Bedside tracking of functional autonomic age in preterm infants.

BACKGROUND: Preterm birth predisposes infants to adverse outcomes that, without early intervention, impacts their long-term health. To assist bedside monitoring, we developed a tool to track the autonomic maturation of the preterm by assessing heart rate variability (HRV) changes during intensive care. METHODS: Electrocardiogram (ECG) recordings were longitudinally recorded in 67 infants (26-38 weeks postmenstrual age (PMA)). Supervised machine learning was used to generate a functional autonomic age (FAA), by combining 50 computed HRV features from successive 5-minute ECG epochs (median of 23 epochs per infant). Performance of the FAA was assessed by correlation to PMA, clinical outcomes and the infant's functional brain age (FBA), an index of maturation derived from the electroencephalogram. RESULTS: The FAA was strongly correlated to PMA (r = 0.86, 95% CI: 0.83-0.93) with a mean absolute error (MAE) of 1.66 weeks and also accurately estimated FBA (MAE = 1.58 weeks, n = 54 infants). The relationship between PMA and FAA was not confounded by neurodevelopmental outcome (p = 0.18, n = 45), sex (p = 0.88, n = 56), patent ductus arteriosus (p = 0.08, n = 56), IVH (p = 0.63, n = 56) or body weight at birth (p = 0.95, n = 56). CONCLUSIONS: The FAA, an index derived from the ubiquitous ECG signal, offers direct avenues towards estimating autonomic maturation at the bedside during intensive care monitoring. IMPACT: The development of a tool to track functional autonomic age in preterm infants based on heart rate variability features in the electrocardiogram provides a rapid and specialized view of autonomic maturation at the bedside. Functional autonomic age is linked closely to postmenstrual age and central nervous system function response, as determined by its relationship to functional brain age from the electroencephalogram. Tracking functional autonomic age during neonatal intensive care unit monitoring offers a unique insight into cardiovascular health in infants born extremely preterm and their maturational trajectories to term age.

Microbiota links to neural dynamics supporting threat processing.

There is growing recognition that the composition of the gut microbiota influences behaviour, including responses to threat. The cognitive-interoceptive appraisal of threat-related stimuli relies on dynamic neural computations between the anterior insular (AIC) and the dorsal anterior cingulate (dACC) cortices. If, to what extent, and how microbial consortia influence the activity of this cortical threat processing circuitry is unclear. We addressed this question by combining a threat processing task, neuroimaging, 16S rRNA profiling and computational modelling in healthy participants. Results showed interactions between high-level ecological indices with threat-related AIC-dACC neural dynamics. At finer taxonomic resolutions, the abundance of Ruminococcus was differentially linked to connectivity between, and activity within the AIC and dACC during threat updating. Functional inference analysis provides a strong rationale to motivate future investigations of microbiota-derived metabolites in the observed relationship with threat-related brain processes.

Modulating functional connectivity with non-invasive brain stimulation for the investigation and alleviation of age-associated declines in response inhibition: A narrative review.

Response inhibition, the ability to withhold a dominant and prepotent response following a change in circumstance or sensory stimuli, declines with advancing age. While non-invasive brain stimulation (NiBS) has shown promise in alleviating some cognitive and motor functions in healthy older individuals, NiBS research focusing on response inhibition has mostly been conducted on younger adults. These extant studies have primarily focused on modulating the activity of distinct neural regions known to be critical for response inhibition, including the right inferior frontal gyrus (rIFG) and the pre-supplementary motor area (pre-SMA). However, given that changes in structural and functional connectivity have been associated with healthy aging, this review proposes that NiBS protocols aimed at modulating the functional connectivity between the rIFG and pre-SMA may be the most efficacious approach to investigate-and perhaps even alleviate-age-related deficits in inhibitory control.

Effective assessments of electroencephalography during stroke recovery: contemporary approaches and considerations.

Stroke is one of the leading causes of permanent disability worldwide, relying conventionally on extended periods of physiotherapy to recover functional ability. While neuroimaging techniques and emerging neurorehabilitation paradigms have advanced our understanding of pathophysiological mechanisms underlying stroke, recent evidence has renewed focus on quantifying features of cortical activity present in electroencephalography recordings to greatly enhance our understanding of stroke treatment and recovery. This Neuro Forum article reviews these key advances and discusses the importance of quantifying electroencephalography in future assessments of stroke survivors.

