Purpose in life as a resilience factor for brain health: diffusion MRI findings from the Midlife in the U.S. study.

Introduction: A greater sense of purpose in life is associated with several health benefits relevant for active aging, but the mechanisms remain unclear. We evaluated if purpose in life was associated with indices of brain health. Methods: We examined data from the Midlife in the United States (MIDUS) Neuroscience Project. Diffusion weighted magnetic resonance imaging data (n=138; mean age 65.2 years, age range 48-95; 80 females; 37 black, indigenous, and people of color) were used to estimate microstructural indices of brain health such as axonal density, and axonal orientation. The seven-item purpose in life scale was used. Permutation analysis of linear models was used to examine associations between purpose in life scores and the diffusion metrics in white matter and in the bilateral hippocampus, adjusting for age, sex, education, and race. Results and discussion: Greater sense of purpose in life was associated with brain microstructural features consistent with better brain health. Positive associations were found in both white matter and the right hippocampus, where multiple convergent associations were detected. The hippocampus is a brain structure involved in learning and memory that is vulnerable to stress but retains the capacity to grow and adapt through old age. Our findings suggest pathways through which an enhanced sense of purpose in life may contribute to better brain health and promote healthy aging. Since purpose in life is known to decline with age, interventions and policy changes that facilitate a greater sense of purpose may extend and improve the brain health of individuals and thus improve public health.

Impact of asthma on the brain: evidence from diffusion MRI, CSF biomarkers and cognitive decline.

Chronic systemic inflammation increases the risk of neurodegeneration, but the mechanisms remain unclear. Part of the challenge in reaching a nuanced understanding is the presence of multiple risk factors that interact to potentiate adverse consequences. To address modifiable risk factors and mitigate downstream effects, it is necessary, although difficult, to tease apart the contribution of an individual risk factor by accounting for concurrent factors such as advanced age, cardiovascular risk, and genetic predisposition. Using a case-control design, we investigated the influence of asthma, a highly prevalent chronic inflammatory disease of the airways, on brain health in participants recruited to the Wisconsin Alzheimer's Disease Research Center (31 asthma patients, 186 non-asthma controls, aged 45-90 years, 62.2% female, 92.2% cognitively unimpaired), a sample enriched for parental history of Alzheimer's disease. Asthma status was determined using detailed prescription information. We employed multi-shell diffusion weighted imaging scans and the three-compartment neurite orientation dispersion and density imaging model to assess white and gray matter microstructure. We used cerebrospinal fluid biomarkers to examine evidence of Alzheimer's disease pathology, glial activation, neuroinflammation and neurodegeneration. We evaluated cognitive changes over time using a preclinical Alzheimer cognitive composite. Using permutation analysis of linear models, we examined the moderating influence of asthma on relationships between diffusion imaging metrics, CSF biomarkers, and cognitive decline, controlling for age, sex, and cognitive status. We ran additional models controlling for cardiovascular risk and genetic risk of Alzheimer's disease, defined as a carrier of at least one apolipoprotein E (APOE) ε4 allele. Relative to controls, greater Alzheimer's disease pathology (lower amyloid-ß42/amyloid-ß40, higher phosphorylated-tau-181) and synaptic degeneration (neurogranin) biomarker concentrations were associated with more adverse white matter metrics (e.g. lower neurite density, higher mean diffusivity) in patients with asthma. Higher concentrations of the pleiotropic cytokine IL-6 and the glial marker S100B were associated with more salubrious white matter metrics in asthma, but not in controls. The adverse effects of age on white matter integrity were accelerated in asthma. Finally, we found evidence that in asthma, relative to controls, deterioration in white and gray matter microstructure was associated with accelerated cognitive decline. Taken together, our findings suggest that asthma accelerates white and gray matter microstructural changes associated with aging and increasing neuropathology, that in turn, are associated with more rapid cognitive decline. Effective asthma control, on the other hand, may be protective and slow progression of cognitive symptoms.

Altered Developmental Trajectory in Male and Female Rats in a Prenatal Valproic Acid Exposure Model of Autism Spectrum Disorder.

Early motor and sensory developmental delays precede Autism Spectrum Disorder (ASD) diagnosis and may serve as early indicators of ASD. The literature on sensorimotor development in animal models is sparse, male centered, and has mixed findings. We characterized early development in a prenatal valproic acid (VPA) model of ASD and found sex-specific developmental delays in VPA rats. We created a developmental composite score combining 15 test readouts, yielding a reliable gestalt measure spanning physical, sensory, and motor development, that effectively discriminated between VPA and control groups. Considering the heterogeneity in ASD phenotype, the developmental composite offers a robust metric that can enable comparison across different animal models of ASD and can serve as an outcome measure for early intervention studies.

