Modelling the signal delivered by a population of first-order neurons in a moth olfactory system

A statistical model of the population of first-order olfactory receptor neurons (ORNs) is proposed and analysed. It describes the relationship between stimulus intensity (odour concentration) and coding variables such as rate and latency of the population of several thousand sex-pheromone sensitive ORNs in male moths. Although these neurons likely express the same olfactory receptor, they exhibit, at any concentration, a relatively large heterogeneity of responses in both peak firing frequency and latency of the first action potential fired after stimulus onset. The stochastic model is defined by a multivariate distribution of six model parameters that describe the dependence of the peak firing rate and the latency on the stimulus dose. These six parameters and their mutual linear correlations were estimated from experiments in single ORNs and included in the multidimensional model distribution. The model is utilized to reconstruct the peak firing rate and latency of the message sent to the brain by the whole ORN population at different stimulus intensities and to establish their main qualitative and quantitative properties. Finally, these properties are shown to be in agreement with those found previously in a vertebrate ORN population

Competition-based model of pheromone component ratio detection in the moth

For some moth species, especially those closely interrelated and sympatric, recognizing a specific pheromone component concentration ratio is essential for males to successfully locate conspecific females. We propose and determine the properties of a minimalist competition-based feed-forward neuronal model capable of detecting a certain ratio of pheromone components independently of overall concentration. This model represents an elementary recognition unit for the ratio of binary mixtures which we propose is entirely contained in the macroglomerular complex (MGC) of the male moth. A set of such units, along with projection neurons (PNs), can provide the input to higher brain centres. We found that (1) accuracy is mainly achieved by maintaining a certain ratio of connection strengths between olfactory receptor neurons (ORN) and local neurons (LN), much less by properties of the interconnections between the competing LNs proper. An exception to this rule is that it is beneficial if connections between generalist LNs (i.e. excited by either pheromone component) and specialist LNs (i.e. excited by one component only) have the same strength as the reciprocal specialist to generalist connections. (2) successful ratio recognition is achieved using latency-to-first-spike in the LN populations which, in contrast to expectations with a population rate code, leads to a broadening of responses for higher overall concentrations consistent with experimental observations. (3) when longer durations of the competition between LNs were observed it did not lead to higher recognition accuracy

Temporal Processing by Caenorhabditis elegans Sensory Neurons

Caenorhabditis elegans is a promising organism for trying to understand how nervous systems generate real-time behavior. Its low neuron count suggests that we may be able to observe all of the constituents of the computation of sophisticated sensorimotor behavior. However, its appropriateness as a system for quantitative dynamical study has yet to be established. We show that C. elegans chemosensory neurons can operate in a highly deterministic and low-noise mode, and they act as reliable linear filters of their input. We then use dynamical systems analysis in combination with classical genetic perturbation to uncover cellular and circuit mechanisms of temporal processing. This work should firmly establish C. elegans as a viable platform for applying quantitative dynamical systems methods to understanding how a nervous system processes sensory information, integrates it with an evolving internal state, and produces goal-directed, coordinated behavior

Olfactory learning in Drosophila

Animals are able to form associative memories and benefit from past experience. In classical conditioning an animal is trained to associate an initially neutral stimulus by pairing it with a stimulus that triggers an innate response. The neutral stimulus is commonly referred to as conditioned stimulus (CS) and the reinforcing stimulus as unconditioned stimulus (US). The underlying neuronal mechanisms and structures are an intensely investigated topic. The fruit fly Drosophila melanogaster is a prime model animal to investigate the mechanisms of learning. In this thesis we propose fundamental circuit motifs that explain aspects of aversive olfactory learning as it is observed in the fruit fly. Changing parameters of the learning paradigm affects the behavioral outcome in different ways. The relative timing between CS and US affects the hedonic value of the CS. Reversing the order changes the behavioral response from conditioned avoidance to conditioned approach. We propose a timing-dependent biochemical reaction cascade, which can account for this phenomenon. In addition to form odor-specific memories, flies are able to associate a specific odor intensity. In aversive olfactory conditioning they show less avoidance to lower and higher intensities of the same odor. However the layout of the first two olfactory processing layers does not support this kind of learning due to a nested representation of odor intensity. We propose a basic circuit motif that transforms the nested monotonic intensity representation to a non-monotonic representation that supports intensity specific learning. Flies are able to bridge a stimulus free interval between CS and US to form an association. It is unclear so far where the stimulus trace of the CS is represented in the fly's nervous system. We analyze recordings from the first three layers of olfactory processing with an advanced machine learning approach. We argue that third order neurons are likely to harbor the stimulus trace

