The natural frequencies of the resting human brain: an MEG-based atlas

Brain oscillations are considered to play a pivotal role in neural communication. However, detailed information regarding the typical oscillatory patterns of individual brain regions is surprisingly scarce. In this study we applied a multivariate data-driven approach to create an atlas of the natural frequencies of the resting human brain on a voxel-by-voxel basis. We analysed resting-state magnetoencephalography (MEG) data from 128 healthy adult volunteers obtained from the Open MEG Archive (OMEGA). Spectral power was computed in source space in 500 ms steps for 82 frequency bins logarithmically spaced from 1.7 to 99.5 Hz. We then applied k-means clustering to detect characteristic spectral profiles and to eventually identify the natural frequency of each voxel. Our results revealed a region-specific organisation of intrinsic oscillatory activity, following both a medial-to-lateral and a posterior-to-anterior gradient of increasing frequency. In particular, medial fronto-temporal regions were characterised by slow rhythms (delta/theta). Posterior regions presented natural frequencies in the alpha band, although with differentiated generators in the precuneus and in sensory-specific cortices (i.e., visual and auditory). Somatomotor regions were distinguished by the mu rhythm, while the lateral prefrontal cortex was characterised by oscillations in the high beta range (>20 Hz). Importantly, the brain map of natural frequencies was highly replicable in two independent subsamples of individuals. To the best of our knowledge, this is the most comprehensive atlas of ongoing oscillatory activity performed to date. Furthermore, the identification of natural frequencies is a fundamental step towards a better understanding of the functional architecture of the human brain.

Emerging Roles of Microglia in Neuro-vascular Unit: Implications of Microglia-Neurons Interactions

Microglia, which serve as the defensive interface of the nervous system, are activated in many neurological diseases. Their role as immune responding cells has been extensively studied in the past few years. Recent studies have demonstrated that neuronal feedback can be shaped by the molecular signals received and sent by microglia. Altered neuronal activity or synaptic plasticity leads to the release of various communication messages from neurons, which in turn exert effects on microglia. Research on microglia-neuron communication has thus expanded from focusing only on neurons to the neurovascular unit (NVU). This approach can be used to explore the potential mechanism of neurovascular coupling across sophisticated receptor systems and signaling cascades in health and disease. However, it remains unclear how microglia-neuron communication happens in the brain. Here, we discuss the functional contribution of microglia to synapses, neuroimmune communication, and neuronal activity. Moreover, the current state of knowledge of bidirectional control mechanisms regarding interactions between neurons and microglia are reviewed, with a focus on purinergic regulatory systems including ATP-P2RY12R signaling, ATP-adenosine-A1Rs/A2ARs, and the ATP-pannexin 1 hemichannel. This review aims to organize recent studies to highlight the multifunctional roles of microglia within the neural communication network in health and disease.

Brain network topology and personality traits: a source level magnetoencephalographic study

Personality neuroscience is focusing on the correlation between individual differences and the efficiency of large-scale networks from the perspective of the brain as an interconnected network. A suitable technique to explore this relationship is the magnetoencephalography (MEG), but little are MEG studies aimed at investigating topological properties correlated to personality traits. By using MEG, the present study is aimed at evaluating how individual differences described in Cloninger’s psychobiological model are correlated with specific cerebral structures. Fifty healthy individuals (20 males, 30 females, mean age: 27.4 ± 4.8 years) underwent Temperament and Character Inventory examination and MEG recording during a resting state condition. High harm avoidance scores were associated with a reduced centrality of the left caudate nucleus and this negative correlation was maintained in females when we analyzed gender differences. Our data suggest that the caudate nucleus plays a key role in adaptive behavior and could be a critical node in insular salience network. The clear difference between males and females allows us to suggest that topological organization correlated to personality is highly dependent on gender. Our findings provide new insights to evaluate the mutual influences of topological and functional connectivity in neural communication efficiency and disruption as biomarkers of psychopathological traits.

White Matter Signals Reflect Information Transmission Between Brain Regions During Seizures

White matter supports critical brain functions such as learning and memory, modulates the distribution of action potentials, and acts as a relay of neural communication between different brain regions. Interestingly, neuronal cell bodies exist in deeper white matter tissue, neurotransmitter vesicles are released directly in white matter, and white matter blood-oxygenation level dependent (BOLD) signals are detectable across a range of different tasks -- all appearing to reflect intrinsic electrical signals in white matter. Yet, such signals within white matter have largely been ignored. Here, we elucidate the properties of white matter signals using intracranial EEG. We show that such signals capture the communication between brain regions and differentiate pathophysiologies of epilepsy. In direct contradiction to past assumptions about white matter inactivity, we show that white matter recordings can elucidate brain function and pathophysiology not apparent in gray matter. Broadly, white matter functional recordings acquired through implantable devices may provide a wealth of currently untapped knowledge about the neurobiology of disease.

