Biology subjects

Stephen, E. P.

Publications and source records attributed to Stephen, E. P..

9 recordsLinked to original sources

bioRxiv2026

Spectral decompositions of neural voltage recordings are susceptible to model misspecifications that cause meaningful estimation error

The power spectra of neural voltage recordings vary systematically across brain states and contain both narrowband (rhythmic) and broadband components. A large class of algorithms seeks to parametrize these spectra by separating rhythms from broadband structure, enabling many robust empirical findings. Here we show that two common assumptions underlying popular spectral decomposition methods are incompatible with standard physical and statistical properties of neural recordings: (1) field potentials arise from additive (linear) superposition of biophysical processes, yet several methods implicitly impose multiplicative structure; (2) power estimates are Gamma distributed, with variance proportional to squared power (heteroscedasticity), yet many methods assume Gaussian, homoscedastic errors across frequencies. Using simulations with known ground truth, we demonstrate how these misspecifications bias estimates of rhythm amplitude and broadband height/slope, even under well-behaved conditions. We introduce a corrected decomposition framework, released as the open-source package SL_specdecomp. Relative to the most widely used method, specparam, our approach recovers rhythms and broadband parameters accurately, while specparam decompositions are biased and can confound rhythmic peaks with broadband slope. We then apply these methods to monkey electrocorticography during propofol anesthesia. SL_specdecomp estimates a substantially steeper (more negative) 40-60 Hz broadband slope during anesthesia than during wakefulness, whereas specparam shows a smaller state difference. We show using simulation that the differences in the two decompositions can arise directly from specparams model misspecification. We also introduce a formal method based on cross-validated log likelihood to compare candidate power spectral decompositions and show that it favors SL_specdecomp. These results suggest that misspecified decompositions can attenuate or distort broadband slope changes in the presence of strong rhythms, and motivate the use of SL_specdecomp as a more reliable decomposition tool.

neuroscience↗

bioRxiv2024

Filtered Point Processes Tractably Capture Rhythmic And Broadband Power Spectral Structure in Neural Electrophysiological Recordings

AO_SCPLOWBSTRACTC_SCPLOWNeural electrophysiological recordings arise from interacting rhythmic (oscillatory) and broadband (aperiodic) biological subprocesses. Both rhythmic and broadband processes contribute to the neural power spectrum, which decomposes the variance of a neural recording across frequencies. Although an extensive body of literature has successfully studied rhythms in various diseases and brain states, researchers only recently have systematically studied the characteristics of broadband effects in the power spectrum. Broadband effects can generally be categorized as 1) shifts in power across all frequencies, which correlate with changes in local firing rates and 2) changes in the overall shape of the power spectrum, such as the spectral slope or power law exponent. Shape changes are evident in various conditions and brain states, influenced by factors such as excitation to inhibition balance, age, and various diseases. It is increasingly recognized that broadband and rhythmic effects can interact on a sub-second timescale. For example, broadband power is time-locked to the phase of <1 Hz rhythms in propofol induced unconsciousness. Modeling tools that explicitly deal with both rhythmic and broadband contributors to the power spectrum and that capture their interactions are essential to help improve the interpretability of power spectral effects. Here, we introduce a tractable stochastic forward modeling framework designed to capture both narrowband and broadband spectral effects when prior knowledge or theory about the primary biophysical processes involved is available. Population-level neural recordings are modeled as the sum of filtered point processes (FPPs), each representing the contribution of a different biophysical process such as action potentials or postsynaptic potentials of different types. Our approach builds on prior neuroscience FPP work by allowing multiple interacting processes and time-varying firing rates and by deriving theoretical power spectra and cross-spectra. We demonstrate several properties of the models, including that they divide the power spectrum into frequency ranges dominated by rhythmic and broadband effects, and that they can capture spectral effects across multiple timescales, including sub-second cross-frequency coupling. The framework can be used to interpret empirically observed power spectra and cross-frequency coupling effects in biophysical terms, which bridges the gap between theoretical models and experimental results.

neuroscience↗

bioRxiv2024

Neurovascular Impulse Response Function (IRF) during spontaneous activity differentially reflects intrinsic neuromodulation across cortical regions

