EEG functional connectivity, axon delays and white matter disease

Neuronal Coupling Modes Show Differential Development in the Early Cortical Activity Networks of Human Newborns

The third trimester is a critical period for the development of functional networks that support the lifelong neurocognitive performance, yet the emergence of neuronal coupling in these networks is poorly understood. Here, we used longitudinal high-density electroencephalographic recordings from preterm infants during the period from 33 to 45 weeks of conceptional age (CA) to characterize early spatiotemporal patterns in the development of local cortical function and the intrinsic coupling modes [ICMs; phase-phase (PPCs), amplitude-amplitude (AACs), and phase-amplitude correlations (PACs)]. Absolute local power showed a robust increase with CA across the full frequency spectrum, while local PACs showed sleep state-specific, biphasic development that peaked a few weeks before normal birth. AACs and distant PACs decreased globally at nearly all frequencies. In contrast, the PPCs showed frequency- and region-selective development, with an increase of coupling strength with CA between frontal, central, and occipital regions at low-delta and alpha frequencies together with a wider-spread decrease at other frequencies. Our findings together present the spectrally and spatially differential development of the distinct ICMs during the neonatal period and provide their developmental templates for future basic and clinical research.

Clinical and neuroradiographic features of fentanyl inhalation-induced leukoencephalopathy

A man in his late 40s with no known past medical history was unresponsive for an unknown period of time. Crushed pills and white residue were found on a nearby table. On presentation he was obtunded and unresponsive to verbal commands but withdrawing to painful stimuli. The initial urine drug screen was negative, but a urine fentanyl screen was subsequently positive with a level of 137.3 ng/mL. MRI of the brain showed reduced diffusivity and fluid attenuated inversion recovery (FLAIR) hyperintensity symmetrically in the bilateral supratentorial white matter, cerebellum and globus pallidus. Alternative diagnoses such as infection were considered, but ultimately the history and workup led to a diagnosis of fentanyl-induced leukoencephalopathy. Three days after admission the patient became able to track, respond to voice and follow basic one-step commands. The patient does not recall the mechanism of inhalation. While there are case reports of heroin-induced leukoencephalopathy following inhaled heroin use and many routes of fentanyl, this is the first reported case of a similar phenomenon due to fentanyl inhalation.

The effects of electroencephalography functional connectivity during emotional recognition among patients with major depressive disorder and healthy controls

BACKGROUND

The brain of major depressive disorder (MDD) is associated with altered functional connectivity (FC) compared to that of healthy individuals when processing positive and negative visual stimuli. Building upon alterations in brain connectivity, some researchers have employed electroencephalography (EEG) to study FC in MDD, aiming to enhance both diagnosis and treatment; however, the results have been inconsistent and the studies involving FC during emotional recognition are limited. This study aims to 1) investigate the effects of MDD on EEG patterns during visual emotional processing, 2) explore the therapeutic effects of antidepressant treatment on brain FC within the first week, and assess whether these effects can be predictive of treatment outcomes four weeks later, and 3) study baseline FC parameter biomarkers that can be used to predict treatment responsiveness in MDD patients.

METHODS

This clinical observational study recruited 38 healthy controls (HC) and 48 MDD patients. Patients underwent an EEG exam while looking at validated images of happy and sad faces at week 0 and 1. MDD patients were categorized into treatment responders and non-responders after 4 weeks of treatment. We conducted the FC analysis (node strength (NS), global efficiency (GE), and cluster coefficient (CC)) on HC and MDD patients using graph theoretical analysis. Multivariable linear regression was used to evaluate the influence of MDD on FC compared to HC, while controlling for confounding variables including age, gender, and academic degrees.

RESULTS

At week 0 and week 1, MDD patients revealed to have significant reductions in FC parameters (NS, GE and CC) compared to HC. When comparing MDD patients at week 1 post-antidepressant treatment and pre-treatment, no significant differences in FC changes were observed. Multivariable regression revealed a significant negative effect on FC of MDD. Compared to the treatment non-responsive group, the responsive group revealed a significantly higher FC in delta band frequency at baseline.

CONCLUSIONS

MDD patient group showed impaired FC during visual emotion-processing and we observed baseline FC parameters to be associated with treatment response at week 4. While signs of FC changes were observed in the brain after a week of treatment, it is possible that one week may still be insufficient to demonstrate significant alterations in the brain. Our results suggest the potential utilization of EEG-based FC as an indicative measure for predicting treatment response and monitoring treatment progress in MDD patients.

Development of the Alpha Rhythm Is Linked to Visual White Matter Pathways and Visual Detection Performance

Alpha is the strongest electrophysiological rhythm in awake humans at rest. Despite its predominance in the EEG signal, large variations can be observed in alpha properties during development, with an increase in alpha frequency over childhood and adulthood. Here, we tested the hypothesis that these changes in alpha rhythm are related to the maturation of visual white matter pathways. We capitalized on a large diffusion MRI (dMRI)-EEG dataset (dMRI n = 2,747, EEG n = 2,561) of children and adolescents of either sex (age range, 5-21 years old) and showed that maturation of the optic radiation specifically accounts for developmental changes of alpha frequency. Behavioral analyses also confirmed that variations of alpha frequency are related to maturational changes in visual perception. The present findings demonstrate the close link between developmental variations in white matter tissue properties, electrophysiological responses, and behavior.

In vivo marker of brainstem myelin is associated to quantitative sleep parameters in healthy young men

The regional integrity of brain subcortical structures has been implicated in sleep-wake regulation, however, their associations with sleep parameters remain largely unexplored. Here, we assessed association between quantitative Magnetic Resonance Imaging (qMRI)-derived marker of the myelin content of the brainstem and the variability in the sleep electrophysiology in a large sample of 18-to-31 years healthy young men (N = 321; ~ 22 years). Separate Generalized Additive Model for Location, Scale and Shape (GAMLSS) revealed that sleep onset latency and slow wave energy were significantly associated with MTsat estimates in the brainstem (pcorrected ≤ 0.03), with overall higher MTsat value associated with values reflecting better sleep quality. The association changed with age, however (MTsat-by-age interaction-pcorrected ≤ 0.03), with higher MTsat value linked to better values in the two sleep metrics in the younger individuals of our sample aged ~ 18 to 20 years. Similar associations were detected across different parts of the brainstem (pcorrected ≤ 0.03), suggesting that the overall maturation and integrity of the brainstem was associated with both sleep metrics. Our results suggest that myelination of the brainstem nuclei essential to regulation of sleep is associated with inter-individual differences in sleep characteristics during early adulthood. They may have implications for sleep disorders or neurological diseases related to myelin.

EEG Correlates of Cognitive Functions in a Child with ASD and White Matter Signal Abnormalities: A Case Report with Two-and-a-Half-Year Follow-Up

This research aimed to examine the EEG correlates of different stimuli processing instances in a child with ASD and white matter signal abnormalities and to investigate their relationship to the results of behavioral tests. The prospective case study reports two and a half years of follow-up data from a child aged 38 to 66 months. Cognitive, speech-language, sensory, and EEG correlates of auditory-verbal and auditory-visual-verbal information processing were recorded during five test periods, and their mutual interrelation was analyzed. EEG findings revealed no functional theta frequency range redistribution in the frontal regions favoring the left hemisphere during speech processing. The results pointed to a positive linear trend in the relative theta frequency range and a negative linear trend in the relative alpha frequency range when listening to and watching the cartoon. There was a statistically significant correlation between EEG signals and behavioral test results. Based on the obtained results, it may be concluded that EEG signals and their association with the results of behavioral tests should be evaluated with certain restraints considering the characteristics of the stimuli during EEG recording.

