Joel Frohlich
@ucla.edu
Postdoc, Monti Lab
University of California, Los Angeles
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Tim Bayne, Joel Frohlich, Rhodri Cusack, Julia Moser, and Lorina Naci
Elsevier BV
Conor H. Murray, Joel Frohlich, Connor J. Haggarty, Ilaria Tare, Royce Lee, and Harriet de Wit
Springer Science and Business Media LLC
Tim Bayne, Joel Frohlich, Rhodri Cusack, Julia Moser, and Lorina Naci
Elsevier BV
Joel Frohlich, Pedro A. M. Mediano, Francesco Bavato, and Alireza Gharabaghi
Springer Science and Business Media LLC
AbstractLow-frequency (<4 Hz) neural activity, particularly in the delta band, is generally indicative of loss of consciousness and cortical down states, particularly when it is diffuse and high amplitude. Remarkably, however, drug challenge studies of several diverse classes of pharmacological agents—including drugs which treat epilepsy, activate GABAB receptors, block acetylcholine receptors, or produce psychedelic effects—demonstrate neural activity resembling cortical down states even as the participants remain conscious. Of those substances that are safe to use in healthy volunteers, some may be highly valuable research tools for investigating which neural activity patterns are sufficient for consciousness or its absence.
Joel Frohlich, Tim Bayne, Julia S. Crone, Alessandra DallaVecchia, Asger Kirkeby-Hinrup, Pedro A.M. Mediano, Julia Moser, Karolina Talar, Alireza Gharabaghi, and Hubert Preissl
Elsevier BV
Joel Frohlich, Jeffrey N. Chiang, Pedro A. M. Mediano, Mark Nespeca, Vidya Saravanapandian, Daniel Toker, John Dell’Italia, Joerg F. Hipp, Shafali S. Jeste, Catherine J. Chu,et al.
Springer Science and Business Media LLC
Joel Frohlich, Jeffrey N. Chiang, Pedro A. M. Mediano, Mark Nespeca, Vidya Saravanapandian, Daniel Toker, John Dell’Italia, Joerg F. Hipp, Shafali S. Jeste, Catherine J. Chu,et al.
Springer Science and Business Media LLC
Joel Frohlich, Julia S. Crone, Pedro A. M. Mediano, Daniel Toker, and Daniel Bor
Frontiers Media SA
activity and conscious state: a key to
Joel Frohlich, Jeffrey N. Chiang, Pedro A. M. Mediano, Mark Nespeca, Vidya Saravanapandian, Daniel Toker, John Dell’Italia, Joerg F. Hipp, Shafali S. Jeste, Catherine J. Chu,et al.
Springer Science and Business Media LLC
AbstractWhat is the common denominator of consciousness across divergent regimes of cortical dynamics? Does consciousness show itself in decibels or in bits? To address these questions, we introduce a testbed for evaluating electroencephalogram (EEG) biomarkers of consciousness using dissociations between neural oscillations and consciousness caused by rare genetic disorders. Children with Angelman syndrome (AS) exhibit sleep-like neural dynamics during wakefulness. Conversely, children with duplication 15q11.2-13.1 syndrome (Dup15q) exhibit wake-like neural dynamics during non-rapid eye movement (NREM) sleep. To identify highly generalizable biomarkers of consciousness, we trained regularized logistic regression classifiers on EEG data from wakefulness and NREM sleep in children with AS using both entropy measures of neural complexity and spectral (i.e., neural oscillatory) EEG features. For each set of features, we then validated these classifiers using EEG from neurotypical (NT) children and abnormal EEGs from children with Dup15q. Our results show that the classification performance of entropy-based EEG biomarkers of conscious state is not upper-bounded by that of spectral EEG features, which are outperformed by entropy features. Entropy-based biomarkers of consciousness may thus be highly adaptable and should be investigated further in situations where spectral EEG features have shown limited success, such as detecting covert consciousness or anesthesia awareness.
Joel Frohlich, Julia S. Crone, Micah A. Johnson, Evan S. Lutkenhoff, Norman M. Spivak, John Dell'Italia, Joerg F. Hipp, Vikesh Shrestha, Jesús E. Ruiz Tejeda, Courtney Real,et al.
