BOLD Signal Research Articles

Synchronous functional magnetic resonance eye imaging, video ophthalmoscopy, and eye surface imaging reveal the human brain and eye pulsation mechanisms

The eye possesses a paravascular solute transport pathway that is driven by physiological pulsations, resembling the brain glymphatic pathway. We developed synchronous multimodal imaging tools aimed at measuring the driving pulsations of the human eye, using an eye-tracking functional eye camera (FEC) compatible with magnetic resonance imaging (MRI) for measuring eye surface pulsations. Special optics enabled integration of the FEC with MRI-compatible video ophthalmoscopy (MRcVO) for simultaneous retinal imaging along with functional eye MRI imaging (fMREye) of the BOLD (blood oxygen level dependent) contrast. Upon optimizing the fMREye parameters, we measured the power of the physiological (vasomotor, respiratory, and cardiac) eye and brain pulsations by fast Fourier transform (FFT) power analysis. The human eye pulsated in all three physiological pulse bands, most prominently in the respiratory band. The FFT power means of physiological pulsation for two adjacent slices was significantly higher than in one-slice scans (RESP1 vs. RESP2; df = 5, p = 0.045). FEC and MRcVO confirmed the respiratory pulsations at the eye surface and retina. We conclude that in addition to the known cardiovascular pulsation, the human eye also has respiratory and vasomotor pulsation mechanisms, which are now amenable to study using non-invasive multimodal imaging of eye fluidics.

The missing third dimension-Functional correlations of BOLD signals incorporating white matter.

Correlations between magnetic resonance imaging (MRI) blood oxygenation level-dependent (BOLD) signals from pairs of gray matter areas are used to infer their functional connectivity, but they are unable to describe how white matter is engaged in brain networks. Recently, evidence that BOLD signals in white matter are robustly detectable and are modulated by neural activities has accumulated. We introduce a three-way correlation between BOLD signals from pairs of gray matter volumes (nodes) and white matter bundles (edges) to define the communication connectivity through each white matter bundle. Using MRI images from publicly available databases, we show, for example, that the three-way connectivity is influenced by age. By integrating functional MRI signals from white matter as a third component in network analyses, more comprehensive descriptions of brain function may be obtained.

Simultaneous fMRI and metabolic MRS of hyperpolarized [1-13C]pyruvate during nicotine stimulus in rat.

Functional MRI (fMRI) and MRS (fMRS) can be used to noninvasively map cerebral activation and metabolism. Recently, hyperpolarized 13C spectroscopy and metabolic imaging have provided an alternative approach to assess metabolism. In this study, we combined 1H fMRI and hyperpolarized [1-13C]pyruvate MRS to compare cerebral blood oxygenation level-dependent (BOLD) response and real-time cerebral metabolism, as assessed with lactate and bicarbonate labelling, during nicotine stimulation. Simultaneous 1H fMRI (multislice gradient echo echo-planar imaging) and 13C spectroscopic (single slice pulse-acquire) data were collected in urethane-anaesthetized female Sprague-Dawley rats (n= 12) at 9.4 T. Animals received an intravenous (i.v.) injection of either nicotine (stimulus; 88 μg/kg, n= 7, or 300 μg/kg, n= 5) or 0.9% saline (matching volume), followed by hyperpolarized [1-13C]pyruvate injection 60 s later. Three hours later, a second injection was administered: the animals that had previously received saline were injected with nicotine and vice versa, both followed by another hyperpolarized [1-13C]pyruvate i.v. injection 60 s later. The low-dose (88 μg/kg) nicotine injection led to a 12% ± 4% (n= 7, t-test, p~ 0.0006 (t-value -5.8, degrees of freedom 6), Wilcoxon p~ 0.0078 (test statistic 0)) increase in BOLD signal. At the same time, an increase in 13C-bicarbonate signal was seen in four out of six animals. Bicarbonate-to-total carbon ratios were 0.010 ± 0.004 and 0.018 ± 0.010 (n= 6, t-test, p~ 0.03 (t-value -2.3, degrees of freedom 5), Wilcoxon p~ 0.08 (test statistic 3)) for saline and nicotine experiments, respectively. No increase in the lactate signal was seen; lactate-to-total carbon was 0.16 ± 0.02 after both injections. The high (300 μg/kg) nicotine dose (n= 5) caused highly variable BOLD and metabolic responses, possibly due to the apparent respiratory distress. Simultaneous detection of 1H fMRI and hyperpolarized 13C-MRS is feasible. A comparison of metabolic response between control and stimulated states showed differences in bicarbonate signal, implying that the hyperpolarization technique could offer complimentary information on brain activation.

