Besides being responsible for olfaction and air intake, the nose contains abundant vasculature and autonomic nervous system innervations, and it is a cerebrospinal fluid clearance site. Therefore, the nose is an attractive target for functional MRI (fMRI). Yet, nose fMRI has not been possible so far due to signal losses originating from nasal air-tissue interfaces. Here, we demonstrated feasibility of nose fMRI by using novel ultrashort/zero echo time (TE) MRI. Results obtained in the resting-state from 13 healthy participants at 7T and in 5 awake mice at 9.4T revealed a highly reproducible resting-state nose functional network that likely reflects autonomic nervous system activity. Another network observed in humans involves the nose, major brain vessels and CSF spaces, presenting a temporal dynamic that correlates with heart rate and breathing rate. These resting-state nose functional signals should help elucidate peripheral and central nervous system integrations.
- MeSH
- Autonomic Nervous System physiology diagnostic imaging MeSH
- Adult MeSH
- Humans MeSH
- Magnetic Resonance Imaging * methods MeSH
- Brain Mapping methods MeSH
- Young Adult MeSH
- Brain physiology diagnostic imaging MeSH
- Mice MeSH
- Nose * physiology diagnostic imaging MeSH
- Rest physiology MeSH
- Heart Rate physiology MeSH
- Animals MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Mice MeSH
- Female MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: Patients with bipolar disorder (BD) and major depressive disorder (MDD) exhibit depressive episodes with similar symptoms despite having different and poorly understood underlying neurobiology, often leading to misdiagnosis and improper treatment. This exploratory study examined whole-brain functional connectivity (FC) using FC multivariate pattern analysis (fc-MVPA) to identify the FC patterns with the greatest ability to distinguish between currently depressed patients with BD type I (BD I) and those with MDD. METHODOLOGY: In a cross-sectional design, 41 BD I, 40 MDD patients and 63 control participants completed resting state functional magnetic resonance imaging scans. Data-driven fc-MVPA, as implemented in the CONN toolbox, was used to identify clusters with differential FC patterns between BD patients and MDD patients. The identified cluster was used as a seed in a post hoc seed-based analysis (SBA) to reveal associated connectivity patterns, followed by a secondary ROI-to-ROI analysis to characterize differences in connectivity between these patterns among BD I patients, MDD patients and controls. RESULTS: FC-MVPA identified one cluster located in the right frontal pole (RFP). The subsequent SBA revealed greater FC between the RFP and posterior cingulate cortex (PCC) and between the RFP and the left inferior/middle temporal gyrus (LI/MTG) and lower FC between the RFP and the left precentral gyrus (LPCG), left lingual gyrus/occipital cortex (LLG/OCC) and right occipital cortex (ROCC) in MDD patients than in BD patients. Compared with the controls, ROI-to-ROI analysis revealed lower FC between the RFP and the PCC and greater FC between the RFP and the LPCG, LLG/OCC and ROCC in BD patients; in MDD patients, the analysis revealed lower FC between the RFP and the LLG/OCC and ROCC and greater FC between the RFP and the LI/MTG. CONCLUSIONS: Differences in the RFP FC patterns between currently depressed patients with BD and those with MDD suggest potential neuroimaging markers that should be further examined. Specifically, BD patients exhibit increased FC between the RFP and the motor and visual networks, which is associated with psychomotor symptoms and heightened compensatory frontoparietal FC to counter distractibility. In contrast, MDD patients exhibit increased FC between the RFP and the default mode network, corresponding to sustained self-focus and rumination.
- MeSH
- Bipolar Disorder * physiopathology diagnostic imaging MeSH
- Depressive Disorder, Major * physiopathology diagnostic imaging MeSH
- Adult MeSH
- Connectome methods MeSH
- Middle Aged MeSH
- Humans MeSH
- Magnetic Resonance Imaging * methods MeSH
- Brain Mapping methods MeSH
- Brain physiopathology diagnostic imaging MeSH
- Multivariate Analysis MeSH
- Nerve Net diagnostic imaging physiopathology MeSH
- Neural Pathways physiopathology diagnostic imaging MeSH
- Cross-Sectional Studies MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
Transcranial Magnetic Stimulation (TMS) is a non-invasive technique for analyzing the central and peripheral nervous system. TMS could be a powerful therapeutic technique for neurological disorders. TMS has also shown potential in treating various neurophysiological complications, such as depression, anxiety, and obsessive-compulsive disorders, without pain and analgesics. Despite advancements in diagnosis and treatment, there has been an increase in the prevalence of brain cancer globally. For surgical planning, mapping brain tumors has proven challenging, particularly those localized in expressive regions. Preoperative brain tumor mapping may lower the possibility of postoperative morbidity in surrounding areas. A navigated TMS (nTMS) uses magnetic resonance imaging (MRI) to enable precise mapping during navigated brain stimulation. The resulting magnetic impulses can be precisely applied to the target spot in the cortical region by employing nTMS. This review focuses on nTMS for preoperative planning for brain cancer. This study reviews several studies on TMS and its subtypes in treating cancer and surgical planning. nTMS gives wider and improved dimensions of preoperative planning of the motor-eloquent areas in brain tumor patients. nTMS also predicts postoperative neurological deficits, which might be helpful in counseling patients. nTMS have the potential for finding possible abnormalities in the motor cortex areas.
