Toward precision brain health: accurate prediction of a cognitive index trajectory using neuroimaging metrics.

The goal of precision brain health is to accurately predict individuals' longitudinal patterns of brain change. We trained a machine learning model to predict changes in a cognitive index of brain health from neurophysiologic metrics. A total of 48 participants (ages 21-65) completed a sensorimotor task during 2 functional magnetic resonance imaging sessions 6 mo apart. Hemodynamic response functions (HRFs) were parameterized using traditional (amplitude, dispersion, latency) and novel (curvature, canonicality) metrics, serving as inputs to a neural network model that predicted gain on indices of brain health (cognitive factor scores) for each participant. The optimal neural network model successfully predicted substantial gain on the cognitive index of brain health with 90% accuracy (determined by 5-fold cross-validation) from 3 HRF parameters: amplitude change, dispersion change, and similarity to a canonical HRF shape at baseline. For individuals with canonical baseline HRFs, substantial gain in the index is overwhelmingly predicted by decreases in HRF amplitude. For individuals with non-canonical baseline HRFs, substantial gain in the index is predicted by congruent changes in both HRF amplitude and dispersion. Our results illustrate that neuroimaging measures can track cognitive indices in healthy states, and that machine learning approaches using novel metrics take important steps toward precision brain health.

Altered linear coupling between stimulus-evoked blood flow and oxygen metabolism in the aging human brain.

Neural-vascular coupling (NVC) is the process by which oxygen and nutrients are delivered to metabolically active neurons by blood vessels. Murine models of NVC disruption have revealed its critical role in healthy neural function. We hypothesized that, in humans, aging exerts detrimental effects upon the integrity of the neural-glial-vascular system that underlies NVC. To test this hypothesis, calibrated functional magnetic resonance imaging (cfMRI) was used to characterize age-related changes in cerebral blood flow (CBF) and oxygen metabolism during visual cortex stimulation. Thirty-three younger and 27 older participants underwent cfMRI scanning during both an attention-controlled visual stimulation task and a hypercapnia paradigm used to calibrate the blood-oxygen-level-dependent signal. Measurement of stimulus-evoked blood flow and oxygen metabolism permitted calculation of the NVC ratio to assess the integrity of neural-vascular communication. Consistent with our hypothesis, we observed monotonic NVC ratio increases with increasing visual stimulation frequency in younger adults but not in older adults. Age-related changes in stimulus-evoked cerebrovascular and neurometabolic signal could not fully explain this disruption; increases in stimulus-evoked neurometabolic activity elicited corresponding increases in stimulus-evoked CBF in younger but not in older adults. These results implicate age-related, demand-dependent failures of the neural-glial-vascular structures that comprise the NVC system.

The neurovascular basis of processing speed differences in humans: A model-systems approach using multiple sclerosis.

Behavioral studies investigating fundamental cognitive abilities provide evidence that processing speed accounts for large proportions of performance variability between individuals. Processing speed decline is a hallmark feature of the cognitive disruption observed in healthy aging and in demyelinating diseases such as multiple sclerosis (MS), neuromyelitis optica, and Wilson's disease. Despite the wealth of evidence suggesting a central role for processing speed in cognitive decline, the neural mechanisms of this fundamental ability remain unknown. Intact neurovascular coupling, acute localized blood flow increases following neural activity, is essential for optimal neural function. We hypothesized that efficient coupling forms the neural basis of processing speed. Because MS features neural-glial-vascular system disruption, we used it as a model to test this hypothesis. To assess the integrity of the coupling system, we measured blood-oxygen-level-dependent (BOLD) signal in healthy controls (HCs) and MS patients using a 3T MRI scanner while they viewed radial checkerboards that flickered periodically at 8 â€‹Hz. To assess processing speed and cognitive function, we administered a battery of neuropsychological tests. While MS patients exhibited reduced ΔBOLD with reductions in processing speed, no such relationships were observed in HCs. To further investigate the mechanisms that underlie ΔBOLD-processing speed relationships, we assessed the physiologic components that constitute ΔBOLD signal (i.e., cerebral blood flow, ΔCBF; cerebral metabolic rate of oxygen, ΔCMRO2; neurovascular coupling ratio) in speed-preserved and -impaired MS patients. While ΔCBF and ΔCMRO2 showed no group-differences, the neurovascular coupling ratio was significantly reduced in speed-impaired MS patients compared to speed-preserved MS patients. Together, these results suggest that neurovascular uncoupling might underlie cognitive slowing in MS and might be the central pathogenic mechanism governing processing speed decline.

