The measure of randomness by leave-one-out prediction error in the analysis of EEG after laser painful stimulation in healthy subjects and migraine patients

TIRES-Center of Innovative Technologies for Signal Detection and Processing, University of Bari, Italy.
Clinical Neurophysiology (Impact Factor: 2.98). 01/2006; 116(12):2775-82. DOI: 10.1016/j.clinph.2005.08.019
Source: PubMed

ABSTRACT We aimed to perform a quantitative analysis of event-related modulation of EEG activity, resulting from a not-warned and a warned paradigm of painful laser stimulation, in migraine patients and controls, by the use of a novel analysis, based upon a parametric approach to measure predictability of short and noisy time series.
Ten migraine patients were evaluated during the not-symptomatic phase and compared to seven age and sex matched controls. The dorsum of the right hand and the right supraorbital zone were stimulated by a painful CO(2) laser, in presence or in absence of a visual warning stimulus. An analysis time of 1s after the stimulus was submitted to a time-frequency analysis by a complex Morlet wavelet and to a cross-correlation analysis, in order to detect the development of EEG changes and the most activated cortical regions. A parametric approach to measure predictability of short and noisy time series was applied, where time series were modeled by leave-one-out (LOO) error.
The averaged laser-evoked potentials features were similar between the two groups in the alerted and not alerted condition. A strong reset of the beta rhythms after the painful stimuli was seen for three groups of electrodes along the midline in patients and controls: the predictability of the series induced by the laser stimulus changed very differently in controls and patients. The separation was more evident after the warning signal, leading to a separation with P-values of 0.0046 for both the hand and the face.
As painful stimulus causes organization of the local activity in cortex, EEG series become more predictable after stimulation. This phenomenon was less evident in migraine, as a sign of an inadequate cortical reactivity to pain.
The LOO method enabled to show in migraine subtle changes in the cortical response to pain.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: BACKGROUND: Dysexcitability characterizes the interictal migraineous brain. The main central expressions of this dysexcitability are decreased habituation and enhanced anticipation and attention to pain and other external sensory stimuli. OBJECTIVE: This study evaluates the effects of anticipation on pain modulation and their neural correlates in migraine. METHODS: In 39 migraineurs (20 migraine with aura [MWA] and 19 migraine without aura [MOA]) and 22 healthy controls, cortical responses to 2 successive trains of noxious contact-heat stimuli, presented in either predicted or unpredicted manner, were analyzed using standardized low-resolution electromagnetic tomography key. RESULTS: A lack of habituation to repeated predicted pain was associated with significantly increased pain-evoked potential amplitudes in MWAs (increase of 3.9 μV) and unchanged ones in MOAs (1.1 μV) but not in controls (decrease of 5 μV). Repeated unpredicted pain resulted in enhanced pain-evoked potential amplitudes in both MWA and MOA groups (increase of 5.5 μV and 4.4 μV, respectively) compared with controls (decrease of 0.2 μV). Source localization revealed reduced activations in the anterior-medial prefrontal cortices and subsequent increased somatosensory activity in migraineurs (P < .05). The prefrontal-somatosensory dysfunction positively correlated with lifetime headache duration (P < .05) and concern of upcoming migraine attacks (P < .05) in MWAs, and with frequency of migraine attacks in MOAs (P < .05). CONCLUSIONS: Our findings of impaired modulation of anticipated pain in migraine suggest a heightened state of anticipatory readiness combined with ineffective recruitment of prefrontal inhibitory pathways during experience of pain; the latter might account for the former, at least partially. In line, less efficient inhibitory capability is a plausible mechanistic explanation for patients' high concern about their upcoming migraine attacks.
    Headache The Journal of Head and Face Pain 12/2012; 53(7). DOI:10.1111/j.1526-4610.2012.02297.x · 3.19 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: We set up a classification system able to detect patients affected by migraine without aura, through the analysis of their spontaneous EEG patterns. First, the signals are characterized by means of wavelet-based features, than a supervised neural network is used to classify the multichannel data. For the feature extraction, scale-dependent and scale-independent methods are considered with a variety of wavelet functions. Both the approaches provide very high and almost comparable classification performances. A complete separation of the two groups is obtained when the data are plotted in the plane spanned by two suitable neural outputs.
    Physica A: Statistical Mechanics and its Applications 08/2007; 382(2):549-556. DOI:10.1016/j.physa.2007.04.023 · 1.72 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Migraine is a cyclic disorder, in which functional and morphological brain changes fluctuate over time, culminating periodically in an attack. In the migrainous brain, temporal processing of external stimuli and sequential recruitment of neuronal networks are often dysfunctional. These changes reflect complex CNS dysfunction patterns. Assessment of multimodal evoked potentials and nociceptive reflex responses can reveal altered patterns of the brain's electrophysiological activity, thereby aiding our understanding of the pathophysiology of migraine. In this Review, we summarize the most important findings on temporal processing of evoked and reflex responses in migraine. Considering these data, we propose that thalamocortical dysrhythmia may be responsible for the altered synchronicity in migraine. To test this hypothesis in future research, electrophysiological recordings should be combined with neuroimaging studies so that the temporal patterns of sensory processing in patients with migraine can be correlated with the accompanying anatomical and functional changes.
    Nature Reviews Neurology 02/2014; DOI:10.1038/nrneurol.2014.14 · 14.10 Impact Factor


Available from