Marcello Massimini

Local sleep and learning

Human sleep is a global state whose functions remain unclear. During much of sleep, cortical neurons undergo slow oscillations in membrane potential, which appear in electroencephalograms as slow wave activity (SWA) of <4 Hz. The amount of SWA is homeostatically regulated, increasing after wakefulness and returning to baseline during sleep. It has been suggested that SWA homeostasis may reflect synaptic changes underlying a cellular need for sleep. If this were so, inducing local synaptic changes should induce local SWA changes, and these should benefit neural function. Here we show that sleep homeostasis indeed has a local component, which can be triggered by a learning task involving specific brain regions. Furthermore, we show that the local increase in SWA after learning correlates with improved performance of the task after sleep. Thus, sleep homeostasis can be induced on a local level and can benefit performance.

The sleep slow oscillation as a traveling wave.

During much of sleep, virtually all cortical neurons undergo a slow oscillation (<1 Hz) in membrane potential, cycling from a hyperpolarized state of silence to a depolarized state of intense firing. This slow oscillation is the fundamental cellular phenomenon that organizes other sleep rhythms such as spindles and slow waves. Using high-density electroencephalogram recordings in humans, we show here that each cycle of the slow oscillation is a traveling wave. Each wave originates at a definite site and travels over the scalp at an estimated speed of 1.2-7.0 m/sec. Waves originate more frequently in prefrontal-orbitofrontal regions and propagate in an anteroposterior direction. Their rate of occurrence increases progressively reaching almost once per second as sleep deepens. The pattern of origin and propagation of sleep slow oscillations is reproducible across nights and subjects and provides a blueprint of cortical excitability and connectivity. The orderly propagation of correlated activity along connected pathways may play a role in spike timing-dependent synaptic plasticity during sleep.

Arm immobilization causes cortical plastic changes and locally decreases sleep slow wave activity

Sleep slow wave activity (SWA) is thought to reflect sleep need, increasing after wakefulness and decreasing after sleep. We showed recently that a learning task involving a circumscribed brain region produces a local increase in sleep SWA. We hypothesized that increases in cortical SWA reflect synaptic potentiation triggered by learning. To further investigate the link between synaptic plasticity and sleep, we asked whether a procedure leading to synaptic depression would cause instead a decrease in sleep SWA. We show here that if a subjects arm is immobilized during the day, motor performance deteriorates and both somatosensory and motor evoked potentials decrease over contralateral sensorimotor cortex, indicative of local synaptic depression. Notably, during subsequent sleep, SWA over the same cortical area is markedly reduced. Thus, cortical plasticity is linked to local sleep regulation without learning in the classical sense. Moreover, when synaptic strength is reduced, local sleep need is also reduced.

A Theoretically Based Index of Consciousness Independent of Sensory Processing and Behavior

A theory-derived index of consciousness, which quantifies the complexity of the brain’s response to a stimulus, measures the level of consciousness in awake, sleeping, anesthetized, and brain-damaged subjects. Quantifying the Unquantifiable Manipulation of consciousness is an everyday medical trick—think anesthesia—but physicians have only the crudest of tools to detect when a person is not aware. The usual question or physical stimulus does not always provide reliable reactions, and a more precise index is needed to avoid, for example, the conclusion that people who have locked-in syndrome (in which they are aware but cannot respond) are unconscious. Here, Casali et al. have extended their previous work on electrical correlates of consciousness to define an electroencephalographic-derived index of human consciousness [the perturbational complexity index (PCI)] that reflects the information content of the brain’s response to a magnetic stimulus. The PCI could allow tracking of consciousness in individual patients. The authors used data already collected from previous experiments, in which they had stimulated people’s brains with transcranial magnetic stimulation. By calculating the likely brain regional sources of the signals and then comparing the unique information in each, the authors derived PCI values. The values ranged from 0.44 to 0.67 in 32 awake healthy people, but fell to 0.18 to 0.28 during nonrapid eye movement (NREM) sleep. Then, to see whether a completely different way of inducing unconsciousness had the same effect on PCI, the authors assessed data from patients given various amounts of the anesthetics midazolam, xenon, and propofol. These agents too caused low “unconscious” values for the PCI: midazolam deep sedation, 0.23 to 0.31; propofol, 0.13 to 0.30; and xenon, 0.12 to 0.31. However, what about patients who suffer brain damage and who exhibit various levels of consciousness by conventional assessment methods? In these people, consciousness varies widely, as does the underlying damage from stroke or trauma. Here, too, the authors found promising results in those who had emerged from coma but were in a vegetative state or minimally conscious state, or exhibited locked-in syndrome. The PCI values from these patients clearly reflected the state of their consciousness, with the six patients in a vegetative state clearly unconscious (0.19 to 0.31), the two with locked-in syndrome clearly aware (0.51 to 0.62), and those in a minimally conscious state showing intermediate values (0.32 to 0.49). The validity of PCI for clinical application will need to be assessed in prospective trials, but it has the advantage of being derived from a simple noninvasive measurement. The new index reported by Casali et al. appears to be a robust measure that distinguishes conscious from unconscious states well enough to be used on an individual basis, a prerequisite for deployment in the clinic. One challenging aspect of the clinical assessment of brain-injured, unresponsive patients is the lack of an objective measure of consciousness that is independent of the subject’s ability to interact with the external environment. Theoretical considerations suggest that consciousness depends on the brain’s ability to support complex activity patterns that are, at once, distributed among interacting cortical areas (integrated) and differentiated in space and time (information-rich). We introduce and test a theory-driven index of the level of consciousness called the perturbational complexity index (PCI). PCI is calculated by (i) perturbing the cortex with transcranial magnetic stimulation (TMS) to engage distributed interactions in the brain (integration) and (ii) compressing the spatiotemporal pattern of these electrocortical responses to measure their algorithmic complexity (information). We test PCI on a large data set of TMS-evoked potentials recorded in healthy subjects during wakefulness, dreaming, nonrapid eye movement sleep, and different levels of sedation induced by anesthetic agents (midazolam, xenon, and propofol), as well as in patients who had emerged from coma (vegetative state, minimally conscious state, and locked-in syndrome). PCI reliably discriminated the level of consciousness in single individuals during wakefulness, sleep, and anesthesia, as well as in patients who had emerged from coma and recovered a minimal level of consciousness. PCI can potentially be used for objective determination of the level of consciousness at the bedside.