Structural and functional brain changes in people with knee osteoarthritis: a scoping review

Background

Knee osteoarthritis is a highly prevalent disease worldwide that leads to functional disability and chronic pain. It has been shown that not only changes are generated at the joint level in these individuals, but also neuroplastic changes are produced in different brain areas, especially in those areas related to pain perception, therefore, the objective of this research was to identify and compare the structural and functional brain changes in knee OA versus healthy subjects.

Methodology

Searches in MEDLINE (PubMed), EMBASE, WOS, CINAHL, SCOPUS, Health Source, and Epistemonikos databases were conducted to explore the available evidence on the structural and functional brain changes occurring in people with knee OA. Data were recorded on study characteristics, participant characteristics, and brain assessment techniques. The methodological quality of the studies was analysed with Newcastle Ottawa Scale.

Results

Sixteen studies met the inclusion criteria. A decrease volume of the gray matter in the insular region, parietal lobe, cingulate cortex, hippocampus, visual cortex, temporal lobe, prefrontal cortex, and basal ganglia was found in people with knee OA. However, the opposite occurred in the frontal lobe, nucleus accumbens, amygdala region and somatosensory cortex, where an increase in the gray matter volume was evidenced. Moreover, a decreased connectivity to the frontal lobe from the insula, cingulate cortex, parietal, and temporal areas, and an increase in connectivity from the insula to the prefrontal cortex, subcallosal area, and temporal lobe was shown.

Conclusion

All these findings are suggestive of neuroplastic changes affecting the pain matrix in people with knee OA.

Neurofilaments - Small proteins of physiological significance and predictive power for future neurodegeneration and cognitive decline across the life span

Neurofilaments (NFs) are not only important for axonal integrity and nerve conduction in large myelinated axons but they are also thought to be crucial for receptor and synaptic functioning. Therefore, NFs may play a critical role in cognitive functions, as cognitive processes are known to depend on synaptic integrity and are modulated by dopaminergic signaling. Here, we present a theory-driven interdisciplinary approach that NFs may link inflammation, neurodegeneration, and cognitive functions. We base our hypothesis on a wealth of evidence suggesting a causal link between inflammation and neurodegeneration and between these two and cognitive decline (see Fig. 1), also taking dopaminergic signaling into account. We conclude that NFs may not only serve as biomarkers for inflammatory, neurodegenerative, and cognitive processes but also represent a potential mechanical hinge between them, moreover, they may even have predictive power regarding future cognitive decline. In addition, we advocate the use of both NFs and MRI parameters, as their synthesis offers the opportunity to individualize medical treatment by providing a comprehensive view of underlying disease activity in neurological diseases. Since our society will become significantly older in the upcoming years and decades, maintaining cognitive functions and healthy aging will play an important role. Thanks to technological advances in recent decades, NFs could serve as a rapid, noninvasive, and relatively inexpensive early warning system to identify individuals at increased risk for cognitive decline and could facilitate the management of cognitive dysfunctions across the lifespan.

Altered static and dynamic functional network connectivity related to cognitive decline in individuals with white matter hyperintensities

White matter hyperintensities (WMH) of assumed vascular origin are common in elderly individuals and are closely associated with cognitive decline. However, the underlying neural mechanisms of WMH-related cognitive impairment remain unclear. After strict screening, 59 healthy controls (HC, n = 59), 51 patients with WMH and normal cognition (WMH-NC, n = 51) and 68 patients with WMH and mild cognitive impairment (WMH-MCI, n = 68) were included in the final analyses. All individuals underwent multimodal magnetic resonance imaging (MRI) and cognitive evaluations. We investigated the neural mechanism underlying WMH-related cognitive impairment based on static and dynamic functional network connectivity (sFNC and dFNC) approaches. Finally, the support vector machine (SVM) method was performed to identify WMH-MCI individuals. The sFNC analysis indicated that functional connectivity within the visual network (VN) could mediate the impairment of information processing speed related to WMH (indirect effect: 0.24; 95% CI: 0.03, 0.88 and indirect effect: 0.05; 95% CI: 0.001, 0.14). WMH may regulate the dFNC between the higher-order cognitive network and other networks and enhance the dynamic variability between the left frontoparietal network (lFPN) and the VN to compensate for the decline in high-level cognitive functions. The SVM model achieved good prediction ability for WMH-MCI patients based on the above characteristic connectivity patterns. Our findings shed light on the dynamic regulation of brain network resources to maintain cognitive processing in individuals with WMH. Crucially, dynamic reorganization of brain networks could be regarded as a potential neuroimaging biomarker for identifying WMH-related cognitive impairment.

Targeted Modulation of Human Brain Interregional Effective Connectivity With Spike-Timing Dependent Plasticity

OBJECTIVE

The ability to selectively up- or downregulate interregional brain connectivity would be useful for research and clinical purposes. Toward this aim, cortico-cortical paired associative stimulation (ccPAS) protocols have been developed in which two areas are repeatedly stimulated with a millisecond-level asynchrony. However, ccPAS results in humans using bifocal transcranial magnetic stimulation (TMS) have been variable, and the mechanisms remain unproven. In this study, our goal was to test whether ccPAS mechanism is spike-timing-dependent plasticity (STDP).

MATERIALS AND METHODS

Eleven healthy participants received ccPAS to the left primary motor cortex (M1) → right M1 with three different asynchronies (5 milliseconds shorter, equal to, or 5 milliseconds longer than the 9-millisecond transcallosal conduction delay) in separate sessions. To observe the neurophysiological effects, single-pulse TMS was delivered to the left M1 before and after ccPAS while cortico-cortical evoked responses were extracted from the contralateral M1 using source-resolved electroencephalography.

RESULTS

Consistent with STDP mechanisms, the effects on synaptic strengths flipped depending on the asynchrony. Further implicating STDP, control experiments suggested that the effects were unidirectional and selective to the targeted connection.

CONCLUSION

The results support the idea that ccPAS induces STDP and may selectively up- or downregulate effective connectivity between targeted regions in the human brain.

Compensatory mechanisms of reduced interhemispheric EEG connectivity during sleep in patients with apnea

We performed a mathematical analysis of functional connectivity in electroencephalography (EEG) of patients with obstructive sleep apnea (OSA) (N = 10; age: 52.8 ± 13 years; median age: 49 years; male/female ratio: 7/3), compared with a group of apparently healthy participants (N = 15; age: 51.5 ± 29.5 years; median age: 42 years; male/female ratio: 8/7), based on the calculation of wavelet bicoherence from nighttime polysomnograms. Having observed the previously known phenomenon of interhemispheric synchronization deterioration, we demonstrated a compensatory increase in intrahemispheric connectivity, as well as a slight increase in the connectivity of the central and occipital areas for high-frequency EEG activity. Significant changes in functional connectivity were extremely stable in groups of apparently healthy participants and OSA patients, maintaining the overall pattern when comparing different recording nights and various sleep stages. The maximum variability of the connectivity was observed at fast oscillatory processes during REM sleep. The possibility of observing some changes in functional connectivity of brain activity in OSA patients in a state of passive wakefulness opens up prospects for further research. Developing the methods of hypnogram evaluation that are independent of functional connectivity may be useful for implementing a medical decision support system.

