Magnetic detection of sleep spindles in normal subjects

Nakasato, Nobukazu; Kado, H.; Nakanishi, Masakazu; Koyanagi, M.; Kasai, Nahoko; Niizuma, H; Yoshimoto, Takashi

doi:10.1016/0013-4694(90)90210-b

Cited by 25 publications

(15 citation statements)

References 22 publications

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“…Previous reports have shown that some spindles are recorded by MEG but not EEG, and vice versa [17], [20], [21], [22], and that intracranially recorded spindles often have no clear or consistent relationship to the spindles recorded simultaneously at the scalp [46], [47], [48], [52]. These observations would also be consistent with the view that MEG and EEG are recording from different brain systems during spindles.…”

Section: Discussionsupporting

confidence: 82%

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Divergent Cortical Generators of MEG and EEG during Human Sleep Spindles Suggested by Distributed Source Modeling

et al. 2010

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BackgroundSleep spindles are ∼1-second bursts of 10–15 Hz activity, occurring during normal stage 2 sleep. In animals, sleep spindles can be synchronous across multiple cortical and thalamic locations, suggesting a distributed stable phase-locked generating system. The high synchrony of spindles across scalp EEG sites suggests that this may also be true in humans. However, prior MEG studies suggest multiple and varying generators.Methodology/Principal FindingsWe recorded 306 channels of MEG simultaneously with 60 channels of EEG during naturally occurring spindles of stage 2 sleep in 7 healthy subjects. High-resolution structural MRI was obtained in each subject, to define the shells for a boundary element forward solution and to reconstruct the cortex providing the solution space for a noise-normalized minimum norm source estimation procedure. Integrated across the entire duration of all spindles, sources estimated from EEG and MEG are similar, diffuse and widespread, including all lobes from both hemispheres. However, the locations, phase and amplitude of sources simultaneously estimated from MEG versus EEG are highly distinct during the same spindles. Specifically, the sources estimated from EEG are highly synchronous across the cortex, whereas those from MEG rapidly shift in phase, hemisphere, and the location within the hemisphere.Conclusions/SignificanceThe heterogeneity of MEG sources implies that multiple generators are active during human sleep spindles. If the source modeling is correct, then EEG spindles are generated by a different, diffusely synchronous system. Animal studies have identified two thalamo-cortical systems, core and matrix, that produce focal or diffuse activation and thus could underlie MEG and EEG spindles, respectively. Alternatively, EEG spindles could reflect overlap at the sensors of the same sources as are seen from the MEG. Although our results generally match human intracranial recordings, additional improvements are possible and simultaneous intra- and extra-cranial measures are needed to test their accuracy.

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Section: Discussionsupporting

confidence: 82%

“…Further evidence against a monolithic distributed synchronous generator has been found in comparisons of simultaneous EEG and MEG (magnetoencephalogram) recordings during spindles. Spindles may appear only in the MEG, only EEG, or in both modalities [15], [17], [20], [21], [22] …”

Section: Introductionmentioning

confidence: 99%

Divergent Cortical Generators of MEG and EEG during Human Sleep Spindles Suggested by Distributed Source Modeling

et al. 2010

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“…The predominantly radial distribution of sleep changes, especially vertex waves and K-complexes (Lu et al, 1992;Nakasato et al, 1990;Numminen et al, 1996;Shih et al, 2000;Shiraishi et al, 2001), is mirrored in the generation of high-amplitude potentials in EEG, known to be dominated by radial activity. On the whole, a higher number of MEG spikes type 1 (54%) were associated with typical sleep changes like vertex waves, spindles, and K-complexes in EEG, compared with spikes type 2 (21%) ( Table 2).…”

