64 research outputs found
Neural representation of a spatial odor memory in the honeybee mushroom body
Nawrot MP, D'Albis T, Menzel R, Strube-Bloss M. Neural representation of a spatial odor memory in the honeybee mushroom body. BMC Neuroscience. 2015;16(S1): P240
Calcium imaging revealed no modulatory effect on odor-evoked responses of the Drosophila antennal lobe by two populations of inhibitory local interneurons
Strube-Bloss M, Grabe V, Hansson BS, Sachse S. Calcium imaging revealed no modulatory effect on odor-evoked responses of the Drosophila antennal lobe by two populations of inhibitory local interneurons. Scientific Reports. 2017;7(1): 7854
Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris
Strube-Bloss M, Brown A, Spaethe J, Schmitt T, Rössler W. Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris. PLOS ONE. 2015;10(9): e0137413
Odor-Induced Multi-Level Inhibitory Maps in Drosophila
Optical imaging of intracellular Ca2+ influx as a correlate of neuronal excitation represents a standard technique for visualizing spatiotemporal activity of neuronal networks. However, the information-processing properties of single neurons and neuronal circuits likewise involve inhibition of neuronal membrane potential. Here, we report spatially resolved optical imaging of odor-evoked inhibitory patterns in the olfactory circuitry of Drosophila using a genetically encoded fluorescent Cl- sensor. In combination with the excitatory component reflected by intracellular Ca2+ dynamics, we present a comprehensive functional map of both odor-evoked neuronal activation and inhibition at different levels of olfactory processing. We demonstrate that odor-evoked inhibition carried by Cl- influx is present both in sensory neurons and second-order projection neurons (PNs), and is characterized by stereotypic, odor-specific patterns. Cl--mediated inhibition features distinct dynamics in different neuronal populations. Our data support a dual role of inhibitory neurons in the olfactory system: global gain control across the neuronal circuitry and glomerulus-specific inhibition to enhance neuronal information processing
Odor-Induced Multi-Level Inhibitory Maps in Drosophila
Grabe V, Schubert M, Strube-Bloss M, et al. Odor-Induced Multi-Level Inhibitory Maps in Drosophila. eNeuro. 2019;7(1): ENEURO.0213-19.2019
25th annual computational neuroscience meeting: CNS-2016
The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong
DuftspezifitÀt, AnwortzuverlÀssigkeit und Lerninduzierte PlastizitÀt
Table of contents Introduction: -1- I. Odor specificity and response
reliability of mushroom body extrinsic neurons in the honeybee: -16- II.
Recruitment and learning induced plasticity in alpha-lobe extrinsic neurons of
the honeybee: -52- III. Side-specific odor representation in alpha-lobe
extrinsic neurons: -86- General Discussion: -116- Summary: -130-
Zusammenfassung: -132- Danksagung: -134- Curriculum vitae: -136-Summary This thesis investigates odor learning in the mushroom body (MB) of
the honeybee Apis mellifera carnica. Using extra cellular long term recordings
of alpha lobe extrinsic neurons [ENs] that read out the information of the MB
were characterized and their changes during and after applying different
learning paradigms documented. The results allow conclusions about the MBs
role regarding learning and memory formation. At the level of the ENs the
information about the conditioned stimulus âCSâ (odor) and the unconditioned
stimulus âUSâ (sucrose reward) seems to be integrating into the bee brain. The
result is a stable stimulus specific response. Furthermore the level of
integrating the information of both brain sides into one compound is shown.
Chapter I addresses the general response properties of the ENs to repeated
odor stimulation. Single mushroom body-extrinsic neurons were recorded while
the bees have been exposed to repeated odor stimulations of 10 different
odors. The responses were characterized regarding their odor specificity and
their reliability. I can show that ENs are initially odor unspecific, meaning
that most of them respond to all of the 10 tested odors. When focusing on the
responses to the repetitions of one identical odor, it appears that ENs
respond rather unreliable. The results indicate that the neural population
activity at the level of the MB output does not reliably represent sensory
stimuli. Chapter II discussed the question if the properties characterized in
chapter 1 can be influenced by applying differential conditioning of two
odors, the forward-paired CS+ and the unpaired CS- and three control odors.