Cortical amyloid-beta burden is associated with changes in intracortical myelin in cognitively normal older adults

Amyloid-beta (Aβ) aggregates and myelin breakdown are among the earliest detrimental effects of Alzheimer's disease (AD), likely inducing abnormal patterns of neuronal communication within cortical networks. However, human in vivo evidence linking Aβ burden, intracortical myelin, and cortical synchronization is lacking in cognitively normal older individuals. Here, we addressed this question combining ¹⁸F-Florbetaben-PET imaging, cortical T1-weigthed/T2-weighted (T1w/T2w) ratio maps, and resting-state functional connectivity (rs-FC) in cognitively unimpaired older adults. Results showed that global Aβ burden was both positively and negatively associated with the T1w/T2w ratio in different cortical territories. Affected cortical regions were further associated with abnormal patterns of rs-FC and with subclinical cognitive deficits. Finally, causal mediation analysis revealed that the negative impact of T1w/T2w ratio in left posterior cingulate cortex on processing speed was driven by Aβ burden. Collectively, these findings provide novel insights into the relationship between initial Aβ plaques and intracortical myelin before the onset of cognitive decline, which may contribute to monitor the efficacy of novel disease-modifying strategies in normal elderly individuals at risk for cognitive impairment.

Predicting individual differences in behavioral activation and behavioral inhibition from functional networks in the resting EEG

The behavioral activation system (BAS) and behavioral inhibition system (BIS) are thought to underly affective dispositions and self-regulatory processes. The BAS is sensitive to reward and involved in approach behaviors, and the BIS is sensitive to punishment and involved in avoidance behaviors. Trait BAS and BIS relate to distinct behavioral profiles and neural activity, but little is known about how trait BAS and BIS relate to functional networks in EEG. We applied a data-driven method called connectome predictive modeling (CPM) to identify networks relating to trait BAS and BIS and tested whether the strength of those networks predicted trait BAS and BIS in novel subjects using a leave-one-out cross-validation procedure. Adult participants (N = 107) completed a resting state task with eyes closed and eyes open, and trait BAS and BIS were measured via Carver and White's (1994) BIS and BAS scales. We hypothesized distinct positive (more synchronization) and negative (less synchronization) networks would relate to trait BAS and BIS. For eyes closed, we identified two negative networks, one in theta and one in alpha predicted BIS. We identified three positive networks, one in theta and one in beta predicted Fun Seeking and one in theta predicted Drive. For eyes open, negative theta and alpha networks predicted BIS, a positive theta network predicted Fun Seeking, and a negative gamma network predicted mean BAS. Visualization of the networks are presented. Discussion centers on the observed networks and how to advance application of CPM to EEG, including with clinical implications.

Individual differences in visual evoked potential latency are associated with variance in brain tissue volume in people with multiple sclerosis: An analysis of brain function-structure correlates

Visual evoked potentials (VEP) index visual pathway functioning, and are often used for clinical assessment and as outcome measures in people with multiple sclerosis (PwMS). VEPs may also reflect broader neural disturbances that extend beyond the visual system, but this possibility requires further investigation. In the present study, we examined the hypothesis that delayed latency of the P100 component of the VEP would be associated with broader structural changes in the brain in PwMS. We obtained VEP latency for a standard pattern-reversal checkerboard stimulus paradigm, in addition to Magnetic Resonance Imaging (MRI) measures of whole brain volume (WBV), gray matter volume (GMV), white matter volume (WMV), and T2-weighted fluid attenuated inversion recovery (FLAIR) white matter lesion volume (FLV). Correlation analyses indicated that prolonged VEP latency was significantly associated with lower WBV, GMV, and WMV, and greater FLV. VEP latency remained significantly associated with WBV, GMV, and WMV even after controlling for the variance associated with inter-ocular latency, age, time between VEP and MRI assessments, and other MRI variables. VEP latency delays were most pronounced in PwMS that exhibited low volume in both white and gray matter simultaneously. Furthermore, PwMS that had delayed VEP latency based on a clinically relevant cutoff (VEP latency ≥ 113 ms) in both eyes had lower WBV, GMV, and WMV and greater FLV in comparison to PwMS that had normal VEP latency in one or both eyes. The findings suggest that PwMS that have delayed latency in both eyes may be particularly at risk for exhibiting greater brain atrophy and lesion volume. These analyses also indicate that VEP latency may index combined gray matter and white matter disturbances, and therefore broader network connectivity and efficiency. VEP latency may therefore provide a surrogate marker of broader structural disturbances in the brain in MS.

Review of electroencephalography signals approaches for mental stress assessment

The innovation of electroencephalography (EEG) more than a century ago supports the technique to assess brain structure and function in clinical health and research applications. The EEG signals were identified on their frequency ranges as delta (from 0.5 to 4 Hz), theta (from 4 to 7 Hz), alpha (from 8 to 12 Hz), beta (from 16 to 31 Hz), and gamma (from 36 to 90 Hz). Stress is a sense of emotional tension caused by several life events. For example, worrying about something, being under pressure, and facing significant challenges are causes of stress. The human body is affected by stress in various ways. It promotes inflammation, which affects cardiac health. The autonomic nervous system is activated during mental stress. Posttraumatic stress disorder and Alzheimer's disease are common brain stress disorders. Several methods have been used previously to identify stress, for instance, magnetic resonance imaging, single-photon emission computed tomography and EEG. The EEG identifies the electrical activity in the human brain by applying small electrodes positioned on the scalp of the brain. It is a useful non-invasive method and collects feedback from stress hormones. In addition, it can serve as a reliable tool for measuring stress. Furthermore, evaluating human stress in real-time is complicated and challenging. This review demonstrates the power of frequency bands for mental stress and the behaviors of frequency bands based on medical and research experiencebands based on medical and research experience.

The focused quantitative EEG bio-marker in studying childhood atrophic encephalopathy

Although it is a normal involution process in advanced age, brain atrophy—also termed atrophic encephalopathy—can also occur prematurely in childhood as a consequential effect of brain tissues injury through trauma or central nervous system infection, though in both normal and premature occurrences this condition always presents with loss of volume relative to the skull. A common tool for the functional study of brain activities is an electroencephalogram, but analyses of this have reportedly identified mismatches between qualitative and quantitative forms, particularly in the use of Delta-alpha ratio (DAR) indices, meaning that the values may be case dependent. The current study thus examines the value of Focused Occipital Beta-Alpha Ratio (FOBAR) as a modified biomarker for evaluating brain functional changes resulting from brain atrophy. This cross-sectional design study involves 260 patients under 18 years of age. Specifically, 207 patients with brain atrophy are compared with 53 control subjects with CT scan-proven normal brain volume. All the children underwent digital electroencephalography with brain mapping. Results show that alpha posterior dominant rhythm was present in 88 atrophic children and 44 controls. Beta as posterior dominant rhythm was present in an overwhelming 91.5% of atrophic subjects, with 0.009 p-values. The focused occipital Beta-alpha ratio correlated significantly with brain volume loss presented in diagonal brain fraction. The FOBAR and DAR values of the QEEG showed no significant correlation. This work concludes that QEEG cerebral dysfunctional studies may be etiologically and case dependent from the nature of the brain injury. Also, the focused Beta-alpha ratio of the QEEG is a prospective and potential biomarker of consideration in studying childhood atrophic encephalopathy.