Neurophysiology of threat processing bias in combat-related post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) is a debilitating condition that may develop after experiencing a traumatic event. Combat exposure increases an individual's chance of developing PTSD, making veterans especially susceptible to the disorder. PTSD is characterized by dysregulated emotional networks, memory deficits, and a hyperattentive response to perceived threatening stimuli. Recently, there have been a number of imaging studies that show structural and functional abnormalities associated with PTSD; however, there have been few studies utilizing electroencephalography (EEG). The goal of this study was to characterize **EEG brain dynamics in individuals with PTSD, in order to better understand the neurophysiological underpinnings of some of the salient features of PTSD, such as threat-processing bias. Veterans of Operation Enduring Freedom/Iraqi Freedom completed an implicit visual threat semantic memory recognition task with stimuli that varied on both category (animals, items, nature, and people) and feature (threatening and nonthreatening) membership, including trauma-related stimuli. Combat veterans with PTSD had slower reaction times for the threatening stimuli relative to the combat veterans without PTSD (VETC). There were trauma-specific effects in frontal regions, with theta band EEG power reductions for the threatening combat scenes in the PTSD patients compared to the VETC group. Additionally, a moderate negative correlation was observed between trauma-specific frontal theta power and hyperarousal symptoms as measured by clinically administered PTSD scale. These findings complement and extend current models of cortico-limbic dysfunction in PTSD. The moderate negative correlation between frontal theta power and hyperarousal endorsements suggests the utility of these measures as therapeutic markers of symptomatology in PTSD patients.

Reduced arterial compliance along the cerebrovascular tree predicts cognitive slowing in multiple sclerosis: Evidence for a neurovascular uncoupling hypothesis.

BACKGROUND: Cognitive slowing occurs in ~70% of multiple sclerosis (MS) patients. The pathophysiology of this slowing is unknown. Neurovascular coupling, acute localized blood flow increases following neural activity, is essential for efficient cognition. Loss of vascular compliance along the cerebrovascular tree would result in suboptimal vasodilation, neurovascular uncoupling, and cognitive slowing. OBJECTIVE: To assess vascular compliance along the cerebrovascular tree and its relationship to MS-related cognition. METHODS: We tested vascular compliance along the cerebrovascular tree by dividing cerebral cortex into nested layers. MS patients and healthy controls were scanned using a dual-echo functional magnetic resonance imaging (fMRI) sequence while they periodically inhaled room air and hypercapnic gas mixture. Cerebrovascular reactivity was calculated from both cerebral blood flow (arterial) and blood-oxygen-level-dependent signal (venous) increases per unit increase in end-tidal CO2. RESULTS: Arterial cerebrovascular reactivity changes along the cerebrovascular tree were reduced in cognitively slow MS compared to cognitively normal MS and healthy controls. These changes were fit to exponential functions, the decay constant (arterial compliance index; ACI) of which was associated with individual subjects' reaction time and predicted reaction time after controlling for disease processes. CONCLUSION: Such associations suggest prospects for utility of ACI in predicting future cognitive disturbances, monitoring cognitive deficiencies and therapeutic responses, and implicates neurovascular uncoupling as a mechanism of cognitive slowing in MS.

BOLD hemodynamic response function changes significantly with healthy aging.

Functional magnetic resonance imaging (fMRI) has been used to infer age-differences in neural activity from the hemodynamic response function (HRF) that characterizes the blood-oxygen-level-dependent (BOLD) signal over time. BOLD literature in healthy aging lacks consensus in age-related HRF changes, the nature of those changes, and their implications for measurement of age differences in brain function. Between-study discrepancies could be due to small sample sizes, analysis techniques, and/or physiologic mechanisms. We hypothesize that, with large sample sizes and minimal analysis assumptions, age-related changes in HRF parameters could reflect alterations in one or more components of the neural-vascular coupling system. To assess HRF changes in healthy aging, we analyzed the large population-derived dataset from the Cambridge Center for Aging and Neuroscience (CamCAN) study (Shafto et al., 2014). During scanning, 74 younger (18-30 years of age) and 173 older participants (54-74 years of age) viewed two checkerboards to the left and right of a central fixation point, simultaneously heard a binaural tone, and responded via right index finger button-press. To assess differences in the shape of the HRF between younger and older groups, HRFs were estimated using FMRIB's Linear Optimal Basis Sets (FLOBS) to minimize a priori shape assumptions. Group mean HRFs were different between younger and older groups in auditory, visual, and motor cortices. Specifically, we observed increased time-to-peak and decreased peak amplitude in older compared to younger adults in auditory, visual, and motor cortices. Changes in the shape and timing of the HRF in healthy aging, in the absence of performance differences, support our hypothesis of age-related changes in the neural-vascular coupling system beyond neural activity alone. More precise interpretations of HRF age-differences can be formulated once these physiologic factors are disentangled and measured separately.

