PLoS Biology, Journal Year: 2024, Volume and Issue: 22(11), P. e3002839 - e3002839
Published: Nov. 6, 2024
Bottom-up, data-driven, large-scale models provide a mechanistic understanding of neuronal functions. A new study in PLOS Biology builds biologically realistic model the rodent CA1 region that aims to become an accessible tool for whole hippocampal community.
Language: Английский
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown
Published: April 28, 2024
Abstract The hippocampus contains many unique cell types, which serve the structure’s specialized functions, including learning, memory and cognition. These cells have distinct spatial topography, morphology, physiology, connectivity, highlighting need for transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of anterior human across ten adult neurotypical donors. We defined molecular profiles hippocampal types domains. Using non-negative matrix factorization transfer integrated these to define gene expression patterns within snRNA-seq infer in SRT data. With this approach, leveraged existing rodent datasets feature information on circuit connectivity neural activity induction make predictions about axonal projection targets likelihood ensemble recruitment spatially-defined cellular populations hippocampus. Finally, genome-wide association studies with transcriptomic identify enrichment genetic components neurodevelopmental, neuropsychiatric, neurodegenerative disorders domains, To comprehensive atlas accessible scientific community, both raw processed are freely available, through interactive web applications.
Language: Английский
Citations
8
Algorithms, Journal Year: 2025, Volume and Issue: 18(3), P. 139 - 139
Published: March 3, 2025
We describe GridMet as open-source software that automatically measures the spatial tuning parameters of grid cells, such firing field size, spacing, and orientation angles. Applying these metrics to experimental data can help quantify changes in geometric characteristics cell across conditions. uses clustering other advanced methods detect characterize fields, increasing accuracy compared alternative those based on peak firing. Novel contributions this work include an effective approach for automated size estimation original method estimating spacing overcome challenges encountered software. The user-friendly yet flexible design aims facilitate widespread community adoption. Specifically, allows basic usage with default parameter settings while also enabling expert configuration many values more applications. Free release MATLAB source code will encourage development custom variations or integration packages. At same time, we provide a runtime version GridMet, thus avoiding requirement purchase any separate licenses. have optimized batch scripting workflows aid investigations multi-trial multiple cells.
Language: Английский
Citations
0
Frontiers in Network Physiology, Journal Year: 2024, Volume and Issue: 4
Published: March 7, 2024
Transient synchronization of bursting activity in neuronal networks, which occurs patterns metastable itinerant phase relationships between neurons, is a notable feature network dynamics observed vivo . However, the mechanisms that contribute to this dynamical complexity circuits are not well understood. Local cortical regions consist populations neurons with diverse intrinsic oscillatory features. In study, we numerically show phenomenon transient synchronization, also referred as metastability, can emerge an inhibitory population when neurons’ fast-spiking appropriately modulated by slower inputs from excitatory population. Using compact model mesoscopic-scale consisting pyramidal and our work demonstrates relationship frequency oscillations features emergent metastability addition, introduce method characterize collective transitions networks. Finally, discuss potential applications study mechanistically understanding dynamics.
Language: Английский
Citations
3
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown
Published: March 29, 2024
Abstract The hippocampal formation is critical for episodic memory, with area Cornu Ammonis 3 (CA3) a necessary substrate auto-associative pattern completion. Recent theoretical and experimental evidence suggests that the retrieval of cell assemblies enable these functions. Yet, how are formed retrieved in full-scale spiking neural network (SNN) CA3 incorporates observed diversity neurons connections within this circuit not well understood. Here, we demonstrate data-driven SNN model quantitatively reflecting neuron type-specific population sizes, intrinsic electrophysiology, connectivity statistics, synaptic signaling, long-term plasticity mouse capable robust auto-association completion via assemblies. Our results show broad range assembly sizes could successfully systematically retrieve patterns from heavily incomplete or corrupted cues after limited number presentations. Furthermore, performance was respect to partial overlap through shared cells, substantially enhancing memory capacity. These novel findings provide computational specific biological properties produce an effective associative learning mammalian brain.
Language: Английский
Citations
2
eLife, Journal Year: 2024, Volume and Issue: 13
Published: Feb. 28, 2024
Automatic leveraging of information in a hippocampal neuron database to generate mathematical models should help foster interactions between experimental and computational neuroscientists.
