Yuval Nir

Regional Slow Waves and Spindles in Human Sleep

The most prominent EEG events in sleep are slow waves, reflecting a slow (<1 Hz) oscillation between up and down states in cortical neurons. It is unknown whether slow oscillations are synchronous across the majority or the minority of brain regions--are they a global or local phenomenon? To examine this, we recorded simultaneously scalp EEG, intracerebral EEG, and unit firing in multiple brain regions of neurosurgical patients. We find that most sleep slow waves and the underlying active and inactive neuronal states occur locally. Thus, especially in late sleep, some regions can be active while others are silent. We also find that slow waves can propagate, usually from medial prefrontal cortex to the medial temporal lobe and hippocampus. Sleep spindles, the other hallmark of NREM sleep EEG, are likewise predominantly local. Thus, intracerebral communication during sleep is constrained because slow and spindle oscillations often occur out-of-phase in different brain regions.

Local sleep in awake rats

In an awake state, neurons in the cerebral cortex fire irregularly and electroencephalogram (EEG) recordings display low-amplitude, high-frequency fluctuations. During sleep, neurons oscillate between ‘on’ periods, when they fire as in an awake brain, and ‘off’ periods, when they stop firing altogether and the EEG displays high-amplitude slow waves. However, what happens to neuronal firing after a long period of being awake is not known. Here we show that in freely behaving rats after a long period in an awake state, cortical neurons can go briefly ‘offline’ as in sleep, accompanied by slow waves in the local EEG. Neurons often go offline in one cortical area but not in another, and during these periods of ‘local sleep’, the incidence of which increases with the duration of the awake state, rats are active and display an ‘awake’ EEG. However, they are progressively impaired in a sugar pellet reaching task. Thus, although both the EEG and behaviour indicate wakefulness, local populations of neurons in the cortex may be falling asleep, with negative consequences for performance.

Dreaming and the brain: from phenomenology to neurophysiology

Dreams are a remarkable experiment in psychology and neuroscience, conducted every night in every sleeping person. They show that the human brain, disconnected from the environment, can generate an entire world of conscious experiences by itself. Content analysis and developmental studies have promoted understanding of dream phenomenology. In parallel, brain lesion studies, functional imaging and neurophysiology have advanced current knowledge of the neural basis of dreaming. It is now possible to start integrating these two strands of research to address fundamental questions that dreams pose for cognitive neuroscience: how conscious experiences in sleep relate to underlying brain activity; why the dreamer is largely disconnected from the environment; and whether dreaming is more closely related to mental imagery or to perception.

Sleep spindles in humans: insights from intracranial EEG and unit recordings

Sleep spindles are an electroencephalographic (EEG) hallmark of non-rapid eye movement (NREM) sleep and are believed to mediate many sleep-related functions, from memory consolidation to cortical development. Spindles differ in location, frequency, and association with slow waves, but whether this heterogeneity may reflect different physiological processes and potentially serve different functional roles remains unclear. Here we used a unique opportunity to record intracranial depth EEG and single-unit activity in multiple brain regions of neurosurgical patients to better characterize spindle activity in human sleep. We find that spindles occur across multiple neocortical regions, and less frequently also in the parahippocampal gyrus and hippocampus. Most spindles are spatially restricted to specific brain regions. In addition, spindle frequency is topographically organized with a sharp transition around the supplementary motor area between fast (13–15 Hz) centroparietal spindles often occurring with slow-wave up-states, and slow (9–12 Hz) frontal spindles occurring 200 ms later on average. Spindle variability across regions may reflect the underlying thalamocortical projections. We also find that during individual spindles, frequency decreases within and between regions. In addition, deeper NREM sleep is associated with a reduction in spindle occurrence and spindle frequency. Frequency changes between regions, during individual spindles, and across sleep may reflect the same phenomenon, the underlying level of thalamocortical hyperpolarization. Finally, during spindles neuronal firing rates are not consistently modulated, although some neurons exhibit phase-locked discharges. Overall, anatomical considerations can account well for regional spindle characteristics, while variable hyperpolarization levels can explain differences in spindle frequency.

Neural “Ignition”: Enhanced Activation Linked to Perceptual Awareness in Human Ventral Stream Visual Cortex

Human recognition performance is characterized by abrupt changes in perceptual states. Understanding the neuronal dynamics underlying such transitions could provide important insights into mechanisms of recognition and perceptual awareness. Here we examined patients monitored for clinical purposes with multiple subdural electrodes. The patients participated in a backward masking experiment in which pictures of various object categories were presented briefly followed by a mask. We recorded ECoG from 445 electrodes placed in 11 patients. We found a striking increase in gamma power (30-70 Hz) and evoked responses specifically associated with successful recognition. The enhanced activation occurred 150-200 ms after stimulus onset and consistently outlasted the stimulus presentation. We propose that the gamma and evoked potential activations reflect a rapid increase in recurrent neuronal activity that plays a critical role in the emergence of a recognizable visual percept in conscious awareness.

