Publications by authors named "Jinseop S Kim"
Article Synopsis
- - The assembly of the Drosophila melanogaster brain connectome, featuring over 125,000 neurons and 50 million synaptic connections, serves as a framework to study sensory processing across the brain.
- - A computational model simulating the fly's brain was created to investigate the neural circuits involved in feeding and grooming behaviors, accurately predicting neuron responses to taste and motor activity.
- - The model also extends to mechanosensory circuits, confirming its ability to predict neuronal activation patterns and providing valuable insights into how the brain processes different sensory stimuli for behaviors.
Article Synopsis
- The study investigates how the nervous system of nematodes changes during the dauer developmental stage, using advanced techniques like deep learning for chemical connectome reconstruction.
- It finds that structural changes in neurons are closely linked to changes in connectivity, which influence specific behaviors such as nictation.
- The analysis highlights significant rewiring of sensory neuron connections and increased clustering in motor neurons, suggesting the nematode's nervous system adapts to unfavorable conditions through a tailored connectome.
The forthcoming assembly of the adult central brain connectome, containing over 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain. Here, we create a leaky integrate-and-fire computational model of the entire brain, based on neural connectivity and neurotransmitter identity, to study circuit properties of feeding and grooming behaviors. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation.
View Article and Find Full Text PDFConnectome, the complete wiring diagram of the nervous system of an organism, is the biological substrate of the mind. While biological neural networks are crucial to the understanding of neural computation mechanisms, recent artificial neural networks (ANNs) have been developed independently from the study of real neural networks. Computational scientists are searching for various ANN architectures to improve machine learning since the architectures are associated with the accuracy of ANNs.
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- The study focuses on improving synapse detection in large-scale 3D electron microscope images of mouse cerebellar molecular layer (CML) due to advancements in neuron reconstruction but slower progress in synapse detection.
- The proposed method uses deep learning AIs to automatically identify and classify synaptic and non-synaptic contacts between neuronal fragments, achieving an impressive F1-score of 0.955.
- The approach allows for detailed analysis of synapse characteristics and connectivity, with potential applications in other brain regions as well.
Article Synopsis
- Critical factors for synaptic functions include their locations, sources of input, and molecular traits, but reliable detection methods are still lacking.
- Electron microscopy is currently the best technique for synapse detection due to its high resolution, though it is time-consuming and complex to prepare samples for.
- A new method called structured illumination microscopy has been developed to efficiently identify synapses in neural circuits, specifically targeting regions determined through low-magnification fluorescence images.
Article Synopsis
- * Researchers used array tomography to map synapses from vM1 and POm on specific dendrites of L5 pyramidal neurons, revealing that both inputs target similar branchlets without a strong preference but form distinct clusters within dendritic branches.
- * This study is the first to provide a detailed look at how synapses from POm and vM1 are organized, which is key to understanding how the brain integrates sensory information from whiskers.
Article Synopsis
- A new digital resource showcases nearly 400 ganglion cells from a mouse retina, allowing users to explore their 3D structures and visual responses interactively.
- The study identifies key principles in the retina's inner plexiform layer: an arbor segregation principle related to light orientation and a density conservation principle in horizontal structure.
- The findings indicate that the anatomical positioning of ganglion cells affects their visual response characteristics, suggesting potential applications for similar methods in mapping neuronal structures and functions elsewhere in the nervous system.
25th Annual Computational Neuroscience Meeting: CNS-2016.
BMC Neurosci
August 2016
Article Synopsis
- The text includes a collection of research topics related to neural circuits, mental disorders, and computational models in neuroscience.
- It features various studies examining the functional advantages of neural heterogeneity, propagation waves in the visual cortex, and dendritic mechanisms crucial for precise neuronal functioning.
- The research covers a range of applications, from understanding complex brain rhythms to modeling auditory processing and investigating the effects of neural regulation on behavior.
Article Synopsis
- Visual motion is processed through separate On and Off pathways in the retina that connect to specific starburst amacrine cells (SACs).
- Researchers reconstructed and classified different types of On bipolar cells (BCs) using electron microscopy and identified a new type.
- The study found that the wiring of On BCs to On SACs is structured similarly to the wiring of Off BCs to Off SACs, supporting the idea that both pathways use similar mechanisms for detecting motion.
From Caenorhabditis elegans to the human connectome: a specific modular organization increases metabolic, functional and developmental efficiency.
Philos Trans R Soc Lond B Biol Sci
October 2014
The connectome, or the entire connectivity of a neural system represented by a network, ranges across various scales from synaptic connections between individual neurons to fibre tract connections between brain regions. Although the modularity they commonly show has been extensively studied, it is unclear whether the connection specificity of such networks can already be fully explained by the modularity alone. To answer this question, we study two networks, the neuronal network of Caenorhabditis elegans and the fibre tract network of human brains obtained through diffusion spectrum imaging.
View Article and Find Full Text PDFHow does the mammalian retina detect motion? This classic problem in visual neuroscience has remained unsolved for 50 years. In search of clues, here we reconstruct Off-type starburst amacrine cells (SACs) and bipolar cells (BCs) in serial electron microscopic images with help from EyeWire, an online community of 'citizen neuroscientists'. On the basis of quantitative analyses of contact area and branch depth in the retina, we find evidence that one BC type prefers to wire with a SAC dendrite near the SAC soma, whereas another BC type prefers to wire far from the soma.
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