Atopic dermatitis and stress: A functional magnetic resonance imaging study of female patients with atopic dermatitis using an arithmetic task

AbstractBackgroundAtopic dermatitis (AD) is a chronic inflammatory skin disorder characterized by eczematous lesions, dry skin and persistent itch. AD may worsen due to psychological stress. However, little is known about the neural correlates that mediate the interaction between psychological stress and AD.ObjectivesTo identify the possible difference in brain activation during arithmetic‐task induced stress in patients with AD versus healthy controls (HC) as well as the link between the brain response and clinical and psychodemographic parameters.MethodsA cohort of 29 AD female patients and 23 matched HC were recruited to investigate the potential difference in functional magnetic resonance imaging (fMRI) response to a block‐designed arithmetic paradigm. Both the HC and AD subjects were evaluated regarding their psychological traits, and for the AD subjects also their clinical characteristics, including stress indicators such as heart rate and salivary cortisol. We employed both univariate and multivariate statistical methods to analyse the blood oxygen level dependent (BOLD) fMRI response of the subjects to the block‐designed arithmetic paradigm.Results(1) Compared with HC subjects, the AD patients depict less deactivation in the default mode network including right angular gyrus, bilateral temporal pole and temporal lobe in response to the arithmetic task. (2) The BOLD fMRI response amplitude in the right postcentral gyrus and inferior parietal lobule is positively correlated with the stress susceptibility scores in the AD subjects, whereas the trend was the opposite of this for the HC subjects. (3) The activation in the postcentral gyrus also shows a correlation with the degree of itch in the AD patients.ConclusionsThe BOLD fMRI measurements based on an arithmetic paradigm can provide useful insight into altered brain processing and its association with psychological traits and clinical characteristics in subjects with AD. Psychological stress exacerbates brain activities for the AD subjects in the motor, somatosensory association cortex, perception and sensory integration processing. The postcentral gyrus might be of particular interest for itch and stress.

Semantic transparency modulates the semantic perception of morphemes: Evidence from RSA of BOLD signals

There is no converging evidence on how a word’s semantic transparency affects morphemes’ potential semantic activation. The inconsistent results may be due to the limitation of traditional univariate analyses, in which the semantic transparency was treated as discrete categories. In the current study, Chinese two-character words were used as stimuli and functional magnetic resonance imaging (fMRI) techniques were combined with a priming paradigm. Unlike most previous studies, the multivariate representation similarity analysis (RSA) was used to treat semantic transparency as a continuous variable. The RSA results showed that widespread regions in the frontal-parietal-temporal network represent the semantic perception of characters in all words and transparent words, but no brain areas were identified in opaque words. Unlike RSA results, univariate analyses showed no significant difference between the opaque and transparent words. These results suggest that RSA is more suitable to examine the neural mechanism related to continuous variables such as semantic transparency.

Exploring Physiological Differences in Brain Areas Using Statistical Complexity Analysis of BOLD Signals.