Classification of Rajayoga Meditators Based on the Duration of Practice Using Graph Theoretical Measures of Functional Connectivity from Task-Based Functional Magnetic Resonance Imaging.

Context: Functional magnetic resonance imaging (fMRI) studies on mental training techniques such as meditation have reported benefits like increased attention and concentration, better emotional regulation, as well as reduced stress and anxiety. Although several studies have examined functional activation and connectivity in long-term as well as short-term meditators from different meditation traditions, it is unclear if long-term meditation practice brings about distinct changes in network properties of brain functional connectivity that persist during task performance. Indeed, task-based functional connectivity studies of meditators are rare. Aims: This study aimed to differentiate between long-term and short-term Rajayoga meditators based on functional connectivity between regions of interest in the brain. Task-based fMRI was captured as the meditators performed an engaging task. The graph theoretical-based functional connectivity measures of task-based fMRI were calculated using CONN toolbox and were used as features to classify the two groups using Machine Learning models. Subjects and Methods: In this study, we recruited two age and sex-matched groups of Rajayoga meditators from the Brahma Kumaris tradition that differed in the duration of their meditation experience: Long-term practitioners (n = 12, mean 13,596 h) and short-term practitioners (n = 10, mean 1095 h). fMRI data were acquired as they performed an engaging task and functional connectivity metrics were calculated from this data. These metrics were used as features in training machine learning algorithms. Specifically, we used adjacency matrices generated from graph measures, global efficiency, and local efficiency, as features. We computed functional connectivity with 132 ROIs as well as 32 network ROIs. Statistical Analysis Used: Five machine learning models, such as logistic regression, SVM, decision tree, random forest, and gradient boosted tree, were trained to classify the two groups. Accuracy, precision, sensitivity, selectivity, area under the curve receiver operating characteristics curve were used as performance measures. Results: The graph measures were effective features, and tree-based algorithms such as decision tree, random forest, and gradient boosted tree yielded the best performance (test accuracy >84% with 132 ROIs) in classifying the two groups of meditators. Conclusions: Our results support the hypothesis that long-term meditative practices alter brain functional connectivity networks even in nonmeditative contexts. Further, the use of adjacency matrices from graph theoretical measures of high-dimensional fMRI data yields a promising feature set for machine learning classifiers.

Asthma amplifies dementia risk: Evidence from CSF biomarkers and cognitive decline.

Introduction: Evidence from epidemiology, neuroimaging, and animal models indicates that asthma adversely affects the brain, but the nature and extent of neuropathophysiological impact remain unclear. Methods: We tested the hypothesis that asthma is a risk factor for dementia by comparing cognitive performance and cerebrospinal fluid biomarkers of glial activation/neuroinflammation, neurodegeneration, and Alzheimer's disease (AD) pathology in 60 participants with asthma to 315 non-asthma age-matched control participants (45-93 years), in a sample enriched for AD risk. Results: Participants with severe asthma had higher neurogranin concentrations compared to controls and those with mild asthma. Positive relationships between cardiovascular risk and concentrations of neurogranin and α-synuclein were amplified in severe asthma. Severe asthma also amplified the deleterious associations that apolipoprotein E ε4 carrier status, cardiovascular risk, and phosphorylated tau181/amyloid beta42 have with rate of cognitive decline. Discussion: Our data suggest that severe asthma is associated with synaptic degeneration and may compound risk for dementia posed by cardiovascular disease and genetic predisposition. Highlights: Those with severe asthma showed evidence of higher dementia risk than controls evidenced by: higher levels of the synaptic degeneration biomarker neurogranin regardless of cognitive status, cardiovascular or genetic risk, and controlling for demographics.steeper increase in levels of synaptic degeneration biomarkers neurogranin and α-synuclein with increasing cardiovascular risk.accelerated cognitive decline with higher cardiovascular risk, genetic predisposition, or pathological tau.

Meditation, well-being and cognition in heartfulness meditators - A pilot study.

Meditative practices can vary considerably in technique as well as their effects. Heartfulness is a popular meditation technique that includes in its repertoire, a unique passive form of meditation. We carried out a pilot study recruiting male heartfulness meditators (proficient n = 24, with 6-28 years of meditation experience; novice n = 24, 5 to 16 months of experience) and subsequently recruited matched controls (n = 15). We examined well-being, and carried out high-density EEG recordings to examine indices of meditation and cognition in these groups. Well-being scores were significantly higher for the proficient meditators as compared to novice and intermediate for the controls. We did not find any group differences in cognitive processing. During meditation, enhanced occipital gamma was found in proficient meditators as compared to controls. We discuss the findings from this pilot study and suggest avenues for future research.

State-trait influences of Vipassana meditation practice on P3 EEG dynamics.

