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  • A dynamic generative model can extract interpretable oscillatory components from multichannel neurophysiological recordings. bioRxiv : the preprint server for biology Das, P., He, M., Purdon, P. L. 2024


    Modern neurophysiological recordings are performed using multichannel sensor arrays that are able to record activity in an increasingly high number of channels numbering in the 100's to 1000's. Often, underlying lower-dimensional patterns of activity are responsible for the observed dynamics, but these representations are difficult to reliably identify using existing methods that attempt to summarize multivariate relationships in a post-hoc manner from univariate analyses, or using current blind source separation methods. While such methods can reveal appealing patterns of activity, determining the number of components to include, assessing their statistical significance, and interpreting them requires extensive manual intervention and subjective judgement in practice. These difficulties with component selection and interpretation occur in large part because these methods lack a generative model for the underlying spatio-temporal dynamics. Here we describe a novel component analysis method anchored by a generative model where each source is described by a bio-physically inspired state space representation. The parameters governing this representation readily capture the oscillatory temporal dynamics of the components, so we refer to it as Oscillation Component Analysis (OCA). These parameters - the oscillatory properties, the component mixing weights at the sensors, and the number of oscillations - all are inferred in a data-driven fashion within a Bayesian framework employing an instance of the expectation maximization algorithm. We analyze high-dimensional electroencephalography and magnetoencephalography recordings from human studies to illustrate the potential utility of this method for neuroscience data.

    View details for DOI 10.1101/2023.07.26.550594

    View details for PubMedID 37546851

    View details for PubMedCentralID PMC10402019

  • Age-Dependent Electroencephalogram Features in Infants Under Spinal Anesthesia Appear to Mirror Physiologic Sleep in the Developing Brain: A Prospective Observational Study ANESTHESIA AND ANALGESIA Santa Cruz Mercado, L. A., Lee, J. M., Liu, R., Deng, H., Johnson, J. J., Chen, A. L., He, M., Chung, E. R., Bharadwaj, K. M., Houle, T. T., Purdon, P. L., Liu, C. A. 2023; 137 (6): 1241-1249


    Infants under spinal anesthesia appear to be sedated despite the absence of systemic sedative medications. In this prospective observational study, we investigated the electroencephalogram (EEG) of infants under spinal anesthesia and hypothesized that we would observe EEG features similar to those seen during sleep.We computed the EEG power spectra and spectrograms of 34 infants undergoing infraumbilical surgeries under spinal anesthesia (median age 11.5 weeks postmenstrual age, range 38-65 weeks postmenstrual age). Spectrograms were visually scored for episodes of EEG discontinuity or spindle activity. We characterized the relationship between EEG discontinuity or spindles and gestational age, postmenstrual age, or chronological age using logistic regression analyses.The predominant EEG patterns observed in infants under spinal anesthesia were slow oscillations, spindles, and EEG discontinuities. The presence of spindles, observed starting at about 49 weeks postmenstrual age, was best described by postmenstrual age ( P =.002) and was more likely with increasing postmenstrual age. The presence of EEG discontinuities, best described by gestational age ( P = .015), was more likely with decreasing gestational age. These age-related changes in the presence of spindles and EEG discontinuities in infants under spinal anesthesia generally corresponded to developmental changes in the sleep EEG.This work illustrates 2 separate key age-dependent transitions in EEG dynamics during infant spinal anesthesia that may reflect the maturation of underlying brain circuits: (1) diminishing discontinuities with increasing gestational age and (2) the appearance of spindles with increasing postmenstrual age. The similarity of these age-dependent transitions under spinal anesthesia with transitions in the developing brain during physiological sleep supports a sleep-related mechanism for the apparent sedation observed during infant spinal anesthesia.

