scholarly journals From BDNF to reading: Neural activation and phonological processing as multiple mediators

2020 ◽  
Author(s):  
Sara Mascheretti ◽  
Meaghan Perdue ◽  
Bei Feng ◽  
Chiara Andreola ◽  
Ginette Dionne ◽  
...  
Keyword(s):  
Phonological Processing ◽  
Neurodevelopmental Disorder ◽  
Brain Activation ◽  
Brain Regions ◽  
Brain Morphology ◽  
Neural Activation ◽  
Imaging Data ◽  
Multiple Mediation ◽  
Val66met Polymorphism ◽  
Intermediate Phenotypes

The BDNF gene is a prominent promoter of neuronal development, maturation and plasticity. Its Val66Met polymorphism affects brain morphology and function within several areas and is associated with several cognitive functions and neurodevelopmental disorder susceptibility. Recently, it has been associated with reading, reading-related traits and altered neural activation in reading–related brain regions. However, it remains unknown if the intermediate phenotypes (IPs, such as brain activation and phonological skills) mediate the pathway from gene to reading or reading disability. By conducting a serial multiple mediation model in a sample of 94 children (age 5-13), our findings revealed no direct effects of genotype on reading. Instead, we found that genotype is associated with brain activation in reading-related and more domain general regions which in turn is associated with phonological processing which is associated with reading. These findings suggest that the BDNF- Val66Met polymorphism is related to reading via phonological processing and functional activation. These results support brain imaging data and neurocognitive traits as viable IPs for complex behaviors.

Reading musical notation versus English letters: Mapping brain activation with MEG

2017 ◽  
Vol 47 (2) ◽  
pp. 255-269 ◽  
Author(s):  
Ching-I Lu ◽  
Margaret L. Greenwald ◽  
Yung-Yang Lin ◽  
Susan M. Bowyer
Keyword(s):  
Cognitive Load ◽  
Left Hemisphere ◽  
Region Of Interest ◽  
Brain Activation ◽  
Brain Regions ◽  
High Temporal Resolution ◽  
Neural Activation ◽  
Professional Musicians ◽  
Musical Notation ◽  
Superior Parietal Cortex

Temporal and spatial analyses of brain function with magnetoencephalography (MEG) are seldom reported in studies of musical sight-reading. We used MEG to compare the timing and localization of brain regions active during print-to-sound translation of musical notation versus English letters. MEG recordings were made on 22 professional musicians during print-to-sound tasks involving low versus high cognitive load. The MEG data were analyzed using MR-FOCUSS, a current density imaging technique. A laterality index was calculated to determine which hemisphere had more neural activation during these music and language reading tasks, and showed brain activation more lateralized to the language dominant (left) hemisphere in these right-handed musicians. Both note and letter reading tasks required translation to phonological codes and activated left hemisphere language areas. Also, the superior parietal cortex was a region of interest bilaterally. The high temporal resolution of MEG, coupled with its spatial resolution, proved sensitive to differences in cognitive load in reading both letters and musical notes. MEG will be useful in future studies of how brain structure or function may change as a result of learning music.

scholarly journals Genetic and Environmental Influence on the Human Functional Connectome

2019 ◽  
Vol 30 (4) ◽  
pp. 2099-2113
Author(s):  
Andrew E Reineberg ◽  
Alexander S Hatoum ◽  
John K Hewitt ◽  
Marie T Banich ◽  
Naomi P Friedman
Keyword(s):  
Resting State ◽  
Environmental Influence ◽  
Brain Regions ◽  
Genetic Influence ◽  
Genetic Influences ◽  
Imaging Data ◽  
Functional Connections ◽  
Functional Connectome ◽  
Intermediate Phenotypes ◽  
Shared Environmental Influence

Abstract Detailed mapping of genetic and environmental influences on the functional connectome is a crucial step toward developing intermediate phenotypes between genes and clinical diagnoses or cognitive abilities. We analyzed resting-state functional magnetic resonance imaging data from two adult twin samples (Nos = 446 and 371) to quantify genetic and environmental influence on all pairwise functional connections between 264 brain regions (~35 000 functional connections). Nonshared environmental influence was high across the whole connectome. Approximately 14–22% of connections had nominally significant genetic influence in each sample, 4.6% were significant in both samples, and 1–2% had heritability estimates greater than 30%. Evidence of shared environmental influence was weak. Genetic influences on connections were distinct from genetic influences on a global summary measure of the connectome, network-based estimates of connectivity, and movement during the resting-state scan, as revealed by a novel connectome-wide bivariate genetic modeling procedure. The brain’s genetic organization is diverse and not as one would expect based solely on structure evident in nongenetically informative data or lower resolution data. As follow-up, we make novel classifications of functional connections and examine highly localized connections with particularly strong genetic influence. This high-resolution genetic taxonomy of brain connectivity will be useful in understanding genetic influences on brain disorders.