Involvement of White Matter Language Tracts in Glioma: Clinical Implications, Operative Management, and Functional Recovery After Injury

To achieve optimal survival and quality of life outcomes in patients with glioma, the extent of tumor resection must be maximized without causing injury to eloquent structures. Preservation of language function is of particular importance to patients and requires careful mapping to reveal the locations of cortical language hubs and their structural and functional connections. Within this language network, accurate mapping of eloquent white matter tracts is critical, given the high risk of permanent neurological impairment if they are injured during surgery. In this review, we start by describing the clinical implications of gliomas involving white matter language tracts. Next, we highlight the advantages and limitations of methods commonly used to identify these tracts during surgery including structural imaging techniques, functional imaging, non-invasive stimulation, and finally, awake craniotomy. We provide a rationale for combining these complementary techniques as part of a multimodal mapping paradigm to optimize postoperative language outcomes. Next, we review local and long-range adaptations that take place as the language network undergoes remodeling after tumor growth and surgical resection. We discuss the probable cellular mechanisms underlying this plasticity with emphasis on the white matter, which until recently was thought to have a limited role in adults. Finally, we provide an overview of emerging developments in targeting the glioma-neuronal network interface to achieve better disease control and promote recovery after injury.

Functional and structural brain network correlates of visual hallucinations in Lewy body dementia

Visual hallucinations are a common feature of Lewy body dementia. Previous studies have shown that visual hallucinations are highly specific in differentiating Lewy body dementia from Alzheimer’s disease dementia and Alzheimer–Lewy body mixed pathology cases. Computational models propose that impairment of visual and attentional networks is aetiologically key to the manifestation of visual hallucinations symptomatology. However, there is still a lack of experimental evidence on functional and structural brain network abnormalities associated with visual hallucinations in Lewy body dementia.

We used EEG source localization and network based statistics to assess differential topographical patterns in Lewy body dementia between 25 participants with visual hallucinations and 17 participants without hallucinations. Diffusion tensor imaging was used to assess structural connectivity between thalamus, basal forebrain and cortical regions belonging to the functionally affected network component in the hallucinating group, as assessed with network based statistics. The number of white matter streamlines within the cortex and between subcortical and cortical regions was compared between hallucinating and not hallucinating groups and correlated with average EEG source connectivity of the affected subnetwork. Moreover, modular organization of the EEG source network was obtained, compared between groups and tested for correlation with structural connectivity.

Network analysis showed that compared to non-hallucinating patients, those with hallucinations feature consistent weakened connectivity within the visual ventral network, and between this network and default mode and ventral attentional networks, but not between or within attentional networks. The occipital lobe was the most functionally disconnected region. Structural analysis yielded significantly affected white matter streamlines connecting the cortical regions to the nucleus basalis of Meynert and the thalamus in hallucinating compared to not hallucinating patients. The number of streamlines in the tract between the basal forebrain and the cortex correlated with cortical functional connectivity in non-hallucinating patients, while a correlation emerged for the white matter streamlines connecting the functionally affected cortical regions in the hallucinating group.

This study proposes, for the first time, differential functional networks between hallucinating and not hallucinating Lewy body dementia patients, and provides empirical evidence for existing models of visual hallucinations. Specifically, the outcome of the present study shows that the hallucinating condition is associated with functional network segregation in Lewy body dementia and supports the involvement of the cholinergic system as proposed in the current literature.

Consequences of Inadequate Caregiving for Children's Attachment, Neurobiological Development, and Adaptive Functioning

Given that human infants are almost fully reliant on caregivers for survival, the presence of parents who provide sensitive, responsive care support infants and young children in developing the foundation for optimal biological functioning. Conversely, when parents are unavailable or insensitive, there are consequences for infants' and children's attachment and neurobiological development. In this paper, we describe effects of inadequate parenting on children's neurobiological and behavioral development, with a focus on developing capacities for executive functioning, emotion regulation, and other important cognitive-affective processes. Most prior research has examined correlational associations among these constructs. Given that interventions tested through randomized clinical trials allow for causal inferences, we review longitudinal intervention effects on children's biobehavioral and cognitive-affective outcomes. In particular, we provide an overview of the Bucharest Early Intervention Project, a study in which children were randomized to continue in orphanage care (typically the most extreme condition of privation) or were placed into the homes of trained, supported foster parents. We also discuss findings regarding Attachment and Biobehavioral Catch-up, an intervention enhancing sensitivity among high-risk parents. We conclude by suggesting future directions for research in this area.

Low-frequency oscillations in cortical level to help diagnose task-specific dystonia

Task-specific dystonia is a neurological movement disorder that abnormal contractions of muscles result in the twisting of fixed postures or muscle spasm during specific tasks. Due to the rareness and the pathophysiology of the disease, there is no test to confirm the diagnosis of task-specific dystonia, except comprehensive observations by the experts. Evidence from neural electrophysiological data suggests that enhanced low frequency (4-12 Hz) oscillations in the subcortical structure of the globus pallidus were associated with the pathological abnormalities concerning β and γ rhythms in motor areas and motor cortical network in patients with task-specific dystonia. However, whether patients with task-specific dystonia have any low-frequency abnormalities in motor cortical areas remains unclear. In this study, we hypothesized that low-frequency abnormalities are present in core motor areas and motor cortical networks in patients with task-specific dystonia during performing the non-symptomatic movements and those low-frequency abnormalities can help the diagnosis of this disease. We tested this hypothesis by using EEG, effective connectivity analysis, and a machine learning method. Fifteen patients with task-specific dystonia and 15 healthy controls were recruited. The machine learning method identified 8 aberrant movement-related network connections concerning low frequency, β and γ frequencies, which enabled the separation of the data of patients from those of controls with an accuracy of 90%. Importantly, 7 of the 8 aberrant connections engaged the premotor area contralateral to the affected hand, suggesting an important role of the premotor area in the pathological abnormities. The patients exhibited significantly lower low frequency activities during the movement preparation and significantly lower β rhythms during movements compared with healthy controls in the core motor areas. Our findings of low frequency- and β-related abnormalities at the cortical level and aberrant motor network could help diagnose task-specific dystonia in the clinical setting, and the importance of the contralesional premotor area suggests its diagnostic potential for task-specific dystonia.

Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel

The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.

Phase-Amplitude Coupling, Mental Health and Cognition: Implications for Adolescence

Identifying biomarkers of developing mental disorder is crucial to improving early identification and treatment-a key strategy for reducing the burden of mental disorders. Cross-frequency coupling between two different frequencies of neural oscillations is one such promising measure, believed to reflect synchronization between local and global networks in the brain. Specifically, in adults phase-amplitude coupling (PAC) has been shown to be involved in a range of cognitive processes, including working and long-term memory, attention, language, and fluid intelligence. Evidence suggests that increased PAC mediates both temporary and lasting improvements in working memory elicited by transcranial direct-current stimulation and reductions in depressive symptoms after transcranial magnetic stimulation. Moreover, research has shown that abnormal patterns of PAC are associated with depression and schizophrenia in adults. PAC is believed to be closely related to cortico-cortico white matter (WM) microstructure, which is well established in the literature as a structural mechanism underlying mental health. Some cognitive findings have been replicated in adolescents and abnormal patterns of PAC have also been linked to ADHD in young people. However, currently most research has focused on cross-sectional adult samples. Whereas initial hypotheses suggested that PAC was a state-based measure due to an early focus on cognitive, task-based research, current evidence suggests that PAC has both state-based and stable components. Future longitudinal research focusing on PAC throughout adolescent development could further our understanding of the relationship between mental health and cognition and facilitate the development of new methods for the identification and treatment of youth mental health.

