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During conversation, people take turns speaking by rapidly responding to their partners while simultaneously avoiding interruption 1 , 2 . Such interactions display a remarkable degree of coordination, as gaps between turns are typically about 200 milliseconds 3 —approximately the duration of an eyeblink 4 . These latencies are considerably shorter than those observed in simple word-production tasks, which indicates that speakers often plan their responses while listening to their partners 2 . Although a distributed network of brain regions has been implicated in speech planning 5 – 9 , the neural dynamics underlying the specific preparatory processes that enable rapid turn-taking are poorly understood. Here we use intracranial electrocorticography to precisely measure neural activity as participants perform interactive tasks, and we observe a functionally and anatomically distinct class of planning-related cortical dynamics. We localize these responses to a frontotemporal circuit centred on the language-critical caudal inferior frontal cortex 10 (Broca’s region) and the caudal middle frontal gyrus—a region not normally implicated in speech planning 11 – 13 . Using a series of motor tasks, we then show that this planning network is more active when preparing speech as opposed to non-linguistic actions. Finally, we delineate planning-related circuitry during natural conversation that is nearly identical to the network mapped with our interactive tasks, and we find this circuit to be most active before participant speech during unconstrained turn-taking. Therefore, we have identified a speech planning network that is central to natural language generation during social interaction. Using intracranial electrocorticography and a series of motor tasks, a speech planning network that is central to natural language generation during social interaction is identified.

Differential DNA methylation in the brain is associated with many psychiatric diseases, but access to brain tissues is essentially limited to postmortem samples. The use of surrogate tissues has become common in identifying methylation changes associated with psychiatric disease. In this study, we determined the extent to which peripheral tissues can be used as surrogates for DNA methylation in the brain. Blood, saliva, buccal, and live brain tissue samples from 27 patients with medically intractable epilepsy undergoing brain resection were collected (age range 5–61 years). Genome-wide methylation was assessed with the Infinium HumanMethylation450 (n = 12) and HumanMethylationEPIC BeadChip arrays (n = 21). For the EPIC methylation data averaged for each CpG across subjects, the saliva–brain correlation (r = 0.90) was higher than that for blood–brain (r = 0.86) and buccal–brain (r = 0.85) comparisons. However, within individual CpGs, blood had the highest proportion of CpGs correlated to brain at nominally significant levels (20.8%), as compared to buccal tissue (17.4%) and saliva (15.1%). For each CpG and each gene, levels of brain-peripheral tissue correlation varied widely. This indicates that to determine the most useful surrogate tissue for representing brain DNA methylation, the patterns specific to the genomic region of interest must be considered. To assist in that objective, we have developed a website, IMAGE-CpG, that allows researchers to interrogate DNA methylation levels and degree of cross-tissue correlation in user-defined locations across the genome.

•iEEG activity during listening can be time-locked to the stimulus or behavior.•Auditory cortex is exclusively stimulus-driven.•Behavior-locked activity is prominent in left prefrontal cortex.•Activity in right sensorimotor cortex is largely stimulus-driven.•Faster reaction times correlate with stimulus-driven iEEG activity. Auditory areas on the superior temporal plane and lateral convexity are key initial stages of speech processing in the human cortex, representing acoustic and phonetic attributes in a temporally precise manner. More complex representations in auditory-related cortex along the ventral and dorsal processing streams and prefrontal cortex are associated with perception and action. In this study, we used intracranial electroencephalography (iEEG) to clarify where and how activity leading to perceptually driven behavioral events emerges. Participants were patients undergoing iEEG monitoring for medically intractable epilepsy. Stimuli were monosyllabic words, and participants pressed a button in response to a semantic target category. Significant high gamma activity after stimulus onset and immediately prior to motor response defined stimulus- and behavior-related activity patterns, respectively. The stimulus-related pattern was more common than behavior-related throughout the cortical auditory hierarchy as well as sensorimotor cortex. Behavior-related activity was sparsely represented, with the highest prevalence in the prefrontal cortex and a more limited representation in anterior temporal and parieto-occipital cortex. Hemispheric asymmetries included a higher prevalence of stimulus-related activity in the right sensorimotor cortex and a higher prevalence of the behavior-related pattern in the left prefrontal cortex. Faster behavioral responses were associated with greater stimulus-locked high gamma power in non-core auditory, prefrontal, and premotor cortex. Results reveal the cortical distribution of sensory stimulus-driven responses and activity time-locked to behavior and provide insights into neural substrates of speech perception.