Dynamical Modeling of the Moth Pheromone-Sensitive Olfactory Receptor Neuron within Its Sensillar Environment

In insects, olfactory receptor neurons (ORNs), surrounded with auxiliary cells and protected by a cuticular wall, form small discrete sensory organs – the sensilla. The moth pheromone-sensitive sensillum is a well studied example of hair-like sensillum that is favorable to both experimental and modeling investigations. The model presented takes into account both the molecular processes of ORNs, i.e. the biochemical reactions and ionic currents giving rise to the receptor potential, and the cellular organization and compartmentalization of the organ represented by an electrical circuit. The number of isopotential compartments needed to describe the long dendrite bearing pheromone receptors was determined. The transduction parameters that must be modified when the number of compartments is increased were identified. This model reproduces the amplitude and time course of the experimentally recorded receptor potential. A first complete version of the model was analyzed in response to pheromone pulses of various strengths. It provided a quantitative description of the spatial and temporal evolution of the pheromone-dependent conductances, currents and potentials along the outer dendrite and served to determine the contribution of the various steps in the cascade to its global sensitivity. A second simplified version of the model, utilizing a single depolarizing conductance and leak conductances for repolarizing the ORN, was derived from the first version. It served to analyze the effects on the sensory properties of varying the electrical parameters and the size of the main sensillum parts. The consequences of the results obtained on the still uncertain mechanisms of olfactory transduction in moth ORNs – involvement or not of G-proteins, role of chloride and potassium currents – are discussed as well as the optimality of the sensillum organization, the dependence of biochemical parameters on the neuron spatial extension and the respective contributions of the biochemical and electrical parameters to the overall neuron response

A Mechanism for Spatial Orientation Based on Sensory Adaptation in Caenorhabditis Elegans

During chemotaxis, animals compute spatial information about odor gradients to make navigational choices for finding or avoiding an odor source. The challenge to the neural circuitry is to interpret and respond to odor concentrations that change over time as animals traverse a gradient. In this thesis, I ask how a nervous system regulates spatial navigation by studying the chemotaxis response of Caenorhabditis elegans to diacetyl. A behavioral analysis demonstrated that AWA sensory neurons drive chemotaxis over several orders of magnitude in odor concentration, providing an entry point for dissecting the mechanistic basis of chemotaxis at the level of neural activity. Precise microfluidic stimulation enabled me to dissociate space from time in the olfactory input to characterize how odor sensing relates to behavior. I systematically measured neuronal responses to odor in the diacetyl chemotaxis circuit, aided by a newly developed imaging system with flexible stimulus delivery and elevated throughput. I found reliable sensory responses to the behaviorally relevant range of odor concentrations. I then followed odor-evoked activity to downstream interneurons that integrate sensory input. Adaptation of neuronal responses to odor yielded a highly sensitive response to small increases in odor concentration at the interneuron level, providing a mechanism for efficient gradient sensing during klinokinesis. Adaptation dynamics at the sensory level were stimulus-dependent and cell-autonomously altered in several classes of mutant animals. Behavioral responses to different concentrations of diacetyl resulted from overlapping contributions from multiple sensory neurons. AWA was specifically required for orientation behavior in response to small increases in odor concentration that are encountered in shallow gradients, demonstrating functional specialization amongst sensory neurons for stimulus characteristics. This work sheds light on an algorithm underlying acute behavioral computation and its biological implementation. The experimental results are presented in two parts: Chapter 2 describes the development of a microscope for high-throughput imaging of neuronal activity in Caenorhabditis elegans. I present a characterization of chemosensory responses to odor and its correlation with behavior. This work has been published (Larsch et al., 2013). Chapter 3 describes the functional architecture of the AWA chemosensory circuit and the role of adaptation in maintaining sensitivity over a wide range of stimulus intensities. This work is currently being prepared for publication

