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.

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.

Exploring how brain health strategy training informs the future of work.

Introduction: The workplace typically affords one of the longest periods for continued brain health growth. Brain health is defined by the World Health Organization (WHO) as the promotion of optimal brain development, cognitive health, and well-being across the life course, which we expanded to also include connectedness to people and purpose. This work was motivated by prior work showing individuals, outside of an aggregate setting, benefitted from training as measured by significant performance gains on a holistic BrainHealth Index and its factors (i.e., clarity, connectedness, emotional balance). The current research was conducted during the changing remote work practices emerging post-pandemic to test whether a capacity-building training would be associated with significant gains on measures of brain health and components of burnout. The study also tested the influence of utilization of training modules and days in office for individuals to inform workplace practices. Methods: We investigated whether 193 individuals across a firm's sites would improve on measures of brain health and burnout from micro-delivery of online tactical brain health strategies, combined with two individualized coaching sessions, and practical exercises related to work and personal life, over a six-month period. Brain health was measured using an evidenced-based measure (BrainHealth™ Index) with its components (clarity, connectedness, emotional balance) consistent with the WHO definition. Burnout was measured using the Maslach Burnout Inventory Human Services Survey. Days in office were determined by access to digital workplace applications from the firm's network. Regression analyses were used to assess relationships between change in BrainHealth factors and change in components of the Maslach Burnout Inventory. Results: Results at posttest indicated that 75% of the individuals showed gains on a composite BrainHealth Index and across all three composite factors contributing to brain health. Benefits were directly tied to training utilization such that those who completed the core modules showed the greatest gains. The current results also found an association between gains on both the connectedness and emotional balance brain health factors and reduced on burnout components of occupational exhaustion and depersonalization towards one's workplace. We found that fewer days in the office were associated with greater gains in the clarity factor, but not for connectedness and emotional balance. Discussion: These results support the value of a proactive, capacity-building training to benefit all employees to complement the more widespread limited offerings that address a smaller segment who need mental illness assistance programs. The future of work may be informed by corporate investment in focused efforts to boost collective brain capital through a human-centered, capacity-building approach. Efforts are underway to uncover the value of better brain health, i.e., Brainomics© - which includes economic, societal, and individual benefits.

Greater physical fitness (Vo2Max) in healthy older adults associated with increased integrity of the Locus Coeruleus-Noradrenergic system.

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 Vo2max - a measure of oxygen uptake and physical fitness (PF). In the current study, we hypothesised that greater Vo2 max would be related to greater Locus Coeruleus (LC) MRI signal intensity. As hypothesised, greater Vo2max related to greater LC signal intensity across 41 healthy adults (age range 60-72). As a control procedure, in which these analyses were repeated for the other neuromodulators' seeds (for Serotonin, Dopamine and Acetylcholine), weaker associations emerged. This newly established link between Vo2max 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 noradrenergic system as a possible key factor building Reserve, it also provide grounds for increasing LC-NA system resilience to neurodegeneration via Vo2max enhancement.

Effects of online brain training on self-reported mental health symptoms for generally healthy adults during the Covid-19 pandemic.

BACKGROUND: The cognitive training Strategic Memory Advanced Reasoning Training (SMART) has been shown to improve symptoms of depression, anxiety, and stress when completed using in-person delivery, but mental health outcomes have not yet been studied for online delivery of SMART. METHODS: Data was analyzed from 145 generally healthy adults participating in the BrainHealth Project pilot study who had access to 12 weeks of online self-paced SMART and self-reported mental health symptoms on the Depression Anxiety Stress Scale (DASS-21) pre- and post-training. We utilized linear models to examine the change in self-reported symptoms of depression, anxiety, and stress following the 12-week training period and to explore the influence of age, gender, and education on changes in symptomatology. Data from 44 participants who completed a follow-up DASS-21 6 months after completing SMART was used to explore the lasting impact of the training. RESULTS: Improvements in depression, anxiety, and stress symptoms were observed following online SMART, evidenced by a significant decrease in self-reported symptoms on the DASS-21. Improvement in self-reported mental health symptomatology was maintained or continued to improve 6-month post-training. No significant effect of gender was observed, but findings motivate additional exploration of the effects of education and age. CONCLUSION: Online SMART should be considered a low-cost, high-impact approach for supporting public mental health for generally healthy adults.

