Deep brain activities can be detected with magnetoencephalography

Pizzo, Francesca; Roehri, Nicolas; Villalon, Samuel Médina; Trébuchon, Agnès; Chen, S.; Lagarde, Stanislas; Carron, Romain; Gavaret, Martine; Giusiano, Bernard; McGonigal, Aileen; Bartolomei, Fabricē; Badier, Jean‐Michel; Bénar, Christian‐George

doi:10.1038/s41467-019-08665-5

Cited by 187 publications

(166 citation statements)

References 70 publications

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“…Reassuringly, recent simultaneous intracerebral electrophysiological and MEG recordings (Pizzo et al, 2019) have led to similar observations, with the invasively recorded hippocampal source giving rise to a strong, yet unilateral, temporal lobe signal.…”

Section: A B C 15mentioning

confidence: 64%

Mouth magnetoencephalography: A unique perspective on the human hippocampus

Tierney

Levy

Barry

et al. 2020

Preprint

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Traditional magnetoencephalographic (MEG) brain imaging scanners consist of a rigid sensor array surrounding the head; this means that they are maximally sensitive to superficial brain structures.New technology based on optical pumping means that we can now consider more flexible and creative sensor placement. Here we explored the magnetic fields generated by a model of the human hippocampus not only across scalp but also at the roof of the mouth. We found that simulated hippocampal sources gave rise to dipolar field patterns with one scalp surface field extremum at the temporal lobe and a corresponding maximum or minimum at the roof of the mouth. We then constructed a fitted dental mould to accommodate an Optically Pumped Magnetometer (OPM). We collected data using a previously validated hippocampal-dependent task to test the empirical utility of a mouth-based sensor, with an accompanying array of left and right temporal lobe OPMs. We found that the mouth sensor showed the greatest task-related theta power change. We also found that, as predicted by the simulations, the mouth sensor was anti-correlated with those on over the temporal lobes. We found that this sensor had a mild effect on the reconstructed power in the hippocampus (~10% change) but that coherence images between the mouth sensor and reconstructed source images showed a global maximum in the right hippocampus. We conclude that augmenting a scalpbased MEG array with sensors in the mouth shows unique promise for both basic scientists and clinicians interested in interrogating the hippocampus.

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Section: A B C 15mentioning

confidence: 64%

Mouth magnetoencephalography: A unique perspective on the human hippocampus

Tierney

Levy

Barry

et al. 2020

Preprint

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“…Nonetheless, it is worth to consider that the sensitivity of MEG (80), and thereby the quality of the source reconstruction, tends to decay with the depth of the analysed brain structure. Hence, the analysis involving the basal ganglia is based on a reconstructed signal that may have suboptimal resolution (as compared to the cortical data).However, it has recently been shown that magnetoencephalography can indeed detect the activity of deep brain sources (81)(82)(83).…”

Section: Discussionmentioning

confidence: 99%

Extensive functional repertoire underpins complex behaviours: insights from Parkinson’s disease

