Biology subjects

Kim, I. H.

Publications and source records attributed to Kim, I. H..

7 recordsLinked to original sources

bioRxiv2024

Inversed association of locus coeruleus MRI integrity with structural volume and its impact on individual's inattentiveness

The locus coeruleus (LC) is a nucleus within the brainstem associated with physiological arousal and altered structure and function in the context of neurodegenerative disorders. Pathologies related to difficulties with attention have previously been associated with abnormalities in neurotransmitter production and sensitivity, suggesting the possibility of abnormality in neurotransmitter producing neural regions. One such region is the LC, associated with norepinephrine production. To examine the possibility that LC alteration is associated with inattentive symptom reporting, a set of analyses have been performed with 141 individuals age-ranged from 8 to 54. We found that the structural integrity value of the LC, especially on the right hemisphere, showed a significant negative association with the level of individuals inattentiveness score. Furthermore, LC volume size was significantly positively associated with inattention, and this finding was also lateralized to the right LC. Interestingly, an inverse association was found between structural integrity and volume size. These findings support the relationship between LC and attention-related behavior through both neuromelanin-sensitive and structural imaging, with important implications for the association between regional structure and function.

neuroscience↗

bioRxiv2024

Differential growth enhancement followed by notable microbiota modulation in growing-finishing pigs by Bacillus subtilis strains ps4060, ps4100, and a 50:50 strain mixture

A 50:50 blend of two Bacillus subtilis strains positively impacted the productivity of finishing pigs. Given this observed effect, we hypothesized that each strain has distinct effects on weight gain and their influence on gut microbiota. In a 16-week test, 160 pigs were divided into four groups: basal diet, B. subtilis ps4100, B. subtilis ps4060, and 50:50 mixture supplemented. Subsequently, we compared body weight and fecal microbiota. Among the supplements, ps4100, ps4060, and the 50:50 mix yielded respective average daily weight gains (ADG) of 3.6%, 4.6%, and 3.9% by the 6th week. The weight difference was maintained through the 16th week. At the 11th week, the difference in -diversity among the fecal microbiota was marginal, and 17 of 229 genera showed differential abundance between the control and either of the treatment groups. A total of 12 of the 17 genera, including Lactobacillus, showed differential abundance between the ps4100 and ps4060-fed groups, and only Eubacterium consistently decreased in abundance in both the ps4100 and ps4060 groups. In comparison, microbial diversity was significantly different at the 16th week (p < 0.05), with 96 out of 229 genera exhibiting differential abundance. A total of 42 of the 96 genera exhibited similar patterns in both the ps4100 and ps4060 groups compared to the control group. Additionally, 236 of 687 microbial enzymes with differential abundance deduced from 16S rRNA reads showed similar differential abundance in both groups compared to the control group. We concluded that the overall microbial balance, rather than the dominance or significant decrease of a few specific genera, likely caused the enhanced ADG until the 11th week. Substantial changes in microbiota manifested at the 16th week did not cause dramatically increased ADG but were a consequence of weight gain and could positively affect animal physiology and health afterward.

microbiology↗

bioRxiv2024

Monosynaptically-interconnected Network Module (MNM) Approach for High-Resolution Brain Sub-Network Analysis

We introduce the Monosynaptically-interconnected Network Module (MNM) approach, an innovative method designed for efficiently analyzing the anatomical structure and functional dynamics of specific brain network modules in vivo. Utilizing an Intein-mediated split-Cre system combined with bidirectional adeno-associated viruses, this technique precisely targets and manipulates monosynaptically interconnected modular subnetworks in freely moving animals. We demonstrate its utility through anatomical and functional mapping of a specific MNM encompassing the prefrontal cortex (PFC), basolateral amygdala (BLA), and intermediary hub regions. Specifically, the MNM approach with Cre-reporter mice visualizes detailed network architecture and enables the tracing of axonal connections among the nodes in the network. Furthermore, integration of the MNM approach with Cre-dependent Ca2+ indicator and multi-fiber photometry in freely moving mice reveals enhanced correlative network activities in social contexts. This versatile technique offers significant potential for advancing our understanding of network functions that underlie complex behaviors, providing a modular network perspective.

neuroscience↗

bioRxiv2021

Excitatory synaptogenesis in the anterior cingulate cortex is required for effort/reward evaluation