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.

EEG theta and alpha oscillations in early versus late mild cognitive impairment during a semantic Go/NoGo task.

Amnestic mild cognitive impairment (aMCI) is marked by episodic memory deficits, which can be used to classify individuals into early MCI (EMCI) and late MCI (LMCI). Although mounting evidence suggests that individuals with aMCI have additional cognitive alterations including deficits in cognitive control, few have examined if EMCI and LMCI differ on processes other than episodic memory. Using a semantic Go/NoGo task, we examined differences in cognitive control between EMCI and LMCI on behavioral (accuracy and reaction time) and neural (scalp-recorded event-related oscillations in theta and alpha band) measures. Although no behavioral differences were observed between the EMCI and LMCI groups, differences in neural oscillations were observed. The LMCI group had higher theta synchronization on Go trials at central electrodes compared to the EMCI group. In addition, the EMCI group showed differences in theta power at central electrodes and alpha power at central and centro-parietal electrodes between Go and NoGo trials, while the LMCI group did not exhibit such differences. These findings suggest that while behavioral differences may not be observable, neural changes underlying cognitive control processes may differentiate EMCI and LMCI stages and may be useful to understand the trajectory of aMCI in future studies.

Snoring Remediation with Oral Appliance Therapy Potentially Reverses Cognitive Impairment: An Intervention Controlled Pilot Study.

Respiration rate (RR) dynamics entrains brain neural networks. RR differences between mild cognitive impairment (MCI) and Alzheimer's disease (AD) in response to oral appliance therapy (OAT) are unknown. This pilot study investigated if RR during stable sleep shows a relationship to pathological severity in subjects with MCI and AD who snore and if RR is influenced following stabilization of the upper airway using OAT. The study cohort was as follows: cognitively normal (CN; n = 14), MCI (n = 14) and AD (n = 9); and a sub-population receiving intervention, CN (n = 5), MCI (n = 7), AD (n = 6) subjects. The intervention used was an oral appliance plus a mouth shield (Tx). RR maximum (max) rate (breaths/minute) and RR fluctuation during 2116 stable sleep periods were measured. The Montreal cognitive assessment (MoCA) was administered before and after 4 weeks with Tx. Baseline data showed significantly higher RR fluctuation in CN vs. AD (p < 0.001) but not between CN vs. MCI (p = 0.668). Linear mixed model analysis indicated Tx effect (p = 0.008) for RR max. Tx after 4 weeks lowered the RR-max in MCI (p = 0.022) and AD (p < 0.001). Compared with AD RR max, CN (p < 0.001) and MCI (p < 0.001) were higher with Tx after 4 weeks. Some MCI and AD subjects improved executive and memory function after 4 weeks of Tx.

A Novel BrainHealth Index Prototype Improved by Telehealth-Delivered Training During COVID-19.

Introduction: Brain health is neglected in public health, receiving attention after something goes wrong. Neuroplasticity research illustrates that preventive steps strengthen the brain's component systems; however, this information is not widely known. Actionable steps are needed to scale proven population-level interventions. Objectives: This pilot tested two main objectives: (1) the feasibility/ease of use of an online platform to measure brain health, deliver training, and offer virtual coaching to healthy adults and (2) to develop a data driven index of brain health. Methods: 180 participants, ages 18-87, enrolled in this 12-week pilot. Participants took a BrainHealth Index™ (BHI), a composite of assessments encompassing cognition, well-being, daily-life and social, pre-post training. Participants engaged in online training with three coaching sessions. We assessed changes in BHI, effects of training utilization and demographics, contributions of sub-domain measures to the BHI and development of a factor analytic structure of latent BrainHealth constructs. Results: The results indicated that 75% of participants showed at least a 5-point gain on their BHI which did not depend on age, education, or gender. The contribution to these gains were from all sub-domains, including stress, anxiety and resilience, even though training focused largely on cognition. Some individuals improved due to increased resilience and decreased anxiety, whereas others improved due to increased innovation and social engagement. Larger gains depended on module utilization, especially strategy training. An exploratory factor analytic solution to the correlation matrix of online assessments identified three latent constructs. Discussion/Conclusion: This pilot study demonstrated the efficacy of an online platform to assess changes on a composite BrainHealth Index and efficacy in delivering training modules and coaching. We found that adults, college age to late life, were motivated to learn about their brain and engage in virtual-training with coaching to improve their brain health. This effort intends to scale up to thousands, thus the pilot data, tested by an impending imaging pilot, will be utilized in ongoing machine learning (ML) algorithms to develop a precision brain health model. This pilot is a first step in scaling evidence-based brain health protocols to reach individuals and positively affect public health globally.

