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Human Brain Mapping Mar 2019The hippocampus, a hub of activity for a variety of important cognitive processes, is a target of increasing interest for researchers and clinicians....
The hippocampus, a hub of activity for a variety of important cognitive processes, is a target of increasing interest for researchers and clinicians. Magnetoencephalography (MEG) is an attractive technique for imaging spectro-temporal aspects of function, for example, neural oscillations and network timing, especially in shallow cortical structures. However, the decrease in MEG signal-to-noise ratio as a function of source depth implies that the utility of MEG for investigations of deeper brain structures, including the hippocampus, is less clear. To determine whether MEG can be used to detect and localize activity from the hippocampus, we executed a systematic review of the existing literature and found successful detection of oscillatory neural activity originating in the hippocampus with MEG. Prerequisites are the use of established experimental paradigms, adequate coregistration, forward modeling, analysis methods, optimization of signal-to-noise ratios, and protocol trial designs that maximize contrast for hippocampal activity while minimizing those from other brain regions. While localizing activity to specific sub-structures within the hippocampus has not been achieved, we provide recommendations for improving the reliability of such endeavors.
Topics: Brain Mapping; Hippocampus; Humans; Magnetoencephalography
PubMed: 30378210
DOI: 10.1002/hbm.24445 -
Socioaffective Neuroscience & Psychology 2016Cognitive impairments are a core feature in schizophrenia and are linked to poor social functioning. Numerous studies have shown that cognitive remediation can enhance... (Review)
Review
BACKGROUND
Cognitive impairments are a core feature in schizophrenia and are linked to poor social functioning. Numerous studies have shown that cognitive remediation can enhance cognitive and functional abilities in patients with this pathology. The underlying mechanism of these behavioral improvements seems to be related to structural and functional changes in the brain. However, studies on neural correlates of such enhancement remain scarce.
OBJECTIVES
We explored the neural correlates of cognitive enhancement following cognitive remediation interventions in schizophrenia and the differential effect between cognitive training and other therapeutic interventions or patients' usual care.
METHOD
We searched MEDLINE, PsycInfo, and ScienceDirect databases for studies on cognitive remediation therapy in schizophrenia that used neuroimaging techniques and a randomized design. Search terms included randomized controlled trial, cognitive remediation, cognitive training, rehabilitation, magnetic resonance imaging, positron emission tomography, electroencephalography, magnetoencephalography, near infrared spectroscopy, and diffusion tensor imaging. We selected randomized controlled trials that proposed multiple sessions of cognitive training to adult patients with a schizophrenia spectrum disorder and assessed its efficacy with imaging techniques.
RESULTS
In total, 15 reports involving 19 studies were included in the systematic review. They involved a total of 455 adult patients, 271 of whom received cognitive remediation. Cognitive remediation therapy seems to provide a neurobiological enhancing effect in schizophrenia. After therapy, increased activations are observed in various brain regions mainly in frontal - especially prefrontal - and also in occipital and anterior cingulate regions during working memory and executive tasks. Several studies provide evidence of an improved functional connectivity after cognitive training, suggesting a neuroplastic effect of therapy through mechanisms of functional reorganization. Neurocognitive and social-cognitive training may have a cumulative effect on neural networks involved in social cognition. The variety of proposed programs, imaging tasks, and techniques may explain the heterogeneity of observed neural improvements. Future studies would need to specify the effect of cognitive training depending on those variables.
PubMed: 26993787
DOI: 10.3402/snp.v6.30054 -
Clinical Neurophysiology : Official... Sep 2017Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these... (Review)
Review
OBJECTIVE
Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients.
METHOD
A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed.
RESULTS
Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection and analysis need to be taken into consideration.
CONCLUSION
Spontaneous MEG data show that local and global neural organization is altered in SZ patients. MEG is a highly promising tool to fill in knowledge gaps about the neurophysiology of SZ. However, to reach its fullest potential, basic methodological challenges need to be overcome.
SIGNIFICANCE
MEG-based resting-state power and connectivity findings could be great assets to clinical and translational research in psychiatry, and SZ in particular.