- MeSH
- Humans MeSH
- Magnetic Resonance Imaging methods MeSH
- Brain Mapping methods MeSH
- Motor Cortex diagnostic imaging MeSH
- Brain Neoplasms * surgery MeSH
- Neuronavigation methods MeSH
- Preoperative Care * methods MeSH
- Transcranial Magnetic Stimulation * methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Alterations in the default mode network (DMN) are associated with aging. We assessed age-dependent changes of DMN interactions and correlations with a battery of neuropsychological tests, to understand the differences of DMN directed connectivity between young and older subjects. Using a novel multivariate analysis method on resting-state functional MRI data from fifty young and thirty-one healthy older subjects, we calculated intra- and inter-DMN 4-nodes directed pathways. For the old subject group, we calculated the partial correlations of inter-DMN pathways with: psychomotor speed and working memory, executive function, language, long-term memory and visuospatial function. Pathways connecting the DMN with visual and limbic regions in older subjects engaged at BOLD low frequency and involved the dorsal posterior cingulate cortex (PCC), whereas in young subjects, they were at high frequency and involved the ventral PCC. Pathways combining the sensorimotor (SM) cortex and the DMN, were SM efferent in the young subjects and SM afferent in the older subjects. Most DMN efferent pathways correlated with reduced speed and working memory. We suggest that the reduced sensorimotor efferent and the increased need to control such activities, cause a higher dependency on external versus internal cues thus suggesting how physical activity might slow aging.
- MeSH
- Memory, Short-Term MeSH
- Humans MeSH
- Magnetic Resonance Imaging methods MeSH
- Brain Mapping * methods MeSH
- Brain * diagnostic imaging MeSH
- Neural Pathways MeSH
- Aged MeSH
- Aging MeSH
- Healthy Volunteers MeSH
- Check Tag
- Humans MeSH
- Aged MeSH
- Publication type
- Journal Article MeSH
Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.
- MeSH
- Biomarkers MeSH
- Humans MeSH
- Magnetic Resonance Imaging methods MeSH
- Brain Mapping methods MeSH
- Neurodegenerative Diseases * MeSH
- Neuroimaging MeSH
- Parkinson Disease * diagnostic imaging pathology MeSH
- Disease Progression MeSH
- Iron MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Recognition memory is the ability to recognize previously encountered objects. Even this relatively simple, yet extremely fast, ability requires the coordinated activity of large-scale brain networks. However, little is known about the sub-second dynamics of these networks. The majority of current studies into large-scale network dynamics is primarily based on imaging techniques suffering from either poor temporal or spatial resolution. We investigated the dynamics of large-scale functional brain networks underlying recognition memory at the millisecond scale. Specifically, we analyzed dynamic effective connectivity from intracranial electroencephalography while epileptic subjects (n = 18) performed a fast visual recognition memory task. Our data-driven investigation using Granger causality and the analysis of communities with the Louvain algorithm spotlighted a dynamic interplay of two large-scale networks associated with successful recognition. The first network involved the right visual ventral stream and bilateral frontal regions. It was characterized by early, predominantly bottom-up information flow peaking at 115 ms. It was followed by the involvement of another network with predominantly top-down connectivity peaking at 220 ms, mainly in the left anterior hemisphere. The transition between these two networks was associated with changes in network topology, evolving from a more segregated to a more integrated state. These results highlight that distinct large-scale brain networks involved in visual recognition memory unfold early and quickly, within the first 300 ms after stimulus onset. Our study extends the current understanding of the rapid network changes during rapid cognitive processes.
Stereoelectroencephalography (SEEG) records electrical brain activity with intracerebral electrodes. However, it has an inherently limited spatial coverage. Electrical source imaging (ESI) infers the position of the neural generators from the recorded electric potentials, and thus, could overcome this spatial undersampling problem. Here, we aimed to quantify the accuracy of SEEG ESI under clinical conditions. We measured the somatosensory evoked potential (SEP) in SEEG and in high-density EEG (HD-EEG) in 20 epilepsy surgery patients. To localize the source of the SEP, we employed standardized low resolution brain electromagnetic tomography (sLORETA) and equivalent current dipole (ECD) algorithms. Both sLORETA and ECD converged to similar solutions. Reflecting the large differences in the SEEG implantations, the localization error also varied in a wide range from 0.4 to 10 cm. The SEEG ESI localization error was linearly correlated with the distance from the putative neural source to the most activated contact. We show that it is possible to obtain reliable source reconstructions from SEEG under realistic clinical conditions, provided that the high signal fidelity recording contacts are sufficiently close to the source of the brain activity.
