Biology subjects

Schaefer, A. T.

Publications and source records attributed to Schaefer, A. T..

At least 19 recordsLinked to original sources

bioRxiv2026

`Silent' mitral cells emerge from common feature subtraction

Whole-cell recordings from olfactory bulb mitral/tufted cells in awake mice revealed an inverse relationship between baseline activation and odour responses wherein cells that were spontaneously active tended to be inhibited by odours, while `silent' cells, quiet at baseline, tended to have vigorous odour responses. In this work we provide a normative explanation for these findings by extending previous sparse coding models of the olfactory system to include `common feature subtraction,' an odour-triggered variant of background subtraction in which the receptor contribution of features common to the odours being discriminated is subtracted. Using a circuit-level formulation of this computation consistent with the anatomy of the olfactory bulb we show how baseline activity cancels the effect of the common olfactory features on receptor activations, promoting inference of the target odours. We provide simulation results showing qualitative agreement with experimental findings. The model also predicts in closed form, without fitting, the slopes of the relationships between a cell's baseline and its common input and between its baseline and its odour response, and these predictions agree with simulations. Our model makes the experimentally testable prediction that a cell's baseline activation is not an intrinsic property, but reflects the negative of its recent activity.

neuroscience↗

bioRxiv2026

Decorrelation by gain control in the mouse olfactory bulb

Classifying sensory stimuli requires neural circuits to transform overlapping inputs into representations that are more distinct and decodable. Odour representations in the olfactory bulb (OB) have been reported to decorrelate from sensory input to output, a transformation thought to enhance odour separability. What has been missing is a systematic quantification of this transformation across odours, and a mechanistic account of how it can be implemented by OB circuitry. Using in vivo two-photon calcium imaging, we recorded glomerular input and output responses to a chemically diverse panel of 47 odours in mice. We observed a robust decorrelation of odour-evoked activity patterns from input to output: correlations between odour representations were consistently reduced, while overall response variance was preserved. This transformation increased the dimensionality of the population code and improved the separability of odour representations. Consistent with this, classification analyses showed that odour identity could be decoded with significantly higher accuracy at the output. To understand the mechanisms underlying this transformation, we developed a linear model of the OB with different levels of connectivity. Models in which each channel underwent only self-gain modulation reproduced the observed decorrelation nearly as well as models with fully unconstrained lateral connectivity. Analysis revealed that channels contributing unique information were selectively amplified, while redundant channels were attenuated. Together, our results show that the OB implements a measurable input-output transformation that enhances odour separability. By combining systematic recordings with computational modelling, we found that feedforward gain modulation serves as a simple and scalable mechanism capable of explaining the observed decorrelation, reframing how we understand the functional architecture of early olfactory processing.

neuroscience↗

bioRxiv2026

Decomposing representational drift across wake and sleep

Neural representations evolve over time, yet the relative contributions of online experience and offline states such as sleep remain unclear. Here, we recorded single-unit activity in the olfactory cortex of mice across cycles of awake odour exposure and sleep, and developed a low-rank decoder to track representational drift. We identified four orthogonal drift modes operating on distinct timescales, revealing that sleep and wake drive qualitatively different transformations, which indicates that offline reorganisation is not a simple continuation of online learning. Rather, sleep initiates an about-turn in the overall drift trajectory, which is uniquely characterised by a combination of decorrelation and rotation of odour representations. We also provide the first evidence for olfactory replay, occurring at ~2.5x temporal compression and associated with locally generated piriform cortex sharp waves. Together, these findings demonstrate that representational drift comprises state-dependent components, and reveal distinct contributions of wake and sleep to sensory representational change.

neuroscience↗

bioRxiv2025

Mice discriminate odour source distance via sub-sniff temporal features of odour plumes

Rodents rely on olfaction to navigate complex environments, particularly where visual cues are limited. Yet how they estimate the distance to an odour source remains unclear. The spatiotemporal dynamics of natural odour plumes, shaped by airflow turbulence, offer valuable cues for locating odour sources. Here, we show that mice can discriminate odour sources placed at different distances by extracting information from the sub-sniff temporal structure of naturalistic odour plumes. Using a wind tunnel and an olfactory virtual reality system, we generated dynamic plumes and demonstrated, through high-throughput automated behaviour, that mice distinguish near from far sources based on odour fluctuations operating faster than their respiratory cycle. Two-photon calcium imaging of olfactory bulb projection neurons revealed that distance-dependent responses are present in a small subset of mitral and tufted cells, and that population activity encodes source distance. Critically, neural responses correlated more strongly with high-frequency plume features than with mean odour concentration. Our results identify a neural basis for distance estimation from odour dynamics and highlight the importance of rapid temporal processing in mammalian olfaction.

