Language is a defining human behavior that emerges from a broadly distributed set of cortical substrates with complex network dynamics. We studied word production using direct intracranial recordings and cortical stimulation in a large cohort to create a detailed spatiotemporal atlas of the entire language-dominant cortex. From this map, we resolved network dynamics comprising sequences of state space transitions for each word articulated. This identified five discrete states for speech production in humans defined by unique patterns of directed interactions within the language network that were conserved across individuals. We then derived a computational lesion model of these state dynamics to elucidate their distinct functional contributions and validated these predictions with causal perturbation by cortical stimulation. Our work suggests that the fundamental unit of language processing in the brain is the global dynamical state. This functional architecture generalizes across individuals, enabling a new framework for understanding fluent speech production as well as speech impairment.

Speech production engages a distributed network of cortical and subcortical brain regions. The supplementary motor area (SMA) has long been thought to be a key hub in coordinating across these regions to initiate voluntary movements, including speech. We analyzed direct intracranial recordings from 115 patients with epilepsy as they articulated a single word in a subset of trials from a picture-naming task. We aimed to characterize the temporal dynamics of SMA relative to other cortical regions. SMA and preSMA were among the first regions to activate after cue onset, peaked in activity before articulation onset, and were the earliest regions to predict trial-to-trial response time. Neural activity at single electrodes in SMA and preSMA was closely associated with speech initiation; activity began at a highly predictable time after stimulus onset and extended until speech onset for any given trial. Our results support the idea that SMA is a key node in the speech initiation network.

Essential tremor DBS targeting the ventral intermediate nucleus (Vim) of the thalamus and its input, the dentato-rubro-thalamic tract (DRTt), has proven to be an effective treatment strategy. We examined thalamo-cortical evoked potentials (TCEPs) and cortical dynamics during stimulation of the DRTt. We recorded TCEPs in primary motor cortex during clinical and supra-clinical stimulation of the DRTt in ten essential tremor patients. Stimulation was varied over pulse amplitude (2–10 mA) and pulse width (30–250 μs) to allow for strength-duration testing. Testing at clinical levels (3 mA, 60 μs) for stimulation frequencies of 1–160 Hz was performed and phase amplitude coupling (PAC) of beta phase and gamma power was calculated. Primary motor cortex TCEPs displayed two responses: early and all-or-none (<20 ms) or delayed and charge-dependent (>50 ms). Strength-duration curve approximation indicates that the chronaxie of the neural elements related to the TCEPs is <200 μs. At the range of clinical stimulation (amplitude 2–5 mA, pulse width 30–60 μs), TCEPs were not noted over primary motor cortex. Decreased pathophysiological phase-amplitude coupling was seen above 70 Hz stimulation without changes in power spectra and below the threshold of TCEPs. Our findings demonstrate that DRTt stimulation within normal clinical bounds does not excite fibers directly connected with primary motor cortex but that supra-clinical stimulation can excite a direct axonal tract. Both clinical efficacy and phase-amplitude coupling were frequency-dependent, favoring a synaptic filtering model as a possible mechanism of action.

Lexical retrieval deficits are characteristic of a variety of different neurological disorders. However, the exact substrates responsible for this are not known. We studied a large cohort of patients undergoing surgery in the dominant temporal lobe for medically intractable epilepsy (n=95) to localize brain regions that were associated with anomia. We performed a multivariate voxel-based lesion–symptom mapping analysis to correlate surgical lesions within the temporal lobe with changes in naming ability. Additionally, we used a surface-based mixed-effects multilevel analysis to estimate group-level broadband gamma activity during naming across a subset of patients with electrocorticographic recordings and integrated these results with lesion–deficit findings. We observed that ventral temporal regions, centered around the middle fusiform gyrus, were significantly associated with a decline in naming. Furthermore, we found that the ventral aspect of temporal lobectomies was linearly correlated to a decline in naming, with a clinically significant decline occurring once the resection extended 6 cm from the anterior tip of the temporal lobe on the ventral surface. On electrocorticography, the majority of these cortical regions were functionally active following visual processing. These loci coincide with the sites of susceptibility artifacts during echoplanar imaging, which may explain why this region has been previously underappreciated as the locus responsible for postoperative naming deficits. Taken together, these data highlight the crucial contribution of the ventral temporal cortex in naming and its important role in the pathophysiology of anomia following temporal lobe resections. As such, surgical strategies should attempt to preserve this region to mitigate postoperative language deficits.