- MeSH
- Electroencephalography methods MeSH
- Electrocorticography * methods MeSH
- Epilepsy * surgery MeSH
- Humans MeSH
- Magnetic Resonance Imaging MeSH
- Brain Mapping methods MeSH
- Neuroimaging MeSH
- Evoked Potentials, Somatosensory MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Brain dynamics and the associations with spatial navigation in individuals with subjective cognitive decline (SCD) remain unknown. In this study, a hidden Markov model (HMM) was inferred from resting-state functional magnetic resonance imaging data in a cohort of 80 SCD and 77 normal control (NC) participants. By HMM, 12 states with distinct brain activity were identified. The SCD group showed increased fractional occupancy in the states with less activated ventral default mode, posterior salience, and visuospatial networks, while decreased fractional occupancy in the state with general network activation. The SCD group also showed decreased probabilities of transition into and out of the state with general network activation, suggesting an inability to dynamically upregulate and downregulate brain network activity. Significant correlations between brain dynamics and spatial navigation were observed. The combined features of spatial navigation and brain dynamics showed an area under the curve of 0.854 in distinguishing between SCD and NC. The findings may provide exploratory evidence of the reconfiguration of brain network dynamics underlying spatial deficits in SCD.
- MeSH
- Cognitive Dysfunction * psychology MeSH
- Humans MeSH
- Magnetic Resonance Imaging * methods MeSH
- Brain Mapping methods MeSH
- Brain physiology MeSH
- Probability MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The phenomenon of déjà vu (DV) has intrigued scientists for decades, yet its neurophysiological underpinnings remain elusive. Brain regions have been identified in which morphometry differs between healthy individuals according to the frequency of their DV experiences. This study built upon these findings by assessing if and how neural activity in these and other brain regions also differ with respect to DV experience. Resting-state fMRI was performed on 68 healthy volunteers, 44 of whom reported DV experiences (DV group) and 24 who did not (NDV group). Using multivariate analyses, we then assessed the (fractional) amplitude of low-frequency fluctuations (fALFF/ALFF), a metric that is believed to index brain tissue excitability, for five discrete frequency bands within sets of brain regions implicated in DV and those comprising the default mode network (DMN). Analyses revealed significantly lower values of fALFF/ALFF for specific frequency bands in the DV relative to the NDV group, particularly within mesiotemporal structures, bilateral putamina, right caudatum, bilateral superior frontal cortices, left lateral parietal cortex, dorsal and ventral medial prefrontal cortex, and the posterior cingulate cortex. The pattern of differences in fALFF/ALFF measures between the brains of individuals who have experienced DV and those who have not provides new neurophysiological insights into this phenomenon, including the potential role of the DMN. We suggest that the erroneous feeling of familiarity arises from a temporary disruption of cortico-subcortical circuitry together with the upregulation of cortical excitability.
- MeSH
- Emotions MeSH
- Humans MeSH
- Magnetic Resonance Imaging * methods MeSH
- Brain Mapping methods MeSH
- Brain diagnostic imaging MeSH
- Brain Waves * physiology MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
We wanted to verify the effect of combining multi-echo (ME) functional magnetic resonance imaging (fMRI) with slice acceleration in simultaneous multi-slice acquisition. The aim was to shed light on the benefits of multiple echoes for various acquisition settings, especially for levels of slice acceleration and flip angle. Whole-brain ME fMRI data were obtained from 26 healthy volunteers (using three echoes; seven runs with slice acceleration 1, 4, 6, and 8; and two different flip angles for each of the first three acceleration factors) and processed as single-echo (SE) data and ME data based on optimal combinations weighted by the contrast-to-noise ratio. Global metrics (temporal signal-to-noise ratio, signal-to-noise separation, number of active voxels, etc.) and local characteristics in regions of interest were used to evaluate SE and ME data. ME results outperformed SE results in all runs; the differences became more apparent for higher acceleration, where a significant decrease in data quality is observed. ME fMRI can improve the observed data quality metrics over SE fMRI for a wide range of accelerated fMRI acquisitions.
- MeSH
- Adult MeSH
- Echo-Planar Imaging methods MeSH
- Globus Pallidus diagnostic imaging physiology MeSH
- Humans MeSH
- Magnetic Resonance Imaging methods MeSH
- Brain Mapping methods MeSH
- Young Adult MeSH
- Cerebral Cortex diagnostic imaging physiology MeSH
- Image Processing, Computer-Assisted methods MeSH
- Psychomotor Performance physiology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
