detection mechanisms and the central processing of pheromone signals in the moth. We can benefit from this work and here, studies on moths are used to highlight some of the gaps in our knowledge of pheromone communication in bees. A better understanding of pheromone communication in honey bees promises improved strategies for the successful management of these extraordinary animals.queen mandibular pheromone / Apis mellifera / olfactory system / biogenic amines / juvenile hormone / ecdysteroids

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

Cited by 187 publications

References 47 publications

Learning pattern recognition and decision making in the insect brain

Learning pattern recognition and decision making in the insect brain

Mind the Gap: Olfactory Trace Conditioning in Honeybees

Queen mandibular pheromone: questions that remain to be resolved

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