Wiley
Electroencephalography (EEG), easily deployed at the bedside, is an attractive modality for deriving quantitative biomarkers of prognosis and differential diagnosis in severe brain injury and disorders of consciousness (DOC). Prior work by Schiff has identified four dynamic regimes of progressive recovery of consciousness defined by the presence or absence of thalamically-driven EEG oscillations. These four predefined categories (ABCD model) relate, on a theoretical level, to thalamocortical integrity and, on an empirical level, to behavioral outcome in patients with cardiac arrest coma etiologies. However, whether this theory-based stratification of patients might be useful as a diagnostic biomarker in DOC and measurably linked to thalamocortical dysfunction remains unknown. In this work, we relate the reemergence of thalamically-driven EEG oscillations to behavioral recovery from traumatic brain injury (TBI) in a cohort of N = 38 acute patients with moderate-to-severe TBI and an average of 1 week of EEG recorded per patient. We analyzed an average of 3.4 hr of EEG per patient, sampled to coincide with 30-min periods of maximal behavioral arousal. Our work tests and supports the ABCD model, showing that it outperforms a data-driven clustering approach and may perform equally well compared to a more parsimonious categorization. Additionally, in a subset of patients (N = 11), we correlated EEG findings with functional magnetic resonance imaging (fMRI) connectivity between nodes in the mesocircuit-which has been theoretically implicated by Schiff in DOC-and report a trend-level relationship that warrants further investigation in larger studies.
Daniel Toker, Ioannis Pappas, Janna D. Lendner, Joel Frohlich, Diego M. Mateos, Suresh Muthukumaraswamy, Robin Carhart-Harris, Michelle Paff, Paul M. Vespa, Martin M. Monti,et al.
Proceedings of the National Academy of Sciences
Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, we empirically identify a mathematically specific critical point near which waking cortical oscillatory dynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of low-frequency cortical electric oscillations away from this critical point; conversely, we show that psychedelics may increase the information richness of cortical activity by tuning low-frequency cortical oscillations closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC) and show that assessing the proximity of slow cortical oscillatory electrodynamics to the edge-of-chaos critical point may be useful as an index of consciousness in the clinical setting.
Joel Frohlich, Micah A. Johnson, David L. McArthur, Evan S. Lutkenhoff, John Dell'Italia, Courtney Real, Vikesh Shrestha, Norman M. Spivak, Jesús E. Ruiz Tejeda, Paul M. Vespa,et al.
Frontiers Media SA
While electroencephalogram (EEG) burst-suppression is often induced therapeutically using sedatives in the intensive care unit (ICU), there is hitherto no evidence with respect to its association to outcome in moderate-to-severe neurological patients. We examined the relationship between sedation-induced burst-suppression (SIBS) and outcome at hospital discharge and at 6-month follow up in patients surviving moderate-to-severe traumatic brain injury (TBI). For each of 32 patients recovering from coma after moderate-to-severe TBI, we measured the EEG burst suppression ratio (BSR) during periods of low responsiveness as assessed with the Glasgow Coma Scale (GCS). The maximum BSR was then used to predict the Glasgow Outcome Scale extended (GOSe) at discharge and at 6 months post-injury. A multi-model inference approach was used to assess the combination of predictors that best fit the outcome data. We found that BSR was positively associated with outcomes at 6 months (P = 0.022) but did not predict outcomes at discharge. A mediation analysis found no evidence that BSR mediates the effects of barbiturates or propofol on outcomes. Our results provide initial observational evidence that burst suppression may be neuroprotective in acute patients with TBI etiologies. SIBS may thus be useful in the ICU as a prognostic biomarker.