Efficacy of Cognitive Training When Translated From the Laboratory to the Real World.

INTRODUCTION: Research shows that cognitive performance and emotional well-being can be significantly strengthened. A high-performance brain training protocol, Strategic Memory Advanced Reasoning Training (SMART), was developed by cognitive neuroscientists at The University of Texas at Dallas Center for BrainHealth based on 25-plus years of scientific study. Randomized controlled trials with various populations have shown that training and use of nine "SMART" strategies for processing information can improve cognitive performance and psychological health. However, the multi-week intensive training used in the laboratory is not practical for widespread use outside the laboratory. This article examines the efficacy of SMART when translated outside the laboratory to two populations (military/veterans and law enforcement) that received SMART in condensed time frames. MATERIALS AND METHODS: In two translation studies with healthy military personnel and veterans, 425 participants received between 6 and 10 hours of SMART over 2 days. In a third translation study, 74 healthy police officers received 9 hours of SMART over 3 days. Training was conducted by clinicians who taught the nine "SMART" strategies related to three core areas-strategic attention, integrated reasoning, and innovation-to groups of up to 25 participants. In all three translation studies, cognitive performance and psychological health data were collected before and immediately following the training. In one of the military/veteran studies, psychological health data were also collected 1 and 4 months following the training. RESULTS: In both translations to military personnel and veterans, there were improvements in the complex cognitive domains of integrated reasoning (P < .0001) and innovation (P < .0001) immediately after undergoing SMART. In the translation to police officers, there were improvements in the cognitive domains of innovation (P = .02) and strategic attention (P = .005). Participants in all three translations saw statistically significant improvements in self-reported symptoms of psychological health. The improvements continued among a subset of participants who responded to the later requests for information. CONCLUSIONS: The results of translating to these two populations provide evidence supporting the efficacy of SMART delivered in an abbreviated time frame. The improvements in two major domains of cognitive function demonstrate that strategies can be taught and immediately applied by those receiving the training. The immediate psychological health improvements may be transient; however, the continued improvements in psychological health observed in a subset of the participants suggest that benefits may be sustainable even at later intervals.

Altered task-induced cerebral blood flow and oxygen metabolism underlies motor impairment in multiple sclerosis.

The neural mechanisms underlying motor impairment in multiple sclerosis (MS) remain unknown. Motor cortex dysfunction is implicated in blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies, but the role of neural-vascular coupling underlying BOLD changes remains unknown. We sought to independently measure the physiologic factors (i.e., cerebral blood flow (ΔCBF), cerebral metabolic rate of oxygen (ΔCMRO2), and flow-metabolism coupling (ΔCBF/ΔCMRO2), utilizing dual-echo calibrated fMRI (cfMRI) during a bilateral finger-tapping task. We utilized cfMRI to measure physiologic responses in 17 healthy volunteers and 32 MS patients (MSP) with and without motor impairment during a thumb-button-press task in thumb-related (task-central) and surrounding primary motor cortex (task-surround) regions of interest (ROIs). We observed significant ΔCBF and ΔCMRO2 increases in all MSP compared to healthy volunteers in the task-central ROI and increased flow-metabolism coupling (ΔCBF/ΔCMRO2) in the MSP without motor impairment. In the task-surround ROI, we observed decreases in ΔCBF and ΔCMRO2 in MSP with motor impairment. Additionally, ΔCBF and ΔCMRO2 responses in the task-surround ROI were associated with motor function and white matter damage in MSP. These results suggest an important role for task-surround recruitment in the primary motor cortex to maintain motor dexterity and its dependence on intact white matter microstructure and neural-vascular coupling.

Relationship of Parieto-Occipital Brain Energy Phosphate Metabolism and Cognition Using 31P MRS at 7-Tesla in Amnestic Mild Cognitive Impairment.

