Biology subjects

Smith, E. H.

Publications and source records attributed to Smith, E. H..

At least 19 recordsLinked to original sources

bioRxiv2026

Low-dimensional factorized neural computations underlie risk-adaptive choices

Real-world decision-making rarely occurs with perfect information. Instead, individuals must constantly weigh potential rewards against the probability of adverse outcomes.1 Failures of this process can lead to maladaptive decisions associated with reduced lifetime success, and numerous psychiatric disorders such as gambling addictions, bulimia nervosa, and substance use disorder.2,3 The neural computations that facilitate inference about the landscape of potential outcomes remain unclear, but are thought to occur in distributed frontotemporal circuits.4 Here we used deep reinforcement learning agents to predict distinct behavioral strategies and their underlying neural population dynamics during a risky decision-making task. Across a range of training conditions, deep reinforcement learning agents separated into strategies marked by either overly cautious exploration of the reward contingency space or a high-performing, risk-adaptive Bimodal strategy. The internal dynamics of high-performing Bimodal agents formed low-dimensional representations that segregated safe and risky states. In contrast, the cautious exploration agents were associated with more skewed and entangled neural representations. We found remarkably similar dynamical representations and their associated behavioral strategies in neuronal ensemble recordings from human epilepsy patients performing a similar risky decision-making task. These results reveal the structure of dynamical computations that underlie inferences about uncertain outcomes and their associated behavioral strategies.

neuroscience↗

bioRxiv2026

Temporal Processing during Decision Making under Uncertainty.

Time perception and decision-making are interrelated processes that are critical to much of human and animal behavior. Although the behavioral importance of this link between the processes has been established, the neural underpinnings of temporal decision-making are unclear. The current study leverages human intracranial electro-physiology to investigate the neural contribution of temporal processing to decision-making under risk. To probe temporal decision-making, we use a version of the Balloon Analogue Risk Task, in which participants inflate virtual balloons with the goal of reaching maximal balloon size but stopping inflation before the balloon pops. Points are awarded based on inflation duration of successful trials, such that points awarded are linearly related to balloon size. By decoding temporal features of the task on a trial-by-trial basis, we find neural representations of time during balloon inflation. Specifically, we find that both medial and lateral temporal regions of the brain encode the majority of this time-related signal. Importantly, we can decode the progression of time leading up to the outcome of a successful decision (pressing a button to stop inflation before the balloon pops). This encoding of time depends on an active decision to end the trial: we cannot decode time during passive observation of balloon inflation to a known maximal size. To validate these results further, we use a temporal convolution network to predict participants response (i.e., time of button press) based on the brain activity leading up to the response. We find that we can predict the moment of response with high accuracy and temporal resolution. The model predicts the timing of successful decisions but not the timing of balloon pops. Together, these findings reveal neural representations that encode the progression of time, specifically in relation to an active decision.

neuroscience↗

bioRxiv2026

Propofol-induced loss of responsiveness reorganizes cortical traveling waves in the human brain

Consciousness depends on the coordinated propagation of neural activity across cortical networks. Traveling waves, the spatiotemporal patterns of phase-aligned neural activity, are thought to support large-scale cortical communication, yet how these dynamics are altered during general anesthesia remains poorly understood. Here, we examined the effects of propofol on cortical traveling waves recorded with high-density microelectrode arrays in the temporal lobes of two human participants (both men). We identified and characterized changes in neural traveling wave properties as participants underwent general anesthesia. Propofol produced robust, state-dependent reorganization of wave dynamics: increased propagation speed, shifted propagation directions, and altered spectral structure. At the neuronal level, propofol was accompanied by pronounced changes in firing activity and spike-wave relationships, linking mesoscale traveling waves to coordinated changes in neuronal firing dynamics. Together, these findings demonstrate how propofol reshapes the spatiotemporal organization of cortical activity across spatial scales.

neuroscience↗

bioRxiv2026

Asymmetric Reinforcement Learning Explains Human Choice Patterns in Decision-making Under Risk

