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Watrous, A. J.

Publications and source records attributed to Watrous, A. J..

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Electrophysiological features of signals recorded from white matter

Intracranial neurophysiology studies have typically ignored signals from electrodes located in white matter (WM), assuming that their information content is artifactual or related to nearby gray matter (GM). Here, we tested the electrophysiological and functional features of signals recorded from different WM locations. Signals were recorded from 19 patients undergoing intracranial monitoring for drug-resistant epilepsy by means of stereo-electroencephalography (sEEG). Each sEEG electrode was classified into WM or GM based on the surrounding tissue. We obtained recordings from a total of 1,717 sEEG electrode contacts, 36% in WM, while the patients were in awake resting state (5 minutes). For each sEEG electrode, we employed a model-based spectral decomposition to separate periodic and aperiodic components, and we computed signal complexity metrics. For a subset of participants, we computed WM structural information from diffusion-weighted magnetic resonance imaging and we evaluated functional signals during a cognitive control task. Our results show that signals recorded from WM have different spectral features and higher complexity than GM. Complexity correlates positively with fractional anisotropy, and modulations related to behavior during the task were detected in WM. Overall, this indicates that WM signals carry information that may reflect signal propagation across WM fiber tracts.

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Perspectives in conducting task-based research in pediatric surgical epilepsy patients

ObjectivePediatric epilepsy patients undergoing stereo-electroencephalography (sEEG) for ictal onset evaluation provide a rare window to study the developing brain. While methodological frameworks for task-based sEEG research are well-established in adults, pediatric-specific guidance remains underdeveloped. Furthermore, many pediatric epilepsy patients have comorbidities that might typically exclude them from participating in research. We examine factors that influence research participation and discuss considerations for conducting sEEG research in children. MethodsHere, we present a retrospective analysis of task-based research participation patterns from an NIH-funded study of speech and language representations (1R01DC018579) in 66 patients (ages 4-24) undergoing sEEG monitoring at Texas Childrens Hospital to determine whether specific comorbidities influenced research participation. ResultsEighty-nine percent (n=66) of patients approached for consent agreed to participate in the study. Despite high rates of comorbidities including neurocognitive disorder (66.67%), language delay (31.75%), global developmental delay (23.81%), mood disorders (33.33%), ADHD (46.03%), autism spectrum disorder (14.29%) or other cognitive/intellectual disabilities (36.51%), all participants engaged in at least one task. While the majority of these diagnoses did not appear to influence subject participation, global developmental delay was associated with a significant reduction in time spent on active tasks. DiscussionDespite high prevalence of neuropsychological comorbidities among participants, our evidence suggests that these participants contribute meaningfully to studies investigating important developmental questions. We suggest strategies for tailoring task-based research to accommodate the unique needs of individuals in this population. Such practices are important for ensuring that research studies reflect the true diversity of the population.

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Distinct tasks engage a shared neural subspace in human hippocampus and anterior cingulate cortex

A hallmark of human cognitive flexibility is the ability to perform a wide range of unrelated tasks. While much is known about how neural circuits support individual tasks, less is understood about how these circuits support multiple tasks. Are neural representations largely task-specific, or do they retain a shared structure across distinct behaviors? To investigate this question, we recorded neural population activity from the hippocampus and anterior cingulate cortex, two regions linked to generalization and cognitive control, in eleven human patients performing three distinct tasks. Using dimensionality reduction, we estimated the neural subspace associated with each task and compared subspace geometry across tasks. We found that task-related subspaces were not independent: across tasks, approximately half of the subspace dimensions were shared, and these were primarily the dimensions containing most of the shared neural covariance. These findings indicate that neural population activity in these regions is not purely task-specific. This suggests a stable, low-dimensional circuit structure may persist even across unrelated behaviors, potentially providing a common substrate for flexible cognition.

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Human auditory cortex preferentially tracks speech over music without explicit attention

Our brains constantly filter incoming sounds to understand our environment. While extensively studied in adults, how this ability develops across childhood remains unclear. We recorded intracranial brain activity from 54 participants aged 4-21 while they watched movie clips containing simultaneous speech and music. We used deep neural networks to separate the mixed audio into isolated speech and music streams, then built encoding models to determine which stream best predicted neural responses in the auditory cortex. Although participants heard only the original mixture with no instruction to attend to either stream, higher-order auditory regions including the superior temporal gyrus (STG), superior temporal sulcus (STS) and middle temporal gyrus (MTG), responded preferentially to speech. This speech-bias strengthened with age in STG, suggesting that this region progressively sharpens its representation of socially relevant sound across development. These findings indicate that speech prioritization in the developing brain emerges automatically, without directed attention.