    View details for DOI 10.1213/ANE.0000000000006410

    View details for Web of Science ID 001112889200007

    View details for PubMedID 36881544

  • Effects of Aging on Externally Cued and Internally Driven Uncertainty Representations NEUROPSYCHOLOGY Korthauer, L. E., Festa, E. K., Gemelli, Z. T., He, M., Heindel, W. C. 2024; 38 (3): 249-258


    The Hick-Hyman law states that response time (RT) increases linearly with increasing information uncertainty. The effects of aging on uncertainty representations in choice RT paradigms remain unclear, including whether aging differentially affects processes mediating externally cued versus internally driven uncertainty. This study sought to characterize age-related differences in uncertainty representations using a card-sorting task.The task separately manipulated internally driven uncertainty (i.e., probability of each stimulus type with fixed number of response piles) and externally cued uncertainty (i.e., number of response piles with fixed probability of each stimulus type).Older adults (OA) showed greater RT slowing than younger adults in response to uncertainty load, an effect that was stronger in the externally cued than internally driven condition. While both age groups showed lower accuracy and greater RTs in response to unexpected (surprising) stimuli in the internally driven condition at low uncertainty loads, OA were unable to distinguish between expected and nonexpected stimuli at higher uncertainty loads when the probability of each stimulus type was close to equal. Among OA, better performance on the internally driven, but not externally cued, condition was associated with better global cognitive performance and verbal fluency.Collectively, these findings provide behavioral evidence of age-related disruptions to bottom-up (externally cued) and top-down (supporting internally driven mental representations) resources to process uncertainty and coordinate task-relevant action. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

    View details for DOI 10.1037/neu0000936

    View details for Web of Science ID 001108485800001

    View details for PubMedID 37917436

  • Pupil size tracks cue-trace interactions during episodic memory retrieval PSYCHOPHYSIOLOGY Siefert, E. M., He, M., Festa, E. K., Heindel, W. C. 2024; 61 (1): e14409


    Our ability to remember past events requires not only storing enduring engrams or memory traces of these events, but also successfully reactivating these latent traces in response to appropriate cues at the time of retrieval-a process that has been termed ecphory. However, relatively little is known about the processes that facilitate the dynamic interactions between retrieval cues and stored memory traces that are critical for successful recognition and recollection. Recently, an intriguing link between pupil dilation and recognition memory has been identified, with studied items eliciting greater pupil dilation than unstudied items during retrieval. However, the processes contributing to this "pupillary old/new effect" remain unresolved, with current explanations suggesting that it reflects the strength of the underlying memory trace. Here, we explore the novel hypothesis that the pupillary old/new effect does not index memory strength alone, but rather reflects the facilitation of cue-trace interactions during episodic memory retrieval that may be supported by activity within the pupil-linked locus coeruleus-noradrenergic (LC-NA) arousal system. First, we show that the magnitude of pupil dilation is influenced by the degree of overlap between cue and trace information. Second, we find that the magnitude of pupil dilation reflects the amount of study contextual information reinstated during retrieval. These findings provide a novel framework for understanding the pupillary old/new effect, and identify a potential role for the LC-NA system in recognition memory retrieval.

    View details for DOI 10.1111/psyp.14409

    View details for Web of Science ID 001046576400001

    View details for PubMedID 37571917

  • Switching state-space modeling of neural signal dynamics. PLoS computational biology He, M., Das, P., Hotan, G., Purdon, P. L. 2023; 19 (8): e1011395


    Linear parametric state-space models are a ubiquitous tool for analyzing neural time series data, providing a way to characterize the underlying brain dynamics with much greater statistical efficiency than non-parametric data analysis approaches. However, neural time series data are frequently time-varying, exhibiting rapid changes in dynamics, with transient activity that is often the key feature of interest in the data. Stationary methods can be adapted to time-varying scenarios by employing fixed-duration windows under an assumption of quasi-stationarity. But time-varying dynamics can be explicitly modeled by switching state-space models, i.e., by using a pool of state-space models with different dynamics selected by a probabilistic switching process. Unfortunately, exact solutions for state inference and parameter learning with switching state-space models are intractable. Here we revisit a switching state-space model inference approach first proposed by Ghahramani and Hinton. We provide explicit derivations for solving the inference problem iteratively after applying a variational approximation on the joint posterior of the hidden states and the switching process. We introduce a novel initialization procedure using an efficient leave-one-out strategy to compare among candidate models, which significantly improves performance compared to the existing method that relies on deterministic annealing. We then utilize this state inference solution within a generalized expectation-maximization algorithm to estimate model parameters of the switching process and the linear state-space models with dynamics potentially shared among candidate models. We perform extensive simulations under different settings to benchmark performance against existing switching inference methods and further validate the robustness of our switching inference solution outside the generative switching model class. Finally, we demonstrate the utility of our method for sleep spindle detection in real recordings, showing how switching state-space models can be used to detect and extract transient spindles from human sleep electroencephalograms in an unsupervised manner.