The brain is a fundamental organ for the human body to function properly, for which it needs to receive a continuous flow of blood, which explains the existence of control mechanisms that act to maintain this flow as constant as possible in a process known as cerebral autoregulation. One way to obtain information on how the levels of oxygen supplied to the brain vary is through of BOLD (Magnetic Resonance) images, which have the advantage of greater spatial resolution than other forms of measurement, such as transcranial Doppler. However, they do not provide good temporal resolution nor allow for continuous prolonged examination. Thus, it is of great importance to find a method to detect regional differences from short BOLD signals. One of the existing alternatives is complexity measures that can detect changes in the variability and temporal organisation of a signal that could reflect different physiological states. The so-called statistical complexity, created to overcome the shortcomings of entropy alone to explain the concept of complexity, has shown potential with haemodynamic signals. The aim of this study is to determine by using statistical complexity whether it is possible to find differences between physiologically distinct brain areas in healthy individuals. The data set includes BOLD images of 10 people obtained at the University Hospital of Leicester NHS Trust with a 1.5 Tesla magnetic resonance imaging scanner. The data were captured for 180 s at a frequency of 1 Hz. Using various combinations of statistical complexities, no differences were found between hemispheres. However, differences were detected between grey matter and white matter, indicating that these measurements are sensitive to differences in brain tissues.

Non-Contrast-Enhanced Multiparametric MRI of the Hypoxic Tumor Microenvironment Allows Molecular Subtyping of Breast Cancer: A Pilot Study.

Tumor neoangiogenesis is an important hallmark of cancer progression, triggered by alternating selective pressures from the hypoxic tumor microenvironment. Non-invasive, non-contrast-enhanced multiparametric MRI combining blood-oxygen-level-dependent (BOLD) MRI, which depicts blood oxygen saturation, and intravoxel-incoherent-motion (IVIM) MRI, which captures intravascular and extravascular diffusion, can provide insights into tumor oxygenation and neovascularization simultaneously. Our objective was to identify imaging markers that can predict hypoxia-induced angiogenesis and to validate our findings using multiplexed immunohistochemical analyses. We present an in vivo study involving 36 female athymic nude mice inoculated with luminal A, Her2+, and triple-negative breast cancer cells. We used a high-field 9.4-tesla MRI system for imaging and subsequently analyzed the tumors using multiplex immunohistochemistry for CD-31, PDGFR-β, and Hif1-α. We found that the hyperoxic-BOLD-MRI-derived parameter ΔR2* discriminated luminal A from Her2+ and triple-negative breast cancers, while the IVIM-derived parameter fIVIM discriminated luminal A and Her2+ from triple-negative breast cancers. A comprehensive analysis using principal-component analysis of both multiparametric MRI- and mpIHC-derived data highlighted the differences between triple-negative and luminal A breast cancers. We conclude that multiparametric MRI combining hyperoxic BOLD MRI and IVIM MRI, without the need for contrast agents, offers promising non-invasive markers for evaluating hypoxia-induced angiogenesis.

Functional brain networks involved in the Raven's standard progressive matrices task and their relation to theories of fluid intelligence

A dimensionality reduction method was used to determine the task-timing-related functional brain networks underlying the Raven's Standard Progressive Matrices (RSPM), a non-verbal estimate of fluid intelligence (Gf). We identified five macro-scale task-based blood‑oxygen-level-dependent (BOLD)-signal brain networks and interpreted their network-level task-induced BOLD changes to provide functional interpretations separately for each network. This led to new observations about the brain networks underlying the RSPM: (1) the multiple demand network (MDN) for solution searching peaked early in the trial (∼9 s peak), followed by response (RESP) for response selection (∼12 s), and re-evaluation (RE-EV) for solution checking (∼18 s peak), (2) high activity in the MDN was correlated with high activity in the later-peaking RE-EV network, proposed to underpin cooperative solution searching (MDN) and checking (RE-EV) processes, and (3) high activity in the MDN in all conditions was associated with low accuracy in the hard RSPM condition, suggesting that those with lower performance on hard problems allocate more resources into solution-searching across all conditions. These findings corroborate the MDN's significance in Gf solution searching, and add the RE-EV network as playing an important checking role, providing overlap with the proposed abstraction/elaboration and hypothesis testing phases of the Parieto-Frontal Integration Theory (P-FIT). Therefore, this set of results not only supports past theoretical work on the brain networks underlying Gf and the RSPM task, but extends it by providing more complete anatomical, temporal, and functional information based on a set of brain task-based networks which replicate over many tasks.