Human decisions under uncertainty are shaped by experience, but the computations that translate expectation and experience into choice remain debated in neural and cognitive science. Prior studies highlight reinforcement learning (RL) as a unifying framework, yet it is unclear whether human behavior under risk is better captured by symmetric updating from outcomes or by asymmetric learning that weights reward and loss differently. This work examines which learning strategies better explain trial-by-trial choices given contextual uncertainty and manipulations of outcome distributions. Our results show that a Risk Sensitive (RS) model with asymmetric learning rates best explains human behavior in our novel decision-making task. Fitting candidate models to individual trial histories yielded value signals that predicted both choice and response time. These results highlight that RS model, as an asymmetric learning provides a concise and identifiable account of behavior in decision-making under risk tasks.

neuroscience↗

bioRxiv2026

Semantic axes in the brain support analogical representations

ABSTRACTIn language models of word meaning, directions in the embedding space often correspond to semantic features that can be reused across different words. For example, a single direction corresponding to gender may differentiate word pairs like "boy/girl", "uncle/aunt" and "king/queen". Here we show that the same principle governs semantically driven neural responses in the human brain. We recorded populations of single neurons during podcast listening and identified word sets with consistent meaning differences. Across fifteen sets, including gender, plural, and negation, we observed consistent vectorial directions, resulting in parallelogram structures within the neural manifold. Deviation from parallelism in large language models (LLMs) predicted corresponding deviations in brain-derived parallelism. Among pronouns, vectors corresponding to case, number and person exhibited parallelogram structures individually and, collectively, obeyed the principle of commutativity, resulting in a prismatic structure. Finally, different semantic variables were preferentially associated with discrete groups of neurons, consistent with energy-efficiency theories. Together, these results establish a geometric foundation for the neural encoding of word meaning.

neuroscience↗

bioRxiv2025

Increased Aperiodic Exponents Track Depression Symptom Severity

Roughly one-third of patients with major depressive disorder (MDD) fail to respond to standard treatments and develop treatment-resistant MDD. For these patients, alternative therapies ofer additional options but yield inconsistent outcomes. Progress has been limited by the absence of objective, brain-based biomarkers to guide target selection or track therapeutic response in real time. Instead, clinicians rely on behavioral assessments that evolve slowly over weeks to months, obscuring the underlying neural dynamics of symptom changes. Here, we test whether the aperiodic exponent of intracranial EEG (iEEG) local field potentials can serve as a neurophysiological marker of depression symptom severity. We leveraged a large iEEG cohort (N = 20) undergoing invasive monitoring for refractory epilepsy, yielding over 1,800 contacts spanning cortical and subcortical zones. For each contact, we estimated the aperiodic exponent (thought to reflect aspects of cortical excitability) of the power spectrum across 10-100 Hz within local brain regions and across distributed cortical association networks. Depressive symptoms were assessed with the Beck Depression Inventory-II (BDI-II) immediately before intracranial resting state recordings. With respect to the BDI-II scale, participants were identified as experiencing minimal (BDI-II [≤] 13) or elevated depression symptoms (BDI-II [≥] 14). Associations between symptom severity (BDI-II total score and Somatic-Afective, Cognitive, and Anhedonia subscales) and region- or network-level exponents were modeled with ordinary least squares (OLS) regression. The whole-brain, mean aperiodic exponent for each participant discriminated symptom status (AUC = 0.82). At the regional level, the orbitofrontal cortex, anterior cingulate cortex, insula, and amygdala showed higher exponents in the elevated depression symptom group (d = 1.18-1.71; p = 0.032-0.004). A post-hoc classification analysis across these four regions misclassified one participant per group (AUC = 0.86; 95% CI 0.64-1.00). In continuous analyses, BDI-II scores correlated positively with exponents in these same four regions (pFDR = 0.019-0.027; partial r=0.61-0.70) and at the network level in the Salience network (pFDR = 0.024; partial r = 0.63) and Default (pFDR = 0.046; partial r = 0.55) network. The Salience network significantly tracked Anhedonia symptoms (p = 0.004; partial r = 0.62). Here we report that intracranial aperiodic exponents within fronto-limbic and insular circuits, overlapping with networks implicated in contemporary accounts of depression pathophysiology, diferentiate depressive symptom status and scale with severity. These findings support the aperiodic exponent as a candidate neurophysiological marker of current depression symptom burden, with potential relevance for individualized neuromodulation in MDD.

