Clinical Applications of Resting State Functional Connectivity

During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI). The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI) and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm

Detection of brain functional-connectivity difference in post-stroke patients using group-level covariance modeling

Functional brain connectivity, as revealed through distant correlations in the signals measured by functional Magnetic Resonance Imaging (fMRI), is a promising source of biomarkers of brain pathologies. However, establishing and using diagnostic markers requires probabilistic inter-subject comparisons. Principled comparison of functional-connectivity structures is still a challenging issue. We give a new matrix-variate probabilistic model suitable for inter-subject comparison of functional connectivity matrices on the manifold of Symmetric Positive Definite (SPD) matrices. We show that this model leads to a new algorithm for principled comparison of connectivity coefficients between pairs of regions. We apply this model to comparing separately post-stroke patients to a group of healthy controls. We find neurologically-relevant connection differences and show that our model is more sensitive that the standard procedure. To the best of our knowledge, these results are the first report of functional connectivity differences between a single-patient and a group and thus establish an important step toward using functional connectivity as a diagnostic tool

Application of laser methods for identification of authenticity of documents fabricated from thermoplastic composite material

Processes of globalization and integration are pervasive all over the world, and rapid innovation of advanced transportation systems resulted in enormous increase in number of persons travelling cross-border. Normally, persons crossing the border are checked at the first control line. Therefore, application of innovative methods that allow identification of partial alterations in a document or a fully counterfeit document, for initial checking of documents remains a relevant issue. The holographic interferometry represents one of the non-destructive control methods applicable for document check that enables assessment of defects in the entire area of a document being checked. This paper presents validation of the real-time method of holographic interferometry used for document check as well as parameters of a holographic setup, description of document investigation and analysis of the obtained finding

Bootstrapped Permutation Test for Multiresponse Inference on Brain Behavior Associations

International audienceDespite that diagnosis of neurological disorders commonly involves a collection of behavioral assessments, most neuroimaging studies investigating the associations between brain and behavior largely analyze each behavioral measure in isolation. To jointly model multiple behavioral scores, sparse mul-tiresponse regression (SMR) is often used. However, directly applying SMR without statistically controlling for false positives could result in many spurious findings. For models, such as SMR, where the distribution of the model parameters is unknown, permutation test and stability selection are typically used to control for false positives. In this paper, we present another technique for inferring statistically significant features from models with unknown parameter distribution. We refer to this technique as bootstrapped permutation test (BPT), which uses Studentized statistics to exploit the intuition that the variability in parameter estimates associated with relevant features would likely be higher with responses permuted. On synthetic data, we show that BPT provides higher sensitivity in identifying relevant features from the SMR model than permutation test and stability selection, while retaining strong control on the false positive rate. We further apply BPT to study the associations between brain connec-tivity estimated from pseudo-rest fMRI data of 1139 fourteen year olds and be-havioral measures related to ADHD. Significant connections are found between brain networks known to be implicated in the behavioral tasks involved. Moreover , we validate the identified connections by fitting a regression model on pseudo-rest data with only those connections and applying this model on resting state fMRI data of 337 left out subjects to predict their behavioral scores. The predicted scores are shown to significantly correlate with the actual scores of the subjects, hence verifying the behavioral relevance of the found connections

Recent Consanguinity and Outbred Autozygosity Are Associated With Increased Risk of Late-Onset Alzheimer's Disease