Identifying the default‐mode component in spatial IC analyses of patients with disorders of consciousness

Objectives:Recent fMRI studies have shown that it is possible to reliably identify the default‐mode network (DMN) in the absence of any task, by resting‐state connectivity analyses in healthy volunteers. We here aimed to identify the DMN in the challenging patient population of disorders of consciousness encountered following coma. Experimental design: A spatial independent component analysis‐based methodology permitted DMN assessment, decomposing connectivity in all its different sources either neuronal or artifactual. Three different selection criteria were introduced assessing anticorrelation‐corrected connectivity with or without an automatic masking procedure and calculating connectivity scores encompassing both spatial and temporal properties. These three methods were validated on 10 healthy controls and applied to an independent group of 8 healthy controls and 11 severely brain‐damaged patients [locked‐in syndrome (n = 2), minimally conscious (n = 1), and vegetative state (n = 8)]. Principal observations: All vegetative patients showed fewer connections in the default‐mode areas, when compared with controls, contrary to locked‐in patients who showed near‐normal connectivity. In the minimally conscious‐state patient, only the two selection criteria considering both spatial and temporal properties were able to identify an intact right lateralized BOLD connectivity pattern, and metabolic PET data suggested its neuronal origin. Conclusions: When assessing resting‐state connectivity in patients with disorders of consciousness, it is important to use a methodology excluding non‐neuronal contributions caused by head motion, respiration, and heart rate artifacts encountered in all studied patients. Hum Brain Mapp, 2012.

Syntactic Structure Building in the Anterior Temporal Lobe during Natural Story Listening.

The neural basis of syntax is a matter of substantial debate. In particular, the inferior frontal gyrus (IFG), or Brocas area, has been prominently linked to syntactic processing, but the anterior temporal lobe has been reported to be activated instead of IFG when manipulating the presence of syntactic structure. These findings are difficult to reconcile because they rely on different laboratory tasks which tap into distinct computations, and may only indirectly relate to natural sentence processing. Here we assessed neural correlates of syntactic structure building in natural language comprehension, free from artificial task demands. Subjects passively listened to Alice in Wonderland during functional magnetic resonance imaging and we correlated brain activity with a word-by-word measure of the amount syntactic structure analyzed. Syntactic structure building correlated with activity in the left anterior temporal lobe, but there was no evidence for a correlation between syntactic structure building and activity in inferior frontal areas. Our results suggest that the anterior temporal lobe computes syntactic structure under natural conditions.

Enhanced Category Tuning Revealed by Intracranial Electroencephalograms in High-Order Human Visual Areas

The functional organization of human sensory cortex was studied by comparing intracranial EEG (iEEG) recordings of local field potentials in neurosurgical patients with functional magnetic resonance imaging (fMRI) obtained in healthy subjects. Using naturalistic movie stimuli, we found a tight correlation between these two measures throughout the human sensory cortex. Importantly, the correlation between the iEEG and fMRI signals was site-specific, exhibiting neuroanatomically specific coupling. In several cortical sites the iEEG activity was confined strictly to one object category. This site selectivity was not limited to faces but included other object categories such as houses and tools. The selectivity of the iEEG signals to images of different object categories was remarkably higher when compared with the selectivity of the corresponding fMRI signals. A plausible interpretation of the fMRI and iEEG results concerns cortical organization in which object categories are organized in a mosaic of narrowly tuned object-selective clusters.

Reduction in inter-hemispheric connectivity in disorders of consciousness.

Clinical diagnosis of disorders of consciousness (DOC) caused by brain injury poses great challenges since patients are often behaviorally unresponsive. A promising new approach towards objective DOC diagnosis may be offered by the analysis of ultra-slow (<0.1 Hz) spontaneous brain activity fluctuations measured with functional magnetic resonance imaging (fMRI) during the resting-state. Previous work has shown reduced functional connectivity within the “default network”, a subset of regions known to be deactivated during engaging tasks, which correlated with the degree of consciousness impairment. However, it remains unclear whether the breakdown of connectivity is restricted to the “default network”, and to what degree changes in functional connectivity can be observed at the single subject level. Here, we analyzed resting-state inter-hemispheric connectivity in three homotopic regions of interest, which could reliably be identified based on distinct anatomical landmarks, and were part of the “Extrinsic” (externally oriented, task positive) network (pre- and postcentral gyrus, and intraparietal sulcus). Resting-state fMRI data were acquired for a group of 11 healthy subjects and 8 DOC patients. At the group level, our results indicate decreased inter-hemispheric functional connectivity in subjects with impaired awareness as compared to subjects with intact awareness. Individual connectivity scores significantly correlated with the degree of consciousness. Furthermore, a single-case statistic indicated a significant deviation from the healthy sample in 5/8 patients. Importantly, of the three patients whose connectivity indices were comparable to the healthy sample, one was diagnosed as locked-in. Taken together, our results further highlight the clinical potential of resting-state connectivity analysis and might guide the way towards a connectivity measure complementing existing DOC diagnosis.

Single-neuron activity and eye movements during human REM sleep and awake vision

Are rapid eye movements (REMs) in sleep associated with visual-like activity, as during wakefulness? Here we examine single-unit activities (n=2,057) and intracranial electroencephalography across the human medial temporal lobe (MTL) and neocortex during sleep and wakefulness, and during visual stimulation with fixation. During sleep and wakefulness, REM onsets are associated with distinct intracranial potentials, reminiscent of ponto-geniculate-occipital waves. Individual neurons, especially in the MTL, exhibit reduced firing rates before REMs as well as transient increases in firing rate immediately after, similar to activity patterns observed upon image presentation during fixation without eye movements. Moreover, the selectivity of individual units is correlated with their response latency, such that units activated after a small number of images or REMs exhibit delayed increases in firing rates. Finally, the phase of theta oscillations is similarly reset following REMs in sleep and wakefulness, and after controlled visual stimulation. Our results suggest that REMs during sleep rearrange discrete epochs of visual-like processing as during wakefulness.