Topics: Brain; Brain Mapping; Humans; Magnetic Resonance Imaging; Magnetoencephalography; Nerve Net; Rest; Schizophrenia
PubMed: 28756348
DOI: 10.1016/j.clinph.2017.06.246 -
Neuroscience and Biobehavioral Reviews Sep 2017Our objective was to identify the physiological measures that are sensitive to assessing cognitive workload across the spectrum of cognitive impairments. Three database... (Review)
Review
Our objective was to identify the physiological measures that are sensitive to assessing cognitive workload across the spectrum of cognitive impairments. Three database searches were conducted: PubMed, PsychINFO, and Web of Science. Studies from the last decade that used physiological measures of cognitive workload in older adults (mean age >65 years-old) were reviewed. The cognitive workload of healthy older individuals was compared with the cognitive workload of younger adults, patients with mild cognitive impairment (MCI), and patients with Alzheimer's diseases (AD). The most common measures of cognitive workload included: electroencephalography, magnetoencephalography, functional magnetic resonance imaging, pupillometry, and heart rate variability. These physiological measures consistently showed greater cognitive workload in healthy older adults compared to younger adults when performing the same task. The same was observed in patients with MCI compared to healthy older adults. Behavioral performance declined when the available cognitive resources became insufficient to cope with the cognitive demands of a task, such as in AD. These findings may have implications for clinical practice and future cognitive interventions.
Topics: Aging; Brain; Cognition; Cognitive Dysfunction; Humans
PubMed: 28711663
DOI: 10.1016/j.neubiorev.2017.07.001 -
Brain Structure & Function Mar 2024This systematic review with a meta-analysis aimed to identify the altered brain structure and function in carpal tunnel syndrome (CTS) by summarizing the literature... (Meta-Analysis)
Meta-Analysis
This systematic review with a meta-analysis aimed to identify the altered brain structure and function in carpal tunnel syndrome (CTS) by summarizing the literature about magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG) outcomes compared to healthy controls (HC). CTS is the most common nerve entrapment in the arm associated with altered peripheral and central nociceptive system. PRISMA guidelines were used to report the outcomes. Six databases were searched for relevant literature (Web of Science, Scopus, PubMed, Sage, EBSCO host, and Cochrane). Eligible studies comparing MRI, fMRI, and MEG findings in people with CTS (present for at least 2 months) and HC through the following parameters: (1) interdigit cortical separation distance, (2) white and grey matter changes, (3) peak latency of M20 wave and recovery function of N20 from the somatosensory cortex (SI), and (4) surface area of activated digit cortical representation. The results from different studies were pooled and a meta-analysis was done. From 17 included, there was a significant reduction of interdigit cortical separation distance of index-middle and index-little fingers in the CTS (SMD = - 0.869, 95% CI (- 1.325, - 0.413), p-value = 0.000) and (SMD = - 0.79, 95% CI (- 1.217, - 0.364), p-value = 0.000), respectively. Middle-little fingers interdigit separation showed no difference (SMD = - 0.2, 95% CI (- 0.903, 1.309), p-value = 0.718). There is evidence supporting the altered brain structure and function in CTS as evidenced by reduction of interdigit cortical separation distance, and excessive blurring and disinhibition of SI, with low resting state functional connectivity. Thus, centrally directed therapeutic approaches might complement peripheral treatments.
Topics: Humans; Carpal Tunnel Syndrome; Brain Mapping; Magnetic Resonance Imaging; Fingers; Somatosensory Cortex
PubMed: 38165482
DOI: 10.1007/s00429-023-02737-5 -
Brain Connectivity Apr 2024Persisting imbalance and falls in community-dwelling traumatic brain injury (TBI) survivors are linked to reduced long-term survival. However, a detailed understanding... (Review)
Review
Persisting imbalance and falls in community-dwelling traumatic brain injury (TBI) survivors are linked to reduced long-term survival. However, a detailed understanding of the impact of TBI upon the brain mechanisms mediating imbalance is lacking. To understand the state of the art concerning the brain mechanisms mediating imbalance in TBI, we performed a systematic review of the literature. PubMed, Web of Science, and Scopus were searched and peer-reviewed research articles in humans, with any severity of TBI (mild, moderate, severe, or concussion), which linked a postural balance assessment (objective or subjective) with brain imaging (through computed tomography, T1-weighted imaging, functional magnetic resonance imaging [fMRI], resting-state fMRI, diffusion tensor imaging, magnetic resonance spectroscopy, single-photon emission computed tomography, electroencephalography, magnetoencephalography, near-infrared spectroscopy, and evoked potentials) were included. Out of 1940 articles, 60 were retrieved and screened, and 25 articles fulfilling inclusion criteria were included. The most consistent finding was the link between imbalance and the cerebellum; however, the regions within the cerebellum were inconsistent. The lack of consistent findings could reflect that imbalance in TBI is due to a widespread brain network dysfunction, as opposed to focal cortical damage. The inconsistency in the reported findings may also be attributed to heterogeneity of methodology, including data analytical techniques, small sample sizes, and choice of control groups. Future studies should include a detailed clinical phenotyping of vestibular function in TBI patients to account for the confounding effect of peripheral vestibular disorders on imbalance and brain imaging.
