Enhanced Dendritic Compartmentalization in Human Cortical Neurons.

The biophysical features of neurons shape information processing in the brain. Cortical neurons are larger in humans than in other species, but it is unclear how their size affects synaptic integration. Here, we perform direct electrical recordings from human dendrites and report enhanced electrical compartmentalization in layer 5 pyramidal neurons. Compared to rat dendrites, distal human dendrites provide limited excitation to the soma, even in the presence of dendritic spikes. Human somas also exhibit less bursting due to reduced recruitment of dendritic electrogenesis. Finally, we find that decreased ion channel densities result in higher input resistance and underlie the lower coupling of human dendrites. We conclude that the increased length of human neurons alters their input-output properties, which will impact cortical computation. VIDEO ABSTRACT.

Neuronal prediction of opponent's behavior during cooperative social interchange in primates.

A cornerstone of successful social interchange is the ability to anticipate each other's intentions or actions. While generating these internal predictions is essential for constructive social behavior, their single neuronal basis and causal underpinnings are unknown. Here, we discover specific neurons in the primate dorsal anterior cingulate that selectively predict an opponent's yet unknown decision to invest in their common good or defect and distinct neurons that encode the monkey's own current decision based on prior outcomes. Mixed population predictions of the other was remarkably near optimal compared to behavioral decoders. Moreover, disrupting cingulate activity selectively biased mutually beneficial interactions between the monkeys but, surprisingly, had no influence on their decisions when no net-positive outcome was possible. These findings identify a group of other-predictive neurons in the primate anterior cingulate essential for enacting cooperative interactions and may pave a way toward the targeted treatment of social behavioral disorders.

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.

Frontal neurons driving competitive behaviour and ecology of social groups.

Competitive interactions have a vital role in the ecology of most animal species1-3 and powerfully influence the behaviour of groups4,5. To succeed, individuals must exert effort based on not only the resources available but also the social rank and behaviour of other group members2,6,7. The single-cellular mechanisms that precisely drive competitive interactions or the behaviour of social groups, however, remain poorly understood. Here we developed a naturalistic group paradigm in which large cohorts of mice competitively foraged for food as we wirelessly tracked neuronal activities across thousands of unique interactions. By following the collective behaviour of the groups, we found neurons in the anterior cingulate that adaptively represented the social rank of the animals in relation to others. Although social rank was closely behaviourally linked to success, these cells disambiguated the relative rank of the mice from their competitive behaviour, and incorporated information about the resources available, the environment, and past success of the mice to influence their decisions. Using multiclass models, we show how these neurons tracked other individuals within the group and accurately predicted upcoming success. Using neuromodulation techniques, we also show how the neurons conditionally influenced competitive effort-increasing the effort of the animals only when they were more dominant to their groupmates and decreasing it when they were subordinate-effects that were not observed in other frontal lobe areas. Together, these findings reveal cingulate neurons that serve to adaptively drive competitive interactions and a putative process that could intermediate the social and economic behaviour of groups.

Single-neuronal predictions of others' beliefs in humans.

Human social behaviour crucially depends on our ability to reason about others. This capacity for theory of mind has a vital role in social cognition because it enables us not only to form a detailed understanding of the hidden thoughts and beliefs of other individuals but also to understand that they may differ from our own1-3. Although a number of areas in the human brain have been linked to social reasoning4,5 and its disruption across a variety of psychosocial disorders6-8, the basic cellular mechanisms that underlie human theory of mind remain undefined. Here, using recordings from single cells in the human dorsomedial prefrontal cortex, we identify neurons that reliably encode information about others' beliefs across richly varying scenarios and that distinguish self- from other-belief-related representations. By further following their encoding dynamics, we show how these cells represent the contents of the others' beliefs and accurately predict whether they are true or false. We also show how they track inferred beliefs from another's specific perspective and how their activities relate to behavioural performance. Together, these findings reveal a detailed cellular process in the human dorsomedial prefrontal cortex for representing another's beliefs and identify candidate neurons that could support theory of mind.

Allometric rules for mammalian cortical layer 5 neuron biophysics.

The biophysical properties of neurons are the foundation for computation in the brain. Neuronal size is a key determinant of single neuron input-output features and varies substantially across species1-3. However, it is unknown whether different species adapt neuronal properties to conserve how single neurons process information4-7. Here we characterize layer 5 cortical pyramidal neurons across 10 mammalian species to identify the allometric relationships that govern how neuronal biophysics change with cell size. In 9 of the 10 species, we observe conserved rules that control the conductance of voltage-gated potassium and HCN channels. Species with larger neurons, and therefore a decreased surface-to-volume ratio, exhibit higher membrane ionic conductances. This relationship produces a conserved conductance per unit brain volume. These size-dependent rules result in large but predictable changes in somatic and dendritic integrative properties. Human neurons do not follow these allometric relationships, exhibiting much lower voltage-gated potassium and HCN conductances. Together, our results in layer 5 neurons identify conserved evolutionary principles for neuronal biophysics in mammals as well as notable features of the human cortex.

Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans.

How the human cortex integrates ("binds") information encoded by spatially distributed neurons remains largely unknown. One hypothesis suggests that synchronous bursts of high-frequency oscillations ("ripples") contribute to binding by facilitating integration of neuronal firing across different cortical locations. While studies have demonstrated that ripples modulate local activity in the cortex, it is not known whether their co-occurrence coordinates neural firing across larger distances. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in the supragranular cortex of 3 patients. Neurons in co-rippling locations showed increased short-latency co-firing, prediction of each other's firing, and co-participation in neural assemblies. Effects were similar for putative pyramidal and interneurons, during non-rapid eye movement sleep and waking, in temporal and Rolandic cortices, and at distances up to 16 mm (the longest tested). Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, indicating that it was not secondary to non-oscillatory activation. Co-rippling enhanced prediction was strongly modulated by ripple phase, supporting the most common posited mechanism for binding-by-synchrony. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple, supporting re-entrant facilitation. Together, these results support the hypothesis that trans-cortical co-occurring ripples increase the integration of neuronal firing of neurons in different cortical locations and do so in part through phase-modulation rather than unstructured activation.

Learned Motor Patterns Are Replayed in Human Motor Cortex during Sleep.

Consolidation of memory is believed to involve offline replay of neural activity. While amply demonstrated in rodents, evidence for replay in humans, particularly regarding motor memory, is less compelling. To determine whether replay occurs after motor learning, we sought to record from motor cortex during a novel motor task and subsequent overnight sleep. A 36-year-old man with tetraplegia secondary to cervical spinal cord injury enrolled in the ongoing BrainGate brain-computer interface pilot clinical trial had two 96-channel intracortical microelectrode arrays placed chronically into left precentral gyrus. Single- and multi-unit activity was recorded while he played a color/sound sequence matching memory game. Intended movements were decoded from motor cortical neuronal activity by a real-time steady-state Kalman filter that allowed the participant to control a neurally driven cursor on the screen. Intracortical neural activity from precentral gyrus and 2-lead scalp EEG were recorded overnight as he slept. When decoded using the same steady-state Kalman filter parameters, intracortical neural signals recorded overnight replayed the target sequence from the memory game at intervals throughout at a frequency significantly greater than expected by chance. Replay events occurred at speeds ranging from 1 to 4 times as fast as initial task execution and were most frequently observed during slow-wave sleep. These results demonstrate that recent visuomotor skill acquisition in humans may be accompanied by replay of the corresponding motor cortex neural activity during sleep.SIGNIFICANCE STATEMENT Within cortex, the acquisition of information is often followed by the offline recapitulation of specific sequences of neural firing. Replay of recent activity is enriched during sleep and may support the consolidation of learning and memory. Using an intracortical brain-computer interface, we recorded and decoded activity from motor cortex as a human research participant performed a novel motor task. By decoding neural activity throughout subsequent sleep, we find that neural sequences underlying the recently practiced motor task are repeated throughout the night, providing direct evidence of replay in human motor cortex during sleep. This approach, using an optimized brain-computer interface decoder to characterize neural activity during sleep, provides a framework for future studies exploring replay, learning, and memory.

Cell diversity and network dynamics in photosensitive human brain organoids.

In vitro models of the developing brain such as three-dimensional brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, the cells generated within organoids and the extent to which they recapitulate the regional complexity, cellular diversity and circuit functionality of the brain remain undefined. Here we analyse gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (more than 9 months), allowing for the establishment of relatively mature features, including the formation of dendritic spines and spontaneously active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photosensitive cells, which may offer a way to probe the functionality of human neuronal circuits using physiological sensory stimuli.

Microscale Physiological Events on the Human Cortical Surface.

Despite ongoing advances in our understanding of local single-cellular and network-level activity of neuronal populations in the human brain, extraordinarily little is known about their "intermediate" microscale local circuit dynamics. Here, we utilized ultra-high-density microelectrode arrays and a rare opportunity to perform intracranial recordings across multiple cortical areas in human participants to discover three distinct classes of cortical activity that are not locked to ongoing natural brain rhythmic activity. The first included fast waveforms similar to extracellular single-unit activity. The other two types were discrete events with slower waveform dynamics and were found preferentially in upper cortical layers. These second and third types were also observed in rodents, nonhuman primates, and semi-chronic recordings from humans via laminar and Utah array microelectrodes. The rates of all three events were selectively modulated by auditory and electrical stimuli, pharmacological manipulation, and cold saline application and had small causal co-occurrences. These results suggest that the proper combination of high-resolution microelectrodes and analytic techniques can capture neuronal dynamics that lay between somatic action potentials and aggregate population activity. Understanding intermediate microscale dynamics in relation to single-cell and network dynamics may reveal important details about activity in the full cortical circuit.

