Network NeurosciencePub Date : 2025-03-03eCollection Date: 2025-01-01DOI: 10.1162/netn_a_00419
Mahdi Moghaddam, Mario Dzemidzic, Daniel Guerrero, Mintao Liu, Jonathan Alessi, Martin H Plawecki, Jaroslaw Harezlak, David A Kareken, Joaquín Goñi
{"title":"Tangent space functional reconfigurations in individuals at risk for alcohol use disorder.","authors":"Mahdi Moghaddam, Mario Dzemidzic, Daniel Guerrero, Mintao Liu, Jonathan Alessi, Martin H Plawecki, Jaroslaw Harezlak, David A Kareken, Joaquín Goñi","doi":"10.1162/netn_a_00419","DOIUrl":"10.1162/netn_a_00419","url":null,"abstract":"<p><p>Human brain function dynamically adjusts to ever-changing stimuli from the external environment. Studies characterizing brain functional reconfiguration are, nevertheless, scarce. Here, we present a principled mathematical framework to quantify brain functional reconfiguration when engaging and disengaging from a stop signal task (SST). We apply tangent space projection (a Riemannian geometry mapping technique) to transform the functional connectomes (FCs) of 54 participants and quantify functional reconfiguration using the correlation distance of the resulting tangent-FCs. Our goal was to compare functional reconfigurations in individuals at risk for alcohol use disorder (AUD). We hypothesized that functional reconfigurations when transitioning to/from a task would be influenced by family history of AUD (FHA) and other AUD risk factors. Multilinear regression models showed that engaging and disengaging functional reconfiguration were associated with FHA and recent drinking. When <i>engaging</i> in the SST after a rest condition, functional reconfiguration was negatively associated with recent drinking, while functional reconfiguration when <i>disengaging</i> from the SST was negatively associated with FHA. In both models, several other factors contributed to the functional reconfiguration. This study demonstrates that tangent-FCs can characterize task-induced functional reconfiguration and that it is related to AUD risk.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"9 1","pages":"38-60"},"PeriodicalIF":3.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949615/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network NeurosciencePub Date : 2025-03-03eCollection Date: 2025-01-01DOI: 10.1162/netn_a_00427
Spandan Sengupta, Afroditi Talidou, Jeremie Lefebvre, Frances K Skinner
{"title":"Cell-type-specific contributions to theta-gamma coupled rhythms in the hippocampus.","authors":"Spandan Sengupta, Afroditi Talidou, Jeremie Lefebvre, Frances K Skinner","doi":"10.1162/netn_a_00427","DOIUrl":"10.1162/netn_a_00427","url":null,"abstract":"<p><p>Distinct inhibitory cell types participate in cognitively relevant nested brain rhythms, and particular changes in such rhythms are known to occur in disease states. Specifically, the coexpression of theta and gamma rhythms in the hippocampus is believed to represent a general coding scheme, but cellular-based generation mechanisms for these coupled rhythms are currently unclear. We develop a population rate model of the CA1 hippocampus that encompasses circuits of three inhibitory cell types (bistratified cells and parvalbumin [PV]-expressing and cholecystokinin [CCK]-expressing basket cells) and pyramidal cells to examine this. We constrain parameters and perform numerical and theoretical analyses. The theory, in combination with the numerical explorations, predicts circuit motifs and specific cell-type mechanisms that are essential for the coexistence of theta and gamma oscillations. We find that CCK-expressing basket cells initiate the coupled rhythms and regularize theta, and PV-expressing basket cells enhance both theta and gamma rhythms. Pyramidal and bistratified cells govern the generation of theta rhythms, and PV-expressing basket and pyramidal cells play dominant roles in controlling theta frequencies. Our circuit motifs for the theta-gamma coupled rhythm generation could be applicable to other brain regions.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"9 1","pages":"100-124"},"PeriodicalIF":3.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949547/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network NeurosciencePub Date : 2025-03-03eCollection Date: 2025-01-01DOI: 10.1162/netn_a_00425
Eric G Ceballos, Andrea I Luppi, Gabriel Castrillon, Manish Saggar, Bratislav Misic, Valentin Riedl
{"title":"The control costs of human brain dynamics.","authors":"Eric G Ceballos, Andrea I Luppi, Gabriel Castrillon, Manish Saggar, Bratislav Misic, Valentin Riedl","doi":"10.1162/netn_a_00425","DOIUrl":"10.1162/netn_a_00425","url":null,"abstract":"<p><p>The human brain is a complex system with high metabolic demands and extensive connectivity that requires control to balance energy consumption and functional efficiency over time. How this control is manifested on a whole-brain scale is largely unexplored, particularly what the associated costs are. Using the network control theory, here, we introduce a novel concept, time-averaged control energy (TCE), to quantify the cost of controlling human brain dynamics at rest, as measured from functional and diffusion MRI. Importantly, TCE spatially correlates with oxygen metabolism measures from the positron emission tomography, providing insight into the bioenergetic footing of resting-state control. Examining the temporal dimension of control costs, we find that brain state transitions along a hierarchical axis from sensory to association areas are more efficient in terms of control costs and more frequent within hierarchical groups than between. This inverse correlation between temporal control costs and state visits suggests a mechanism for maintaining functional diversity while minimizing energy expenditure. By unpacking the temporal dimension of control costs, we contribute to the neuroscientific understanding of how the brain governs its functionality while managing energy expenses.