Prefrontal-subthalamic theta signaling mediates delayed responses during conflict processing.

While medial frontal cortex (MFC) and subthalamic nucleus (STN) have been implicated in conflict monitoring and action inhibition, respectively, an integrated understanding of the spatiotemporal and spectral interaction of these nodes and how they interact with motor cortex (M1) to definitively modify motor behavior during conflict is lacking. We recorded neural signals intracranially across presupplementary motor area (preSMA), M1, STN, and globus pallidus internus (GPi), during a flanker task in 20 patients undergoing deep brain stimulation implantation surgery for Parkinson disease or dystonia. Conflict is associated with sequential and causal increases in local theta power from preSMA to STN to M1 with movement delays directly correlated with increased STN theta power, indicating preSMA is the MFC locus that monitors conflict and signals STN to implement a 'break.' Transmission of theta from STN-to-M1 subsequently results in a transient increase in M1-to-GPi beta flow immediately prior to movement, modulating the motor network to actuate the conflict-related action inhibition (i.e., delayed response). Action regulation during conflict relies on two distinct circuits, the conflict-related theta and movement-related beta networks, that are separated spatially, spectrally, and temporally, but which interact dynamically to mediate motor performance, highlighting complex parallel yet interacting networks regulating movement.

Control of working memory by phase-amplitude coupling of human hippocampal neurons.

Retaining information in working memory is a demanding process that relies on cognitive control to protect memoranda-specific persistent activity from interference1,2. However, how cognitive control regulates working memory storage is unclear. Here we show that interactions of frontal control and hippocampal persistent activity are coordinated by theta-gamma phase-amplitude coupling (TG-PAC). We recorded single neurons in the human medial temporal and frontal lobe while patients maintained multiple items in their working memory. In the hippocampus, TG-PAC was indicative of working memory load and quality. We identified cells that selectively spiked during nonlinear interactions of theta phase and gamma amplitude. The spike timing of these PAC neurons was coordinated with frontal theta activity when cognitive control demand was high. By introducing noise correlations with persistently active neurons in the hippocampus, PAC neurons shaped the geometry of the population code. This led to higher-fidelity representations of working memory content that were associated with improved behaviour. Our results support a multicomponent architecture of working memory1,2, with frontal control managing maintenance of working memory content in storage-related areas3-5. Within this framework, hippocampal TG-PAC integrates cognitive control and working memory storage across brain areas, thereby suggesting a potential mechanism for top-down control over sensory-driven processes.

Multimodal single-neuron, intracranial EEG, and fMRI brain responses during movie watching in human patients.

We present a multimodal dataset of intracranial recordings, fMRI, and eye tracking in 20 participants during movie watching. Recordings consist of single neurons, local field potential, and intracranial EEG activity acquired from depth electrodes targeting the amygdala, hippocampus, and medial frontal cortex implanted for monitoring of epileptic seizures. Participants watched an 8-min long excerpt from the video "Bang! You're Dead" and performed a recognition memory test for movie content. 3 T fMRI activity was recorded prior to surgery in 11 of these participants while performing the same task. This NWB- and BIDS-formatted dataset includes spike times, field potential activity, behavior, eye tracking, electrode locations, demographics, and functional and structural MRI scans. For technical validation, we provide signal quality metrics, assess eye tracking quality, behavior, the tuning of cells and high-frequency broadband power field potentials to familiarity and event boundaries, and show brain-wide inter-subject correlations for fMRI. This dataset will facilitate the investigation of brain activity during movie watching, recognition memory, and the neural basis of the fMRI-BOLD signal.

Encoding of Predictive Associations in Human Prefrontal and Medial Temporal Neurons During Pavlovian Appetitive Conditioning.

Pavlovian conditioning is thought to involve the formation of learned associations between stimuli and values, and between stimuli and specific features of outcomes. Here, we leveraged human single neuron recordings in ventromedial prefrontal, dorsomedial frontal, hippocampus, and amygdala while patients of both sexes performed an appetitive Pavlovian conditioning task probing both stimulus-value and stimulus-stimulus associations. Ventromedial prefrontal cortex encoded predictive value along with the amygdala, and also encoded predictions about the identity of stimuli that would subsequently be presented, suggesting a role for neurons in this region in encoding predictive information beyond value. Unsigned error signals were found in dorsomedial frontal areas and hippocampus, potentially supporting learning of non-value related outcome features. Our findings implicate distinct human prefrontal and medial temporal neuronal populations in mediating predictive associations which could partially support model-based mechanisms during Pavlovian conditioning.

