The use of rodent models to better characterize the relationship among epilepsy, sleep, and memory.

Epilepsy, a neurological disorder characterized by recurrent seizures, is known to be associated with impaired sleep and memory. Although the specific mechanisms underlying these impairments are uncertain, the known role of sleep in memory consolidation suggests a potential relationship may exist between seizure activity, disrupted sleep, and memory impairment. A possible mediator in this relationship is the sleep spindle, the characteristic electroencephalographic (EEG) feature of non-rapid-eye-movement (NREM) sleep in humans and other mammals. Growing evidence supports the idea that sleep spindles, having thalamic origin, may mediate the process of long-term memory storage and plasticity by generating neuronal conditions that favor these processes. To study this potential relationship, a single model in which memory, sleep, and epilepsy can be simultaneously observed is of necessity. Rodent models of epilepsy appear to fulfill this requirement. Not only do rodents express both sleep spindles and seizure-induced sleep disruptions, but they also allow researchers to invasively study neurobiological processes both pre- and post- epileptic onset via the artificial induction of epilepsy (a practice that cannot be carried out in human subjects). However, the degree to which sleep architecture differs between rodents and humans makes direct comparisons between the two challenging. This review addresses these challenges and concludes that rodent sleep studies are useful in observing the functional roles of sleep and how they are affected by epilepsy.

The Human Connectome Project: A retrospective.

The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the "WU-Minn-Ox" HCP consortium centered at Washington University, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image reconstruction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the ConnectomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The "HCP-style" neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium.

Effects of age of onset and medication on cognitive performance and quality of life in patients with epilepsy.

Previous research shows that earlier age of onset of epilepsy and larger antiepileptic drug (AED) load are related to cognitive impairment and lower quality of life in patients with epilepsy. However, there has been a discrepancy in the specific cognitive domains that are affected and whether AED load is a significant contributor to the cognitive impairment. This study aimed to examine (a) the specific cognitive domains that are affected by age of epilepsy onset and (b) the effects of AED treatment and age of onset on cognition and quality of life. Participant data included scores on (1) the Wisconsin Card Sorting Test (WCST), (2) Digit Span subtest of the Wechsler Adult Intelligence Scale - Fourth Edition (WAIS-IV), (3) Test of Everyday Attention (TEA), (4) Brief Visuospatial Memory Test (BVMT), (5) Quality of Life in Epilepsy (QOLIE-31), (6) Beck Depression Inventory (BDI-2), and (7) a medical record review for drug treatment information. Earlier age of epilepsy onset predicted lower auditory attention span and working memory as assessed by digit span forward (DSF) and digit span backward (DSB). Additionally, larger AED load predicted lower visuospatial memory as assessed by BVMT-Delayed Recall (BVMT-DR). No relationship between either age of onset or AED load and quality of life in epilepsy was found. However, depression was highly correlated with quality of life. These results highlight the need to balance epilepsy control and AED effects, especially in early-onset epilepsy, and to gain awareness of the specific cognitive domains affected by epilepsy variables to effectively monitor and treat it.

ConnectomeDB--Sharing human brain connectivity data.

ConnectomeDB is a database for housing and disseminating data about human brain structure, function, and connectivity, along with associated behavioral and demographic data. It is the main archive and dissemination platform for data collected under the WU-Minn consortium Human Connectome Project. Additional connectome-style study data is and will be made available in the database under current and future projects, including the Connectome Coordination Facility. The database currently includes multiple modalities of magnetic resonance imaging (MRI) and magnetoencephalograpy (MEG) data along with associated behavioral data. MRI modalities include structural, task, resting state and diffusion. MEG modalities include resting state and task. Imaging data includes unprocessed, minimally preprocessed and analysis data. Imaging data and much of the behavioral data are publicly available, subject to acceptance of data use terms, while access to some sensitive behavioral data is restricted to qualified investigators under a more stringent set of terms. ConnectomeDB is the public side of the WU-Minn HCP database platform. As such, it is geared towards public distribution, with a web-based user interface designed to guide users to the optimal set of data for their needs and a robust backend mechanism based on the commercial Aspera fasp service to enable high speed downloads. HCP data is also available via direct shipment of hard drives and Amazon S3.

Gibbs distribution for statistical analysis of graphical data with a sample application to fcMRI brain images.