Language depends critically on the integration of lexical information across multiple words to derive semantic concepts. Limitations of spatiotemporal resolution have previously rendered it difficult to isolate processes involved in semantic integration. We utilized intracranial recordings in epilepsy patients (n=58) who read written word definitions. Descriptions were either referential or non-referential to a common object. Semantically referential sentences enabled high frequency broadband gamma activation (70–150 Hz) of the inferior frontal sulcus (IFS), medial parietal cortex, orbitofrontal cortex (OFC) and medial temporal lobe in the left, language-dominant hemisphere. IFS, OFC and posterior middle temporal gyrus activity was modulated by the semantic coherence of non-referential sentences, exposing semantic effects that were independent of task-based referential status. Components of this network, alongside posterior superior temporal sulcus, were engaged for referential sentences that did not clearly reduce the lexical search space by the final word. These results indicate the existence of complementary cortical mosaics for semantic integration in posterior temporal and inferior frontal cortex.

Visual inputs to early visual cortex integrate with semantic, linguistic and memory inputs in higher visual cortex, in a manner that is rapid and accurate, and enables complex computations such as face recognition and word reading. This implies the existence of fundamental organizational principles that enable such efficiency. To elaborate on this, we performed intracranial recordings in 82 individuals while they performed tasks of varying visual and cognitive complexity. We discovered that visual inputs induce highly organized posterior-to-anterior propagating patterns of phase modulation across the ventral occipitotemporal cortex. At individual electrodes there was a stereotyped temporal pattern of phase progression following both stimulus onset and offset, consistent across trials and tasks. The phase of low frequency activity in anterior regions was predicted by the prior phase in posterior cortical regions. This spatiotemporal propagation of phase likely serves as a feed-forward organizational influence enabling the integration of information across the ventral visual stream. This phase modulation manifests as the early components of the event related potential; one of the most commonly used measures in human electrophysiology. These findings illuminate fundamental organizational principles of the higher order visual system that enable the rapid recognition and characterization of a variety of inputs.

Reading is a rapid, distributed process that engages multiple components of the ventral visual stream. To understand the neural constituents and their interactions that allow us to identify written words, we performed direct intra-cranial recordings in a large cohort of humans. This allowed us to isolate the spatiotemporal dynamics of visual word recognition across the entire left ventral occipitotemporal cortex. We found that mid-fusiform cortex is the first brain region sensitive to lexicality, preceding the traditional visual word form area. The magnitude and duration of its activation are driven by the statistics of natural language. Information regarding lexicality and word frequency propagates posteriorly from this region to visual word form regions and to earlier visual cortex, which, while active earlier, show sensitivity to words later. Further, direct electrical stimulation of this region results in reading arrest, further illustrating its crucial role in reading. This unique sensitivity of mid-fusiform cortex to sub-lexical and lexical characteristics points to its central role as the orthographic lexicon—the long-term memory representations of visual word forms.

Spoken language, both perception and production, is thought to be facilitated by an ensemble of predictive mechanisms. We obtain intracranial recordings in 37 patients using depth probes implanted along the anteroposterior extent of the supratemporal plane during rhythm listening, speech perception, and speech production. These reveal two predictive mechanisms in early auditory cortex with distinct anatomical and functional characteristics. The first, localized to bilateral Heschl's gyri and indexed by low-frequency phase, predicts the timing of acoustic events. The second, localized to planum temporale only in language-dominant cortex and indexed by high-gamma power, shows a transient response to acoustic stimuli that is uniquely suppressed during speech production. Chronometric stimulation of Heschl's gyrus selectively disrupts speech perception, while stimulation of planum temporale selectively disrupts speech production. This work illuminates the fundamental acoustic infrastructure— both architecture and function—for spoken language, grounding cognitive models of speech perception and production in human neurobiology.

