High-density single-unit human cortical recordings using the Neuropixels probe

The action potential is a fundamental unit of neural computation. Even though significant advances have been made in recording large numbers of individual neurons in animal models, translation of these methodologies to humans has been limited because of clinical constraints and electrode reliability. Here, we present a reliable method for intraoperative recording of dozens of neurons in humans using the Neuropixels probe, yielding up to ∼100 simultaneously recorded single units. Most single units were active within 1 min of reaching target depth. The motion of the electrode array had a strong inverse correlation with yield, identifying a major challenge and opportunity to further increase the probe utility. Cell pairs active close in time were spatially closer in most recordings, demonstrating the power to resolve complex cortical dynamics. Altogether, this approach provides access to population single-unit activity across the depth of human neocortex at scales previously only accessible in animal models.

Improved Speech Hearing in Noise with Invasive Electrical Brain Stimulation

Speech perception in noise is a challenging everyday task with which many listeners have difficulty. Here, we report a case in which electrical brain stimulation of implanted intracranial electrodes in the left planum temporale (PT) of a neurosurgical patient significantly and reliably improved subjective quality (up to 50%) and objective intelligibility (up to 97%) of speech in noise perception. Stimulation resulted in a selective enhancement of speech sounds compared with the background noises. The receptive fields of the PT sites whose stimulation improved speech perception were tuned to spectrally broad and rapidly changing sounds. Corticocortical evoked potential analysis revealed that the PT sites were located between the sites in Heschl's gyrus and the superior temporal gyrus. Moreover, the discriminability of speech from nonspeech sounds increased in population neural responses from Heschl's gyrus to the PT to the superior temporal gyrus sites. These findings causally implicate the PT in background noise suppression and may point to a novel potential neuroprosthetic solution to assist in the challenging task of speech perception in noise.SIGNIFICANCE STATEMENT Speech perception in noise remains a challenging task for many individuals. Here, we present a case in which the electrical brain stimulation of intracranially implanted electrodes in the planum temporale of a neurosurgical patient significantly improved both the subjective quality (up to 50%) and objective intelligibility (up to 97%) of speech perception in noise. Stimulation resulted in a selective enhancement of speech sounds compared with the background noises. Our local and network-level functional analyses placed the planum temporale sites in between the sites in the primary auditory areas in Heschl's gyrus and nonprimary auditory areas in the superior temporal gyrus. These findings causally implicate planum temporale in acoustic scene analysis and suggest potential neuroprosthetic applications to assist hearing in noise.

Longevity and reliability of chronic unit recordings using the Utah, intracortical multi-electrode arrays

Objective.Microelectrode arrays are standard tools for conducting chronic electrophysiological experiments, allowing researchers to simultaneously record from large numbers of neurons. Specifically, Utah electrode arrays (UEAs) have been utilized by scientists in many species, including rodents, rhesus macaques, marmosets, and human participants. The field of clinical human brain-computer interfaces currently relies on the UEA as a number of research groups have clearance from the United States Federal Drug Administration (FDA) for this device through the investigational device exemption pathway. Despite its widespread usage in systems neuroscience, few studies have comprehensively evaluated the reliability and signal quality of the Utah array over long periods of time in a large dataset.Approach.We collected and analyzed over 6000 recorded datasets from various cortical areas spanning almost nine years of experiments, totaling 17 rhesus macaques (Macaca mulatta) and 2 human subjects, and 55 separate microelectrode Utah arrays. The scale of this dataset allowed us to evaluate the average life of these arrays, based primarily on the signal-to-noise ratio of each electrode over time.Main results.Using implants in primary motor, premotor, prefrontal, and somatosensory cortices, we found that the average lifespan of available recordings from UEAs was 622 days, although we provide several examples of these UEAs lasting over 1000 days and one up to 9 years; human implants were also shown to last longer than non-human primate implants. We also found that electrode length did not affect longevity and quality, but iridium oxide metallization on the electrode tip exhibited superior yield as compared to platinum metallization.Significance.Understanding longevity and reliability of microelectrode array recordings allows researchers to set expectations and plan experiments accordingly and maximize the amount of high-quality data gathered. Our results suggest that one can expect chronic unit recordings to last at least two years, with the possibility for arrays to last the better part of a decade.