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"9 1","pages":"77-99"},"PeriodicalIF":3.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949579/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network NeurosciencePub Date : 2025-03-03eCollection Date: 2025-01-01DOI: 10.1162/netn_a_00432
Isaac N Treves, Winson F Z Yang, Terje Sparby, Matthew D Sacchet
{"title":"Dynamic brain states underlying advanced concentrative absorption meditation: A 7-T fMRI-intensive case study.","authors":"Isaac N Treves, Winson F Z Yang, Terje Sparby, Matthew D Sacchet","doi":"10.1162/netn_a_00432","DOIUrl":"10.1162/netn_a_00432","url":null,"abstract":"<p><p>Advanced meditation consists of states and stages of practice that unfold with mastery and time. Dynamic functional connectivity (DFC) analysis of fMRI could identify brain states underlying advanced meditation. We conducted an intensive DFC case study of a meditator who completed 27 runs of <i>jhāna</i> advanced absorptive concentration meditation (ACAM-J), concurrently with 7-T fMRI and phenomenological reporting. We identified three brain states that marked differences between ACAM-J and nonmeditative control conditions. These states were characterized as a DMN-anticorrelated brain state, a hyperconnected brain state, and a sparsely connected brain state. Our analyses indicate higher prevalence of the DMN-anticorrelated brain state during ACAM-J than control states, and the prevalence increased significantly with deeper ACAM-J states. The hyperconnected brain state was also more common during ACAM-J and was characterized by elevated thalamocortical connectivity and somatomotor network connectivity. The hyperconnected brain state significantly decreased over the course of ACAM-J, associating with self-reports of wider attention and diminished physical sensations. This brain state may be related to sensory awareness. Advanced meditators have developed well-honed abilities to move in and out of different altered states of consciousness, and this study provides initial evidence that functional neuroimaging can objectively track their dynamics.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"9 1","pages":"125-145"},"PeriodicalIF":3.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949543/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network NeurosciencePub Date : 2025-03-03eCollection Date: 2025-01-01DOI: 10.1162/netn_a_00421
Shiva Mirzaeian, Ashkan Faghiri, Vince D Calhoun, Armin Iraji
{"title":"A telescopic independent component analysis on functional magnetic resonance imaging dataset.","authors":"Shiva Mirzaeian, Ashkan Faghiri, Vince D Calhoun, Armin Iraji","doi":"10.1162/netn_a_00421","DOIUrl":"10.1162/netn_a_00421","url":null,"abstract":"<p><p>Brain function can be modeled as dynamic interactions between functional sources at different spatial scales, and each spatial scale can contain its functional sources with unique information, thus using a single scale may provide an incomplete view of brain function. This paper introduces a novel approach, termed \"telescopic independent component analysis (TICA),\" designed to construct spatial functional hierarchies and estimate functional sources across multiple spatial scales using fMRI data. The method employs a recursive independent component analysis (ICA) strategy, leveraging information from a larger network to guide the extraction of information about smaller networks. We apply our model to the default mode network (DMN), visual network (VN), and right frontoparietal network (RFPN). We investigate further on the DMN by evaluating the difference between healthy people and individuals with schizophrenia. We show that the TICA approach can detect the spatial hierarchy of the DMN, VN, and RFPN. In addition, the TICA revealed DMN-associated group differences between cohorts that may not be captured if we focus on a single-scale ICA. In sum, our proposed approach represents a promising new tool for studying functional sources.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"9 1","pages":"61-76"},"PeriodicalIF":3.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network NeurosciencePub Date : 2025-03-03eCollection Date: 2025-01-01DOI: 10.1162/netn_a_00417
Ioanna A Amaya, Till Nierhaus, Timo T Schmidt