neuroscience↗

bioRxiv2025

Frontotemporal bursting supports human working memory

Cortical neural activity varies dynamically during memory periods, when relevant information is not present in the environment. But how those dynamics are related to a code defining working memory (WM) performance is not known. Recent data shows brief bursts of activity in the high gamma (70-140 Hz) and beta (12-30 Hz) band within non-human primate lateral prefrontal cortex (PFC) is associated with WM processing. However, WM may be related to activity within a network of frontal executive and posterior sensory areas involved in stimulus perception. Here we tested whether gamma and beta bursting exist in lateral PFC and multisensory lateral temporal areas in humans during visual WM, and whether these areas are coupled via a phase-burst code. We used intracranial macroelectrode recordings from the middle frontal gyrus (MFG), which includes dorsolateral PFC, and from the middle temporal gyrus (MTG), an area important for visual processing. High gamma bursting increased in human left PFC during encoding and delay periods while beta bursting decreased. Interestingly, beta bursting increased in multisensory areas during encoding and remained high during the delay period, more so on the right. These effects varied with WM performance. Finally, we quantify the degree to which delay-period gamma bursting is locked to beta phase within and between regions of this network using a proposed metric termed phase-burst coupling (PBC). We find evidence that delay-period gamma bursting in temporal areas is locked to beta phase in PFC. Our findings suggest that WM may use bursting to support memory maintenance until readout. Significance StatementWorking memory is critical for everyday functioning and its disruption results in significant disability in patients with dementia, traumatic brain injury, and stroke. We recorded human intracranial data during a visual working memory task. We found that prefrontal cortex and multisensory temporal brain areas show neural bursting activity during the memory period and that such bursting is related to trial performance. Furthermore, these two areas may be coupled by a phase-burst code. Bursting has been found in non-human primates, rodents, and even crows, suggesting it is a general feature of memory, and perhaps of other aspects of cognition.

neuroscience↗

bioRxiv2025

Human brain network control of creativity

The ability to think creatively is fundamental to human cognition, shaping how we interact with the world and navigate complex problems. Creativity depends on the interaction of multiple large-scale brain networks, but how these networks represent creative thought and distinguish it from other cognitive states remains unclear. Here, we use invasive intracranial recordings in the human brain to explore the network-level representations underlying creative thinking. Our results demonstrate that cortical networks in the human brain differentially encode distinct cognitive states: we found unique brain states underlying creative thinking vs. arithmetic calculations, particularly in the default mode network. Further, in the dorsal attention network, we uncovered nonlinear, high-dimensional representations of moment-by-moment fluctuations in creative performance. These representations define a neural creativity axis shared between network-level and single-neuron computations. Our findings reveal widespread neural representations of cognitive state and suggest distinct roles of specific cortical networks in controlling creativity, with the default mode network gating access to creative states and the dorsal attention network regulating the quality of creative output.

neuroscience↗

bioRxiv2025

Human and Rodent Seizures Demonstrate a Dynamic Interplay with Spreading Depolarizations

Seizure termination has been linked to spreading depolarizations (SDs) in experimental epilepsy models, and SDs have recently been suggested to protect against seizures. The precise mechanism, however, remains unclear. Additionally, the co-occurrence of SDs with human seizures remains debated. In this study, we found that SDs are a prominent feature following ictal events in both human clinical recordings (n=20 seizures from 7 epilepsy patients) using direct-current amplifiers and in the 0 Mg2+ model of ictogenesis from rodent brain slices (n=17). Approximately one-third of rodent seizure-like events (SLEs) were associated with SDs, while all human seizures analyzed had associated infraslow shifts, a hallmark of SDs. SDs were more prominent in the lateral frontal, medial frontal, and lateral temporal lobes, as well as the insular cortex in human patients, but were observed in all recorded brain regions. In rodents, SDs clustered toward the end of ictal events, resulting in significantly shorter SLEs (SLE without SD: 32.60 {+/-} 5.31 s; SLE with SD: 16.03 {+/-} 4.45 s) and delayed onset of subsequent SLEs. These SDs also caused significant AC band silencing compared to SLEs without SDs. Interestingly, SLEs with SDs displayed significantly more low gamma activity during ictal events. Using ion- selective microelectrodes, we found no significant correlation between extracellular [K+] levels and SLEs ending in SDs, questioning the role of [K+]o in SD induction during seizures. We observed more heterogeneity in human seizures than in rodent SLEs, with some human seizures showing SD-associated termination and others demonstrating SDs in the middle of ictal events; such intra-seizure SDs were never observed in our rodent model. The human data, collected from patients with intractable epilepsy, demonstrate clear SD propagation during seizures and show that SDs appear and propagate, in multiple brain regions simultaneously with ictal events. Collectively, these results indicate that SDs are a hallmark of ictal activity and may contribute to seizure termination in both experimental and clinical settings. Furthermore, these findings provide unique insight into the neuronal dynamics that promote SD induction by showing that increased low gamma activity during SLEs is more predictive of SD induction than extracellular [K+] levels. We also add further support for the hypothesis that SDs are both anti- seizure and anti-ictogenic as they not only limit and delay subsequent ictal activity but also reduce the duration of SLEs. Taken together, these findings provide rationale for further exploration of SDs as a means to prematurely terminate life-threatening seizures.

