
Alexander Fleischmann
· Provost's Professor of Brain ScienceVerifiedBrown University · Microbiology and Immunology
Active 2000–2026
About
Alexander Fleischmann is the Provost's Professor of Brain Science at Brown University, who joined the Brown Neuroscience Department in January 2018. His laboratory focuses on understanding how neural circuits generate sensory perception and behavior, particularly in the mouse olfactory cortex. His research employs molecular genetic, in vivo imaging, computational, and behavioral approaches to explore the fundamental properties of neural networks involved in odor information coding, neural cell type contributions, and the transmission of sensory information to downstream areas involved in sensory integration, cognition, and motor control. Fleischmann's work has led to the development of new molecular genetic and viral techniques for targeting and manipulating neural cell types, as well as characterizing odor coding principles through in vivo microscopy, electrophysiology, and computational methods. His research also investigates how learning and experience influence olfactory neural network functions and behavior.
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Research topics
- Biology
- Computational biology
- Cell biology
- Genetics
- Neuroscience
Selected publications
medRxiv · 2026-03-31
articleOpen accessAbstract Normal pressure hydrocephalus (NPH) is a potentially reversible neurological disorder characterized by urinary incontinence, gait impairment, and cognitive decline. However, postoperative improvement after shunt placement is variable, and reliable preoperative predictors are lacking, leaving patients exposed to uncertain surgical benefit and procedural risk. We therefore asked whether preoperative cerebrospinal fluid (CSF) metabolic profiles capture biological states associated with recovery potential. We analyzed ventricular CSF from patients undergoing shunt placement and identified metabolic patterns that differed between patients who improved postoperatively and those who did not. These signatures were detectable prior to intervention and were consistent across analytical approaches and patient cohorts. Multivariate models based on metabolite features were associated with postoperative improvement, with strongest performance observed for cognitive outcomes. Pathway-level analyses indicated coordinated alterations in processes related to redox balance, immune–metabolic signaling, and energy substrate utilization. These findings indicate that preoperative CSF metabolite profiles reflect biological states associated with recovery potential in NPH. The results further suggest that metabolic and immune–metabolic processes contribute to variability in surgical responsiveness and support the development of predictive biomarkers for patient stratification.
Zenodo (CERN European Organization for Nuclear Research) · 2026-04-27
otherOpen accessbioRxiv (Cold Spring Harbor Laboratory) · 2026-04-22
articleOpen accessRecent advances in spatial omics technologies have enabled simultaneous profiling of transcriptomic, proteomic, epigenomic, metabolomic, and imaging data at high spatial resolution, offering unprecedented opportunities to dissect tissue complexity. However, integrating these diverse and large-scale spatial multi-modal datasets remains a major computational challenge. We present SCIGMA, a scalable and generalizable deep learning framework for spatial multi- omics integration. SCIGMA introduces a novel uncertainty-aware contrastive learning objective and multi-view graph neural networks to preserve modality-specific signals while learning biologically meaningful joint representations. Unlike existing methods, SCIGMA provides spatially resolved uncertainty estimates, improving interpretability and identifying regions of biological or technical heterogeneity. SCIGMA is the first spatial multi-omics method to support integration of up to five modalities - as demonstrated on Spatial-Mux-Seq data - and its modular framework is extensible to future technologies with even more modalities. It also scales to over one million spatial locations, enabling analysis of ultra-high-resolution datasets such as VisiumHD and Xenium Prime. We evaluated SCIGMA across 19 datasets spanning 8 modalities, 10 tissues, and 9 platforms. On benchmarkable datasets, SCIGMA outperformed existing methods in spatial domain detection, modality preservation, feature reconstruction, and reproducibility. Across applications, it uncovered biologically meaningful structures, refined spatial domains, and modality-specific regulatory programs, while its uncertainty estimates revealed tissue regions with potential biological or technical variation. Together, SCIGMA provides a robust, flexible, and future-ready solution for scalable spatial multi-modal integration.