{"title":"Thalamocortical interactions reflecting the intensity of flicker light-induced visual hallucinatory phenomena.","authors":"Ioanna A Amaya, Till Nierhaus, Timo T Schmidt","doi":"10.1162/netn_a_00417","DOIUrl":"10.1162/netn_a_00417","url":null,"abstract":"<p><p>Aberrant thalamocortical connectivity occurs together with visual hallucinations in various pathologies and drug-induced states, highlighting the need to better understand how thalamocortical interactions may contribute to hallucinatory phenomena. Flicker light stimulation (FLS) at 10-Hz reliably and selectively induces transient visual hallucinations in healthy participants. Arrhythmic flicker elicits fewer hallucinatory effects while delivering equal amounts of visual stimulation, together facilitating a well-controlled experimental setup to investigate the neural correlates of visual hallucinations driven by flicker rhythmicity. Using rhythmic and arrhythmic FLS during fMRI scanning, we found that rhythmic FLS elicited stronger activation in higher order visual cortices compared with arrhythmic control. Consistently, we found that rhythmic flicker selectively increased connectivity between ventroanterior thalamic nuclei and higher order visual cortices, which was also positively associated with the subjective intensity of visual hallucinatory effects. As these thalamic and cortical areas do not receive primary visual inputs, it suggests that the thalamocortical connectivity changes relate to a higher order function of the thalamus, such as in the coordination of cortical activity. In sum, we present novel evidence for the role of specific thalamocortical interactions with ventroanterior nuclei within visual hallucinatory experiences. Importantly, this can inform future clinical research into the mechanistic underpinnings of pathologic hallucinations.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"9 1","pages":"1-17"},"PeriodicalIF":3.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949548/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network NeurosciencePub Date : 2024-12-10eCollection Date: 2024-01-01DOI: 10.1162/netn_a_00403
Daniel Haşegan, Caleb Geniesse, Samir Chowdhury, Manish Saggar
{"title":"Deconstructing the Mapper algorithm to extract richer topological and temporal features from functional neuroimaging data.","authors":"Daniel Haşegan, Caleb Geniesse, Samir Chowdhury, Manish Saggar","doi":"10.1162/netn_a_00403","DOIUrl":"10.1162/netn_a_00403","url":null,"abstract":"<p><p>Capturing and tracking large-scale brain activity dynamics holds the potential to deepen our understanding of cognition. Previously, tools from topological data analysis, especially Mapper, have been successfully used to mine brain activity dynamics at the highest spatiotemporal resolutions. Even though it is a relatively established tool within the field of topological data analysis, Mapper results are highly impacted by parameter selection. Given that noninvasive human neuroimaging data (e.g., from fMRI) is typically fraught with artifacts and no gold standards exist regarding \"true\" state transitions, we argue for a thorough examination of Mapper parameter choices to better reveal their impact. Using synthetic data (with known transition structure) and real fMRI data, we explore a variety of parameter choices for each Mapper step, thereby providing guidance and heuristics for the field. We also release our parameter exploration toolbox as a software package to make it easier for scientists to investigate and apply Mapper to any dataset.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1355-1382"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11675014/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network NeurosciencePub Date : 2024-12-10eCollection Date: 2024-01-01DOI: 10.1162/netn_a_00391
Suhnyoung Jun, Thomas H Alderson, Stephen M Malone, Jeremy Harper, Ruskin H Hunt, Kathleen M Thomas, William G Iacono, Sylia Wilson, Sepideh Sadaghiani
{"title":"Rapid dynamics of electrophysiological connectome states are heritable.","authors":"Suhnyoung Jun, Thomas H Alderson, Stephen M Malone, Jeremy Harper, Ruskin H Hunt, Kathleen M Thomas, William G Iacono, Sylia Wilson, Sepideh Sadaghiani","doi":"10.1162/netn_a_00391","DOIUrl":"10.1162/netn_a_00391","url":null,"abstract":"<p><p>Time-varying changes in whole-brain connectivity patterns, or connectome state dynamics, are a prominent feature of brain activity with broad functional implications. While infraslow (<0.1 Hz) connectome dynamics have been extensively studied with fMRI, rapid dynamics highly relevant for cognition are poorly understood. Here, we asked whether rapid electrophysiological connectome dynamics constitute subject-specific brain traits and to what extent they are under genetic influence. Using source-localized EEG connectomes during resting state (<i>N</i> = 928, 473 females), we quantified the heritability of multivariate (multistate) features describing temporal or spatial characteristics of connectome dynamics. States switched rapidly every ∼60-500 ms. Temporal features were heritable, particularly Fractional Occupancy (in theta, alpha, beta, and gamma bands) and Transition Probability (in theta, alpha, and gamma bands), representing the duration spent in each state and the frequency of state switches, respectively. Genetic effects explained a substantial proportion of the phenotypic variance of these features: Fractional Occupancy in beta (44.3%) and gamma (39.8%) bands and Transition Probability in theta (38.4%), alpha (63.3%), beta (22.6%), and gamma (40%) bands. However, we found no evidence for the heritability of dynamic spatial features, specifically states' Modularity and connectivity pattern. We conclude that genetic effects shape individuals' connectome dynamics at rapid timescales, specifically states' overall occurrence and sequencing.