Preserved canonicality of the BOLD hemodynamic response reflects healthy cognition: Insights into the healthy brain through the window of Multiple Sclerosis.

The hemodynamic response function (HRF), a model of brain blood-flow changes in response to neural activity, reflects communication between neurons and the vasculature that supplies these neurons in part by means of glial cell intermediaries (e.g., astrocytes). Intact neural-vascular communication might play a central role in optimal cognitive performance. This hypothesis can be tested by comparing healthy individuals to those with known white-matter damage and impaired performance, as seen in Multiple Sclerosis (MS). Glial cell intermediaries facilitate the ability of neurons to adequately convey metabolic needs to cerebral vasculature for sufficient oxygen and nutrient perfusion. In this study, we isolated measurements of the HRF that could quantify the extent to which white-matter affects neural-vascular coupling and cognitive performance. HRFs were modeled from multiple brain regions during multiple cognitive tasks using piecewise cubic spline functions, an approach that minimized assumptions regarding HRF shape that may not be valid for diseased populations, and were characterized using two shape metrics (peak amplitude and time-to-peak). Peak amplitude was reduced, and time-to-peak was longer, in MS patients relative to healthy controls. Faster time-to-peak was predicted by faster reaction time, suggesting an important role for vasodilatory speed in the physiology underlying processing speed. These results support the hypothesis that intact neural-glial-vascular communication underlies optimal neural and cognitive functioning.

Enhancing latent cognitive capacity in mild cognitive impairment with gist reasoning training: a pilot study.

OBJECTIVE: Cognitive training offers a promising way to mitigate cognitive deterioration in individuals with mild cognitive impairment (MCI). This randomized control pilot trial examined the effects of Gist Reasoning Training on cognition as compared with a training involving New Learning in a well-characterized MCI group. METHODS: Fifty participants with amnestic MCI were randomly assigned to the experimental Gist Training group or an active control New Learning group. Both groups received 8 h of training over a 4-week period. We compared pre-training with post-training changes in cognitive functions between the two training groups. RESULTS: The Gist Training group showed higher performance in executive function (strategic control and concept abstraction) and memory span compared with the New Learning group. Conversely, the New Learning group showed gains in memory for details. CONCLUSION: These findings suggest that cognitive training in general yields benefits, and more specifically, training programs that target top-down cognitive functions such as gist reasoning may have a broad impact on improving cognition in MCI. © 2016 The Authors. International Journal of Geriatric Psychiatry Published by John Wiley & Sons Ltd.

Long-term effects of marijuana use on the brain.

Questions surrounding the effects of chronic marijuana use on brain structure continue to increase. To date, however, findings remain inconclusive. In this comprehensive study that aimed to characterize brain alterations associated with chronic marijuana use, we measured gray matter (GM) volume via structural MRI across the whole brain by using voxel-based morphology, synchrony among abnormal GM regions during resting state via functional connectivity MRI, and white matter integrity (i.e., structural connectivity) between the abnormal GM regions via diffusion tensor imaging in 48 marijuana users and 62 age- and sex-matched nonusing controls. The results showed that compared with controls, marijuana users had significantly less bilateral orbitofrontal gyri volume, higher functional connectivity in the orbitofrontal cortex (OFC) network, and higher structural connectivity in tracts that innervate the OFC (forceps minor) as measured by fractional anisotropy (FA). Increased OFC functional connectivity in marijuana users was associated with earlier age of onset. Lastly, a quadratic trend was observed suggesting that the FA of the forceps minor tract initially increased following regular marijuana use but decreased with protracted regular use. This pattern may indicate differential effects of initial and chronic marijuana use that may reflect complex neuroadaptive processes in response to marijuana use. Despite the observed age of onset effects, longitudinal studies are needed to determine causality of these effects.

