An electroencephalogram microdisplay to visualize neuronal activity on the brain surface

Functional mapping during brain surgery is applied to define brain areas that control critical functions and cannot be removed. Currently, these procedures rely on verbal interactions between the neurosurgeon and electrophysiologist, which can be time-consuming. In addition, the electrode grids that are used to measure brain activity and to identify the boundaries of pathological versus functional brain regions have low resolution and limited conformity to the brain surface. Here, we present the development of an intracranial electroencephalogram (iEEG)-microdisplay that consists of freestanding arrays of 2048 GaN light-emitting diodes laminated on the back of micro-electrocorticography electrode grids. With a series of proof-of-concept experiments in rats and pigs, we demonstrate that these iEEG-microdisplays allowed us to perform real-time iEEG recordings and display cortical activities by spatially corresponding light patterns on the surface of the brain in the surgical field. Furthermore, iEEG-microdisplays allowed us to identify and display cortical landmarks and pathological activities from rat and pig models. Using a dual-color iEEG-microdisplay, we demonstrated coregistration of the functional cortical boundaries with one color and displayed the evolution of electrical potentials associated with epileptiform activity with another color. The iEEG-microdisplay holds promise to facilitate monitoring of pathological brain activity in clinical settings.

Emergent effects of synaptic connectivity on the dynamics of global and local slow waves in a large-scale thalamocortical network model of the human brain

Slow-wave sleep (SWS), characterized by slow oscillations (SO, <1Hz) of alternating active and silent states in the thalamocortical network, is a primary brain state during Non-Rapid Eye Movement (NREM) sleep. In the last two decades, the traditional view of SWS as a global and uniform whole-brain state has been challenged by a growing body of evidence indicating that sleep oscillations can be local and can coexist with wake-like activity. However, the understanding of how global and local SO emerges from micro-scale neuron dynamics and network connectivity remains unclear. We developed a multi-scale, biophysically realistic human whole-brain thalamocortical network model capable of transitioning between the awake state and slow-wave sleep, and we investigated the role of connectivity in the spatio-temporal dynamics of sleep SO. We found that the overall strength and a relative balance between long and short-range synaptic connections determined the network state. Models with relatively weaker long-range connectivity resulted in mixed states of global and local slow waves. Increase of synaptic strength led to more synchronized global SO. These results were compared to human data to validate probable models of biophysically realistic slow waves. The model producing mixed states provided the best match to the spatial coherence profiles obtained in the human subjects. These findings shed light on how the spatio-temporal properties of SO emerge from local and global cortical connectivity and provide a framework for further exploring the mechanisms and functions of SWS in health and disease.

Intraoperative application and early experience with novel high-resolution, high-channel-count thin-film electrodes for human microelectrocorticography

OBJECTIVE

The study objective was to evaluate intraoperative experience with newly developed high-spatial-resolution microelectrode grids composed of poly(3,4-ethylenedioxythiophene) with polystyrene sulfonate (PEDOT:PSS), and those composed of platinum nanorods (PtNRs).

METHODS

A cohort of patients who underwent craniotomy for pathological tissue resection and who had high-spatial-resolution microelectrode grids placed intraoperatively were evaluated. Patient demographic and baseline clinical variables as well as relevant microelectrode grid characteristic data were collected. The primary and secondary outcome measures of interest were successful microelectrode grid utilization with usable resting-state or task-related data, and grid-related adverse intraoperative events and/or grid dysfunction.

RESULTS

Included in the analysis were 89 cases of patients who underwent a craniotomy for resection of neoplasms (n = 58) or epileptogenic tissue (n = 31). These cases accounted for 94 grids: 58 PEDOT:PSS and 36 PtNR grids. Of these 94 grids, 86 were functional and used successfully to obtain cortical recordings from 82 patients. The mean cortical grid recording duration was 15.3 ± 1.15 minutes. Most recordings in patients were obtained during experimental tasks (n = 52, 58.4%), involving language and sensorimotor testing paradigms, or were obtained passively during resting state (n = 32, 36.0%). There were no intraoperative adverse events related to grid placement. However, there were instances of PtNR grid dysfunction (n = 8) related to damage incurred by suboptimal preoperative sterilization (n = 7) and improper handling (n = 1); intraoperative recordings were not performed. Vaporized peroxide sterilization was the most optimal sterilization method for PtNR grids, providing a significantly greater number of usable channels poststerilization than did steam-based sterilization techniques (median 905.0 [IQR 650.8-935.5] vs 356.0 [IQR 18.0-597.8], p = 0.0031).

CONCLUSIONS

High-spatial-resolution microelectrode grids can be readily incorporated into appropriately selected craniotomy cases for clinical and research purposes. Grids are reliable when preoperative handling and sterilization considerations are accounted for. Future investigations should compare the diagnostic utility of these high-resolution grids to commercially available counterparts and assess whether diagnostic discrepancies relate to clinical outcomes.

Neural manifolds carry reactivation of phonetic representations during semantic processing

Traditional models of speech perception posit that neural activity encodes speech through a hierarchy of cognitive processes, from low-level representations of acoustic and phonetic features to high-level semantic encoding. Yet it remains unknown how neural representations are transformed across levels of the speech hierarchy. Here, we analyzed unique microelectrode array recordings of neuronal spiking activity from the human left anterior superior temporal gyrus, a brain region at the interface between phonetic and semantic speech processing, during a semantic categorization task and natural speech perception. We identified distinct neural manifolds for semantic and phonetic features, with a functional separation of the corresponding low-dimensional trajectories. Moreover, phonetic and semantic representations were encoded concurrently and reflected in power increases in the beta and low-gamma local field potentials, suggesting top-down predictive and bottom-up cumulative processes. Our results are the first to demonstrate mechanisms for hierarchical speech transformations that are specific to neuronal population dynamics.

Modular Phoneme Processing in Human Superior Temporal Gyrus

Modular organization is fundamental to cortical processing, but its presence is human association cortex is unknown. We characterized phoneme processing with 128-1024 channel micro-arrays at 50-200µm pitch on superior temporal gyrus of 7 patients. High gamma responses were highly correlated within ~1.7mm diameter modules, sharply delineated from adjacent modules with distinct time-courses and phoneme-selectivity. We suggest that receptive language cortex may be organized in discrete processing modules.

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.

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.

Binding of cortical functional modules by synchronous high frequency oscillations

High-frequency phase-locked oscillations have been hypothesized to facilitate integration ('binding') of information encoded across widespread cortical areas. Ripples (~100ms long ~90Hz oscillations) co-occur ('co-ripple') broadly in multiple states and locations, but have only been associated with memory replay. We tested whether cortico-cortical co-ripples subserve a general role in binding by recording intracranial EEG during reading. Co-rippling increased to words versus consonant-strings between visual, wordform and semantic cortical areas when letters are binding into words, and words to meaning. Similarly, co-ripples strongly increased before correct responses between executive, response, wordform and semantic areas when word meanings bind instructions and response. Task-selective co-rippling dissociated from non-oscillatory activation and memory reinstatement. Co-ripples were phase-locked at zero-lag, even at long distances (>12cm), supporting a general role in cognitive binding.

