X-ray nano-holotomography provides fast phase contrast imaging of nanoscale structures in three dimensions, but reconstruction quality is limited by beam imperfections and scan-position errors. We present a joint framework that simultaneously recovers the three-dimensional object, illumination probe, and scan-position errors from multi-distance measurements, preserving their coupling to substantially improve robustness and precision. A bilinear-Hessian method with a scalable multi-node multi-GPU implementation reconstructs large datasets with runtimes comparable to acquisition. Applied to an atomic layer deposition pattern and mouse brain tissue, the approach improves sharpness and contrast, revealing neuronal structures such as synapses and achieving high-fidelity three-dimensional imaging at synchrotron beamlines.

Abstract 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 ~2.5× 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.

Although topographical maps organize many peripheral sensory systems, mouse olfactory sensory neurons (OSNs) are thought to randomly choose which one of ∼1,100 possible olfactory receptors (ORs) to express, with spatial organization in the olfactory epithelium limited to a handful of broad anatomical "zones" that modestly restrict OR choice. Here, we reveal that each OR is instead expressed at a unique mean dorsoventral position, thereby instantiating a stereotyped receptor map in the olfactory epithelium. OSN dorsoventral identities are encoded by a coherent gene expression program, which includes key transcription factors and axon guidance molecules; use of this program reflects a dorsoventral gradient in retinoic acid signaling, translates each physical location into a spatially appropriate distribution of potential OR choices, and aligns receptor maps in the nose and brain. Spatial order in the olfactory system, therefore, arises from a continuously varying transcriptional code that precisely organizes the many discrete channels responsible for smell.

Food sensory perception has emerged as a potent regulator of specialized feeding circuits; yet, the consequences on feeding behaviour and the underlying neuronal basis remain poorly understood. Here, we reveal a sensory pathway that co-ordinately integrates food odours to control forthcoming nutrient intake in male mice. Unbiased whole-brain mapping of food odour-induced brain activity revealed a potent activation of the medial septum (MS), where food odours selectively activate MS glutamatergic neurons (MSVGLUT2). Activity dynamics of MSVGLUT2 neurons uncovered a biphasic modulation of their neuronal activity with a transient activation after detection of food odours and a long-lasting inhibition following food ingestion, independent of the caloric value and identity of the food. MSVGLUT2 neurons receive direct projections from the olfactory bulb (OB) and acute optogenetic stimulation of OB→MS projections selectively before food ingestion decreased feeding in lean mice. However, acute OB→MS optogenetic stimulation in diet-induced obese mice failed to reduce feeding, suggesting the involvement of this pathway in calorie-rich diet-induced hyperphagia and obesity development. Altogether, our study uncovered a sensory circuit by which the organism integrates olfactory food cues to prime satiety at the outset of a meal.

A common view of sensory processing is as probabilistic inference of latent causes from receptor activations. Standard approaches often assume these causes are a priori independent, yet real-world generative factors are typically correlated. Representing such structured priors in neural systems poses architectural challenges, particularly when direct interactions between units representing latent causes are biologically implausible or computationally expensive. Inspired by the architecture of the olfactory bulb, we propose a novel circuit motif that enables inference with correlated priors without requiring direct interactions among latent cause units. The key insight lies in using sister cells: neurons receiving shared receptor input but connected differently to local interneurons. The required interactions among latent units are implemented indirectly through their connections to the sister cells, such that correlated connectivity implies anti-correlation in the prior and vice versa. We use geometric arguments to construct connectivity that implements a given prior and to bound the number of causes for which such priors can be constructed. Using simulations, we demonstrate the efficacy of such priors for inference in noisy environments and compare the inference dynamics to those experimentally observed. Finally, we show how, under certain assumptions on latent representations, the prior used can be inferred from sister cell activations. While biologically grounded in the olfactory system, our mechanism generalises to other natural and artificial sensory systems and may inform the design of architectures for efficient inference under correlated latent structure.

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.

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 nanotomography (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 neurosciences, 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 improves simultaneously 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. ### Competing Interest Statement The authors have declared no competing interest.