Preserved Feedforward But Impaired Top-Down Processes in the Vegetative State

Discerning the neural correlates of (un)consciousness sheds light on the mechanisms underlying vegetative states. Frontoparietal cortex is involved in the explicit processing (awareness) of stimuli. Frontoparietal activation has also been found in studies of subliminal stimulus processing. We hypothesized that an impairment of top-down processes, involved in recurrent neuronal message-passing and the generation of long-latency electrophysiological responses, might provide a more reliable correlate of consciousness in severely brain-damaged patients, than frontoparietal responses. We measured effective connectivity during a mismatch negativity paradigm and found that the only significant difference between patients in a vegetative state and controls was an impairment of backward connectivity from frontal to temporal cortices. This result emphasizes the importance of top-down projections in recurrent processing that involve high-order associative cortices for conscious perception.

Breakdown in cortical effective connectivity during midazolam-induced loss of consciousness

By employing transcranial magnetic stimulation (TMS) in combination with high-density electroencephalography (EEG), we recently reported that cortical effective connectivity is disrupted during early non-rapid eye movement (NREM) sleep. This is a time when subjects, if awakened, may report little or no conscious content. We hypothesized that a similar breakdown of cortical effective connectivity may underlie loss of consciousness (LOC) induced by pharmacologic agents. Here, we tested this hypothesis by comparing EEG responses to TMS during wakefulness and LOC induced by the benzodiazepine midazolam. Unlike spontaneous sleep states, a subject’s level of vigilance can be monitored repeatedly during pharmacological LOC. We found that, unlike during wakefulness, wherein TMS triggered responses in multiple cortical areas lasting for >300 ms, during midazolam-induced LOC, TMS-evoked activity was local and of shorter duration. Furthermore, a measure of the propagation of evoked cortical currents (significant current scattering, SCS) could reliably discriminate between consciousness and LOC. These results resemble those observed in early NREM sleep and suggest that a breakdown of cortical effective connectivity may be a common feature of conditions characterized by LOC. Moreover, these results suggest that it might be possible to use TMS-EEG to assess consciousness during anesthesia and in pathological conditions, such as coma, vegetative state, and minimally conscious state.

Natural Frequencies of Human Corticothalamic Circuits

The frequency tuning of a system can be directly determined by perturbing it and by observing the rate of the ensuing oscillations, the so called natural frequency. This approach is used, for example, in physics, in geology, and also when one tunes a musical instrument. In the present study, we employ transcranial magnetic stimulation (TMS) to directly perturb a set of selected corticothalamic modules (Brodmann areas 19, 7, and 6) and high-density electroencephalogram to measure their natural frequency. TMS consistently evoked dominant α-band oscillations (8–12 Hz) in the occipital cortex, β-band oscillations (13–20 Hz) in the parietal cortex, and fast β/γ-band oscillations (21–50 Hz) in the frontal cortex. Each cortical area tended to preserve its own natural frequency also when indirectly engaged by TMS through brain connections and when stimulated at different intensities, indicating that the observed oscillations reflect local physiological mechanisms. These findings were reproducible across individuals and represent the first direct characterization of the coarse electrophysiological properties of three associative areas of the human cerebral cortex. Most importantly, they indicate that, in healthy subjects, each corticothalamic module is normally tuned to oscillate at a characteristic rate. The natural frequency can be directly measured in virtually any area of the cerebral cortex and may represent a straightforward and flexible way to probe the state of human thalamocortical circuits at the patients bedside.

