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Institute
- Theodor-Boveri-Institut für Biowissenschaften (93)
- Physikalisches Institut (92)
- Graduate School of Life Sciences (65)
- Klinik und Poliklinik für Nuklearmedizin (34)
- Medizinische Klinik und Poliklinik II (27)
- Institut für Psychologie (23)
- Klinik und Poliklinik für Psychiatrie, Psychosomatik und Psychotherapie (23)
- Institut für Anorganische Chemie (22)
- Institut für Virologie und Immunbiologie (16)
- Medizinische Klinik und Poliklinik I (16)
Sonstige beteiligte Institutionen
- Johns Hopkins School of Medicine (15)
- Johns Hopkins University School of Medicine (5)
- Department of Biomedical Imaging, National Cerebral and Cardiovascular Research Center, Suita, Japan (2)
- Division of Medical Technology and Science, Department of Medical Physics and Engineering, Course of Health Science, Osaka University Graduate School of Medicine, Suita Japan (2)
- Institut for Molecular Biology and CMBI, Department of Genomics, Stem Cell Biology and Regenerative Medicine, Leopold-Franzens-University Innsbruck, Innsbruck, Austria (2)
- International Max Planck Research School Molecular Biology, University of Göttingen, Germany (2)
- Johns Hopkins School of Medicine, The Russell H Morgan Department of Radiology and Radiological Science, Baltimore, MD, USA (2)
- ACC GmbH Analytical Clinical Concepts (1)
- BMBF (1)
- Boehringer Ingelheim Pharma GmbH & Co. KG (1)
ResearcherID
- J-8841-2015 (1)
The first part of the present work provides an insight into the chemistry of iridium complexes bearing the bis(phosphinite) pincer ligand tBuPOCOP (k3-C6H3-1,3-(OPtBu2)2) towards primary boranes and phosphines as well as phosphine-borane Lewis adducts. It furthermore encloses some more detailed studies on their application as catalyst for the dehydrogenative coupling of the latter compounds. The results presented herein can be divided into three sections:
I. synthesis and characterization of aryl dihydroborate ligated iridium(III) complexes
II. and aryl phosphine coordinated iridium(I) and dihydrido iridium(III) complexes,
III. as well as studies on the reactivity of the parent iridium pincer complexes towards BH3 adducts of primary phosphines, which led to first results in the homogeneous catalytic dehydrocoupling of P-aryl substituted phosphine boranes mediated by such iridium pincer complexes.
The second part of the present work provides an insight into the chemistry of cyclic (alkyl)(amino) carbene-stabilized nickel complexes as well as it encloses some more detailed studies on the properties and reactivity of the free carbenes itself. The results presented herein can be divided into four sections:
I. synthesis and characterization of cyclic (alkyl)(amino) carbene-stabilized nickel carbonyl complexes,
II. which allow the evaluation and quantification of the steric and electronic properties of these cyclic (alkyl)(amino) carbenes,
III. first studies on the reactivity of these novel nickel complexes, and
IV. investigations on C–F and C–H bond activation at the carbene center of cyclic (alkyl)(amino) carbenes.
West Africa is one of the fastest growing regions in the world with annual population growth rates of more than three percent for several countries. Since the 1950s, West Africa experienced a fivefold increase of inhabitants, from 71 to 353 million people in 2015 and it is expected that the region’s population will continue to grow to almost 800 million people by the year 2050. This strong trend has and will have serious consequences for food security since agricultural productivity is still on a comparatively low level in most countries of West Africa. In order to compensate for this low productivity, an expansion of agricultural areas is rapidly progressing. The mapping and monitoring of agricultural areas in West Africa is a difficult task even on the basis of remote sensing. The small scale extensive farming practices with a low level of agricultural inputs and mechanization make the delineation of cultivated land from other land cover and land use (LULC) types highly challenging. In addition, the frequent cloud coverage in the region considerably decreases the availability of earth observation datasets. For the accurate mapping of agricultural area in West Africa, high temporal as well as spatial resolution is necessary to delineate the small-sized fields and to obtain data from periods where different LULC types are distinguishable. However, such consistent time series are currently not available for West Africa. Thus, a spatio-temporal data fusion framework was developed in this thesis for the generation of high spatial and temporal resolution time series.