Zenodo (CERN European Organization for Nuclear Research) · 2026-04-27
otherOpen accessProjection-specific Routing of Odor Information in the Olfactory Cortex
bioRxiv (Cold Spring Harbor Laboratory) · 2025-12-16
articleOpen accessSenior authorSensory processing in the mammalian cortex relies on extensive feedforward and feedback connections, yet how information is routed along these pathways remains poorly understood. Here, we examined the functional properties of feedback and feedforward neurons in the mouse olfactory (piriform) cortex. We selectively labeled neurons projecting to the olfactory bulb (OB, feedback) or medial prefrontal cortex (mPFC, feedforward) and recorded their activity during passive odor exposure and learning of an odor discrimination task. We found that odor identity and reward associations were encoded by OB-projecting ensembles early during odor exposure, whereas mPFC-projecting neurons encoded this information later, aligned with behavioral responses. Moreover, mPFC-projecting neurons maintained a stable representation of valence across days, while OB-projecting neurons exhibited pronounced plasticity. Together, these findings reveal that odor information is selectively routed through feedforward and feedback pathways and suggest that the functional properties of piriform neurons mirror the computational demands of their downstream targets.
eLife · 2025-03-14
preprintOpen accessAbstract Two-photon (2P) fluorescence imaging through gradient index (GRIN) lens-based endoscopes is fundamental to investigate the functional properties of neural populations in deep brain circuits. However, GRIN lenses have intrinsic optical aberrations, which severely degrade their imaging performance. GRIN aberrations decrease the signal-to-noise ratio (SNR) and spatial resolution of fluorescence signals, especially in lateral portions of the field-of-view (FOV), leading to restricted FOV and smaller number of recorded neurons. This is especially relevant for GRIN lenses of several millimeters in length, which are needed to reach the deeper regions of the rodent brain. We have previously demonstrated a novel method to enlarge the FOV and improve the spatial resolution of two-photon microendoscopes based on GRIN lenses of length < 4.1 mm (Antonini et al. eLife 2020). However, previously developed microendoscopes were too short to reach the most ventral regions of the mouse brain. In this study, we combined optical simulations with fabrication of aspherical polymer microlenses through three-dimensional (3D) microprinting to correct for optical aberrations in long (length > 6 mm) GRIN lens-based microendoscopes (diameter, 500 µm). Long corrected microendoscopes had improved spatial resolution, enabling imaging in significantly enlarged FOVs. Moreover, using synthetic calcium data we showed that aberration correction enabled detection of cells with higher SNR of fluorescent signals and decreased cross-contamination between neurons. Finally, we applied long corrected microendoscopes to perform large-scale and high precision recordings of calcium signals in populations of neurons in the olfactory cortex, a brain region laying approximately 5 mm from the brain surface, of awake head-tethered mice. Long corrected microendoscopes are powerful new tools enabling population imaging with unprecedented large FOV and high spatial resolution in the most ventral regions of the mouse brain.
2025-03-14
peer-reviewOpen accessTwo-photon (2P) fluorescence imaging through gradient index (GRIN) lens-based endoscopes is fundamental to investigate the functional properties of neural populations in deep brain circuits. However, GRIN lenses have intrinsic optical aberrations, which severely degrade their imaging performance. GRIN aberrations decrease the signal-to-noise ratio (SNR) and spatial resolution of fluorescence signals, especially in lateral portions of the field-of-view (FOV), leading to restricted FOV and smaller number of recorded neurons. This is especially relevant for GRIN lenses of several millimeters in length, which are needed to reach the deeper regions of the rodent brain. We have previously demonstrated a novel method to enlarge the FOV and improve the spatial resolution of two-photon microendoscopes based on GRIN lenses of length < 4.1 mm (Antonini et al. eLife 2020). However, previously developed microendoscopes were too short to reach the most ventral regions of the mouse brain. In this study, we combined optical simulations with fabrication of aspherical polymer microlenses through three-dimensional (3D) microprinting to correct for optical aberrations in long (length > 6 mm) GRIN lens-based microendoscopes (diameter, 500 µm). Long corrected microendoscopes had improved spatial resolution, enabling imaging in significantly enlarged FOVs. Moreover, using synthetic calcium data we showed that aberration correction enabled detection of cells with higher SNR of fluorescent signals and decreased cross-contamination between neurons. Finally, we applied long corrected microendoscopes to perform large-scale and high precision recordings of calcium signals in populations of neurons in the olfactory cortex, a brain region laying approximately 5 mm from the brain surface, of awake head-tethered mice. Long corrected microendoscopes are powerful new tools enabling population imaging with unprecedented large FOV and high spatial resolution in the most ventral regions of the mouse brain.