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

BACKGROUND: Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in human subjects. The aim of this study was to develop a statistical approach, using a machine learning framework, to correctly classify brain images of cocaine-dependent participants and healthy controls. In this study, a framework suitable for educing potential brain regions that differed between the two groups was developed and implemented. Single Photon Emission Computerized Tomography (SPECT) images obtained during rest or a saline infusion in three cohorts of 2-4 week abstinent cocaine-dependent participants (n = 93) and healthy controls (n = 69) were used to develop a classification model. An information theoretic-based feature selection algorithm was first conducted to reduce the number of voxels. A density-based clustering algorithm was then used to form spatially connected voxel clouds in three-dimensional space. A statistical classifier, Support Vectors Machine (SVM), was then used for participant classification. Statistically insignificant voxels of spatially connected brain regions were removed iteratively and classification accuracy was reported through the iterations. RESULTS: The voxel-based analysis identified 1,500 spatially connected voxels in 30 distinct clusters after a grid search in SVM parameters. Participants were successfully classified with 0.88 and 0.89 F-measure accuracies in 10-fold cross validation (10xCV) and leave-one-out (LOO) approaches, respectively. Sensitivity and specificity were 0.90 and 0.89 for LOO; 0.83 and 0.83 for 10xCV. Many of the 30 selected clusters are highly relevant to the addictive process, including regions relevant to cognitive control, default mode network related self-referential thought, behavioral inhibition, and contextual memories. Relative hyperactivity and hypoactivity of regional cerebral blood flow in brain regions in cocaine-dependent participants are presented with corresponding level of significance. CONCLUSIONS: The SVM-based approach successfully classified cocaine-dependent and healthy control participants using voxels selected with information theoretic-based and statistical methods from participants' SPECT data. The regions found in this study align with brain regions reported in the literature. These findings support the future use of brain imaging and SVM-based classifier in the diagnosis of substance use disorders and furthering an understanding of their underlying pathology.

Factors Impacting Functional Status in Veterans of Recent Conflicts With PTSD.

Veterans with posttraumatic stress disorder (PTSD) underwent a systematic evaluation to determine which factors were associated with the degree of functional status. Demographic information, self-report scales, and symptom ratings performed by trained evaluators were investigated in multiple regression models to determine their contribution to functional status. Ninety-six participants were included in the model assessing degree of functional status. Depressive symptoms, a depressive disorder diagnosis, and to a lesser extent, the Clinician-Administered PTSD Scale were selected in the final model that best predicted the degree of functional status. Depressive symptoms significantly affect the function of veterans with PTSD.

Neural mechanisms of brain plasticity with complex cognitive training in healthy seniors.

Complex mental activity induces improvements in cognition, brain function, and structure in animals and young adults. It is not clear to what extent the aging brain is capable of such plasticity. This study expands previous evidence of generalized cognitive gains after mental training in healthy seniors. Using 3 MRI-based measurements, that is, arterial spin labeling MRI, functional connectivity, and diffusion tensor imaging, we examined brain changes across 3 time points pre, mid, and post training (12 weeks) in a randomized sample (n = 37) who received cognitive training versus a control group. We found significant training-related brain state changes at rest; specifically, 1) increases in global and regional cerebral blood flow (CBF), particularly in the default mode network and the central executive network, 2) greater connectivity in these same networks, and 3) increased white matter integrity in the left uncinate demonstrated by an increase in fractional anisotropy. Improvements in cognition were identified along with significant CBF correlates of the cognitive gains. We propose that cognitive training enhances resting-state neural activity and connectivity, increasing the blood supply to these regions via neurovascular coupling. These convergent results provide preliminary evidence that neural plasticity can be harnessed to mitigate brain losses with cognitive training in seniors.

¹H MRS characterization of neurochemical profiles in orthotopic mouse models of human brain tumors.

Glioblastoma (GBM), the most common primary brain tumor, is resistant to currently available treatments. The development of mouse models of human GBM has provided a tool for studying mechanisms involved in tumor initiation and growth as well as a platform for preclinical investigation of new drugs. In this study we used (1) H MR spectroscopy to study the neurochemical profile of a human orthotopic tumor (HOT) mouse model of human GBM. The goal of this study was to evaluate differences in metabolite concentrations in the GBM HOT mice when compared with normal mouse brain in order to determine if MRS could reliably differentiate tumor from normal brain. A TE =19 ms PRESS sequence at 9.4 T was used for measuring metabolite levels in 12 GBM mice and 8 healthy mice. Levels for 12 metabolites and for lipids/macromolecules at 0.9 ppm and at 1.3 ppm were reliably detected in all mouse spectra. The tumors had significantly lower concentrations of total creatine, GABA, glutamate, total N-acetylaspartate, aspartate, lipids/macromolecules at 0.9 ppm, and lipids/macromolecules at 1.3 ppm than did the brains of normal mice. The concentrations of glycine and lactate, however, were significantly higher in tumors than in normal brain.