Several studies have demonstrated that meditation naïve subjects can, in just a few weeks, become proficient enough in meditation to show cognitive improvements accompanied with functional and structural changes in the brain. Would long-term exposure to qualitatively different levels of meditative training bring about differences in cognitive processing? Would meditation prior to task performance help separate out these differences? Could the nature of the task influence the findings related to cognitive enhancements? To address these questions, we evaluated cognitive functions in three groups of experienced Vipassana practitioners (Novices: n=22, Mean±SD meditation experience=989±595h; Senior practitioners: 21, 10,510±5313; Teachers: 16, 14,648±9623) who differed in terms of duration and quality of meditative practice. Specifically, we employed "ANGEL" a gamified multilevel oddball paradigm, to assess P3 event-related potentials (ERPs) and associated EEG dynamics-power spectra, event related spectral perturbations (ERSP) and inter-trial coherence (ITC). In order to elicit the state-trait influences of meditation, the cognitive task was performed after the participants had undergone an hour long traditional meditation session. All participants could perform the task well and the gross ERP waveforms were similar for the three groups. As hypothesized, we found distinct state-trait influences of meditation leading to graded differences in P3 EEG dynamics. Specifically, we found reduced theta synchrony, enhanced alpha de-synchrony and lesser theta-alpha coherence in the more proficient meditators. Post hoc analyses revealed several differences between the novice and teacher groups but not as many between novice and seniors suggesting that the senior meditators formed an intermediate group. Our study demonstrates that both quantity and quality of meditation influence EEG dynamics during cognitive processing and that meditation prior to a task can provide additional state-trait effects involved in meeting the specific cognitive demands.

Beyond Hypnograms: Assessing Sleep Stability Using Acoustic and Electrical Stimulation.

OBJECTIVE: Conventional polysomnographic recordings reflect brain dynamics associated with sleep architecture. We hypothesized that noninvasive tools like transcranial alternating current stimulation (tACS) and acoustic stimulation (for generating event related potentials [ERPs]) would help to predict sleep stability and provide a window to actively assess brain activity during sleep. MATERIALS AND METHODS: Twelve healthy male volunteers participated in the multiple whole-night polysomnography (PSG) recording protocol. Acoustic tones (100 msec duration) were presented throughout night to evaluate ERP during sleep. Furthermore, 30 sec tACS were presented during nonrapid eye movement (NREM) and rapid eye movement (REM) sleep on subsequent two nights without disturbing the subject's sleep. For ERP analysis, event-locked artifact-free epochs from each sleep stage were averaged separately. For tACS analysis, 30 sec prestimulus and poststimulus artifact-free EEG epochs were subjected to bootstrapping-based comparison of power spectral values. RESULTS: Acoustic stimulation generated sleep stage-dependent ERP components (N350, N550, and P900) in all participants. The tACS stimulation during NREM sleep (0.75 Hz) increased parietal delta power but decreased frontocentral theta and increased frontal gamma power when delivered during REM sleep (40Hz). These interventions provide details on sleep stability as larger N550-P900 ERP-complex correlated with lower NREM disruptions (Spearman's rho = -0.553; p = 0.049; n = 10) and tACS-related theta power perturbation with higher REM disruptions (Spearman's rho = 0.734; p = 0.030; n = 7). CONCLUSIONS: Noninvasive brain stimulation approaches such as sleep ERP and sleep tACS are reliable tools to evaluate sleep stability during NREM and REM sleep, respectively, but more large-sample studies are warranted.

Dissociating meditation proficiency and experience dependent EEG changes during traditional Vipassana meditation practice.

Meditation, as taught by most schools of practice, consists of a set of heterogeneous techniques. We wanted to assess if EEG profiles varied across different meditation techniques, proficiency levels and experience of the practitioners. We examined EEG dynamics in Vipassana meditators (Novice, Senior meditators and Teachers) while they engaged in their traditional meditation practice (concentration, mindfulness and loving kindness in a structured manner) as taught by S.N. Goenka. Seniors and Teachers (vs Novices) showed trait increases in delta (1-4 Hz), theta-alpha (6-10 Hz) and low-gamma power (30-40 Hz) at baseline rest; state-trait increases in low-alpha (8-10 Hz) and low-gamma power during concentrative and mindfulness meditation; and theta-alpha and low-gamma power during loving-kindness meditation. Permutation entropy and Higuchi fractal dimension measures further dissociated high proficiency from duration of experience as only Teachers showed consistent increase in network complexity from baseline rest and state transitions between the different meditation states.

Further evidences for sleep instability and impaired spindle-delta dynamics in schizophrenia: a whole-night polysomnography study with neuroloop-gain and sleep-cycle analysis.