neuroscience↗

bioRxiv2024

Cell-type specific responses to single-pulse electrical stimulation of the human brain

Neuromodulation techniques, such as deep brain stimulation, intraoperative brain mapping, and responsive neurostimulation, use electricity to alter brain activity. Despite daily clinical use in thousands of patients, it remains fundamentally unknown how human neurons respond to intracranial stimulation. We address this question at a basic level by characterizing neuronal cell-type specific firing rate responses to single pulses of electrical stimulation of the human brain. We carried out broadly distributed stimulation in 30 patients undergoing neuromonitoring for epilepsy while recording from isolated neurons on microwires implanted into the medial temporal and frontal lobes. Out of a total of 228 recorded units, 16.2% (N = 191) were classified as interneurons and 83.8% (N = 37) were classified as principal cells, using a threshold clustering method, based on intrinsic waveshape characteristics. To see how stimulation affected neuronal activation for each cell type, we calculated firing rate change between a pre-stimulation and post-stimulation window and observed that 174 units were significantly modulated with the vast majority (91%) showing firing rate suppression. We then characterized stimulation-evoked changes in firing rate to gain insight into cell type-specific responses. Additionally, in a subset of the units, we observed that firing rate responses were modulated by stimulation distance, where local stimulation (within approximately 40 mm) could evoke instantaneous firing, whereas distant stimulation reliably suppressed firing in the same units. Finally, we analyzed a subset of units within the seizure onset zone, which exhibited unique waveform features and responses to stimulation. This study bridges a gap in the neuromodulation field by examining the single-unit firing rate response to direct electrical stimulation of the human brain and analyzing cell-type specific firing rate responses. We show that low frequency, single-pulse stimulation broadly elicits firing rate suppression, but parameters, such as distance from the unit, can have diverse effects on firing rate responses. This work informs the neuronal basis of CCEP generation and therefore has implications for clinical mapping and informs novel active probing strategies for precision diagnosis and neuromodulation of seizure pathophysiology in surgical cases. Moreover, this research has general implications for understanding neuromodulation via direct brain stimulation. Highlights- Putative principal cell waveform shapes are characterized by longer trough-to-peak and full-width half max durations (s) compared to interneurons. - Monopolar stimulation @ 3 mA generally has a widespread suppressive effect on neuronal firing, lasting approximately 1.5 s. - Principal cells show greater suppression amplitude and longer suppression durations than interneurons. - Stimulation within [~] 40 mm is capable of evoking instantaneous firing, despite general suppression from stimulation at greater distances.

neuroscience↗

bioRxiv2024

Human single-neuron activity is modulated by intracranial theta burst stimulation of the basolateral amygdala