The Brain Electroencephalogram Microdisplay for Precision Neurosurgery

Brain surgeries are among the most delicate clinical procedures and must be performed with the most technologically robust and advanced tools. When such surgical procedures are performed in functionally critical regions of the brain, functional mapping is applied as a standard practice that involves direct coordinated interactions between the neurosurgeon and the clinical neurology electrophysiology team. However, information flow during these interactions is commonly verbal as well as time consuming which in turn increases the duration and cost of the surgery, possibly compromising the patient outcomes. Additionally, the grids that measure brain activity and identify the boundaries of pathological versus functional brain regions suffer from low resolution (3-10 mm contact to contact spacing) with limited conformity to the brain surface. Here, we introduce a brain intracranial electroencephalogram microdisplay (Brain-iEEG-microdisplay) which conforms to the brain to measure the brain activity and display changes in near real-time (40 Hz refresh rate) on the surface of the brain in the surgical field. We used scalable engineered gallium nitride (GaN) substrates with 6" diameter to fabricate, encapsulate, and release free-standing arrays of up to 2048 GaN light emitting diodes (μLEDs) in polyimide substrates. We then laminated the μLED arrays on the back of micro-electrocorticography (μECoG) platinum nanorod grids (PtNRGrids) and developed hardware and software to perform near real-time intracranial EEG analysis and activation of light patterns that correspond to specific cortical activities. Using the Brain-iEEG-microdisplay, we precisely ideFSntified and displayed important cortical landmarks and pharmacologically induced pathological activities. In the rat model, we identified and displayed individual cortical columns corresponding to individual whiskers and the near real-time evolution of epileptic discharges. In the pig animal model, we demonstrated near real-time mapping and display of cortical functional boundaries using somatosensory evoked potentials (SSEP) and display of responses to direct electrical stimulation (DES) from the surface or within the brain tissue. Using a dual-color Brain-iEEG-microdisplay, we demonstrated co-registration of the functional cortical boundaries with one color and displayed the evolution of electrical potentials associated with epileptiform activity with another color. The Brain-iEEG-microdisplay holds the promise of increasing the efficiency of diagnosis and possibly surgical treatment, thereby reducing the cost and improving patient outcomes which would mark a major advancement in neurosurgery. These advances can also be translated to broader applications in neuro-oncology and neurophysiology.

The role of superficial and deep layers in the generation of high frequency oscillations and interictal epileptiform discharges in the human cortex

Describing intracortical laminar organization of interictal epileptiform discharges (IED) and high frequency oscillations (HFOs), also known as ripples. Defining the frequency limits of slow and fast ripples. We recorded potential gradients with laminar multielectrode arrays (LME) for current source density (CSD) and multi-unit activity (MUA) analysis of interictal epileptiform discharges IEDs and HFOs in the neocortex and mesial temporal lobe of focal epilepsy patients. IEDs were observed in 20/29, while ripples only in 9/29 patients. Ripples were all detected within the seizure onset zone (SOZ). Compared to hippocampal HFOs, neocortical ripples proved to be longer, lower in frequency and amplitude, and presented non-uniform cycles. A subset of ripples (≈ 50%) co-occurred with IEDs, while IEDs were shown to contain variable high-frequency activity, even below HFO detection threshold. The limit between slow and fast ripples was defined at 150 Hz, while IEDs' high frequency components form clusters separated at 185 Hz. CSD analysis of IEDs and ripples revealed an alternating sink-source pair in the supragranular cortical layers, although fast ripple CSD appeared lower and engaged a wider cortical domain than slow ripples MUA analysis suggested a possible role of infragranularly located neural populations in ripple and IED generation. Laminar distribution of peak frequencies derived from HFOs and IEDs, respectively, showed that supragranular layers were dominated by slower (< 150 Hz) components. Our findings suggest that cortical slow ripples are generated primarily in upper layers while fast ripples and associated MUA in deeper layers. The dissociation of macro- and microdomains suggests that microelectrode recordings may be more selective for SOZ-linked ripples. We found a complex interplay between neural activity in the neocortical laminae during ripple and IED formation. We observed a potential leading role of cortical neurons in deeper layers, suggesting a refined utilization of LMEs in SOZ localization.

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

Synchronous bursts of high frequency oscillations ('ripples') are hypothesized to contribute to binding by facilitating integration of neuronal firing across cortical locations. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in 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 NREM sleep and waking, in temporal and Rolandic cortices, and at distances up to 16mm. Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, and were strongly modulated by ripple phase. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple. Together, these results support the hypothesis that trans-cortical co-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.

Restricted language access during childhood affects adult brain structure in selective language regions

Due to the ubiquitous nature of language in the environment of infants, how it affects the anatomical structure of the brain language system over the lifespan is not well understood. In this study, we investigated the effects of early language experience on the adult brain by examining anatomical features of individuals born deaf with typical or restricted language experience in early childhood. Twenty-two deaf adults whose primary language was American Sign Language and were first immersed in it at ages ranging from birth to 14 y participated. The control group was 21 hearing non-signers. We acquired T1-weighted magnetic resonance images and used FreeSurfer [B. Fischl, Neuroimage 62, 774-781(2012)] to reconstruct the brain surface. Using an a priori regions of interest (ROI) approach, we identified 17 language and 19 somatomotor ROIs in each hemisphere from the Human Connectome Project parcellation map [M. F. Glasser et al., Nature 536, 171-178 (2016)]. Restricted language experience in early childhood was associated with negative changes in adjusted grey matter volume and/or cortical thickness in bilateral fronto-temporal regions. No evidence of anatomical differences was observed in any of these regions when deaf signers with infant sign language experience were compared with hearing speakers with infant spoken language experience, showing that the effects of early language experience on the brain language system are supramodal.

Cortical Ripples during NREM Sleep and Waking in Humans

Hippocampal ripples index the reconstruction of spatiotemporal neuronal firing patterns essential for the consolidation of memories in the cortex during non-rapid eye movement sleep (NREM). Recently, cortical ripples in humans have been shown to enfold the replay of neuron firing patterns during cued recall. Here, using intracranial recordings from 18 patients (12 female), we show that cortical ripples also occur during NREM in humans, with similar density, oscillation frequency (∼90 Hz), duration, and amplitude to waking. Ripples occurred in all cortical regions with similar characteristics, unrelated to putative hippocampal connectivity, and were less dense and robust in higher association areas. Putative pyramidal and interneuron spiking phase-locked to cortical ripples during NREM, with phase delays consistent with ripple generation through pyramidal-interneuron feedback. Cortical ripples were smaller in amplitude than hippocampal ripples but were similar in density, frequency, and duration. Cortical ripples during NREM typically occurred just before the upstate peak, often during spindles. Upstates and spindles have previously been associated with memory consolidation, and we found that cortical ripples grouped cofiring between units within the window of spike timing-dependent plasticity. Thus, human NREM cortical ripples are as follows: ubiquitous and stereotyped with a tightly focused oscillation frequency; similar to hippocampal ripples; associated with upstates and spindles; and associated with unit cofiring. These properties are consistent with cortical ripples possibly contributing to memory consolidation and other functions during NREM in humans.SIGNIFICANCE STATEMENT In rodents, hippocampal ripples organize replay during sleep to promote memory consolidation in the cortex, where ripples also occur. However, evidence for cortical ripples in human sleep is limited, and their anatomic distribution and physiological properties are unexplored. Here, using human intracranial recordings, we demonstrate that ripples occur throughout the cortex during waking and sleep with highly stereotyped characteristics. During sleep, cortical ripples tend to occur during spindles on the down-to-upstate transition, and thus participate in a sequence of sleep waves that is important for consolidation. Furthermore, cortical ripples organize single-unit spiking with timing optimal to facilitate plasticity. Therefore, cortical ripples in humans possess essential physiological properties to support memory and other cognitive functions.