Cortical burst dynamics predict clinical outcome early in extremely preterm infants.

Intermittent bursts of electrical activity are a ubiquitous signature of very early brain activity. Previous studies have largely focused on assessing the amplitudes of these transient cortical bursts or the intervals between them. Recent advances in basic neuroscience have identified the presence of scale-free 'avalanche' processes in bursting patterns of cortical activity in other clinical contexts. Here, we hypothesize that cortical bursts in human preterm infants also exhibit scale-free properties, providing new insights into the nature, temporal evolution, and prognostic value of spontaneous brain activity in the days immediately following preterm birth. We examined electroencephalographic recordings from 43 extremely preterm infants (gestational age 22-28 weeks) and demonstrated that their cortical bursts exhibit scale-free properties as early as 12 h after birth. The scaling relationships of cortical bursts correlate significantly with later mental development-particularly within the first 12 h of life. These findings show that early preterm brain activity is characterized by scale-free dynamics which carry developmental significance, hence offering novel means for rapid and early clinical prediction of neurodevelopmental outcomes.

Spin-glass behavior and pyroelectric anomalies in a new lithium-based oxide, Li3FeRuO5.

The results of dc and ac magnetization, heat capacity, (57)Fe Mössbauer spectroscopy, dielectric, pyroelectric current and isothermal magneto-capacitance measurements of a recently reported lithium-rich layered oxide, Li3FeRuO5, related to LiCoO2-type (rhombohedral, space group R3[combining macron]m), are presented. The results reveal that the compound undergoes spin-glass freezing at 15 K. There is a peak around 34 K in pyroelectric data, which cannot be attributed to ferroelectricity, but to the phenomenon of thermally stimulated depolarization current. As revealed by magnetocapacitance data above and below the magnetic ordering temperature, magnetic and electric dipoles appear to be coupled, thereby offering evidence for magnetodielectric coupling.

Scale-free bursting in human cortex following hypoxia at birth.

The human brain is fragile in the face of oxygen deprivation. Even a brief interruption of metabolic supply at birth challenges an otherwise healthy neonatal cortex, leading to a cascade of homeostatic responses. During recovery from hypoxia, cortical activity exhibits a period of highly irregular electrical fluctuations known as burst suppression. Here we show that these bursts have fractal properties, with power-law scaling of burst sizes across a remarkable 5 orders of magnitude and a scale-free relationship between burst sizes and durations. Although burst waveforms vary greatly, their average shape converges to a simple form that is asymmetric at long time scales. Using a simple computational model, we argue that this asymmetry reflects activity-dependent changes in the excitatory-inhibitory balance of cortical neurons. Bursts become more symmetric following the resumption of normal activity, with a corresponding reorganization of burst scaling relationships. These findings place burst suppression in the broad class of scale-free physical processes termed crackling noise and suggest that the resumption of healthy activity reflects a fundamental reorganization in the relationship between neuronal activity and its underlying metabolic constraints.

Early Detection of Preterm Intraventricular Hemorrhage From Clinical Electroencephalography.

OBJECTIVES: Intraventricular hemorrhage is a common neurologic complication of extremely preterm birth and leads to lifelong neurodevelopmental disabilities. Early bedside detection of intraventricular hemorrhage is crucial to enabling timely interventions. We sought to detect early markers of brain activity that preempt the occurrence of intraventricular hemorrhage in extremely preterm infants during the first postnatal days. DESIGN: Cross-sectional study. SETTING: Level III neonatal ICU. PATIENTS: Twenty-five extremely preterm infants (22-28 wk gestational age). MEASUREMENTS AND MAIN RESULTS: We quantitatively assessed electroencephalography in the first 72 hours of postnatal life, focusing on the electrical burst activity of the preterm. Cranial ultrasound was performed on day 1 (0-24 hr) and day 3 (48-72 hr). Outcomes were categorized into three classes: 1) no intraventricular hemorrhage (grade 0); 2) mild-moderate intraventricular hemorrhage (grades 1-2, i.e., germinal matrix hemorrhages or intraventricular hemorrhage without ventricular dilatation, respectively); and 3) severe intraventricular hemorrhage (grades 3-4, i.e., intraventricular hemorrhage with ventricular dilatation or intraparenchymal involvement). Quantitative assessment of electroencephalography burst shapes was used to preempt the occurrence and severity of intraventricular hemorrhage as detected by ultrasound. The shapes of electroencephalography bursts found in the intraventricular hemorrhage infants were significantly sharper (F = 13.78; p < 0.0001) and less symmetric (F = 6.91; p < 0.015) than in preterm infants without intraventricular hemorrhage. Diagnostic discrimination of intraventricular hemorrhage infants using measures of burst symmetry and sharpness yielded high true-positive rates (82% and 88%, respectively) and low false-positive rates (19% and 8%). Conventional electroencephalography measures of interburst intervals and burst counts were not significantly associated with intraventricular hemorrhage. CONCLUSIONS: Detection of intraventricular hemorrhage during the first postnatal days is possible from bedside measures of brain activity prior to ultrasound confirmation of intraventricular hemorrhage. Significantly, our novel automated assessment of electroencephalography preempts the occurrence of intraventricular hemorrhage in the extremely preterm. Early bedside detection of intraventricular hemorrhage holds promise for advancing individual care, targeted therapeutic trials, and understanding mechanisms of brain injury in neonates.