Acidosis can stop seizures, but it is unclear how it does this. This study demonstrates that the acid-sensing channel ASIC1a is required for either spontaneous or CO 2 -induced termination of convulsant-induced seizures in mice. Moreover, ASIC1a strongly activates inhibitory interneurons under acidotic conditions, which may explain the effect. Most seizures stop spontaneously; however, the molecular mechanisms that terminate seizures remain unknown. Observations that seizures reduced brain pH and that acidosis inhibited seizures indicate that acidosis halts epileptic activity. Because acid-sensing ion channel 1a (ASIC1a) is exquisitely sensitive to extracellular pH and regulates neuron excitability, we hypothesized that acidosis might activate ASIC1a, which would terminate seizures. Disrupting mouse ASIC1a increased the severity of chemoconvulsant-induced seizures, whereas overexpressing ASIC1a had the opposite effect. ASIC1a did not affect seizure threshold or onset, but shortened seizure duration and prevented seizure progression. CO 2 inhalation, long known to lower brain pH and inhibit seizures, required ASIC1a to interrupt tonic-clonic seizures. Acidosis activated inhibitory interneurons through ASIC1a, suggesting that ASIC1a might limit seizures by increasing inhibitory tone. Our results identify ASIC1a as an important element in seizure termination when brain pH falls and suggest both a molecular mechanism for how the brain stops seizures and new therapeutic strategies.

Generative models, such as predictive coding, posit that perception results from a combination of sensory input and prior prediction, each weighted by its precision (inverse variance), with incongruence between these termed prediction error (deviation from prediction) or surprise (negative log probability of the sensory input). However, direct evidence for such a system, and the physiological basis of its computations, is lacking. Using an auditory stimulus whose pitch value changed according to specific rules, we controlled and separated the three key computational variables underlying perception, and discovered, using direct recordings from human auditory cortex, that surprise due to prediction violations is encoded by local field potential oscillations in the gamma band (>30 Hz), changes to predictions in the beta band (12-30 Hz), and that the precision of predictions appears to quantitatively relate to alpha band oscillations (8-12 Hz). These results confirm oscillatory codes for critical aspects of generative models of perception. Our perception of the world is not only based on input from our senses. Instead, what we perceive is also heavily altered by the context of what is being sensed and our expectations about it. Some researchers have suggested that perception results from combining information from our senses and our predictions. This school of thought, referred to as “predictive coding”, essentially proposed that the brain stores a model of the world and weighs it up against information from our senses in order to determine what we perceive. Nevertheless, direct evidence for the brain working in this way was still missing. While neuroscientists had seen the brain respond when there was a mismatch between an expectation and incoming sensory information, no one has observed the predictions themselves within the brain. Sedley et al. now provide such direct evidence for predictions about upcoming sensory information, by directly recording the electrical activity in the brains of human volunteers who were undergoing surgery for epilepsy. The experiment made use of a new method in which the volunteers listened to a sequence of sounds that was semi-predictable. That is to say that, at first, the volunteers heard a selection of similarly pitched sounds. After random intervals, the average pitch of these sounds changed and they became more or less variable for a while before randomly changing again. This approach meant that the volunteers had to continually update their predictions throughout the experiment In keeping with previous studies, the unexpected sounds, which caused a mismatch between the sensory information and the brain’s prediction, were linked to high-frequency brainwaves. However, Sedley et al. discovered that updating the predictions themselves was linked to middle-frequency brainwaves; this confirms what the predictive coding model had suggested. Finally, this approach also unexpectedly revealed that how confident the volunteer was about the prediction was linked to low-frequency brainwaves. In the future, this new method will provide an easy way of directly studying elements of perception in humans and, since the experiments do not require complex learning, in other animals too.

Under the predictive coding hypothesis, specific spatiotemporal patterns of cortical activation are postulated to occur during sensory processing as expectations generate feedback predictions and prediction errors generate feedforward signals. Establishing experimental evidence for this information flow within cortical hierarchy has been difficult, especially in humans, due to spatial and temporal limitations of non-invasive measures of cortical activity. This study investigated cortical responses to auditory novelty using the local/global deviant paradigm, which engages the hierarchical network underlying auditory predictive coding over short (‘local deviance’; LD) and long (‘global deviance’; GD) time scales. Electrocorticographic responses to auditory stimuli were obtained in neurosurgical patients from regions of interest (ROIs) including auditory, auditory-related and prefrontal cortex. LD and GD effects were assayed in averaged evoked potential (AEP) and high gamma (70–150 Hz) signals, the former likely dominated by local synaptic currents and the latter largely reflecting local spiking activity. AEP LD effects were distributed across all ROIs, with greatest percentage of significant sites in core and non-core auditory cortex. High gamma LD effects were localized primarily to auditory cortex in the superior temporal plane and on the lateral surface of the superior temporal gyrus (STG). LD effects exhibited progressively longer latencies in core, non-core, auditory-related and prefrontal cortices, consistent with feedforward signaling. The spatial distribution of AEP GD effects overlapped that of LD effects, but high gamma GD effects were more restricted to non-core areas. High gamma GD effects had shortest latencies in STG and preceded AEP GD effects in most ROIs. This latency profile, along with the paucity of high gamma GD effects in the superior temporal plane, suggest that the STG plays a prominent role in initiating novelty detection signals over long time scales. Thus, the data demonstrate distinct patterns of information flow in human cortex associated with auditory novelty detection over multiple time scales. •Local deviance effects are more broadly distributed than global effects.•Local deviance effects have the shortest onset latencies in core auditory cortex.•Local deviance effect latencies become longer along the auditory cortical hierarchy.•Global deviance effects have the shortest onset latencies in lateral temporal cortex.