Spatiotemporal dynamics of human high gamma discriminate naturalistic behavioral states

In analyzing the neural correlates of naturalistic and unstructured behaviors, features of neural activity that are ignored in a trial-based experimental paradigm can be more fully studied and investigated. Here, we analyze neural activity from two patients using electrocorticography (ECoG) and stereo-electroencephalography (sEEG) recordings, and reveal that multiple neural signal characteristics exist that discriminate between unstructured and naturalistic behavioral states such as “engaging in dialogue” and “using electronics”. Using the high gamma amplitude as an estimate of neuronal firing rate, we demonstrate that behavioral states in a naturalistic setting are discriminable based on long-term mean shifts, variance shifts, and differences in the specific neural activity’s covariance structure. Both the rapid and slow changes in high gamma band activity separate unstructured behavioral states. We also use Gaussian process factor analysis (GPFA) to show the existence of salient spatiotemporal features with variable smoothness in time. Further, we demonstrate that both temporally smooth and stochastic spatiotemporal activity can be used to differentiate unstructured behavioral states. This is the first attempt to elucidate how different neural signal features contain information about behavioral states collected outside the conventional experimental paradigm.

Widespread ripples synchronize human cortical activity during sleep, waking, and memory recall

Declarative memory encoding, consolidation, and retrieval require the integration of elements encoded in widespread cortical locations. The mechanism whereby such "binding" of different components of mental events into unified representations occurs is unknown. The "binding-by-synchrony" theory proposes that distributed encoding areas are bound by synchronous oscillations enabling enhanced communication. However, evidence for such oscillations is sparse. Brief high-frequency oscillations ("ripples") occur in the hippocampus and cortex and help organize memory recall and consolidation. Here, using intracranial recordings in humans, we report that these ∼70-ms-duration, 90-Hz ripples often couple (within ±500 ms), co-occur (≥ 25-ms overlap), and, crucially, phase-lock (have consistent phase lags) between widely distributed focal cortical locations during both sleep and waking, even between hemispheres. Cortical ripple co-occurrence is facilitated through activation across multiple sites, and phase locking increases with more cortical sites corippling. Ripples in all cortical areas co-occur with hippocampal ripples but do not phase-lock with them, further suggesting that cortico-cortical synchrony is mediated by cortico-cortical connections. Ripple phase lags vary across sleep nights, consistent with participation in different networks. During waking, we show that hippocampo-cortical and cortico-cortical coripples increase preceding successful delayed memory recall, when binding between the cue and response is essential. Ripples increase and phase-modulate unit firing, and coripples increase high-frequency correlations between areas, suggesting synchronized unit spiking facilitating information exchange. co-occurrence, phase synchrony, and high-frequency correlation are maintained with little decrement over very long distances (25 cm). Hippocampo-cortico-cortical coripples appear to possess the essential properties necessary to support binding by synchrony during memory retrieval and perhaps generally in cognition.

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.

Human Spindle Variability

In humans, sleep spindles are 10- to 16-Hz oscillations lasting approximately 0.5-2 s. Spindles, along with cortical slow oscillations, may facilitate memory consolidation by enabling synaptic plasticity. Early recordings of spindles at the scalp found anterior channels had overall slower frequency than central-posterior channels. This robust, topographical finding led to dichotomizing spindles as "slow" versus "fast," modeled as two distinct spindle generators in frontal versus posterior cortex. Using a large dataset of intracranial stereoelectroencephalographic (sEEG) recordings from 20 patients (13 female, 7 male) and 365 bipolar recordings, we show that the difference in spindle frequency between frontal and parietal channels is comparable to the variability in spindle frequency within the course of individual spindles, across different spindles recorded by a given site, and across sites within a given region. Thus, fast and slow spindles only capture average differences that obscure a much larger underlying overlap in frequency. Furthermore, differences in mean frequency are only one of several ways that spindles differ. For example, compared with parietal, frontal spindles are smaller, tend to occur after parietal when both are engaged, and show a larger decrease in frequency within-spindles. However, frontal and parietal spindles are similar in being longer, less variable, and more widespread than occipital, temporal, and Rolandic spindles. These characteristics are accentuated in spindles which are highly phase-locked to posterior hippocampal spindles. We propose that rather than a strict parietal-fast/frontal-slow dichotomy, spindles differ continuously and quasi-independently in multiple dimensions, with variability due about equally to within-spindle, within-region, and between-region factors.SIGNIFICANCE STATEMENT Sleep spindles are 10- to 16-Hz neural oscillations generated by cortico-thalamic circuits that promote memory consolidation. Spindles are often dichotomized into slow-anterior and fast-posterior categories for cognitive and clinical studies. Here, we show that the anterior-posterior difference in spindle frequency is comparable to that observed between different cycles of individual spindles, between spindles from a given site, or from different sites within a region. Further, we show that spindles vary on other dimensions such as duration, amplitude, spread, primacy and consistency, and that these multiple dimensions vary continuously and largely independently across cortical regions. These findings suggest that multiple continuous variables rather than a strict frequency dichotomy may be more useful biomarkers for memory consolidation or psychiatric disorders.

An estimation of the absolute number of axons indicates that human cortical areas are sparsely connected

The tracts between cortical areas are conceived as playing a central role in cortical information processing, but their actual numbers have never been determined in humans. Here, we estimate the absolute number of axons linking cortical areas from a whole-cortex diffusion MRI (dMRI) connectome, calibrated using the histologically measured callosal fiber density. Median connectivity is estimated as approximately 6,200 axons between cortical areas within hemisphere and approximately 1,300 axons interhemispherically, with axons connecting functionally related areas surprisingly sparse. For example, we estimate that <5% of the axons in the trunk of the arcuate and superior longitudinal fasciculi connect Wernicke's and Broca's areas. These results suggest that detailed information is transmitted between cortical areas either via linkage of the dense local connections or via rare, extraordinarily privileged long-range connections.