Reduced Sleep Spindle Activity in Schizophrenia Patients

OBJECTIVE High-density EEG during sleep represents a powerful new tool to reveal potential abnormalities in rhythm-generating mechanisms while avoiding confounding factors associated with waking activities. As a first step in this direction, the authors employed high-density EEG to explore whether sleep rhythms differ between schizophrenia subjects, healthy individuals, and a psychiatric control group with a history of depression. METHOD Healthy comparison subjects (N=17), medicated schizophrenia patients (N=18), and subjects with a history of depression (N=15) were recruited. Subjects were recorded during the first sleep episode of the night with a 256-electrode high-density EEG. Recordings were analyzed for changes in EEG power spectra, power topography, and sleep-specific cortical oscillations. RESULTS The authors found that the schizophrenia group had a significant reduction in centroparietal EEG power, from 13.75 to 15.00 Hz, in relation to both the comparison and depression groups. No significant difference in EEG power between the comparison and depression groups was identified. The authors also found a decrease in sleep spindle number, amplitude, duration, and integrated spindle activity in schizophrenia patients. Furthermore, integrated spindle activity had an effect size corresponding to 93.0% or 90.2% separation of the schizophrenia from the comparison or depression group. CONCLUSIONS Sleep spindles are generated by the thalamic reticular nucleus in conjunction with specific thalamic nuclei and are modulated by corticothalamic and thalamocortical connections. The deficit in sleep spindles in schizophrenia subjects may reflect dysfunction in thalamic-reticular and thalamocortical mechanisms and could represent a biological marker of illness.

Triggering sleep slow waves by transcranial magnetic stimulation

During much of sleep, cortical neurons undergo near-synchronous slow oscillation cycles in membrane potential, which give rise to the largest spontaneous waves observed in the normal electroencephalogram (EEG). Slow oscillations underlie characteristic features of the sleep EEG, such as slow waves and spindles. Here we show that, in sleeping subjects, slow waves and spindles can be triggered noninvasively and reliably by transcranial magnetic stimulation (TMS). With appropriate stimulation parameters, each TMS pulse at <1 Hz evokes an individual, high-amplitude slow wave that originates under the coil and spreads over the cortex. TMS triggering of slow waves reveals intrinsic bistability in thalamocortical networks during non-rapid eye movement sleep. Moreover, evoked slow waves lead to a deepening of sleep and to an increase in EEG slow-wave activity (0.5–4.5 Hz), which is thought to play a role in brain restoration and memory consolidation.

Recovery of cortical effective connectivity and recovery of consciousness in vegetative patients.

Patients surviving severe brain injury may regain consciousness without recovering their ability to understand, move and communicate. Recently, electrophysiological and neuroimaging approaches, employing simple sensory stimulations or verbal commands, have proven useful in detecting higher order processing and, in some cases, in establishing some degree of communication in brain-injured subjects with severe impairment of motor function. To complement these approaches, it would be useful to develop methods to detect recovery of consciousness in ways that do not depend on the integrity of sensory pathways or on the subjects ability to comprehend or carry out instructions. As suggested by theoretical and experimental work, a key requirement for consciousness is that multiple, specialized cortical areas can engage in rapid causal interactions (effective connectivity). Here, we employ transcranial magnetic stimulation together with high-density electroencephalography to evaluate effective connectivity at the bedside of severely brain injured, non-communicating subjects. In patients in a vegetative state, who were open-eyed, behaviourally awake but unresponsive, transcranial magnetic stimulation triggered a simple, local response indicating a breakdown of effective connectivity, similar to the one previously observed in unconscious sleeping or anaesthetized subjects. In contrast, in minimally conscious patients, who showed fluctuating signs of non-reflexive behaviour, transcranial magnetic stimulation invariably triggered complex activations that sequentially involved distant cortical areas ipsi- and contralateral to the site of stimulation, similar to activations we recorded in locked-in, conscious patients. Longitudinal measurements performed in patients who gradually recovered consciousness revealed that this clear-cut change in effective connectivity could occur at an early stage, before reliable communication was established with the subject and before the spontaneous electroencephalogram showed significant modifications. Measurements of effective connectivity by means of transcranial magnetic stimulation combined with electroencephalography can be performed at the bedside while by-passing subcortical afferent and efferent pathways, and without requiring active participation of subjects or language comprehension; hence, they offer an effective way to detect and track recovery of consciousness in brain-injured patients who are unable to exchange information with the external environment.