Semantic encoding during language comprehension at single-cell resolution.

From sequences of speech sounds1,2 or letters3, humans can extract rich and nuanced meaning through language. This capacity is essential for human communication. Yet, despite a growing understanding of the brain areas that support linguistic and semantic processing4-12, the derivation of linguistic meaning in neural tissue at the cellular level and over the timescale of action potentials remains largely unknown. Here we recorded from single cells in the left language-dominant prefrontal cortex as participants listened to semantically diverse sentences and naturalistic stories. By tracking their activities during natural speech processing, we discover a fine-scale cortical representation of semantic information by individual neurons. These neurons responded selectively to specific word meanings and reliably distinguished words from nonwords. Moreover, rather than responding to the words as fixed memory representations, their activities were highly dynamic, reflecting the words' meanings based on their specific sentence contexts and independent of their phonetic form. Collectively, we show how these cell ensembles accurately predicted the broad semantic categories of the words as they were heard in real time during speech and how they tracked the sentences in which they appeared. We also show how they encoded the hierarchical structure of these meaning representations and how these representations mapped onto the cell population. Together, these findings reveal a finely detailed cortical organization of semantic representations at the neuron scale in humans and begin to illuminate the cellular-level processing of meaning during language comprehension.

Single-neuronal elements of speech production in humans.

Humans are capable of generating extraordinarily diverse articulatory movement combinations to produce meaningful speech. This ability to orchestrate specific phonetic sequences, and their syllabification and inflection over subsecond timescales allows us to produce thousands of word sounds and is a core component of language1,2. The fundamental cellular units and constructs by which we plan and produce words during speech, however, remain largely unknown. Here, using acute ultrahigh-density Neuropixels recordings capable of sampling across the cortical column in humans, we discover neurons in the language-dominant prefrontal cortex that encoded detailed information about the phonetic arrangement and composition of planned words during the production of natural speech. These neurons represented the specific order and structure of articulatory events before utterance and reflected the segmentation of phonetic sequences into distinct syllables. They also accurately predicted the phonetic, syllabic and morphological components of upcoming words and showed a temporally ordered dynamic. Collectively, we show how these mixtures of cells are broadly organized along the cortical column and how their activity patterns transition from articulation planning to production. We also demonstrate how these cells reliably track the detailed composition of consonant and vowel sounds during perception and how they distinguish processes specifically related to speaking from those related to listening. Together, these findings reveal a remarkably structured organization and encoding cascade of phonetic representations by prefrontal neurons in humans and demonstrate a cellular process that can support the production of speech.

Temporal dynamics of neural activity in macaque frontal cortex assessed with large-scale recordings.

The cortical network controlling the arm and hand when grasping objects consists of several areas in parietal and frontal cortex. Recently, more anterior prefrontal areas have also been implicated in object grasping, but their exact role is currently unclear. To investigate the neuronal encoding of objects during grasping in these prefrontal regions and their relation with other cortical areas of the grasping network, we performed large-scale recordings (more than 2000 responsive sites) in frontal cortex of monkeys during a saccade-reach-grasp task. When an object appeared in peripheral vision, the first burst of activity emerged in prearcuate areas (the FEF and area 45B), followed by dorsal and ventral premotor cortex, and a buildup of activity in primary motor cortex. After the saccade, prearcuate activity remained elevated while primary motor and premotor activity rose in anticipation of the upcoming arm and hand movement. Remarkably, a large number of premotor and prearcuate sites responded when the object appeared in peripheral vision and remained active when the object came into foveal vision. Thus, prearcuate and premotor areas continuously encode object information when directing gaze and grasping objects.

Shape responses in a macaque frontal area connected to posterior parietal cortex.

The primate dorsal visual stream processes object shape to guide actions involving an object, but the transmission of shape information beyond posterior parietal cortex remains largely unknown. To clarify the information flow between parietal and frontal cortex, we applied electrical microstimulation during functional Magnetic Resonance Imaging (fMRI) in a shape-selective patch in the posterior part of the Anterior Intraparietal area (pAIP) to chart its connectivity. Subsequently, we recorded single-unit responses to images of objects in the fMRI activation in prefrontal cortex, corresponding to area 45B, elicited by pAIP microstimulation. Neurons in area 45B had properties similar to neurons in pAIP, responding selectively to shape contours and to very small shape fragments measuring less than one deg at exceedingly short latencies. However, contrary to the prevailing view on the hierarchical organization of cortical areas, neurons in area 45B preferred even smaller shape fragments and had smaller receptive fields than neurons in pAIP. These findings provide the first evidence for ultra-fast shape processing in prefrontal cortex, and suggest that the pathway from pAIP to area 45B may not be important for object grasping.

