62 research outputs found

    Human hypocretin and melanin-concentrating hormone levels are linked to emotion and social interaction.

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    The neurochemical changes underlying human emotions and social behaviour are largely unknown. Here we report on the changes in the levels of two hypothalamic neuropeptides, hypocretin-1 and melanin-concentrating hormone, measured in the human amygdala. We show that hypocretin-1 levels are maximal during positive emotion, social interaction and anger, behaviours that induce cataplexy in human narcoleptics. In contrast, melanin-concentrating hormone levels are minimal during social interaction, but are increased after eating. Both peptides are at minimal levels during periods of postoperative pain despite high levels of arousal. Melanin-concentrating hormone levels increase at sleep onset, consistent with a role in sleep induction, whereas hypocretin-1 levels increase at wake onset, consistent with a role in wake induction. Levels of these two peptides in humans are not simply linked to arousal, but rather to specific emotions and state transitions. Other arousal systems may be similarly emotionally specialized

    Bimodal coupling of ripples and slower oscillations during sleep in patients with focal epilepsy.

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    OBJECTIVE: Differentiating pathologic and physiologic high-frequency oscillations (HFOs) is challenging. In patients with focal epilepsy, HFOs occur during the transitional periods between the up and down state of slow waves. The preferred phase angles of this form of phase-event amplitude coupling are bimodally distributed, and the ripples (80-150 Hz) that occur during the up-down transition more often occur in the seizure-onset zone (SOZ). We investigated if bimodal ripple coupling was also evident for faster sleep oscillations, and could identify the SOZ. METHODS: Using an automated ripple detector, we identified ripple events in 40-60 min intracranial electroencephalography (iEEG) recordings from 23 patients with medically refractory mesial temporal lobe or neocortical epilepsy. The detector quantified epochs of sleep oscillations and computed instantaneous phase. We utilized a ripple phasor transform, ripple-triggered averaging, and circular statistics to investigate phase event-amplitude coupling. RESULTS: We found that at some individual recording sites, ripple event amplitude was coupled with the sleep oscillatory phase and the preferred phase angles exhibited two distinct clusters (p \u3c 0.05). The distribution of the pooled mean preferred phase angle, defined by combining the means from each cluster at each individual recording site, also exhibited two distinct clusters (p \u3c 0.05). Based on the range of preferred phase angles defined by these two clusters, we partitioned each ripple event at each recording site into two groups: depth iEEG peak-trough and trough-peak. The mean ripple rates of the two groups in the SOZ and non-SOZ (NSOZ) were compared. We found that in the frontal (spindle, p = 0.009; theta, p = 0.006, slow, p = 0.004) and parietal lobe (theta, p = 0.007, delta, p = 0.002, slow, p = 0.001) the SOZ incidence rate for the ripples occurring during the trough-peak transition was significantly increased. SIGNIFICANCE: Phase-event amplitude coupling between ripples and sleep oscillations may be useful to distinguish pathologic and physiologic events in patients with frontal and parietal SOZ

    Fast Ripples Reflect Increased Excitability That Primes Epileptiform Spikes

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    The neuronal circuit disturbances that drive inter-ictal and ictal epileptiform discharges remain elusive. Using a combination of extra-operative macro-electrode and micro-electrode inter-ictal recordings in six pre-surgical patients during non-rapid eye movement sleep, we found that, exclusively in the seizure onset zone, fast ripples (200–600 Hz), but not ripples (80–200 Hz), frequently occur \u3c300 ms before an inter-ictal intra-cranial EEG spike with a probability exceeding chance (bootstrapping, P \u3c 1e−5). Such fast ripple events are associated with higher spectral power (P \u3c 1e−10) and correlated with more vigorous neuronal firing than solitary fast ripple (generalized linear mixed-effects model, P \u3c 1e−9). During the intra-cranial EEG spike that follows a fast ripple, action potential firing is lower than during an intra-cranial EEG spike alone (generalized linear mixed-effects model, P \u3c 0.05), reflecting an inhibitory restraint of intra-cranial EEG spike initiation. In contrast, ripples do not appear to prime epileptiform spikes. We next investigated the clinical significance of pre-spike fast ripple in a separate cohort of 23 patients implanted with stereo EEG electrodes, who underwent resections. In non-rapid eye movement sleep recordings, sites containing a high proportion of fast ripple preceding intra-cranial EEG spikes correlate with brain areas where seizures begin more than solitary fast ripple (P \u3c 1e−5). Despite this correlation, removal of these sites does not guarantee seizure freedom. These results are consistent with the hypothesis that fast ripple preceding EEG spikes reflect an increase in local excitability that primes EEG spike discharges preferentially in the seizure onset zone and that epileptogenic brain regions are necessary, but not sufficient, for initiating inter-ictal epileptiform discharges