Word-finding impairment in veterans of the 1991 Persian Gulf War.

Approximately one quarter of 1991 Persian Gulf War Veterans experience cognitive and physiological sequelae that continue to be unexplained by known medical or psychological conditions. Difficulty coming up with words and names, familiar before the war, is a hallmark of the illness. Three Gulf War Syndrome subtypes have been identified and linked to specific war-time chemical exposures. The most functionally impaired veterans belong to the Gulf War Syndrome 2 (Syndrome 2) group, for which subcortical damage due to toxic nerve gas exposure is the suspected cause. Subcortical damage is often associated with specific complex language impairments, and Syndrome 2 veterans have demonstrated poorer vocabulary relative to controls. 11 Syndrome 1, 16 Syndrome 2, 9 Syndrome 3, and 14 age-matched veteran controls from the Seabees Naval Construction Battalion were compared across three measures of complex language. Additionally, functional magnetic resonance imaging (fMRI) was collected during a covert category generation task, and whole-brain functional activity was compared between groups. Results demonstrated that Syndrome 2 veterans performed significantly worse on letter and category fluency relative to Syndrome 1 veterans and controls. They also exhibited reduced activity in the thalamus, putamen, and amygdala, and increased activity in the right hippocampus relative to controls. Syndrome 1 and Syndrome 3 groups tended to show similar, although smaller, differences than the Syndrome 2 group. Hence, these results further demonstrate specific impairments in complex language as well as subcortical and hippocampal involvement in Syndrome 2 veterans. Further research is required to determine the extent of language impairments in this population and the significance of altered neurologic activity in the aforementioned brain regions with the purpose of better characterizing the Gulf War Syndromes.

Interaction between early life stress and alcohol dependence on neural stress reactivity.

Stress response biologic systems are altered in alcohol-dependent individuals. Early life stress (ELS) is associated with a heightened risk of alcohol dependence, presumably because of stress-induced neuroplastic changes. This study was designed to assess the contribution of ELS to a stress-induced neural response in alcohol-dependent participants. Fifteen alcohol-dependent men abstinent for 3-5 weeks and 15 age- and race-matched healthy controls were studied. Anticipatory anxiety was induced by a conditioned stimulus paired with an uncertain physically painful unconditioned stressor. Neural response was assessed with functional magnetic resonance imaging. ELS was assessed with the Childhood Adversity Interview. There was a significant interaction between ELS and group on blood-oxygen-level-dependent (BOLD) amplitude during anticipatory anxiety in the right amygdala and bilateral orbitofrontal cortex, posterior putamen and insula. Higher ELS scores were associated with decreased BOLD amplitude during anticipatory anxiety in alcohol-dependent, but not control, participants. These findings suggest that ELS interacts with alcohol dependence to induce a muted cortico-striatal response to high threat stimuli. Allostatic changes due to both ELS and excessive alcohol use may jointly induce persistent changes in the neural response to acute stressors.

Electrophysiological spatiotemporal dynamics during implicit visual threat processing.

Numerous studies have found evidence for corticolimbic theta band electroencephalographic (EEG) oscillations in the neural processing of visual stimuli perceived as threatening. However, varying temporal and topographical patterns have emerged, possibly due to varying arousal levels of the stimuli. In addition, recent studies suggest neural oscillations in delta, theta, alpha, and beta-band frequencies play a functional role in information processing in the brain. This study implemented a data-driven PCA based analysis investigating the spatiotemporal dynamics of electroencephalographic delta, theta, alpha, and beta-band frequencies during an implicit visual threat processing task. While controlling for the arousal dimension (the intensity of emotional activation), we found several spatial and temporal differences for threatening compared to nonthreatening visual images. We detected an early posterior increase in theta power followed by a later frontal increase in theta power, greatest for the threatening condition. There was also a consistent left lateralized beta desynchronization for the threatening condition. Our results provide support for a dynamic corticolimbic network, with theta and beta band activity indexing processes pivotal in visual threat processing.

Residual and enduring effects of cannabis use on cognitive and psychomotor function: A study of adults during unrestricted cannabis use, short-term abstinence, and protracted abstinence.