scholarly journals Reliability of neural food cue-reactivity in participants with obesity undergoing bariatric surgery: a 26-week longitudinal fMRI study

2020 ◽  
Author(s):  
Patrick Bach ◽  
Martin Grosshans ◽  
Anne Koopmann ◽  
Peter Kienle ◽  
Georgi Vassilev ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Treatment Outcome ◽  
Cue Reactivity ◽  
Intraclass Correlation ◽  
Brain Activation ◽  
Brain Regions ◽  
Current Data ◽  
Neural Activation ◽  
Food Craving ◽  
Good Reliability

AbstractObesity is highly prevalent worldwide and results in a high disease burden. The efforts to monitor and predict treatment outcome in participants with obesity using functional magnetic resonance imaging (fMRI) depends on the reliability of the investigated task-fMRI brain activation. To date, no study has investigated whole-brain reliability of neural food cue-reactivity. To close this gap, we analyzed the longitudinal reliability of an established food cue-reactivity task. Longitudinal reliability of neural food-cue-induced brain activation and subjective food craving ratings over three fMRI sessions (T0: 2 weeks before surgery, T1: 8 weeks and T2: 24 weeks after surgery) were investigated in N = 11 participants with obesity. We computed an array of established reliability estimates, including the intraclass correlation (ICC), the Dice and Jaccard coefficients and similarity of brain activation maps. The data indicated good reliability (ICC > 0.6) of subjective food craving ratings over 26 weeks and excellent reliability (ICC > 0.75) of brain activation signals for the contrast of interest (food > neutral) in the caudate, putamen, thalamus, middle cingulum, inferior, middle and superior occipital gyri, and middle and superior temporal gyri and cunei. Using similarity estimates, it was possible to re-identify individuals based on their neural activation maps (73%) with a fading degree of accuracy, when comparing fMRI sessions further apart. The results show excellent reliability of task-fMRI neural brain activation in several brain regions. Current data suggest that fMRI-based measures might indeed be suitable to monitor and predict treatment outcome in participants with obesity undergoing bariatric surgery.

Brain activation patterns elicited by the `Faces Symbol Test' — a pilot fMRI study

2008 ◽  
Vol 14 (3) ◽  
pp. 354-363 ◽  
Author(s):  
RH Grabner ◽  
F. Popotnig ◽  
S. Ropele ◽  
C. Neuper ◽  
F. Gorani ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Brain Activation ◽  
Brain Regions ◽  
Screening Tests ◽  
Choice Test ◽  
Imaging Data ◽  
Attention And Executive Control ◽  
Experimental Conditions ◽  
Activation Patterns ◽  
Serial Addition

The Faces Symbol Test (FST) has recently been proposed as a brief and patient-friendly screening instrument for the assessment of cognitive dysfunction in patients with multiple sclerosis (MS). However, in contrast to well-established MS screening tests such as the Paced Auditory Serial Addition Test, the neural correlates of the FST have not been investigated so far. In the present study, we developed a functional MRI (fMRI) version of the FST to provide first data on brain regions and networks involved in this test. A sample of 19 healthy participants completed a version of the FST adapted for fMRI, requiring matching of faces and symbols in a multiple choice test and two further experimental conditions drawing on cognitive subcomponents (face matching and symbol matching). Imaging data showed a differential involvement of a fronto-parieto-occipital network in the three conditions. The most demanding FST condition elicited brain activation patterns related with sustained attention and executive control. These results suggest that the FST recruits brain networks critical for higher-order cognitive functions often impaired in MS patients. Multiple Sclerosis 2008; 14: 354—363. http://msj.sagepub.com

scholarly journals Radial Basis Function-Sparse Partial Least Squares for Application to Brain Imaging Data

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Hisako Yoshida ◽  
Atsushi Kawaguchi ◽  
Kazuhiko Tsuruya
Keyword(s):  
Radial Basis Function ◽  
Least Squares ◽  
Partial Least Squares ◽  
Basis Function ◽  
Clinical Characteristics ◽  
Occipital Lobe ◽  
Brain Regions ◽  
Brain Morphology ◽  
Imaging Data ◽  
Radial Basis