Joerg F. Hipp, Joel Frohlich, Marius Keute, Wen-Hann Tan, and Lynne M. Bird
Elsevier BV
Joel Frohlich, Daniel Toker, and Martin M Monti
Oxford University Press (OUP)
Abstract A common observation in EEG research is that consciousness vanishes with the appearance of delta (1–4 Hz) waves, particularly when those waves are high amplitude. High amplitude delta oscillations are frequently observed in states of diminished consciousness, including slow wave sleep, anaesthesia, generalized epileptic seizures, and disorders of consciousness, such as coma and the vegetative state. This strong correlation between loss of consciousness and high amplitude delta oscillations is thought to stem from the widespread cortical deactivation that occurs during the ‘down states’ or troughs of these slow oscillations. Recently, however, many studies have reported the presence of prominent delta activity during conscious states, which casts doubt on the hypothesis that high amplitude delta oscillations are an indicator of unconsciousness. These studies include work in Angelman syndrome, epilepsy, behavioural responsiveness during propofol anaesthesia, postoperative delirium, and states of dissociation from the environment such as dreaming and powerful psychedelic states. The foregoing studies complement an older, yet largely unacknowledged, body of literature that has documented awake, conscious patients with high amplitude delta oscillations in clinical reports from Rett syndrome, Lennox-Gastaut syndrome, schizophrenia, mitochondrial diseases, hepatic encephalopathy, and non-convulsive status epilepticus. At the same time, a largely parallel body of recent work has reported convincing evidence that the complexity or entropy of EEG and magnetoencephalographic signals strongly relates to an individual’s level of consciousness. Having reviewed this literature, we discuss plausible mechanisms that would resolve the seeming contradiction between high amplitude delta oscillations and consciousness. We also consider implications concerning theories of consciousness, such as integrated information theory and the entropic brain hypothesis. Finally, we conclude that false inferences of unconscious states can be best avoided by examining measures of electrophysiological complexity in addition to spectral power.
Xuan A. Tran, Nicole McDonald, Abigail Dickinson, Aaron Scheffler, Joel Frohlich, Andrew Marin, Christopher Kure Liu, Erin Nosco, Damla Şentürk, Mirella Dapretto,et al.
Wiley
Auditory statistical learning (ASL) plays a role in language development and may lay a foundation for later social communication impairment. As part of a longitudinal study of infant siblings, we asked whether electroencephalography (EEG) measures of connectivity during ASL at 3 months of age‐differentiated infants who showed signs of autism spectrum disorder (ASD) at age 18 months. We measured spectral power and phase coherence in the theta (4–6 Hz) and alpha (6–12 Hz) frequency bands within putative language networks. Infants were divided into ASD‐concern (n = 14) and No‐ASD‐concern (n = 49) outcome groups based on their ASD symptoms at 18 months, measured using the Autism Diagnostic Observation Scale Toddler Module. Using permutation testing, we identified a trend toward reduced left fronto‐central phase coherence at the electrode pair F9‐C3 in both theta and alpha frequency bands in infants who later showed ASD symptoms at 18 months. Across outcome groups, alpha coherence at 3 months correlated with greater word production at 18 months on the MacArthur‐Bates Communicative Development Inventory. This study introduces signal processing and analytic tools that account for the challenges inherent in infant EEG studies, such as short duration of recordings, considerable movement artifact, and variable volume conduction. Our results indicate that connectivity, as measured by phase coherence during 2.5 min of ASL, can be quantified as early as 3 months and suggest that early alternations in connectivity may serve as markers of resilience for neurodevelopmental impairments.
