Giuseppe Curcio

The electroencephalographic fingerprint of sleep is genetically determined: a twin study.

Humans have an individual profile of the electroencephalographic power spectra at the 8 to 16Hz frequency during non–rapid eye movement sleep that is stable over time and resistant to experimental perturbations. We tested the hypothesis that this electroencephalographic “fingerprint” is genetically determined, by recording 40 monozygotic and dizygotic twins during baseline and recovery sleep after prolonged wakefulness. We show a largely greater similarity within monozygotic than dizygotic pairs, resulting in a heritability estimate of 96%, not influenced by sleep need and intensity. If replicated, these results will establish the electroencephalographic profile during sleep as one of the most heritable traits of humans. Ann Neurol 2008

Is the brain influenced by a phone call? An EEG study of resting wakefulness

We recorded the resting electroencephalogram of 20 healthy subjects in order to investigate the effect of electromagnetic field (EMF) exposure on EEG waking activity and its temporal development. The subjects were randomly assigned to two groups and exposed, in double-blind conditions, to a typical mobile phone signal (902.40 MHz, modulated at 217 Hz, with an average power of 0.25 W) before or during the EEG recording session. The results show that, under real exposure as compared to baseline and sham conditions, EEG spectral power was influenced in some bins of the alpha band. This effect was greater when the EMF was on during the EEG recording session than before it. The present data lend further support to the idea that pulsed high-frequency electromagnetic fields can affect normal brain functioning, also if no conclusions can be drawn about the possible health effects.

Antero-posterior EEG changes during the wakefulness-sleep transition

OBJECTIVES To investigate the brain topography of the human sleep EEG along the antero-posterior axis during the wakefulness-sleep transition, by means of both a single Hz analysis and a grouped-frequency analysis of EEG changes. METHODS EEG power values were calculated across a 1-28 Hz frequency range in a 1 Hz resolution during the wakefulness-sleep transition of 7 normal subjects. Topographical changes were assessed from C3-A2, C4-A1, Fpz-A1, Fz-A1, Cz-A1, Pz-A1, Oz-A1 recordings, after averaging individual time series, aligned with respect to the onset of stage 2. RESULTS The single Hz analysis showed that before sleep onset (SO), the <7 Hz slow frequencies were more prominent at the more anterior scalp locations; this anterior prominence was counterbalanced by a reciprocal prevalence across the >8 Hz frequencies of EEG activity from the occipital areas; while the >13 Hz fast frequencies were not characterized by significant antero-posterior differences. After SO, more EEG power was found in the range of slow frequencies at the centro-frontal scalp locations and a second peak of EEG activity was also revealed within the range of the sigma frequency, higher at the centro-parietal scalp locations. No consistent topographical changes were observed within the range of faster EEG frequencies. Grouped-frequency analysis confirmed these results, also pointing to different changes in the alpha frequency as a function of the SO point. CONCLUSIONS The results suggest that: (a) the alpha rhythm spreads anteriorly as the transition progresses; (b) several anterior areas first synchronize EEG activity; (c) the functional meaning of the EEG bands during the SO period should be partially revised with regard at least to alpha rhythm; (d) SO coincides with the start of stage 2.

Mobile phone emissions and human brain excitability

To test—via Transcranial Magnetic Stimulation (TMS)—the excitability of each brain hemisphere after ‘real’ or ‘sham’ exposure to the electromagnetic field (EMF) generated by a mobile phone operating in the Global System for Mobile Communication (GSM).

Validity of the Italian version of the Pittsburgh Sleep Quality Index (PSQI)

The aim of this study is to validate the Italian version of the Pittsburgh Sleep Quality Index (PSQI), comparing five different groups of individuals (healthy young and elderly, sleep apnoea syndrome patients, depressed patients, individuals with dementia) by both questionnaire scores and polysomnographic measures. Fifty individuals (10 for each group) participated in the study. Each of them filled in the PSQI and slept for two consecutive nights in the sleep laboratory. The PSQI showed an overall reliability coefficient (Cronbach’s α) of 0.835, indicating a high degree of internal consistency. The mean PSQI global score showed significant differences between groups, with an impaired overall quality of sleep in patients’ groups with respect to both the healthy groups. Results also indicated that the best cut-off score (differentiating “good” from “bad” sleepers) is 5. Pittsburgh Sleep Quality Index is a useful, valid and reliable tool for the assessment of sleep quality, with an overall efficiency comparable to the mother language version and differentiate “good” from “bad” sleepers. The Italian version of the questionnaire provides a good and reliable differentiation between normal and pathological groups, with higher scores reported by people characterized by impaired objectively evaluated sleep quality.

Sleepiness: evaluating and quantifying methods.

The aim of this literature review is to analyze the methods mainly used for evaluating and quantifying the complex phenomenon of sleepiness. The most common distinction is between subjective measures or self-evaluations, performance decrement measures, measures for evaluating sleep propensity and measures of arousal decrease. Techniques mainly used in specialized literature will be briefly presented and commented upon, evaluating their sensitivity, advantages and limitations. We conclude that: (a) different measures inevitably are differently sensitive to sleepiness fluctuations; (b) the amount of prior sleep is strongly relevant in quantifying sleepiness levels; (c) subjective and behavioral measures show a higher level of vulnerability to external and motivational factors.