The Precentral Gyrus Contributions to the Early Time-Course of Grapheme-to-Phoneme Conversion

As part of silent reading models, visual orthographic information is transduced into an auditory phonological code in a process of grapheme-to-phoneme conversion (GPC). This process is often identified with lateral temporal-parietal regions associated with auditory phoneme encoding. However, the role of articulatory phonemic representations and the precentral gyrus in GPC is ambiguous. Though the precentral gyrus is implicated in many functional MRI studies of reading, it is not clear if the time course of activity in this region is consistent with the precentral gyrus being involved in GPC. We recorded cortical electrophysiology during a bimodal match/mismatch task from eight patients with perisylvian subdural electrodes to examine the time course of neural activity during a task that necessitated GPC. Patients made a match/mismatch decision between a 3-letter string and the following auditory bi-phoneme. We characterized the distribution and timing of evoked broadband high gamma (70-170 Hz) as well as phase-locking between electrodes. The precentral gyrus emerged with a high concentration of broadband high gamma responses to visual and auditory language as well as mismatch effects. The pars opercularis, supramarginal gyrus, and superior temporal gyrus were also involved. The precentral gyrus showed strong phase-locking with the caudal fusiform gyrus during letter-string presentation and with surrounding perisylvian cortex during the bimodal visual-auditory comparison period. These findings hint at a role for precentral cortex in transducing visual into auditory codes during silent reading.

The Cortical Organization of Syntactic Processing Is Supramodal: Evidence from American Sign Language

Areas within the left-lateralized neural network for language have been found to be sensitive to syntactic complexity in spoken and written language. Previous research has revealed that these areas are active for sign language as well, but whether these areas are specifically responsive to syntactic complexity in sign language independent of lexical processing has yet to be found. To investigate the question, we used fMRI to neuroimage deaf native signers' comprehension of 180 sign strings in American Sign Language (ASL) with a picture-probe recognition task. The ASL strings were all six signs in length but varied at three levels of syntactic complexity: sign lists, two-word sentences, and complex sentences. Syntactic complexity significantly affected comprehension and memory, both behaviorally and neurally, by facilitating accuracy and response time on the picture-probe recognition task and eliciting a left lateralized activation response pattern in anterior and posterior superior temporal sulcus (aSTS and pSTS). Minimal or absent syntactic structure reduced picture-probe recognition and elicited activation in bilateral pSTS and occipital-temporal cortex. These results provide evidence from a sign language, ASL, that the combinatorial processing of anterior STS and pSTS is supramodal in nature. The results further suggest that the neurolinguistic processing of ASL is characterized by overlapping and separable neural systems for syntactic and lexical processing.

High γ Activity in Cortex and Hippocampus Is Correlated with Autonomic Tone during Sleep

Studies in animals have demonstrated a strong relationship between cortical and hippocampal activity, and autonomic tone. However, the extent, distribution, and nature of this relationship have not been investigated with intracranial recordings in humans during sleep. Cortical and hippocampal population neuronal firing was estimated from high γ band activity (HG) from 70 to 110 Hz in local field potentials (LFPs) recorded from 15 subjects (nine females) during nonrapid eye movement (NREM) sleep. Autonomic tone was estimated from heart rate variability (HRV). HG and HRV were significantly correlated in the hippocampus and multiple cortical sites in NREM stages N1-N3. The average correlation between HG and HRV could be positive or negative across patients given anatomic location and sleep stage and was most profound in lateral temporal lobe in N3, suggestive of greater cortical activity associated with sympathetic tone. Patient-wide correlation was related to δ band activity (1-4 Hz), which is known to be correlated with high γ activity during sleep. The percentage of statistically correlated channels was weaker in N1 and N2 as compared with N3, and was strongest in regions that have previously been associated with autonomic processes, such as anterior hippocampus and insula. The anatomic distribution of HRV-HG correlations during sleep did not reproduce those usually observed with positron emission tomography (PET) or functional magnetic resonance imaging (fMRI) during waking. This study aims to characterize the relationship between autonomic tone and neuronal firing rate during sleep and further studies are needed to investigate finer temporal resolutions, denser coverages, and different frequency bands in both waking and sleep.

An Intracranial Electrophysiology Study of Visual Language Encoding: The Contribution of the Precentral Gyrus to Silent Reading

Models of reading emphasize that visual (orthographic) processing provides input to phonological as well as lexical-semantic processing. Neurobiological models of reading have mapped these processes to distributed regions across occipital-temporal, temporal-parietal, and frontal cortices. However, the role of the precentral gyrus in these models is ambiguous. Articulatory phonemic representations in the precentral gyrus are obviously involved in reading aloud, but it is unclear if the precentral gyrus is recruited during reading silently in a time window consistent with participation in phonological processing contributions. Here, we recorded intracranial electrophysiology during a speeded semantic decision task from 24 patients to map the spatio-temporal flow of information across the cortex during silent reading. Patients selected animate nouns from a stream of nonanimate words, letter strings, and false-font stimuli. We characterized the distribution and timing of evoked high-gamma power (70-170 Hz) as well as phase-locking between electrodes. The precentral gyrus showed a proportion of electrodes responsive to linguistic stimuli (27%) that was at least as high as those of surrounding peri-sylvian regions. These precentral gyrus electrodes had significantly greater high-gamma power for words compared to both false-font and letter-string stimuli. In a patient with word-selective effects in the fusiform, superior temporal, and precentral gyri, there was significant phase-locking between the fusiform and precentral gyri starting at ∼180 msec and between the precentral and superior temporal gyri starting at ∼220 msec. Finally, our large patient cohort allowed exploratory analyses of the spatio-temporal reading network underlying silent reading. The distribution, timing, and connectivity results place the precentral gyrus as an important hub in the silent reading network.

Microscale dynamics of electrophysiological markers of epilepsy

OBJECTIVE

Interictal discharges (IIDs) and high frequency oscillations (HFOs) are established neurophysiologic biomarkers of epilepsy, while microseizures are less well studied. We used custom poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) microelectrodes to better understand these markers' microscale spatial dynamics.

METHODS

Electrodes with spatial resolution down to 50 µm were used to record intraoperatively in 30 subjects. IIDs' degree of spread and spatiotemporal paths were generated by peak-tracking followed by clustering. Repeating HFO patterns were delineated by clustering similar time windows. Multi-unit activity (MUA) was analyzed in relation to IID and HFO timing.

RESULTS

We detected IIDs encompassing the entire array in 93% of subjects, while localized IIDs, observed across < 50% of channels, were seen in 53%. IIDs traveled along specific paths. HFOs appeared in small, repeated spatiotemporal patterns. Finally, we identified microseizure events that spanned 50-100 µm. HFOs covaried with MUA, but not with IIDs.

CONCLUSIONS

Overall, these data suggest that irritable cortex micro-domains may form part of an underlying pathologic architecture which could contribute to the seizure network.

SIGNIFICANCE

These results, supporting the possibility that epileptogenic cortex comprises a mosaic of irritable domains, suggests that microscale approaches might be an important perspective in devising novel seizure control therapies.