neuroscience↗

bioRxiv2025

3D spatial transcriptomics reveals the molecular domain structure of the mouse olfactory bulb

A core organizing principle of the vertebrate brain is its symmetry along multiple axes. However, the precision with which neurons, circuit modules, and brain regions align to these axes remains poorly understood. Here, we used 3D spatial transcriptomics to reconstruct the anatomical and molecular organization of the mouse olfactory bulb. We mapped the positions of nearly one thousand molecularly distinct glomeruli, the structural and functional units of odor processing, revealing highly symmetric organization across hemispheres. Within each bulb, we delineated a curved axis of symmetry that divides pairs of sister glomeruli. Gene expression in the olfactory epithelium predicted glomerular position with near-glomerular resolution. However, glomerular symmetry did not extend to deeper layer mitral and granule cells, suggesting a reorganization from sensory input to cortical output pathways. Our findings provide the first comprehensive map of the olfactory bulb and reveal how its molecular structure is instructed by epithelial gene expression programs.

neuroscience↗

bioRxiv2025

Self-supervised image restoration in coherent X-rayneuronal microscopy

Coherent X-ray microscopy is emerging as a transformative technology for neuronal imaging, with the potential to offer a scalable solution for reconstruction of neural circuits in millimeter sized tissue volumes. Specifically, X-ray holographic nanoto-mography (XNH) brings together outstanding capabilities in terms of contrast, spatial resolution and data acquisition speed. While recent XNH developments already enabled generating valuable datasets for neuro-sciences, a major challenge for reconstruction of neural circuits remained overcoming resolving power limits to distinguish smaller neurites and synapses in the reconstructed volumes. Here we present a self-supervised image restoration approach that simultaneously improves spatial resolution, contrast, and data acquisition speed. This enables revealing synapses with XNH, marking a major milestone in the quest for generating connectomes of full mammalian brains. We demonstrate that this method is effective for various types of neuronal tissues and acquisition schemes. We propose a scalable implementation compatible with multi-terabyte image volumes. Altogether, this work brings large-scale X-ray nanotomography to a new precision level.

neuroscience↗

bioRxiv2024

Robust encoding of sub-sniff temporal information in the mouse olfactory bulb

SummaryThe sensory world is highly dynamic, and the temporal structure of stimuli contains rich information about the environment. Odour plumes are shaped by complex airflow that imprint information about the nature and spatial organisation of the olfactory environment onto their temporal dynamics. Whilst insects and mammals alike can discern high-frequency information, how temporal properties of the olfactory environment are represented in the brain remains largely unknown. Here, we presented temporally rich and systematically varying odour stimuli whilst electrically recording from the output neurons of the mouse olfactory bulb, mitral and tufted cells (MTC). We found that temporal aspects of odour stimuli could readily be read out from MTC responses, with a temporal resolution of up to 20 ms. Remarkably, temporal representation was virtually identical across three different odours. To understand which temporal features are encoded, we developed a single-cell model accurately describing both single-cell and population responses. Temporal receptive fields of MTCs translated between different odours, indicating that MTC tuning to odour quality and dynamics are partially separable. Together, this suggests a stereotypical representation of odour dynamics across projection neurons and can serve as an entry point into dissecting mechanisms underlying how information about the environment is extracted from temporally fluctuating odour plumes.

neuroscience↗

bioRxiv2024

Quantifying spectral information about source separation in multisource odour plumes

