Biology subjects

Fujisawa, S.

Publications and source records attributed to Fujisawa, S..

8 recordsLinked to original sources

bioRxiv2025

The Spiking Tolman-Eichenbaum Machine: Emergent Spatial and Temporal Coding through Spiking Network Dynamics

The hippocampal-entorhinal system supports spatial navigation and memory by orchestrating the interaction between grid cells and place cells. While various models have reproduced these patterns, many rely on predefined connectivity or fixed weights and lack mechanisms for learning or biologically realistic temporal dynamics. The Tolman-Eichenbaum Machine (TEM) has recently gained attention as a unified generative model that explains the emergence of both grid and place cells through learning. However, existing TEM implementations rely on rate-based units and simplified architectures, which limit their biological plausibility. Here, we introduce the Spiking Tolman-Eichenbaum Machine (Spiking TEM) -- a spiking neural network model that extends the original TEM with spike-based computation and an anatomically inspired hippocampal-entorhinal architecture. Our model learns grid-like codes in the entorhinal module and context-specific place codes in the hippocampal module, while also exhibiting key temporal coding phenomena observed in electrophysiological recordings, including phase locking of spikes to theta oscillations and phase precession. Furthermore, the model gives rise to predictive grid cells in layer III of the entorhinal cortex, which prospectively encode upcoming spatial positions. These results demonstrate that structured spatial representations and temporally precise coding schemes can emerge from biologically plausible spike-based learning and dynamics, offering a unified framework for understanding spatial and temporal coding in the hippocampal-entorhinal circuit. Author SummaryAnimals, including humans, rely on an internal map of the environment to navigate and remember places. In the brain, this ability depends on two key types of neurons: place cells in the hippocampus, which fire when an animal is in a specific location, and grid cells in the entorhinal cortex, which form a hexagonal coordinate-like map of space. Understanding how neural circuits generate these spatial representations is a major goal in neuroscience. In this study, we developed a biologically grounded spiking neural network model -- the Spiking Tolman-Eichenbaum Machine (Spiking TEM)--that can learn both grid and place cell patterns through realistic neural dynamics. Our model reproduces key temporal features observed in the brain, including phase precession. In this phenomenon, neurons fire slightly earlier in each successive theta cycle as an animal moves through a place field. The model also predicts grid cells that anticipate future positions. These results provide new insight into how the hippocampal-entorhinal circuit generates and organizes spatial and memory-related representations through learning and temporal coding.

neuroscience↗

bioRxiv2024

Synchronous processing of temporal information across the hippocampus, striatum, and orbitofrontal cortex

Information processing for interval timing is supported by several brain regions, including the hippocampus, basal ganglia, and frontal cortical areas. However, little is known about the mechanism by which temporal information is processed cooperatively in the distributed brain network. Here, we investigated the neuronal processing of temporal information in the hippocampal CA1, dorsal striatum, and orbitofrontal cortex by simultaneously recording neuronal activity during a temporal bisection task. We found time cells representing elapsed time during the interval period across all three regions. Seeking a potential mechanism for the correlative representation of time, we found that theta oscillations were dominant in these areas and modulated the activity of these time cells. Moreover, the synchronization of the time cell pairs across the areas was also regulated by theta oscillations. Taken together, these results demonstrated the presence of synchronous activity of time cells across the three areas on a fine time scale, which was supported by theta oscillations. In addition, decoding analysis revealed that the activity of the time cells in these areas correlated with the rats decisions based on their internal time estimation, with the decoded time also showing correlations across the three regions. Thus, the cooperative activity of time-cell assemblies in the three regions reflected the recognition of elapsed time in the rats. In conclusion, these results demonstrate the pivotal role of neuronal synchronization of time cells in supporting temporal processing in the distributed brain network.

neuroscience↗

bioRxiv2024

The transcription factor BATF pioneers the differentiation program of cytolytic effector CD8+ T cells through the direct interaction with IRF4