Controlled noninvasive modulation of deep brain regions in humans

Transcranial focused ultrasound provides noninvasive and reversible approaches for precise and personalized manipulations of brain circuits, with the potential to transform our understanding of brain function and treatments of brain dysfunction. However, effective applications in humans have been limited by the human head, which attenuates and distorts ultrasound severely and unpredictably. This has led to uncertain ultrasound intensities delivered into the brain. Here, we address this lingering barrier using a direct measurement approach that can be repeatedly applied to the human brain. The approach uses an ultrasonic scan of the head to measure and compensate for the attenuation of the ultrasound by all obstacles within the ultrasound path. No other imaging modality is required and the method is parameter-free and personalized to each subject. The approach accurately restores operators’ intended intensities inside ex-vivo human skulls. Moreover, the approach is critical for effective modulation of deep brain regions in humans. When applied, the approach modulates fMRI Blood Oxygen Level Dependent (BOLD) activity in disease-relevant deep brain regions. This tool unlocks the potential of emerging approaches based on low-intensity ultrasound for controlled manipulations of neural circuits in humans.

Value of blood oxygenation level-dependent magnetic resonance imaging in early evaluation of the response and prognosis of esophageal squamous cell carcinoma treated with definitive chemoradiotherapy: a preliminary study

BackgroundTo find a useful hypoxia non-invasive biomarker for evaluating early treatment response and prognosis to definitive chemoradiotherapy (dCRT) in patients with esophageal squamous cell carcinoma (ESCC), using blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI).MethodsThe R2* values were obtained pre- and 2–3 weeks post-dCRT in 28 patients with ESCC using BOLD MRI. Independent samples t-test (normality) or Mann-Whitney U test (non-normality) was used to compare the differences of R2*-related parameters between the complete response (CR) and the non-CR groups. Diagnostic performance of parameters in predicting response was tested with receiver operating characteristic (ROC) curve analysis. The 3-year overall survival (OS) was evaluated using Kaplan Meier curve, log rank test, and Cox proportional hazards regression analysis.ResultsThe post-R2*, ∆R2*, and ∆%R2* in the CR group were significantly higher than those in the non-CR group (P = 0.002, 0.003, and 0.006, respectively). The R2*-related parameters showed good prediction of tumor response, with AUC ranging from 0.813 to 0.829. The 3-year OS rate in patients with ∆R2* >-7.54 s− 1 or CR were significantly longer than those with ∆R2* ≤ -7.54 s− 1 (72.37% vs. 0.00%; Hazard ratio, HR = 0.196; 95% confidence interval, 95% CI = 0.047–0.807; P = 0.024) or non-CR (76.47% vs. 29.27%; HR = 0.238, 95% CI = 0.059–0.963; P = 0.044).ConclusionsThe preliminary results demonstrated that the R2* value might be a useful hypoxia non-invasive biomarker for assessing response and prognosis of ESCC treated with dCRT. BOLD MRI might be used as a potential tool for evaluating tumor oxygenation metabolism, which is routinely applied in clinical practice and beneficial to clinical decision-making. A large sample size was needed for further follow-up studies to confirm the findings.

BOLD cardiorespiratory pulsatility in the brain: from noise to signal of interest.