Mapping electromagnetic networks to haemodynamic networks in the human brain

Whole-brain neural communication is typically estimated from statistical associations among electromagnetic or haemodynamic time-series. The relationship between functional network architectures recovered from these two types of neural activity remains unknown. Here we map electromagnetic networks (measured using magnetoencephalography; MEG) to haemodynamic networks (measured using functional magnetic resonance imaging; fMRI). We find that the relationship between the two modalities is regionally heterogeneous and systematically follows the cortical hierarchy, with close correspondence in unimodal cortex and poor correspondence in transmodal cortex, potentially reflecting patterns of laminar differentiation, recurrent subcortical input and neurovascular coupling. Correspondence between the two is largely driven by slower rhythms, particularly the delta (2-4 Hz) and beta (15-29 Hz) frequency band. Moreover, haemodynamic connectivity cannot be explained by electromagnetic activity in a single frequency band, but rather arises from the mixing of multiple neurophysiological rhythms. Collectively, these findings demonstrate highly organized but only partly overlapping patterns of connectivity in MEG and fMRI functional networks, opening fundamentally new avenues for studying the relationship between cortical micro-architecture and multi-modal connectivity patterns.

Abstract P373: The Occurrence Of Neurovascular And Adipose Neuropathy In The Genetically Diverse Het3 Mouse With Aging

Energy homeostasis and adipose tissue metabolism are regulated in large part through peripheral sympathetic nerve innervation of metabolically important tissues and organs. This neural communication from the brain to adipose tissues results in release of the neurotransmitter norepinephrine that regulates energy expenditure through modulation of lipolysis, adipogenesis, ‘browning’ (development of brown adipocytes in white adipose depots), and non-shivering thermogenesis. Subcutaneous white adipose tissue (scWAT) is an energy storing tissue that is highly plastic, responding to metabolic need by changing mass and cellularity, as well as responding to challenges (including cold temperature, exercise, fasting) by modifying neural activity and metabolism. Within scWAT lies a dense bed of nerves and blood vessels that are integrated closely, and in large part, rely on one another to function properly. Even if not directly innervating the blood vessels themselves (as is the case with capillaries), neurites that appear to innervate single adipocytes use these blood vessels as scaffolding to traverse the tissue. We have recently demonstrated that under pathological conditions (obesity and aging), scWAT innervation decreases through a process termed ‘adipose neuropathy’. With advanced age the small fiber peripheral nerve endings in adipose die back, including reducing contact with adipose-resident blood vessels (as observed previously in the C57BL6/J mouse). This likely poses a physiological challenge for metabolism and for vascular or adipose tissue health and function. For this work, we compared C57BL6/J mice with the more genetically diverse HET3 mouse model, established for the NIA’s Intervention Testing Program to more accurately represent the variability of age-related mortality/morbidity. We investigated incidence of peripheral neuropathy with aging (skin, scWAT muscle) as well as changes to the neurovascular supply of scWAT across several ages in both males and females. We also investigated the anti-aging drug Rapamycin as a potential means to prevent or reduce adipose neuropathy. We found that HET3 mice display a reduced neuropathy phenotype compared to inbred C56BL6/J mice. Importantly, the nerve die-back around blood vessels was not observed in the HET3 model. However, male HET3 mice did reveal neuropathic phenotypes by 62wks of age, characterized by decreased mechanoreception in hind paw skin, reduced NMJ occupation, and decreased expression of the Schwann cell marker Sox10 in scWAT. Female HET3 mice appeared to have increased protection from neuropathy until advanced age (126wks) when they began to show stronger phenotypes than males (excluding Sox10 analysis.) Despite its success as a longevity treatment in mice, rapamycin had little to no effect on reducing or preventing the onset of adipose neuropathy.