Ascending neuromodulatory projections from deep brain nuclei generate internal brain states that differentially engage specific neuronal cell types. Because neurovascular coupling is cell-type specific and neuromodulatory transmitters have vasoactive properties, we hypothesized that the impulse response function (IRF) linking spontaneous neuronal activity with hemodynamics would depend on neuromodulation. To test this hypothesis, we used optical imaging to measure (1) release of neuromodulatory transmitters norepinephrine (NE) or acetylcholine (ACh), (2) Ca2+ activity of local cortical neurons, and (3) changes in hemoglobin concentration and oxygenation across the dorsal surface of cerebral cortex during spontaneous neuronal activity in awake mice. A canonical convolution model with a global, stationary IRF (i.e., the convolution kernel) describing evolution of total hemoglobin (HbT, reflective of dilation dynamics) with respect to Ca2+, resulted in a poor fit to the data. However, the HbT time-course was well predicted, pixel-by-pixel, by a weighted sum of Ca2+ and NE time-courses. Consistent with this result, modeling HbT as a weighted sum of stationary Ca2+ - and NE-specific IRFs (IRFCa2+ and IRFNE) convolved with the respective time-courses dramatically improved the fit compared to the global IRF. IRFCa2+ and IRFNE, estimated from the data, were positive and negative, respectively. In contrast to NE, ACh was largely redundant with Ca2+ and therefore did not improve HbT estimation. Because NE covaried with arousal, we observed instances of the diminished hemodynamic coherence between cortical regions during high arousal despite coherent behavior of the underlying neuronal Ca2+ activity. We conclude that while neurovascular coupling with respect to neuronal Ca2+ is a dynamic and seemingly complex phenomenon, hemodynamic fluctuations can be captured by a simple linear model with stationary IRFs with respect to the underlying dilatory and constrictive forces. In the current study, these forces were captured by the positive IRFCa2+ (dilation) and negative IRFNE (constriction). Without accounting for NE neuromodulation and the associated vasoconstriction, diminished hemodynamic coherence, commonly referred to as "functional (dys)connectivity" in BOLD fMRI studies, can be falsely interpreted as neuronal desynchronizations.

neuroscience↗

bioRxiv2024

Spike-wave discharges during low-current thalamic deep brain stimulation in mice

BackgroundDeep brain stimulation of central thalamus (CT-DBS) has potential for modulating states of consciousness, but it can also trigger spike-wave discharges (SWDs). ObjectivesTo report the probability of inducing SWDs during CT-DBS in awake mice. MethodsMice were implanted with electrodes to deliver unilateral and bilateral CT-DBS at different frequencies while recording EEG. We titrated stimulation current by gradually increasing it at each frequency until an SWD appeared. Subsequent stimulations to test arousal modulation were performed at the current one step below the current that caused an SWD during titration. ResultsIn 2.21% of the test stimulations (10 out of 12 mice), CT-DBS caused SWDs at currents lower than the titrated current, at currents as low as 20 A. ConclusionOur study found a small but significant probability of inducing SWDs even after titration and at relatively low currents. EEG should be closely monitored for SWDs when performing CT-DBS in both research and clinical settings.

neuroscience↗

bioRxiv2023

Propofol Mediated Unconsciousness Disrupts Progression of Sensory Signals through the Cortical Hierarchy

A critical component of anesthesia is the loss sensory perception. Propofol is the most widely used drug for general anesthesia, but the neural mechanisms of how and when it disrupts sensory processing are not fully understood. We analyzed local field potential (LFP) and spiking recorded from Utah arrays in auditory cortex, associative cortex, and cognitive cortex of non-human primates before and during propofol mediated unconsciousness. Sensory stimuli elicited robust and decodable stimulus responses and triggered periods of stimulus-induced coherence between brain areas in the LFP of awake animals. By contrast, propofol mediated unconsciousness eliminated stimulus-induced coherence and drastically weakened stimulus responses and information in all brain areas except for auditory cortex, where responses and information persisted. However, we found stimuli occurring during spiking Up states triggered weaker spiking responses than in awake animals in auditory cortex, and little or no spiking responses in higher order areas. These results suggest that propofols effect on sensory processing is not just due to asynchronous down states. Rather, both Down states and Up states reflect disrupted dynamics.

neuroscience↗

bioRxiv2022

Propofol disrupts alpha dynamics in distinct thalamocortical networks underlying sensory and cognitive function during loss of consciousness