Odor coding and memory traces in the antennal lobe of honeybee

In dieser Arbeit werden zwei wesentliche neue Ergebnisse vorgestellt. Das erste bezieht sich auf die olfaktorische Kodierung und das zweite auf das sensorische Gedaechtnis. Beide Phaenomene werden am Beispiel des Gehirns der Honigbiene untersucht. In Bezug auf die olfaktorische Kodierung zeige ich, dass die neuronale Dynamik waehrend der Stimulation im Antennallobus duftspezifische Trajektorien beschreibt, die in duftspezifischen Attraktoren enden. Das Zeitinterval, in dem diese Attraktoren erreicht werden, betraegt unabhaengig von der Identitaet und der Konzentration des Duftes ungefaehr 800 ms. Darueber hinaus zeige ich, dass Support-Vektor Maschinen, und insbesondere Perzeptronen, ein realistisches und biologisches Model der Wechselwirkung zwischen dem Antennallobus (dem kodierenden Netwerk) und dem Pilzkoerper (dem dekodierenden Netzwerk) darstellen. Dieses Model kann sowohl Reaktionszeiten von ca. 300 ms als auch die Invarianz der Duftwahrnehmung gegenueber der Duftkonzentration erklaeren. In Bezug auf das sensorische Gedaechtnis zeige ich, dass eine einzige Stimulation ohne Belohnung dem Hebbschen Postulat folgend Veraenderungen der paarweisen Korrelationen zwischen Glomeruli induziert. Ich zeige, dass diese Veranderungen der Korrelationen bei 2/3 der Bienen ausreichen, um den letzten Stimulus zu bestimmen. In der zweiten Minute nach der Stimulation ist eine erfolgreiche Bestimmung des Stimulus nur bei 1/3 der Bienen moeglich. Eine Hauptkomponentenanalyse der spontanen Aktivitaet laesst erkennen, dass das dominante Muster des Netzwerks waehrend der spontanen Aktivitaet nach, aber nicht vor der Stimulation das duftinduzierte Aktivitaetsmuster bei 2/3 der Bienen nachbildet. Man kann deshalb die duftinduzierten (Veraenderungen der) Korrelationen als Spuren eines Kurzzeitgedaechtnisses bzw. als Hebbsche "Reverberationen" betrachtet werden.Two major novel results are reported in this work. The first concerns olfactory coding and the second concerns sensory memory. Both phenomena are investigated in the brain of the honeybee as a model system. Considering olfactory coding I demonstrate that the neural dynamics in the antennal lobe describe odor-specific trajectories during stimulation that converge to odor-specific attractors. The time interval to reach these attractors is, regardless of odor identity and concentration, approximately 800 ms. I show that support-vector machines and, in particular perceptrons provide a realistic and biological model of the interaction between the antennal lobe (coding network) and the mushroom body (decoding network). This model can also account for reaction-times of about 300 ms and for concentration invariance of odor perception. Regarding sensory memory I show that a single stimulation without reward induces changes of pairwise correlation between glomeruli in a Hebbian-like manner. I demonstrate that those changes of correlation suffice to retrieve the last stimulus presented in 2/3 of the bees studied. Succesful retrieval decays to 1/3 of the bees within the second minute after stimulation. In addition, a principal-component analysis of the spontaneous activity reveals that the dominant pattern of the network during the spontaneous activity after, but not before stimulation, reproduces the odor-induced activity pattern in 2/3 of the bees studied. One can therefore consider the odor-induced (changes of) correlation as traces of a short-term memory or as Hebbian reverberations

