Biology subjects

Isogai, Y.

Publications and source records attributed to Isogai, Y..

7 recordsLinked to original sources

bioRxiv2026

Dynamic belief representation and updating through learned attractor-like dynamics in the frontal cortex

To act adaptively, animals must infer hidden states of the world from incomplete sensory information and update beliefs as new observations accrue. While dopamine signals are well explained by reinforcement learning models that incorporate belief states, how the brain implements belief-state inference remains unknown. Prior modeling work showed that recurrent neural networks trained to predict value (Value-RNN) develop task-specific, attractor-like dynamics that mirror evolution of beliefs. Here we performed high-density electrophysiological recordings from orbitofrontal cortex (OFC) and other brain areas of mice performing two variants of a Pavlovian task that differ in reward probability, which produce different within-trial belief dynamics. We find that OFC population activity exhibits task-specific attractor-like dynamics that mirror the within-trial dynamics in the Value-RNN. These dynamics are absent in motor and olfactory regions, are not explained by behavioral differences, and emerge progressively with learning. Our findings indicate that the brain approximates belief-state inference through learned, task-specific attractor-like dynamics.

neuroscience↗

bioRxiv2026

Selective collateralization of transcriptomically distinct neurons organizes visual-stream output from the primary visual cortex

Parallel visual streams segregate information into pathways specialized for distinct computations, but how this segregation is achieved by anatomical segregation of primary visual cortex output remains unclear. This problem is complicated because individual neurons frequently send broadcasting projections to multiple cortical areas, and the target choice depends on both topographical location and molecular identity. Here we developed axonal BARseq2 to jointly map gene expression and high-resolution axonal projections from 1,448 neurons spanning the mouse primary visual cortex (VISp). Axonal BARseq2 recapitulated projection patterns observed by bulk tracing and single-neuron reconstruction, and recovered transcriptomic identities consistent with reference snRNA-seq datasets. Retinotopy strongly predicted projections to individual cortical targets, particularly for areas proximal to VISp, but explained little of which areas are frequently co-innervated. Instead, co-innervation patterns defined three preferential output pathways that largely corresponded to the ventral stream and two subdivisions of the dorsal stream. These pathways were associated with fine-grained transcriptional identities of L4/5 intra-telencephalic neurons, which were further validated with an external MERFISH dataset. Thus, VISp output is organized by two distinct rules: retinotopy constrains where neurons project, whereas cell-type-associated collateralization constrains which targets are co-innervated. This selective broadcasting, in which single neurons reach many higher visual areas in cell-type-specific combinations, could provide an anatomical substrate for visual-stream segregation at the level of VISp output in mice.

neuroscience↗

bioRxiv2026

Spatially resolved transcriptomic identification of thousands of neurons recorded in vivo.

Transcriptomics has transformed our understanding of the brain, but assigning transcriptomic identities to neurons recorded in vivo remains challenging at scale. Existing platforms can pair transcriptomic identity with two-photon calcium imaging in small populations of approximately 100 neurons, but they require recorded cells to be sparse and therefore cannot be applied to large population recordings. Here, we present coppaFISH 3D, a spatially resolved transcriptomics method, and CASTalign, an in silico alignment framework, which together enable transcriptomic identification of thousands of simultaneously recorded cells. coppaFISH 3D detects hundreds of genes in thick 50m fixed sections while preserving tissue integrity, enabling both 3D registration to in vivo imaging and integration with immunofluorescence labelling. The platform is fully powered by open chemistry and open source software, runs on commodity hardware, and can be performed at very low cost per section. It therefore enables transcriptomic identification of recorded neurons at scale, making it possible to study how transcriptomic identity shapes activity in neural populations.

neuroscience↗

bioRxiv2025

Molecular and Spatial Organization of the Primary Olfactory System and its Responses to Social Odors

The detection of olfactory cues is essential to signal food, predators, and social encounters. To determine how the sensory detection of physiologically relevant odors is systematically mapped into the mouse primary olfactory system, we used Multiplexed Error Robust Fluorescent In Situ Hybridization (MERFISH) to construct a molecular atlas of odorant receptor (OR) expression in the main olfactory epithelium (MOE) and olfactory bulb (OB). We comprehensively quantified the expression of the mouse OR repertoire and uncovered stereotypical gradients of sensory neuron distribution in the MOE along two, central-to-peripheral and basal-to-apical, axes. Projections of sensory neurons mirror MOE gradients along the dorsal-ventral and anterior-posterior axes of the OB, respectively. Integration with sequencing data revealed candidate signaling molecules underlying this spatial organization. Co-imaging OR and activity marker expression identified distinct spatial domains of sensory responses in the MOE and OB, providing a topographical basis for olfactory responses to ethologically relevant odors.