Local and distant responses to single pulse electrical stimulation reflect different forms of connectivity.

Measuring connectivity in the human brain involves innumerable approaches using both noninvasive (fMRI, EEG) and invasive (intracranial EEG or iEEG) recording modalities, including the use of external probing stimuli, such as direct electrical stimulation. To examine how different measures of connectivity correlate with one another, we compared 'passive' measures of connectivity during resting state conditions to the more 'active' probing measures of connectivity with single pulse electrical stimulation (SPES). We measured the network engagement and spread of the cortico-cortico evoked potential (CCEP) induced by SPES at 53 out of 104 total sites across the brain, including cortical and subcortical regions, in patients with intractable epilepsy (N=11) who were undergoing intracranial recordings as a part of their clinical care for identifying seizure onset zones. We compared the CCEP network to functional, effective, and structural measures of connectivity during a resting state in each patient. Functional and effective connectivity measures included correlation or Granger causality measures applied to stereoEEG (sEEGs) recordings. Structural connectivity was derived from diffusion tensor imaging (DTI) acquired before intracranial electrode implant and monitoring (N=8). The CCEP network was most similar to the resting state voltage correlation network in channels near to the stimulation location. In contrast, the distant CCEP network was most similar to the DTI network. Other connectivity measures were not as similar to the CCEP network. These results demonstrate that different connectivity measures, including those derived from active stimulation-based probing, measure different, complementary aspects of regional interrelationships in the brain.

Vagus Nerve Stimulation versus Responsive Neurostimulator System in Patients with Temporal Lobe Epilepsy.

INTRODUCTION: Patients with medically refractory temporal lobe epilepsy (TLE) are candidates for neuromodulation procedures. While vagus nerve stimulation (VNS) was historically the procedure of choice for this condition, the responsive neurostimulation system (RNS) has come into favor for its more targeted approach. While both VNS and RNS have been reported as efficacious treatments for TLE, the outcomes of these 2 procedures have not been directly compared. This study aims to compare outcomes following VNS versus RNS for TLE. METHODS: We retrospectively reviewed the records of all patients with TLE who underwent VNS or RNS placement at our institution from 2003 to 2018. The primary outcome was change in seizure frequency. Other outcomes included Engel score, change in anti-epileptic medications, and complications. RESULTS: Twenty-three patients met inclusion criteria; 11 underwent VNS and 12 underwent RNS. At baseline, the 2 groups were statistically similar regarding age at surgery, epilepsy duration, and preoperative seizure frequency. At last follow-up, both groups displayed reduced seizure frequency (mean reduction of 46.3% for the VNS group and 58.1% for the RNS group, p = 0.49). Responder rate, Engel score, and change in medications were statistically similar between groups. Compared to 0.0% of the VNS group, 13.3% of the RNS group experienced infection requiring re-operation. CONCLUSION: Despite their different mechanisms, VNS and RNS resulted in similar response rates for patients with TLE. We suggest that VNS should not be excluded as a treatment for patients with medically refractory TLE who are not candidates for resective or ablative procedures.

Human dorsal anterior cingulate cortex neurons mediate ongoing behavioural adaptation.

The ability to optimize behavioural performance when confronted with continuously evolving environmental demands is a key element of human cognition. The dorsal anterior cingulate cortex (dACC), which lies on the medial surface of the frontal lobes, is important in regulating cognitive control. Hypotheses about its function include guiding reward-based decision making, monitoring for conflict between competing responses and predicting task difficulty. Precise mechanisms of dACC function remain unknown, however, because of the limited number of human neurophysiological studies. Here we use functional imaging and human single-neuron recordings to show that the firing of individual dACC neurons encodes current and recent cognitive load. We demonstrate that the modulation of current dACC activity by previous activity produces a behavioural adaptation that accelerates reactions to cues of similar difficulty to previous ones, and retards reactions to cues of different difficulty. Furthermore, this conflict adaptation, or Gratton effect, is abolished after surgically targeted ablation of the dACC. Our results demonstrate that the dACC provides a continuously updated prediction of expected cognitive demand to optimize future behavioural responses. In situations with stable cognitive demands, this signal promotes efficiency by hastening responses, but in situations with changing demands it engenders accuracy by delaying responses.