This paper develops object-oriented data analysis (OODA) statistical methods that are novel and complementary to existing methods of analysis of human brain scan connectomes, defined as graphs representing brain anatomical or functional connectivity. OODA is an emerging field where classical statistical approaches (e.g., hypothesis testing, regression, estimation, and confidence intervals) are applied to data objects such as graphs or functions. By analyzing data objects directly we avoid loss of information that occurs when data objects are transformed into numerical summary statistics. By providing statistical tools that analyze sets of connectomes without loss of information, new insights into neurology and medicine may be achieved. In this paper we derive the formula for statistical model fitting, regression, and mixture models; test their performance in simulation experiments; and apply them to connectomes from fMRI brain scans collected during a serial reaction time task study. Software for fitting graphical object-oriented data analysis is provided.

Resting-state Functional Magnetic Resonance Imaging Correlates of Sevoflurane-induced Unconsciousness.

BACKGROUND: Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been used to study the effects of anesthetic agents on correlated intrinsic neural activity. Previous studies have focused primarily on intravenous agents. The authors studied the effects of sevoflurane, an inhaled anesthetic. METHODS: Resting-state BOLD fMRI was acquired from 10 subjects before sedation and from 9 subjects rendered unresponsive by 1.2% sevoflurane. The fMRI data were analyzed taking particular care to minimize the impact of artifact generated by head motion. RESULTS: BOLD correlations were specifically weaker within the default mode network and ventral attention network during sevoflurane-induced unconsciousness, especially between anterior and posterior midline regions. Reduced functional connectivity between these same networks and the thalamus was also spatially localized to the midline frontal regions. The amplitude of BOLD signal fluctuations was substantially reduced across all brain regions. The importance of censoring epochs contaminated by head motion was demonstrated by comparative analyses. CONCLUSIONS: Sevoflurane-induced unconsciousness is associated with both globally reduced BOLD signal amplitudes and selectively reduced functional connectivity within cortical networks associated with consciousness (default mode network) and orienting to salient external stimuli (ventral attention network). Scrupulous attention to minimizing the impact of head motion artifact is critical in fMRI studies using anesthetic agents.

Allodynia and descending pain modulation in migraine: a resting state functional connectivity analysis.

OBJECTIVE: Most migraineurs develop cutaneous allodynia during migraines, and many have cutaneous sensitization between attacks. Atypical pain modulation via the descending pain system may contribute to this sensitization and allodynia. The objective of this study was to test the hypothesis that compared with non-allodynic migraineurs, allodynic migraineurs have atypical periaqueductal gray (PAG) and nucleus cuneiformis (NCF) resting-state functional connectivity (rs-fc) with other pain processing regions. DESIGN: Ten minutes resting-state blood-oxygen-level-dependent data were collected from 38 adult migraineurs and 20 controls. Seed-based analyses compared whole-brain rs-fc with PAG and with NCF in migraineurs with severe ictal allodynia (N = 8) to migraineurs with no ictal allodynia (N = 8). Correlations between the strength of functional connections that differed between severely allodynic and non-allodynic migraineurs with allodynia severity were determined for all migraineurs (N = 38). PAG and NCF rs-fc in all migraineurs was compared with rs-fc in controls. RESULTS: Migraineurs with severe allodynia had stronger PAG and NCF rs-fc to other brainstem, thalamic, insula and cerebellar regions that participate in discriminative pain processing, as well as to frontal and temporal regions implicated in higher order pain modulation. Evidence that these rs-fc differences were specific for allodynia included: 1) strong correlations between some rs-fc strengths and allodynia severity among all migraineurs; and 2) absence of overlap when comparing rs-fc differences in severely allodynic vs non-allodynic migraineurs with those in all migraineurs vs controls. CONCLUSION: Atypical rs-fc of brainstem descending modulatory pain regions with other brainstem and higher order pain-modulating regions is associated with migraine-related allodynia.

A Systematic Review over the Effect of Early Infant Diet on Neurodevelopment: Insights from Neuroimaging.

The optimization of infant neuronal development through nutrition is an increasingly studied area. While human milk consumption during infancy is thought to give a slight cognitive advantage throughout early childhood in comparison to commercial formula, the biological underpinnings of this process are less well-known and debated in the literature. This systematic review seeks to quantitatively analyze whether early diet affects infant neurodevelopment as measured by various neuroimaging modalities and techniques. Results presented suggest that human milk does have a slight positive impact on the structural development of the infant brain-and that this impact is larger in preterm infants. Other diets with distinct macronutrient compositions were also considered, although these had more conflicting results.

Feasibility of regional center telehealth visits utilizing a rural research network in people with Parkinson's disease.