Human Hippocampal Neurons Track Moments in a Sequence of Events

An indispensable feature of episodic memory is our ability to temporally piece together different elements of an experience into a coherent memory. Hippocampal time cells-neurons that represent temporal information-may play a critical role in this process. Although these cells have been repeatedly found in rodents, it is still unclear to what extent similar temporal selectivity exists in the human hippocampus. Here, we show that temporal context modulates the firing activity of human hippocampal neurons during structured temporal experiences. We recorded neuronal activity in the human brain while patients of either sex learned predictable sequences of pictures. We report that human time cells fire at successive moments in this task. Furthermore, time cells also signaled inherently changing temporal contexts during empty 10 s gap periods between trials while participants waited for the task to resume. Finally, population activity allowed for decoding temporal epoch identity, both during sequence learning and during the gap periods. These findings suggest that human hippocampal neurons could play an essential role in temporally organizing distinct moments of an experience in episodic memory.SIGNIFICANCE STATEMENT Episodic memory refers to our ability to remember the what, where, and when of a past experience. Representing time is an important component of this form of memory. Here, we show that neurons in the human hippocampus represent temporal information. This temporal signature was observed both when participants were actively engaged in a memory task, as well as during 10-s-long gaps when they were asked to wait before performing the task. Furthermore, the activity of the population of hippocampal cells allowed for decoding one temporal epoch from another. These results suggest a robust representation of time in the human hippocampus.

Time cells in the human hippocampus and entorhinal cortex support episodic memory

The organization of temporal information is critical for the encoding and retrieval of episodic memories. In the rodent hippocampus and entorhinal cortex, evidence accumulated over the last decade suggests that populations of "time cells" in the hippocampus encode temporal information. We identify time cells in humans using intracranial microelectrode recordings obtained from 27 human epilepsy patients who performed an episodic memory task. We show that time cell activity predicts the temporal organization of retrieved memory items. We also uncover evidence of ramping cell activity in humans, which represents a complementary type of temporal information. These findings establish a cellular mechanism for the representation of temporal information in the human brain needed to form episodic memories.

No Evidence that Predictions and Attention Modulate the First Feedforward Sweep of Cortical Information Processing

Predictive coding models propose that predictions (stimulus likelihood) reduce sensory signals as early as primary visual cortex (V1), and that attention (stimulus relevance) can modulate these effects. Indeed, both prediction and attention have been shown to modulate V1 activity, albeit with fMRI, which has low temporal resolution. This leaves it unclear whether these effects reflect a modulation of the first feedforward sweep of visual information processing and/or later, feedback-related activity. In two experiments, we used electroencephalography and orthogonally manipulated spatial predictions and attention to address this issue. Although clear top-down biases were found, as reflected in pre-stimulus alpha-band activity, we found no evidence for top-down effects on the earliest visual cortical processing stage (<80 ms post-stimulus), as indexed by the amplitude of the C1 event-related potential component and multivariate pattern analyses. These findings indicate that initial visual afferent activity may be impenetrable to top-down influences by spatial prediction and attention.

Value-Related Neuronal Responses in the Human Amygdala during Observational Learning

The amygdala plays an important role in many aspects of social cognition and reward learning. Here, we aimed to determine whether human amygdala neurons are involved in the computations necessary to implement learning through observation. We performed single-neuron recordings from the amygdalae of human neurosurgical patients (male and female) while they learned about the value of stimuli through observing the outcomes experienced by another agent interacting with those stimuli. We used a detailed computational modeling approach to describe patients' behavior in the task. We found a significant proportion of amygdala neurons whose activity correlated with both expected rewards for oneself and others, and in tracking outcome values received by oneself or other agents. Additionally, a population decoding analysis suggests the presence of information for both observed and experiential outcomes in the amygdala. Encoding and decoding analyses suggested observational value coding in amygdala neurons occurred in a different subset of neurons than experiential value coding. Collectively, these findings support a key role for the human amygdala in the computations underlying the capacity for learning through observation.SIGNIFICANCE STATEMENT Single-neuron studies of the human brain provide a unique window into the computational mechanisms of cognition. In this study, epilepsy patients implanted intracranially with hybrid depth electrodes performed an observational learning (OL) task. We measured single-neuron activity in the amygdala and found a representation for observational rewards as well as observational expected reward values. Additionally, distinct subsets of amygdala neurons represented self-experienced and observational values. This study provides a rare glimpse into the role of human amygdala neurons in social cognition.

α Power Modulation and Event-Related Slow Wave Provide Dissociable Correlates of Visual Working Memory

Traditionally, electrophysiological correlates of visual working memory (VWM) capacity have been characterized using a lateralized VWM task in which participants had to remember items presented on the cued hemifield while ignoring the distractors presented on the other hemifield. Though this approach revealed a lateralized parieto-occipital negative slow wave (i.e., the contralateral delay activity) and lateralized α power modulation as neural correlates of VWM capacity that may be mechanistically related, recent evidence suggested that these measures might be reflecting individuals' ability to ignore distractors rather than their ability to maintain VWM representations. To better characterize the neural correlates of VWM capacity, we had human participants perform a whole-field VWM task in which they remembered all the items on the display. Here, we found that both the parieto-occipital negative slow wave and the α power suppression showed the characteristics of VWM capacity in the absence of distractors, suggesting that they reflect the maintenance of VWM representations rather than filtering of distractors. Furthermore, the two signals explained unique portions of variance in individual differences of VWM capacity and showed differential temporal characteristics. This pattern of results clearly suggests that individual differences in VWM capacity are determined by dissociable neural mechanisms reflected in the ERP and the oscillatory measures of VWM capacity.