Dataset of human-single neuron activity during a Sternberg working memory task.

We present a dataset of 1809 single neurons recorded from the human medial temporal lobe (amygdala and hippocampus) and medial frontal lobe (anterior cingulate cortex, pre-supplementary motor area, ventral medial prefrontal cortex) across 41 sessions from 21 patients that underwent seizure monitoring with depth electrodes. Subjects performed a screening task (907 neurons) to identify images for which highly selective cells were present. Subjects then performed a working memory task (902 neurons), in which they were sequentially presented with 1-3 images for which highly selective cells were present and, following a maintenance period, were asked if the probe was identical to one of the maintained images. This Neurodata Without Borders formatted dataset includes spike times, extracellular spike waveforms, stimuli presented, behavior, electrode locations, and subject demographics. As validation, we replicate previous findings on the selectivity of concept cells and their persistent activity during working memory maintenance. This large dataset of rare human single-neuron recordings and behavior enables the investigation of the neural mechanisms of working memory in humans.

Single-neuron spiking variability in hippocampus dynamically tracks sensory content during memory formation in humans.

During memory formation, the hippocampus is presumed to represent the content of stimuli, but how it does so is unknown. Using computational modelling and human single-neuron recordings, we show that the more precisely hippocampal spiking variability tracks the composite features of each individual stimulus, the better those stimuli are later remembered. We propose that moment-to-moment spiking variability may provide a new window into how the hippocampus constructs memories from the building blocks of our sensory world.

Neural mechanisms of face familiarity and learning in the human amygdala and hippocampus.

Recognizing familiar faces and learning new faces play an important role in social cognition. However, the underlying neural computational mechanisms remain unclear. Here, we record from single neurons in the human amygdala and hippocampus and find a greater neuronal representational distance between pairs of familiar faces than unfamiliar faces, suggesting that neural representations for familiar faces are more distinct. Representational distance increases with exposures to the same identity, suggesting that neural face representations are sharpened with learning and familiarization. Furthermore, representational distance is positively correlated with visual dissimilarity between faces, and exposure to visually similar faces increases representational distance, thus sharpening neural representations. Finally, we construct a computational model that demonstrates an increase in the representational distance of artificial units with training. Together, our results suggest that the neuronal population geometry, quantified by the representational distance, encodes face familiarity, similarity, and learning, forming the basis of face recognition and memory.

Abstract representations emerge in human hippocampal neurons during inference behavior.

Humans have the remarkable cognitive capacity to rapidly adapt to changing environments. Central to this capacity is the ability to form high-level, abstract representations that take advantage of regularities in the world to support generalization 1 . However, little is known about how these representations are encoded in populations of neurons, how they emerge through learning, and how they relate to behavior 2,3 . Here we characterized the representational geometry of populations of neurons (single-units) recorded in the hippocampus, amygdala, medial frontal cortex, and ventral temporal cortex of neurosurgical patients who are performing an inferential reasoning task. We find that only the neural representations formed in the hippocampus simultaneously encode multiple task variables in an abstract, or disentangled, format. This representational geometry is uniquely observed after patients learn to perform inference, and consisted of disentangled directly observable and discovered latent task variables. Interestingly, learning to perform inference by trial and error or through verbal instructions led to the formation of hippocampal representations with similar geometric properties. The observed relation between representational format and inference behavior suggests that abstract/disentangled representational geometries are important for complex cognition.

Benefits of sharing neurophysiology data from the BRAIN Initiative Research Opportunities in Humans Consortium.

Sharing human brain data can yield scientific benefits, but because of various disincentives, only a fraction of these data is currently shared. We profile three successful data-sharing experiences from the NIH BRAIN Initiative Research Opportunities in Humans (ROH) Consortium and demonstrate benefits to data producers and to users.

A uniform human multimodal dataset for emotion perception and judgment.