Odours released by objects in natural environments can contain information about their spatial locations. In particular, the correlation of odour concentration fields produced by two spatially separated sources contains information about the distance between the sources. Mice are able to distinguish correlated and anti-correlated odour fluctuations at frequencies up to 40 Hz. Can this high-frequency acuity support odour source localization? Here we answer this question by quantifying the spatial information about source separation contained in the spectral constituents of correlations. We used computational fluid dynamics simulations of multisource plumes in two-dimensional chaotic flow environments to generate temporally complex, covarying odour concentration fields. By relating the correlation of these fields to the spectral decompositions of the associated odour concentration timeseries, and making simplifying assumptions about the statistics of these decompositions, we derived analytic expressions for the Fisher information contained in the spectral components of the correlations about source separation. We computed the Fisher information for a broad range of frequencies and source separations and found that high frequencies were more informative than low frequencies when sources were close relative to the sizes of the large eddies in the flow. We observed a qualitatively similar effect in an independent set of simulations with different geometry, but not for surrogate data with a similar power spectrum to our simulations but in which all frequencies were a priori equally informative. Our work suggests that the high-frequency acuity of the murine olfactory system may support high-resolution spatial localization of odour sources. We also provide a model of the distribution of the spectral components of correlations that is accurate over a broad range of frequencies and source separations. More broadly, our work establishes an approach for the quantification of the spatial information in odour concentration timeseries.

biophysics↗

bioRxiv2022

Sample preparation and warping accuracy for correlative multimodal imaging in the mouse olfactory bulb using 2-photon, synchrotron X-ray and volume electron microscopy

Integrating physiology with structural insights of the same neuronal circuit provides a unique approach to understanding how the mammalian brain computes information. However, combining the techniques that provide both streams of data represents an experimental challenge. When studying glomerular column circuits in the mouse olfactory bulb, this approach involves e.g. recording the neuronal activity with in vivo 2-photon (2P) calcium imaging, retrieving the circuit structure with synchrotron X-ray computed tomography with propagation-based phase contrast (SXRT) and/or serial block-face electron microscopy (SBEM) and correlating these datasets. Sample preparation and dataset correlation are two key bottlenecks in this correlative workflow. Here, we first quantify the occurrence of different artefacts when staining tissue slices with heavy metals to generate X-ray or electron contrast. We report improvements in the staining procedure, ultimately achieving perfect staining in [~]67% of the 0.6 mm thick olfactory bulb slices that were previously imaged in vivo with 2P. Secondly, we characterise the accuracy of the spatial correlation between functional and structural datasets. We demonstrate that direct, single-cell precise correlation between in vivo 2P and SXRT tissue volumes is possible and as reliable as correlating between 2P and SBEM. Altogether, these results pave the way for experiments that require retrieving physiology, circuit structure and synaptic signatures in targeted regions. These correlative function-structure studies will bring a more complete understanding of mammalian olfactory processing across length scales and time.

neuroscience↗

bioRxiv2021

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. SummarySensory systems must infer latent variables from noisy and ambiguous input. MAP inference - choosing the most likely latent variable given the sensory input - is one of the simplest methods for doing that, but its neural implementation often requires all-to-all connectivity between the neurons involved. In common sensory contexts this can require a single neuron to connect to hundreds of thousands of others, which is biologically implausible. In this work we take inspiration from the sister mitral cells of the olfactory system - groups of neurons associated with the same input channel - to derive a method for performing MAP inference using sparse connectivity. We do so by assigning sister cells to random subsets of the latent variables and using additional cells to ensure that sisters correctly share information. We then derive the circuitry and dynamics required for the sister cells to compute the original MAP inference solution. Our work yields a biologically plausible circuit that provably solves the MAP inference problem and provides experimentally testable predictions. While inspired by the olfactory system, our method is quite general, and is likely to apply to other sensory modalities.

neuroscience↗

bioRxiv2021

Functional and multiscale 3D structural investigation of brain tissue through correlative in vivo physiology, synchrotron micro-tomography and volume electron microscopy

Attributing in vivo neurophysiology to the brains ultrastructure requires a large field of view containing contextual anatomy. Electron microscopy (EM) is the gold standard technique to identify ultrastructure, yet acquiring volumes containing full mammalian neural circuits is challenging and time consuming using EM. Here, we show that synchrotron X-ray computed tomography (SXRT) provides rapid imaging of EM-prepared tissue volumes of several cubic millimetres. Resolution was sufficient for distinguishing cell bodies as well as for tracing apical dendrites in olfactory bulb and hippocampus, for up to 350 m. Correlating EM with SXRT allowed us to associate dendritic spines on pyramidal cell apical dendrites in the stratum radiatum to their corresponding soma locations. Superficial pyramidal neurons had larger spine apparatus density compared to deeper ones, implying differential synaptic plasticity for superficial and deeper cells. Finally, we show that X-ray tomography and volume EM can be reliably correlated to prior in vivo imaging. Thus, combining functional measurements with multiscale X-ray microscopy and volume EM establishes a correlative workflow that enables functional and structural investigation of subcellular features in the context of cellular morphologies, tissues and ultimately whole organs.