Data fusion algorithms such as the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) enjoyed increasing popularity during recent years but they have hardly been used for the application on larger scales. In order to make it applicable for this purpose and to increase the input data availability, especially in cloud-prone areas such as West Africa, the ESTARFM framework was developed in this thesis introducing several enhancements. An automatic filling of cloud gaps was included in the framework in order to use even partly cloud-covered Landsat images for the fusion without producing gaps on the output images. In addition, the ESTARFM algorithm was improved to automatically account for regional differences in the heterogeneity of the study region. Further improvements comprise the automation of the time series generation as well as the significant acceleration of the processing speed through parallelization. The performance of the developed ESTARFM framework was tested by fusing an 8-day NDVI time series from Landsat and MODIS data for a focus area of 98,000 km² in the border region between Burkina Faso and Ghana. The results of this test show the capability of the ESTARFM framework to accurately produce high temporal resolution time series while maintaining the spatial detail, even in such a heterogeneous and cloud-prone region.
The successfully tested framework was subsequently applied to generate consistent time series as the basis for the mapping of agricultural area in Burkina Faso for the years 2001, 2007, and 2014. In a first step, high temporal (8-day) and high spatial (30 m) resolution NDVI time series for the entire country and the three years were derived with the ESTARFM framework. More than 500 Landsat scenes and 3000 MODIS scenes were automatically processed for this purpose. From the fused ESTARFM NDVI time series, phenological metrics were extracted and together with the single time steps of NDVI served as input for the delineation of rainfed agricultural areas, irrigated agricultural areas and plantations. The classification was conducted with the random forest algorithm at a 30 m spatial resolution for entire Burkina Faso and the three years 2001, 2007, and 2014. For the training and validation of the classifier, a randomly sampled reference dataset was generated from Google Earth images based on expert knowledge of the region. The overall classification accuracies of 92% (2001), 91% (2007), and 91% (2014) indicate the well-functioning of the developed methodology. The resulting maps show an expansion of agricultural area of 91% from about 61,000 km² in 2001 to 116,900 km² in 2014. While rainfed agricultural areas account for the major part of this increase, irrigated areas and plantations also spread considerably. Especially the expansion of irrigation systems and plantation area can be explained by the promotion through various national and international development projects. The increase of agricultural areas goes in line with the rapid population growth in most of Burkina Faso’s provinces which still had available land resources for an expansion of agricultural area. An analysis of the development of agricultural areas in the vicinity of protected areas highlighted the increased human pressure on these reserves. The protection of the remnant habitats for flora and fauna while at the same time improving food security for a rapidly growing population, are the major challenges for the region in the future.
The developed ESTARFM framework showed great potential beyond its utilization for the mapping of agricultural area. Other large-scale research that requires a sufficiently high temporal and spatial resolution such as the monitoring of land degradation or the investigation of land surface phenology could greatly benefit from the application of this framework.
The present thesis considers the modelling of gas mixtures via a kinetic description. Fundamentals about the Boltzmann equation for gas mixtures and the BGK approximation are presented. Especially, issues in extending these models to gas mixtures are discussed. A non-reactive two component gas mixture is considered. The two species mixture is modelled by a system of kinetic BGK equations featuring two interaction terms to account for momentum and energy transfer between the two species. The model presented here contains several models from physicists and engineers as special cases. Consistency of this model is proven: conservation properties, positivity of all temperatures and the H-theorem. The form in global equilibrium as Maxwell distributions is specified. Moreover, the usual macroscopic conservation laws can be derived.
In the literature, there is another type of BGK model for gas mixtures developed by Andries, Aoki and Perthame, which contains only one interaction term. In this thesis, the advantages of these two types of models are discussed and the usefulness of the model presented here is shown by using this model to determine an unknown function in the energy exchange of the macroscopic equations for gas mixtures described in the literature by Dellacherie. In addition, for each of the two models existence and uniqueness of mild solutions is shown. Moreover, positivity of classical solutions is proven.
Then, the model presented here is applied to three physical applications: a plasma consisting of ions and electrons, a gas mixture which deviates from equilibrium and a gas mixture consisting of polyatomic molecules.
First, the model is extended to a model for charged particles. Then, the equations of magnetohydrodynamics are derived from this model. Next, we want to apply this extended model to a mixture of ions and electrons in a special physical constellation which can be found for example in a Tokamak. The mixture is partly in equilibrium in some regions, in some regions it deviates from equilibrium. The model presented in this thesis is taken for this purpose, since it has the advantage to separate the intra and interspecies interactions. Then, a new model based on a micro-macro decomposition is proposed in order to capture the physical regime of being partly in equilibrium, partly not. Theoretical results are presented, convergence rates to equilibrium in the space-homogeneous case and the Landau damping for mixtures, in order to compare it with numerical results.
