Dinu Florin Albeanu - US grants

DESCRIPTION (provided by applicant): The brain encodes sensory inputs as patterns of neuronal activity. While stimuli in the environment can vary over several orders of magnitude, neuronal responses cannot scale infinitely and span a limited range of outputs. Thus, a fundamental problem in sensory encoding lies in the trade-off between maintaining responsiveness to a wide range of intensities and resolving subtle variations in a stimulus. To overcome this challenge, sensory systems need to tune their output in order to match the average variation in input intensity. One way to achieve this is by proportionately changing the slope (gain) of the input-output function of individual neurons to increase or decrease the dynamic range of the outputs. This process is called gain control and has been shown to be implemented via normalization mechanisms in the auditory and visual systems. In the olfactory system, less is understood regarding how odors are reliably identified despite huge variations in their concentration. Several possible mechanisms have been suggested to contribute to olfactory gain control, ranging from local inhibition via interneurons that regulate the firing of he olfactory bulb's outputs, to feedback signals to the bulb from the olfactory cortex or the brainstem, or local processing in the cortex itself. In this proposal, we will study a particular class of neurons called short axon cells (SA cells) that are best suited anatomically and physiologically to implement gain control in this early olfactory circuit. We will test whether removing the contribution of these cells in the intact brain narrows the response spectrum of the output neurons of the bulb (mitral/tufted cells, M/T) across odors and concentrations. To this end, we will first characterize responses of SA cells to a large set of odors and concentrations. We will use genetic targeting to express optical indicators of neuronal activity specifically in th SA cells and monitor odor triggered responses via wide-field and multiphoton imaging. Then, using a similar approach, we will express light-gated (optogenetic) switches of neuronal activity in SA cells and use patterned optical illumination to suppress their activity in a controlled and reversible fashion. Simultaneously, we will present odor stimuli and monitor the response of M/T cells via electrophysiological recordings. We will compare M/T responses to increasing odor concentrations both in the presence and absence of SA inputs. Alterations in the concentration response curve of M/T cells upon light-induced inhibition of SA cells will directly reveal the contribution (if any) of SA cells. Finally, we will begin to dissect the specific mechanisms by which SA cells modulate M/T activity. These cells are known to be the only source of the neurotransmitter dopamine in the bulb. We will determine the contribution of dopamine in mediating SA to M/T cell communication by using blockers of dopamine activity. We will determine whether blocking dopamine action can reverse the effects on M/T cell activity observed upon optogenetic manipulation of SA cells.

A central goal of systems neuroscience is to describe behaviors in terms of the neuronal circuits that control them. This constitutes a monumental challenge in the mammalian brain because behaviors are thought to rely on widely distributed neural representations, which are technically difficult to monitor at large scales or to manipulate at cellular resolution. This research will implement, optimize, and ultimately broadly distribute via online repositories and workshops, a three-dimensional, two-photon microscope, exploiting patterned illumination strategies for fast manipulation and monitoring of large neuronal populations in behaving animals. First, the PI will implement and optimize a dual photo-stimulation system to enable both precise two-dimensional illumination across wide fields of view using a digital micro-mirror device, as well as high-resolution three-dimensional stimulation using digital holography. Photo-stimulation will be combined with two photon resonant scanning imaging to achieve fast sampling rate of hundreds of neurons across large brain volumes. Second, these technologies will be demonstrated for in vivo use, in head-fixed behaving rodents, optimizing their applicability for experimental use. This approach will enable dynamic testing of the functional roles of arbitrary neurons and combinations of choice in behaving rodents.

This project will develop and implement innovative optical methods for fine patterned stimulation of nervous systems and other excitable biological tissues. The approach will exploit current light-sensitive ion channels that can be inserted into neurons using the techniques of optogenetics. The planed optical illumination methods will, for the first time, allow fine spatial control and monitoring of brain activity. Further, these developments will provide new applications for high-resolution three-dimensional optical control of intra- and inter-cellullar signaling processes in any optically accessible tissue, greatly broaden their applicability in biological research and bioengineering. The project will result in broad distribution among interested scientists of all the methods developed. In addition, the results will be used to increase the awareness among the general public of the relevance of applied optics to daily life. These goals will be achieved through a concerted outreach program including optical imaging courses in Cold Spring Harbor Laboratory, volunteering internships, and lectures to local schools in Long Island and New York City.

