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Articles, Systems/Circuits

Emergence of Sensory Patterns during Sleep Highlights Differential Dynamics of REM and Non-REM Sleep Stages

Michal Ramot, Lior Fisch, Ido Davidesco, Michal Harel, Svetlana Kipervasser, Fani Andelman, Miri Y. Neufeld, Uri Kramer, Itzhak Fried and Rafael Malach
Journal of Neuroscience 11 September 2013, 33 (37) 14715-14728; DOI: https://doi.org/10.1523/JNEUROSCI.0232-13.2013
Michal Ramot
1Interdisciplinary Center for Neural Computation, The Hebrew University of Jerusalem, Jerusalem 91904, Israel,
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Lior Fisch
2Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel,
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Ido Davidesco
1Interdisciplinary Center for Neural Computation, The Hebrew University of Jerusalem, Jerusalem 91904, Israel,
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Michal Harel
2Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel,
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Svetlana Kipervasser
3EEG and Epilepsy Unit, Department of Neurology, and
5Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel, and
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Fani Andelman
4Functional Neurosurgery Unit, Tel Aviv Sourasky Medical Center, Tel Aviv 64239, Israel,
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Miri Y. Neufeld
3EEG and Epilepsy Unit, Department of Neurology, and
5Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel, and
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Uri Kramer
3EEG and Epilepsy Unit, Department of Neurology, and
5Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel, and
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Itzhak Fried
4Functional Neurosurgery Unit, Tel Aviv Sourasky Medical Center, Tel Aviv 64239, Israel,
6Department of Neurosurgery, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California 90095
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Rafael Malach
2Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel,
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  • Figure 1.
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    Figure 1.

    Experimental paradigm and calculation of HBB. a, Experimental paradigm. A 9 min segment from the engaging film The Good the Bad and the Ugly was presented to patients twice. b, Calculation of the smoothed HBB signal, which was used throughout the analysis. Arrows highlight times with high levels of gamma in the raw signal. c, Preparing the time courses for computing sham correlations: for each electrode in the second movie presentation, the time course was scrambled so that the second half of the time course was placed before the first half.

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    Figure 2.

    Location of sensory electrodes. Location of all sensory electrodes (electrodes whose HBB time course was highly reproducible across movie presentations) of all subjects on the brain. Electrodes are color coded according to their cross-movie correlation. A, Anterior; P, posterior.

  • Figure 3.
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    Figure 3.

    Example of functional organization patterns during awake and sleep states. a, Example time courses from a single patient from four different visual and auditory electrodes. The time courses of one visual and one auditory electrode were taken from the first movie presentation, and the others from the second movie presentation. Note the strong within-category correlation across movie repeats and the lack of between-category correlation. b, Correlation structure of all the sensory electrodes reflecting the underlying functional organization. The bottom left half depicts the correlation between the time course of each electrode in the first movie presentation (along the y-axis) and the time courses of electrodes in the second movie presentation (along the x-axis), while the top right half depicts the inverse. The diagonal depicts the correlation of each electrode with itself across movie presentations. Note the remarkable reproducibility of the functional organization reflected in the mirror symmetry across the diagonal, despite these being two independent datasets. The visual electrode pair plotted in a is circled in blue, the auditory electrode pair is circled in green, and the visual–auditory pair is circled in black. Inset, The location of these four electrodes on the brain. c, Average correlation structure of all sensory electrodes for all odd (bottom left) and even (top right) time windows during sleep. Same presentation and electrode pairs circled as those in b. This time the two diagonal halves separated by the black line are a combination of two separate matrices, depicting odd and even time windows—note again the highly reproducible symmetrical pattern, but also the robust common activation element (reflected in overall brighter colors) in the sleep pattern. d, Time courses of the same four electrodes as in a during 5 min of sleep. e, Electrode.

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    Figure 4.

    Visualizing the similarity of sleep patterns to sensory functional organization. Examples of endo-activations in two patients. Left panels, Correlation values of all electrode pairs across movie presentations, ordered in an outward spiral from the center of the square. Middle panels, The correlation values of the same electrode pairs during sleep, arranged in the same order as in the left panels (i.e., according to their correlation between movie presentations). Note the similarity between the movie and sleep structures, reflecting the endo-activation of the movie correlation pattern. Right panels, The same electrode pairs during sleep, only this time electrode pairs were ordered according to the sham correlations (see Materials and Methods). Note the lack of any structure in sleep when ordered according to the sham correlations. corr, Correlations.

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    Figure 5.