ROBUST ONLINE MULTIBAND DRIFT ESTIMATION IN ELECTROPHYSIOLOGY DATA.

High-density electrophysiology probes have opened new possibilities for systems neuroscience in human and non-human animals, but probe motion poses a challenge for downstream analyses, particularly in human recordings. We improve on the state of the art for tracking this motion with four major contributions. First, we extend previous decentralized methods to use multiband information, leveraging the local field potential (LFP) in addition to spikes. Second, we show that the LFP-based approach enables registration at sub-second temporal resolution. Third, we introduce an efficient online motion tracking algorithm, enabling the method to scale up to longer and higher-resolution recordings, and possibly facilitating real-time applications. Finally, we improve the robustness of the approach by introducing a structure-aware objective and simple methods for adaptive parameter selection. Together, these advances enable fully automated scalable registration of challenging datasets from human and mouse.

Modified Neuropixels probes for recording human neurophysiology in the operating room.

Neuropixels are silicon-based electrophysiology-recording probes with high channel count and recording-site density. These probes offer a turnkey platform for measuring neural activity with single-cell resolution and at a scale that is beyond the capabilities of current clinically approved devices. Our team demonstrated the first-in-human use of these probes during resection surgery for epilepsy or tumors and deep brain stimulation electrode placement in patients with Parkinson's disease. Here, we provide a better understanding of the capabilities and challenges of using Neuropixels as a research tool to study human neurophysiology, with the hope that this information may inform future efforts toward regulatory approval of Neuropixels probes as research devices. In perioperative procedures, the major concerns are the initial sterility of the device, maintaining a sterile field during surgery, having multiple referencing and grounding schemes available to de-noise recordings (if necessary), protecting the silicon probe from accidental contact before insertion and obtaining high-quality action potential and local field potential recordings. The research team ensures that the device is fully operational while coordinating with the surgical team to remove sources of electrical noise that could otherwise substantially affect the signals recorded by the sensitive hardware. Prior preparation using the equipment and training in human clinical research and working in operating rooms maximize effective communication within and between the teams, ensuring high recording quality and minimizing the time added to the surgery. The perioperative procedure requires ~4 h, and the entire protocol requires multiple weeks.

DREDge: robust motion correction for high-density extracellular recordings across species.

High-density microelectrode arrays (MEAs) have opened new possibilities for systems neuroscience in human and non-human animals, but brain tissue motion relative to the array poses a challenge for downstream analyses, particularly in human recordings. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm which is well suited for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from spikes in the action potential (AP) frequency band, DREDge enables automated tracking of motion at high temporal resolution in the local field potential (LFP) frequency band. In human intraoperative recordings, which often feature fast (period <1s) motion, DREDge correction in the LFP band enabled reliable recovery of evoked potentials, and significantly reduced single-unit spike shape variability and spike sorting error. Applying DREDge to recordings made during deep probe insertions in nonhuman primates demonstrated the possibility of tracking probe motion of centimeters across several brain regions while simultaneously mapping single unit electrophysiological features. DREDge reliably delivered improved motion correction in acute mouse recordings, especially in those made with an recent ultra-high density probe. We also implemented a procedure for applying DREDge to recordings made across tens of days in chronic implantations in mice, reliably yielding stable motion tracking despite changes in neural activity across experimental sessions. Together, these advances enable automated, scalable registration of electrophysiological data across multiple species, probe types, and drift cases, providing a stable foundation for downstream scientific analyses of these rich datasets.

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings.

Previous studies have shown that neurons in parieto-frontal areas of the macaque brain can be highly selective for real-world objects, disparity-defined curved surfaces, and images of real-world objects (with and without disparity) in a similar manner as described in the ventral visual stream. In addition, parieto-frontal areas are believed to convert visual object information into appropriate motor outputs, such as the pre-shaping of the hand during grasping. To better characterize object selectivity in the cortical network involved in visuomotor transformations, we provide a battery of tests intended to analyze the visual object selectivity of neurons in parieto-frontal regions.