During propofol-induced general anesthesia, alpha rhythms undergo a striking shift from posterior to anterior, termed anteriorization. We combined human intracranial recordings with diffusion imaging to show that anteriorization occurs with opposing dynamics in two distinct thalamocortical subnetworks. The cortical and thalamic anatomy involved, as well as their known functional roles, suggest multiple means by which propofol dismantles sensory and cognitive processes to achieve loss of consciousness.

neuroscience↗

bioRxiv2021

Latent neural dynamics encode temporal context in speech

Direct neural recordings from human auditory cortex have demonstrated encoding for acoustic-phonetic features of consonants and vowels. Neural responses also encode distinct acoustic amplitude cues related to timing, such as those that occur at the onset of a sentence after a silent period or the onset of the vowel in each syllable. Here, we used a group reduced rank regression model to show that distributed cortical responses support a low-dimensional latent state representation of temporal context in speech. The timing cues each capture more unique variance than all other phonetic features and exhibit rotational or cyclical dynamics in latent space from activity that is widespread over the superior temporal gyrus. We propose that these spatially distributed timing signals could serve to provide temporal context for, and possibly bind across time, the concurrent processing of individual phonetic features, to compose higher-order phonological (e.g. word-level) representations.

neuroscience↗

bioRxiv2019

State Space Methods for Phase Amplitude Coupling Analysis

Phase Amplitude Coupling (PAC) is thought to play a fundamental role in the dynamic coordination of brain circuits and systems. There are however growing concerns that existing methods for PAC analysis are prone to error and misinterpretation. Improper frequency band selection can render true PAC undetectable, while non-linearities or abrupt changes in the signal can produce spurious PAC. Current methods require substantial amounts of data and lack formal statistical inference tools. We describe here a novel approach for PAC analysis that substantially addresses these problems. We use a state space model to estimate the component oscillations, avoiding problems with frequency band selection, nonlinearities, and sharp signal transitions. We represent cross-frequency coupling in parametric and time-varying forms to further improve statistical efficiency and estimate the posterior distribution of the coupling parameters to derive their credible intervals. We demonstrate the method using simulated data, rat LFP data, and human EEG data.

neuroscience↗

bioRxiv2019

Broadband slow-wave modulation in posterior and anterior cortex tracks distinct states of propofol-induced unconsciousness

A controversy 5 has developed in recent years over the role that frontal and posterior cortices play in mediating consciousness and unconsciousness. One hypothesis proposes that posterior sensory and association cortices are the principal mediators of consciousness, citing evidence that strong slow-wave activity over posterior cortex during sleep disrupts the contents of dreaming. A competing hypothesis proposes that frontal-posterior interactions are critical to ignite a conscious percept, since activation of frontal cortex appears necessary for perception and can reverse unconsciousness under anesthesia. In both cases, EEG slow-waves (< 1 Hz) are considered evidence that up- and down-states are disrupting cortical activity necessary for consciousness. Here, we used anesthesia to study the interaction between the slow-wave and higher frequency activity in humans. If slow-waves are derived from underlying up and down-states, then they should modulate activity across a broad range of frequencies. We found that this broadband slow-wave modulation does occur: broadband slow-wave modulation occurs over posterior cortex when subjects initially become unconscious, but later encompasses both frontal and posterior cortex when subjects are more deeply anesthetized and likely unarousable. Based on these results, we argue that unconsciousness under anesthesia comprises several shifts in brain state that disrupt the sensory contents of consciousness distinct from arousal and awareness of those contents.\n\nSignificance StatementThe roles of frontal and posterior cortices in mediating consciousness and unconsciousness are controversial. Disruption of posterior cortex during sleep appears to suppress the contents of dreaming, yet activation of frontal cortex appears necessary for perception and can reverse unconsciousness under anesthesia. We studied the time course of regional cortical disruption, as mediated by slow-wave modulation of broadband activity, during anesthesia-induced unconsciousness in humans. We found that broadband slow-wave modulation covered posterior cortex when subjects initially became unconscious, but later encompassed both frontal and posterior cortex when subjects were deeply anesthetized and likely unarousable. This suggests that unconsciousness under anesthesia comprises several shifts in brain state that disrupt the contents of consciousness distinct from arousal and awareness of those contents.

neuroscience↗