Brain computations involve multiple processes by which sensory information is encoded and transformed to drive behavior. These computations are thought to be mediated by dynamic interactions between populations of neurons. Here, we demonstrate that human brains exhibit a reliable sequence of neural interactions during speech production. We use an autoregressive Hidden Markov Model (ARHMM) to identify dynamical network states exhibited by electrocorticographic signals recorded from human neurosurgical patients. Our method resolves dynamic latent network states on a trial-by-trial basis. We characterize individual network states according to the patterns of directional information flow between cortical regions of interest. These network states occur consistently and in a specific, interpretable sequence across trials and subjects: the data support the hypothesis of a fixed-length visual processing state, followed by a variable-length language state, and then by a terminal articulation state. This empirical evidence validates classical psycholinguistic theories that have posited such intermediate states during speaking. It further reveals these state dynamics are not localized to one brain area or one sequence of areas, but are instead a network phenomenon.

Semantic memory underpins our understanding of objects, people, places, and ideas. Anomia, a disruption of semantic memory access, is the most common residual language disturbance and is seen in dementia and following injury to temporal cortex. While such anomia has been well characterized by lesion symptom mapping studies, its pathophysiology is not well understood. We hypothesize that inputs to the semantic memory system engage a specific heteromodal network hub that integrates lexical retrieval with the appropriate semantic content. Such a network hub has been proposed by others, but has thus far eluded precise spatiotemporal delineation. This limitation in our understanding of semantic memory has impeded progress in the treatment of anomia. We evaluated the cortical structure and dynamics of the lexical semantic network in driving speech production in a large cohort of patients with epilepsy using electrocorticography (n = 64), functional MRI (n = 36), and direct cortical stimulation (n = 30) during two generative language processes that rely on semantic knowledge: visual picture naming and auditory naming to definition. Each task also featured a non-semantic control condition: scrambled pictures and reversed speech, respectively. These large-scale data of the left, language-dominant hemisphere uniquely enable convergent, high-resolution analyses of neural mechanisms characterized by rapid, transient dynamics with strong interactions between distributed cortical substrates. We observed three stages of activity during both visual picture naming and auditory naming to definition that were serially organized: sensory processing, lexical semantic processing, and articulation. Critically, the second stage was absent in both the visual and auditory control conditions. Group activity maps from both electrocorticography and functional MRI identified heteromodal responses in middle fusiform gyrus, intraparietal sulcus, and inferior frontal gyrus; furthermore, the spectrotemporal profiles of these three regions revealed coincident activity preceding articulation. Only in the middle fusiform gyrus did direct cortical stimulation disrupt both naming tasks while still preserving the ability to repeat sentences. These convergent data strongly support a model in which a distinct neuroanatomical substrate in middle fusiform gyrus provides access to object semantic information. This under-appreciated locus of semantic processing is at risk in resections for temporal lobe epilepsy as well as in trauma and strokes that affect the inferior temporal cortex—it may explain the range of anomic states seen in these conditions. Further characterization of brain network behaviour engaging this region in both healthy and diseased states will expand our understanding of semantic memory and further development of therapies directed at anomia.

Invasive intracranial EEG (icEEG) offers a unique opportunity to study human cognitive networks at an unmatched spatiotemporal resolution. To date, the contributions of icEEG have been limited to the individual-level analyses or cohorts whose data are not integrated in any way. Here we discuss how grouped approaches to icEEG overcome challenges related to sparse-sampling, correct for individual variations in response and provide statistically valid models of brain activity in a population. By the generation of whole-brain activity maps, grouped icEEG enables the study of intra and interregional dynamics between distributed cortical substrates exhibiting task-dependent activity. In this fashion, grouped icEEG analyses can provide significant advances in understanding the mechanisms by which cortical networks give rise to cognitive functions.