Synaptogenesis is essential for circuit development; however, it is unknown whether it is critical for the establishment and performance of goal-directed voluntary behaviors. Here, we show that operant-conditioning via lever-press for food reward-training in mice induces excitatory synapse formation onto a subset of Anterior Cingulate Cortex neurons projecting to the dorsomedial striatum (ACC->DMS). Training-induced synaptogenesis is controlled by the Gabapentin/Thrombospondin receptor 2{delta}-1, which is an essential neuronal protein for proper intracortical excitatory synaptogenesis. Using germline and conditional knockout mice, we found that deletion of 2{delta}-1 in the adult ACC->DMS circuit diminishes training-induced excitatory synaptogenesis. Surprisingly, this manipulation did not impact learning but instead resulted in a profound increase in effort exertion without affecting sensitivity to reward value or changing contingencies. Bidirectional optogenetic manipulation of ACC->DMS neurons rescued or phenocopied the behaviors of the 2{delta}-1 cKO mice highlighting the importance of synaptogenesis within this cortico-striatal circuit in regulating effort exertion.

neuroscience↗

bioRxiv2020

Genetic Disruption of WASHC4 Drives Endo-lysosomal Dysfunction and Cognitive-Movement Impairments in Mice and Humans

Mutation of the WASH complex subunit, SWIP, is implicated in human intellectual disability, but the cellular etiology of this association is unknown. We identify the neuronal WASH complex proteome, revealing a network of endosomal proteins. To uncover how dysfunction of endosomal SWIP leads to disease, we generate a mouse model of the human WASHC4c.3056C>G mutation. Quantitative spatial proteomics analysis of SWIPP1019R mouse brain reveals that this mutation destabilizes the WASH complex and uncovers significant perturbations in both endosomal and lysosomal pathways. Cellular and histological analyses confirm that SWIPP1019R results in endo-lysosomal disruption and uncover indicators of neurodegeneration. We find that SWIPP1019R not only impacts cognition, but also causes significant progressive motor deficits in mice. Remarkably, a retrospective analysis of SWIPP1019R patients confirms motor deficits in humans. Combined, these findings support the model that WASH complex destabilization, resulting from SWIPP1019R, drives cognitive and motor impairments via endo-lysosomal dysfunction in the brain.

cell biology↗

bioRxiv2019

Brain-wide electrical spatiotemporal dynamics encode reward anticipation

Anticipation of an upcoming stimulus induces neural activity across cortical and subcortical regions and influences subsequent behavior. Nevertheless, the network mechanism whereby the brain integrates this information to signal the anticipation of rewards remains relatively unexplored. Here we employ multi-circuit electrical recordings from six brain regions as mice perform a sample-to-match task in which reward anticipation is operationalized as their progress towards obtaining a potential reward. We then use machine learning to discover the naturally occurring network patterns that integrate this neural activity across timescales. Only one of the networks that we uncovered signals responses linked to reward anticipation, specifically relative proximity and reward magnitude. Activity in this Electome (electrical functional connectivity) network is dominated by theta oscillations leading from prelimbic cortex and striatum that converge on ventral tegmental area, and by beta oscillations leading from striatum that converge on prelimbic cortex. Network activity is also synchronized with brain-wide cellular firing. Critically, this network generalizes to new groups of healthy mice, as well as a mouse line that models aberrant neural circuitry observed in brain disorders that show altered reward anticipation. Thus, our findings reveal the network-level architecture whereby the brain integrates spatially distributed activity across timescales to signal reward anticipation.

neuroscience↗

bioRxiv2018

A Striatal interneuron circuit for continuous target pursuit

Most adaptive behaviors require precise tracking of targets in space. In pursuit behavior with a moving target, mice use distance to target to guide their own movement continuously. Here we show that in the sensorimotor striatum, parvalbumin-positive fast-spiking interneurons (FSIs) can represent the distance between self and target during pursuit behavior, while striatal projection neurons (SPNs), which receive FSI projections, can represent self-velocity. FSIs are shown to regulate velocity-related SPN activity during pursuit, so that movement velocity is continuously modulated by distance to target. Moreover, bidirectional manipulation of FSI activity can selectively disrupt performance by increasing or decreasing the self-target distance. Our results reveal a key role of the FSI-SPN interneuron circuit in pursuit behavior, and elucidate how this circuit implements distance to velocity transformation required for the critical underlying computation.

neuroscience↗