Genome-Wide Scan for Five Brain Oscillatory Phenotypes Identifies a New QTL Associated with Theta EEG Band

Brain waves, measured by electroencephalography (EEG), are a powerful tool in the investigation of neurophysiological traits and a noninvasive and cost-effective alternative in the diagnostic of some neurological diseases. In order to identify novel Quantitative Trait Loci (QTLs) for brain wave relative power (RP), we collected resting state EEG data in five frequency bands (δ, θ, α, β1, and β2) and genome-wide data in a cohort of 105 patients with late onset Alzheimer’s disease (LOAD), 41 individuals with mild cognitive impairment and 45 controls from Iberia, correcting for disease status. One novel association was found with an interesting candidate for a role in brain wave biology, CLEC16A (C-type lectin domain family 16), with a variant at this locus passing the adjusted genome-wide significance threshold after Bonferroni correction. This finding reinforces the importance of immune regulation in brain function. Additionally, at a significance cutoff value of 5 × 10⁻⁶, 18 independent association signals were detected. These signals comprise brain expression Quantitative Loci (eQTLs) in caudate basal ganglia, spinal cord, anterior cingulate cortex and hypothalamus, as well as chromatin interactions in adult and fetal cortex, neural progenitor cells and hippocampus. Moreover, in the set of genes showing signals of association with brain wave RP in our dataset, there is an overrepresentation of loci previously associated with neurological traits and pathologies, evidencing the pleiotropy of the genetic variation modulating brain function.

Social Cognition and White Matter: Connectivity and Cooperation

Humans are highly social animals whose survival and well-being depend on their capacity to cooperate in complex social settings. Advances in anthropology and psychology have demonstrated the importance of cooperation for enhancing social cohesion and minimizing conflict. The understanding of social behavior is informed by the notion of social cognition, a set of mental operations including emotion perception, mentalizing, and empathy. The social brain hypothesis posits that the mammalian brain has enlarged over evolution to meet the challenges of social life, culminating in a large human brain well adapted for social cognition. The structures subserving social cognition are mainly located in the frontal and temporal lobes, and although gray matter is critical, social cognition also requires white matter. Whereas the social brain hypothesis assumes that brain enlargement has been driven by neocortical expansion, cerebral white matter has expanded even more robustly than the neocortex, coinciding with the emergence of social cognition. White matter expansion is most evident in the frontal and temporal lobes, where it enhances connectivity between regions critical for social cognition. Myelination has, in turn, conferred adaptive social advantages by enabling prompt empathic concern for offspring and by strengthening networks that support cooperation and the related capacities of altruism and morality. Social cognition deficits related to myelinated tract involvement occur in many disorders, including stroke, Binswanger disease, traumatic brain injury, multiple sclerosis, glioma, and behavioral variant frontotemporal dementia. The contribution of white matter to social cognition can be conceptualized as the enhancement of cooperation through brain connectivity.

White matter injury and neurodevelopmental disabilities: A cross-disease (dis)connection

White matter (WM) injury, once known primarily in preterm newborns, is emerging in its non-focal (diffused), non-necrotic form as a critical component of subtle brain injuries in many early-life diseases like prematurity, intrauterine growth restriction, congenital heart defects, and hypoxic-ischemic encephalopathy. While advances in medical techniques have reduced the number of severe outcomes, the incidence of tardive impairments in complex cognitive functions or psychopathology remains high, with lifelong detrimental effects. The importance of WM in coordinating neuronal assemblies firing and neural groups synchronizing within multiple frequency bands through myelination, even mild alterations in WM structure, may interfere with the cognitive performance that increasing social and learning demands would exploit tardively during children growth. This phenomenon may contribute to explaining longitudinally the high incidence of late-appearing impairments that affect children with a history of perinatal insults. Furthermore, WM abnormalities have been highlighted in several neuropsychiatric disorders, such as autism and schizophrenia. In this review, we gather and organize evidence on how diffused WM injuries contribute to neurodevelopmental disorders through different perinatal diseases and insults. An insight into a possible common, cross-disease, mechanism, neuroimaging and monitoring, biomarkers, and neuroprotective strategies will also be presented.

Full Recovery From Cocaine-Induced Toxic Leukoencephalopathy: Emphasizing the Role of Neuroinflammation and Brain Edema

Toxic leukoencephalopathy (TL) is characterized by white matter disease on magnetic resonance imaging (MRI) and evidence of exposure to a neurotoxic agent. We describe a case of cocaine-induced TL in which extensive white matter disease did not preclude full recovery. A 57-year-old man with substance abuse disorder presented with a 5-day history of strange behavior. On admission, he was alert but had difficulty concentrating, psychomotor retardation, and diffuse hyperreflexia. Brain MRI revealed confluent subcortical white matter hyperintensities with restricted diffusion in some but not in other areas. Electroencephalography (EEG) showed mild diffuse slowing. Blood tests were normal except for mild hyperammonemia. Urine screen was positive for cocaine and benzodiazepine but quantitative analysis was significant only for cocaine. Prednisone 60-mg qd was initiated on day 4, tapered over a 5-day period, and discontinued on day 9. He was discharged after 3 weeks. Cognitive function returned to normal 2 weeks after discharge. Five months later, neurologic exam and EEG were normal and MRI showed near-100% resolution of white matter lesions. TL has been attributed to white matter ischemia/hypoxia resulting in demyelination/axonal injury. The clinical, EEG, and MRI findings and time course of recovery of our patient suggest that cocaine-induced inflammation/edema resulted in TL but not in ischemic/hypoxic injury. While inflammation/edema may have regressed when cocaine was discontinued, we cannot exclude a role for prednisone in protecting the patient from the ischemic/hypoxic sequelae of inflammation/edema. MRI is indispensable for diagnosing TL but EEG may provide additional useful diagnostic and prognostic information.

Associations of Alpha and Beta Interhemispheric EEG Coherences with Indices of Attentional Control and Academic Performance

Introduction. Heretofore, research on optimizing academic performance has suffered from an inability to translate what is known about an individual's learning behaviors to how effectively they are able to use the critical nodes and hubs in their cerebral cortex for learning. A previous study from our laboratory suggests that lower theta-beta ratios (TBRs) measured by EEG may be associated with higher academic performance in a medical school curriculum.

METHODS

In this study, we tested the hypothesis that TBR and academic performance may be correlated with EEG coherence, a measure of brain connectivity. We analyzed the interhemispheric coherences of the subjects involved in our prior study. TBR and coherence measurements were made at 19 scalp electrode recording sites and 171 electrode combinations with eyes open and closed (EO, EC). Control data were acquired during a session of acclimation to the research protocol 3 d before an initial examination in anatomy-physiology (control exam) and were repeated five weeks later, 3 d before a second exam covering different anatomy-physiology topics (comparison exam).

RESULTS

Between the control and comparison exams, beta coherences increased significantly at the frontal pole, frontal, parietal, midtemporal, posterior temporal, and occipital recording sites under the EO condition and at the inferior frontal, central, midtemporal, and posterior temporal sites under the EC condition. Alpha coherences increased significantly at the same sites and under the same EO/EC conditions as found for the beta coherences. The beta coherences were negatively correlated with the TBR and were positively correlated with the comparison exam score at the midfrontal electrode site (F3-F4) but only under the EO condition. Beta and alpha coherences at the midfrontal, inferior frontal midtemporal, posterior temporal, and occipital sites were also negatively correlated with the average TBR under the EO condition.