    The local component of endo-activation patterns. a, Left, Distribution of real endo-activation and sham levels across all time windows during sleep [correlation of the pattern in all sleep time windows with the cross-presentation movie pattern (red) and the sham pattern (blue)]. Middle, Distribution of endo-activation and sham of only the electrodes that contributed most to endo-activation, after projecting out their common signal. Right, The distribution (blue) of the endo-activation permutation test (see Materials and Methods). Red, green, and cyan dots indicate the means of the distributions of full endo-activation (depicted in the histogram in the left panel), endo-activation without a nearest neighbor, and endo-activation without two nearest neighbors, respectively. b, Location of all the electrodes of all subjects on the brain, color coded according to their contribution to endo-activation. Note the clustering of highly contributing electrodes in sensory cortices. Inset, The relationship between endo-activation contribution and sensory sensitivity; colors in the inset reflect data from different subjects. A, Anterior; P, posterior.

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    Figure 6.

    Endo-activation per patient. Electrode locations for each patient, shown on a reconstruction of his or her own brain. Electrodes are color-coded according to their contribution to endo-activation (compare Fig. 5b). Arrows show the pair of electrodes most highly correlated across movie presentations. A, Anterior; P, posterior.

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    Figure 7.

    Sleep staging from intracranial recordings. The inverse of the average delta power calculated from the LFP of all leads in this dataset throughout the night (black trace). Colors and stars indicate the sleep staging derived in a conventional manner (surface EEG, EOG, and EMG; see Materials and Methods) by a sleep expert. Blue denotes episodes scored as awake, orange denotes periods scored as REM sleep, and purple denotes periods scored as NREM sleep. Note the remarkable fit between the two, with the delta power clearly distinguishing between REM sleep/wakefulness and NREM sleep. Video monitoring was used to distinguish REM sleep from wakefulness.

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    Figure 8.

    Endo-activation dynamics. Degree of endo-activation throughout the night, superimposed on the various sleep stages. Note the consistently higher endo-activation during NREM sleep. Using the same visualization as in Figure 4, the red frame illustrates electrode correlations during sleep taken from a moment with high endo-activation (marked by red dot), while green shows the same electrode correlations taken from a moment of low endo-activation (marked by green dot). The black frame shows the average difference between NREM and REM endo-activation for all subjects (red dot) versus a random distribution (permutation test: blue, distribution; cyan, mean), and the mean NREM–REM difference for sham data (green).

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    Figure 9.

    Relationship between global correlations and momentary correlations to sleep template. Strength of global (averaged across all pairs) correlation (x-axis) plotted versus distance from REM/NREM templates accordingly (defined as 1 minus the correlation between the template and the momentary pattern; y-axis) for each momentary 5 min correlation structure of either REM sleep (blue) or NREM sleep (red). Data from all subjects plotted together, over 2000 data points for each sleep state in total. Note the striking increase in the range of momentary templates in REM compared with NREM sleep.

Tables

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    Table 1.

    Patient information table

    Patient no.GenderAgeElectrodesLocation
    1M2849LH: Tem, Occ, Fro; RH: Tem, Fro
    2M4547LH: Tem Fro; RH: Tem, Fro
    3F1871RH: Tem, Par, Occ
    4F4141LH: Tem; RH: Tem, Par, Fro
    5F3353LH: Tem Fro; RH: Tem, Fro
    6M3666RH: Tem, Fro, Par, Occ
    7F1661LH: Tem, Fro, Par, Occ
    • Electrodes, Number of electrodes analyzed after subtraction of trigger electrodes (used to synchronize the stimuli and ECoG recordings) and electrodes with bad leads; LH, left hemisphere; RH, right hemisphere; Tem, temporal; Occ, occipital; Fro, frontal; Par, parietal; M, male; F, female.

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The Journal of Neuroscience: 33 (37)
Journal of Neuroscience
Vol. 33, Issue 37
11 Sep 2013
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Emergence of Sensory Patterns during Sleep Highlights Differential Dynamics of REM and Non-REM Sleep Stages
Michal Ramot, Lior Fisch, Ido Davidesco, Michal Harel, Svetlana Kipervasser, Fani Andelman, Miri Y. Neufeld, Uri Kramer, Itzhak Fried, Rafael Malach
Journal of Neuroscience 11 September 2013, 33 (37) 14715-14728; DOI: 10.1523/JNEUROSCI.0232-13.2013

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Emergence of Sensory Patterns during Sleep Highlights Differential Dynamics of REM and Non-REM Sleep Stages
Michal Ramot, Lior Fisch, Ido Davidesco, Michal Harel, Svetlana Kipervasser, Fani Andelman, Miri Y. Neufeld, Uri Kramer, Itzhak Fried, Rafael Malach
Journal of Neuroscience 11 September 2013, 33 (37) 14715-14728; DOI: 10.1523/JNEUROSCI.0232-13.2013
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