Breakdown of cortical effective connectivity during sleep

University of Milan, Milano, Lombardy, Italy
Science (Impact Factor: 31.48). 10/2005; 309(5744):2228-32. DOI: 10.1126/science.1117256
Source: PubMed

ABSTRACT When we fall asleep, consciousness fades yet the brain remains active. Why is this so? To investigate whether changes in cortical information transmission play a role, we used transcranial magnetic stimulation together with high-density electroencephalography and asked how the activation of one cortical area (the premotor area) is transmitted to the rest of the brain. During quiet wakefulness, an initial response (approximately 15 milliseconds) at the stimulation site was followed by a sequence of waves that moved to connected cortical areas several centimeters away. During non-rapid eye movement sleep, the initial response was stronger but was rapidly extinguished and did not propagate beyond the stimulation site. Thus, the fading of consciousness during certain stages of sleep may be related to a breakdown in cortical effective connectivity.

Download full-text


Available from: Giulio Tononi, Jun 30, 2015
1 Follower
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: During non-rapid eye movement (NREM) sleep (stage N3), when consciousness fades, cortico-cortical interactions are impaired while neurons are still active and reactive. Why is this? We compared cortico-cortical evoked-potentials recorded during wakefulness and NREM by means of time-frequency analysis and phase-locking measures in 8 epileptic patients undergoing intra-cerebral stimulations/recordings for clinical evaluation. We observed that, while during wakefulness electrical stimulation triggers a chain of deterministic phase-locked activations in its cortical targets, during NREM the same input induces a slow wave associated with an OFF-period (suppression of power>20Hz), possibly reflecting a neuronal down-state. Crucially, after the OFF-period, cortical activity resumes to wakefulness-like levels, but the deterministic effects of the initial input are lost, as indicated by a sharp drop of phase-locked activity. These findings suggest that the intrinsic tendency of cortical neurons to fall into a down-state after a transient activation (i.e. bistability) prevents the emergence of stable patterns of causal interactions among cortical areas during NREM. Besides sleep, the same basic neurophysiological dynamics may play a role in pathological conditions in which thalmo-cortical information integration and consciousness are impaired in spite of preserved neuronal activity. Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 03/2015; 6. DOI:10.1016/j.neuroimage.2015.02.056 · 6.13 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In transcranial magnetic stimulation (TMS) a strong, brief current pulse driven through a coil is used for non-invasively stimulating the cortex. Properties of the electric field (E-field) induced by the pulse together with physiological parameters determine the outcome of the stimulation. In research and clinical use, TMS is delivered using a wide range of different coils and stimulator units, all having their own characteristics; however, the parameters of the induced E-field are often inadequately known by the user.
    Brain Stimulation 01/2015; 8(3). DOI:10.1016/j.brs.2015.01.004 · 5.43 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Cortical stimulation is used for therapeutic applications and research into neural processes. Cortical evoked responses to stimulation yield important information about neural connectivity and cortical excitability but are sensitive to changes in stimulation parameters. So far, the relationship between the stimulation parameters and the evoked responses has been reported only descriptively. In this paper we propose the use of regression analysis to train models that infer the stimulation intensity from the shape of the evoked activity. Using Support Vector Regression and electrocorticogram (ECoG) responses to electrical stimulation via epidural electrodes collected from two stroke patients, we show that the models can capture this relationship and generalize to intensities not used during the training process.
    Neurocomputing 10/2014; 141:46–53. DOI:10.1016/j.neucom.2014.01.048 · 2.01 Impact Factor