Functional magnetic resonance imaging (fMRI) based on the Blood Oxygen Level Dependent (BOLD) contrast has been extensively used to map brain activity and connectivity in health and disease. Standard fMRI preprocessing includes different steps to remove confounds unrelated to neuronal activity. First, this narrative review explores how signal fluctuations due to cardiac and respiratory activity, usually considered as "physiological noise" and regressed out from fMRI time series. However, these signal components bear useful information about some mechanisms of brain functioning (e.g., glymphatic clearance) or cerebrovascular compliance in response to arterial pressure waves. Aging and chronic diseases can cause stiffening of the aorta and other main arteries, with a reduced dampening effect resulting in greater transmission of pressure impulses to the brain. Importantly, the continuous hammering of cardiac pulsations can produce local alterations of the mechanical properties of the small cerebral vessels, with a progressive deterioration that ultimately affects neuronal functionality. Second, the review emphasizes how fMRI can study the brain patterns most affected by cardiac pulsations in health and disease with high spatiotemporal resolution, offering the opportunity to identify much more specific risk markers than systemic factors based on measurements of the vascular compliance of large arteries or other global risk factors. In this regard, modern fast fMRI acquisition techniques allow a better characterization of these pulsatile signal components due to reduced aliasing effects, turning what has been traditionally considered as noise in a signal of interest that can be used to develop novel non-invasive biomarkers in different clinical contexts.

GABAergic inhibition shapes behavior and neural dynamics in human visual working memory.

Neuronal inhibition, primarily mediated by GABAergic neurotransmission, is crucial for brain development and healthy cognition. Gamma-aminobutyric acid concentration levels in sensory areas have been shown to correlate with hemodynamic and oscillatory neuronal responses. How these measures relate to one another during working memory, a higher-order cognitive process, is still poorly understood. We address this gap by collecting magnetoencephalography, functional magnetic resonance imaging, and Flumazenil positron emission tomography data within the same subject cohort using an n-back working-memory paradigm. By probing the relationship between GABAA receptor distribution, neural oscillations, and Blood Oxygen Level Dependent (BOLD) modulations, we found that GABAA receptor density in higher-order cortical areas predicted the reaction times on the working-memory task and correlated positively with the peak frequency of gamma power modulations and negatively with BOLD amplitude. These findings support and extend theories linking gamma oscillations and hemodynamic responses to gamma-aminobutyric acid neurotransmission and to the excitation-inhibition balance and cognitive performance in humans. Considering the small sample size of the study, future studies should test whether these findings also hold for other, larger cohorts as well as to examine in detail how the GABAergic system and neural fluctuations jointly support working-memory task performance.

Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA.

Motor-task functional magnetic resonance imaging (fMRI) is crucial in the study of several clinical conditions, including stroke and Parkinson's disease. However, motor-task fMRI is complicated by task-correlated head motion, which can be magnified in clinical populations and confounds motor activation results. One method that may mitigate this issue is multi-echo independent component analysis (ME-ICA), which has been shown to separate the effects of head motion from the desired blood oxygenation level dependent (BOLD) signal but has not been tested in motor-task datasets with high amounts of motion. In this study, we collected an fMRI dataset from a healthy population who performed a hand grasp task with and without task-correlated amplified head motion to simulate a motor-impaired population. We analyzed these data using three models: single-echo (SE), multi-echo optimally combined (ME-OC), and ME-ICA. We compared the models' performance in mitigating the effects of head motion on the subject level and group level. On the subject level, ME-ICA better dissociated the effects of head motion from the BOLD signal and reduced noise. Both ME models led to increased t-statistics in brain motor regions. In scans with high levels of motion, ME-ICA additionally mitigated artifacts and increased stability of beta coefficient estimates, compared to SE. On the group level, all three models produced activation clusters in expected motor areas in scans with both low and high motion, indicating that group-level averaging may also sufficiently resolve motion artifacts that vary by subject. These findings demonstrate that ME-ICA is a useful tool for subject-level analysis of motor-task data with high levels of task-correlated head motion. The improvements afforded by ME-ICA are critical to improve reliability of subject-level activation maps for clinical populations in which group-level analysis may not be feasible or appropriate, for example, in a chronic stroke cohort with varying stroke location and degree of tissue damage.