Magnetic resonance imaging (MRI) data is an invaluable tool in brain morphology research. Here, we propose a novel statistical method for investigating the relationship between clinical characteristics and brain morphology based on three-dimensional MRI data via radial basis function-sparse partial least squares (RBF-sPLS). Our data consisted of MRI image intensities for multimillion voxels in a 3D array along with 73 clinical variables. This dataset represents a suitable application of RBF-sPLS because of a potential correlation among voxels as well as among clinical characteristics. Additionally, this method can simultaneously select both effective brain regions and clinical characteristics based on sparse modeling. This is in contrast to existing methods, which consider prespecified brain regions because of the computational difficulties involved in processing high-dimensional data. RBF-sPLS employs dimensionality reduction in order to overcome this obstacle. We have applied RBF-sPLS to a real dataset composed of 102 chronic kidney disease patients, while a comparison study used a simulated dataset. RBF-sPLS identified two brain regions of interest from our patient data: the temporal lobe and the occipital lobe, which are associated with aging and anemia, respectively. Our simulation study suggested that such brain regions are extracted with excellent accuracy using our method.

scholarly journals Disrupted metabolic connectivity in dopaminergic and cholinergic networks at different stages of dementia from 18F-FDG PET brain persistent homology network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tun-Wei Hsu ◽  
Jong-Ling Fuh ◽  
Da-Wei Wang ◽  
Li-Fen Chen ◽  
Chia-Jung Chang ◽  
...  
Keyword(s):  
Algebraic Topology ◽  
Fdg Pet ◽  
Persistent Homology ◽  
Network Connectivity ◽  
Brain Regions ◽  
Imaging Data ◽  
Cholinergic Pathways ◽  
Positron Emission ◽  
Metabolic Connectivity ◽  
Neurochemical Changes

AbstractDementia is related to the cellular accumulation of β-amyloid plaques, tau aggregates, or α-synuclein aggregates, or to neurotransmitter deficiencies in the dopaminergic and cholinergic pathways. Cellular and neurochemical changes are both involved in dementia pathology. However, the role of dopaminergic and cholinergic networks in metabolic connectivity at different stages of dementia remains unclear. The altered network organisation of the human brain characteristic of many neuropsychiatric and neurodegenerative disorders can be detected using persistent homology network (PHN) analysis and algebraic topology. We used 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) imaging data to construct dopaminergic and cholinergic metabolism networks, and used PHN analysis to track the evolution of these networks in patients with different stages of dementia. The sums of the network distances revealed significant differences between the network connectivity evident in the Alzheimer’s disease and mild cognitive impairment cohorts. A larger distance between brain regions can indicate poorer efficiency in the integration of information. PHN analysis revealed the structural properties of and changes in the dopaminergic and cholinergic metabolism networks in patients with different stages of dementia at a range of thresholds. This method was thus able to identify dysregulation of dopaminergic and cholinergic networks in the pathology of dementia.

scholarly journals Dissecting the midlife crisis: disentangling social, personality and demographic determinants in social brain anatomy

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Hannah Kiesow ◽  
Lucina Q. Uddin ◽  
Boris C. Bernhardt ◽  
Joseph Kable ◽  
Danilo Bzdok
Keyword(s):  
Brain Regions ◽  
Interindividual Variation ◽  
Brain Morphology ◽  
Brain Anatomy ◽  
Leadership Roles ◽  
Social Brain ◽  
Aging Parents ◽  
Health Satisfaction ◽  
Midlife Transitions ◽  
Fully Bayesian

AbstractIn any stage of life, humans crave connection with other people. In midlife, transitions in social networks can relate to new leadership roles at work or becoming a caregiver for aging parents. Previous neuroimaging studies have pinpointed the medial prefrontal cortex (mPFC) to undergo structural remodelling during midlife. Social behavior, personality predisposition, and demographic profile all have intimate links to the mPFC according in largely disconnected literatures. Here, we explicitly estimated their unique associations with brain structure using a fully Bayesian framework. We weighed against each other a rich collection of 40 UK Biobank traits with their interindividual variation in social brain morphology in ~10,000 middle-aged participants. Household size and daily routines showed several of the largest effects in explaining variation in social brain regions. We also revealed male-biased effects in the dorsal mPFC and amygdala for job income, and a female-biased effect in the ventral mPFC for health satisfaction.

scholarly journals Comparison of Activation in the Prefrontal Cortex of Native Speakers of Mandarin by Ability of Japanese as a Second Language Using a Novel Speaking Task