? DESCRIPTION (provided by applicant): All sensory circuits, including the olfactory system, ascend from the sensory periphery to higher brain areas where stimuli are represented in sparse, stimulus-specific activity patterns. This sparse format is useful for accurate memory formation and retrieval. However, these specific signals must converge at some downstream site, given the limited numbers of motor neurons that represent the ultimate output of the circuit. We know very little about sensory processing downstream of sparse representations, on the converging side of neural networks. The Drosophila mushroom body (MB) has been an important model system for studying sparse representations in the olfactory system. New genetic labeling tools have revealed that the 2000 Kenyon cells (KCs) of the MB converge down onto a total of only 35 MB Output Neurons (MBONs). We will use these new tools to target MBONs for both electrophysiological recordings and calcium imaging, to examine nearly the entire layer of the network where the transition from sensory to motor begins. Using imaging to get a population-level view of activity patterns, we will determine how odor representations are reformatted as the circuit transitions from KCs to MBONs. Many of the MBONs are uniquely identifiable using these genetic labels. This enables us to compare their response properties of the same neuron across flies that have had different types of olfactory experience, to examine how plasticity shapes odor representations at this layer. Additionally, the neuromodulator dopamine is thought to play an important role in signal transmission across the KC-MBON synapse. By optogenetically controlling these specific dopaminergic inputs, we can examine how this neuromodulator regulates the flow of olfactory information across this layer of the circuit. Insights from this work will provide an important conceptual framework to understand how sensory perception is turned into action, and potentially contribute to our understanding of how sensory-motor coupling is impaired in disease states such as Parkinson's.

? DESCRIPTION (provided by applicant): Sensory circuits integrate inputs from the environment, as well as feedback signals from higher brain regions. The interplay of feed-forward and feedback signals is proposed to be fundamental for processing behaviorally relevant information related to expectation, reward, attention and action, during learning and memory recall. Though rich glutamatergic cortical feedback projections innervate inhibitory interneurons in all olfactory bulb layers, to date their specific dynamics and contribution to olfactory processing remains largely unknown. Using multiphoton imaging of GCaMP5 signals in awake head-fixed mice, the Albeanu group recently established that, in response to a diverse panel of odors and across concentrations, corticalbulbar feedback is sparse, odor selective, long-lasting post stimulus offset, spatially diverse and carried by two largely independent bouton/fiber types. Here, the PI, Albeanu, will test the central hypothesis that, in awake mice, cortical feedback contextually modulates inhibitory micro-circuits in the olfactory bulb to enhance discriminability of behaviorally relevant odors. Mechanistically, Dr. Albeanu's group proposes that cortico-bulbar projections respond specifically to stimulus identity and concentration by increasing the odor responsiveness of inhibitory interneurons and de-correlating the responses of mitral/tufted cells to different odors, and that these feedback effect are tuned by odor learning. Aim 1: Suppress olfactory cortex activity pharmacologically or optogenetically, while monitoring its effects on the dynamics of two classes of interneurons in the bulb - the granule cells, and the deep short axon - on the mitral cells, the bulb outputs via multiphoton imaging. To achieve further specificity, suppress cortical feedback boutons locally in the bulb while monitoring their targets in the bulb. Aim 2: Investigate how cortical feedback changes pre- versus post-acquisition of olfactory discrimination tasks and multisensory reversal learning paradigms. Train head-fixed mice in simple olfactory go-no go and two forced choice tasks, monitor the cortical feedback, and compare the correlations between learned and unfamiliar odors before and after training, as well as responses to the same sensory stimuli under different contingencies. Aim 3: Assess the effects of cortical feedback suppression on behavioral performance in olfactory sensory discrimination and reverse learning tasks, and on the responses of granule cells, deep short axon cells and mitral cells via monitoring GCaMP6 signals. The following hypotheses will be tested: (1) cortical feedback binds recent activity patterns in the piriform cortex to ongoing sensory inputs in the olfactory bulb and modulates mitral cell representations to facilitate the identification of behaviorally relevant odors, and (2 cortical feedback broadcasts contextual signals that are used by the olfactory bulb output to help identify rewarded stimuli.