Electrochemical safety limits for clinical stimulation investigated using depth and strip electrodes in the pig brain

Objective. Diagnostic and therapeutic electrical stimulation are increasingly utilized with the rise of neuromodulation devices. However, systematic investigations that depict the practical clinical stimulation paradigms (bipolar, two-electrode configuration) to determine the safety limits are currently lacking. Further, safe charge densities that were classically determined from conical sharp electrodes are generalized for cylindrical (depth) and flat (surface grid) electrodes completely ignoring geometric factors that govern current spreading and trajectories in tissue.Approach. This work reports the first investigations comparing stimulation limits for clinically used electrodes in two mediums: in benchtop experiments in saline andin vivoin a single acute experiment in the pig brain. We experimentally determine the geometric factors, the water electrolysis windows, and the current safety limits from voltage transients, for the sEEG, depth and surface strip electrodes in both mediums. Using four-electrode and three-electrode configuration measurements and comprehensive circuit models that accurately depict our measurements, we delineate the various elements of the stimulation medium, including the tissue-electrode interface impedance spectra, the medium impedance and the bias-dependent change in the interface impedance as a function of stimulation parameters.Main results. The results of our systematics studies suggest that safe currents in clinical bipolar stimulation determinedin vivocan be as much as 24 times smaller than those determined from benchtop experiments (for depth electrodes at a 1 ms pulse duration). Our detailed circuit modeling attributes this drastic difference in safe limits to the greatly dissimilar electrode/tissue and electrode/saline impedances.Significance. We established the electrochemical safety limits for commonly used clinical electrodesin vivoand revealed by detailied electrochemical modeling how they differ from benchtop evaluation. We argue that electrochemical limits and currents are unique for each electrode, should be measuredin vivoaccording to the protocols established in this work, and should be accounted for while setting the stimulation parameters for clinical applications including for chronic applications.

A Whole-Cortex Probabilistic Diffusion Tractography Connectome

The WU-Minn Human Connectome Project (HCP) is a publicly-available dataset containing state-of-the-art structural magnetic resonance imaging (MRI), functional MRI (fMRI), and diffusion MRI (dMRI) for over a thousand healthy subjects. While the planned scope of the HCP included an anatomic connectome, resting-state fMRI (rs-fMRI) forms the bulk of the HCP's current connectomic output. We address this by presenting a full-cortex connectome derived from probabilistic diffusion tractography and organized into the HCP-MMP1.0 atlas. Probabilistic methods and large sample sizes are preferable for whole-connectome mapping as they increase the fidelity of traced low-probability connections. We find that overall, connection strengths are lognormally distributed and decay exponentially with tract length, that connectivity reasonably matches macaque histologic tracing in homologous areas, that contralateral homologs and left-lateralized language areas are hyperconnected, and that hierarchical similarity influences connectivity. We compare the dMRI connectome to existing rs-fMRI and cortico-cortico-evoked potential connectivity matrices and find that it is more similar to the latter. This work helps fulfill the promise of the HCP and will make possible comparisons between the underlying structural connectome and functional connectomes of various modalities, brain states, and clinical conditions.

Bidirectional Interaction of Hippocampal Ripples and Cortical Slow Waves Leads to Coordinated Spiking Activity During NREM Sleep

The dialogue between cortex and hippocampus is known to be crucial for sleep-dependent memory consolidation. During slow wave sleep, memory replay depends on slow oscillation (SO) and spindles in the (neo)cortex and sharp wave-ripples (SWRs) in the hippocampus. The mechanisms underlying interaction of these rhythms are poorly understood. We examined the interaction between cortical SO and hippocampal SWRs in a model of the hippocampo-cortico-thalamic network and compared the results with human intracranial recordings during sleep. We observed that ripple occurrence peaked following the onset of an Up-state of SO and that cortical input to hippocampus was crucial to maintain this relationship. A small fraction of ripples occurred during the Down-state and controlled initiation of the next Up-state. We observed that the effect of ripple depends on its precise timing, which supports the idea that ripples occurring at different phases of SO might serve different functions, particularly in the context of encoding the new and reactivation of the old memories during memory consolidation. The study revealed complex bidirectional interaction of SWRs and SO in which early hippocampal ripples influence transitions to Up-state, while cortical Up-states control occurrence of the later ripples, which in turn influence transition to Down-state.

The laminar profile of sleep spindles in humans

Sleep spindles are functionally important NREM sleep EEG oscillations which are generated in thalamocortical, corticothalamic and possibly cortico-cortical circuits. Previous hypotheses suggested that slow and fast spindles or spindles with various spatial extent may be generated in different circuits with various cortical laminar innervation patterns. We used NREM sleep EEG data recorded from four human epileptic patients undergoing presurgical electrophysiological monitoring with subdural electrocorticographic grids (ECoG) and implanted laminar microelectrodes penetrating the cortex (IME). The position of IMEs within cortical layers was confirmed using postsurgical histological reconstructions. Many spindles detected on the IME occurred only in one layer and were absent from the ECoG, but with increasing amplitude simultaneous detection in other layers and on the ECoG became more likely. ECoG spindles were in contrast usually accompanied by IME spindles. Neither IME nor ECoG spindle cortical profiles were strongly associated with sleep spindle frequency or globality. Multiple-unit and single-unit activity during spindles, however, was heterogeneous across spindle types, but also across layers and patients. Our results indicate that extremely local spindles may occur in any cortical layer, but co-occurrence at other locations becomes likelier with increasing amplitude and the relatively large spindles detected on ECoG channels have a stereotypical laminar profile. We found no compelling evidence that different spindle types are associated with different laminar profiles, suggesting that they are generated in cortical and thalamic circuits with similar cortical innervation patterns. Local neuronal activity is a stronger candidate mechanism for driving functional differences between spindles subtypes.

Reactivation of Motor-Related Gamma Activity in Human NREM Sleep

Models of memory consolidation posit a central role for reactivation of brain activity patterns during sleep, especially in non-Rapid Eye Movement (NREM) sleep. While such "replay" of recent waking experiences has been well-demonstrated in rodents, electrophysiological evidence of reactivation in human sleep is still largely lacking. In this intracranial study in patients with epilepsy (N = 9) we explored the spontaneous electroencephalographic reactivation during sleep of spatial patterns of brain activity evoked by motor learning. We first extracted the gamma-band (60-140 Hz) patterns underlying finger movements during a tapping task and underlying no-movement during a short rest period just prior to the task, and trained a binary classifier to discriminate between motor movements vs. rest. We then used the trained model on NREM sleep data immediately after the task and on NREM sleep during a control sleep period preceding the task. Compared with the control sleep period, we found, at the subject level, an increase in the detection rate of motor-related patterns during sleep following the task, but without association with performance changes. These data provide electrophysiological support for the reoccurrence in NREM sleep of the neural activity related to previous waking experience, i.e. that a basic tenet of the reactivation theory does occur in human sleep.