CONCLUSIONS

Lower TBR, an indicator of attentional control, was associated with higher alpha and beta interhemispheric coherences measured with eyes open at sites overlying the frontal, temporal, and occipital cortices. Changes in EEG coherences and TBRs might be useful as neurophysiological measures of neuroplasticity and the efficacy of strategies for preventing academic underachievement and treatments for improving academic performance.

BOLD and EEG signal variability at rest differently relate to aging in the human brain

Variability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability - identified with either hemodynamic or electrophysiological methods - reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25 ​± ​3 years, N ​= ​135) and older (67 ​± ​4 years, N ​= ​54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1-12 ​Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode network. Moreover, age-related increases of variability in the amplitude of beta-band frequency EEG oscillations (15-25 ​Hz) were seen predominantly in temporal brain regions. There were significant sex differences in EEG signal variability in various brain regions while no significant sex differences were observed in BOLD signal variability. Bivariate and multivariate correlation analyses revealed no significant associations between EEG- and fMRI-based variability measures. In summary, we show that both BOLD and EEG signal variability reflect aging-related processes but are likely to be dominated by different physiological origins, which relate differentially to age and sex.

Large-scale cortical travelling waves predict localized future cortical signals

Predicting future brain signal is highly sought-after, yet difficult to achieve. To predict the future phase of cortical activity at localized ECoG and MEG recording sites, we exploit its predominant, large-scale, spatiotemporal dynamics. The dynamics are extracted from the brain signal through Fourier analysis and principal components analysis (PCA) only, and cast in a data model that predicts future signal at each site and frequency of interest. The dominant eigenvectors of the PCA that map the large-scale patterns of past cortical phase to future ones take the form of smoothly propagating waves over the entire measurement array. In ECoG data from 3 subjects and MEG data from 20 subjects collected during a self-initiated motor task, mean phase prediction errors were as low as 0.5 radians at local sites, surpassing state-of-the-art methods of within-time-series or event-related models. Prediction accuracy was highest in delta to beta bands, depending on the subject, was more accurate during episodes of high global power, but was not strongly dependent on the time-course of the task. Prediction results did not require past data from the to-be-predicted site. Rather, best accuracy depended on the availability in the model of long wavelength information. The utility of large-scale, low spatial frequency traveling waves in predicting future phase activity at local sites allows estimation of the error introduced by failing to account for irreducible trajectories in the activity dynamics.

Prediction is an important step in scientific progress, often leading to real-world applications. Prediction of future brain activity could lead to improvements in detecting driver and pilot error or real-time brain testing using transcranial magnetic stimulation. Previous studies have either supposed that the ‘noise’ level in the cortex is high, setting the prediction bar rather low; or used localized measurements to predict future activity, with modest success. A long-held but controversial hypothesis is that the cortex is best characterized as a multi-scale dynamic structure, in which the flow of activity at one scale, say, the area responsible for motor control, is inextricably tied to activity at smaller and larger scales, for example within a cortical column and the whole cortex. We test this hypothesis by analyzing large-scale traveling waves of cortical activity. Like waves arriving on a beach, the ongoing wave motion allows better prediction of future activity compared to monitoring the local rise and fall; in the best cases the future wave cycle is predicted with as low as 20° average error angle. The prediction techniques developed for the present research rely on mathematics related to quantifying large-scale weather patterns or analysis of fluid dynamics.

Low-Frequency Brain Oscillations Track Motor Recovery in Human Stroke

OBJECTIVE

The majority of patients with stroke survive the acute episode and live with enduring disability. Effective therapies to support recovery of motor function after stroke are yet to be developed. Key to this development is the identification of neurophysiologic signals that mark recovery and are suitable and susceptible to interventional therapies. Movement preparatory low-frequency oscillations (LFOs) play a key role in cortical control of movement. Recent animal data point to a mechanistic role of motor cortical LFOs in stroke motor deficits and demonstrate neuromodulation intervention with therapeutic benefit. Their relevance in human stroke pathophysiology is unknown.

METHODS

We studied the relationship between movement-preparatory LFOs during the performance of a visuomotor grip task and motor function in a longitudinal (<5 days, 1 and 3 months) cohort study of 33 patients with motor stroke and in 19 healthy volunteers.

RESULTS

Acute stroke-lesioned brains fail to generate the LFO signal. Whereas in healthy humans, a transient occurrence of LFOs preceded movement onset at predominantly contralateral frontoparietal motor regions, recordings in patients revealed that movement-preparatory LFOs were substantially diminished to a level of 38% after acute stroke. LFOs progressively increased at 1 and 3 months. This re-emergence closely tracked the recovery of motor function across several movement qualities including grip strength, fine motor skills, and synergies and was frequency band specific.

INTERPRETATION

Our results provide the first human evidence for a link between movement-preparatory LFOs and functional recovery after stroke, promoting their relevance for movement control. These results suggest that it may be interesting to explore targeted, LFOs-restorative brain stimulation therapy in human stroke patients. ANN NEUROL 2019;86:853-865.

Frequency-Dependent Changes in Resting State Electroencephalogram Functional Networks after Traumatic Brain Injury in Piglets

Traumatic brain injury (TBI) is a major health concern in children, as it can cause chronic cognitive and behavioral deficits. The lack of objective involuntary metrics for the diagnosis of TBI makes prognosis more challenging, especially in the pediatric context, in which children are often unable to articulate their symptoms. Resting state electroencephalograms (EEG), which are inexpensive and non-invasive, and do not require subjects to perform cognitive tasks, have not yet been used to create functional brain networks in relation to TBI in children or non-human animals; here we report the first such study. We recorded resting state EEG in awake piglets before and after TBI, from which we generated EEG functional networks from the alpha (8-12 Hz), beta (16.5-25 Hz), broad (1-35 Hz), delta (1-3.5 Hz), gamma (30-35 Hz), sigma (13-16 Hz), and theta (4-7.5 Hz) frequency bands. We hypothesize that mild TBI will induce persistent frequency-dependent changes in the 4-week-old piglet at acute and chronic time points. Hyperconnectivity was found in several frequency band networks after TBI. This study serves as proof of concept that the study of EEG functional networks in awake piglets may be useful for the development of diagnostic metrics for TBI in children.

Epilepsy in Tubulinopathy: Personal Series and Literature Review

Mutations in tubulin genes are responsible for a large spectrum of brain malformations secondary to abnormal neuronal migration, organization, differentiation and axon guidance and maintenance. Motor impairment, intellectual disability and epilepsy are the main clinical symptoms. In the present study 15 patients from a personal cohort and 75 from 21 published studies carrying mutations in TUBA1A, TUBB2B and TUBB3 tubulin genes were evaluated with the aim to define a clinical and electrophysiological associated pattern. Epilepsy shows a wide range of severity without a specific pattern. Mutations in TUBA1A (60%) and TUBB2B (74%) and TUBB3 (25%) genes are associated with epilepsy. The accurate analysis of the Electroencephalogram (EEG) pattern in wakefulness and sleep in our series allows us to detect significant abnormalities of the background activity in 100% of patients. The involvement of white matter and of the inter-hemispheric connection structures typically observed in tubulinopathies is evidenced by the high percentage of asynchronisms in the organization of sleep activity recorded. In addition to asymmetries of the background activity, excess of slowing, low amplitude and Magnetic Resonance (MR) imaging confirm the presence of extensive brain malformations involving subcortical and midline structures. In conclusion, epilepsy in tubulinopathies when present has a favorable evolution over time suggesting a not particularly aggressive therapeutic approach.

