The neural processes that underlie your ability to read and understand this sentence are unknown. Sentence comprehension occurs very rapidly, and can only be understood at a mechanistic level by discovering the precise sequence of underlying computational and neural events. However, we have no continuous and online neural measure of sentence processing with high spatial and temporal resolution. Here we report just such a measure: intracranial recordings from the surface of the human brain show that neural activity, indexed by γ-power, increases monotonically over the course of a sentence as people read it. This steady increase in activity is absent when people read and remember nonword-lists, despite the higher cognitive demand entailed, ruling out accounts in terms of generic attention, working memory, and cognitive load. Response increases are lower for sentence structure without meaning ("Jabberwocky" sentences) and word meaning without sentence structure (word-lists), showing that this effect is not explained by responses to syntax or word meaning alone. Instead, the full effect is found only for sentences, implicating compositional processes of sentence understanding, a striking and unique feature of human language not shared with animal communication systems. This work opens up new avenues for investigating the sequence of neural events that underlie the construction of linguistic meaning.ow does a sequence of sounds emerging from one person's mouth create a complex meaning in another person's mind? Although we have long known where language is processed in the brain (1-3), we still know almost nothing about how neural circuits extract and represent the meaning of a sentence. A powerful method for addressing this question is intracranial recording of neural activity directly from the cortical surface in neurosurgery patients (i.e., electrocorticography or ECoG) (4, 5). Although opportunities for ECoG data collection are rare, determined by clinical-not scientific-priorities, they nonetheless offer an unparalleled combination of spatial and temporal resolution, and further provide direct measures of actual neural activity, rather than indirect measures via blood flow (as in PET, fMRI, and near infrared spectroscopy/optical imaging). ECoG data are particularly valuable for the study of uniquely human functions like language, where animal models are inadequate. Here we used ECoG to identify the neural events that occur online as the meaning of a sentence is extracted and represented.Prior intracranial recording studies of language have largely focused on speech perception and production (e.g., refs. 6-11) and word-level processes (e.g., refs. 12-26). However, the most distinctive feature of human language is its compositionality: the ability to create and understand complex meanings from novel combinations of words structured into phrases and sentences (27). As a first step toward understanding the neural basis of sentence comprehension, we recorded intracranial responses while participants read sentences and...

Performing different tasks, such as generating motor movements or processing sensory input, requires the recruitment of specific networks of neuronal populations. Previous studies suggested that power variations in the alpha band (8–12 Hz) may implement such recruitment of task-specific populations by increasing cortical excitability in task-related areas while inhibiting population-level cortical activity in task-unrelated areas (Klimesch et al., 2007; Jensen and Mazaheri, 2010). However, the precise temporal and spatial relationships between the modulatory function implemented by alpha oscillations and population-level cortical activity remained undefined. Furthermore, while several studies suggested that alpha power indexes task-related populations across large and spatially separated cortical areas, it was largely unclear whether alpha power also differentially indexes smaller networks of task-related neuronal populations. Here we addressed these questions by investigating the temporal and spatial relationships of electrocorticographic (ECoG) power modulations in the alpha band and in the broadband gamma range (70–170 Hz, indexing population-level activity) during auditory and motor tasks in five human subjects and one macaque monkey. In line with previous research, our results confirm that broadband gamma power accurately tracks task-related behavior and that alpha power decreases in task-related areas. More importantly, they demonstrate that alpha power suppression lags population-level activity in auditory areas during the auditory task, but precedes it in motor areas during the motor task. This suppression of alpha power in task-related areas was accompanied by an increase in areas not related to the task. In addition, we show for the first time that these differential modulations of alpha power could be observed not only across widely distributed systems (e.g., motor vs. auditory system), but also within the auditory system. Specifically, alpha power was suppressed in the locations within the auditory system that most robustly responded to particular sound stimuli. Altogether, our results provide experimental evidence for a mechanism that preferentially recruits task-related neuronal populations by increasing cortical excitability in task-related cortical areas and decreasing cortical excitability in task-unrelated areas. This mechanism is implemented by variations in alpha power and is common to humans and the non-human primate under study. These results contribute to an increasingly refined understanding of the mechanisms underlying the selection of the specific neuronal populations required for task execution.