Topics: Humans; Brain Injuries, Traumatic; Postural Balance; Brain; Magnetic Resonance Imaging
PubMed: 38343363
DOI: 10.1089/brain.2023.0064 -
Frontiers in Human Neuroscience 2020The development of language functions is of great interest to neuroscientists, as these functions are among the fundamental capacities of human cognition. For many...
The development of language functions is of great interest to neuroscientists, as these functions are among the fundamental capacities of human cognition. For many years, researchers aimed at identifying cerebral correlates of language abilities. More recently, the development of new data analysis tools has generated a shift toward the investigation of complex cerebral networks. In 2015, Weiss-Croft and Baldeweg published a very interesting systematic review on the development of functional language networks, explored through the use of functional magnetic resonance imaging (fMRI). Compared to fMRI and because of their excellent temporal resolution, magnetoencephalography (MEG) and electroencephalography (EEG) provide different and important information on brain activity. Both therefore constitute crucial neuroimaging techniques for the investigation of the maturation of functional language brain networks. The main objective of this systematic review is to provide a state of knowledge on the investigation of language-related cerebral networks in children, through the use of EEG and MEG, as well as a detailed portrait of relevant MEG and EEG data analysis methods used in that specific research context. To do so, we have summarized the results and systematically compared the methodological approach of 24 peer-reviewed EEG or MEG scientific studies that included healthy children and children with or at high risk of language disabilities, from birth up to 18 years of age. All included studies employed functional and effective connectivity measures, such as coherence, phase locking value, and Phase Slope Index, and did so using different experimental paradigms (e.g., at rest or during language-related tasks). This review will provide more insight into the use of EEG and MEG for the study of language networks in children, contribute to the current state of knowledge on the developmental path of functional connectivity in language networks during childhood and adolescence, and finally allow future studies to choose the most appropriate type of connectivity analysis.
PubMed: 32226367
DOI: 10.3389/fnhum.2020.00062 -
Brain Topography Sep 2019Electromagnetic source characterisation requires accurate volume conductor models representing head geometry and the electrical conductivity field. Head tissue... (Meta-Analysis)
Meta-Analysis
Electromagnetic source characterisation requires accurate volume conductor models representing head geometry and the electrical conductivity field. Head tissue conductivity is often assumed from previous literature, however, despite extensive research, measurements are inconsistent. A meta-analysis of reported human head electrical conductivity values was therefore conducted to determine significant variation and subsequent influential factors. Of 3121 identified publications spanning three databases, 56 papers were included in data extraction. Conductivity values were categorised according to tissue type, and recorded alongside methodology, measurement condition, current frequency, tissue temperature, participant pathology and age. We found variation in electrical conductivity of the whole-skull, the spongiform layer of the skull, isotropic, perpendicularly- and parallelly-oriented white matter (WM) and the brain-to-skull-conductivity ratio (BSCR) could be significantly attributed to a combination of differences in methodology and demographics. This large variation should be acknowledged, and care should be taken when creating volume conductor models, ideally constructing them on an individual basis, rather than assuming them from the literature. When personalised models are unavailable, it is suggested weighted average means from the current meta-analysis are used. Assigning conductivity as: 0.41 S/m for the scalp, 0.02 S/m for the whole skull, or when better modelled as a three-layer skull 0.048 S/m for the spongiform layer, 0.007 S/m for the inner compact and 0.005 S/m for the outer compact, as well as 1.71 S/m for the CSF, 0.47 S/m for the grey matter, 0.22 S/m for WM and 50.4 for the BSCR.