neuroscience↗

bioRxiv2020

Coupling of mouse olfactory bulb projection neurons to fluctuating odour pulses

Odours are transported by turbulent air currents, creating complex temporal fluctuations in odour concentration. Recently, we have shown that mice can discriminate odour stimuli based on their temporal structure, indicating that information present in the temporal structure of odour plumes may be extracted by the mouse olfactory system. Here using in vivo electrophysiological recordings, we show that mitral and tufted cells (M/TCs), the projection neurons of the mouse olfactory bulb, can encode the dominant temporal frequencies present in odour stimuli up to frequencies of at least 20 Hz. We show that M/TCs couple their membrane potential to odour concentration fluctuations; coupling was variable between M/TCs but independent of the odour presented and with TCs displaying slightly elevated coupling compared to MCs in particular for higher frequency stimulation (20Hz). Pharmacologically blocking the inhibitory circuitry strongly modulated frequency coupling. Together this suggests that both cellular and circuit properties contribute to the encoding of temporal odour features in the mouse olfactory bulb.

neuroscience↗

bioRxiv2019

jULIEs: extracellular probes for recordings and stimulation in the structurally and functionally intact mouse brain

High signal-to-noise, scalable and minimally invasive recording and stimulation of the nervous system in intact animals is of fundamental importance to advance the understanding of brain function. Extracellular electrodes are among the most powerful tools capable of interfacing with large neuronal populations1-3. Neuronal tissue damage remains a major limiting factor in scaling electrode arrays, and has been found to correlate with electrode diameter across different electrode materials, such as microfabricated Michigan and Utah-style arrays4, MEMS and microsystems5, soft polymer or tungsten electrodes6 and Parylene C probes7. Small diameter ultramicroelectrodes (UMEs), while highly desirable, pose significant technical challenges such as reaching sufficient electrolyte-electrode coupling and limiting stray signal loss. To overcome these challenges, we have designed juxtacellular Ultra-Low Impedance Electrodes (jULIEs), a scalable technique for achieving high signal-to-noise electrical recordings as well as stimulation with UMEs. jULIEs are metal-glass composite UMEs thermally drawn to outer diameters (OD) of <25 {micro}m, with metal core diameters (ID) of as little as 1 {micro}m. We introduce a two-step electrochemical modification strategy that reduces UME coupling impedances by two orders of magnitude. Modifications enabled high signal-to-noise neural recordings in vivo through wires with micrometer scale core diameters. Histological and imaging experiments indicated that local vascular damage is minimal. Spikes reached amplitudes over 1 mV in vivo, indicating that recordings are possible in close proximity to intact neurons. Recording sites can be arranged in arbitrary patterns tailored to various neuroanatomical target structures and allowing parallel penetrations. jULIEs thus represent a versatile platform that allows for reliable recording and manipulation of neural activity in any areas of the functionally intact mammalian brain.

neuroscience↗

bioRxiv2019

Massively Parallel Microwire Arrays Integrated with CMOS chips for Neural Recording

Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.