Second, the model presented here is applied to a gas mixture which deviates from equilibrium such that it is described by Navier-Stokes equations on the macroscopic level. In this macroscopic description it is expected that four physical coefficients will show up, characterizing the physical behaviour of the gases, namely the diffusion coefficient, the viscosity coefficient, the heat conductivity and the thermal diffusion parameter. A Chapman-Enskog expansion of the model presented here is performed in order to capture three of these four physical coefficients. In addition, several possible extensions to an ellipsoidal statistical model for gas mixtures are proposed in order to capture the fourth coefficient. Three extensions are proposed: An extension which is as simple as possible, an intuitive extension copying the one species case and an extension which takes into account the physical motivation of the physicist Holway who invented the ellipsoidal statistical model for one species. Consistency of the extended models like conservation properties, positivity of all temperatures and the H-theorem are proven. The shape of global Maxwell distributions in equilibrium are specified.
Third, the model presented here is applied to polyatomic molecules. A multi component gas mixture with translational and internal energy degrees of freedom is considered. The two species are allowed to have different degrees of freedom in internal energy and are modelled by a system of kinetic ellipsoidal statistical equations. Consistency of this model is shown: conservation properties, positivity of the temperature, H-theorem and the form of Maxwell distributions in equilibrium. For numerical purposes the Chu reduction is applied to the developed model for polyatomic gases to reduce the complexity of the model and an application for a gas consisting of a mono-atomic and a diatomic gas is given.
Last, the limit from the model presented here to the dissipative Euler equations for gas mixtures is proven.
Purpose: Early identification of aggressive disease could improve decision-support in pancreatic neuroendocrine tumor (pNET) patients prior to peptide receptor radionuclide therapy (PRRT). The prognostic value of intratumoral textural features (TF) determined by baseline somatostatin receptor (SSTR)-PET before PRRT was analyzed.
Procedures: 31 patients with G1/G2 pNET were enrolled (G2, n=23/31). Prior to PRRT with [\(^{177}\)Lu]DOTATATE (mean, 3.6 cycles), baseline SSTR-PET/CT was performed. By segmentation of 162 (median per patient, 5) metastases, intratumoral TF were computed. The impact of conventional PET parameters (SUV\(_{mean/max}\)), imaging-based TF as well as clinical parameters (Ki67, CgA) for prediction of both progression-free (PFS) and overall survival (OS) after PRRT was evaluated.
Results: Within a median follow-up of 3.7y, tumor progression was detected in 21 patients (median, 1.5y) and 13/31 deceased (median, 1.9y). In ROC analysis, the TF Entropy, reflecting derangement on a voxel-by-voxel level, demonstrated predictive capability for OS (cutoff=6.7, AUC=0.71, p=0.02). Of note, increasing Entropy could predict a longer survival (>6.7, OS=2.5y, 17/31), whereas less voxel-based derangement portended inferior outcome (<6.7, OS=1.9y, 14/31). These findings were supported in a G2 subanalysis (>6.9, OS=2.8y, 9/23 vs. <6.9, OS=1.9y, 14/23). Kaplan-Meier analysis revealed a significant distinction between high- and low-risk groups using Entropy (n=31, p<0.05). For those patients below the ROC-derived threshold, the relative risk of death after PRRT was 2.73 (n=31, p=0.04). Ki67 was negatively associated with PFS (p=0.002); however, SUVmean/max failed in prognostication (n.s.).
Conclusions: In contrast to conventional PET parameters, assessment of intratumoral heterogeneity demonstrated superior prognostic performance in pNET patients undergoing PRRT. This novel PET-based strategy of outcome prediction prior to PRRT might be useful for patient risk stratification.
The aim of the book is to ground the logical origins of consciousness in what I have previously called the ‘minimal self’. The idea is that elementary forms of consciousness are logically dependent not, as is commonly assumed, on ownership of an anatomical brain or nervous system, but on the intrinsic reflexivity that defines minimal selfhood. The book seeks to trace the logical pathway by which minimal selfhood gives rise to the possible appearance of consciousness. It is argued that in specific circumstances it thus makes sense to ascribe elementary consciousness to certain predatory single-celled organisms such as amoebae and dinoflagellates as well as to some of the simpler animals. Such an argument involves establishing exactly what those specific circumstances are and determining how elementary consciousness differs in nature and scope from its more complex manifestations.