    Graph Theoretical Measures of Fast Ripple Networks Improve the Accuracy of Post-operative Seizure Outcome Prediction

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    Fast ripples (FR) are a biomarker of epileptogenic brain, but when larger portions of FR generating regions are resected seizure freedom is not always achieved. To evaluate and improve the diagnostic accuracy of FR resection for predicting seizure freedom we compared the FR resection ratio (RR) with FR network graph theoretical measures. In 23 patients FR were semi-automatically detected and quantified in stereo EEG recordings during sleep. MRI normalization and co-registration localized contacts and relation to resection margins. The number of FR, and graph theoretical measures, which were spatial (i.e., FR rate-distance radius) or temporal correlational (i.e., FR mutual information), were compared with the resection margins and with seizure outcome We found that the FR RR did not correlate with seizure-outcome (p \u3e 0.05). In contrast, the FR rate-distance radius resected difference and the FR MI mean characteristic path length RR did correlate with seizure-outcome (p \u3c 0.05). Retesting of positive FR RR patients using either FR rate-distance radius resected difference or the FR MI mean characteristic path length RR reduced seizure-free misclassifications from 44 to 22% and 17%, respectively. These results indicate that graph theoretical measures of FR networks can improve the diagnostic accuracy of the resection of FR events for predicting seizure freedom

    Ripples Have Distinct Spectral Properties and Phase-Amplitude Coupling With Slow Waves, but Indistinct Unit Firing, in Human Epileptogenic Hippocampus

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    Ripple oscillations (80–200 Hz) in the normal hippocampus are involved in memory consolidation during rest and sleep. In the epileptic brain, increased ripple and fast ripple (200–600 Hz) rates serve as a biomarker of epileptogenic brain. We report that both ripples and fast ripples exhibit a preferred phase angle of coupling with the trough-peak (or On-Off) state transition of the sleep slow wave in the hippocampal seizure onset zone (SOZ). Ripples on slow waves in the hippocampal SOZ also had a lower power, greater spectral frequency, and shorter duration than those in the non-SOZ. Slow waves in the mesial temporal lobe modulated the baseline firing rate of excitatory neurons, but did not significantly influence the increased firing rate associated with ripples. In summary, pathological ripples and fast ripples occur preferentially during the On-Off state transition of the slow wave in the epileptogenic hippocampus, and ripples do not require the increased recruitment of excitatory neurons.Fil: Weiss, Shennan A.. Thomas Jefferson University; Estados UnidosFil: Song, Inkyung. Thomas Jefferson University; Estados UnidosFil: Leng, Mei. University of California at Los Angeles; Estados UnidosFil: Pastore, Tomás. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Fernandez Slezak, Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Waldman, Zachary. Thomas Jefferson University; Estados UnidosFil: Orosz, Iren. University of California at Los Angeles; Estados UnidosFil: Gorniak, Richard. Thomas Jefferson University; Estados UnidosFil: Donmez, Mustafa. Thomas Jefferson University; Estados UnidosFil: Sharan, Ashwini. Thomas Jefferson University; Estados UnidosFil: Wu, Chengyuan. Thomas Jefferson University; Estados UnidosFil: Fried, Itzhak. University of California at Los Angeles; Estados UnidosFil: Sperling, Michael R.. Thomas Jefferson University; Estados UnidosFil: Bragin, Anatol. University of California at Los Angeles; Estados UnidosFil: Engel, Jerome. University of California at Los Angeles; Estados UnidosFil: Nir, Yuval. Tel Aviv University; IsraelFil: Staba, Richard. University of California at Los Angeles; Estados Unido

    Delta oscillation coupled propagating fast ripples precede epileptiform discharges in patients with focal epilepsy.