Information is routed between brain areas via parallel streams. Neurons may share common inputs yet convey distinct information to different downstream targets. Here, we leverage the anatomical organisation of the mouse olfactory bulb (OB), where dozens of projection neurons (mitral and tufted cells, M/TCs) affiliate with a single input unit, a glomerulus[1][1]–[3][2]. To link functional properties of M/TCs to their anatomical glomerular association at scale, we combine in vivo two-photon (2P) imaging with synchrotron µCT[4][3]–[6][4] anatomical analysis and targeted X- ray nano-holotomography (XNH)[7][5],[8][6]. Improving XNH resolution for mm3 volumes enables us to reliably identify subcellular features, automatically segment >80,000 cell nuclei in individual experiments, and delineate several hundred functionally imaged projection neurons and their detailed morphology, including up to 20 M/TCs per individual glomerulus (“sister” cells). In over 2400 sister cell pairs, we consistently find that odour response amplitudes to a panel of 47 monomolecular odours are conserved between sister cells, with, however, distinct responses to individual odours. Responses correlated with anatomical features such as cell body position and lateral dendritic arborisation. Thus, sister cells neither simply relay glomerular inputs nor are they dominated by network activity. Instead, they show a “balanced diversity” in their responses, enabling efficient encoding of odour stimuli whilst retaining the overall structure of odour space. Thus, synchrotron X-ray tomography can reliably link subcellular anatomy to function in a non-destructive way across the mm3 scale. With recent advances in X-ray optics[9][7] and the emergence of 4th generation synchrotrons[10][8],[11][9], it becomes conceivable to extend this highly accessible approach to entire brain regions with increasing resolution. ### Competing Interest Statement The authors have declared no competing interest. EPSRC and Wellcome, , Physics of Life grant (EP/W024292/1) Wellcome Trust, https://ror.org/029chgv08, FC001153, 110174/Z/15/Z European Synchrotron Radiation Facility, https://ror.org/02550n020, ls2918, ls3025, ls3186, ls3231 Swiss Light Source, https://ror.org/04xrb7c55, e18026, e19556, e20104 Diamond Light Source, https://ror.org/05etxs293, MT20274 The Francis Crick Institute, https://ror.org/04tnbqb63, FC001153 European Research Council, https://ror.org/0472cxd90, European Union’s Horizon 2020 Research and Innovation Programme (852455) [1]: #ref-1 [2]: #ref-3 [3]: #ref-4 [4]: #ref-6 [5]: #ref-7 [6]: #ref-8 [7]: #ref-9 [8]: #ref-10 [9]: #ref-11

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. ### Competing Interest Statement The authors have declared no competing interest. Cancer Research UK, https://ror.org/054225q67, FC001153 Medical Research Council, FC001153 Wellcome Trust, https://ror.org/029chgv08, FC001153, 110174/Z/15/Z National Science Foundation, https://ror.org/021nxhr62, NeuroNex Program "From Odor to Action" Boehringer Ingelheim Fonds, https://ror.org/00dkye506, Doctoral Fellowship Deutsche Forschungsgemeinschaft, https://ror.org/018mejw64, Postdoctoral Fellowship, Research Unit FOR5424 “Modolfor” European Research Council, https://ror.org/0472cxd90, “TempCOdE” (101077017)

Hard X-ray nanotomography is a promising technology for nondestructive imaging of biological tissues with three-dimensional isotropic resolution. The implementation of fourth-generation synchrotron sources brings coherent X-ray microscopy to the central stage and fosters further development of this class of techniques. Here, we present an experimental comparison of X-ray near-field ptychography and X-ray holography, two high-resolution X-ray microscopy techniques applied under cryogenic conditions to the exact same sample at two different synchrotron sources. Using a heavy-metal-stained, resin-embedded brain tissue sample, we obtain similar contrast and spatial resolutions at equivalent radiation doses with these two approaches. We discuss the current benefits and limitations of the two methods. These results provide a basis for developments in X-ray microscopy of biological samples at present and future beamlines of fourth-generation synchrotron sources.

Neuronal circuit reconstruction from X-ray holographic nanotomography (XNH) images of neuronal tissue requires overcoming limits in acquisition speed, image quality, and sample size. To fully exploit the higher brilliance of the European Synchrotron's upgraded source, advances in endstation instrumentation and adapted data collection strategies are necessary. A detector upgrade combined with continuous scanning for XNH of neural tissue samples at the ESRF's ID16A beamline demonstrates preserved or improved quality of images of large samples whilst increasing data acquisition time by more than a factor of two. This is a critical step in enabling the scaling up of XNH for neuronal tissue imaging.