BACKGROUND: The human brain has high energy requirements that continuously support healthy neuronal activity and cognition. A disruption in brain energy metabolism (BEM) may contribute to early neuropathological changes such as accumulation of ß-amyloid and tau in vulnerable populations. One such population is amnestic mild cognitive impairment (aMCI) where some individuals are at risk for developing dementia, i.e. Alzheimer's disease (AD). Recent advances in imaging technology are providing new avenues to measure BEM accurately using 31phosphorus magnetic resonance spectroscopy (31P MRS) at ultra-high-field (UHF) magnetic strength 7-Tesla. This study investigates whether a methodology using partial volume-coil 31P MRS at 7T over parieto-occipital lobes can accurately quantify high-energy phosphate and membrane phospholipid metabolites in aMCI. A secondary objective was to explore BEM and membrane phospholipid indices' correspondence with cognitive performance in domains of executive function (EF), memory, attention, and visuospatial skills in aMCI, a heterogeneous population. METHODS: 19 aMCI participants enrolled in the study completed cognitive assessment and 31P MRS scan. BEM indices were measured using three energy indicators: energy reserve (PCr/t-ATP), energy consumption (intracellular_Pi/t-ATP), and metabolic state (PCr/intracellular_Pi) along with regulatory co-factors of BEM-intracellular Mg2 + and pH; whereas the ratio of phosphomonoesters (PMEs) to phosphodiesters (PDEs) - membrane phospholipid indicator. RESULTS: 31P MRS scan showed thirteen well-resolved peaks with precise quantification of the phosphorus metabolites at UHF. The higher BEM indices were associated with lower cognitive performance of memory [(energy reserve indicator: CVLT p = 0.004), (metabolic state indicator: CVLT p = 0.007)], executive function [(metabolic state indicator: TOSL (p = 0.044)], and attention [(pH: selective auditory task, p = 0.044)]. The finding of an inverse relationship observed in the parieto-occipital lobes suggests an association between neuronal energy markers with cognition in aMCI. CONCLUSION: The significant contribution of this preliminary research was to establish the feasibility of utilizing a methodology at UHF to accurately measure high-energy phosphate and membrane phospholipid metabolites in a population with heterogeneous outcomes. This work offers a novel approach for future work to further elucidate early dementia biomarkers or precursors to the downstream accumulation of amyloid and tau using the combination of MRS-PET imaging modalities in AD.

Identification of selection and inhibition components in a Go/NoGo task from EEG spectra using a machine learning classifier.

INTRODUCTION: Prior Go/NoGo studies have localized specific regions and EEG spectra for which traditional approaches have distinguished between Go and NoGo conditions. A more detailed characterization of the spatial distribution and timing of the synchronization of frequency bands would contribute substantially to the clarification of neural mechanisms that underlie performance of the Go/NoGo task. METHODS: The present study used a machine learning approach to learn the features that distinguish between ERSPs involved in selection and inhibition in a Go/NoGo task. A single-layer neural network classifier was used to predict task conditions for each subject to characterize ERSPs associated with Go versus NoGo trials. RESULTS: The final classifier accurately identified individual task conditions at an overall rate of 92%, estimated by fivefold cross-validation. The detailed accounting of EEG time-frequency patterns localized to brain regions (i.e., thalamus, pre-SMA, orbitofrontal cortex, and superior parietal cortex) corroborates and also elaborates upon previous findings from fMRI and EEG studies, and expands the information about EEG power changes in multiple frequency bands (i.e., primarily theta power increase, alpha decreases, and beta increases and decreases) within these regions underlying the selection and inhibition processes engaged in the Go and NoGo trials. CONCLUSION: This time-frequency-based classifier extends previous spatiotemporal findings and provides information about neural mechanisms underlying selection and inhibition processes engaged in Go and NoGo trials, respectively. This neural network classifier can be used to assess time-frequency patterns from an individual subject and thus may offer insight into therapeutic uses of neuromodulation in neural dysfunction.

Multimodal feature binding in object memory retrieval using event-related potentials: Implications for models of semantic memory.