Healthcare ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 412
Author(s):  
Li Cong ◽  
Hideki Miyaguchi ◽  
Chinami Ishizuki
Keyword(s):  
Second Language ◽  
Prefrontal Cortex ◽  
Cognitive Load ◽  
Near Infrared ◽  
Native Speakers ◽  
Brain Activation ◽  
Brain Regions ◽  
Strong Inhibition ◽  
Functional Near Infrared Spectroscopy ◽  
High Level

Evidence shows that second language (L2) learning affects cognitive function. Here in this work, we compared brain activation in native speakers of Mandarin (L1) who speak Japanese (L2) between and within two groups (high and low L2 ability) to determine the effect of L2 ability in L1 and L2 speaking tasks, and to map brain regions involved in both tasks. The brain activation during task performance was determined using prefrontal cortex blood flow as a proxy, measured by functional near-infrared spectroscopy (fNIRS). People with low L2 ability showed much more brain activation when speaking L2 than when speaking L1. People with high L2 ability showed high-level brain activation when speaking either L2 or L1. Almost the same high-level brain activation was observed in both ability groups when speaking L2. The high level of activation in people with high L2 ability when speaking either L2 or L1 suggested strong inhibition of the non-spoken language. A wider area of brain activation in people with low compared with high L2 ability when speaking L2 is considered to be attributed to the cognitive load involved in code-switching L1 to L2 with strong inhibition of L1 and the cognitive load involved in using L2.

scholarly journals A Computational Network Control Theory Analysis of Depression Symptoms

2018 ◽  
Vol 1 ◽  
Author(s):  
Yoed N. Kenett ◽  
Roger E. Beaty ◽  
John D. Medaglia
Keyword(s):  
Control Theory ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Brain Network ◽  
Network Control ◽  
Depression Symptoms ◽  
Theory Approach ◽  
Imaging Data ◽  
The Brain ◽  
Subclinical Depression

AbstractRumination and impaired inhibition are considered core characteristics of depression. However, the neurocognitive mechanisms that contribute to these atypical cognitive processes remain unclear. To address this question, we apply a computational network control theory approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how network control theory relates to individual differences in subclinical depression. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that subclinical depression is negatively related to higher integration abilities in the right anterior insula, replicating and extending previous studies implicating atypical switching between the default mode and Executive Control Networks in depression. We also find that subclinical depression is related to the ability to “drive” the brain system into easy to reach neural states in several brain regions, including the bilateral lingual gyrus and lateral occipital gyrus. These findings highlight brain regions less known in their role in depression, and clarify their roles in driving the brain into different neural states related to depression symptoms.

Distinct Effects of D9-tetrahydrocannabinol and Cannabidiol on Neural Activation During Emotional Processing

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1 ◽  
Author(s):  
P. Fusar-Poli
Keyword(s):  
Emotional Processing ◽  
Electrodermal Activity ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Psychotic Symptoms ◽  
Neural Activation ◽  
Double Blind ◽  
Posterior Cingulate ◽  
Fearful Faces ◽  
Scanning Session

Aims:Cannabis use can both increase and reduce anxiety in humans. The neurophysiological substrates of these effects are unknown.Method:Fifteen healthy English-native right-handed men were studied on three separate occasions using an event-related fMRI paradigm while viewing faces that implicitly elicited different levels of anxiety. Each scanning session was preceded by the ingestion of either 10mg of D-9-THC, 600mg of CBD, or a placebo, in a double-blind, randomised, placebo controlled design. Electrodermal activity (Skin Conductance Response, SCR) and objective and subjective ratings of anxiety were recorded durign the scanning.Results:D-9THC increased anxiety, as well as levels of intoxication, sedation and psychotic symptoms, whereas there was a trend for a reduction in anxiety following administration of CBD. The number of SCR fluctuations during the processing of intensely fearful faces increased following administration of D-9THC but decreased following administration of CBD. CBD attenuated the BOLD signal in the amygdala and the anterior and posterior cingulate cortex while subjects were processing intensely fearful faces, and its suppression of the amygdalar and posterior cingulate responses was correlated with the concurrent reduction in SCR fluctuations. D-9-THC mainly modulated activation in frontal and parietal areas.Conclusions:D-9-THC and CBD had clearly distinct effects on the neural, eclectrodermal and symptomatic response to fearful faces. The effects of CBD on activation in limbic and paralimbic regions may contribute to its ability to reduce autonomic arousal and subjective anxiety, whereas the anxiogenic effects of D-9-THC may be related to effects in other brain regions.

Sign in / Sign up

Export Citation Format

Share Document