eLife · 2025-05-02
articleOpen accessTwo-photon (2P) fluorescence imaging through gradient index (GRIN) lens-based endoscopes is fundamental to investigate the functional properties of neural populations in deep brain circuits. However, GRIN lenses have intrinsic optical aberrations, which severely degrade their imaging performance. GRIN aberrations decrease the signal-to-noise ratio (SNR) and spatial resolution of fluorescence signals, especially in lateral portions of the field-of-view (FOV), leading to restricted FOV and smaller number of recorded neurons. This is especially relevant for GRIN lenses of several millimeters in length, which are needed to reach the deeper regions of the rodent brain. We have previously demonstrated a novel method to enlarge the FOV and improve the spatial resolution of 2P microendoscopes based on GRIN lenses of length <4.1 mm (Antonini et al., 2020). However, previously developed microendoscopes were too short to reach the most ventral regions of the mouse brain. In this study, we combined optical simulations with fabrication of aspherical polymer microlenses through three-dimensional (3D) microprinting to correct for optical aberrations in long (length >6 mm) GRIN lens-based microendoscopes (diameter, 500 µm). Long corrected microendoscopes had improved spatial resolution, enabling imaging in significantly enlarged FOVs. Moreover, using synthetic calcium data we showed that aberration correction enabled detection of cells with higher SNR of fluorescent signals and decreased cross-contamination between neurons. Finally, we applied long corrected microendoscopes to perform large-scale and high-precision recordings of calcium signals in populations of neurons in the olfactory cortex, a brain region laying approximately 5 mm from the brain surface, of awake head-fixed mice. Long corrected microendoscopes are powerful new tools enabling population imaging with unprecedented large FOV and high spatial resolution in the most ventral regions of the mouse brain.
Nature Neuroscience · 2025-04-08 · 6 citations
articleOpen accessSenior authorDifferential Encoding of Odor and Place in the Mouse Piriform and Entorhinal Cortex
eNeuro · 2025-09-19
articleOpen accessThe integration of olfactory and spatial information is critical for guiding animal behavior. The lateral entorhinal cortex (LEC) is reciprocally interconnected with cortical areas for olfaction and the hippocampus and thus ideally positioned to encode odor-place associations. Here, we used miniendoscopes to record neural activity in the mouse piriform cortex (PCx) and LEC. We show that in head-fixed mice, odor identity could be decoded from LEC ensembles but less accurately than from PCx. In male mice freely navigating a linear track, LEC ensemble activity at the odor ports was dominated by spatial information. Spatial position along the linear track could be decoded from LEC and PCx activity; however, PCx but not LEC exhibited strong behavior-driven modulation of positional information. Together, our data reveal that information about odor cues and spatial context is differentially encoded along the PCx-LEC axis.
Frequent coauthors
- 57 shared
Claire Meissner-Bernard
Friedrich Miescher Institute
- 54 shared
Yulia Dembitskaya
Université de Bordeaux
- 54 shared
Laurent Venance
Centre National de la Recherche Scientifique
- 52 shared
Nell Klimpert
Allen Institute for Brain Science
- 39 shared
Benjamin Shykind
- 39 shared
Assunta Diodato
Centre National de la Recherche Scientifique
- 39 shared
Benjamin Roland
Inserm
- 37 shared
Sara Zeppilli
Brown University
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