The value of functional magnetic resonance imaging in evaluating renal allograft function

BackgroundTo explore the value of arterial spin labeled (ASL) and blood oxygen level dependent (BOLD) imaging in evaluating allogeneic kidney function after renal transplantation. MethodsOne hundred and thirty-five renal transplant patients were included. Demographic and imaging data were collected. Transplanted renal function, pathology, ASL and BOLD parameters were obtained. The patients were divided into normal, mild and severe injury group. The correlation between BOLD/ASL parameters and clinical data were evaluated. The prediction models were based on ASL and BOLD parameters using multivariate logistic analysis. Cox proportional hazards regression model was used to analyze the effects of gender, age, ASL and BOLD on the survival of renal transplant patients. ResultsASL and BOLD parameters were independently associated with renal function injury and renal allograft positive pathology. The AUC of prediction model for renal allograft function based on ASL and BOLD parameters was 0.85, while the AUC based on BOLD parameters was 0.70. Renal transplantation time showed a positive correlation with age, BOLD parameters and SCr，while a negative correlation with ASL parameters and eGFR. ASL parameter was positively correlated with eGFR and negatively correlated with Scr. BOLD parameter was negatively correlated with eGFR, ASL and positively correlated with Scr. Cox proportional hazards regression model showed that the increase of age could reduce the risk of renal function injury and positive pathology. ConclusionsASL and BOLD were associated with renal function injury and renal allograft positive pathology. ASL and BOLD had some value in predicting renal allograft function.

Patterns of cortical oxygenation may predict the response to stenting in subjects with renal artery stenosis: A radiomics-based model

BackgroundPercutaneous-transluminal renal angioplasty (PTRA) and stenting aim to halt the progression of kidney disease in patients with renal artery stenosis (RAS), but its outcome is often suboptimal. We hypothesized that a model incorporating markers of renal function and oxygenation extracted using radiomics analysis of blood oxygenation-level dependent (BOLD)-MRI images may predict renal response to PTRA in swine RAS. Materials and MethodsTwenty domestic pigs with RAS were scanned with CT and BOLD MRI before and 4 weeks after PTRA. Stenotic (STK) and contralateral (CLK) kidney volume, blood flow (RBF), and glomerular filtration rate (GFR) were determined, and BOLD-MRI R2 * maps were generated before and after administration of furosemide, a tubular reabsorption inhibitor. Radiomics features were extracted from pre-PTRA BOLD maps and Robust features were determined by Intraclass correlation coefficients (ICC). Prognostic models were developed to predict post-PTRA renal function based on the baseline functional and BOLD-radiomics features, using Lasso-regression for training, and testing with resampling. ResultsTwenty-six radiomics features passed the robustness test. STK oxygenation distribution pattern did not respond to furosemide, whereas in the CLK radiomics features sensitive to oxygenation heterogeneity declined. Radiomics-based model predictions of post-PTRA GFR (r = 0.58, p = 0.007) and RBF (r = 0.68; p = 0.001) correlated with actual measurements with sensitivity and specificity of 92% and 67%, respectively. Models were unsuccessful in predicting post-PTRA systemic measures of renal function. ConclusionsSeveral radiomics features are sensitive to cortical oxygenation patterns and permit estimation of post-PTRA renal function, thereby distinguishing subjects likely to respond to PTRA and stenting.

Pathological Factors Affecting the R2* Values of the Kidney in Blood Oxygenation Level-dependent MR Imaging: A Retrospective Study.