Optogenetic activation of the distal colon epithelium engages enteric nervous system circuits to initiate motility patterns

Background & Aims: Digestive functions of the colon depend on sensory-motor reflexes in the enteric nervous system (ENS), initiated by intrinsic primary afferent neurons (IPANs). IPAN terminals project to the mucosal layer of the colon, allowing communication with epithelial cells comprising the colon lining. The chemical nature and functional significance of this epithelial-neural communication in regards to secretion and colon motility are of high interest. Colon epithelial cells can produce and release neuroactive substances such as ATP and 5-HT, which can activate receptors on adjacent nerve fibers, including IPAN subtypes. In this study we examined if stimulation of epithelial cells alone is sufficient to activate neural circuits that control colon motility. Methods: Optogenetics and calcium imaging were used in ex vivo preparations of the mouse colon to selectively stimulate the colon epithelium, measure changes in motility and record activity of neurons within the myenteric plexus. Results: Light-mediated activation of epithelial cells lining the distal, but not proximal, colon caused local contractions and increased the rate of colonic migrating motor complexes. Epithelial-evoked local contractions in the distal colon were reduced by both ATP and 5-HT receptor antagonists. Conclusions: Our findings indicate that colon epithelial cells likely utilize purinergic and serotonergic signaling to initiate activity in myenteric neurons, produce local contractions and facilitate large-scale coordination of ENS activity responsible for whole-colon motility patterns.

Learning to be on time: temporal coordination of neural dynamics by activity-dependent myelination

Activity-dependent myelination is the mechanism by which myelin changes as a function of neural activity, and plays a fundamental role in brain plasticity. Mediated by structural changes in glia, activity-dependent myelination regulates axonal conduction velocity. It remains unclear how neural activity impacts myelination to orchestrate the timing of neural signaling. We developed a model of spiking neurons enhanced with neuron-glia feedback. Inspired by experimental data and use-dependent synaptic plasticity, we introduced a learning rule, called the Activity-Dependent Myelination (ADM) rule, by which conduction velocity scales with firing rates. We found that the ADM rule implements a homeostatic control mechanism that promotes and preserves synchronization. ADM-mediated plasticity was found to optimize synchrony by compensating for variability in axonal lengths by scaling conduction velocity in an axon-specific way. This property was maintained even when the network structure is altered. We further explored how external stimuli interact with the ADM rule to trigger bidirectional and reversible changes in conduction delays. These results highlight the role played by activity-dependent myelination in synchronous neural communication and brain plasticity.

Can fMRI functional connectivity index dynamic neural communication?

In order to continuously respond to a changing environment and support self-generating cognition and behaviour, neural communication must be highly flexible and dynamic at the same time than hierarchically organized. While whole-brain fMRI measures have revealed robust yet changing patterns of statistical dependencies between regions, it is not clear whether these statistical patterns (referred to as functional connectivity) can reflect dynamic large-scale communication in a way that is relevant to cognition. For functional connectivity to reflect actual communication, we propose three necessary conditions: it must span sufficient temporal complexity to support the needs of cognition while still being highly organized so that the system behaves reliably; it must be able to adapt to the current behavioural context; and it must exhibit fluctuations at sufficiently short timescales. In this paper, we introduce principal components of connectivity analysis (PCCA), an approach based on running principal component analysis on multiple runs of a time-varying functional connectivity model to show that functional connectivity follows low- yet multi-dimensional trajectories that can be reliably measured, and that these trajectories meet the aforementioned criteria to index flexible communication between neural populations and support moment-to-moment cognition.

Spatiotemporal dynamics of maximal and minimal EEG spectral power

Oscillatory neural activities are prevalent in the brain with their phase realignment contributing to the coordination of neural communication. Phase realignments may have especially strong (or weak) impact when neural activities are strongly synchronized (or desynchronized) within the interacting populations. We report that the spatiotemporal dynamics of strong regional synchronization measured as maximal EEG spectral power—referred to as activation—and strong regional desynchronization measured as minimal EEG spectral power—referred to as suppression—are characterized by the spatial segregation of small-scale and large-scale networks. Specifically, small-scale spectral-power activations and suppressions involving only 2–7% (1–4 of 60) of EEG scalp sites were prolonged (relative to stochastic dynamics) and consistently co-localized in a frequency specific manner. For example, the small-scale networks for θ, α, β1, and β2 bands (4–30 Hz) consistently included frontal sites when the eyes were closed, whereas the small-scale network for γ band (31–55 Hz) consistently clustered in medial-central-posterior sites whether the eyes were open or closed. Large-scale activations and suppressions involving over 17–30% (10–18 of 60) of EEG sites were also prolonged and generally clustered in regions complementary to where small-scale activations and suppressions clustered. In contrast, intermediate-scale activations and suppressions (involving 7–17% of EEG sites) tended to follow stochastic dynamics and were less consistently localized. These results suggest that strong synchronizations and desynchronizations tend to occur in small-scale and large-scale networks that are spatially segregated and frequency specific. These synchronization networks may broadly segregate the relatively independent and highly cooperative oscillatory processes while phase realignments fine-tune the network configurations based on behavioral demands.