The functional role of beta-oscillations in the supplementary motor area during reaching and grasping after stroke: A question of structural damage to the corticospinal tract

Hand motor function is often severely affected in stroke patients. Non-satisfying recovery limits reintegration into normal daily life. Understanding stroke-related network changes and identifying common principles that might underlie recovered motor function is a prerequisite for the development of interventional therapies to support recovery. Here, we combine the evaluation of functional activity (multichannel electroencephalography) and structural integrity (diffusion tensor imaging) in order to explain the degree of residual motor function in chronic stroke patients. By recording neural activity during a reaching and grasping task that mimics activities of daily living, the study focuses on deficit-related neural activation patterns. The study showed that the functional role of movement-related beta desynchronization in the supplementary motor area (SMA) for residual hand motor function in stroke patients depends on the microstructural integrity of the corticospinal tract (CST). In particular, in patients with damaged CST, stronger task-related activity in the SMA was associated with worse residual motor function. Neither CST damage nor functional brain activity alone sufficiently explained residual hand motor function. The findings suggest a central role of the SMA in the motor network during reaching and grasping in stroke patients, the degree of functional relevance of the SMA is depending on CST integrity.

White matter plasticity and maturation in human cognition

White matter plasticity likely plays a critical role in supporting cognitive development. However, few studies have used the imaging methods specific to white matter tissue structure or experimental designs sensitive to change in white matter necessary to elucidate these relations. Here we briefly review novel imaging approaches that provide more specific information regarding white matter microstructure. Furthermore, we highlight recent studies that provide greater clarity regarding the relations between changes in white matter and cognition maturation in both healthy children and adolescents and those with white matter insult. Finally, we examine the hypothesis that white matter is linked to cognitive function via its impact on neural synchronization. We test this hypothesis in a population of children and adolescents with recurrent demyelinating syndromes. Specifically, we evaluate group differences in white matter microstructure within the optic radiation; and neural phase synchrony in visual cortex during a visual task between 25 patients and 28 typically developing age-matched controls. Children and adolescents with demyelinating syndromes show evidence of myelin and axonal compromise and this compromise predicts reduced phase synchrony during a visual task compared to typically developing controls. We investigate one plausible mechanism at play in this relationship using a computational model of gamma generation in early visual cortical areas. Overall, our findings show a fundamental connection between white matter microstructure and neural synchronization that may be critical for cognitive processing. In the future, longitudinal or interventional studies can build upon our knowledge of these exciting relations between white matter, neural communication, and cognition.

Neural field theory of evoked response potentials in a spherical brain geometry

Evoked response potentials (ERPs) are calculated in spherical and planar geometries using neural field theory of the corticothalamic system. The ERP is modeled as an impulse response and the resulting modal effects of spherical corticothalamic dynamics are explored, showing that results for spherical and planar geometries converge in the limit of large brain size. Cortical modal effects can lead to a double-peak structure in the ERP time series. It is found that the main difference between infinite planar geometry and spherical geometry is that the ERP peak is sharper and stronger in the spherical geometry. It is also found that the magnitude of the response decreases with increasing spatial width of the stimulus at the cortex. The peak is slightly delayed at large angles from the stimulus point, corresponding to group velocities of 6-10 m s^{-1}. Strong modal effects are found in the spherical geometry, with the lowest few modes sufficing to describe the main features of ERPs, except very near to spatially narrow stimuli.

Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative. A Tutorial Review

A biophysical framework needed to interpret electrophysiological data recorded at multiple spatial scales of brain tissue is developed. Micro current sources at membrane surfaces produce local field potentials, electrocorticography, and electroencephalography (EEG). We categorize multi-scale sources as genuine, equivalent, or representative. Genuine sources occur at the micro scale of cell surfaces. Equivalent sources provide identical experimental outcomes over a range of scales and applications. In contrast, each representative source distribution is just one of many possible source distributions that yield similar experimental outcomes. Macro sources ("dipoles") may be defined at the macrocolumn (mm) scale and depend on several features of the micro sources-magnitudes, micro synchrony within columns, and distribution through the cortical depths. These micro source properties are determined by brain dynamics and the columnar structure of cortical tissue. The number of representative sources underlying EEG data depends on the spatial scale of neural tissue under study. EEG inverse solutions (e.g. dipole localization) and high resolution estimates (e.g. Laplacian, dura imaging) have both strengths and limitations that depend on experimental conditions. The proposed theoretical framework informs studies of EEG source localization, source characterization, and low pass filtering. It also facilitates interpretations of brain dynamics and cognition, including measures of synchrony, functional connections between cortical locations, and other aspects of brain complexity.

Cross-subject network investigation of the EEG microstructure: A sleep spindles study

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Grand averages across subjects can distort connectivity results for a group.

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Within-group network variance may hold information for the EEG event under investigation.

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The proposed method can serve as an observatory tool, complementary to the existing topography EEG techniques.

Background

The microstructural EEG elements and their functional networks relate to many neurophysiological functions of the brain and can reveal abnormalities. Despite the blooming variety of methods for estimating connectivity in the EEG of a single subject, a common pitfall is seen in relevant studies; grand averaging is used for estimating the characteristic connectivity patterns of a group of subjects. This averaging may distort results and fail to account for the internal variability of connectivity results across the subjects of a group.

New Method

In this study, we propose a novel methodology for the cross-subject network investigation of EEG graphoelements. We used dimensionality reduction techniques in order to reveal internal connectivity properties and to examine how consistent these are across a number of subjects. In addition, graph theoretical measures were utilized to prioritize regions according to their network attributes.

Results

As proof of concept, we applied this method on fast sleep spindles across 10 healthy subjects. Neurophysiological findings revealed subnetworks of the spindle events across subjects, highlighting a predominance for occipito-parietal areas and their connectivity with frontal regions.

Comparison with existing methods

This is a new approach for the examination of within-group connectivities in EEG research. The results accounted for more than 85% of the overall data variance and the detected subnetworks were found to be meaningful down-projections of the grand average of the group, suggesting sufficient performance for the proposed methodology.

Conclusion

We conclude that the proposed methodology can serve as an observatory tool for the EEG connectivity patterns across subjects, providing a supplementary analysis of the existing topography techniques.

Inter-ictal network of focal epilepsy and effects of clinical factors on network activity

OBJECTIVE

Aim of the study was to explore the inter-ictal, resting-state EEG network in patients with focal epilepsy (FE) and to specify clinical factors that influence network activity.

METHODS

Functional EEG connectivity (EEGfC) differences were computed between 232 FE patients (FE group) and 77 healthy controls. EEGfC was computed among 23 cortical regions within each hemisphere, for 25 very narrow bands from 1 to 25 Hz. We computed independent effects for six clinical factors on EEGfC in the FE group, by ANOVA and post-hoc t-statistics, corrected for multiple comparisons by false discovery rate method.

RESULTS

Robust, statistically significant EEGfC differences emerged between the FE and the healthy control groups. Etiology, seizure type, duration of the illness and antiepileptic treatment were independent factors that influenced EEGfC. Statistically significant results occurred selectively in one or a few very narrow bands and outlined networks. Most abnormal EEGfC findings occurred at frequencies that mediate integrative and motor activities.