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1065-1088"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674403/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network NeurosciencePub Date : 2024-12-10eCollection Date: 2024-01-01DOI: 10.1162/netn_a_00394
Ilaria Carannante, Martina Scolamiero, J J Johannes Hjorth, Alexander Kozlov, Bo Bekkouche, Lihao Guo, Arvind Kumar, Wojciech Chachólski, Jeanette Hellgren Kotaleski
{"title":"The impact of Parkinson's disease on striatal network connectivity and corticostriatal drive: An in silico study.","authors":"Ilaria Carannante, Martina Scolamiero, J J Johannes Hjorth, Alexander Kozlov, Bo Bekkouche, Lihao Guo, Arvind Kumar, Wojciech Chachólski, Jeanette Hellgren Kotaleski","doi":"10.1162/netn_a_00394","DOIUrl":"10.1162/netn_a_00394","url":null,"abstract":"<p><p>Striatum, the input stage of the basal ganglia, is important for sensory-motor integration, initiation and selection of behavior, as well as reward learning. Striatum receives glutamatergic inputs from mainly cortex and thalamus. In rodents, the striatal projection neurons (SPNs), giving rise to the direct and the indirect pathway (dSPNs and iSPNs, respectively), account for 95% of the neurons, and the remaining 5% are GABAergic and cholinergic interneurons. Interneuron axon terminals as well as local dSPN and iSPN axon collaterals form an intricate striatal network. Following chronic dopamine depletion as in Parkinson's disease (PD), both morphological and electrophysiological striatal neuronal features have been shown to be altered in rodent models. Our goal with this in silico study is twofold: (a) to predict and quantify how the intrastriatal network connectivity structure becomes altered as a consequence of the morphological changes reported at the single-neuron level and (b) to investigate how the effective glutamatergic drive to the SPNs would need to be altered to account for the activity level seen in SPNs during PD. In summary, we predict that the richness of the connectivity motifs in the striatal network is significantly decreased during PD while, at the same time, a substantial enhancement of the effective glutamatergic drive to striatum is present.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1149-1172"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674317/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network NeurosciencePub Date : 2024-12-10eCollection Date: 2024-01-01DOI: 10.1162/netn_a_00410
Rubén Herzog, Pedro A M Mediano, Fernando E Rosas, Andrea I Luppi, Yonatan Sanz-Perl, Enzo Tagliazucchi, Morten L Kringelbach, Rodrigo Cofré, Gustavo Deco
{"title":"Neural mass modeling for the masses: Democratizing access to whole-brain biophysical modeling with FastDMF.","authors":"Rubén Herzog, Pedro A M Mediano, Fernando E Rosas, Andrea I Luppi, Yonatan Sanz-Perl, Enzo Tagliazucchi, Morten L Kringelbach, Rodrigo Cofré, Gustavo Deco","doi":"10.1162/netn_a_00410","DOIUrl":"10.1162/netn_a_00410","url":null,"abstract":"<p><p>Different whole-brain computational models have been recently developed to investigate hypotheses related to brain mechanisms. Among these, the Dynamic Mean Field (DMF) model is particularly attractive, combining a biophysically realistic model that is scaled up via a mean-field approach and multimodal imaging data. However, an important barrier to the widespread usage of the DMF model is that current implementations are computationally expensive, supporting only simulations on brain parcellations that consider less than 100 brain regions. Here, we introduce an efficient and accessible implementation of the DMF model: the FastDMF. By leveraging analytical and numerical advances-including a novel estimation of the feedback inhibition control parameter and a Bayesian optimization algorithm-the FastDMF circumvents various computational bottlenecks of previous implementations, improving interpretability, performance, and memory use. Furthermore, these advances allow the FastDMF to increase the number of simulated regions by one order of magnitude, as confirmed by the good fit to fMRI data parcellated at 90 and 1,000 regions. These advances open the way to the widespread use of biophysically grounded whole-brain models for investigating the interplay between anatomy, function, and brain dynamics and to identify mechanistic explanations of recent results obtained from fine-grained neuroimaging recordings.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"8 4","pages":"1590-1612"},"PeriodicalIF":3.6,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11674928/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}