Attention Please! Unravelling the Link Between Brain Network Connectivity and Cognitive Attention Following Acquired Brain Injury: A Systematic Review of Structural and Functional Measures.

Traumatic brain injury (TBI) and stroke are the most common causes of acquired brain injury (ABI), annually affecting 69 million and 15 million people, respectively. Following ABI, the relationship between brain network disruption and common cognitive issues including attention dysfunction is heterogenous. Using PRISMA guidelines, we systematically reviewed 43 studies published by February 2023 that reported correlations between attention and connectivity. Across all ages and stages of recovery, following TBI, greater attention was associated with greater structural efficiency within/between executive control network (ECN), salience network (SN), and default mode network (DMN) and greater functional connectivity (fc) within/between ECN and DMN, indicating DMN interference. Following stroke, greater attention was associated with greater structural connectivity (sc) within ECN; or greater fc within the dorsal attention network (DAN). In childhood ABI populations, decreases in structural network segregation were associated with greater attention. Longitudinal recovery from TBI was associated with normalization of DMN activity, and in stroke, normalization of DMN and DAN activity. Results improve clinical understanding of attention-related connectivity changes after ABI. Recommendations for future research include increased use of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to measure connectivity at the point of care, standardized attention and connectivity outcome measures and analysis pipelines, detailed reporting of patient symptomatology, and casual analysis of attention-related connectivity using brain stimulation.

A growth chart of brain function from infancy to adolescence based on EEG.

BACKGROUND: In children, objective, quantitative tools that determine functional neurodevelopment are scarce and rarely scalable for clinical use. Direct recordings of cortical activity using routinely acquired electroencephalography (EEG) offer reliable measures of brain function. METHODS: We developed and validated a measure of functional brain age (FBA) using a residual neural network-based interpretation of the paediatric EEG. In this cross-sectional study, we included 1056 children with typical development ranging in age from 1 month to 18 years. We analysed a 10- to 15-min segment of 18-channel EEG recorded during light sleep (N1 and N2 states). FINDINGS: The FBA had a weighted mean absolute error (wMAE) of 0.85 years (95% CI: 0.69-1.02; n = 1056). A two-channel version of the FBA had a wMAE of 1.51 years (95% CI: 1.30-1.73; n = 1056) and was validated on an independent set of EEG recordings (wMAE = 2.27 years, 95% CI: 1.90-2.65; n = 723). Group-level maturational delays were also detected in a small cohort of children with Trisomy 21 (Cohen's d = 0.36, p = 0.028). INTERPRETATION: A FBA, based on EEG, is an accurate, practical and scalable automated tool to track brain function maturation throughout childhood with accuracy comparable to widely used physical growth charts. FUNDING: This research was supported by the National Health and Medical Research Council, Australia, Helsinki University Diagnostic Center Research Funds, Finnish Academy, Finnish Paediatric Foundation, and Sigrid Juselius Foundation.

Conducting shorter VEP tests to estimate visual acuity via assessment of SNR.