OBJECTIVE: Sleep offers a unique window into the brain dysfunctions in schizophrenia. Many past sleep studies have reported abnormalities in both macro-sleep architecture (like increased awakenings) as well as micro-sleep-architecture (like spindle deficits) in patients with schizophrenia (PSZ). The present study attempts to replicate previous reports of macro- and micro-sleep-architectural abnormalities in schizophrenia. In addition, the study also examined sleep-stage changes and spindle-delta dynamics across sleep-cycles to provide further evidence in support of the dysfunctional thalamocortical mechanisms causing sleep instability and poor sleep maintenance associated with schizophrenia pathophysiology. METHODS: Whole-night polysomnography was carried out among 45 PSZ and 39 age- and gender-matched healthy control subjects. Sleep-stage dynamics were assessed across sleep-cycles using a customized software algorithm. Spindle-delta dynamics across sleep-cycles were determined using neuroloop-gain analysis. RESULTS: PSZ showed macro-sleep architecture abnormalities such as prolonged sleeplessness, increased intermittent-awakenings, long sleep-onset latency, reduced non-rapid eye movement (NREM) stage 2 sleep, increased stage transitions, and poor sleep efficiency. They also showed reduced spindle density (sigma neuroloop-gain) but comparable slow wave density (delta neuroloop-gain) throughout the sleep. Sleep-cycle-wise analysis revealed transient features of sleep instability due to significantly increased intermittent awakenings especially in the first and third sleep-cycles, and unstable and recurrent stage transitions in both NREM (first sleep-cycle) and rapid eye movement (REM) sleep-periods (second sleep-cycle). Spindle deficits were persistent across the first three cycles and were positively correlated with sleep disruption during the subsequent REM sleep. CONCLUSIONS: In addition to replicating previously reported sleep deficits in PSZ, the current study showed subtle deficits in NREM-REM alterations across whole-night polysomnography. These results point towards a possible maladaptive interplay between unstable thalamocortical networks, resulting in sleep-cycle-specific instability patterns associated with schizophrenia pathophysiology.

Altered attentional processing in male and female rats in a prenatal valproic acid exposure model of autism spectrum disorder.

Attention is foundational to efficient perception and optimal goal driven behavior. Intact attentional processing is crucial for the development of social and communication skills. Deficits in attention are therefore likely contributors to the core pathophysiology of autism spectrum disorder (ASD). Clinical evidence in ASD is suggestive of impairments in attention and its control, but the underlying mechanisms remain elusive. We examined sustained, spatially divided attention in a prenatal valproic acid (VPA) model of ASD using the 5-choice serial reaction time task (5-CSRTT). As compared to controls, male and female VPA rats had progressively lower accuracy and higher omissions with increasing attentional demands during 5-CSRTT training, and showed further performance decrements when subjected to parametric task manipulations. It is noteworthy that although VPA exposure induced attentional deficits in both sexes, there were task parameter specific sex differences. Importantly, we did not find evidence of impulsivity or motivational deficits in VPA rats but we did find reduced social preference, as well as sensorimotor deficits that suggest pre-attentional information processing impairments. Importantly, with fixed rules, graded difficulty levels, and more time, VPA rats could be successfully trained on the attentional task. To the best of our knowledge, this is the first study examining attentional functions in a VPA model. Our work underscores the need for studying both sexes in ASD animal models and validates the use of the VPA model in the quest for mechanistic understanding of aberrant attentional functions and for evaluating suitable therapeutic targets. Autism Res 2017, 10: 1929-1944. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: We studied rats prenatally exposed to valproic acid (VPA), an established rodent model of autism. Both male and female VPA rats had a range of attentional impairments with sex-specific characteristics. Importantly, with fixed rules, graded difficulty levels, and more time, VPA rats could be successfully trained on the attentional task. Our work validates the use of the VPA model in the quest for evaluating suitable therapeutic targets for improving attentional performance.

Just a minute meditation: Rapid voluntary conscious state shifts in long term meditators.

Meditation induces a modified state of consciousness that remains under voluntary control. Can meditators rapidly and reversibly bring about mental state changes on demand? To check, we carried out 128 channel EEG recordings on Brahma Kumaris Rajayoga meditators (36 long term: median 14240h meditation; 25 short term: 1095h) and controls (25) while they tried to switch every minute between rest and meditation states in different conditions (eyes open and closed; before and after an engaging task). Long term meditators robustly shifted states with enhanced theta power (4-8Hz) during meditation. Short term meditators had limited ability to shift between states and showed increased lower alpha power (8-10Hz) during eyes closed meditation only when pre and post task data were combined. Controls could not shift states. Thus trained beginners can reliably meditate but it takes long term practice to exercise more refined control over meditative states.