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Attention is all you need (in the brain): semantic contextualization in human hippocampus

Word meanings in language are contextualized by surrounding words. Inspired by the self-attention mechanism in transformer-based large language models (LLMs), we hypothesized that structural composition in the brain arises from combining canonical (non-contextual) word representations with those of nearby words. We analyzed single unit activity in the human hippocampus, a region involved in semantic and contextual processing, while n=10 participants listened to podcasts. We found that hippocampal neurons encoded word position within a clause, using both ordinal and frequency-domain positional encoding. Moreover, neural responses to specific words reflected both the words own lexical semantics and a weighted sum of the embeddings of preceding words. The relative weighting of these contextualizing words correlated with LLM self-attention weights. These findings suggest that contextualization in the brain makes use of vectorial shifts that have a resemblance to attentional reweighting in LLMs, and highlight the role of the mesial temporal lobe within the broader language network.

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Insula uses overlapping codes for emotion in self and others

In daily life, we must recognize others emotions so we can respond appropriately. This ability may rely, at least in part, on neural responses similar to those associated with our own emotions. We hypothesized that the insula, a cortical region near the junction of the temporal, parietal, and frontal lobes, may play a key role in this process. We recorded local field potential (LFP) activity in human neurosurgical patients performing two tasks, one focused on identifying their own emotional response and one on identifying facial emotional responses in others. We found matching patterns of gamma- and high-gamma band activity for the two tasks in the insula. Three other regions (MTL, ACC, and OFC) clearly encoded both self- and other-emotions, but used orthogonal activity patterns to do so. These results support the hypothesis that the insula plays a particularly important role in mediating between experienced vs. observed emotions.

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Processing of auditory feedback in perisylvian and insular cortex

When we speak, we not only make movements with our mouth, lips, and tongue, but we also hear the sound of our own voice. Thus, speech production in the brain involves not only controlling the movements we make, but also auditory and sensory feedback. Auditory responses are typically suppressed during speech production compared to perception, but how this manifests across space and time is unclear. Here we recorded intracranial EEG in seventeen pediatric, adolescent, and adult patients with medication-resistant epilepsy who performed a reading/listening task to investigate how other auditory responses are modulated during speech production. We identified onset and sustained responses to speech in bilateral auditory cortex, with a selective suppression of onset responses during speech production. Onset responses provide a temporal landmark during speech perception that is redundant with forward prediction during speech production. Phonological feature tuning in these "onset suppression" electrodes remained stable between perception and production. Notably, the posterior insula responded at sentence onset for both perception and production, suggesting a role in multisensory integration during feedback control.

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A biophysically constrained brain connectivity model based on stimulation-evoked potentials.

BackgroundSingle-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies. New MethodUsing intracranial electrophysiology data recorded from a single patient undergoing sEEG evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D conductivity propagation from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features. ResultsThe proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlates with additional PEP features and displayed stable, weak correlations with tractography measures. Comparison with existing methodsExisting methods for estimating conductivity propagation are imaging-based and thus rely on anatomical inferences. ConclusionsThese results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.

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Brain mechanisms underlying the emotion processing bias in treatment-resistant depression

Depression is associated with a cognitive bias towards negative information and away from positive information. This biased emotion processing may underlie core depression symptoms, including persistent feelings of sadness or low mood and a reduced capacity to experience pleasure. The neural mechanisms responsible for this biased emotion processing remain unknown. Here, we had a unique opportunity to record stereotactic electroencephalography (sEEG) signals in the amygdala and prefrontal cortex (PFC) from 5 treatment-resistant depression (TRD) patients and 12 epilepsy patients (as control) while they participated in an affective bias task in which happy and sad faces were rated. First, compared with the control group, patients with TRD showed increased amygdala responses to sad faces in the early stage (around 300 ms) and decreased amygdala responses to happy faces in the late stage (around 600 ms) following the onset of faces. Further, during the late stage of happy face processing, alpha-band activity in PFC as well as alpha-phase locking between the amygdala and PFC were significantly greater in TRD patients compared to the controls. Second, after deep brain stimulation (DBS) delivered to bilateral subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS), atypical amygdala and PFC processing of happy faces in TRD patients remitted toward the normative pattern. The increased amygdala activation during the early stage of sad face processing suggests an overactive bottom-up processing system in TRD. Meanwhile, the reduced amygdala response during the late stage of happy face processing could be attributed to inhibition by PFC through alpha-band oscillation, which can be released by DBS in SCC and VC/VS.