The control of energy homeostasis is of pivotal importance for all living organisms. In the last years emerged the idea that many stress responses that are apparently unrelated, are actually united by a common increase of the cellular energy demand. Therefore, the so called energy signaling is activated by many kind of stresses and is responsible for the activation of the general stress response. In Arabidopsis thaliana the protein family SnF1- related protein kinases (SnRK1) is involved in the regulation of many physiological processes but is more known for its involvement in the regulation of the energy homeostasis in response to various stresses. To the SnRK1 protein family belong SnRK1.1 (also known as KIN10), SnRK1.2 (KIN11), and SnRK1.3 (KIN12). SnRK1 exerts its function regulating directly the activity of metabolic enzymes or those of key transcription factors (TFs). The only TFs regulated by SnRK1 identified so far is the basic leucine zipper (bZIP) 63. bZIP63 belongs to the C group of bZIPs (C-bZIPs) protein family together with bZIP9, bZIP10, and bZIP25. SnRK1.1 phosphorylates bZIP63 on three amino acids residues, serine (S) 29, S294, and S300. The phosphorylation of tbZIP63 is strongly related to the energy status of the plant, shifting from almost absent during the normal growth to strongly phosphorylated when the plant is exposed to extended dark. bZIPs normally bind the DNA as dimer in order to regulate the expression of their target genes. C-bZIPs preferentially form dimers with S1-bZIPs, constituting the so called C/S1- bZIPs network. The SnRk1 dependent phosphorylation of bZIP63 regulates its activation potential and its dimerization properties. In particular bZIP63 shift its dimerization preferences according to its phosphorylation status. The non-phosphorylated form of bZIP63 dimerize bZIP1, the phosphorylates ones, instead, forms dimer with bZIP1, bZIP11, and bZIP63 its self. Together with bZIP63, S1-bZIPs are important mediator of part of the huge transcriptional reprogramming induced by SnRK1 in response to extended dark. S1-bZIPs regulate, indeed, the expression of 4'000 of the 10'000 SnRK1-regulated genes in response to energy deprivation. In particular S1-bZIPs are very important for the regulation of many genes encoding for enzymes involved in the amino acid metabolism and for their use as alternative energy source. After the exposition for some hours to extended dark, indeed, the plant make use of every energy substrate and amino acids are considered an important energy source together with lipids and proteins. Interestingly, S1- bZIPs regulate the expression of ETFQO. ETFQO is a unique protein that convoglia the electrons provenienti from the branch chain amino acids catabolism into the mitochondrial electron transport chain. The dimer formed between bZIP63 and bZIP2 recruits SnRK1.1 directly on the chromatin of ETFQO promoter. The recruitment of SnRK1 on ETFQO promoter is associated with its acetylation on the lysine 14 of the histone protein 3 (K14H3). This chromatin modification is normally asociated with an euchromatic status of the DNA and therefore with its transcriptional activation. Beside the particular case of the regulation of ETFQO gene, S1-bZIPs are involved in the regulation of many other genes activated in response of different stresses. bZIP1 is for example an important mediator of the salt stress response. In particular bZIP1 regulates the primary C- and N-metabolism. The expression of bZIP1, in response of both salt ans energy stress seems to be regulated by SnRK1, as it is the expression of bZIP53 and bZIP63.
Beside its involvement in the regulation of the energy stress response and salt response, SnRK1 is the primary activators of the lipids metabolism during see germination. SnRK1, indeed, controls the expression of CALEOSINs and OLEOSINs. Those proteins are very important for lipids remobilization from oil droplets. Without their expression seed germination and subsequent establishment do not take place because of the absence of fuel to sustain these highly energy costly processes, which entirely depend on the catabolism of seed storages.