To test the hypothesis that semantic processes are represented in multiple subsystems, we recorded electroencephalogram (EEG) as we elicited object memories using the modified Semantic Object Retrieval Test, during which an object feature, presented as a visual word [VW], an auditory word [AW], or a picture [Pic], was followed by a second feature always presented as a visual word. We performed both hypothesis-driven and data-driven analyses using event-related potentials (ERPs) time locked to the second stimulus. We replicated a previously reported left fronto-temporal ERP effect (750-1000 ms post-stimulus) in the VW task, and also found that this ERP component was only present during object memory retrieval in verbal (VW, AW) as opposed to non-verbal (Pic) stimulus types. We also found a right temporal ERP effect (850-1000 ms post-stimulus) that was present in auditory (AW) but not in visual (VW, Pic) stimulus types. In addition, we found an earlier left temporo-parietal ERP effect between 350 and 700 ms post-stimulus and a later midline parietal ERP effect between 700 and 1100 ms post-stimulus, present in all stimulus types, suggesting common neural mechanisms for object retrieval processes and object activation, respectively. These findings support multiple semantic subsystems that respond to varying stimulus modalities, and argue against an ultimate unitary amodal semantic analysis.

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.

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.

High-Definition Transcranial Direct Current Stimulation to Improve Verbal Retrieval Deficits in Chronic Traumatic Brain Injury.

Chronic verbal retrieval deficits have been noted in traumatic brain injury (TBI), but no U.S. Food and Drug Administration-approved interventions are available. The present study investigated whether 10 sessions of 20 min of 1 mA anodal high-definition transcranial direct current stimulation (HD-tDCS) targeting pre-supplementary motor area/dorsal anterior cingulate cortex (preSMA/dACC) compared with sham HD-tDCS would improve verbal retrieval deficits in TBI patients. Improvements in verbal retrieval processes were observed up to 8 weeks post-treatment. Thus, potential dysfunction to verbal retrieval circuitry in TBI appears amenable to remediation through electromodulation with HD tDCS to the preSMA/dACC. Although further studies clarifying mechanisms by which tDCS brought about these improvements will likely inform refinements in the application of this therapeutic technique, the findings suggest the efficacy of using HD-tDCS to target other systems vulnerable to TBI to improve functioning.

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.

Cognitive Training and Transcranial Direct Current Stimulation in Mild Cognitive Impairment: A Randomized Pilot Trial.

BACKGROUND: Transcranial direct current stimulation (tDCS), a non-invasive stimulation, represents a potential intervention to enhance cognition across clinical populations including Alzheimer's disease and mild cognitive impairment (MCI). This randomized clinical trial in MCI investigated the effects of anodal tDCS (a-tDCS) delivered to left inferior frontal gyrus (IFG) combined with gist-reasoning training (SMART) versus sham tDCS (s-tDCS) plus SMART on measures of cognitive and neural changes in resting cerebral blood flow (rCBF). We were also interested in SMART effects on cognitive performance regardless of the tDCS group. METHODS: Twenty-two MCI participants, who completed the baseline cognitive assessment (T1), were randomized into one of two groups: a-tDCS + SMART and s-tDCS + SMART. Of which, 20 participants completed resting pCASL MRI scan to measure rCBF. Eight SMART sessions were administered over 4 weeks with a-tDCS or s-tDCS stimulation for 20 min before each session. Participants were assessed immediately (T2) and 3-months after training (T3). RESULTS: Significant group × time interactions showed cognitive gains at T2 in executive function (EF) measure of inhibition [DKEFS- Color word (p = 0.047)], innovation [TOSL (p = 0.01)] and on episodic memory [TOSL (p = 0.048)] in s-tDCS + SMART but not in a-tDCS + SMART group. Nonetheless, the gains did not persist for 3 months (T3) after the training. A voxel-based analysis showed significant increase in regional rCBF in the right middle frontal cortex (MFC) (cluster-wise p = 0.05, k = 1,168 mm3) in a-tDCS + SMART compared to s-tDCS + SMART. No significant relationship was observed between the increased CBF with cognition. Irrespective of group, the combined MCI showed gains at T2 in EF of conceptual reasoning [DKEFS card sort (p = 0.033)] and category fluency [COWAT (p = 0.055)], along with gains at T3 in EF of verbal fluency [COWAT (p = 0.009)]. CONCLUSION: One intriguing finding is a-tDCS to left IFG plus SMART increased blood flow to right MFC, however, the stimulation seemingly blocked cognitive benefits of SMART on EF (inhibition and innovation) and episodic memory compared to s-tDCS + SMART group. Although the sample size is small, this paper contributes to growing evidence that cognitive training provides a way to significantly enhance cognitive performance in adults showing memory loss, where the role of a-tDCS in augmenting these effects need further study.