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The Oscillatory ReConstruction Algorithm (ORCA) adaptively identifies frequency bands to improve spectral decomposition in human and rodent neural recordings

Neural oscillations are routinely analyzed using methods that measure activity in canonical frequency bands (e.g. alpha, 8-12 Hz), though the frequency of neural signals is not fixed and varies within and across individuals based on numerous factors including neuroanatomy, behavioral demands, and species. Further, band-limited activity is an often assumed, typically unmeasured model of neural activity and band definitions vary considerably across studies. These factors together mask individual differences and can lead to noisy spectral estimates and interpretational problems when linking electrophysiology to behavior. We developed the Oscillatory ReConstruction Algorithm ("ORCA"), an unsupervised method to measure the spectral characteristics of neural signals in adaptively identified bands which incorporates two new methods for frequency band identification. ORCA uses the instantaneous power, phase, and frequency of activity in each band to reconstruct the signal and directly quantify spectral decomposition performance using each of four different models. To reduce researcher bias, ORCA provides spectral estimates derived from the best model and requires minimal hyperparameterization. Analyzing human scalp EEG data during eyes open and eyes-closed "resting" conditions, we first identify variability in the frequency content of neural signals across subjects and electrodes. We demonstrate that ORCA significantly improves spectral decomposition compared to conventional methods and captures the well-known increase in low-frequency activity during eyes closure in electrode- and subject-specific frequency bands. We further illustrate the utility of our method in rodent CA1 recordings. ORCA is a novel analytic tool that will allow researchers to investigate how non-stationary neural oscillations vary across behaviors, brain regions, individuals, and species.

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The effects of direct brain stimulation in humans depend on frequency, amplitude, and white-matter proximity.

Researchers have used direct electrical brain stimulation to treat a range of neurological and psychiatric disorders. However, for brain stimulation to be maximally effective, clinicians and researchers should optimize stimulation parameters according to desired outcomes. To examine how different kinds of stimulation affect human brain activity, we compared the changes in neuronal activity that resulted from stimulation at a range of frequencies, amplitudes, and locations with direct human brain recordings. We recorded human brain activity directly with electrodes that were implanted in widespread regions across 106 neurosurgical epilepsy patients while systematically stimulating across a range of parameters and locations. Overall, stimulation most often had an inhibitory effect on neuronal activity, consistent with earlier work. When stimulation excited neuronal activity, it most often occurred from high-frequency stimulation. These effects were modulated by the location of the stimulating electrode, with stimulation sites near white matter more likely to cause excitation and sites near gray matter more likely to inhibit neuronal activity. By characterizing how different stimulation parameters produced specific neuronal activity patterns on a large scale, our results help guide clinicians and researchers when designing stimulation protocols to cause precisely targeted changes in human brain activity.

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Functionally distinct high and low theta oscillations in the human hippocampus

Based on rodent models, researchers have theorized that the hippocampus supports episodic memory and navigation via the theta oscillation, a ~4-10-Hz rhythm that coordinates brain-wide neural activity. However, recordings from humans have indicated that hippocampal theta oscillations are lower in frequency and less prevalent than in rodents, suggesting interspecies differences in thetas function. To characterize human hippocampal theta, we examined the properties of theta oscillations throughout the anterior-posterior length of the hippocampus as neurosurgical subjects performed a virtual spatial navigation task. During virtual movement, we observed hippocampal oscillations at multiple frequencies from 2 to 14 Hz. The posterior hippocampus prominently displayed oscillations at ~8-Hz and the precise frequency of these oscillations correlated with the speed of movement, implicating these signals in spatial navigation. We also observed slower ~3-Hz oscillations, but these signals were more prevalent in the anterior hippocampus and their frequency did not vary with movement speed. Our results converge with recent findings to suggest an updated view of human hippocampal electrophysiology. Rather than one hippocampal theta oscillation with a single general role, high-and low-theta oscillations, respectively, may reflect spatial and non-spatial cognitive processes.