The primate amygdala is a complex consisting of over a dozen nuclei that have been implicated in a host of cognitive functions, individual differences, and psychiatric illnesses. These functions are implemented through distinct connectivity profiles, which have been documented in animals but remain largely unknown in humans. Here we present results from 25 neurosurgical patients who had concurrent electrical stimulation of the amygdala with intracranial electroencephalography (electrical stimulation tract-tracing; es-TT), or fMRI (electrical stimulation fMRI; es-fMRI), methods providing strong inferences about effective connectivity of amygdala subdivisions with the rest of the brain. We quantified functional connectivity with medial and lateral amygdala, the temporal order of these connections on the timescale of milliseconds, and also detail second-order effective connectivity among the key nodes. These findings provide a uniquely detailed characterization of human amygdala functional connectivity that will inform functional neuroimaging studies in healthy and clinical populations. The amygdala is known to be engaged in emotional and autonomic function, yet the detailed functional connectivity of the human amygdala remains unclear. Here, the authors examine effective connectivity in the amygdala of patients with epilepsy using direct focal electrical stimulation.

Learning complex ordering relationships between sensory events in a sequence is fundamental for animal perception and human communication. While it is known that rhythmic sensory events can entrain brain oscillations at different frequencies, how learning and prior experience with sequencing relationships affect neocortical oscillations and neuronal responses is poorly understood. We used an implicit sequence learning paradigm (an \"artificial grammar\") in which humans and monkeys were exposed to sequences of nonsense words with regularities in the ordering relationships between the words. We then recorded neural responses directly from the auditory cortex in both species in response to novel legal sequences or ones violating specific ordering relationships. Neural oscillations in both monkeys and humans in response to the nonsense word sequences show strikingly similar hierarchically nested low-frequency phase and high-gamma amplitude coupling, establishing this form of oscillatory coupling-previously associated with speech processing in the human auditory cortex-as an evolutionarily conserved biological process. Moreover, learned ordering relationships modulate the observed form of neural oscillatory coupling in both species, with temporally distinct neural oscillatory effects that appear to coordinate neuronal responses in the monkeys. This study identifies the conserved auditory cortical neural signatures involved in monitoring learned sequencing operations, evident as modulations of transient coupling and neuronal responses to temporally structured sensory input.

During speaking, auditory feedback is used to adjust vocalizations. The brain systems mediating this integrative ability have been investigated using a wide range of experimental strategies. In this report we examined how vocalization alters speech-sound processing within auditory cortex by directly recording evoked responses to vocalizations and playback stimuli using intracranial electrodes implanted in neurosurgery patients. Several new findings resulted from these high-resolution invasive recordings in human subjects. Suppressive effects of vocalization were found to occur only within circumscribed areas of auditory cortex. In addition, at a smaller number of sites, the opposite pattern was seen; cortical responses were enhanced during vocalization. This increase in activity was reflected in high gamma power changes, but was not evident in the averaged evoked potential waveforms. These new findings support forward models for vocal control in which efference copies of premotor cortex activity modulate sub-regions of auditory cortex.

The neural mechanisms underlying processing of auditory feedback during self-vocalization are poorly understood. One technique used to study the role of auditory feedback involves shifting the pitch of the feedback that a speaker receives, known as pitch-shifted feedback. We utilized a pitch shift self-vocalization and playback paradigm to investigate the underlying neural mechanisms of audio-vocal interaction. High-resolution electrocorticography (ECoG) signals were recorded directly from auditory cortex of 10 human subjects while they vocalized and received brief downward (-100 cents) pitch perturbations in their voice auditory feedback (speaking task). ECoG was also recorded when subjects passively listened to playback of their own pitch-shifted vocalizations. Feedback pitch perturbations elicited average evoked potential (AEP) and event-related band power (ERBP) responses, primarily in the high gamma (70-150 Hz) range, in focal areas of non-primary auditory cortex on superior temporal gyrus (STG). The AEPs and high gamma responses were both modulated by speaking compared with playback in a subset of STG contacts. From these contacts, a majority showed significant enhancement of high gamma power and AEP responses during speaking while the remaining contacts showed attenuated response amplitudes. The speaking-induced enhancement effect suggests that engaging the vocal motor system can modulate auditory cortical processing of self-produced sounds in such a way as to increase neural sensitivity for feedback pitch error detection. It is likely that mechanisms such as efference copies may be involved in this process, and modulation of AEP and high gamma responses imply that such modulatory effects may affect different cortical generators within distinctive functional networks that drive voice production and control.