Language: Английский
Citations
1
International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(11), P. 6059 - 6059
Published: May 31, 2024
Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize wealth cellular properties from Hippocampome.org to study spatial coding spiking continuous attractor network model medial entorhinal cortex circuit activity. The primary goal is investigate if adding such realistic constraints could produce firing patterns similar those measured real neurons. Biological characteristics included work are excitability, connectivity, and synaptic signaling neuron types defined primarily by their axonal dendritic morphologies. We dynamics specific activities between groups Modeling rodent hippocampal formation keeps computationally reasonable scale while also anchoring parameters results experimental measurements. Our generates grid cell activity that well matches spacing, size, rates fields recorded live behaving animals both published datasets new experiments performed for this study. recreate different scales properties, e.g., small large, as found along dorsoventral axis cortex. exploration neuronal reveals broad range simulation. These demonstrate cells compatible implementation sourcing biophysical anatomical Hippocampome.org. software (version 1.0) released open source enable community reuse encourage novel applications.
Language: Английский
Citations
1
PLoS ONE, Journal Year: 2024, Volume and Issue: 19(8), P. e0309461 - e0309461
Published: Aug. 28, 2024
Epidemiological studies suggest that poor nutrition during pregnancy predisposes offspring to the development of lifestyle-related noncommunicable diseases and psychiatric disorders later in life. However, molecular mechanisms underlying this predisposition are not well understood. In our previous study, using rats as model animals, we showed behavioral impairments induced by prenatal undernutrition. identified solute carrier 22 family member 23 (Slc22a23) a gene is irreversibly upregulated rat brain undernutrition fetal development. Because substrate SLC22A23 transporter has yet been biological role Slc22a23 vivo fully understood, generated pan-Slc22a23 knockout examined their phenotype detail. The lean phenotype, an increase spontaneous locomotion, improved endurance, indicating they overweight even healthier ad libitum feeding environment. had reduced hippocampal volume, analysis suggested may have impaired cognitive function regarding novel objects.
Language: Английский
Citations
1
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown
Published: May 1, 2024
Abstract Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize wealth cellular properties from Hippocampome.org to study spatial coding spiking continuous attractor network model medial entorhinal cortex circuit activity. The primary goal was investigate if adding such realistic constraints could produce firing patterns similar those measured real neurons. Biological characteristics included work are excitability, connectivity, and synaptic signaling neuron types defined primarily by their axonal dendritic morphologies. We dynamics specific activities between groups Modeling rodent hippocampal formation keeps computationally reasonable scale while also anchoring parameters results experimental measurements. Our generates grid cell activity that well matches spacing, size, rates fields recorded live behaving animals both published datasets new experiments performed for this study. recreate different scales properties, e.g., small large, as found along dorsoventral axis cortex. exploration neuronal reveals broad range simulation. These demonstrate cells is compatible implementation sourcing biophysical anatomical . software released open source enable community reuse encourage novel applications.
Language: Английский
Citations
1
Journal of Computational Neuroscience, Journal Year: 2024, Volume and Issue: 52(4), P. 303 - 321
Published: Sept. 17, 2024
Abstract The hippocampal formation is critical for episodic memory, with area Cornu Ammonis 3 (CA3) a necessary substrate auto-associative pattern completion. Recent theoretical and experimental evidence suggests that the retrieval of cell assemblies enable these functions. Yet, how are formed retrieved in full-scale spiking neural network (SNN) CA3 incorporates observed diversity neurons connections within this circuit not well understood. Here, we demonstrate data-driven SNN model quantitatively reflecting neuron type-specific population sizes, intrinsic electrophysiology, connectivity statistics, synaptic signaling, long-term plasticity mouse capable robust auto-association completion via assemblies. Our results show broad range assembly sizes could successfully systematically retrieve patterns from heavily incomplete or corrupted cues after limited number presentations. Furthermore, performance was respect to partial overlap through shared cells, substantially enhancing memory capacity. These novel findings provide computational specific biological properties produce an effective associative learning mammalian brain.
Language: Английский
Citations
1
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown
Published: April 4, 2024
Abstract Electrophysiological features of excitatory synapses vary widely throughout the brain, granting neuronal circuits ability to decode and store diverse patterns information. Synapses formed by same neurons have similar electrophysiological characteristics, belonging type. However, these are generally confined microscopic brain regions, precluding their proteomic analysis. This has greatly limited our investigate molecular basis synaptic physiology. Here we introduce a procedure characterise proteome individual types. We reveal remarkable diversity among types trisynaptic circuit. Differentially expressed proteins participate in well-known processes, controlling signalling pathways preferentially used synapses. Noteworthy, all differentially express directly involved function glutamate receptors. Moreover, neuron-specific gene expression programs would regulation. Indeed, genes coding for exhibit such distinct profiles between that they contribute classification. Our data is an important resource exploring mechanisms behind properties different hippocampal combined analysis proteomics transcriptomics uncovers previously unrecognised transcriptomic control diversity, directed towards regulation receptors regulatory proteins.
Language: Английский
Citations
0