This project makes use of recent advances in optical imaging and optogenetic strategies to monitor the brain at work. Specifically, the project is focused on understanding the interplay between ascending and descending (feedback) activity patterns in the olfactory system of behaving mice. Here, the investigator does not simply focus on the olfactory sensory module that integrates and transmits information from the nose to the brain but determines how higher brain areas, namely, the olfactory cortex, interact in the recurrent processing loop. This strategy enables the investigator to evaluate how sensory inputs are shaped by internal brain states via feedback. Furthermore, the investigator works at the interface of two approaches by combining cutting-edge experimental approaches--optical imaging and optogenetic strategies-- with novel computational models that give rise to non-mutually exclusive testable predictions. The investigator determines whether these feedforward-feedback loops contribute to attention states, extraction of odor identity, or broadcasting of predictions and error signals related to the incoming odorants. Experimental techniques are complemented, through an international collaboration, with state-of-the-art data analysis that characterizes neuronal population dynamics along high-dimensional trajectories and measures occurrence of activity patterns, characteristic timescales, patterns interaction, and coordination as a function of behavior. Additionally, the project provides opportunities for students and postdoctoral trainees from the USA and Romania to expand their experimental and computational skills through their participation in the international collaboration.

A central goal of systems neuroscience is to describe behaviors in terms of the neuronal circuits that control them. This constitutes a steep challenge in the mammalian brain, because behaviors are thought to rely on widely distributed feedforward, as well as top-down feedback neural representations, which are technically difficult to monitor at large scales and manipulate at cellular resolution. The project builds on recent experimental results from the lead investigator and novel algorithms for odor identification developed by the international collaborator. Specifically, the project probes the fine structure of olfactory perception and tests the central hypothesis that feedback serves one or more of the following three mechanisms: predictive coding, attractor generation, or attention to enhance the discriminability of behaviorally relevant stimuli. The dynamics of: a) cortical-bulbar feedback, and b) olfactory bulb output neurons on which feedback acts indirectly via interneurons are monitored and subsequently modulated with cellular resolution in mice engaged in olfactory discrimination forced-choice tasks and contextual reversal learning tasks. Reversible optogenetic local suppression of cortical feedback in the olfactory bulb is combined with simultaneous two-photon resonant scanning imaging (100 Hz) of hundreds of neurons. To address the proposed feedback roles, specific experimental design is combined with machine learning tools and dynamical systems analysis.

Producing behavior is the brain's principal function. While a technological revolution in systems neuroscience yielded a broad array of tools to observe and manipulate neural circuits, behavioral technologies have lagged behind. The problem of behavioral measurement and description is as complex as behaviors are diverse. To study behavior, laboratories employ complex behavioral systems, often in combination with custom-made hardware and software, and use these to define the tasks animals are required to learn and perform. As a consequence, the descriptions of behavioral tasks are tied to the hardware of each system, and there is no general, abstract description format to bridge across laboratories employing different systems. Building on insights from computer science, computational linguistics, and psychology, the goal of this project is to develop a formal language to describe behavioral tasks. This new behavioral task description language enhances accurate task design, improves reproducibility of existing tasks, enables widespread sharing and publication of task descriptions, and supports cross-system implementation. The project has broad benefits for improving scientific rigor and reproducibility in behavioral neuroscience. Moreover, the project reduces a significant barrier to sophisticated behavioral neuroscience experiments, putting them within reach of undergraduate class projects, and exposing students to a highly interdisciplinary approach, drawing on neuroscience, computer science, psychology, and linguistics.

The project entails the development of a formal computer language that can describe all laboratory behavioral tasks in a platform-independent manner. Currently, behavioral tasks are described largely with a combination of flowcharts and textual explanation, beyond the specific software codes used to control behavioral hardware. These descriptions do not provide formal accounts that ensure identical re-implementation or the rigorous comparison of similarly described paradigms. In addition, the hardware-bound codes tend hide the logic of behavioral tasks. The objective of this project is to design a new language, an extension to finite state machine descriptions, that can serve both as abstract illustrations for publications and also ready-to-run programs to control hardware. The new behavioral task description language builds on the class virtual finite state machines, a finite state machine extension framework that was developed to provide software specifications for real-time control systems. Additionally, the new task description language introduces ways to encapsulate common design motifs so they can be treated as primitives and additional features to define trial structures. The consistent high-level description enhances behavioral task design, distilling critical features into an easy-to-understand and formally rigorous structure. To demonstrate the use of this language, a turn-key implementation, including a graphical editor, is produced. In addition, templates for an array of commonly used behavioral tasks are produced. The platform-independent behavior description language exposes the underlying behavioral task logic and makes it easier to describe, reproduce, and share behavioral tasks across laboratories. This NeuroNex Innovation Award is part of the BRAIN Initiative and NSF's Understanding the Brain activities.