Direct electrical stimulation of the human brain has been used for numerous clinical and scientific applications. At present, however, little is known about how intracranial stimulation affects activity at the microscale. In this study, we recorded intracranial EEG data from a cohort of patients with medically refractory epilepsy as they completed a visual recognition memory task. During the memory task, brief trains of intracranial theta burst stimulation (TBS) were delivered to the basolateral amygdala (BLA). Using simultaneous microelectrode recordings, we isolated neurons in the hippocampus, amygdala, orbitofrontal cortex, and anterior cingulate cortex and tested whether stimulation enhanced or suppressed firing rates. Additionally, we characterized the properties of modulated neurons, clustered presumed excitatory and inhibitory neurons by waveform morphology, and examined the extent to which modulation affected memory task performance. We observed a subset of neurons ([~]30%) whose firing rate was modulated by TBS, exhibiting highly heterogeneous responses with respect to onset latency, duration, and direction of effect. Notably, location and baseline activity predicted which neurons were most susceptible to modulation, although the impact of this neuronal modulation on memory remains unclear. These findings advance our limited understanding of how focal electrical fields influence neuronal firing at the single-cell level. HighlightsIndividual neurons in the human brain were responsive to theta burst stimulation Basolateral amygdala stimulation preferentially modulated neurons in the hippocampus, orbitofrontal cortex, and amygdala Excitatory and inhibitory neurons were modulated equally Neurons modulated by stimulation tended to have greater baseline firing rates Duration, onset, and valence of neuronal modulation were heterogeneous

neuroscience↗

bioRxiv2024

More widespread and rigid neuronal representation of reward expectation underlies impulsive choices

Impulsive choices prioritize smaller, more immediate rewards over larger, delayed, or potentially uncertain rewards. Impulsive choices are a critical aspect of substance use disorders and maladaptive decision-making across the lifespan. Here, we sought to understand the neuronal underpinnings of expected reward and risk estimation on a trial-by-trial basis during impulsive choices. To do so, we acquired electrical recordings from the human brain while participants carried out a risky decision-making task designed to measure choice impulsivity. Behaviorally, we found a reward-accuracy tradeoff, whereby more impulsive choosers were more accurate at the task, opting for a more immediate reward while compromising overall task performance. We then examined how neuronal populations across frontal, temporal, and limbic brain regions parametrically encoded reinforcement learning model variables, namely reward and risk expectation and surprise, across trials. We found more widespread representations of reward value expectation and prediction error in more impulsive choosers, whereas less impulsive choosers preferentially represented risk expectation. A regional analysis of reward and risk encoding highlighted the anterior cingulate cortex for value expectation, the anterior insula for risk expectation and surprise, and distinct regional encoding between impulsivity groups. Beyond describing trial-by-trial population neuronal representations of reward and risk variables, these results suggest impaired inhibitory control and model-free learning underpinnings of impulsive choice. These findings shed light on neural processes underlying reinforced learning and decision-making in uncertain environments and how these processes may function in psychiatric disorders.

neuroscience↗

bioRxiv2024

Comparative specialization of intrinsic cardiac neurons in humans, mice, and pigs

Intrinsic cardiac neurons (ICNs) play a crucial role in the proper functioning of the heart; yet a paucity of data pertaining to human ICNs exists. We took a multidisciplinary approach to complete a detailed cellular comparison of the structure and function of ICNs from mice, pigs, and humans. Immunohistochemistry of whole and sectioned ganglia, transmission electron microscopy, intracellular microelectrode recording and dye filling for quantitative morphometry were used to define the neurophysiology, histochemistry, and ultrastructure of these cells across species. The densely packed, smaller ICNs of mouse lacked dendrites, formed axosomatic connections, and had high synaptic efficacy constituting an obligatory synapse. At Pig ICNs, a convergence of subthreshold cholinergic inputs onto extensive dendritic arbors supported greater summation and integration of synaptic input. Human ICNs were tonically firing, with synaptic stimulation evoking large suprathreshold excitatory postsynaptic potentials like mouse, and subthreshold potentials like pig. Ultrastructural examination of synaptic terminals revealed conserved architecture, yet small clear vesicles (SCVs) were larger in pigs and humans. The presence and localization of ganglionic neuropeptides was distinct, with abundant VIP observed in human but not pig or mouse ganglia, and little SP or CGRP in pig ganglia. Action potential waveforms were similar, but human ICNs had larger after-hyperpolarizations. Intrinsic excitability differed; 93% of human cells were tonic, all pig neurons were phasic, and both phasic and tonic phenotypes were observed in mouse. In combination, this publicly accessible, multimodal atlas of ICNs from mice, pigs, and humans identifies similarities and differences in the evolution of ICNs.