    View details for DOI 10.1371/journal.pcbi.1011395

    View details for PubMedID 37639391

    View details for PubMedCentralID PMC10491408

  • Age-related differences in prefrontal glutamate are associated with increased working memory decay that gives the appearance of learning deficits. eLife Rmus, M., He, M., Baribault, B., Walsh, E. G., Festa, E. K., Collins, A. G., Nassar, M. R. 2023; 12


    The ability to use past experience to effectively guide decision-making declines in older adulthood. Such declines have been theorized to emerge from either impairments of striatal reinforcement learning systems (RL) or impairments of recurrent networks in prefrontal and parietal cortex that support working memory (WM). Distinguishing between these hypotheses has been challenging because either RL or WM could be used to facilitate successful decision-making in typical laboratory tasks. Here we investigated the neurocomputational correlates of age-related decision-making deficits using an RL-WM task to disentangle these mechanisms, a computational model to quantify them, and magnetic resonance spectroscopy to link them to their molecular bases. Our results reveal that task performance is worse in older age, in a manner best explained by working memory deficits, as might be expected if cortical recurrent networks were unable to sustain persistent activity across multiple trials. Consistent with this, we show that older adults had lower levels of prefrontal glutamate, the excitatory neurotransmitter thought to support persistent activity, compared to younger adults. Individuals with the lowest prefrontal glutamate levels displayed the greatest impairments in working memory after controlling for other anatomical and metabolic factors. Together, our results suggest that lower levels of prefrontal glutamate may contribute to failures of working memory systems and impaired decision-making in older adulthood.

    View details for DOI 10.7554/eLife.85243

    View details for PubMedID 37070807

  • Transient oscillation dynamics during sleep provide a robust basis for electroencephalographic phenotyping and biomarker identification SLEEP Stokes, P. A., Rath, P., Possidente, T., He, M., Purcell, S., Manoach, D. S., Stickgold, R., Prerau, M. J. 2023; 46 (1)


    Transient oscillatory events in the sleep electroencephalogram represent short-term coordinated network activity. Of particular importance, sleep spindles are transient oscillatory events associated with memory consolidation, which are altered in aging and in several psychiatric and neurodegenerative disorders. Spindle identification, however, currently contains implicit assumptions derived from what waveforms were historically easiest to discern by eye, and has recently been shown to select only a high-amplitude subset of transient events. Moreover, spindle activity is typically averaged across a sleep stage, collapsing continuous dynamics into discrete states. What information can be gained by expanding our view of transient oscillatory events and their dynamics? In this paper, we develop a novel approach to electroencephalographic phenotyping, characterizing a generalized class of transient time-frequency events across a wide frequency range using continuous dynamics. We demonstrate that the complex temporal evolution of transient events during sleep is highly stereotyped when viewed as a function of slow oscillation power (an objective, continuous metric of depth-of-sleep) and phase (a correlate of cortical up/down states). This two-fold power-phase representation has large intersubject variability-even within healthy controls-yet strong night-to-night stability for individuals, suggesting a robust basis for phenotyping. As a clinical application, we then analyze patients with schizophrenia, confirming established spindle (12-15 Hz) deficits as well as identifying novel differences in transient non-rapid eye movement events in low-alpha (7-10 Hz) and theta (4-6 Hz) ranges. Overall, these results offer an expanded view of transient activity, describing a broad class of events with properties varying continuously across spatial, temporal, and phase-coupling dimensions.

    View details for DOI 10.1093/sleep/zsac223

    View details for Web of Science ID 000874337300001

    View details for PubMedID 36107467

    View details for PubMedCentralID PMC9832519

  • Time perception in film is modulated by sensory modality and arousal ATTENTION PERCEPTION & PSYCHOPHYSICS Appelqvist-Dalton, M., Wilmott, J. P., He, M., Simmons, A. 2022; 84 (3): 926-942