neuroscience↗

bioRxiv2024

Combined transcriptomic, connectivity, and activity profiling of the medial amygdala using highly amplified multiplexed in situ hybridization (hamFISH)

In situ transcriptomic technologies provide a promising avenue to link gene expression, connectivity, and physiological properties of neural cell types. Commercialized methods that allow the detection of hundreds of genes in situ, however, are expensive and therefore typically used for generating unimodal reference data rather than for resource-intensive multimodal analyses. A major bottleneck is the lack of a routine means to efficiently generate cell type data. Here, we have developed hamFISH (highly amplified multiplexed fluorescence in situ hybridization), which enables the sequential detection of 32 genes using multiplexed branched DNA amplification. We used hamFISH to profile the projection, activity, and transcriptomic diversity of the medial amygdala (MeA), a critical node for innate social and defensive behaviors in mice. In total, we profiled 643,834 cells and classified neurons into 16 inhibitory and 10 excitatory types, many of which were found to be spatially clustered. We then examined the organization of outputs of these cells and activation profiles during different social contexts. Therefore, by facilitating multiplexed detection of single molecule RNAs, hamFISH provides a streamlined and versatile platform for multimodal profiling of specific brain nuclei.

neuroscience↗

bioRxiv2024

Repix: reliable, reusable, versatile chronic Neuropixels implants using minimal components

Neuropixels probes represent the state-of-the-art for high-yield electrophysiology in neuroscience: the simultaneous recording of hundreds of neurons is now routinely carried out in head-restrained animals. In contrast, neural recording in unrestrained animals, as well as recording and tracking neurons over days, remains challenging, though it is possible using chronic implants. A major challenge is the availability of simple methods that can be implemented with limited or no prior experience with Neuropixels probes, while achieving reliable, reusable, versatile high-density electrophysiology. Here we developed, deployed, and evaluated the real-world performance of Repix, a chronic implantation system that permits the repeated re-use of Neuropixels probes. The lightweight system allows implanted animals to express a full range of natural behaviors, including social behaviors. We show that Repix allows the recording of hundreds of neurons across many months, up to a year, with implants across cortical and subcortical brain regions. Probes can be reused repeatedly with stable yield. Repix has been used by 16 researchers in 10 laboratories to date, and we evaluated the real-world performance of Repix in a variety of chronic recording paradigms in both mice and rats with a combined 209 implantations. We found that the key advantage of Repix is robustness and simplicity. Adopters of Repix became proficient at five procedures on average, regardless of prior experience with in vivo electrophysiology. With the companion protocol alongside this article, the performance and user-friendliness of Repix should facilitate a wide uptake of chronic Neuropixels recordings.

neuroscience↗

bioRxiv2021

A transcriptomic axis predicts state modulation of cortical interneurons

Transcriptomics has revealed the exquisite diversity of cortical inhibitory neurons1-7, but it is not known whether these fine molecular subtypes have correspondingly diverse activity patterns in the living brain. Here, we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, but that this diversity is organized by a single factor: position along their main axis of transcriptomic variation. We combined in vivo 2-photon calcium imaging of mouse V1 with a novel transcriptomic method to identify mRNAs for 72 selected genes in ex vivo slices. We used transcriptomic clusters (t-types)4 to classify inhibitory neurons imaged in layers 1-3 using a three-level hierarchy of 5 Families, 11 Classes, and 35 t-types. Visual responses differed significantly only across Families, but modulation by brain state differed at all three hierarchical levels. Nevertheless, this diversity could be predicted from the first transcriptomic principal component, which predicted a cell types brain state modulation and correlations with simultaneously recorded cells. Inhibitory t-types with narrower spikes, lower input resistance, weaker adaptation, and less axon in layer 1 as determined in vitro8 fired more in resting, oscillatory brain states. Transcriptomic types with the opposite properties fired more during arousal. The former cells had more inhibitory cholinergic receptors, and the latter more excitatory receptors. Thus, despite the diversity of V1 inhibitory neurons, a simple principle determines how their joint activity shapes state-dependent cortical processing.

neuroscience↗