PROJECT SUMMARY We propose to develop a strategy for understanding olfactory coding by linking the molecular identity of odorant receptors (OR) to their odor sensitivities in vivo and discovering the logic of neural circuits that process smell. Unlike for other sensory modalities (i.e. vision, audition), it is not understood what properties of odorants are important for olfaction, how these properties are processed by olfactory neural circuits, and how odorant receptor genes have evolved to optimize such an encoding. The relationship between odorant structure (chemical space), the sequence of odorant receptors, the underlying spatial-temporal patterns of activity in the brain (neuronal space) and the perceived odor quality (perceptual space) has been elusive. An efficient method for connecting the olfactory sensory spaces will have a paradigm-shifting effect on olfactory research. Our multidisciplinary approach will use cutting edge next-generation sequencing technologies (FISSEQ, MAPseq and RNAseq) together with functional widefield fluorescence and two photon imaging in vivo to define the functional properties of olfactory sensory neurons that express defined odorant receptors (ORs), to discover their connections to individual glomeruli olfactory bulb (OB), second order OB output (mitral/tufted) cells and map their projection statistics to the downstream olfactory processing brain areas. Using these tools, we will map the identity and spatial layout of all 3,500 glomeruli in the mouse olfactory bulb according to the OR types from which they receive inputs. We will further link the molecular identity of ORs to their glomerular responses to hundreds of odorants (>500) in the form of OR/odorant binding affinity matrices across hundreds of glomeruli (~500) that are optically accessible in vivo. In the same samples, we will track thousands (>1,000/experiment) of individual olfactory bulb projections to their input glomeruli and their target brain areas by RNA-barcoding in relation to their tuning to odorants via multiphoton imaging in vivo. Our approach will bridge the gap between the molecular biology of ORs and neurophysiology and will usher in a new era of understanding the functional basis of olfaction. It will allow unprecedented resolution and throughput for determining OR-ligand interactions across hundreds of odorants, and the connectivity of tens of thousands of single neurons at once in a single specimen. The data obtained will enable the study of OR- ligand interactions, relate the chemical identity of odorants to olfactory perception, and the construction of artificial nose devices for immediate biomedical applications, including disease diagnostics.

SUMMARY To date, fundamental understanding of which features of odorants are decoded by the brain, and how information about these features is channeled through the olfactory system is still lacking. Odorants are sensed by the olfactory sensory neurons (OSNs) in the olfactory epithelium expressing specialized odorant receptors (ORs). Each OSN expresses one OR gene out of a species-dependent complement of hundreds of OR genes. OSN axons expressing the same OR type converge onto the same glomerulus on the olfactory bulb (OB) surface, forming a 2D map which is approximately stereotypical across individuals. Mitral/tufted cells (MTCs), the principal neurons of the OB are driven by inputs from glomeruli, as well as lateral and top-down signals. MTCs send their axons to higher olfactory processing centers, forming what is commonly assumed to be, highly distributed and largely random projection patterns. Computational models of olfactory processing are sensitive to the structure of the MTC projectome, with different models relying on different statistics of connections. Determining the structure of MTC connectivity is therefore of utmost importance for understanding the computational principles underlying olfactory information processing. However, to date, the structure of these projections across individuals remains uncharted territory, and information on the statistics of projections for ensembles of single MT neurons per individual is very limited, especially, in mammals. This is due to the low yield of imaging-based anatomical reconstruction strategies via sparse labeling of a small number of individual neurons per brain. To understand the logic and specificity of the MTC projectome, in this project, we will leverage the high throughput of state-of-the-art sequencing technologies, such as fluorescence in situ sequencing (FISSEQ) and a novel RNA barcoding sequencing-based method (MAPseq) in conjunction with in vivo functional imaging, modern computational technologies and theoretical tools. Preliminary data comprising of the brain-wide projections of hundreds of individual neurons supports the existence of specialized, non-random projection motifs that can be compared between animals. We will further investigate the structure of the brain-wide MTC projections and relate it to the MTC responses to large sets of odorants. We will share this data with the broader olfaction community and incorporate it into a computational network model of olfactory processing. The Specific Aims (SAs) of this project are: SA1. To determine the logic and specificity of individual mitral and tufted cells projections across the major target brain regions of the olfactory bulb. SA2. To investigate the structure of mitral and tufted cells' projectome within individual OB target brain regions. SA3. To understand the relationship between the bulb projectome and the odor responses of mitral and tufted cells.