After conditioning the odors, two groups of neurons appeared. One group was
completely unaffected (âstereotypicâ). Units related to the other group showed
learning dependent plasticity. I found two types of âplasticâ units. One type
responded, before the subjects had built an association rather unreliable to
only a few different odors, meaning that they were more odor specific compared
to the stereotypic units. After the animals had built an association, 30 % of
these units were recruited to respond to the rewarded odor (CS+) more
reliable. Other plastic units were initially odor non-responding and started
to respond for different odors after the conditioning. These units started
already to respond during the overlap (coincidence) of the CS and the US.
Chapter III deals with the question, if the information of both MBs is
integrated at the level of the ENs. Side specific conditioning experiments
were performed during which the antennae of the bees received different input.
The differential conditioning of the odors, where one odor was presented
reinforced (CS+) and the other non reinforced (CS-), was always performed on
the contralateral side related to the recording position. Like in chapter II
also during the contra lateral conditioning I observed activity changes in the
recorded ENs if the CS and the US were presented overlapping, although I
recorded the activity of ENs of the contra lateral brain site, where the
antennae of the bees received no odor input. However, after three hours
resting time a stable and reliable representation of the different side
specific stimuli was established. Thus, the general properties described in
chapter I changed after differential odor conditioning as demonstrated in
chapter II. Also the conditioning at only one antennae recruits units and
changed the general response properties of the contralateral recorded ENs as
demonstrated in chapter III. The representation of the odor stimulus at the
output of the MB is laterally dissolved.Zusammenfassung Diese Arbeit untersucht das olfaktorische Lernen im Pilzkörper
der Honigbiene Apis mellifera carnica. Mittels extrazellulÀrer
Langzeitaufnahmen wurde die AktivitÀt von Alpha Lobus extrinsischen Neuronen
[EN], die den Ausgang des Pilzkörpers darstellen, gemessen. Die
Antworteigenschaften dieser Neurone wurden charakterisiert und ihre
VerÀnderungen wÀhrend und nach unterschiedlichen differentiellen
Konditionierungsexperimenten dokumentiert. Die Ergebnisse bestÀtigen, das auf
der Ebene der Pilzkörper der konditionierte Stimulus âCSâ (Duft) und der
unkonditionierte Stimulus âUSâ (Zuckerbelohnung) zusammengefĂŒhrt werden. Nach
der Konditionierung rufen die Stimulationen mit den gelernten und mit den
KontrolldĂŒften unterschiedliche Antworten in den EN hervor. Einige von ihnen
werden sogar rekrutiert um auf den assoziierten Duft zu antworten. Des
Weiteren konnte gezeigt werden, dass auf dieser neuronalen Ebene die
Information der beiden GehirnhÀlften zu einem seitenspezifischen Gesamtbild
zusammengefasst werden. In Kapitel I werden die allgemeinen
Antworteigenschaften der EN charakterisiert. Dazu wurden einzelne EN
elektrophysiologisch erfasst und ihre Antworten auf wiederholte Duftgaben
ausgewertet. Zehn unterschiedliche DĂŒfte wurden jeweils zehn mal getestet. Aus
den Wiederholungen jedes einzelnen Duftes wurden ZuverlÀssigkeits- indices
errechnet. AuĂerdem wurde ĂŒber die gepolten 10 Wiederholungen jedes Duftes
erfasst, ob der jeweilige Duft im mittel eine Antwort im abgeleiteten Neuron
hervorruft oder nicht. Daraus wurde ermittelt wie breit das Duftspektrum jedes
Neurons ist. Es stellte sich heraus, dass die meisten EN sehr unzuverlÀssig
und duftunspezifisch antworten. Daraus schlieĂe ich, dass diese Neurone nicht
an der Duftkodierung beteiligt sind, sondern andere Eigenschaften der
wahrgenommenen DĂŒfte vermitteln. In Kapitel II wurden differentielle
Konditionierungsexperimente durchgefĂŒhrt, um zu testen, ob die in Kapitel I
herausgearbeiteten Eigenschaften (unzuverlÀssige und duftunspezifische
Antworten) beeinflussbar sind. Dazu wurden fĂŒnf unterschiedliche DĂŒfte jeweils
zehnmal vor und nach der Konditionierung getestet. Zwischen den Tests wurden
zwei der fĂŒnf DĂŒfte fĂŒr eine differentielle Konditionierung benutzt. Dabei
wurde ein Duft belohnt (CS+) der andere unbelohnt (CS-) presentiert. Zwei
Hauptgruppen von EN lieĂen sich unterscheiden. Eine Gruppe von Neuronen
reagierte eher âstereotypâ, und lieĂen sich nicht durch das verwendete
Lernparadigma beeinflussen. In der anderen Gruppe, bestehend aus âplastischenâ
EN zeigte sich, dass die Duftspektren verĂ€nderbar sind und von den DĂŒften, die
wÀhrend der differentiellen Konditionierung verwendet wurden, dominiert sind.