Prior work in late-onset Alzheimer's disease (LOAD) has resulted in discrepant findings as to whether recent consanguinity and outbred autozygosity are associated with LOAD risk. In the current study, we tested the association between consanguinity and outbred autozygosity with LOAD in the largest such analysis to date, in which 20 LOAD GWAS datasets were retrieved through public databases. Our analyses were restricted to eight distinct ethnic groups: African-Caribbean, Ashkenazi-Jewish European, European-Caribbean, French-Canadian, Finnish European, North-Western European, South-Eastern European, and Yoruba African for a total of 21,492 unrelated subjects (11,196 LOAD and 10,296 controls). Recent consanguinity determination was performed using FSuite v1.0.3, according to subjects' ancestral background. The level of autozygosity in the outbred population was assessed by calculating inbreeding estimates based on the proportion (FROH) and the number (NROH) of runs of homozygosity (ROHs). We analyzed all eight ethnic groups using a fixed-effect meta-analysis, which showed a significant association of recent consanguinity with LOAD (N = 21,481; OR = 1.262, P = 3.6 × 10-4), independently of APOE∗4 (N = 21,468, OR = 1.237, P = 0.002), and years of education (N = 9,257; OR = 1.274, P = 0.020). Autozygosity in the outbred population was also associated with an increased risk of LOAD, both for FROH (N = 20,237; OR = 1.204, P = 0.030) and NROH metrics (N = 20,237; OR = 1.019, P = 0.006), independently of APOE∗4 [(FROH, N = 20,225; OR = 1.222, P = 0.029) (NROH, N = 20,225; OR = 1.019, P = 0.007)]. By leveraging the Alzheimer's Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data, we determined that LOAD subjects do not show an enrichment of rare, risk-enhancing minor homozygote variants compared to the control population. A two-stage recessive GWAS using ADSP data from 201 consanguineous subjects in the discovery phase followed by validation in 10,469 subjects led to the identification of RPH3AL p.A303V (rs117190076) as a rare minor homozygote variant increasing the risk of LOAD [discovery: Genotype Relative Risk (GRR) = 46, P = 2.16 × 10-6; validation: GRR = 1.9, P = 8.0 × 10-4]. These results confirm that recent consanguinity and autozygosity in the outbred population increase risk for LOAD. Subsequent work, with increased samples sizes of consanguineous subjects, should accelerate the discovery of non-additive genetic effects in LOAD

Substantial Doubt Remains about the Efficacy of Anti-Amyloid Antibodies

Alzheimer's disease (AD) is a prevalent, progressive, and ultimately fatal neurodegenerative disorder that is defined pathologically by the accumulation of amyloid plaques and tau neurofibrillary tangles in the brain. There remains an unmet need for therapies that can halt or slow the course of AD. To address this need, the FDA has provided a mechanism, under its Accelerated Approval pathway, for potential therapeutics to be approved based in part on their ability to reduce brain amyloid. Through this pathway, two monoclonal anti-amyloid antibodies, aducanumab and lecanemab, have been approved for clinical use. More recently, another amyloid-lowering antibody, donanemab, generated a statistically significant outcome in a phase 3 clinical trial and will shortly come under FDA review. While these monoclonal antibodies are not yet routinely used in clinical practice, the series of recent positive clinical trials has fostered enthusiasm amongst some AD experts. Here, we discuss three key limitations regarding recent anti-amyloid clinical trials: (1) there is little to no evidence that amyloid reduction correlates with clinical outcome, (2) the reported efficacy of anti-amyloid therapies may be partly, or wholly, explained by functional unblinding, and (3) donanemab in its phase 3 trial had no effect on tau burden, the pathological hallmark more closely related to cognition. Taken together, these observations call into question the efficacy of anti-amyloid therapies.Comment: 11 pages, 2 figures; Update 11/18/2023: Added subheadings to manuscript to improve readability, added a new data point to Figure 1A and Figure 2 for the recently published A4 clinical tria

Humor Modulates the Mesolimbic Reward Centers

AbstractHumor plays an essential role in many facets of human life including psychological, social, and somatic functioning. Recently, neuroimaging has been applied to this critical human attribute, shedding light on the affective, cognitive, and motor networks involved in humor processing. To date, however, researchers have failed to demonstrate the subcortical correlates of the most fundamental feature of humor—reward. In an effort to elucidate the neurobiological substrate that subserves the reward components of humor, we undertook a high-field (3 Tesla) event-related functional MRI study. Here we demonstrate that humor modulates activity in several cortical regions, and we present new evidence that humor engages a network of subcortical regions including the nucleus accumbens, a key component of the mesolimbic dopaminergic reward system. Further, the degree of humor intensity was positively correlated with BOLD signal intensity in these regions. Together, these findings offer new insight into the neural basis of salutary aspects of humor