Background: Impaired motor and cognitive function can make travel cumbersome for People with Parkinson's disease (PwPD). Over 50% of PwPD cared for at the University of Arkansas for Medical Sciences (UAMS) Movement Disorders Clinic reside over 30 miles from Little Rock. Improving access to clinical care for PwPD is needed. Objective: To explore the feasibility of remote clinic-to-clinic telehealth research visits for evaluation of multi-modal function in PwPD. Methods: PwPD residing within 30 miles of a UAMS Regional health center were enrolled and clinic-to-clinic telehealth visits were performed. Motor and non-motor disease assessments were administered and quantified. Results were compared to participants who performed at-home telehealth visits using the same protocols during the height of the COVID pandemic. Results: Compared to the at-home telehealth visit group (n = 50), the participants from regional centers (n = 13) had similar age and disease duration, but greater disease severity with higher total Unified Parkinson's disease rating scale scores (Z = -2.218, p = 0.027) and lower Montreal Cognitive Assessment scores (Z = -3.350, p < 0.001). Regional center participants had lower incomes (Pearson's chi = 21.3, p < 0.001), higher costs to attend visits (Pearson's chi = 16.1, p = 0.003), and lived in more socioeconomically disadvantaged neighborhoods (Z = -3.120, p = 0.002). Prior research participation was lower in the regional center group (Pearson's chi = 4.5, p = 0.034) but both groups indicated interest in future research participation. Conclusions: Regional center research visits in PwPD in medically underserved areas are feasible and could help improve access to care and research participation in these traditionally underrepresented populations.

A network correspondence toolbox for quantitative evaluation of novel neuroimaging results.

Decades of neuroscience research has shown that macroscale brain dynamics can be reliably decomposed into a subset of large-scale functional networks, but the specific spatial topographies of these networks and the names used to describe them can vary across studies. Such discordance has hampered interpretation and convergence of research findings across the field. To address this problem, we have developed the Network Correspondence Toolbox (NCT) to permit researchers to examine and report spatial correspondence between their novel neuroimaging results and sixteen widely used functional brain atlases, consistent with recommended reporting standards developed by the Organization for Human Brain Mapping. The atlases included in the toolbox show some topographical convergence for specific networks, such as those labeled as default or visual. Network naming varies across atlases, particularly for networks spanning frontoparietal association cortices. For this reason, quantitative comparison with multiple atlases is recommended to benchmark novel neuroimaging findings. We provide several exemplar demonstrations using the Human Connectome Project task fMRI results and UK Biobank independent component analysis maps to illustrate how researchers can use the NCT to report their own findings through quantitative evaluation against multiple published atlases. The NCT provides a convenient means for computing Dice coefficients with spin test permutations to determine the magnitude and statistical significance of correspondence among user-defined maps and existing atlas labels. The NCT also includes functionality to incorporate additional atlases in the future. The adoption of the NCT will make it easier for network neuroscience researchers to report their findings in a standardized manner, thus aiding reproducibility and facilitating comparisons between studies to produce interdisciplinary insights.

Atypical resting-state functional connectivity of affective pain regions in chronic migraine.

OBJECTIVE: Chronic migraineurs (CM) have painful intolerances to somatosensory, visual, olfactory, and auditory stimuli during and between migraine attacks. These intolerances are suggestive of atypical affective responses to potentially noxious stimuli. We hypothesized that atypical resting-state functional connectivity (rs-fc) of affective pain-processing brain regions may associate with these intolerances. This study compared rs-fc of affective pain-processing regions in CM with controls. METHODS: Twelve minutes of resting-state blood oxygenation level-dependent data were collected from 20 interictal adult CM and 20 controls. Rs-fc between 5 affective regions (anterior cingulate cortex, right/left anterior insula, and right/left amygdala) with the rest of the brain was determined. Functional connections consistently differing between CM and controls were identified using summary analyses. Correlations between number of migraine years and the strengths of functional connections that consistently differed between CM and controls were calculated. RESULTS: Functional connections with affective pain regions that differed in CM and controls included regions in anterior insula, amygdala, pulvinar, mediodorsal thalamus, middle temporal cortex, and periaqueductal gray. There were significant correlations between the number of years with CM and functional connectivity strength between the anterior insula with mediodorsal thalamus and anterior insula with periaqueductal gray. CONCLUSION: CM is associated with interictal atypical rs-fc of affective pain regions with pain-facilitating and pain-inhibiting regions that participate in sensory-discriminative, cognitive, and integrative domains of the pain experience. Atypical rs-fc with affective pain regions may relate to aberrant affective pain processing and atypical affective responses to painful stimuli characteristic of CM.

Effects of Early Nutrition Factors on Baseline Neurodevelopment during the First 6 Months of Life: An EEG Study.