neuroscience↗

bioRxiv2023

Subsets of cortico-cortical evoked potentials propagate as traveling waves

Understanding the spatiotemporal dynamics of neural signal propagation is fundamental to unraveling the complexities of brain function. Emerging evidence suggests that cortico-cortical evoked potentials (CCEPs) resulting from single-pulse electrical stimulation may be used to characterize the patterns of information flow between and within brain networks. At present, the basic spatiotemporal dynamics of CCEP propagation cortically and subcortically are incompletely understood. We hypothesized that single-pulse electrical stimulation evokes neural traveling waves detectable in the three-dimensional space sampled by intracranial stereoelectroencephalography. Across a cohort of 21 adult patients with intractable epilepsy, we delivered 17,631 stimulation pulses and recorded CCEP responses in 1,019 electrode contacts. The distance between each pair of electrode contacts was approximated using three different metrics (Euclidean distance, path length, and geodesic distance), representing direct, tractographic, and transcortical propagation, respectively. For each robust CCEP, we extracted amplitude-, spectral-, and phase-based features to identify traveling waves emanating from the site of stimulation. Many evoked responses to stimulation appear to propagate as traveling waves ([~]14-28%), despite sparse sampling throughout the brain. These stimulation-evoked traveling waves exhibited biologically plausible propagation velocities (range 0.1-9.6 m/s). Our results reveal that direct electrical stimulation elicits neural activity with variable spatiotemporal dynamics, including the initiation of neural traveling waves. Significance StatementUsing single-pulse stimulation, we identify a subset of intracranial evoked potentials that propagate as neural traveling waves. Our results were robust across a range of distinct but complementary analysis methods. The identification of stimulation-evoked traveling waves may help to better characterize the pathways traversed by spontaneous, pathological, or task-evoked traveling waves and distinguish biologically plausible propagation from volume-conducted signals.

neuroscience↗

bioRxiv2023

Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings

Pain is a complex experience involving sensory, emotional, and cognitive aspects, and multiple networks manage its processing in the brain. Examining how pain transforms into a behavioral response can shed light on the networks relationships and facilitate interventions to treat chronic pain. However, studies using high spatial and temporal resolution methods to investigate the neural encoding of pain and its psychophysical correlates have been limited. We recorded from intracranial stereo-EEG (sEEG) electrodes implanted in sixteen different brain regions of twenty patients who underwent psychophysical pain testing consisting of a tonic thermal stimulus to the hand. Broadband high-frequency local field potential amplitude (HFA; 70-150 Hz) was isolated to investigate the relationship between the ongoing neural activity and the resulting psychophysical pain evaluations. Two different generalized linear mixed-effects models (GLME) were employed to assess the neural representations underlying binary and graded pain psychophysics. The first model examined the relationship between HFA and whether the patient responded "yes" or "no" to whether the trial was painful. The second model investigated the relationship between HFA and how painful the stimulus was rated on a visual analog scale. GLMEs revealed that HFA in the inferior temporal gyrus (ITG), superior frontal gyrus (SFG), and superior temporal gyrus (STG) predicted painful responses at stimulus onset. An increase in HFA in the orbitofrontal cortex (OFC), SFG, and striatum predicted pain responses at stimulus offset. Numerous regions including the anterior cingulate cortex, hippocampus, IFG, MTG, OFC, and striatum, predicted the pain rating at stimulus onset. However, only the amygdala and fusiform gyrus predicted increased pain ratings at stimulus offset. We characterized the spatiotemporal representations of binary and graded painful responses during tonic pain stimuli. Our study provides evidence from intracranial recordings that the neural encoding of psychophysical pain changes over time during a tonic thermal stimulus, with different brain regions being predictive of pain at the beginning and end of the stimulus. Significance StatementWe investigated the neural encoding of pain psychophysics across 16 brain regions during a continuous thermal stimulus in humans. Mixed-effects models were used to analyze trends across 20 human subjects. Using intracranial electrodes, we show a parametric relationship between behavioral responses and HFA during ongoing pain. We found that HFA in cognitive and emotional pain processing regions was closely associated with pain evaluation at the stimulus onset, end, or both. The neural encoding of subjective pain intensity, measured by a visual analog scale, differed from that of binary pain intensity. Perception and psychophysical correlates to pain depend on how patients are asked to evaluate it. Our findings provide evidence that HFA can serve as a neural marker within specific brain regions of behavioral pain responses, as measured by sEEG.

neuroscience↗

bioRxiv2021

The Spatial Reach of Neuronal Coherence and Spike-field Coupling across the Human Neocortex

