Many neurological and psychiatric diseases in humans are caused by disruptions to large-scale functional properties of the brain, including functional connectivity. There has been growing interest in discovering the functional organization of brain networks in larger animal models. As a result, the use of translational pig models in neuroscience has significantly increased in the past decades. The gyrencephalic pig brain resembles the human brain more in anatomy, growth, and development than the brains of commonly used small laboratory animals such as rodents. In this work, resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) data were acquired from a group of pigs ( = 12). rs-fMRI data were analyzed for resting-state networks (RSNs) by using independent component analysis and sparse dictionary learning. Six RSNs (executive control, cerebellar, sensorimotor, visual, auditory, and default mode) were detected that resemble their counterparts in human brains, as measured by Pearson spatial correlations and mean ratios. Supporting evidence of the validity of these RSNs was provided through the evaluation and quantification of structural connectivity measures (mean diffusivity, fractional anisotropy, fiber length, and fiber density) estimated from the DTI data. This study shows that as a translational, large animal model, pigs demonstrate great potential for mapping connectome-scale functional connectivity in experimental modeling of human brain disorders.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6727477PMC
http://dx.doi.org/10.1089/brain.2019.0673DOI Listing

Publication Analysis

Top Keywords

resting-state networks
8
human brains
8
functional connectivity
8
human brain
8
dti data
8
functional
5
brain
5
pig brains
4
brains homologous
4
homologous resting-state
4

Similar Publications

Background: Repetitive transcranial magnetic stimulation enhances cognition in people with mild cognitive impairment (MCI). Whereas conventional treatment requires daily sessions for 4-6 weeks, accelerated intermittent theta burst stimulation (iTBS) shortens the treatment course to just 3 days, substantially improving feasibility of use in people with MCI. We conducted a Phase I safety and feasibility trial of iTBS in MCI, finding preliminary evidence of cognitive improvement.

View Article and Find Full Text PDF

Reorganization of Dynamic Network in Stroke Patients and Its Potential for Predicting Motor Recovery.

Neural Plast

January 2025

Department of Neurology, The Fifth Affiliated hospital of Guangxi Medical University, The First People's Hospital of Nanning, Nanning, China.

The investigation of brain functional network dynamics offers a promising approach to understanding network reorganization poststroke. This study aims to explore the dynamic network configurations associated with motor recovery in stroke patients and assess their predictive potential using multilayer network analysis. Resting-state functional magnetic resonance imaging data were collected from patients with subacute stroke within 2 weeks of onset and from matched healthy controls (HCs).

View Article and Find Full Text PDF

Unlabelled: Juvenile myoclonic epilepsy (JME) exhibits abnormal functional connectivity of brain networks at multiple frequencies. We used the multilayer network model to address the heterogeneous features at different frequencies and assess the mechanisms of functional integration and segregation of brain networks in JME patients. To address the possibility of false edges or missing edges during network construction, we combined multilayer networks with link prediction techniques.

View Article and Find Full Text PDF

Bayesian thresholded modeling for integrating brain node and network predictors.

Biostatistics

December 2024

Department of Biostatistics, Yale University, 300 George St, New Haven, CT 06511, United States.

Progress in neuroscience has provided unprecedented opportunities to advance our understanding of brain alterations and their correspondence to phenotypic profiles. With data collected from various imaging techniques, studies have integrated different types of information ranging from brain structure, function, or metabolism. More recently, an emerging way to categorize imaging traits is through a metric hierarchy, including localized node-level measurements and interactive network-level metrics.

View Article and Find Full Text PDF

Trait mindfulness refers to one's disposition or tendency to pay attention to their experiences in the present moment, in a non-judgmental and accepting way. Trait mindfulness has been robustly associated with positive mental health outcomes, but its neural underpinnings are poorly understood. Prior resting-state fMRI studies have associated trait mindfulness with within- and between-network connectivity of the default-mode (DMN), fronto-parietal (FPN), and salience networks.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!