Handedness is mainly associated with an asymmetry of corticospinal excitability and not of transcallosal inhibition

OBJECTIVE The study aims to compare transcallosal inhibition (TI), as assessed by the paired-pulse transcranial magnetic stimulation (TMS) technique, in a sample of right-handed subjects (RH) and left-handed subjects (LH). Motor thresholds (MTs) and motor evoked potential (MEP) amplitudes were also measured in the two groups, as an index of corticospinal activity. METHODS Thirty-two normal subjects (16 RH and 16 LH) were recorded with a paired-pulse TMS paradigm (intensity of both pulses=120% of MT). The inter-stimulus intervals (ISIs) were 2, 4, 6, 8, 10, 12, 14, 16, 18, and 20 ms for both motor cortices, and MEP responses were recorded from the abductor digiti minimi muscles. RESULTS Both groups showed a clear TI centred around the 12 ms ISI, but no difference was found as a function of handedness or of hemisphere. On the other hand, the two groups differed in terms of corticospinal activity, since the hand motor dominant hemisphere had lower MTs than the non-dominant one in LH, and larger MEP amplitudes for the right hand were found in RH. CONCLUSIONS Results point to a functional asymmetry of the motor cortex on the hand-dominant versus the non-dominant hemisphere, while handedness does not seem associated with functional differences in callosal inhibition, as measured by the inter-hemispheric paired-pulse TMS technique.

Neurophysiological correlates of sleepiness: A combined TMS and EEG study

Changes of cortical and corticospinal excitability as a function of sleep deprivation have been studied, using EEG power maps and several TMS measures in 33 normal subjects before and after a 40-h sleep deprivation (SD). The effects of SD were independently assessed by subjective and EEG measures of sleepiness, the latter being represented in terms of cortical maps for different frequency bands. Short intracortical facilitation (SICF) and inhibition (SICI) were measured by the paired-pulse TMS technique with different inter-stimulus intervals. Besides standardized motor threshold (MT), lower threshold (LT) and upper threshold (UT) were also determined. Subjective sleepiness severely increased as a consequence of SD, paralleled by a drastic decrease of alertness. EEG topography showed large increases in delta and theta activity, mainly evident at fronto-central areas. Standard MTs, as well as LTs and UTs, all increased as a consequence of SD. SICF also showed a significant increase as compared to pre-deprivation values, but only in females. The increase of theta activity was strongly associated in the left frontal and prefrontal cortex to a smaller decrease of corticospinal excitability, expressed by MTs, and a larger increase of intracortical facilitation, expressed by SICF. TMS and EEG measures converge in indicating that SD has severe effects on both cortical and corticospinal excitability, as shown respectively by the increases of slow-frequency EEG power and MTs. The SICF enhancement in females and the results of the combined topographical analysis of EEG and TMS changes are coherent with the hypothesis that cortical TMS-evoked responses are higher as a consequence of a longer wakefulness. However, the lack of an increase in cortical excitability after prolonged wakefulness in males suggests some caution in the generalization of these effects, that deserve further investigation.

The effects of sleep and sleep deprivation on task-switching performance

Neural systems of the prefrontal cortex (PFC) involved in executive functions are particularly vulnerable to sleep deprivation (SD). In this study, we investigated whether SD selectively affects specific components of the executive control processes involved in task‐switching performance. Two different tasks are performed in rapid and random succession in this procedure, so that the to‐be‐executed task may change from one trial to the next (switch trial), or may be repeated (repetition trial). Task‐switches are usually slower than task repetitions, giving way to the ‘switch cost’. One hundred and eight university students were assigned randomly to the sleep (S) or the SD group. Each of them was tested on a task‐switching paradigm before and after an experimental night (S or SD), and after one recovery night. SD impaired both task‐switching accuracy and speed. A higher proportion of errors and increased switch costs after SD have been observed, compared to normal sleep. Control analyses on switch and repetition trials showed that the SD group was significantly worse only on the switch trials. The effects of SD are reverted by one night of recovery sleep. It is concluded that the ability to adjust behaviour rapidly and flexibly to changing environmental demands, which relies on the functional integrity of the PFC, is impacted negatively by sleep loss.

Sleep to find your way: The role of sleep in the consolidation of memory for navigation in humans

Although a large body of evidence indicates that sleep plays an important role in learning and memory processes, the actual existence of a sleep‐dependent spatial memory consolidation has been not firmly established. Here, by using a computerized 3D virtual navigation tool, we were able to show that topographical orientation in humans largely benefits from sleep after learning, while 10 h of wakefulness during the daytime do not exert similar beneficial effects. In particular, navigation performance enhancement needs sleep in the first post‐training night, and no further improvements were seen after a second night of sleep. On the other hand, sleep deprivation hinders any performance enhancement and exerts a proactive disruption of spatial memory consolidation, since recovery sleep do not revert its effects. Spatial memory performance does not benefit from the simple passage of time, and a period of wakefulness between learning and sleep does not seem to have the role of stabilizing memory traces. In conclusion, our results indicate that spatial performance improvement is observed only when learning is followed by a period of sleep, regardless of the retention interval length.