Vidya Saravanapandian, Joel Frohlich, Joerg F. Hipp, Carly Hyde, Aaron W. Scheffler, Peyman Golshani, Edwin H. Cook, Lawrence T. Reiter, Damla Senturk, and Shafali S. Jeste
Springer Science and Business Media LLC
Background Duplications of 15q11.2-q13.1 (Dup15q syndrome) are highly penetrant for autism, intellectual disability, hypotonia, and epilepsy. The 15q region harbors genes critical for brain development, particularly UBE3A and a cluster of gamma-aminobutyric acid type A receptor (GABA A R) genes. We recently described an electrophysiological biomarker of the syndrome, characterized by excessive beta oscillations (12–30 Hz), resembling electroencephalogram (EEG) changes induced by allosteric modulation of GABA A Rs. In this follow-up study, we tested a larger cohort of children with Dup15q syndrome to comprehensively examine properties of this EEG biomarker that would inform its use in future clinical trials, specifically, its (1) relation to basic clinical features, such as age, duplication type, and epilepsy; (2) relation to behavioral characteristics, such as cognition and adaptive function; (3) stability over time; and (4) reproducibility of the signal in clinical EEG recordings. Methods We computed EEG power and beta peak frequency (BPF) in a cohort of children with Dup15q syndrome ( N = 41, age range 9–189 months). To relate EEG parameters to clinical (study 1) and behavioral features (study 2), we examined age, duplication type, epilepsy, cognition, and daily living skills (DLS) as predictors of beta power and BPF. To evaluate stability over time (study 3), we derived the intraclass correlation coefficients (ICC) from beta power and BPF computed from children with multiple EEG recordings ( N = 10, age range 18–161 months). To evaluate reproducibility in a clinical setting (study 4), we derived ICCs from beta power computed from children ( N = 8, age range 19–96 months), who had undergone both research EEG and clinical EEG. Results The most promising relationships between EEG and clinical traits were found using BPF. BPF was predicted both by epilepsy status ( R 2 = 0.11, p = 0.038) and the DLS component of the Vineland Adaptive Behavior Scale ( R 2 = 0.17, p = 0.01). Beta power and peak frequency showed high stability across repeated visits (beta power ICC = 0.93, BPF ICC = 0.92). A reproducibility analysis revealed that beta power estimates are comparable between research and clinical EEG (ICC = 0.94). Conclusions In this era of precision health, with pharmacological and neuromodulatory therapies being developed and tested for specific genetic etiologies of neurodevelopmental disorders, quantification and examination of mechanistic biomarkers can greatly improve clinical trials. To this end, the robust beta oscillations evident in Dup15q syndrome are clinically reproducible and stable over time. With future preclinical and computational studies that will help disentangle the underlying mechanism, it is possible that this biomarker could serve as a robust measure of drug target engagement or a proximal outcome measure in future disease modifying intervention trials.
Joel Frohlich, Lynne M Bird, John Dell’Italia, Micah A Johnson, Joerg F Hipp, and Martin M Monti
Oxford University Press (OUP)
[This corrects the article DOI: 10.1093/nc/niaa005.][This corrects the article DOI: 10.1093/nc/niaa005.].
Joel Frohlich, Lynne M Bird, John Dell’Italia, Micah A Johnson, Joerg F Hipp, and Martin M Monti
Oxford University Press (OUP)
Abstract Abundant evidence from slow wave sleep, anesthesia, coma, and epileptic seizures links high-voltage, slow electroencephalogram (EEG) activity to loss of consciousness. This well-established correlation is challenged by the observation that children with Angelman syndrome (AS), while fully awake and displaying volitional behavior, display a hypersynchronous delta (1–4 Hz) frequency EEG phenotype typical of unconsciousness. Because the trough of the delta oscillation is associated with down-states in which cortical neurons are silenced, the presence of volitional behavior and wakefulness in AS amidst diffuse delta rhythms presents a paradox. Moreover, high-voltage, slow EEG activity is generally assumed to lack complexity, yet many theories view functional brain complexity as necessary for consciousness. Here, we use abnormal cortical dynamics in AS to assess whether EEG complexity may scale with the relative level of consciousness despite a background of hypersynchronous delta activity. As characterized by multiscale metrics, EEGs from 35 children with AS feature significantly greater complexity during wakefulness compared with sleep, even when comparing the most pathological segments of wakeful EEG to the segments of sleep EEG least likely to contain conscious mentation and when factoring out delta power differences across states. These findings (i) warn against reverse inferring an absence of consciousness solely on the basis of high-amplitude EEG delta oscillations, (ii) corroborate rare observations of preserved consciousness under hypersynchronization in other conditions, (iii) identify biomarkers of consciousness that have been validated under conditions of abnormal cortical dynamics, and (iv) lend credence to theories linking consciousness with complexity.
Joel Frohlich, Lawrence T. Reiter, Vidya Saravanapandian, Charlotte DiStefano, Scott Huberty, Carly Hyde, Stormy Chamberlain, Carrie E. Bearden, Peyman Golshani, Andrei Irimia,et al.