INTRODUCTION: The estimation of visual acuity (VA) via visual evoked potentials (VEP) is a valuable measure for all preverbal and non-verbal subjects whether adults or children. The aim of this study is to introduce a novel technique of VEP acquisition based on estimates of signal-to-noise ratio (SNR) and comparison to a predefined detection threshold. We aim to demonstrate the reduction in total study time without compromising the accuracy of the VEP-determined acuity estimate. METHODS: The VEP-determined acuity of twelve normal subjects was assessed via a spatial frequency (SF) sweep. A pattern reversal checkerboard stimulus utilised SFs ranging from 0.1 to 28 cycles per degree (cpd). Using linear extrapolation and Bland-Altman analysis, VEP-acquired acuity was compared to a conventional Snellen Acuity measurement. An SNR test, Fsp, assessed signal quality to determine the minimum amount of sweep data required for VEP-based VA estimation. RESULTS: VEP acuity estimates correlated strongly (r2=0.91, SD=0.06), leading to a VA limit via extrapolation. Bland-Altman analysis revealed agreement between tests is statistically valid (95% CI -0.11 to 0.42 logMAR). The Fsp statistic indicated SFs 1.3-3.6 cpd yielded Fsp>3.1 within 15 s of acquisition with frequencies>3.6 cpd being sub-threshold. The Kruskal-Wallis statistic compared final Fsp values for SFs as groups, where F=208.82 ranking each frequency, with frequencies>7.2 cpd ranking lowest. DISCUSSION: The Fsp as an SNR measurement shows that rapid, quality-driven clinical tests for VEP-based acuity estimates can be conducted without compromising accuracy.

Mechanisms underlying pathological cortical bursts during metabolic depletion.

Cortical activity depends upon a continuous supply of oxygen and other metabolic resources. Perinatal disruption of oxygen availability is a common clinical scenario in neonatal intensive care units, and a leading cause of lifelong disability. Pathological patterns of brain activity including burst suppression and seizures are a hallmark of the recovery period, yet the mechanisms by which these patterns arise remain poorly understood. Here, we use computational modeling of coupled metabolic-neuronal activity to explore the mechanisms by which oxygen depletion generates pathological brain activity. We find that restricting oxygen supply drives transitions from normal activity to several pathological activity patterns (isoelectric, burst suppression, and seizures), depending on the potassium supply. Trajectories through parameter space track key features of clinical electrophysiology recordings and reveal how infants with good recovery outcomes track toward normal parameter values, whereas the parameter values for infants with poor outcomes dwell around the pathological values. These findings open avenues for studying and monitoring the metabolically challenged infant brain, and deepen our understanding of the link between neuronal and metabolic activity.

Optimization of time series features to estimate brain age in children from electroencephalography.

Functional brain age measures in children, derived from the electroencephalogram (EEG), offer direct and objective measures in assessing neurodevelopmental status. Here we explored the effectiveness of 32 preselected 'handcrafted' EEG features in predicting brain age in children. These features were benchmarked against a large library of highly comparative multivariate time series features (>7000 features). Results showed that age predictors based on handcrafted EEG features consistently outperformed a generic set of time series features. These findings suggest that optimization of brain age estimation in children benefits from careful preselection of EEG features that are related to age and neurodevelopmental trajectory. This approach shows potential for clinical translation in the future.Clinical Relevance-Handcrafted EEG features provide an accurate functional neurodevelopmental biomarker that tracks brain function maturity in children.

Modulations of right hemisphere connectivity in young children relates to the perception of spoken words.

The early school years shape a young brain's capability to comprehend and contextualize words within milliseconds of exposure. Parsing word sounds (phonological interpretation) and word recognition (enabling semantic interpretation) are integral to this process. Yet little is known about the causal mechanisms of cortical activity during these early developmental stages. In this study, we aimed to explore these causal mechanisms via dynamic causal modelling of event-related potentials (ERPs) acquired from 30 typically developing children (ages 6-8 years) as they completed a spoken word-picture matching task. Source reconstruction of high-density electroencephalography (128 channels) was used to ascertain differences in whole-brain cortical activity during semantically "congruent" and "incongruent" conditions. Source activations analyzed during the N400 ERP window identified significant regions-of-interest (pFWE<.05) localized primarily in the right hemisphere when contrasting congruent and incongruent word-picture stimuli. Dynamic causal models (DCMs) were tested on source activations in the fusiform gyrus (rFusi), inferior parietal lobule (rIPL), inferior temporal gyrus (rITG) and superior frontal gyrus (rSFG). DCM results indicated that a fully connected bidirectional model with self-(inhibiting) connections over rFusi, rIPL and rSFG provided the highest model evidence, based on exceedance probabilities derived from Bayesian statistical inferences. Connectivity parameters of rITG and rSFG regions from the winning DCM were negatively correlated with behavioural measures of receptive vocabulary and phonological memory (pFDR<.05), such that lower scores on these assessments corresponded with increased connectivity between temporal pole and anterior frontal regions. The findings suggest that children with lower language processing skills required increased recruitment of right hemisphere frontal/temporal areas during task performance.