Neural Circuit Dependence of Acute and Subacute Nociception in C. Elegans

Nociception, the detection and avoidance of harmful cues, is a crucial system in all organisms. Animals use nociceptive systems to escape from substances that decrease survival, and can also modulate the threshold for avoidance behaviors to weigh the attractive features of an environment against its harmful features. To allow regulation, the nociception system of mammals incorporates multiple feedback and feedforward loops in its central and peripheral pathways. The nociception system of the roundworm Caenorhabditis elegans shares many features of the mammalian circuit. Both neural circuits feature a direct path from sensory neurons to motor neurons that is connected by a single class of interneuron, bypassing the higher processing centers. Both neural circuits also feature higher processing pathways that receive information from sensory neurons and provide further input onto the direct pathway. While the anatomical wiring of the C. elegans nervous system has been known for decades, how sensory neurons access different downstream paths in the circuit is less clear. One possible route of differential access of sensory input to downstream neurons is through different dynamics of activation. The temporal dimension of neural circuits cannot be deduced by anatomical wiring, but must be measured directly. In my thesis, I have characterized and manipulated the dynamic properties of a classical nociceptor in C. elegans, the polymodal sensory neuron ASH, and asked how these properties instruct downstream circuits and behavior. I thus first elucidated ASH calcium activation dynamics using simple step responses and using a newly developed systems identification approach for C. elegans. Using both long pulses and rapidly fluctuating “white noise” sequences of different nociceptive stimuli, I deduced their ASH activation profiles and linear temporal filters describing how the neuron summates the history of stimulus encounter. This analysis demonstrated that ASH calcium responses to natural stimuli include both linear features and multiple nonlinear components. Mutations in G protein-coupled sensory signaling disrupt both fast linear filtering and sustained responses to nociceptive stimuli. Mutations in a voltage gated calcium channel alter the temporal qualities of the ASH response in a pattern suggesting a role of this channel in sensory adaptation. In the course of these studies, I discovered several additional classes of sensory neurons that respond to nociceptive stimuli with robust calcium responses, even though past studies did not demonstrate a role for these neurons in nociceptive behavior. To gain experimental control over the dynamic activity that initiates nociceptive signaling, I ectopically expressed the pheromone receptors SRG-34 and SRG-36 in ASH and activated this system with their endogenous ligand, the ascaroside C3. ASH does not normally detect C3, but when it expresses either of these receptors it generates robust calcium responses to C3. These calcium signals have distinct temporal dynamics: SRG-34 mediated calcium signals are fast rising and fast adapting, while SRG-36 mediated calcium signals increase slowly during stimulation with little adaptation. Expression of SRG-34 or SRG-36 in ASH caused animals to avoid C3. Remarkably, time-aligned histograms of C3-induced avoidance behavior during stimulus onset, presence, and removal closely followed the dynamics of ASH calcium activity at these same time points, with a fast onset and adaptation for SRG-34 and a slow, sustained avoidance of SRG-36. ASH can directly activated the backward command motor neuron AVA or indirectly activate AVA through other neuronal pathways, including the intermediate interneuron AIB. Selectively silencing the AIB interneuron with the a chemical genetics system using the histamine-gated chloride channel resulted in complete loss of nociceptive avoidance behaviors induced by slow-ramping SRG-36 receptor in ASH, but had less of an effect on SRG-34 avoidance. Selectively silencing the AVA backward command interneuron reduced reversals, but spared or increased other avoidance behaviors for both SRG-34 and SRG-36. These results indicate that downstream interneurons are engaged in different ways, and to different degrees, depending on the mechanism of ASH activation. I next monitored the activity of AIB and AVA neurons in freely-moving ASH:srg-34 or ASH:srg-36 animals responding to C3. In ASH:srg-34 animals, AIB and AVA begin increasing activity upon C3 onset. In ASH:srg-36 worms, AIB increased activity before AVA. Together with my AIB silencing results, these observations suggest that AIB accumulates signals from ASH over time to promote AVA activity. Using a coherent type-1 feed forward loop with a calcium slope-determined AND or OR logic, I modeled features of AIB contribution to nociceptive behaviors in response to different ASH temporal dynamics. These findings suggest that feedforward excitation loops, a motif seen in C. elegans and mammalian nervous systems, can result in behaviorally-salient consequences in response to different sensory neuron calcium dynamics