Plant-associated fungi can affect the plants‘ interaction with herbivores and
other microorganisms. For example, many common forage grasses are infected
with Epichloë endophytes. The endophytes systemically colonize the aerial
parts of the plants. They produce bioprotective alkaloids that can negatively
affect insects and livestock feeding on the grasses, and interact with other
fungal species which living from the plants‘ nutrients. Environmental conditions
strongly influence Epichloë endophytes. Endophyte-mediated effects
on herbivores are more pronounced under increased temperatures and the
endophytes may benefit from land use in managed grasslands. Under the
framework of the large-scale German project “Biodiversity Exploratories”, I
investigated whether infection rates and alkaloid concentrations of Epichloë
festucae var. lolii in Lolium perenne (Chapter I) and Epichloë endophytes (E.
uncinata, E. siegelii) in Festuca pratensis (Chapter II) depend on land use and
season. Further I analysed, whether foliar fungal assemblages of L. perenne
are affected by the presence of Epichloë endophytes (Chapter IV).
Almost once a week broadcasts about earthquakes, hurricanes, tsunamis, or forest fires are filling the news. While oneself feels it is hard to watch such news, it is even harder for rescue troops to enter such areas. They need some skills to get a quick overview of the devastated area and find victims. Time is ticking, since the chance for survival shrinks the longer it takes till help is available. To coordinate the teams efficiently, all information needs to be collected at the command center. Therefore, teams investigate the destroyed houses and hollow spaces for victims. Doing so, they never can be sure that the building will not fully collapse while they
are inside. Here, rescue robots are welcome helpers, as they are replaceable and make work more secure. Unfortunately, rescue robots are not usable off-the-shelf, yet.
There is no doubt, that such a robot has to fulfil essential requirements to successfully accomplish a rescue mission. Apart from the mechanical requirements it has to be able to build
a 3D map of the environment. This is essential to navigate through rough terrain and fulfil manipulation tasks (e.g. open doors). To build a map and gather environmental information, robots are equipped with multiple sensors. Since laser scanners produce precise measurements and support a wide scanning range, they are common visual sensors utilized for mapping.
Unfortunately, they produce erroneous measurements when scanning transparent (e.g. glass, transparent plastic) or specular reflective objects (e.g. mirror, shiny metal). It is understood that such objects can be everywhere and a pre-manipulation to prevent their influences is impossible. Using additional sensors also bear risks.
The problem is that these objects are occasionally visible, based on the incident angle of the laser beam, the surface, and the type of object. Hence, for transparent objects, measurements might result from the object surface or objects behind it. For specular reflective objects, measurements might result from the object surface or a mirrored object. These mirrored objects are illustrated behind the surface which is wrong. To obtain a precise map, the surfaces need to
be recognised and mapped reliably. Otherwise, the robot navigates into it and crashes. Further, points behind the surface should be identified and treated based on the object type. Points behind a transparent surface should remain as they represent real objects. In contrast, Points behind a specular reflective surface should be erased. To do so, the object type needs to be classified. Unfortunately, none of the current approaches is capable to fulfil these requirements.
Therefore, the following thesis addresses this problem to detect transparent and specular reflective objects and to identify their influences. To give the reader a start up, the first chapters
describe: the theoretical background concerning propagation of light; sensor systems applied for range measurements; mapping approaches used in this work; and the state-of-the-art concerning detection and identification of transparent and specular reflective objects. Afterwards, the Reflection-Identification-Approach, which is the core of subject thesis is presented. It describes 2D and a 3D implementation to detect and classify such objects. Both are available as ROS-nodes. In the next chapter, various experiments demonstrate the applicability and reliability of these nodes. It proves that transparent and specular reflective objects can be detected and classified. Therefore, a Pre- and Post-Filter module is required in 2D. In 3D, classification is possible solely with the Pre-Filter. This is due to the higher amount of measurements. An
example shows that an updatable mapping module allows the robot navigation to rely on refined maps. Otherwise, two individual maps are build which require a fusion afterwards. Finally, the
last chapter summarizes the results and proposes suggestions for future work.
The Dual Olfactory Pathway in the Honeybee Brain: Sensory Supply and Electrophysiological Properties
(2018)
The olfactory sense is of utmost importance for honeybees, Apis mellifera. Honeybees use olfaction for communication within the hive, for the identification of nest mates and non-nest mates, the localization of food sources, and in case of drones (males), for the detection of the queen and mating. Honeybees, therefore, can serve as excellent model systems for an integrative analysis of an elaborated olfactory system.