Topics: Brain; Computer Simulation; Electric Conductivity; Electroencephalography; Gray Matter; Head; Humans; Scalp; Skull; White Matter
PubMed: 31054104
DOI: 10.1007/s10548-019-00710-2 -
Infant Behavior & Development Feb 2020The past decade has seen the emergence of neuroimaging studies of infant populations. Incorporating imaging has resulted in invaluable insights about neurodevelopment at...
The past decade has seen the emergence of neuroimaging studies of infant populations. Incorporating imaging has resulted in invaluable insights about neurodevelopment at the start of life. However, little has been enquired of the experimental specifications and study characteristics of typical findings. This review systematically screened empirical studies that used electroencephalography (EEG), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) on infants (max. age of 24 months). From more than 21,000 publications, a total of 710 records were included for analyses. With the exception of EEG studies, infant studies with MEG, fNIRS, and fMRI were most often conducted around birth and at 12 months. The vast majority of infant studies came from North America, with very few studies conducted in Africa, certain parts of South America, and Southeast Asia. Finally, longitudinal neuroimaging studies were inclined to adopt EEG, followed by fMRI, fNIRS, and MEG. These results show that there is compelling need for studies with larger sample sizes, studies investigating a broader range of infant developmental periods, and studies from under- and less-developed regions in the world. Addressing these shortcomings in the future will provide a more representative and accurate understanding of neurodevelopment in infancy.
Topics: Brain; Brain Mapping; Child Development; Electroencephalography; Female; Humans; Infant; Infant, Newborn; Longitudinal Studies; Magnetic Resonance Imaging; Magnetoencephalography; Male; Neuroimaging; Spectroscopy, Near-Infrared
PubMed: 31778859
DOI: 10.1016/j.infbeh.2019.101389 -
Frontiers in Neuroscience 2018Familiarity in music has been reported as an important factor modulating emotional and hedonic responses in the brain. Familiarity and repetition may increase the liking...
Familiarity in music has been reported as an important factor modulating emotional and hedonic responses in the brain. Familiarity and repetition may increase the liking of a piece of music, thus inducing positive emotions. Neuroimaging studies have focused on identifying the brain regions involved in the processing of familiar and unfamiliar musical stimuli. However, the use of different modalities and experimental designs has led to discrepant results and it is not clear which areas of the brain are most reliably engaged when listening to familiar and unfamiliar musical excerpts. In the present study, we conducted a systematic review from three databases (Medline, PsychoINFO, and Embase) using the keywords (recognition OR familiar OR familiarity OR exposure effect OR repetition) AND (music OR song) AND (brain OR brains OR neuroimaging OR functional Magnetic Resonance Imaging OR Position Emission Tomography OR Electroencephalography OR Event Related Potential OR Magnetoencephalography). Of the 704 titles identified, 23 neuroimaging studies met our inclusion criteria for the systematic review. After removing studies providing insufficient information or contrasts, 11 studies (involving 212 participants) qualified for the meta-analysis using the activation likelihood estimation (ALE) approach. Our results did not find significant peak activations consistently across included studies. Using a less conservative approach ( < 0.001, uncorrected for multiple comparisons) we found that the left superior frontal gyrus, the ventral lateral (VL) nucleus of the left thalamus, and the left medial surface of the superior frontal gyrus had the highest likelihood of being activated by familiar music. On the other hand, the left insula, and the right anterior cingulate cortex had the highest likelihood of being activated by unfamiliar music. We had expected limbic structures as top clusters when listening to familiar music. But, instead, music familiarity had a motor pattern of activation. This could reflect an audio-motor synchronization to the rhythm which is more engaging for familiar tunes, and/or a sing-along response in one's mind, anticipating melodic, harmonic progressions, rhythms, timbres, and lyric events in the familiar songs. These data provide evidence for the need for larger neuroimaging studies to understand the neural correlates of music familiarity.
PubMed: 30344470
DOI: 10.3389/fnins.2018.00686