neuroscience↗

bioRxiv2019

Mammalian olfaction is a high temporal bandwidth sense

Odours are transported in turbulent plumes resulting locally in highly fluctuating odour concentration (Celani et al., 2014; Murlis et al., 1992; Mylne and Mason, 1991; Shraiman and Siggia, 2000). Yet, whether mammals can make use of the ensuing temporal structure (Celani et al., 2014; Crimaldi and Koseff, 2001; Murlis et al., 1992; Mylne and Mason, 1991; Schmuker et al., 2016; Vickers, 2000) to extract information about the olfactory environment remains unknown. Here, we use dual-energy photoionisation recording with >300 Hz bandwidth to simultaneously determine odour concentrations of two odours in air. We show that temporal correlation of odour concentrations reliably predicts whether odorants emerge from the same or different sources in normal turbulent environments outside and in laboratory conditions. To replicate natural odour dynamics in a reproducible manner we developed a multichannel odour delivery device allowing presentation of several odours with 10 ms temporal resolution. Integrating this device in an automated operant conditioning system we demonstrate that mice can reliably discriminate the correlation structure of odours at frequencies of up to 40 Hz. Consistent with this finding, output neurons in the olfactory bulb show segregated responses depending on the correlation of odour stimuli with populations of 10s of neurons sufficient to reach behavioural performance. Our work thus demonstrates that mammals can perceive temporal structure in odour stimuli at surprisingly fast timescales. This in turn might be useful for key behavioural challenges (Jacobs, 2012) such as odour source separation (Hopfield, 1991), figure-ground separation (Rokni et al., 2014) or odour localisation (Vergassola et al., 2007; Vickers, 2000).

neuroscience↗

bioRxiv2019

CHIME: CMOS-hosted in-vivo microelectrodes for massively scalable neuronal recordings

Mammalian brains consist of 10s of millions to 100s of billions of neurons operating at millisecond time scales, of which current recording techniques only capture a tiny fraction. Recording techniques capable of sampling neural activity at such temporal resolution have been difficult to scale: The most intensively studied mammalian neuronal networks, such as the neocortex, show layered architecture, where the optimal recording technology samples densely over large areas. However, the need for application-specific designs as well as the mismatch between the threedimensional architecture of the brain and largely two-dimensional microfabrication techniques profoundly limits both neurophysiological research and neural prosthetics.\n\nHere, we propose a novel strategy for scalable neuronal recording by combining bundles of glass-ensheathed microwires with large-scale amplifier arrays derived from commercial CMOS of in-vitro MEA systems or high-speed infrared cameras. High signal-to-noise ratio (<20 V RMS noise floor, SNR up to 25) is achieved due to the high conductivity of core metals in glass-ensheathed microwires allowing for ultrathin metal cores (down to <1 m) and negligible stray capacitance. Multi-step electrochemical modification of the tip enables ultra-low access impedance with minimal geometric area and largely independent of core diameter. We show that microwire size can be reduced to virtually eliminate damage to the blood-brain-barrier upon insertion and demonstrate that microwire arrays can stably record single unit activity.\n\nCombining microwire bundles and CMOS arrays allows for a highly scalable neuronal recording approach, linking the progress of electrical neuronal recording to the rapid scaling of silicon microfabrication. The modular design of the system allows for custom arrangement of recording sites. Our approach of employing bundles of minimally invasive, highly insulated and functionalized microwires to lift a 2-dimensional CMOS architecture into the 3rd dimension can be translated to other CMOS arrays such as electrical stimulation devices.

neuroscience↗

bioRxiv2018

Rapid task-dependent tuning of the mouse olfactory bulb

Adapting neural representation to rapidly changing behavioural demands is a key challenge for the nervous system. Here, we demonstrate that the output of the primary olfactory area, the mouse olfactory bulb, is already a target of dynamic and reproducible modulation. The modulation depends on the stimulus tuning of a given neuron, making olfactory responses more discriminable through selective amplification in a demand-specific way.

neuroscience↗

bioRxiv2018

AutonoMouse: High throughput automated operant conditioning shows progressive behavioural impairment with graded olfactory bulb lesions.

Operant conditioning is a crucial tool in neuroscience research for probing brain function. While molecular, anatomical and even physiological techniques have seen radical increases in throughput, efficiency, and reproducibility in recent years, behavioural tools have seen much less of an improvement. Here we present a fully automated, high-throughput system for self-initiated conditioning of up to 25 group-housed, radio-frequency identification (RFID) tagged mice over periods of several months and >10^6 trials. We validate this \"AutonoMouse\" system in a series of olfactory behavioural tasks and show that acquired data is comparable to previous semi-manual approaches. Furthermore, we use AutonoMouse to systematically probe the impact of graded olfactory bulb lesions on olfactory behaviour and resolve the long-standing conundrum about the apparent lack of impact of lesions on olfactory abilities. The modular nature and open-source design of AutonoMouse should allow for similar robust and systematic assessments across neuroscience research areas.

neuroscience↗