The impact of cannabis on cognitive and psychomotor function is important to understand, given the role of the endocannabinoid system in these critical processes. The literature has shown robust acute negative effects of cannabis on cognition and psychomotor skills during intoxication, and to a lesser degree, persisting effects following short-term abstinence up to 4 weeks. However, whether these decrements resolve after long-term cessation of use remains unclear. We evaluated cognitive and psychomotor function in 31 adults with current cannabis use during unrestricted use (UNR) and after a 3-day abstinence (RES), 23 adults with former cannabis use (> 90 days abstinent; FU), and 58 nonusing controls (CON) using the cognition and motor batteries of the National Institutes of Health Toolbox. Linear mixed models showed no significant differences in cognitive and motor performance between UNR, RES, and FU groups. Group effects emerged such that CON outperformed UNR on the Oral Reading Recognition Test, and CON outperformed both UNR and RES on the Picture Vocabulary Test. In terms of psychomotor function, FU, RES, and UNR performed better than CON on the Grip Strength Test. In this comprehensive examination of cognitive and psychomotor performance in adults with cannabis use with 3 days to > 90 days of abstinence, our results indicated that the cognitive impacts of chronic, heavy cannabis use are observable during short-term abstinence but remit after > 90 days of abstinence. This highlights widespread impacts of cannabis use abstinence across cognitive and psychomotor domains. Future studies are needed to evaluate whether these effects are also observable with use reduction, as opposed to abstinence. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Multimodal Predictive Modeling: Scalable Imaging Informed Approaches to Predict Future Brain Health.

Background: Predicting future brain health is a complex endeavor that often requires integrating diverse data sources. The neural patterns and interactions identified through neuroimaging serve as the fundamental basis and early indicators that precede the manifestation of observable behaviors or psychological states. New Method: In this work, we introduce a multimodal predictive modeling approach that leverages an imaging-informed methodology to gain insights into future behavioral outcomes. We employed three methodologies for evaluation: an assessment-only approach using support vector regression (SVR), a neuroimaging-only approach using random forest (RF), and an image-assisted method integrating the static functional network connectivity (sFNC) matrix from resting-state functional magnetic resonance imaging (rs-fMRI) alongside assessments. The image-assisted approach utilized a partially conditional variational autoencoder (PCVAE) to predict brain health constructs in future visits from the behavioral data alone. Results: Our performance evaluation indicates that the image-assisted method excels in handling conditional information to predict brain health constructs in subsequent visits and their longitudinal changes. These results suggest that during the training stage, the PCVAE model effectively captures relevant information from neuroimaging data, thereby potentially improving accuracy in making future predictions using only assessment data. Comparison with Existing Methods: The proposed image-assisted method outperforms traditional assessment-only and neuroimaging-only approaches by effectively integrating neuroimaging data with assessment factors. Conclusion: This study underscores the potential of neuroimaging-informed predictive modeling to advance our comprehension of the complex relationships between cognitive performance and neural connectivity.

Greater physical fitness ( VO 2 max ) in healthy older adults associated with increased integrity of the locus coeruleus-noradrenergic system.

AIM: Physical activity (PA) is a key component for brain health and Reserve, and it is among the main dementia protective factors. However, the neurobiological mechanisms underpinning Reserve are not fully understood. In this regard, a noradrenergic (NA) theory of cognitive reserve (Robertson, 2013) has proposed that the upregulation of NA system might be a key factor for building reserve and resilience to neurodegeneration because of the neuroprotective role of NA across the brain. PA elicits an enhanced catecholamine response, in particular for NA. By increasing physical commitment, a greater amount of NA is synthetised in response to higher oxygen demand. More physically trained individuals show greater capabilities to carry oxygen resulting in greater Vo 2 max - a measure of oxygen uptake and physical fitness (PF). METHODS: We hypothesized that greater Vo 2 max would be related to greater Locus Coeruleus (LC) MRI signal intensity. In a sample of 41 healthy subjects, we performed Voxel-Based Morphometry analyses, then repeated for the other neuromodulators as a control procedure (Serotonin, Dopamine and Acetylcholine). RESULTS: As hypothesized, greater Vo 2 max related to greater LC signal intensity, and weaker associations emerged for the other neuromodulators. CONCLUSION: This newly established link between Vo 2 max and LC-NA system offers further understanding of the neurobiology underpinning Reserve in relationship to PA. While this study supports Robertson's theory proposing the upregulation of the NA system as a possible key factor building Reserve, it also provides ground for increasing LC-NA system resilience to neurodegeneration via Vo 2 max enhancement.

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task.