Springer Science and Business Media LLC
Following publication of the original article [1], we have been notified that the Ethics statement of the articles should be changed. The Ethics statement now reads:
Joel Frohlich, Lawrence T. Reiter, Vidya Saravanapandian, Charlotte DiStefano, Scott Huberty, Carly Hyde, Stormy Chamberlain, Carrie E. Bearden, Peyman Golshani, Andrei Irimia,et al.
Springer Science and Business Media LLC
BackgroundDuplications of 15q11.2-q13.1 (Dup15q syndrome), including the paternally imprinted gene UBE3A and three nonimprinted gamma-aminobutyric acid type-A (GABAA) receptor genes, are highly penetrant for neurodevelopmental disorders such as autism spectrum disorder (ASD). To guide targeted treatments of Dup15q syndrome and other forms of ASD, biomarkers are needed that reflect molecular mechanisms of pathology. We recently described a beta EEG phenotype of Dup15q syndrome, but it remains unknown which specific genes drive this phenotype.MethodsTo test the hypothesis that UBE3A overexpression is not necessary for the beta EEG phenotype, we compared EEG from a reference cohort of children with Dup15q syndrome (n = 27) to (1) the pharmacological effects of the GABAA modulator midazolam (n = 12) on EEG from healthy adults, (2) EEG from typically developing (TD) children (n = 14), and (3) EEG from two children with duplications of paternal 15q (i.e., the UBE3A-silenced allele).ResultsPeak beta power was significantly increased in the reference cohort relative to TD controls. Midazolam administration recapitulated the beta EEG phenotype in healthy adults with a similar peak frequency in central channels (f = 23.0 Hz) as Dup15q syndrome (f = 23.1 Hz). Both paternal Dup15q syndrome cases displayed beta power comparable to the reference cohort.ConclusionsOur results suggest a critical role for GABAergic transmission in the Dup15q syndrome beta EEG phenotype, which cannot be explained by UBE3A dysfunction alone. If this mechanism is confirmed, the phenotype may be used as a marker of GABAergic pathology in clinical trials for Dup15q syndrome.
Qian Li, Damla Şentürk, Catherine A. Sugar, Shafali Jeste, Charlotte DiStefano, Joel Frohlich, and Donatello Telesca
Informa UK Limited
ABSTRACT Inferring patterns of synchronous brain activity from a heterogeneous sample of electroencephalograms is scientifically and methodologically challenging. While it is intuitively and statistically appealing to rely on readings from more than one individual in order to highlight recurrent patterns of brain activation, pooling information across subjects presents nontrivial methodological problems. We discuss some of the scientific issues associated with the understanding of synchronized neuronal activity and propose a methodological framework for statistical inference from a sample of EEG readings. Our work builds on classical contributions in time-series, clustering, and functional data analysis, in an effort to reframe a challenging inferential problem in the context of familiar analytical techniques. Some attention is paid to computational issues, with a proposal based on the combination of machine learning and Bayesian techniques. Code submitted with this article was checked by an Associate Editor for Reproducibility and is available as an online supplement.
Joel Frohlich, Meghan T. Miller, Lynne M. Bird, Pilar Garces, Hannah Purtell, Marius C. Hoener, Benjamin D. Philpot, Michael S. Sidorov, Wen-Hann Tan, Maria-Clemencia Hernandez,et al.
Elsevier BV
BACKGROUND
Angelman syndrome (AS) is a severe neurodevelopmental disorder caused by either disruptions of the gene UBE3A or deletion of chromosome 15 at 15q11-q13, which encompasses UBE3A and several other genes, including GABRB3, GABRA5, GABRG3, encoding gamma-aminobutyric acid type A receptor subunits (β3, α5, γ3). Individuals with deletions are generally more impaired than those with other genotypes, but the underlying pathophysiology remains largely unknown. Here, we used electroencephalography (EEG) to test the hypothesis that genes other than UBE3A located on 15q11-q13 cause differences in pathophysiology between AS genotypes.
METHODS
We compared spectral power of clinical EEG recordings from children (1-18 years of age) with a deletion genotype (n = 37) or a nondeletion genotype (n = 21) and typically developing children without Angelman syndrome (n = 48).