Stimulus Driven Single Unit Activity From Micro-Electrocorticography

High-fidelity measurements of neural activity can enable advancements in our understanding of the neural basis of complex behaviors such as speech, audition, and language, and are critical for developing neural prostheses that address impairments to these abilities due to disease or injury. We develop a novel high resolution, thin-film micro-electrocorticography (micro-ECoG) array that enables high-fidelity surface measurements of neural activity from songbirds, a well-established animal model for studying speech behavior. With this device, we provide the first demonstration of sensory-evoked modulation of surface-recorded single unit responses. We establish that single unit activity is consistently sensed from micro-ECoG electrodes over the surface of sensorimotor nucleus HVC (used as a proper name) in anesthetized European starlings, and validate responses with correlated firing in single units recorded simultaneously at surface and depth. The results establish a platform for high-fidelity recording from the surface of subcortical structures that will accelerate neurophysiological studies, and development of novel electrode arrays and neural prostheses.

Improved identification and differentiation from epileptiform activity of human hippocampal sharp wave ripples during NREM sleep

In rodents, pyramidal cell firing patterns from waking may be replayed in nonrapid eye movement sleep (NREM) sleep during hippocampal sharp wave ripples (HC-SWR). In humans, HC-SWR have only been recorded with electrodes implanted to localize epileptogenicity. Here, we characterize human HC-SWR with rigorous rejection of epileptiform activity, requiring multiple oscillations and coordinated sharp waves. We demonstrated typical SWR in those rare HC recordings which lack interictal epileptiform spikes (IIS) and with no or minimal seizure involvement. These HC-SWR have a similar rate (~12 min^-1 on average, variable across NREM stages and anterior/posterior HC) and apparent intra-HC topography (ripple maximum in putative stratum pyramidale, slow wave in radiatum) as rodents, though with lower frequency (~85 Hz compared to ~140 Hz in rodents). Similar SWR are found in HC with IIS, but no significant seizure involvement. These SWR were modulated by behavior, being largely absent (<2 min^-1 ) except during NREM sleep in both Stage 2 (~9 min^-1 ) and Stage 3 (~15 min^-1 ), distinguishing them from IIS. This study quantifies the basic characteristics of a strictly selected sample of SWR recorded in relatively healthy human hippocampi.

Effects of Early Language Deprivation on Brain Connectivity: Language Pathways in Deaf Native and Late First-Language Learners of American Sign Language

Previous research has identified ventral and dorsal white matter tracts as being crucial for language processing; their maturation correlates with increased language processing capacity. Unknown is whether the growth or maintenance of these language-relevant pathways is shaped by language experience in early life. To investigate the effects of early language deprivation and the sensory-motor modality of language on white matter tracts, we examined the white matter connectivity of language-relevant pathways in congenitally deaf people with or without early access to language. We acquired diffusion tensor imaging (DTI) data from two groups of individuals who experienced language from birth, twelve deaf native signers of American Sign Language, and twelve hearing L2 signers of ASL (native English speakers), and from three, well-studied individual cases who experienced minimal language during childhood. The results indicate that the sensory-motor modality of early language experience does not affect the white matter microstructure between crucial language regions. Both groups with early language experience, deaf and hearing, show leftward laterality in the two language-related tracts. However, all three cases with early language deprivation showed altered white matter microstructure, especially in the left dorsal arcuate fasciculus (AF) pathway.

Selective Formation of Porous Pt Nanorods for Highly Electrochemically Efficient Neural Electrode Interfaces

The enhanced electrochemical activity of nanostructured materials is readily exploited in energy devices, but their utility in scalable and human-compatible implantable neural interfaces can significantly advance the performance of clinical and research electrodes. We utilize low-temperature selective dealloying to develop scalable and biocompatible one-dimensional platinum nanorod (PtNR) arrays that exhibit superb electrochemical properties at various length scales, stability, and biocompatibility for high performance neurotechnologies. PtNR arrays record brain activity with cellular resolution from the cortical surfaces in birds and nonhuman primates. Significantly, strong modulation of surface recorded single unit activity by auditory stimuli is demonstrated in European Starling birds as well as the modulation of local field potentials in the visual cortex by light stimuli in a nonhuman primate and responses to electrical stimulation in mice. PtNRs record behaviorally and physiologically relevant neuronal dynamics from the surface of the brain with high spatiotemporal resolution, which paves the way for less invasive brain-machine interfaces.

Cortical gray-white matter blurring and declarative memory impairment in MRI-negative temporal lobe epilepsy

Magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE) may be a distinct syndrome from TLE with mesial temporal sclerosis (TLE-MTS). Imaging and neuropsychological features of TLE-MTS are well-known; yet, these features are only beginning to be described in MRI-negative TLE. This study examined whether a quantitative measure of cortical gray and white matter blurring (GWB) was elevated in the temporal lobes ipsilateral to the seizure onset zone of individuals with MRI-negative TLE relative to TLE-MTS and healthy controls (HCs) and whether GWB elevations were associated with neuropsychological comorbidity. Gray-white matter blurring from 34 cortical regions and hippocampal volumes were quantified and compared across 28 people with MRI-negative TLE, 15 people with TLE-MTS, and 51 HCs. Declarative memory was assessed with standard neuropsychological tests and the intracarotid amobarbital procedure (IAP). In the group with MRI-negative TLE (left and right onsets combined), hippocampal volumes were within normal range but GWB was elevated, relative to HCs, across several mesial and lateral temporal lobe regions ipsilateral to the seizure onset zone. Gray-white matter blurring did not differ between the groups with TLE-MTS and HC or between the groups with TLE-MTS and MRI-negative TLE. The group with MRI-negative TLE could not be distinguished from the group with TLE-MTS on any of the standard neuropsychological tests; however, ipsilateral hippocampal volumes and IAP memory scores were lower in the group with TLE-MTS than in the group with MRI-negative TLE. The group with left MRI-negative TLE had lower general cognitive abilities and verbal fluency relative to the HC group, which adds to the characterization of neuropsychological comorbidities in left MRI-negative TLE. In addition, ipsilateral IAP memory performance was reduced relative to contralateral memory performance in MRI-negative TLE, indicating some degree of ipsilateral memory dysfunction. There was no relationship between hippocampal volume and IAP memory scores in MRI-negative TLE; however, decreased ipsilateral IAP memory scores were correlated with elevated GWB in the ipsilateral superior temporal sulcus of people with left MRI-negative TLE. In sum, GWB elevations in the ipsilateral temporal lobe of people with MRI-negative TLE suggest that GWB may serve as a marker for reduced structural integrity in regions in or near the seizure onset zone. Although mesial temporal abnormalities might be the major driver of memory dysfunction in TLE-MTS, a loss of structural integrity in lateral temporal lobe regions may contribute to IAP memory dysfunction in MRI-negative TLE.

Simulating human sleep spindle MEG and EEG from ion channel and circuit level dynamics

BACKGROUND

Although they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain.

METHOD

We present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors.

RESULTS

The simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted.

COMPARISON WITH EXISTING METHODS

Previous models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales.

CONCLUSIONS

This multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses.