Face perception is a fundamental aspect of human social interaction, yet most research on this topic has focused on single modalities and specific aspects of face perception. Here, we present a comprehensive multimodal dataset for examining facial emotion perception and judgment. This dataset includes EEG data from 97 unique neurotypical participants across 8 experiments, fMRI data from 19 neurotypical participants, single-neuron data from 16 neurosurgical patients (22 sessions), eye tracking data from 24 neurotypical participants, behavioral and eye tracking data from 18 participants with ASD and 15 matched controls, and behavioral data from 3 rare patients with focal bilateral amygdala lesions. Notably, participants from all modalities performed the same task. Overall, this multimodal dataset provides a comprehensive exploration of facial emotion perception, emphasizing the importance of integrating multiple modalities to gain a holistic understanding of this complex cognitive process. This dataset serves as a key missing link between human neuroimaging and neurophysiology literature, and facilitates the study of neuropsychiatric populations.

Slow ramping emerges from spontaneous fluctuations in spiking neural networks.

The capacity to initiate actions endogenously is critical for goal-directed behavior. Spontaneous voluntary actions are typically preceded by slow-ramping medial frontal cortex activity that begins around two seconds before movement, which may reflect spontaneous fluctuations that influence action timing. However, the mechanisms by which these slow ramping signals emerge from single-neuron and network dynamics remain poorly understood. Here, we developed a spiking neural network model that produces spontaneous slow ramping activity in single neurons and population activity with onsets ∼2 seconds before threshold crossings. A key prediction of our model is that neurons that ramp together have correlated firing patterns before ramping onset. We confirmed this model-derived hypothesis in a dataset of human single neuron recordings from medial frontal cortex. Our results suggest that slow ramping signals reflect bounded spontaneous fluctuations that emerge from quasi-winner-take-all dynamics in clustered networks that are temporally stabilized by slow-acting synapses. Highlights: We reveal a mechanism for slow-ramping signals before spontaneous voluntary movements.Slow synapses stabilize spontaneous fluctuations in spiking neural network.We validate model predictions in human frontal cortical single neuron recordingsThe model recreates the readiness potential in an EEG proxy signal.Neurons that ramp together had correlated activity before ramping onset.

Control of working memory maintenance by theta-gamma phase amplitude coupling of human hippocampal neurons.

Retaining information in working memory (WM) is a demanding process that relies on cognitive control to protect memoranda-specific persistent activity from interference. How cognitive control regulates WM storage, however, remains unknown. We hypothesized that interactions of frontal control and hippocampal persistent activity are coordinated by theta-gamma phase amplitude coupling (TG-PAC). We recorded single neurons in the human medial temporal and frontal lobe while patients maintained multiple items in WM. In the hippocampus, TG-PAC was indicative of WM load and quality. We identified cells that selectively spiked during nonlinear interactions of theta phase and gamma amplitude. These PAC neurons were more strongly coordinated with frontal theta activity when cognitive control demand was high, and they introduced information-enhancing and behaviorally relevant noise correlations with persistently active neurons in the hippocampus. We show that TG-PAC integrates cognitive control and WM storage to improve the fidelity of WM representations and facilitate behavior.

Neurons in human pre-supplementary motor area encode key computations for value-based choice.

Adaptive behaviour in real-world environments requires that choices integrate several variables, including the novelty of the options under consideration, their expected value and uncertainty in value estimation. Here, to probe how integration over decision variables occurs during decision-making, we recorded neurons from the human pre-supplementary motor area (preSMA), ventromedial prefrontal cortex and dorsal anterior cingulate. Unlike the other areas, preSMA neurons not only represented separate pre-decision variables for each choice option but also encoded an integrated utility signal for each choice option and, subsequently, the decision itself. Post-decision encoding of variables for the chosen option was more widely distributed and especially prominent in the ventromedial prefrontal cortex. Our findings position the human preSMA as central to the implementation of value-based decisions.

Neurophysiological mechanisms of error monitoring in human and non-human primates.

Performance monitoring is an important executive function that allows us to gain insight into our own behaviour. This remarkable ability relies on the frontal cortex, and its impairment is an aspect of many psychiatric diseases. In recent years, recordings from the macaque and human medial frontal cortex have offered a detailed understanding of the neurophysiological substrate that underlies performance monitoring. Here we review the discovery of single-neuron correlates of error monitoring, a key aspect of performance monitoring, in both species. These neurons are the generators of the error-related negativity, which is a non-invasive biomarker that indexes error detection. We evaluate a set of tasks that allows the synergistic elucidation of the mechanisms of cognitive control across the two species, consider differences in brain anatomy and testing conditions across species, and describe the clinical relevance of these findings for understanding psychopathology. Last, we integrate the body of experimental facts into a theoretical framework that offers a new perspective on how error signals are computed in both species and makes novel, testable predictions.