Dorsal and Ventral Cortical Connectivity Is Mediated by the Inferior Frontal Gyrus During Facilitated Naming of Pictures.

Background: It is well recognized that semantic processing and auditory repetition facilitate subsequent naming of pictures. However, the neurocognitive mechanisms that underpin these facilitation effects remain unclear. Materials and Methods: The current study utilized a dynamic causal modeling (DCM) approach to examine high-density electroencephalographic (128-channel EEG) recordings and investigate connectivity modulations during facilitated naming of pictures in 18 healthy older adults (mean age 61.50 years). Source reconstruction of event-related potentials was performed in two specific time windows, (1) 150-250 msec and (2) 300-500 msec, to establish the timescale of significant cortical activations present during participation of semantic and phonological tasks. Hypothesis-driven DCM of source-activated regions was tested to ascertain which model most likely explained the semantic and phonological conditions, respectively. Results: DCM results indicated that a common cortical network comprising dorsal and ventral cortical connections best explained EEG task data derived from repetition and semantic tasks. For repetition (phonological) tasks, this model featured long feedback, bidirectional connections from inferior frontal gyrus (IFG) to occipitotemporal areas. Semantic tasks were most plausibly explained by a model that featured a self-inhibiting connection over the IFG only. Conclusions: Findings from this study reveal that a common cortical model comprising pathways that include dorsal and ventral regions is appropriate for characterizing EEG naming facilitation data, and that distinct cortical connections explain differences between semantic and auditory repetition processes. These models could be repurposed for naming facilitation paradigms in patients with language difficulties to optimize prediction and responsiveness to such paradigms. Impact statement The combination of semantic (word-level) and phonological (sound-level) processing in the cortex facilitates one of the most robust responses-the naming of pictures. Here, dynamic causal modeling of high-density electroencephalography during facilitated naming tasks revealed a model consisting of common dorsal and ventral connections that best explained response to semantic and phonological stimuli. Within this cortical network, phonological facilitation involved a long-range connection from inferior frontal gyrus (IFG) to occipitotemporal regions, whereas semantic facilitation contributed to self-inhibition of the IFG. The IFG is therefore a key region mediating cortical activity when switching between phonological and semantic conditions.

Focal neural perturbations reshape low-dimensional trajectories of brain activity supporting cognitive performance.

The emergence of distributed patterns of neural activity supporting brain functions and behavior can be understood by study of the brain's low-dimensional topology. Functional neuroimaging demonstrates that brain activity linked to adaptive behavior is constrained to low-dimensional manifolds. In human participants, we tested whether these low-dimensional constraints preserve working memory performance following local neuronal perturbations. We combined multi-session functional magnetic resonance imaging, non-invasive transcranial magnetic stimulation (TMS), and methods translated from the fields of complex systems and computational biology to assess the functional link between changes in local neural activity and the reshaping of task-related low dimensional trajectories of brain activity. We show that specific reconfigurations of low-dimensional trajectories of brain activity sustain effective working memory performance following TMS manipulation of local activity on, but not off, the space traversed by these trajectories. We highlight an association between the multi-scale changes in brain activity underpinning cognitive function.

Enhanced electrical resistance at the field-induced magnetic transitions in some non-stoichiometric and stoichiometric Tb-based ternary germanides.