Transgenerational influence of sensorimotor training on offspring behavior and its neural basis in Drosophila.

Whether specific learning experiences by parents influence the behavior of subsequent generations remains unclear. This study examines whether and what aspects of parental sensorimotor training prior to conception affect the behavior of subsequent generations and identifies the neural circuitries in Drosophila responsible for mediating these effects. Using genetic and anatomic techniques, I find that both first- and second-generation offspring of parents who underwent prolonged olfactory training over many days displayed a weak but selective approach bias to the same trained odors. However, I also find that the offspring did not differentiate between orders based on whether parental training was aversive or appetitive. Disruption of both olfactory-receptor and dorsal-paired-medial neuron input into the mushroom bodies abolished this change in offspring response, but disrupting synaptic output from α/ß neurons of the mushroom body themselves had little effect on behavior even though they remained necessary for enacting newly trained conditioned responses. This study provides a circuit-based understanding of how specific sensory experiences in Drosophila may bias the behavior of subsequent generations, and identifies a transgenerational dissociation between the effects of conditioned and unconditioned sensory stimuli.

Frontal neurons modulate memory retrieval across widely varying temporal scales.

Once a memory has formed, it is thought to undergo a gradual transition within the brain from short- to long-term storage. This putative process, however, also poses a unique problem to the memory system in that the same learned items must also be retrieved across broadly varying time scales. Here, we find that neurons in the ventrolateral prefrontal cortex (VLPFC) of monkeys, an area interconnected with both temporal and frontal associative neocortical regions, signaled the need to alter between retrieval of memories formed at different times. These signals were most closely related to the time interval between initial learning and later retrieval, and did not correlate with task switch demands, novelty, or behavioral response. Consistent with these physiological findings, focal inactivation of the VLPFC led to a marked degradation in retrieval performance. These findings suggest that the VLPFC plays a necessary regulatory role in retrieving memories over different temporal scales.

Encoding of rules by neurons in the human dorsolateral prefrontal cortex.

We use rules to extend learned behavior beyond specific instances to general scenarios. The prefrontal cortex (PFC) is thought to play an important role in representing rules, as evidenced by subjects who have difficulty in following rules after PFC damage and by animal studies demonstrating rule sensitivity of individual PFC neurons. How rules are instantiated at the single-neuronal level in the human brain, however, remains unclear. Here, we recorded from individual neurons in the human dorsolateral prefrontal cortex (DLPFC) as subjects performed a task in which they evaluated pairs of images using either of 2 abstract rules. We find that DLPFC neurons selectively encoded these rules while carrying little information about the subjects' responses or the sensory cues used to guide their decisions.

Flexible, scalable, high channel count stereo-electrode for recording in the human brain.

Over the past decade, stereotactically placed electrodes have become the gold standard for deep brain recording and stimulation for a wide variety of neurological and psychiatric diseases. Current electrodes, however, are limited in their spatial resolution and ability to record from small populations of neurons, let alone individual neurons. Here, we report on an innovative, customizable, monolithically integrated human-grade flexible depth electrode capable of recording from up to 128 channels and able to record at a depth of 10 cm in brain tissue. This thin, stylet-guided depth electrode is capable of recording local field potentials and single unit neuronal activity (action potentials), validated across species. This device represents an advance in manufacturing and design approaches which extends the capabilities of a mainstay technology in clinical neurology.

Electrical stimulation-evoked dopamine release in the primate striatum.

BACKGROUND: Primate studies demonstrate that high-frequency electrical stimulation (HFS) of the caudate can enhance learning. Importantly, in these studies, stimulation was applied following the execution of behavior and the effect persisted into subsequent trials, suggesting a change in plasticity rather than a momentary facilitation of behavior. OBJECTIVES/METHODS: Although the mechanism of HFS-enhanced learning is not understood, evidence suggests that dopamine plays a critical role. Therefore, we used in vivo amperometry to evaluate the effects of HFS on striatal dopamine release in the anesthetized primate. While this does not directly examine dopamine during learning, it provides insight with relation to dopamine dynamics during electrical stimulation and specifically between different stimulation parameters and striatal compartments. RESULTS: We demonstrate that HFS results in significantly more dopamine release in the striatum compared to low-frequency stimulation. In addition, electrical stimulation operates differentially on specific neuronal elements, as the parameters for dopamine release are different for the caudate, putamen and medial forebrain bundle. CONCLUSIONS: While not direct evidence, these data suggest that HFS evokes significant dopamine release which may play a role in stimulation-enhanced learning. Moreover, these data suggest a means to modulate extracellular dopamine with a high degree of temporal and spatial precision for either research or clinical applications.