CONCLUSIONS

FE patients have abnormal resting-state EEGfC network activity. Clinical factors significantly modify EEGfC.

SIGNIFICANCE

Delineation of the FE network and modifying factors can open the way for targeted investigations and introduction of EEGfC into epilepsy research and practice.

Electrophysiological impact of multiple concussions in asymptomatic athletes: A re-analysis based on alpha activity during a visual-spatial attention task

Most EEG studies used event-related potentials to assess long-term and cumulative effects of sport-related concussions on brain activity. Time-frequency methods provide another approach that allows the detection of subtle shifts in types and patterns of brain oscillations. We sought to discover whether event-related alpha activity would be significantly affected in asymptomatic multi-concussed athletes. We measured the amplitude of alpha activity (8-12Hz) from the EEG recorded during a visual-spatial attention task to compare event-related alpha perturbations in 13 multi-concussed athletes and 14 age-equivalent, non-concussed teammates. Relative to non-concussed athletes, multi-concussed athletes showed significantly less event-related perturbations time-locked to stimulus presentation. Alpha activity alterations were closely related to the number of concussions sustained. Event-related alpha activity differed in asymptomatic multi-concussed athletes when compared to controls. Our study suggests that low-level neurophysiological underpinnings of the deployment of visual-spatial attention are affected in multi-concussed athletes even though their last concussion occurred on average 30 months prior to testing.

Evidence for frequency-dependent cortical plasticity in the human brain

Frequency-dependent plasticity (FDP) describes adaptation at the synapse in response to stimulation at different frequencies. Its consequence on the structure and function of cortical networks is unknown. We tested whether cortical "resonance," favorable stimulation frequencies at which the sensory cortices respond maximally, influenced the impact of FDP on perception, functional topography, and connectivity of the primary somatosensory cortex using psychophysics and functional imaging (fMRI). We costimulated two digits on the hand synchronously at, above, or below the resonance frequency of the somatosensory cortex, and tested subjects' accuracy and speed on tactile localization before and after costimulation. More errors and slower response times followed costimulation at above- or below-resonance, respectively. Response times were faster after at-resonance costimulation. In the fMRI, the cortical representations of the two digits costimulated above-resonance shifted closer, potentially accounting for the poorer performance. Costimulation at-resonance did not shift the digit regions, but increased the functional coupling between them, potentially accounting for the improved response time. To relate these results to synaptic plasticity, we simulated a network of oscillators incorporating Hebbian learning. Two neighboring patches embedded in a cortical sheet, mimicking the two digit regions, were costimulated at different frequencies. Network activation outside the stimulated patches was greatest at above-resonance frequencies, reproducing the spread of digit representations seen with fMRI. Connection strengths within the patches increased following at-resonance costimulation, reproducing the increased fMRI connectivity. We show that FDP extends to the cortical level and is influenced by cortical resonance.

Changes in White Matter Microstructure Impact Cognition by Disrupting the Ability of Neural Assemblies to Synchronize

Cognition is compromised by white matter (WM) injury but the neurophysiological alterations linking them remain unclear. We hypothesized that reduced neural synchronization caused by disruption of neural signal propagation is involved. To test this, we evaluated group differences in: diffusion tensor WM microstructure measures within the optic radiations, primary visual area (V1), and cuneus; neural phase synchrony to a visual attention cue during visual-motor task; and reaction time to a response cue during the same task between 26 pediatric patients (17/9: male/female) treated with cranial radiation treatment for a brain tumor (12.67 ± 2.76 years), and 26 healthy children (16/10: male/female; 12.01 ± 3.9 years). We corroborated our findings using a corticocortical computational model representing perturbed signal conduction from myelin. Patients show delayed reaction time, WM compromise, and reduced phase synchrony during visual attention compared with healthy children. Notably, using partial least-squares-path modeling we found that WM insult within the optic radiations, V1, and cuneus is a strong predictor of the slower reaction times via disruption of neural synchrony in visual cortex. Observed changes in synchronization were reproduced in a computational model of WM injury. These findings provide new evidence linking cognition with WM via the reliance of neural synchronization on propagation of neural signals.SIGNIFICANCE STATEMENT By comparing brain tumor patients to healthy children, we establish that changes in the microstructure of the optic radiations and neural synchrony during visual attention predict reaction time. Furthermore, by testing the directionality of these links through statistical modeling and verifying our findings with computational modeling, we infer a causal relationship, namely that changes in white matter microstructure impact cognition in part by disturbing the ability of neural assemblies to synchronize. Together, our human imaging data and computer simulations show a fundamental connection between WM microstructure and neural synchronization that is critical for cognitive processing.

EEG-based motor network biomarkers for identifying target patients with stroke for upper limb rehabilitation and its construct validity

Rehabilitation is the main therapeutic approach for reducing poststroke functional deficits in the affected upper limb; however, significant between-patient variability in rehabilitation efficacy indicates the need to target patients who are likely to have clinically significant improvement after treatment. Many studies have determined robust predictors of recovery and treatment gains and yielded many great results using linear approachs. Evidence has emerged that the nonlinearity is a crucial aspect to study the inter-areal communication in human brains and abnormality of oscillatory activities in the motor system is linked to the pathological states. In this study, we hypothesized that combinations of linear and nonlinear (cross-frequency) network connectivity parameters are favourable biomarkers for stratifying patients for upper limb rehabilitation with increased accuracy. We identified the biomarkers by using 37 prerehabilitation electroencephalogram (EEG) datasets during a movement task through effective connectivity and logistic regression analyses. The predictive power of these biomarkers was then tested by using 16 independent datasets (i.e. construct validation). In addition, 14 right handed healthy subjects were also enrolled for comparisons. The result shows that the beta plus gamma or theta network features provided the best classification accuracy of 92%. The predictive value and the sensitivity of these biomarkers were 81.3% and 90.9%, respectively. Subcortical lesion, the time poststroke and initial Wolf Motor Function Test (WMFT) score were identified as the most significant clinical variables affecting the classification accuracy of this predictive model. Moreover, 12 of 14 normal controls were classified as having favourable recovery. In conclusion, EEG-based linear and nonlinear motor network biomarkers are robust and can help clinical decision making.

EEG based zero-phase phase-locking value (PLV) and effects of spatial filtering during actual movement

Phase-locking value (PLV) is a well-known feature in sensorimotor rhythm (SMR) based BCI. Zero-phase PLV has not been explored because it is generally regarded as the result of volume conduction. Because spatial filters are often used to enhance the amplitude (square root of band power (BP)) feature and attenuate volume conduction, they are frequently applied as pre-processing methods when computing PLV. However, the effects of spatial filtering on PLV are ambiguous. Therefore, this article aims to explore whether zero-phase PLV is meaningful and how this is influenced by spatial filtering. Based on archival EEG data of left and right hand movement tasks for 32 subjects, we compared BP and PLV feature using data with and without pre-processing by a large Laplacian. Results showed that using ear-referenced data, zero-phase PLV provided unique information independent of BP for task prediction which was not explained by volume conduction and was significantly decreased when a large Laplacian was applied. In other words, the large Laplacian eliminated the useful information in zero-phase PLV for task prediction suggesting that it contains effects of both amplitude and phase. Therefore, zero-phase PLV may have functional significance beyond volume conduction. The interpretation of spatial filtering may be complicated by effects of phase.