Despite the usefulness of blood oxygenation level-dependent (BOLD) MRI in assessing glomerulonephritis activity, its relationship with histological findings remains unclear. Because glomerulonephritis presents multiple complex injury patterns, analysis of each pattern is essential. We aimed to elucidate the relationship between the histological findings of the kidney and BOLD MRI findings in mesangial proliferative glomerulonephritis. Children under 16 years of age diagnosed with mesangial proliferative glomerulonephritis by kidney biopsy at our university hospital between January 2013 and September 2022 were included in this study. Cortical and medullary spin relaxation rate (R2*) values were measured using BOLD MRI at 3T within two weeks before and after the kidney biopsy. The R2* values, including the fluctuations with low-dose oxygen administration, were retrospectively examined in relation to the cortical (mesangial proliferation, endothelial cell proliferation, crescent, sclerosis, and fibrosis) and medullary findings (fibrosis). Sixteen times kidney biopsies were performed for glomerulonephritis during the study period, and one patient was excluded because of comorbidities; the remaining 14 patients included six boys with a mean age of 11.9 ± 3.5 years at the BOLD examination. None of the patients had medullary fibrosis. Among the kidney tissue parameters, only sclerosis showed a significant correlation with R2* values: medulla with R2* values under atmospheric pressure (r = 0.53, P < 0.05) and cortex with the rate of change in R2* values with low-dose oxygen administration (r = -0.57, P < 0.03). In the multiple regression analysis, only sclerosis was an independent contributor to the change in R2* values with oxygen administration in the cortex (regression coefficient -0.109, P < 0.05). Since the R2* values reflect histological changes in the kidney, BOLD MRI may facilitate the evaluation of mesangial proliferative glomerulonephritis, potentially reducing the patient burden.

Local variation in brain temperature explains gender-specificity of working memory performance.

Exploring gender differences in cognitive abilities offers vital insights into human brain functioning. Our study utilized advanced techniques like magnetic resonance thermometry, standard working memory n-back tasks, and functional MRI to investigate if gender-based variations in brain temperature correlate with distinct neuronal responses and working memory capabilities. We observed a significant decrease in average brain temperature in males during working memory tasks, a phenomenon not seen in females. Although changes in female brain temperature were significantly lower than in males, we found an inverse relationship between the absolute temperature change (ATC) and cognitive performance, alongside a correlation with blood oxygen level dependent (BOLD) signal change induced by neural activity. This suggests that in females, ATC is a crucial determinant for the link between cognitive performance and BOLD responses, a linkage not evident in males. However, we also observed additional female specific BOLD responses aligned with comparable task performance to that of males. Our results suggest that females compensate for their brain's heightened temperature sensitivity by activating additional neuronal networks to support working memory. This study not only underscores the complexity of gender differences in cognitive processing but also opens new avenues for understanding how temperature fluctuations influence brain functionality.

Deep Learning and fMRI-Based Pipeline for Optimization of Deep Brain Stimulation During Parkinson's Disease Treatment: Toward Rapid Semi-Automated Stimulation Optimization.

Optimized deep brain stimulation (DBS) is fast becoming a therapy of choice for the treatment of Parkinson's disease (PD). However, the post-operative optimization (aimed at maximizing patient clinical benefits and minimizing adverse effects) of all possible DBS parameter settings using the standard-of-care clinical protocol requires numerous clinical visits, which substantially increases the time to optimization per patient (TPP), patient cost burden and limit the number of patients who can undergo DBS treatment. The TPP is further elongated in electrodes with stimulation directionality or in diseases with latency in clinical feedback. In this work, we proposed a deep learning and fMRI-based pipeline for DBS optimization that can potentially reduce the TPP from ~1 year to a few hours during a single clinical visit. We developed an unsupervised autoencoder (AE)-based model to extract meaningful features from 122 previously acquired blood oxygenated level dependent (BOLD) fMRI datasets from 39 a priori clinically optimized PD patients undergoing DBS therapy. The extracted features are then fed into multilayer perceptron (MLP)-based parameter classification and prediction models for rapid DBS parameter optimization. The AE-extracted features of optimal and non-optimal DBS were disentangled. The AE-MLP classification model yielded accuracy, precision, recall, F1 score, and combined AUC of 0.96 ± 0.04, 0.95 ± 0.07, 0.92 ± 0.07, 0.93 ± 0.06, and 0.98 respectively. Accuracies of 0.79 ± 0.04, 0.85 ± 0.04, 0.82 ± 0.05, 0.83 ± 0.05, and 0.70 ± 0.07 were obtained in the prediction of voltage, frequency, and x-y-z contact locations, respectively. The proposed AE-MLP models yielded promising results for fMRI-based DBS parameter classification and prediction, potentially facilitating rapid semi-automated DBS parameter optimization. Clinical and Translational Impact Statement-A deep learning-based pipeline for semi-automated DBS parameter optimization is presented, with the potential to significantly decrease the optimization duration per patient and patients' financial burden while increasing patient throughput.