Throughout infancy, the brain undergoes rapid changes in structure and function that are sensitive to environmental influences, such as diet. Breastfed (BF) infants score higher on cognitive tests throughout infancy and into adolescence than formula fed (FF) infants, and these differences in neurocognitive development are reflected in higher concentrations of white and grey matter as measured by MRI. To further explore the effect diet has on cognitive development, electroencephalography (EEG) is used as a direct measure of neuronal activity and to assess specific frequency bands associated with cognitive processes. Task-free baseline EEGs were collected from infants fed with human milk (BF), dairy-based formula (MF), or soy-based formula (SF) at 2, 3, 4, 5, and 6 months of age to explore differences in frequency bands in both sensor and source space. Significant global differences in sensor space were seen in beta and gamma bands between BF and SF groups at ages 2 and 6 months, and these differences were further observed through volumetric modeling in source space. We conclude that BF infants exhibit earlier brain maturation reflected in greater power spectral density in these frequency bands.

Development and implementation of the frog-in-maze game to study upper limb movement in people with Parkinson's disease.

Upper-limb bradykinesia occurs early in Parkinson's disease (PD) and bradykinesia is required for diagnosis. Our goal was to develop, implement and validate a game "walking" a frog through a maze using bimanual, alternating finger-tapping movements to provide a salient, objective, and remotely monitorable method of tracking disease progression and response to therapy in PD. Twenty-five people with PD and 16 people without PD participated. Responses on 5 different mazes were quantified and compared to spatiotemporal gait parameters and standard disease metrics in these participants. Intertap interval (ITI) on maze 2 & 3, which included turns, was strongly inversely related to stride-length and stride-velocity and directly related to motor UPDRS scores. Levodopa decreased ITI, except in maze 4. PD participants with freezing of gait had longer ITI on all mazes. The responses quantified on maze 2 & 3 were related to disease severity and gait stride-length, were levodopa responsive, and were worse in people with freezing of gait, suggesting that these mazes could be used to quantify motor dysfunction in PD. Programming our frog-in-maze game onto a remotely distributable platform could provide a tool to monitor disease progression and therapeutic response in people with PD, including during clinical trials.

Impact of feeding habits on the development of language-specific processing of phonemes in brain: An event-related potentials study.

Introduction: Infancy is a stage characterized by multiple brain and cognitive changes. In a short time, infants must consolidate a new brain network and develop two important properties for speech comprehension: phonemic normalization and categorical perception. Recent studies have described diet as an essential factor in normal language development, reporting that breastfed infants show an earlier brain maturity and thus a faster cognitive development. Few studies have described a long-term effect of diet on phonological perception. Methods: To explore that effect, we compared the event-related potentials (ERPs) collected during an oddball paradigm (frequent /pa/80%, deviant/ba/20%) of infants fed with breast milk (BF), cow-milk-based formula (MF), and soy-based formula (SF), which were assessed at 3, 6, 9, 12, and 24 months of age [Mean across all age groups: 127 BF infants, Mean (M) 39.6 gestation weeks; 121 MF infants, M = 39.16 gestation weeks; 116 SF infants, M = 39.16 gestation weeks]. Results: Behavioral differences between dietary groups in acoustic comprehension were observed at 24-months of age. The BF group displayed greater scores than the MF and SF groups. In phonological discrimination task, the ERPs analyses showed that SF group had an electrophysiological pattern associated with difficulties in phonological-stimulus awareness [mismatch negativity (MMN)-2 latency in frontal left regions of interest (ROI) and longer MMN-2 latency in temporal right ROI] and less brain maturity than BF and MF groups. The SF group displayed more right-lateralized brain recruitment in phonological processing at 12-months old. Discussion: We conclude that using soy-based formula in a prolonged and frequent manner might trigger a language development different from that observed in the BF or MF groups. The soy-based formula's composition might affect frontal left-brain area development, which is a nodal brain region in phonological-stimuli awareness.

Gait Declines Differentially in, and Improves Prediction of, People with Parkinson's Disease Converting to a Freezing of Gait Phenotype.