SIGNIFICANCE STATEMENT

Our work demonstrates that there exist event-related potential and oscillatory correlates of visual working memory (VWM) capacity even in the absence of task-irrelevant distractors. This clearly shows that the two neural correlates are directly linked to maintenance of task-relevant information rather than filtering of task-irrelevant information. Furthermore, we found that these two correlates show differential temporal characteristics. These results are inconsistent with proposals that the two neural correlates are byproducts of asymmetric α power suppression and indicate that they reflect dissociable neural mechanisms subserving VWM.

Predicting and Improving Recognition Memory Using Multiple Electrophysiological Signals in Real Time

Although people are capable of storing a virtually infinite amount of information in memory, their ability to encode new information is far from perfect. The quality of encoding varies from moment to moment and renders some memories more accessible than others. Here, we were able to forecast the likelihood that a given item will be later recognized by monitoring two dissociable fluctuations of the electroencephalogram during encoding. Next, we identified individual items that were poorly encoded, using our electrophysiological measures in real time, and we successfully improved the efficacy of learning by having participants restudy these items. Thus, our memory forecasts using multiple electrophysiological signals demonstrate the feasibility and the effectiveness of using real-time monitoring of the moment-to-moment fluctuations of the quality of memory encoding to improve learning.

Acuity-independent effects of visual deprivation on human visual cortex

Visual development depends on sensory input during an early developmental critical period. Deviation of the pointing direction of the two eyes (strabismus) or chronic optical blur (anisometropia) separately and together can disrupt the formation of normal binocular interactions and the development of spatial processing, leading to a loss of stereopsis and visual acuity known as amblyopia. To shed new light on how these two different forms of visual deprivation affect the development of visual cortex, we used event-related potentials (ERPs) to study the temporal evolution of visual responses in patients who had experienced either strabismus or anisometropia early in life. To make a specific statement about the locus of deprivation effects, we took advantage of a stimulation paradigm in which we could measure deprivation effects that arise either before or after a configuration-specific response to illusory contours (ICs). Extraction of ICs is known to first occur in extrastriate visual areas. Our ERP measurements indicate that deprivation via strabismus affects both the early part of the evoked response that occurs before ICs are formed as well as the later IC-selective response. Importantly, these effects are found in the normal-acuity nonamblyopic eyes of strabismic amblyopes and in both eyes of strabismic patients without amblyopia. The nonamblyopic eyes of anisometropic amblyopes, by contrast, are normal. Our results indicate that beyond the well-known effects of strabismus on the development of normal binocularity, it also affects the early stages of monocular feature processing in an acuity-independent fashion.

Stimulus Dependence of Gamma Oscillations in Human Visual Cortex

A striking feature of some field potential recordings in visual cortex is a rhythmic oscillation within the gamma band (30-80 Hz). These oscillations have been proposed to underlie computations in perception, attention, and information transmission. Recent studies of cortical field potentials, including human electrocorticography (ECoG), have emphasized another signal within the gamma band, a nonoscillatory, broadband signal, spanning 80-200 Hz. It remains unclear under what conditions gamma oscillations are elicited in visual cortex, whether they are necessary and ubiquitous in visual encoding, and what relationship they have to nonoscillatory, broadband field potentials. We demonstrate that ECoG responses in human visual cortex (V1/V2/V3) can include robust narrowband gamma oscillations, and that these oscillations are reliably elicited by some spatial contrast patterns (luminance gratings) but not by others (noise patterns and many natural images). The gamma oscillations can be conspicuous and robust, but because they are absent for many stimuli, which observers can see and recognize, the oscillations are not necessary for seeing. In contrast, all visual stimuli induced broadband spectral changes in ECoG responses. Asynchronous neural signals in visual cortex, reflected in the broadband ECoG response, can support transmission of information for perception and recognition in the absence of pronounced gamma oscillations.

Rhythmic fluctuations in evidence accumulation during decision making in the human brain

Categorical choices are preceded by the accumulation of sensory evidence in favor of one action or another. Current models describe evidence accumulation as a continuous process occurring at a constant rate, but this view is inconsistent with accounts of a psychological refractory period during sequential information processing. During multisample perceptual categorization, we found that the neural encoding of momentary evidence in human electrical brain signals and its subsequent impact on choice fluctuated rhythmically according to the phase of ongoing parietal delta oscillations (1-3 Hz). By contrast, lateralized beta-band power (10-30 Hz) overlying human motor cortex encoded the integrated evidence as a response preparation signal. These findings draw a clear distinction between central and motor stages of perceptual decision making, with successive samples of sensory evidence competing to pass through a serial processing bottleneck before being mapped onto action.