Neural Representations of Courtship Song in the Drosophila Brain

Acoustic communication in drosophilid flies is based on the production and perception of courtship songs, which facilitate mating. Despite decades of research on courtship songs and behavior in Drosophila, central auditory responses have remained uncharacterized. In this study, we report on intracellular recordings from central neurons that innervate the Drosophila antennal mechanosensory and motor center (AMMC), the first relay for auditory information in the fly brain. These neurons produce graded-potential (nonspiking) responses to sound; we compare recordings from AMMC neurons to extracellular recordings of the receptor neuron population [Johnston's organ neurons (JONs)]. We discover that, while steady-state response profiles for tonal and broadband stimuli are significantly transformed between the JON population in the antenna and AMMC neurons in the brain, transient responses to pulses present in natural stimuli (courtship song) are not. For pulse stimuli in particular, AMMC neurons simply low-pass filter the receptor population response, thus preserving low-frequency temporal features (such as the spacing of song pulses) for analysis by postsynaptic neurons. We also compare responses in two closely related Drosophila species, Drosophila melanogaster and Drosophila simulans, and find that pulse song responses are largely similar, despite differences in the spectral content of their songs. Our recordings inform how downstream circuits may read out behaviorally relevant information from central neurons in the AMMC

Sparse connectivity for MAP inference in linear models using sister mitral cells

Sensory processing is hard because the variables of interest are encoded in spike trains in a relatively complex way. A major goal in studies of sensory processing is to understand how the brain extracts those variables. Here we revisit a common encoding model in which variables are encoded linearly. Although there are typically more variables than neurons, this problem is still solvable because only a small number of variables appear at any one time (sparse prior). However, previous solutions require all-to-all connectivity, inconsistent with the sparse connectivity seen in the brain. Here we propose an algorithm that provably reaches the MAP (maximum a posteriori) inference solution, but does so using sparse connectivity. Our algorithm is inspired by the circuit of the mouse olfactory bulb, but our approach is general enough to apply to other modalities. In addition, it should be possible to extend it to nonlinear encoding models

Encoding of Mixtures in a Simple Olfactory System

Natural odors are usually mixtures; yet, humans and animals can experience them as unitary percepts. Olfaction also enables stimulus categorization and generalization. We studied how these computations are performed with the responses of 168 locust antennal lobe projection neurons (PNs) to varying mixtures of two monomolecular odors, and of 174 PNs and 209 mushroom body Kenyon cells (KCs) to mixtures of up to eight monomolecular odors. Single- PN responses showed strong hypoadditivity and population trajectories clustered by odor concentration and mixture similarity. KC responses were much sparser on average than those of PNs and often signaled the presence of single components in mixtures. Linear classifiers could read out the responses of both populations in single time bins to perform odor identification, categorization, and generalization. Our results suggest that odor representations in the mushroom body may result from competing optimization constraints to facilitate memorization (sparseness) while enabling identification, classification, and generalization

Fast odour dynamics are encoded in the olfactory system and guide behaviour

Odours are transported in turbulent plumes, which result in rapid concentration fluctuations1,2 that contain rich information about the olfactory scenery, such as the composition and location of an odour source2,3,4. However, it is unclear whether the mammalian olfactory system can use the underlying temporal structure to extract information about the environment. Here we show that ten-millisecond odour pulse patterns produce distinct responses in olfactory receptor neurons. In operant conditioning experiments, mice discriminated temporal correlations of rapidly fluctuating odours at frequencies of up to 40 Hz. In imaging and electrophysiological recordings, such correlation information could be readily extracted from the activity of mitral and tufted cells—the output neurons of the olfactory bulb. Furthermore, temporal correlation of odour concentrations5 reliably predicted whether odorants emerged from the same or different sources in naturalistic environments with complex airflow. Experiments in which mice were trained on such tasks and probed using synthetic correlated stimuli at different frequencies suggest that mice can use the temporal structure of odours to extract information about space. Thus, the mammalian olfactory system has access to unexpectedly fast temporal features in odour stimuli. This endows animals with the capacity to overcome key behavioural challenges such as odour source separation5, figure–ground segregation6 and odour localization7 by extracting information about space from temporal odour dynamics

Functional and anatomical specificity in a higher olfactory centre.