    Considerable research has shown that the perception of time can be distorted subjectively, but little empirical work has examined what factors affect time perception in film, a naturalistic multimodal stimulus. Here, we explore the effect of sensory modality, arousal, and valence on how participants estimate durations in film. Using behavioral ratings combined with pupillometry in a within-participants design, we analyzed responses to and duration estimates of film clips in three experimental conditions: audiovisual (containing music and sound effects), visual (without music and sound effects), and auditory (music and sound effects without a visual scene). Participants viewed clips from little-known nature documentaries, fiction, animation, and experimental films. They were asked to judge clip duration and to report subjective arousal and valence, as their pupil sizes were recorded. Data were analyzed using linear mixed-effects models. Results reveal duration estimates varied between experimental conditions. Clip durations were judged to be shorter than actual durations in all three conditions, with visual-only clips perceived as longer (i.e., less distorted in time) than auditory-only and audiovisual clips. High levels of Composite Arousal (an average of self-reported arousal and pupil size changes) were correlated with longer (more accurate) estimates of duration, particularly in the audiovisual modality. This effect may reflect stimulus complexity or greater cognitive engagement. Increased ratings of valence were correlated with longer estimates of duration. The use of naturalistic, complex stimuli such as film can enhance our understanding of the psychology of time perception.

    View details for DOI 10.3758/s13414-022-02464-9

    View details for Web of Science ID 000770541100001

    View details for PubMedID 35304701

    View details for PubMedCentralID 5383908

  • Automatic segmentation of sleep spindles: A variational switching state-space approach He, M., Das, P., Hotan, G., Purdon, P. L., Matthews, M. B. IEEE. 2022: 1301-1305
  • Age-Related EEG Power Reductions Cannot Be Explained by Changes of the Conductivity Distribution in the Head Due to Brain Atrophy FRONTIERS IN AGING NEUROSCIENCE He, M., Liu, F., Nummenmaa, A., Hamalainen, M., Dickerson, B. C., Purdon, P. L. 2021; 13: 632310


    Electroencephalogram (EEG) power reductions in the aging brain have been described by numerous previous studies. However, the underlying mechanism for the observed brain signal power reduction remains unclear. One possible cause for reduced EEG signals in elderly subjects might be the increased distance from the primary neural electrical currents on the cortex to the scalp electrodes as the result of cortical atrophies. While brain shrinkage itself reflects age-related neurological changes, the effects of changes in the distribution of electrical conductivity are often not distinguished from altered neural activity when interpreting EEG power reductions. To address this ambiguity, we employed EEG forward models to investigate whether brain shrinkage is a major factor for the signal attenuation in the aging brain. We simulated brain shrinkage in spherical and realistic brain models and found that changes in the conductor geometry cannot fully account for the EEG power reductions even when the brain was shrunk to unrealistic sizes. Our results quantify the extent of power reductions from brain shrinkage and pave the way for more accurate inferences about deficient neural activity and circuit integrity based on EEG power reductions in the aging population.

    View details for DOI 10.3389/fnagi.2021.632310

    View details for Web of Science ID 000624934200001

    View details for PubMedID 33679380

    View details for PubMedCentralID PMC7929986

  • Age-related changes in the functional integrity of the phasic alerting system: a pupillometric investigation NEUROBIOLOGY OF AGING He, M., Heindel, W. C., Nassar, M. R., Siefert, E. M., Festa, E. K. 2020; 91: 136-147


    Enhanced processing following a warning cue is thought to be mediated by a phasic alerting response involving the locus coeruleus-noradrenergic (LC-NA) system. We examined the effect of aging on phasic alerting using pupil dilation as a marker of LC-NA activity in conjunction with a novel assessment of task-evoked pupil dilation. While both young and older adults displayed behavioral and pupillary alerting effects, reflected in decreased RT and increased pupillary response under high (tone) versus low (no tone) alerting conditions, older adults displayed a weaker pupillary response that benefited more from the alerting tone. The strong association between dilation and speed displayed by older adults in both alerting conditions was reduced in young adults in the high alerting condition, suggesting that in young (but not older) adults the tone conferred relatively little behavioral benefit beyond that provided by the alerting effect elicited by the target. These findings suggest a functioning but deficient LC-NA alerting system in older adults, and help reconcile previous results concerning the effects of aging on phasic alerting.

    View details for DOI 10.1016/j.neurobiolaging.2020.02.025

    View details for Web of Science ID 000534538900015

    View details for PubMedID 32224065

    View details for PubMedCentralID PMC7548963