RESULTS
We found elevated theta power (peak frequency: 5.3 Hz) and diminished beta power (peak frequency: 23 Hz) in the deletion genotype compared with the nondeletion genotype as well as excess broadband EEG power (1-32 Hz) peaking in the delta frequency range (peak frequency: 2.8 Hz), shared by both genotypes but stronger for the deletion genotype at younger ages.
CONCLUSIONS
Our results provide strong evidence for the contribution of non-UBE3A neuronal pathophysiology in deletion AS and suggest that hemizygosity of the GABRB3-GABRA5-GABRG3 gene cluster causes abnormal theta and beta EEG oscillations that may underlie the more severe clinical phenotype. Our work improves the understanding of AS pathophysiology and has direct implications for the development of AS treatments and biomarkers.
C. Willfors, K. Tammimies and S. Bölte
CRC Press
Joel Frohlich, Damla Senturk, Vidya Saravanapandian, Peyman Golshani, Lawrence T. Reiter, Raman Sankar, Ronald L. Thibert, Charlotte DiStefano, Scott Huberty, Edwin H. Cook,et al.
Public Library of Science (PLoS)
Background Duplications of 15q11.2-q13.1 (Dup15q syndrome) are highly penetrant for autism spectrum disorder (ASD). A distinct electrophysiological (EEG) pattern characterized by excessive activity in the beta band has been noted in clinical reports. We asked whether EEG power in the beta band, as well as in other frequency bands, distinguished children with Dup15q syndrome from those with non-syndromic ASD and then examined the clinical correlates of this electrophysiological biomarker in Dup15q syndrome. Methods In the first study, we recorded spontaneous EEG from children with Dup15q syndrome (n = 11), age-and-IQ-matched children with ASD (n = 10) and age-matched typically developing (TD) children (n = 9) and computed relative power in 6 frequency bands for 9 regions of interest (ROIs). Group comparisons were made using a repeated measures analysis of variance. In the second study, we recorded spontaneous EEG from a larger cohort of individuals with Dup15q syndrome (n = 27) across two sites and examined age, epilepsy, and duplication type as predictors of beta power using simple linear regressions. Results In the first study, spontaneous beta1 (12–20 Hz) and beta2 (20–30 Hz) power were significantly higher in Dup15q syndrome compared with both comparison groups, while delta (1–4 Hz) was significantly lower than both comparison groups. Effect sizes in all three frequency bands were large (|d| > 1). In the second study, we found that beta2 power was significantly related to epilepsy diagnosis in Dup15q syndrome. Conclusions Here, we have identified an electrophysiological biomarker of Dup15q syndrome that may facilitate clinical stratification, treatment monitoring, and measurement of target engagement for future clinical trials. Future work will investigate the genetic and neural underpinnings of this electrophysiological signature as well as the functional consequences of excessive beta oscillations in Dup15q syndrome.
Joel Frohlich and John Darrell Van Horn
Elsevier
Dissociative agents—uncompetitive N-methyl-d-aspartate receptor (NMDAR) antagonists—such as ketamine, phencyclidine, and dizocilpine are known to transiently induce positive, negative, and cognitive symptoms of schizophrenia in healthy adults. Herein, we conclude that dissociative drug challenge accurately models neurotransmitter dysfunction, excitotoxicity, neurodegeneration, age of onset, gamma band aberrations, and electroencephalogram signal complexity observed in schizophrenia. Furthermore, dissociative drugs bind to a host of other receptors (e.g., sigma, opioid, dopamine D2, cholinergic) and thus transcend NMDAR hypofunction models of schizophrenia. Principal effects of dissociative agents are mediated by blockade of NMDARs expressed by gamma-aminobutyric acid (GABA)ergic interneurons, resulting in disruptions of gamma oscillations and disinhibition of glutamatergic and cholinergic afferents, triggering patterns of excitotoxic neurodegeneration seen in schizophrenia. Future work should seek to understand the extent to which ketamine and other dissociative drugs might effect psychomimesis through action at muscarinic, nicotinic, opioid, and sigma-1 receptors, as well as monoamine transporters.