30 % der plastischen neurone lieĂen sich durch den CS+ recrutieren. Auch die
ZuverlÀssigkeit der Neurone auf einen bestimmten Duft zu reagieren konnte
durch lernen beeinflusst werden. Auch hier scheinen die beiden konditionierten
DĂŒfte zu dominieren. In Kapitel III wird untersucht, wie die Information der
beiden Pilzkörper auf der Ebene der EN reprÀsentiert ist. Dazu wurden die
Antennen der Bienen rÀumlich getrennt und seitenspezifische Dufttests
durchgefĂŒhrt. Eine einseitige differentielle Konditionierung bei der einer der
DĂŒfte belohnt wurde (CS+) und der anderer nicht (CS-) wurde durchgefĂŒhrt, und
zwar an der contralateralen Antenne bezogen auf die Ableitposition. Nach dem
die Tiere drei Stunden ruhen konnten, wurden die DĂŒfte wieder auf beiden
Seiten getestet. Bei diesem Test zeigte sich, dass der belohnte Duft auf der
Seite gegeben, auf der er zuvor konditioniert worden war, zu einer Antwort im
contralateral aufgenommenen Neuron fĂŒhrte. Derselbe Duft auf der Seite
prÀsentiert, auf der er nicht konditioniert wurde (ipsilateral zur
Elektrodenposition) erzeugte keine Antwort, bzw. fĂŒhrte in einigen FĂ€llen
sogar zu einer Inhibition. Demnach wird auf der ebene der EN die LateralitÀt
des gelernten Duftes reprÀsentiert. Zusammenfassend lÀsst sich sagen, dass die
in Kapitel I beschriebenen allgemeinen Eigenschaften der EN (UnzuverlÀssigkeit
und UnspezifitÀt) durch lernen verÀndert werden können, wie Kapitel II zeigt.
Auch das Lernen mit nur einer Antenne fĂŒhrt dazu, dass Neurone der
contralateralen Seite rekrutiert werden und nach dem seitenspezifischen Lernen
die jeweiligen seitenspezifischen Stimuli zu unterschiedlicher AktivitÀt in
den EN fĂŒhren (siehe Kapitel III). Demnach scheint die LateralitĂ€t des der
gelernten DĂŒfte auf dieser neuronalen Ebene mit codiert zu sein
Multimodal integration and stimulus categorization in putative mushroom body output neurons of the honeybee
Strube-Bloss M, Rössler W. Multimodal integration and stimulus categorization in putative mushroom body output neurons of the honeybee. Royal Society Open Science. 2018;5(2): 171785.Flowers attract pollinating insects like honeybees by sophisticated compositions of olfactory and visual cues. Using honeybees as a model to study olfactoryâvisual 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 olfactoryâvisual 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 olfactoryâvisual information across MB input layers. In these neurons, representation of the olfactoryâvisual compound was significantly increased compared with that of single components, suggesting an additive, but nonlinear integration. Population analyses of olfactoryâvisual MBONs revealed three categories: (i) olfactory, (ii) visual and (iii) olfactoryâvisual 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.</jats:p
Serial correlation in neural spike trains: Experimental evidence, stochastic modeling, and single neuron variability
Farkhooi F, Strube-Bloss M, Nawrot MP. Serial correlation in neural spike trains: Experimental evidence, stochastic modeling, and single neuron variability. Physical Review E. 2009;79(2): 021905
Rapid encoding of stimulus-reward association in mushroom body output neurons of the honeybee.
Nawrot MP, Strube-Bloss M, Menzel R. Rapid encoding of stimulus-reward association in mushroom body output neurons of the honeybee. Frontiers in Computational Neuroscience. 2010;4
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