Neuronal coherence is thought to be a fundamental mechanism of communication in the brain, where synchronized field potentials coordinate synaptic and spiking events to support plasticity and learning. Although the spread of field potentials has garnered great interest, little is known about the spatial reach of phase synchronization, or neuronal coherence. Functional connectivity between different brain regions is known to occur across long distances, but the locality of coherence within a brain region is understudied. Here we used simultaneous recordings from electrocorticography (ECoG) grids and high-density microelectrode arrays to estimate the spatial reach of neuronal coherence and spike-field coherence (SFC) across frontal, temporal, and occipital cortices during cognitive tasks in humans. We observed the strongest coherence within a 2-3 cm distance from the microelectrode arrays, potentially defining an effective range for local communication. This range was relatively consistent across brain regions, spectral frequencies, and cognitive tasks. The magnitude of coherence showed power law decay with increasing distance from the microelectrode arrays, where the highest coherence occurred between ECoG contacts, followed by coherence between ECoG and deep cortical LFP, and then SFC (i.e., ECoG > LFP > SFC). The spectral frequency of coherence also affected its magnitude. Alpha coherence (8-14 Hz) was generally higher than other frequencies for signals nearest the microelectrode arrays, whereas delta coherence (1-3 Hz) was higher for signals that were farther away. Action potentials in all brain regions were most coherent with the phase of alpha oscillations, which suggests that alpha waves could play a larger, more spatially local role in spike timing than other frequencies. These findings provide a deeper understanding of the spatial and spectral dynamics of neuronal coherence, further advancing knowledge about how activity propagates across the human brain.

neuroscience↗

bioRxiv2021

Human interictal epileptiform discharges are traveling waves reflecting ictal self-organization

Interictal epileptiform discharges (IEDs), also known as interictal spikes, are large intermittent electrophysiological events observed between seizures in patients with epilepsy. Though they occur far more often than seizures, IEDs are less studied, and their relationship to seizures remains unclear. To better understand this relationship, we examined multi-day recordings of microelectrode arrays implanted in human epilepsy patients, allowing us to precisely observe the spatiotemporal propagation of IEDs, spontaneous seizures, and how they relate. These recordings showed that the majority of IEDs are traveling waves, traversing the same path as ictal discharges during seizures, and with a fixed direction relative to seizure propagation. Moreover, the majority of IEDs, like ictal discharges, were bidirectional, with one predominant and a second, less frequent antipodal direction. These results reveal a fundamental spatiotemporal similarity between IEDs and ictal discharges. These results also imply that most IEDs arise in brain tissue outside the site of seizure onset and propagate toward it, indicating that the propagation of IEDs provides useful information for localizing the seizure focus.

neuroscience↗

bioRxiv2020

Innervation and Neuronal Control of the Mammalian Sinoatrial Node: A Comprehensive Atlas

Cardiac function is under exquisite intrinsic cardiac neural control. Neuroablative techniques to modulate control of cardiac function are currently being studied in patients, albeit with variable and sometimes deleterious results. Recognizing the major gaps in our understanding of cardiac neural control, we sought to evaluate neural regulation of impulse initiation in the sinoatrial node as an initial discovery step. Here, we report an in-depth, multi-scale structural and functional characterization of the innervation of the sinoatrial node (SAN) by the right atrial ganglionated plexus (RAGP) in porcine and human hearts. Combining intersectional strategies including tissue clearing, immunohistochemical and ultrastructural techniques, we have delineated a comprehensive neuroanatomic atlas of the RAGP-SAN complex. The RAGP shows significant phenotypic diversity of neurons while maintaining predominant cholinergic innervation. Cellular and tissue-level electrophysiologic mapping and ablation studies demonstrate interconnected ganglia with synaptic convergence within the RAGP to modulate SAN automaticity, atrioventricular (AV) conduction and left ventricular (LV) contractility. For the first time, we demonstrate that intrinsic cardiac neurons influence the pacemaking site in the heart. This provides an experimental demonstration of a discrete neuronal population controlling a specific geographic region of the heart (SAN) that can serve as a framework for further exploration of other parts of the intrinsic cardiac nervous system (ICNS) in mammalian hearts and for developing targeted therapies.

neuroscience↗