The transcription factor BATF plays critical roles in the differentiation of various immune cells, including CD8+ T cells. Here, we demonstrated that BATF controls epigenomic and transcriptomic reprogramming of CD8+ T cells at an early phase of acute viral infection, thereby promoting the differentiation of cytolytic effector CD8+ T cells. Loss of BATF drastically perturbed gene expression, chromatin accessibility, and the bindings of key transcription factors including Jun, T-bet, and IRF4. The direct interaction with IRF4 was essential for BATF-mediated effector differentiation, as the BATF mutant lacking this interaction failed to induce proper chromatin remodeling and proliferation of antigen-specific CD8+ T cells. Notably, IRF4 binding was exhaustively dependent on BATF, whereas BATF retained binding capacity even in IRF4-deficient CD8+ T cells. Furthermore, BATF initiated chromatin remodeling in the absence of IRF4, whereas subsequent dynamic epigenomic reorganization required IRF4. Our data proposed that BATF serves as a "pioneer transcription factor" spearheading the reorganization of chromatin architecture upon antigen encounter, followed by further rearrangement of epigenomic and transcriptomic landscapes through the cooperation with IRF4.

immunology↗

bioRxiv2023

Memory-specific encoding activities of the ventral tegmental area dopamine and GABA neurons

Although the midbrain dopamine (DA) system plays a crucial role in higher cognitive functions, including updating and maintaining short-term memory, the encoding properties of the somatic spiking activity of ventral tegmental area (VTA) DA neurons for short-term memory computations have not yet been identified. Here, we probed and analyzed the activity of optogenetically identified DA and GABA neurons while mice engaged in short-term memory-dependent behavior in a T-maze task. Single-neuron analysis revealed that significant subpopulations of DA and GABA neurons responded differently between left and right trials in the memory delay. With a series of control behavioral tasks and regression analysis tools, we show that firing rate differences are linked to short-term memory-dependent decisions and cannot be explained by reward-related processes, motivated behavior, or motor-related activities. This evidence provides novel insights into the mnemonic encoding activities of midbrain DA and GABA neurons.

neuroscience↗

bioRxiv2023

Estimation of animal location from grid cell populationactivity using persistent cohomology

Many cognitive functions are represented as cell assemblies. For example, the population activity of place cells in the hippocampus and grid cells in the entorhinal cortex represent self-location in the environment. The brain cannot directly observe self-location information in the environment. Instead, it relies on sensory information and memory to estimate self-location. Therefore, estimating low-dimensional dynamics, such as the movement trajectory of an animal exploring its environment, from only the high-dimensional neural activity is important in deciphering the information represented in the brain. Most previous studies have estimated the low-dimensional dynamics behind neural activity by unsupervised learning with dimensionality reduction using artificial neural networks or Gaussian processes. This paper shows theoretically and experimentally that these previous research approaches fail to estimate well when the nonlinearity between high-dimensional neural activity and low-dimensional dynamics becomes strong. We estimate the animals position in 2-D and 3-D space from the activity of grid cells using an unsupervised method based on persistent cohomology. The method using persistent cohomology estimates low-dimensional dynamics from the phases of manifolds created by neural activity. Much cognitive information, including self-location information, is expressed in the phases of the manifolds created by neural activity. The persistent cohomology may be useful for estimating these cognitive functions from neural population activity in an unsupervised manner. Author summaryHippocampal place cells fire only when the animal is in a specific position in the environment. Grid cells in entorhinal cortex fire to spatial locations in a repeating hexagonal grid. Information about self-location in the environment is expressed by the population activity of place cells and grid cells. The brain cannot directly observe the information of self-position in the environment but relies on the direction of movement, distance, and landmarks to estimate self-position. This corresponds to unsupervised learning. Estimating the position of an animal from neural activity alone, without using information about the animals position, is important for understanding the brains representation of information. Unsupervised learning methods using artificial neural networks and Gaussian processes have been used in previous studies to address this problem. However, we show that these previous studies cannot estimate the position of an animal in two dimensions from the population activity of grid cells. As an alternative to the previous studies, we used a topological method called persistent cohomolohy to estimate the animals position in 2D and 3D space from the population activity of grid cells. However, it was impossible to estimate the animals position from the population activity of place cells. We discussed the causes and solutions to this problem.

neuroscience↗

bioRxiv2022

Glutamatergic projections from ventral hippocampus to nucleus accumbens cholinergic neurons are altered in a mouse model of depression