We present the magnetic and transport behavior of some Tb compounds, namely TbIrGe(2), TbFe(0.4)Ge(2) and TbCo(0.4)Ge(2). The stoichiometric germanide TbIrGe(2) exhibits at least two distinct magnetic transitions in a close temperature interval around 10 K. Non-stoichiometric compounds, TbFe(0.4)Ge(2) and TbCo(0.4)Ge(2), undergo magnetic ordering around 17 and 19 K, respectively. The magnetic state of these compounds appears to be antiferromagnetic-like. Qualitatively there is a correlation between the field response of the magnetization (M), the magnetoresistance (MR) and the entropy change (ΔS) curve in all three compounds. That is, these Tb compounds exhibit a positive MR and ΔS beyond a magnetic field where M also shows a field-induced transition. On the basis of this correlation, we conclude that magnetic disorder/fluctuations beyond a critical field-a phenomenon called 'inverse metamagnetism'-rather than metamagnetism is induced in these compounds.

Neural Correlates of Sleep Recovery following Melatonin Treatment for Pediatric Concussion: A Randomized Controlled Trial.

Evidence-based treatments for children with persistent post-concussion symptoms (PPCS) are few and limited. Common PPCS complaints such as sleep disturbance and fatigue could be ameliorated via the supplementation of melatonin, which has significant neuroprotective and anti-inflammatory properties. This study aims to identify neural correlates of melatonin treatment with changes in sleep disturbances and clinical recovery in a pediatric cohort with PPCS. We examined structural and functional neuroimaging (fMRI) in 62 children with PPCS in a randomized, double-blind, placebo-controlled trial of 3 mg or 10 mg of melatonin (NCT01874847). The primary outcome was the total youth self-report Post-Concussion Symptom Inventory (PCSI) score after 28 days of treatment. Secondary outcomes included the change in the sleep domain PCSI score and sleep-wake behavior (assessed using wrist-worn actigraphy). Whole-brain analyses of (1) functional connectivity (FC) of resting-state fMRI, and (2) structural gray matter volumes via voxel-based morphometry were assessed immediately before and after melatonin treatment and compared with placebo to identify neural effects of melatonin treatment. Increased FC of posterior default mode network (DMN) regions with visual, somatosensory, and dorsal networks was detected in the melatonin groups over time. The FC increases also corresponded with reduced wake periods (r = -0.27, p = 0.01). Children who did not recover (n = 39) demonstrated significant FC increases within anterior DMN and limbic regions compared with those who did recover (i.e., PCSI scores returned to pre-injury level, n = 23) over time, (p = 0.026). Increases in GM volume within the posterior cingulate cortex were found to correlate with reduced wakefulness after sleep onset (r = -0.32, p = 0.001) and sleep symptom improvement (r = 0.29, p = 0.02). Although the melatonin treatment trial was negative and did not result in PPCS recovery (with or without sleep problems), the relationship between melatonin and improvement in sleep parameters was linked to changes in function-structure within and between brain regions interacting with the DMN.

Theta and gamma connectivity is linked with affective and cognitive symptoms in Parkinson's disease.

BACKGROUND: The progression of Parkinson's disease (PD) can often exacerbate symptoms of depression, anxiety, and/or cognitive impairment. In this study, we explore the possibility that multiple brain network responses are associated with symptoms of depression, anxiety and cognitive impairment in PD. This association is likely to provide insights into a single multivariate relationship, where common affective symptoms occurring in PD cohorts are related with alterations to electrophysiological response. METHODS: 70 PD patients and 21 healthy age-matched controls (HC) participated in a high-density electroencephalography (EEG) study. Functional connectivity differences between PD and HC groups of oscillatory activity at rest and during completion of an emotion-cognition task were examined to identify key brain oscillatory activities. A canonical correlation analysis (CCA) was applied to identify a putative multivariate relationship between connectivity patterns and affective symptoms in PD groups. RESULTS: A CCA analysis identified a single mode of co-variation linking theta and gamma connectivity with affective symptoms in PD groups. Increases in frontotemporal gamma, frontal and parietal theta connectivity were related with increased anxiety and cognitive impairment. Decreases in temporal region theta and frontoparietal gamma connectivity were associated with higher depression ratings and PD patient age. LIMITATIONS: This study only reports on optimal dosage of dopaminergic treatment ('on' state) in PD and did not investigate at "off" medication". CONCLUSIONS: Theta and gamma connectivity during rest and task-states are linked to affective and cognitive symptoms within fronto-temporo-parietal networks, suggesting a potential assessment avenue for understanding brain-behaviour associations in PD with electrophysiological task paradigms.