LITTLE MEMORY EDITORS LIVING INSIDE YOUR BRAIN.

We interact with the world continuously. However, memories of our experiences are stored as individual events. For example, when we go on a road trip, we do not remember what happens second by second. Instead, we remember only a few special moments or events from a trip, such as dancing around the campfire. Our brains constantly extract memorable events while we interact with the world, and we organize those events based on their relevance. This process is like grouping road trip photos under different folders on the computer, so we can efficiently and accurately retrieve those memories in the future. How does the brain create these memorable events? In this article, you will learn about two groups of neurons inside the brain that help achieve this remarkable feat. You will also learn about how the activation of these neurons shapes the formation and retrieval of memories.

Multi-modal characterization and simulation of human epileptic circuitry.

Temporal lobe epilepsy is the fourth most common neurological disorder, with about 40% of patients not responding to pharmacological treatment. Increased cellular loss is linked to disease severity and pathological phenotypes such as heightened seizure propensity. While the hippocampus is the target of therapeutic interventions, the impact of the disease at the cellular level remains unclear. Here, we show that hippocampal granule cells change with disease progression as measured in living, resected hippocampal tissue excised from patients with epilepsy. We show that granule cells increase excitability and shorten response latency while also enlarging in cellular volume and spine density. Single-nucleus RNA sequencing combined with simulations ascribes the changes to three conductances: BK, Cav2.2, and Kir2.1. In a network model, we show that these changes related to disease progression bring the circuit into a more excitable state, while reversing them produces a less excitable, "early-disease-like" state.

Probing the human brain at single-neuron resolution with high-density cortical recordings.

Recording in vivo from large numbers of neurons is a core neuroscience technique not typically possible in humans. In this issue of Neuron, Chung et al. (2022) show high-density acute recordings in human cortex using the Neuropixels probe.

The geometry of domain-general performance monitoring in the human medial frontal cortex.

Controlling behavior to flexibly achieve desired goals depends on the ability to monitor one's own performance. It is unknown how performance monitoring can be both flexible, to support different tasks, and specialized, to perform each task well. We recorded single neurons in the human medial frontal cortex while subjects performed two tasks that involve three types of cognitive conflict. Neurons encoding conflict probability, conflict, and error in one or both tasks were intermixed, forming a representational geometry that simultaneously allowed task specialization and generalization. Neurons encoding conflict retrospectively served to update internal estimates of conflict probability. Population representations of conflict were compositional. These findings reveal how representations of evaluative signals can be both abstract and task-specific and suggest a neuronal mechanism for estimating control demand.

Saccade-related neural communication in the human medial temporal lobe is modulated by the social relevance of stimuli.

Humans predominantly explore their environment by moving their eyes. To optimally communicate and process visual information, neural activity needs to be coordinated with the execution of eye movements. We investigated the coordination between visual exploration and interareal neural communication by analyzing local field potentials and single neuron activity in patients with epilepsy. We demonstrated that during the free viewing of images, neural communication between the human amygdala and hippocampus is coordinated with the execution of eye movements. The strength and direction of neural communication and hippocampal saccade-related phase alignment were strongest for fixations that landed on human faces. Our results argue that the state of the human medial temporal lobe network is selectively coordinated with motor behavior. Interareal neural communication was facilitated for social stimuli as indexed by the category of the attended information.

Neurons detect cognitive boundaries to structure episodic memories in humans.

While experience is continuous, memories are organized as discrete events. Cognitive boundaries are thought to segment experience and structure memory, but how this process is implemented remains unclear. We recorded the activity of single neurons in the human medial temporal lobe (MTL) during the formation and retrieval of memories with complex narratives. Here, we show that neurons responded to abstract cognitive boundaries between different episodes. Boundary-induced neural state changes during encoding predicted subsequent recognition accuracy but impaired event order memory, mirroring a fundamental behavioral tradeoff between content and time memory. Furthermore, the neural state following boundaries was reinstated during both successful retrieval and false memories. These findings reveal a neuronal substrate for detecting cognitive boundaries that transform experience into mnemonic episodes and structure mental time travel during retrieval.