Delay differential analysis for dynamical sleep spindle detection

BACKGROUND

Sleep spindles are involved in memory consolidation and other cognitive functions. Numerous automated methods for detection of spindles have been proposed; most of these rely on spectral analysis in some form. However, none of these approaches are ideal, and novel approaches to the problem could provide additional insights.

NEW METHOD

Here, we apply delay differential analysis (DDA), a time-domain technique based on nonlinear dynamics to detect sleep spindles in human intracranial sleep data, including laminar electrode, stereoelectroencephalogram (sEEG), and electrocorticogram (ECoG) recordings.

RESULTS

We show that this approach is computationally fast, generalizable, requires minimal preprocessing, and provides excellent agreement with human scoring.

COMPARISON WITH EXISTING METHODS

We compared the method with established methods on a set of intracranial recordings and this method provided the highest agreement with human expert scoring when evaluated with F₁ score while being the second-fastest to run. We also compared the results on the DREAMS surface EEG data, where the method produced a higher average F₁ score than all other tested methods except the automated detections published with the DREAMS data. Further, in addition to being a fast and reliable method for spindle detection, DDA also provides a novel characterization of spindle activity based on nonlinear dynamical content of the data.

CONCLUSIONS

This additional, non-frequency-based perspective could prove particularly useful for certain atypical spindles, or identifying spindles of different types.

Neuroanatomical correlates of emotion-processing in children with unilateral brain lesion: A preliminary study of limbic system organization

In this study, MRI and DTI were employed to examine subcortical volume and microstructural properties (FA, MD) of the limbic network, and their relationships with affect discrimination in 13 FL (6 right FL, M = 10.17 years; 7 left FL; M = 10.09) and 13 typically-developing children (TD; M = 10.16). Subcortical volume of the amygdala, hippocampus and thalamus and FA and MD of the fornix and anterior thalamic radiation (ATR) were examined. Results revealed no group differences across emotion-perception tasks or amygdalar volume. However, contrasting neuroanatomical patterns were observed in right versus left FL youth. Right FL participants showed increased left hippocampal and thalamic volume relative to left FL participants; whereas, the latter group showed increased right thalamic volume. DTI findings also indicated right FL children show greater MD of right fornix than other groups, whereas, left FL youth showed greater MD of left fornix. Right FL youth also showed lower FA of right fornix than left FL children, whereby the latter showed greater FA of left fornix and ATR. Differential associations between DTI indices and auditory/visual emotion-perception were observed across FL groups. Findings indicate diverging brain-behavioral relationships for emotion-perception among right and left FL children.

Theta Bursts Precede, and Spindles Follow, Cortical and Thalamic Downstates in Human NREM Sleep

Since their discovery, slow oscillations have been observed to group spindles during non-REM sleep. Previous studies assert that the slow-oscillation downstate (DS) is preceded by slow spindles (10-12 Hz) and followed by fast spindles (12-16 Hz). Here, using both direct transcortical recordings in patients with intractable epilepsy (n = 10, 8 female), as well as scalp EEG recordings from a healthy cohort (n = 3, 1 female), we find in multiple cortical areas that both slow and fast spindles follow the DS. Although discrete oscillations do precede DSs, they are theta bursts (TBs) centered at 5-8 Hz. TBs were more pronounced for DSs in NREM stage 2 (N2) sleep compared with N3. TB with similar properties occur in the thalamus, but unlike spindles they have no clear temporal relationship with cortical TB. These differences in corticothalamic dynamics, as well as differences between spindles and theta in coupling high-frequency content, are consistent with NREM theta having separate generative mechanisms from spindles. The final inhibitory cycle of the TB coincides with the DS peak, suggesting that in N2, TB may help trigger the DS. Since the transition to N1 is marked by the appearance of theta, and the transition to N2 by the appearance of DS and thus spindles, a role of TB in triggering DS could help explain the sequence of electrophysiological events characterizing sleep. Finally, the coordinated appearance of spindles and DSs are implicated in memory consolidation processes, and the current findings redefine their temporal coupling with theta during NREM sleep.SIGNIFICANCE STATEMENT Sleep is characterized by large slow waves which modulate brain activity. Prominent among these are downstates (DSs), periods of a few tenths of a second when most cells stop firing, and spindles, oscillations at ∼12 times a second lasting for ∼a second. In this study, we provide the first detailed description of another kind of sleep wave: theta bursts (TBs), a brief oscillation at ∼six cycles per second. We show, recording during natural sleep directly from the human cortex and thalamus, as well as on the scalp, that TBs precede, and spindles follow DSs. TBs may help trigger DSs in some circumstances, and could organize cortical and thalamic activity so that memories can be consolidated during sleep.

Monolithic and Scalable Au Nanorod Substrates Improve PEDOT-Metal Adhesion and Stability in Neural Electrodes

Poly(3,4-ethylenenedioxythiophene) or PEDOT is a promising candidate for next-generation neuronal electrode materials but its weak adhesion to underlying metallic conductors impedes its potential. An effective method of mechanically anchoring the PEDOT within an Au nanorod (Au-nr) structure is reported and it is demonstrated that it provides enhanced adhesion and overall PEDOT layer stability. Cyclic voltammetry (CV) stress is used to investigate adhesion and stability of spin-cast and electrodeposited PEDOT. The Au-nr adhesion layer permits 10 000 CV cycles of coated PEDOT film in phosphate buffered saline solution without delamination nor significant change of the electrochemical impedance, whereas PEDOT coating film on planar Au electrodes delaminates at or below 1000 cycles. Under CV stress, spin-cast PEDOT on planar Au delaminates, whereas electroplated PEDOT on planar Au encounters surface leaching/decomposition. After 5 weeks of accelerated aging tests at 60 °C, the electrodeposited PEDOT/Au-nr microelectrodes demonstrate a 92% channel survival compared to only 25% survival for spin-cast PEDOT on planar films. Furthermore, after a 10 week chronic implantation onto mouse barrel cortex, PEDOT/Au-nr microelectrodes do not exhibit delamination nor morphological changes, whereas the conventional PEDOT microelectrodes either partially or fully delaminate. Immunohistochemical evaluation demonstrates no or minimal response to the PEDOT implant.

Toward a Database of Intracranial Electrophysiology during Natural Language Presentation

Intracranial electrophysiology (iEEG) studies using cognitive tasks contribute to the understanding of the neural basis of language. However, though iEEG is recorded continuously during clinical treatment, due to patient considerations task time is limited. To increase the usefulness of iEEG recordings for language study, we provided patients with a tablet pre-loaded with media filled with natural language, wirelessly synchronized to clinical iEEG. This iEEG data collected and time-locked to natural language presentation is particularly applicable for studying the neural basis of combining words into larger contexts. We validate this approach with pilot analyses involving words heard during a movie, tagging syntactic properties and verb contextual probabilities. Event-related averages of high-frequency power (70-170Hz) identified bilateral perisylvian electrodes with differential responses to syntactic class and a linear regression identified activity associated with contextual probabilities, demonstrating the usefulness of aligning media to iEEG. We imagine future multi-site collaborations building an 'intracranial neurolinguistic corpus'.