To efficiently filter odorants out of the air with their antennae, honeybees possess a multitude of sensilla that contain the olfactory sensory neurons (OSN). Three types of olfactory sensilla are known from honeybee worker antennae: Sensilla trichoidea, Sensilla basiconica and Sensilla placodea. In the sensilla, odorant receptors that are located in the dendritic arborizations of the OSNs transduce the odorant information into electrical information. Approximately 60.000 OSN axons project in two parallel bundles along the antenna into the brain. Before they enter the primary olfactory brain center, the antennal lobe (AL), they diverge into four distinct tracts (T1-T4). OSNs relay onto ~3.000-4.000 local interneurons (LN) and ~900 projection neurons (PN), the output neurons of the AL. The axons of the OSNs together with neurites from LNs and PNs form spheroidal neuropil units, the so-called glomeruli. OSN axons from the four AL input tracts (T1-T4) project into four glomerular clusters. LNs interconnect the AL glomeruli, whereas PNs relay the information to the next brain centers, the mushroom body (MB) - associated with sensory integration, learning and memory - and the lateral horn (LH). In honeybees, PNs project to the MBs and the LH via two separate tracts, the medial and the lateral antennal-lobe tract (m/lALT) which run in parallel in opposing directions. The mALT runs first to the MB and then to the LH, the lALT runs first to the LH and then to the MB. This dual olfactory pathway represents a feature unique to Hymenoptera. Interestingly, both tracts were shown to process information about similar sets of odorants by extracting different features. Individual mALT PNs are more odor specific than lALT PNs. On the other hand, lALT PNs have higher spontaneous and higher odor response action potential (AP) frequencies than mALT PNs. In the MBs, PNs form synapses with ~184.000 Kenyon cells (KC), which are the MB intrinsic neurons. KCs, in contrast to PNs, show almost no spontaneous activity and employ a spatially and temporally sparse code for odor coding.
In manuscript I of my thesis, I investigated whether the differences in specificity of odor responses between m- and lALT are due to differences in the synaptic input. Therefore, I investigated the axonal projection patterns of OSNs housed in S. basiconica in honeybee workers and compared them with S. trichoidea and S. placodea using selective anterograde labeling with fluorescent tracers and confocal- microscopy analyses of axonal projections in AL glomeruli. Axons of S. basiconica-associated OSNs preferentially projected into the T3 input-tract cluster in the AL, whereas the two other types of sensilla did not show a preference for a specific glomerular cluster. T3- associated glomeruli had previously been shown to be innervated by mALT PNs. Interestingly, S. basiconica as well as a number of T3 glomeruli lack in drones. Therefore I set out to determine whether this was associated with the reduction of glomeruli innervated by mALT PNs. Retrograde tracing of mALT PNs in drones and counting of innervated glomeruli showed that the number of mALT-associated glomeruli was strongly reduced in drones compared to workers. The preferential projections of S. basiconica-associated OSNs into T3 glomeruli in female workers together with the reduction of mALT-associated glomeruli in drones support the presence of a female-specific olfactory subsystem that is partly innervated by OSNs from S. basiconica and is associated with mALT projection neurons. As mALT PNs were shown to be more odor specific, I suppose that already the OSNs in this subsystem are more odor specific than lALT associated OSNs. I conclude that this female-specific subsystem allows the worker honeybees to respond adequately to the enormous variety of odorants they experience during their lifetime.
In manuscript II, I investigated the ion channel composition of mALT and lALT PNs and KCs in situ. This approach represents the first study dealing with the honeybee PN and KC ion channel composition under standard conditions in an intact brain preparation. With these recordings I set out to investigate the potential impact of intrinsic neuronal properties on the differences between m- and lALT PNs and on the sparse odor coding properties of KCs. In PNs, I identified a set of Na+ currents and diverse K+ currents depending on voltage and Na+ or Ca2+ that support relatively high spontaneous and odor response AP frequencies. This set of currents did not significantly differ between mALT and lALT PNs, but targets for potential modulation of currents leading to differences in AP frequencies were found between both types of PNs. In contrast to PNs, KCs have very prominent K+ currents, which are likely to contribute to the sparse response fashion observed in KCs. Furthermore, Ca2+ dependent K+ currents were found, which may be of importance for coincidence detection, learning and memory formation.
Finally, I conclude that the differences in odor specificity between m- and lALT PNs are due to their synaptic input from different sets of OSNs and potential processing by LNs. The differences in spontaneous activity between the two tracts may be caused by different neuronal modulation or, in addition, also by interaction with LNs. The temporally sparse representation of odors in KCs is very likely based on the intrinsic KC properties, whereas general excitability and spatial sparseness are likely to be regulated through GABAergic feedback neurons.