Most sensory systems are organized into parallel neuronal pathways that process distinct aspects of incoming stimuli. In the insect olfactory system, second order projection neurons target both the mushroom body, required for learning, and the lateral horn (LH), proposed to mediate innate olfactory behavior. Mushroom body neurons form a sparse olfactory population code, which is not stereotyped across animals. In contrast, odor coding in the LH remains poorly understood. We combine genetic driver lines, anatomical and functional criteria to show that the Drosophila LH has ~1400 neurons and >165 cell types. Genetically labeled LHNs have stereotyped odor responses across animals and on average respond to three times more odors than single projection neurons. LHNs are better odor categorizers than projection neurons, likely due to stereotyped pooling of related inputs. Our results reveal some of the principles by which a higher processing area can extract innate behavioral significance from sensory stimuli

Responses of Drosophila giant descending neurons to visual and mechanical stimuli

In Drosophila, the paired giant descending neurons (GDNs), also known as giant fibers, and the paired giant antennal mechanosensory descending neurons (GAMDNs), are supplied by visual and mechanosensory inputs. Both neurons have the largest cell bodies in the brain and both supply slender axons to the neck connective. The GDN axon thereafter widens to become the largest axon in the thoracic ganglia, supplying information to leg extensor and wing depressor muscles. The GAMDN axon remains slender, interacting with other descending neuron axons medially. GDN and GAMDN dendrites are partitioned to receive inputs from antennal mechanosensory afferents and inputs from the optic lobes. Although GDN anatomy has been well studied in Musca domestica, less is known about the Drosophila homolog, including electrophysiological responses to sensory stimuli. Here we provide detailed anatomical comparisons of the GDN and the GAMDN, characterizing their sensory inputs. The GDN showed responses to light-on and light-off stimuli, expanding stimuli that result in luminance decrease, mechanical stimulation of the antennae, and combined mechanical and visual stimulation. We show that ensembles of lobula columnar neurons (type Col A) and mechanosensory antennal afferents are likely responsible for these responses. The reluctance of the GDN to spike in response to stimulation confirms observations of the Musca GDN. That this reluctance may be a unique property of the GDN is suggested by comparisons with the GAMDN, in which action potentials are readily elicited by mechanical and visual stimuli. The results are discussed in the context of descending pathways involved in multimodal integration and escape responses

On the Analysis and Design of the Locust Olfactory System

The ~ 830 projection neurons (PNs) of the locust antennal lobe respond to odors with dense, odor-specific spatio-temporal activity patterns that are mapped via intrinsic and circuit properties into a sparse representation by the Kenyon cells of the mushroom body, which are in turn read out by the beta-lobe neurons (bLNs). In this thesis we present several analyses of this system. First, we describe metrics for quantifying the geometric properties of PN population responses in the full response space that verify the structures revealed by locally linear embedding. Second, we analyze the mixture responses of single PNs and find that in many cases the mixture response can be explained using one of the component responses. Grouping PNs by their single component preferences reveals a potentially simple substrate for olfactory computations. Third, we look for evidence of cycle-by-cycle decoding of PNs by KCs. We show that much of the variance in single KC responses can be explained using small numbers of PNs, and conversely, that PN odor response trajectories can be reconstructed using KC responses. Finally, in a theoretical / computational analysis, we assemble some of the basic biological facts about the locust olfactory system into an architecture for the online learning of arbitrary mappings from odors to valences

Strain sensitivity enhancement for the hole-drilling residual stresses measurement method

Two methods for enhancing the strain sensitivity of the hole-drilling method for measuring residual stress fields were examined in this thesis. Such enhanced strain sensitivity is important because it improves the accuracy of the residual stress evaluation. The first method involves enlarging the effective hole size by drilling a reverse taper hole. A simple practical technique for drilling reverse taper holes is described. The strain sensitivity for this new method is compared with that of the conventional hole-drilling method. Experimental results show excellent correspondence with theoretical results. The reasons for the sensitivity improvement are explained. The second method involves designing a 6-element strain gauge rosette. It is shown that the new 6-element rosette significantly enhances the strain sensitivity of the hole-drilling method. Experimental results show excellent agreement with predicted results. Moreover, it is shown that this new rosette improves the accuracy of the method concerning the measurement of the variation of residual stresses with depth.Applied Science, Faculty ofMechanical Engineering, Department ofGraduat