Williams Syndrome neuroanatomical score associates with GTF2IRD1 in large-scale magnetic resonance imaging cohorts: a proof of concept for multivariate endophenotypes

Despite great interest in using magnetic resonance imaging (MRI) for studying the effects of genes on brain structure in humans, current approaches have focused almost entirely on predefined regions of interest and had limited success. Here, we used multivariate methods to define a single neuroanatomical score of how William's Syndrome (WS) brains deviate structurally from controls. The score is trained and validated on measures of T1 structural brain imaging in two WS cohorts (training, n = 38; validating, n = 60). We then associated this score with single nucleotide polymorphisms (SNPs) in the WS hemi-deleted region in five cohorts of neurologically and psychiatrically typical individuals (healthy European descendants, n = 1863). Among 110 SNPs within the 7q11.23 WS chromosomal region, we found one associated locus (p = 5e-5) located at GTF2IRD1, which has been implicated in animal models of WS. Furthermore, the genetic signals of neuroanatomical scores are highly enriched locally in the 7q11.23 compared with summary statistics based on regions of interest, such as hippocampal volumes (n = 12,596), and also globally (SNP-heritability = 0.82, se = 0.25, p = 5e-4). The role of genetic variability in GTF2IRD1 during neurodevelopment extends to healthy subjects. Our approach of learning MRI-derived phenotypes from clinical populations with well-established brain abnormalities characterized by known genetic lesions may be a powerful alternative to traditional region of interest-based studies for identifying genetic variants regulating typical brain development.

Thalamocortical and intracortical laminar connectivity determines sleep spindle properties

Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.

Sub-millimeter ECoG pitch in human enables higher fidelity cognitive neural state estimation

Electrocorticography (ECoG), electrophysiological recording from the pial surface of the brain, is a critical measurement technique for clinical neurophysiology, basic neurophysiology studies, and demonstrates great promise for the development of neural prosthetic devices for assistive applications and the treatment of neurological disorders. Recent advances in device engineering are poised to enable orders of magnitude increase in the resolution of ECoG without comprised measurement quality. This enhancement in cortical sensing enables the observation of neural dynamics from the cortical surface at the micrometer scale. While these technical capabilities may be enabling, the extent to which finer spatial scale recording enhances functionally relevant neural state inference is unclear. We examine this question by employing a high-density and low impedance 400 μm pitch microECoG (μECoG) grid to record neural activity from the human cortical surface during cognitive tasks. By applying machine learning techniques to classify task conditions from the envelope of high-frequency band (70-170Hz) neural activity collected from two study participants, we demonstrate that higher density grids can lead to more accurate binary task condition classification. When controlling for grid area and selecting task informative sub-regions of the complete grid, we observed a consistent increase in mean classification accuracy with higher grid density; in particular, 400 μm pitch grids outperforming spatially sub-sampled lower density grids up to 23%. We also introduce a modeling framework to provide intuition for how spatial properties of measurements affect the performance gap between high and low density grids. To our knowledge, this work is the first quantitative demonstration of human sub-millimeter pitch cortical surface recording yielding higher-fidelity state estimation relative to devices at the millimeter-scale, motivating the development and testing of μECoG for basic and clinical neurophysiology as well as towards the realization of high-performance neural prostheses.

Superficial Slow Rhythms Integrate Cortical Processing in Humans

The neocortex is composed of six anatomically and physiologically specialized layers. It has been proposed that integration of activity across cortical areas is mediated anatomically by associative connections terminating in superficial layers, and physiologically by slow cortical rhythms. However, the means through which neocortical anatomy and physiology interact to coordinate neural activity remains obscure. Using laminar microelectrode arrays in 19 human participants, we found that most EEG activity is below 10-Hz (delta/theta) and generated by superficial cortical layers during both wakefulness and sleep. Cortical surface grid, grid-laminar, and dual-laminar recordings demonstrate that these slow rhythms are synchronous within upper layers across broad cortical areas. The phase of this superficial slow activity is reset by infrequent stimuli and coupled to the amplitude of faster oscillations and neuronal firing across all layers. These findings support a primary role of superficial slow rhythms in generating the EEG and integrating cortical activity.

Replay of large-scale spatio-temporal patterns from waking during subsequent NREM sleep in human cortex

Animal studies support the hypothesis that in slow-wave sleep, replay of waking neocortical activity under hippocampal guidance leads to memory consolidation. However, no intracranial electrophysiological evidence for replay exists in humans. We identified consistent sequences of population firing peaks across widespread cortical regions during complete waking periods. The occurrence of these “Motifs” were compared between sleeps preceding the waking period (“Sleep-Pre”) when the Motifs were identified, and those following (“Sleep-Post”). In all subjects, the majority of waking Motifs (most of which were novel) had more matches in Sleep-Post than in Sleep-Pre. In rodents, hippocampal replay occurs during local sharp-wave ripples, and the associated neocortical replay tends to occur during local sleep spindles and down-to-up transitions. These waves may facilitate consolidation by sequencing cell-firing and encouraging plasticity. Similarly, we found that Motifs were coupled to neocortical spindles, down-to-up transitions, theta bursts, and hippocampal sharp-wave ripples. While Motifs occurring during cognitive task performance were more likely to have more matches in subsequent sleep, our studies provide no direct demonstration that the replay of Motifs contributes to consolidation. Nonetheless, these results confirm a core prediction of the dominant neurobiological theory of human memory consolidation.

Increased glia density in the caudate nucleus in williams syndrome: Implications for frontostriatal dysfunction in autism

Williams syndrome (WS) is a rare neurodevelopmental disorder with a well-described, known genetic etiology. In contrast to Autism Spectrum Disorders (ASD), WS has a unique phenotype characterized by global reductions in IQ and visuospatial ability, with relatively preserved language function, enhanced reactivity to social stimuli and music, and an unusual eagerness to interact socially with strangers. A duplication of the deleted region in WS has been implicated in a subset of ASD cases, defining a spectrum of genetic and behavioral variation at this locus defined by these opposite extremes in social behavior. The hypersociability characteristic of WS may be linked to abnormalities of frontostriatal circuitry that manifest as deficits in inhibitory control of behavior. Here, we examined the density of neurons and glia in associative and limbic territories of the striatum including the caudate, putamen, and nucleus accumbens regions in Nissl stained sections in five pairs of age, sex, and hemisphere-matched WS and typically-developing control (TD) subjects. In contrast to what is reported in ASD, no significant increase in overall neuron density was observed in this study. However, we found a significant increase in the density of glia in the dorsal caudate nucleus, and in the ratio of glia to neurons in the dorsal and medial caudate nucleus in WS, accompanied by a significant increase in density of oligodendrocytes in the medial caudate nucleus. These cellular abnormalities may underlie reduced frontostriatal activity observed in WS, with implications for understanding altered connectivity and function in ASD. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 531-545, 2018.