Active sampling in the olfactory domain is an important aspect of mouse behaviour, and there is increasing evidence that respiration-entrained neural activity outside of the olfactory system sets an important global brain rhythm. It is therefore important to accurately measure breathing during natural behaviours. We develop a new approach to do this in freely moving animals, by implanting a telemetry-based pressure sensor into the right jugular vein, which allows for wireless monitoring of thoracic pressure. After verifying this technique against standard head-fixed respiration measurements, we combined it with EEG and EMG recording and used evolving partial coherence analysis to investigate the relationship between respiration and brain activity across a range of experiments in which the mice could move freely. During voluntary exploration of odours and objects, we found that the association between respiration and cortical delta and theta rhythms decreased, while the association between respiration and cortical alpha rhythm increased. During sleep, however, the presentation of an odour was able to cause a transient increase in sniffing without changing dominant sleep rhythms (delta and theta) in the cortex. Our data align with the emerging idea that the respiration rhythm could act as a synchronising scaffold for specific brain rhythms during wakefulness and exploration, but suggest that respiratory changes are less able to impact brain activity during sleep. Combining wireless respiration monitoring with different types of brain recording across a variety of behaviours will further increase our understanding of the important links between active sampling, passive respiration, and neural activity.

Odors are transported by seemingly chaotic plumes, whose spatiotemporal structure contains rich information about space, with olfaction serving as a gateway for obtaining and processing this spatial information. Beyond tracking odors, olfaction provides localization and chemical communication cues for detecting conspecifics and predators, and linking external environments to internal cognitive maps. In this Essay, we discuss recent physiological, behavioral, and methodological advancements in mammalian olfactory research to present our current understanding of how olfaction can be used to navigate the environment. We also examine potential neural mechanisms that might convert dynamic olfactory inputs into environmental maps along this axis. Finally, we consider technological applications of odor dynamics for developing bio-inspired sensor technologies, robotics, and computational models. By shedding light on the principles underlying the processing of odor dynamics, olfactory research will pave the way for innovative solutions that bridge the gap between biology and technology, enriching our understanding of the natural world.

Summary The 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. ### Competing Interest Statement The authors have declared no competing interest.

Implanted cortical neuroprosthetics (ICNs) are medical devices developed to replace dysfunctional neural pathways by creating information exchange between the brain and a digital system which can facilitate interaction with the external world. Over the last decade, researchers have explored the application of ICNs for diverse conditions including blindness, aphasia, and paralysis. Both transcranial and endovascular approaches have been used to record neural activity in humans, and in a laboratory setting, high-performance decoding of the signals associated with speech intention has been demonstrated. Particular progress towards a device which can move into clinical practice has been made with ICNs focussed on the restoration of speech and movement. This article provides an overview of contemporary ICNs for speech and movement restoration, their mechanisms of action and the unique ethical challenges raised by the field.

What is the neural basis of our perceptual experience? Simultaneous recordings from many individual neurons in humans provide surprising insights into how odours are processed in different regions of the brain. Olfactory 'concept neurons' also respond to words and pictures.

The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity.

Correlative multimodal imaging is a useful approach to investigate complex structural relations in life sciences across multiple scales. For these experiments, sample preparation workflows that are compatible with multiple imaging techniques must be established. In one such implementation, a fluorescently labeled region of interest in a biological soft tissue sample can be imaged with light microscopy before staining the specimen with heavy metals, enabling follow-up higher resolution structural imaging at the targeted location, bringing context where it is required. Alternatively, or in addition to fluorescence imaging, other microscopy methods, such as synchrotron x-ray computed tomography with propagation-based phase contrast or serial blockface scanning electron microscopy, might also be applied. When combining imaging techniques across scales, it is common that a volumetric region of interest (ROI) needs to be carved from the total sample volume before high resolution imaging with a subsequent technique can be performed. In these situations, the overall success of the correlative workflow depends on the precise targeting of the ROI and the trimming of the sample down to a suitable dimension and geometry for downstream imaging. Here, we showcase the utility of a femtosecond laser (fs laser) device to prepare microscopic samples (1) of an optimized geometry for synchrotron x-ray tomography as well as (2) for volume electron microscopy applications and compatible with correlative multimodal imaging workflows that link both imaging modalities.