Section: Influence Of Background Activity (Sleep Changes) On Detectionmentioning

confidence: 98%

MEG Versus EEG: Influence of Background Activity on Interictal Spike Detection

Ramantani

Boor²,

Paetau³

et al. 2006

Journal of Clinical Neurophysiology

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The comparative sensitivity of EEG and magnetoencephalography (MEG) in the visual detection of focal epileptiform activity in simultaneous interictal sleep recordings were investigated. The authors examined 14 patients aged 3.5 to 17 years with localization-related epilepsy. Simultaneous 122-channel whole-head MEG and 33-channel EEG were recorded for 20 to 40 minutes during spontaneous sleep. The EEG and MEG data were separated and four blinded independent reviewers marked the presence and timing of epileptic discharges (ED) in the 28 data segments. EEG and MEG data were matched and spikes identified by at least three reviewers were classified in three categories according to the following criteria: type 1 MEG > EEG, type 2 EEG > MEG (type 1/2: difference of three or more raters), and type 3 EEG = MEG (three or more raters each). The presence of simultaneous sleep changes was visually determined for every single EEG-segment. Spikes with high spatiotemporal correlation were averaged and subjected to single dipole analysis of peak activity in EEG. Out of 4704 marked patterns, 1387 spikes fulfilled the above criteria. In fact, more spikes were unique to MEG (689) than to EEG (136) and to the combination of both modalities (562). ED were detected predominantly by MEG in eight patients and by EEG in two patients. The presence of vertex waves and spindles lead to a significantly higher number of spikes identified only in MEG. Averaging of type 1 spikes produced clear spike activity in EEG in 9 of 12 cases. On the contrary, only 2 of 10 type 2 spikes were visible in MEG after averaging. Dipoles of spikes visible in MEG showed a more tangential orientation compared with more radial dipoles of type 2 spikes. Spike characteristics, e.g., dipole orientation, are a key factor for a sole EEG representation. Exclusive MEG detection is more likely influenced by overlapping background activity in EEG. Because MEG is indifferent to radial activity, i.e., sleep changes, a higher ratio of spikes unique to MEG compared with EEG is detected in the case of overlapping sleep changes.

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“…Recordings of electromagnetic fields indeed demonstrate this property (Gray et al 1989), with the 10-beats-per-second rhythm commonly seen over occipital regions on EEG also seen on MEG (Cuffin and Cohen 1979). Similarly, the 14-beat-per-second rhythm seen on EEG during sleep ("sleep spindles") has an MEG analog (Nakasato et al 1990). Various components of the cortical representation of the motor program are each associated with a distinct frequency, mainly in the 10-, 20-, and 40 Hz ranges (Hari and Salenius 1999).…”

Section: Fields In the Brainmentioning

confidence: 90%

Cognition without a Neural Code: How a Folded Cortex Might Think by Harmonizing Its Own Electromagnetic Fields

Erlich

2016

EJBM

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Extensive investigation of the brain's synaptic connectivity, the presumed material basis of cognition, has failed to explain how the brain thinks. Further, the neural code that purportedly allows the brain to coordinate synaptic modulation over wide areas of cortex has yet to be found and may not exist. An alternative approach, focusing on the possibility that the brain's internally generated electromagnetic fields might be biologically effective, leads to a model that solves this "binding problem." The model of cognition proposed here permits mind and consciousness to arise naturally from the brain as trains of signifying states, or stationarities. Neuronal circuits in suitably constructed hierarchies produce thought by reconciling themselves with each other through the forward-and back-broadcast of specific electromagnetic fields, executing a natural algorithm as a harmonized set is selected. Beyond the postulation that information is encoded in specifically organized electromagnetic fields, the only other "code" necessary is topographic, one that is already known. That the brain might use its own fields to think is supported by the literature on the widespread sensitivity of biological organisms to small, windowed fields. This model may help explain the coherence of the brain's fields, the conservation of the folded cortex, and, in its emphasis on a self-harmonizing process, the universality of the esthetic impulse as a projection of the brain's basic mechanism of thought. COGNITION BASED BOTH ON FIELDS AND ON SYNAPTIC CONNECTIVITYA ny credible model of thought must embody in a natural way the known physical features of the human brain. Such a model will encode a myriad of memory traces, and it will assemble them rapidly and reliably, excluding extraneous matter without having to consult any list of rules, for which there is no time or place. The model will automatically focus attention where attention is needed, and it will spontaneously apply an internal logic that leads to survivable behavior. At the same time, it will demonstrate the human capacity for loose associations, self-contradictions, and even wild delusions. The model must be self-reading (no homunculi allowed), self-validating, and self-conscious. A model of human cognition should perform as the brain does; it should be at once reliable and suspect, esthetic and erratic.Most such models rest on synaptic connectivity. Disappointingly, the study of neurons and their connections in the cortex has produced much detailed physiology and many wiring diagrams but no convincing model of how the cortex makes an image, let alone a thought (Felleman and Van Essen 1991;Van Essen 1997).Neuroscientists have demonstrated that the brain parses its tasks into multiple subunits, all of which involve toand-fro axonal conduction followed by modification of synaptic interconnectivity, and they argue that after abundant "parallel processing" the brain somehow integrates what it has previously divided. But it is not clear how interlocking webs of neurons can r...

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Magnetic detection of sleep spindles in normal subjects

Cited by 25 publications

References 22 publications

Divergent Cortical Generators of MEG and EEG during Human Sleep Spindles Suggested by Distributed Source Modeling

Divergent Cortical Generators of MEG and EEG during Human Sleep Spindles Suggested by Distributed Source Modeling

MEG Versus EEG: Influence of Background Activity on Interictal Spike Detection

Cognition without a Neural Code: How a Folded Cortex Might Think by Harmonizing Its Own Electromagnetic Fields

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