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    Epileptiform spikes are used to localize epileptogenic brain tissue. The mechanisms that spontaneously trigger epileptiform discharges are not yet elucidated. Pathological fast ripple (FR, 200-600 Hz) are biomarkers of epileptogenic brain, and we postulated that FR network interactions are involved in generating epileptiform spikes. Using macroelectrode stereo intracranial EEG (iEEG) recordings from a cohort of 46 patients we found that, in the seizure onset zone (SOZ), propagating FR were more often followed by an epileptiform spike, as compared with non-propagating FR (p \u3c 0.05). Propagating FR had a distinct frequency and larger power (p \u3c 1e-10) and were more strongly phase coupled to the peak of iEEG delta oscillation, which likely correspond with the DOWN states during non-REM sleep (p \u3c 1e-8), than non-propagating FR. While FR propagation was rare, all FR occurred with the highest probability within +/- 400 msec of epileptiform spikes with superimposed high-frequency oscillations (p \u3c 0.05). Thus, a sub-population of epileptiform spikes in the SOZ, are preceded by propagating FR that are coordinated by the DOWN state during non-REM sleep

    Delta Oscillation Coupled Propagating Fast Ripples Precede Epileptiform Discharges in Patients With Focal Epilepsy

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    Epileptiform spikes are used to localize epileptogenic brain tissue. The mechanisms that spontaneously trigger epileptiform discharges are not yet elucidated. Pathological fast ripple (FR, 200–600 Hz) are biomarkers of epileptogenic brain, and we postulated that FR network interactions are involved in generating epileptiform spikes. Using macroelectrode stereo intracranial EEG (iEEG) recordings from a cohort of 46 patients we found that, in the seizure onset zone (SOZ), propagating FR were more often followed by an epileptiform spike, as compared with non-propagating FR (p \u3c 0.05). Propagating FR had a distinct frequency and larger power (p \u3c 1e-10) and were more strongly phase coupled to the peak of iEEG delta oscillation, which likely correspond with the DOWN states during non-REM sleep (p \u3c 1e-8), than non-propagating FR. While FR propagation was rare, all FR occurred with the highest probability within +/− 400 msec of epileptiform spikes with superimposed high-frequency oscillations (p \u3c 0.05). Thus, a sub-population of epileptiform spikes in the SOZ, are preceded by propagating FR that are coordinated by the DOWN state during non-REM sleep

    Characterization, sources and reactivity of volatile organic compounds (VOCs) in Seoul and surrounding regions during KORUS-AQ

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    The Korea-United States Air Quality Study (KORUS-AQ) took place in spring 2016 to better understand air pollution in Korea. In support of KORUS-AQ, 2554 whole air samples (WAS) were collected aboard the NASA DC-8 research aircraft and analyzed for 82 C₁–C₁₀ volatile organic compounds (VOCs) using multi-column gas chromatography. Together with fast-response measurements from other groups, the air samples were used to characterize the VOC composition in Seoul and surrounding regions, determine which VOCs are major ozone precursors in Seoul, and identify the sources of these reactive VOCs. (1) The WAS VOCs showed distinct signatures depending on their source origins. Air collected over Seoul had abundant ethane, propane, toluene and n-butane while plumes from the Daesan petrochemical complex were rich in ethene, C₂–C₆ alkanes and benzene. Carbonyl sulfide (COS), CFC-113, CFC-114, carbon tetrachloride (CCl₄) and 1,2-dichloroethane were good tracers of air originating from China. CFC-11 was also elevated in air from China but was surprisingly more elevated in air over Seoul. (2) Methanol, isoprene, toluene, xylenes and ethene were strong individual contributors to OH reactivity in Seoul. However methanol contributed less to ozone formation based on photochemical box modeling, which better accounts for radical chemistry. (3) Positive Matrix Factorization (PMF) and other techniques indicated a mix of VOC source influences in Seoul, including solvents, traffic, biogenic, and long-range transport. The solvent and traffic sources were roughly equal using PMF, and the solvents source was stronger in the KORUS-AQ emission inventory. Based on PMF, ethene and propene were primarily associated with traffic, and toluene, ethylbenzene and xylenes with solvents, especially non-paint solvents for toluene and paint solvents for ethylbenzene and xylenes. This suggests that VOC control strategies in Seoul could continue to target vehicle exhaust and paint solvents, with additional regulations to limit the VOC content in a variety of non-paint solvents
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