The cholinergic interneurons (ChATs) of the nucleus accumbens (NAc) have a critical role in the activity of this region, specifically in the context of major depressive disorder. To understand the circuitry regulating this behavior we sought to determine the areas that directly project to these cells/interneurons by utilizing the monosynaptic cell-specific tracing technique. Mapping showed monosynaptic projections that are exclusive to NAc ChATs. To determine if some of these projections are altered in a depression mouse model, we used mice that do not express the calcium binding protein p11 specifically in ChATs (ChAT-p11 cKO) and display a depressive-like phenotype. Our data demonstrated that while the overall projection areas remain similar between wild type and in ChAT-p11 cKO mice, the number of projections coming from the ventral hippocampus (vHIP) is significantly reduced in the ChAT-p11 cKO mice. Furthermore, using optogenetics and electrophysiology we showed that glutamatergic projections from vHIP to NAc ChATs are severely altered in mutant mice. These results show that specific alterations in the circuitry of the accumbal ChAT interneurons could play an important role in the regulation of depressive-like behavior, reward seeking behavior in addictions, or psychiatric symptoms in neurodegenerative diseases.

neuroscience↗

bioRxiv2019

Cell-projection pumping: A hydrodynamic cell-stiffness dependent mechanism for cytoplasmic transfer between mammalian cells

We earlier reported cytoplasmic fluorescence exchange between cultured human fibroblasts (Fib) and malignant cells (MC). Others report similar transfer via either tunneling nanotubes (TNT) or shed membrane vesicles and this changes the phenotype of recipient cells. Our current time-lapse microscopy showed most exchange was from Fib into MC, with less in the reverse direction. Although TNT were seen, we were surprised transfer was not via TNT, but was instead via fine and often branching cell projections that defied direct visual resolution because of their size and rapid movement. Their structure was revealed nonetheless, by their organellar cargo and the grooves they formed indenting MC, while this was consistent with holotomography. Discrete, rapid and highly localized transfer events, evidenced against a role for shed vesicles. Transfer coincided with rapid retraction of the cell-projections, suggesting a hydrodynamic mechanism. Increased hydrodynamic pressure in retracting cell-projections normally returns cytoplasm to the cell body. We hypothesize cell-projection pumping (CPP), where cytoplasm in retracting cell-projections partially equilibrates into adjacent recipient cells via micro-fusions that form temporary inter-cellular cytoplasmic continuities. We tested plausibility for CPP by combined mathematical modelling, comparison of predictions from the model with experimental results, and then computer simulations based on experimental data. The mathematical model predicted preferential CPP into cells with lower cell stiffness, expected from equilibration of pressure towards least resistance. Predictions from the model were satisfied when Fib were co-cultured with MC, and fluorescence exchange related with cell stiffness by atomic force microscopy. When transfer into 5000 simulated recipient MC or Fib was studied in computer simulations, inputting experimental cell stiffness and donor cell fluorescence values generated transfers to simulated recipient cells similar to those seen by experiment. We propose CPP as a potentially novel mechanism in mammalian inter-cellular cytoplasmic transfer and communication. SIGNIFICANCETime-lapse observations of co-cultured cells led us to hypothesize what we believe to be a novel hydrodynamic mechanism transferring cytoplasm between cells. Similar transfer by other mechanisms markedly affects cell behavior. Combined mathematical modelling, satisfaction of predictions from the mathematical model in cell culture experiments, and separate computer simulations that generate outcomes similar to experimental observations, support our hypothesized mechanism.

cell biology↗

bioRxiv2018

The hippocampus encodes delay and value information during delay-discounting decision making

The hippocampus, a region critical for memory and spatial navigation, has been implicated in delay discounting, the decline in subjective reward value when a delay is imposed. However, how delay discounting is encoded in the hippocampus is poorly understood. Here we recorded from the hippocampal CA1 region of mice performing a delay-discounting decision-making task, where delay lengths and reward amounts were changed across sessions, and identified subpopulations of neurons in CA1 which increased or decreased their firing rate during long delays. The activity of both delay-active and -suppressive cells reflected delay length, reward amount, and arm position, however manipulating reward amount differentially impacted the two populations, suggesting distinct roles in the valuation process. Further, genetic deletion of NMDA receptor in hippocampal pyramidal cells impaired delay-discount behavior and diminished delay-dependent activity in CA1. Our results suggest that distinct subclasses of hippocampal neurons concertedly support delay-discounting decision in a manner dependent on NMDA receptor function.

neuroscience↗