BACKGROUND: Freezing of gait (FOG) is a debilitating, variably expressed motor symptom in people with Parkinson's disease (PwPD) with limited treatments. OBJECTIVE: To determine if the rate of progression in spatiotemporal gait parameters in people converting from a noFOG to a FOG phenotype (FOGConv) was faster than non-convertors, and determine if gait parameters can help predict this conversion. METHODS: PwPD were objectively monitored longitudinally, approximately every 6 months. Non-motor assessments were performed at the initial visit. Steady-state gait in the levodopa ON-state was collected using a gait mat (Protokinetics) at each visit. The rate of progression in 8 spatiotemporal gait parameters was calculated. FOG convertors (FOGConv) were classified if they did not have FOG at initial visit and developed FOG at a subsequent visit. RESULTS: Thirty freezers (FOG) and 30 non-freezers were monitored an average of 3.5 years, with 10 non-freezers developing FOG (FOGConv). FOGConv and FOG had faster decline in mean stride-length, swing-phase-percent, and increase in mean total-double-support percent, coefficient of variability (CV) foot-strike-length and CV swing-phase-percent than the remaining non-freezers (noFOG). On univariate modeling, progression rates of mean stride-length, stride-velocity, swing-phase-percent, total-double-support-percent and of CV swing-phase-percent had high discriminative power (AUC > 0.83) for classification of the FOGConv and noFOG groups. CONCLUSION: FOGConv had a faster temporal decline in objectively quantified gait than noFOG, and progression rates of spatiotemporal gait parameters were more predictive of FOG phenotype conversion than initial (static) parameters Objectively monitoring gait in disease prediction models may help define FOG prone groups for testing putative treatments.

A machine learning method to process voice samples for identification of Parkinson's disease.

Machine learning approaches have been used for the automatic detection of Parkinson's disease with voice recordings being the most used data type due to the simple and non-invasive nature of acquiring such data. Although voice recordings captured via telephone or mobile devices allow much easier and wider access for data collection, current conflicting performance results limit their clinical applicability. This study has two novel contributions. First, we show the reliability of personal telephone-collected voice recordings of the sustained vowel /a/ in natural settings by collecting samples from 50 people with specialist-diagnosed Parkinson's disease and 50 healthy controls and applying machine learning classification with voice features related to phonation. Second, we utilize a novel application of a pre-trained convolutional neural network (Inception V3) with transfer learning to analyze the spectrograms of the sustained vowel from these samples. This approach considers speech intensity estimates across time and frequency scales rather than collapsing measurements across time. We show the superiority of our deep learning model for the task of classifying people with Parkinson's disease as distinct from healthy controls.

Analysis of Caregiver Burden Expressed in Social Media Discussions.

Almost 40% of US adults provide informal caregiving, yet research gaps remain around what burdens affect informal caregivers. This study uses a novel social media site, Reddit, to mine and better understand what online communities focus on as their caregiving burdens. These forums were accessed using an application programming interface, a machine learning classifier was developed to remove low information posts, and topic modeling was applied to the corpus. An expert panel summarized the forums' themes into ten categories. The largest theme extracted from Reddit's forums discussed the personal emotional toll of being a caregiver. This was followed by logistic issues while caregiving and caring for parents who have cancer. Smaller themes included approaches to end-of-life care, physical equipment needs when caregiving, and the use of wearables or technology to help monitor care recipients. The platform often discusses caregiving for parents which may reflect the age of Reddit's users. This study confirms that Reddit forums are used for caregivers to discuss the burdens associated with their role and the types of stress that can result from informal caregiving.

Controversies and progress on standardization of large-scale brain network nomenclature.

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.

Dissociated mean and functional connectivity BOLD signals in visual cortex during eyes closed and fixation.

We investigated the effects of resting state type on blood oxygen level-dependent (BOLD) signal and functional connectivity in two paradigms: participants either alternated between fixation and eyes closed or maintained fixation or eyes closed throughout each scan. The BOLD signal and functional connectivity of lower and higher tiers of the visual cortical hierarchy were found to be differentially modulated during eyes closed versus fixation. Fixation was associated with greater mean BOLD signals in primary visual cortex and lower mean BOLD signals in extrastriate visual areas than periods of eyes closed. In addition, analysis of thalamocortical functional connectivity during scans in which participants maintained fixation showed synchronized BOLD fluctuations between those thalamic nuclei whose mean BOLD signal was systematically modulated during alternating epochs of eyes closed and fixation, primary visual cortex and the attention network, while during eyes closed negatively correlated fluctuations were seen between the same thalamic nuclei and extrastriate visual areas. Finally, in all visual areas the amplitude of spontaneous BOLD fluctuations was greater during eyes closed than during fixation. The dissociation between early and late tiers of visual cortex, which characterizes both mean and functionally connected components of the BOLD signal, may depend on the reorganization of thalamocortical networks. Since dissociated changes in local blood flow also characterize transitions between different stages of sleep and wakefulness (Braun AR, Balkin TJ, Wesenten NJ, Gwadry F, Carson RE, Varga M, Baldwin P, Belenky G, Herscovitch P. Science 279: 91-95, 1998), our results suggest that dissociated endogenous neural activity in primary and extrastriate cortex may represent a general aspect of brain function.