Neurochemistry and functional connectivity in the brain of people with Charles Bonnet syndrome.

Charles Bonnet syndrome (CBS) is a condition in which people with vision loss experience complex visual hallucinations. These complex visual hallucinations may be caused by increased excitability in the visual cortex that are present in some people with vision loss but not others. We aimed to evaluate the association between γ-aminobutyric acid (GABA) in the visual cortex and CBS. We also tested the relationship among visually evoked responses, functional connectivity, and CBS. This is a prospective, case-controlled, cross-sectional observational study. We applied 3-Tesla magnetic resonance spectroscopy, as well as task-based and resting state (RS) connectivity functional magnetic resonance imaging in six participants with CBS and six controls without CBS. GABA+ was measured in the early visual cortex (EVC) and in the lateral occipital cortex (LOC). Participants also completed visual acuity and cognitive tests, and the North-East Visual Hallucinations Interview. The two groups were well-matched for age, gender, visual acuity and cognitive scores. There was no difference in GABA+ levels between groups in the visual cortex. Most participants showed the expected blood oxygenation level dependent (BOLD) activation to images of objects and the phase-scrambled control. Using a fixed effects analysis, we found that BOLD activation was greater in participants with CBS compared to controls. Analysis of RS connectivity with LOC and EVC showed little difference between groups. A fixed effects analysis showed a correlation between the extent of functional connectivity with LOC and hallucination strength. Overall, our results provide no strong evidence for an association between GABAergic inhibition in the visual cortex and CBS. We only found subtle differences in visual function and connectivity between groups. These findings suggest that the neurochemistry and visual connectivity for people with Charles Bonnet hallucinations are comparable to a sight loss population. Differences between groups may emerge when investigating subtle and transient changes that occur at the time of visual hallucinations.

Recent Advances in MR Imaging-based Quantification of Brain Oxygen Metabolism.

The metabolic rate of oxygen (MRO2) is fundamental to tissue metabolism. Determination of MRO2 demands knowledge of the arterio-venous difference in hemoglobin-bound oxygen concentration, typically expressed as oxygen extraction fraction (OEF), and blood flow rate (BFR). MRI is uniquely suited for measurement of both these quantities, yielding MRO2 in absolute physiologic units of µmol O2 min-1/100 g tissue. Two approaches are discussed, both relying on hemoglobin magnetism. Emphasis will be on cerebral oxygen metabolism expressed in terms of the cerebral MRO2 (CMRO2), but translation of the relevant technologies to other organs, including kidney and placenta will be touched upon as well. The first class of methods exploits the blood's bulk magnetic susceptibility, which can be derived from field maps. The second is based on measurement of blood water T2, which is modulated by diffusion and exchange in the local-induced fields within and surrounding erythrocytes. Some whole-organ methods achieve temporal resolution adequate to permit time-series studies of brain energetics, for instance, during sleep in the scanner with concurrent electroencephalogram (EEG) sleep stage monitoring. Conversely, trading temporal for spatial resolution has led to techniques for spatially resolved approaches based on quantitative blood oxygen level dependent (BOLD) or calibrated BOLD models, allowing regional assessment of vascular-metabolic parameters, both also exploiting deoxyhemoglobin paramagnetism like their whole-organ counterparts.