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Electrophysiological signatures of spatial boundaries in the human subiculum

Environmental boundaries play a crucial role in spatial navigation and memory across a wide range of distantly-related species. In rodents, boundary representations have been identified at the single-cell level in the subiculum and entorhinal cortex of the hippocampal formation. While studies of hippocampal function and spatial behavior suggest that similar representations might exist in humans, boundary-related neural activity has not been identified electrophysiologically in humans until now. Here we present direct intracranial recordings from the hippocampal formation of surgical epilepsy patients while they performed a virtual spatial navigation task. Our results suggest that encoding target locations near boundaries elicited stronger theta oscillations than for target locations near the center of the environment and that this difference cannot be explained by variables such as trial length, speed, or movement. These findings provide the first direct evidence of boundary-dependent neural activity localized in humans to the subiculum, the homologue of the hippocampal subregion in which most rodent boundary cells are found.\n\nSignificance StatementSpatial computations using environmental boundaries are an integral part of the brains spatial mapping system. In rodents, border/boundary cells in the subiculum and entorhinal cortex reveal boundary coding at the single-neuron level. Although there is good reason to believe that such representations also exist in humans, the evidence has thus far been limited to fMRI studies that broadly implicate the hippocampus in boundary-based navigation. By combining intracranial recordings with high-resolution imaging of hippocampal subregions we identified, for the first time in humans, a neural marker of boundary representation in the subiculum.

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Theta and alpha oscillations are traveling waves in the human neocortex

Human cognition requires the coordination of neural activity across widespread brain networks. Here we describe a new mechanism for large-scale coordination in the human brain: traveling waves of theta and alpha oscillations. Examining direct brain recordings from neurosurgical patients performing a memory task, we found that contiguous clusters of cortex in individual patients showed oscillations at specific frequencies in the range of 2 to 15 Hz. These clusters displayed spatial phase gradients, indicating that individual oscillation cycles moved across the cortex at ~0.25-0.75 m/s. We found that traveling waves were relevant behaviorally because their propagation correlated with task events and was more consistent during good performance. Traveling waves showed a correlation between propagation speed and temporal frequency, which suggests that they propagate across the cortex following principles of phase-coupled oscillatory networks. By demonstrating that theta and alpha traveling waves are widespread and behaviorally relevant, our results suggest a broad role for brain oscillations in supporting cortical connectivity by organizing neural activity across space and time.

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The medial temporal lobe organizes memory across time and space: Causal evidence from brain stimulation

The medial temporal lobe (MTL) is widely implicated in supporting episodic memory and navigation, but its precise functional role in organizing memory across time and space remains elusive. Here we examine the specific cognitive processes implemented by MTL structures (hippocampus and entorhinal cortex) to organize memory by using electrical brain stimulation, leveraging its ability to establish causal links between brain regions and features of behavior. We studied neurosurgical patients who performed spatial-navigation and verbal-episodic memory tasks while brain stimulation was applied in various regions during learning. During the verbal memory task, stimulation in the MTL disrupted the temporal organization of encoded memories such that items learned with stimulation tended to be recalled in a more randomized order. During the spatial task, MTL stimulation impaired subjects abilities to remember items using view-independent (allocentric) navigation strategies. These stimulation effects were specific to the MTL. Our findings thus provide the first causal demonstration in humans of the specific memory processes that are performed by the MTL to encode when and where events occurred.\n\nSignificance StatementNumerous studies have implicated the medial temporal lobe (MTL) in encoding spatial and temporal memories, but they have not been able to causally demonstrate the nature of the cognitive processes by which this occurs in real-time. Electrical brain stimulation is able to demonstrate causal links between a brain region and a given function with high temporal precision. By examining behavior in a memory task as subjects received MTL stimulation, we provide the first causal evidence demonstrating the role of the MTL in organizing the spatial and temporal aspects of episodic memory.

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Phase-tuned neuronal firing encodes human contextual representations for navigational goals

We previously demonstrated that the phase of oscillations modulates neural activity representing categorical information using human intracranial recordings and high-frequency activity from local field potentials (Watrous et al., 2015b). We extend these findings here using human single-neuron recordings during a navigation task. We identify neurons in the medial temporal lobe with firing-rate modulations for specific navigational goals, as well as for navigational planning and goal arrival. Going beyond this work, using a novel oscillation detection algorithm, we identify phase-locked neural firing that encodes information about a persons prospective navigational goal in the absence of firing rate changes. These results provide evidence for navigational planning and contextual accounts of human MTL function at the single-neuron level. More generally, our findings identify phase-coded neuronal firing as a component of the human neural code.

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