To what extent do all brains work alike during natural conditions? We explored this question by letting five subjects freely view half an hour of a popular movie while undergoing functional brain imaging. Applying an unbiased analysis in which spatiotemporal activity patterns in one brain were used to "model" activity in another brain, we found a striking level of voxel-by-voxel synchronization between individuals, not only in primary and secondary visual and auditory areas but also in association cortices. The results reveal a surprising tendency of individual brains to "tick collectively" during natural vision. The intersubject synchronization consisted of a widespread cortical activation pattern correlated with emotionally arousing scenes and regionally selective components. The characteristics of these activations were revealed with the use of an open-ended "reverse-correlation" approach, which inverts the conventional analysis by letting the brain signals themselves "pick up" the optimal stimuli for each specialized cortical area.

SUMMARY 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.

When the brain is awake, neurons in the cerebral cortex fire irregularly and the electroencephalogram (EEG) displays low amplitude, high frequency fluctuations. After falling asleep, neurons start oscillating between ON periods, when they fire as during wake, and OFF periods, when they stop firing altogether, and the EEG displays high amplitude slow waves. But what happens to neuronal firing after a long period of wake? We show here in freely behaving rats that, after prolonged wake, cortical neurons can go briefly “OFF line” as they do in sleep, accompanied by slower waves in the local EEG. Strikingly, neurons often go OFF line in one cortical area and not in another. During these periods of “local sleep”, whose incidence increases with wake duration, rats appear awake, active, and display a wake EEG. However, they are progressively impaired in a sugar pellet reaching task. Thus, though both the EEG and behavior indicate wakefulness, local populations of neurons in the cortex may be falling asleep, with negative consequences on performance.

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 utilized 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 (13-15Hz) centroparietal spindles often occurring with slow wave up-states, and slow (9-12Hz) frontal spindles occurring 200ms 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 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.

Our results offer a resolution to a central controversy regarding the coupling between neurons, LFP, and BOLD signals by demonstrating, for the first time, that the coupling of single units to the other measures is variable yet it is tightly related to the degree of interneuronal correlations in the human auditory cortex.

Animal studies have shown robust electrophysiological activity in the sensory cortex in the absence of stimuli or tasks. Similarly, recent human functional magnetic resonance imaging (fMRI) revealed widespread, spontaneously emerging cortical fluctuations. However, it is unknown what neuronal dynamics underlie this spontaneous activity in the human brain. Here we studied this issue by combining bilateral single-unit, local field potentials (LFPs) and intracranial electrocorticography (ECoG) recordings in individuals undergoing clinical monitoring. We found slow (<0.1 Hz, following 1/f-like profiles) spontaneous fluctuations of neuronal activity with significant interhemispheric correlations. These fluctuations were evident mainly in neuronal firing rates and in gamma (40-100 Hz) LFP power modulations. Notably, the interhemispheric correlations were enhanced during rapid eye movement and stage 2 sleep. Multiple intracranial ECoG recordings revealed clear selectivity for functional networks in the spontaneous gamma LFP power modulations. Our results point to slow spontaneous modulations in firing rate and gamma LFP as the likely correlates of spontaneous fMRI fluctuations in the human sensory cortex.The neuronal events occurring in the sensory cortex when no stimulus is presented are not well understood. Contrary to traditional feed-forward models of information processing, a growing body of single-unit, LFP, electroencephalography (EEG), and optical imaging data point to robust levels of spontaneous neuronal activity in sensory areas of the mammalian cortex 1-7 . The modulation of such spontaneous neuronal activity can occur on very slow time scales 8, 9 . These robust spontaneous waves pose a challenge for models linking neuronal activity and sensory perception 10,11 , namely in explaining how the brain distinguishes between spontaneous events and vivid sensory percepts. One possibility is that the precise neuronal dynamics differ substantially between spontaneous and sensory-evoked conditions. This

Dreams are a most remarkable experiment in psychology and neuroscience, conducted every night in every sleeping person. They show that our brain, disconnected from the environment, can generate by itself an entire world of conscious experiences. Content analysis and developmental studies have furthered our understanding of dream phenomenology. In parallel, brain lesion studies, functional imaging, and neurophysiology have advanced our knowledge of the neural basis of dreaming. It is now possible to start integrating these two strands of research in order to address some 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. Contemporary dream researchAlthough dreams have fascinated us since the dawn of time, their rigorous, scientific study is a recent development [1][2][3][4] (Supplementary Fig. 1). In The interpretation of dreams [5] Freud predicted that "Deeper research will one day trace the path further and discover an organic basis for the mental event." Recent work, which we review in this article, begins to fulfill Freud s prediction.The study of dreams is a formidable task, because dream consciousness is only accessible via report rather than direct observation (Box 1) and because it is difficult to manipulate dream content experimentally, whether by exposure to stimuli before [6,7] or during sleep [7,8]. Therefore, it is difficult to predict the contents of specific dreams [9], and most modern dream research tries to relate neuronal activity retrospectively to dream form rather than dream content, i.e. to focus on properties of all dreams rather than to investigate the neural correlates of a particular dream. Yet, as we shall see, encouraging progress has been made in relating the phenomenology of dreams to underlying brain activity, and to studies of brain damage and development. BOX 1 Can reports be trusted to accurately convey internal experiences in sleep?Do dream reports obtained by awakening a sleeping subject accurately convey subjective experiences in sleep? At one extreme, we could be fully conscious throughout sleep but remember dreams well, little, or not at all depending on the brain state when we are awakened. Indeed, we know that dreaming often goes unreported -some people claim they *Corresponding author: Tononi, G. (gtononi@wisc.edu). Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author Manuscrip...

SUMMARY 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.