Sorrentino

Rucco

Baselice

et al. 2019

Preprint

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Rapid reconfigurations of brain activity support efficient neuronal communication and flexible behaviour. Suboptimal brain dynamics impair this adaptability, possibly leading to functional deficiencies. We hypothesize that impaired flexibility in brain activity can lead to motor and cognitive symptoms of Parkinson's disease (PD). To test this hypothesis, we studied the 'functional repertoire' the number of distinct configurations of neural activityusing source-reconstructed magnetoencephalography in PD patients and controls. We found stereotyped brain dynamics and reduced flexibility in PD. The intensity of this reduction was proportional to symptoms severity, and explained by beta-band hyper-synchronization. Moreover, the basal ganglia were prominently involved in the abnormal patterns of brain activity. Our findings support the hypotheses that: symptoms in PD reflect impaired brain flexibility, this impairment preferentially involves the basal ganglia, and beta-band hypersynchronization is associated with reduced brain flexibility. These findings highlight the importance of extensive functional repertoires for behaviour and motor.Parkinson's disease (PD) is a severe and disabling neurodegenerative disorder. It is characterized by reduced amplitude of movements, and slowing of cognitive processes, imposing major individual and social burden (24). The main histopathological finding in PD is a severe nigrostriatal dopamine depletion (25,26). PD has traditionally been regarded predominantly as a motor disease. However, recent clinical and neuroimaging findings have questioned these views (27). For example, the first symptoms to appear are often not motor, and the clinical phenotype clearly goes well beyond the motor impairment, with other domains, such as executive functioning, involved (28,29). Structural Magnetic Resonance Imaging (MRI) has also confirmed that PD is more widespread than previously thought (27). Although functional magnetic resonance (fMRI) studies have identified impairment in the corticostriatal network in PD patients, the observed changes in functional connectivity extend into many other brain systems (30). Similarly, magnetoencephalography (MEG) studies have also reported widespread functional connectivity alterations in PD (31-34) .The brain can be represented as a network, with, at the macro-scale, brain areas as 'nodes' and structural or functional relationships between the brain areas as 'edges ' (35, 36), following which the topology of the network can be characterised using graph theory. A rapidly growing body of research now uses graph theory to characterize large-scale patterns of brain activation in health (37) and disease (38). Graph theory has highlighted the multifaceted nature of large-scale interactions in PD, with studies reporting more-connected networks (39-42), less-connected networks (43-48), and a combination of both (49,50). However, most research in this area has assumed brain activity to be stationary, and did not explore the structure of dynamic fluctuations in activity...

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“…It has been debated whether MEG is sensitive enough to measure signals from deep brain structures, such as the hippocampus. In recent years, however, a consensus has emerged that, given proper source reconstruction techniques, MEG is indeed able to measure signals from the hippocampus (Dalal et al, 2013;Pu et al, 2018;Pizzo et al, 2019). We furthermore note that we did not start with an anatomical hippocampus-based region of interest and test the signals coming from that region, but instead used a data-driven approach which subsequently yielded the hippocampus as a strong and significant source of sensor-level effects.…”

Section: Hippocampal and Prefrontal Theta Activity Underlies Learningmentioning

confidence: 99%

Implicit learning and exploitation of regularities involve hippocampal and prefrontal theta activity

Spaak

Lange

2019

Preprint

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Observers rapidly and seemingly automatically learn to predict where to expect relevant items when those items are repeatedly presented in the same spatial context. This form of statistical learning in visual search has been studied extensively using a paradigm known as contextual cueing. The neural mechanisms underlying the learning and exploiting of such regularities remain unclear. We sought to elucidate these by examining behaviour and recording neural activity using magneto-encephalography (MEG) while observers were implicitly acquiring and exploiting statistical regularities. Computational modelling of behavioural data suggested that after repeated exposures to a spatial context, participants' behaviour was marked by an abrupt switch to an exploitation strategy of the learnt regularities. MEG recordings showed that the initial learning phase was associated with larger hippocampal theta band activity for repeated scenes, while the subsequent exploitation phase showed larger prefrontal theta band activity for these repeated scenes. Strikingly, the behavioural benefit of repeated exposures to certain scenes was inversely related to explicit awareness of such repeats, demonstrating the implicit nature of the expectations acquired. This elucidates how theta activity in the hippocampus and prefrontal cortex underpins the implicit learning and exploitation of spatial statistical regularities to optimize visual search behaviour.

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Deep brain activities can be detected with magnetoencephalography

Cited by 187 publications

References 70 publications

Mouth magnetoencephalography: A unique perspective on the human hippocampus

Mouth magnetoencephalography: A unique perspective on the human hippocampus

Extensive functional repertoire underpins complex behaviours: insights from Parkinson’s disease

Implicit learning and exploitation of regularities involve hippocampal and prefrontal theta activity

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