Camarin Rolle

All Publications

• Responsive deep brain stimulation guided by ventral striatal electrophysiology of obsession durably ameliorates compulsion. Neuron Nho, Y. H., Rolle, C. E., Topalovic, U., Shivacharan, R. S., Cunningham, T. N., Hiller, S., Batista, D., Feng, A., Espil, F. M., Kratter, I. H., Bhati, M. T., Kellogg, M., Raslan, A. M., Williams, N. R., Garnett, J., Pesaran, B., Oathes, D. J., Suthana, N., Barbosa, D. A., Halpern, C. H. 2023

  Abstract

  Treatment-resistant obsessive-compulsive disorder (OCD) occurs in approximately one-third of OCD patients. Obsessions may fluctuate over time but often occur or worsen in the presence of internal (emotional state and thoughts) and external (visual and tactile) triggering stimuli. Obsessive thoughts and related compulsive urges fluctuate (are episodic) and so may respond well to a time-locked brain stimulation strategy sensitive and responsive to these symptom fluctuations. Early evidence suggests that neural activity can be captured from ventral striatal regions implicated in OCD to guide such a closed-loop approach. Here, we report on a first-in-human application of responsive deep brain stimulation (rDBS) of the ventral striatum for a treatment-refractory OCD individual who also had comorbid epilepsy. Self-reported obsessive symptoms and provoked OCD-related distress correlated with ventral striatal electrophysiology. rDBS detected the time-domain area-based feature from invasive electroencephalography low-frequency oscillatory power fluctuations that triggered bursts of stimulation to ameliorate OCD symptoms in a closed-loop fashion. rDBS provided rapid, robust, and durable improvement in obsessions and compulsions. These results provide proof of concept for a personalized, physiologically guided DBS strategy for OCD.

  View details for DOI 10.1016/j.neuron.2023.09.034

  View details for PubMedID 37865084

• Accumbens connectivity during deep-brain stimulation differentiates loss of control from physiologic behavioral states. Brain stimulation Rolle, C. E., Ng, G. Y., Nho, Y. H., Barbosa, D. A., Shivacharan, R. S., Gold, J. I., Bassett, D. S., Halpern, C. H., Buch, V. 2023

  Abstract

  Loss of control (LOC) eating, the subjective sense that one cannot control what or how much one eats, characterizes binge-eating behaviors pervasive in obesity and related eating disorders. Closed-loop deep-brain stimulation (DBS) for binge eating should predict LOC and trigger an appropriately timed intervention.This study aimed to identify a sensitive and specific biomarker to detect LOC onset for DBS. We hypothesized that changes in phase-locking value (PLV) predict the onset of LOC-associated cravings and distinguish them from potential confounding states.Using DBS data recorded from the nucleus accumbens (NAc) of two patients with binge eating disorder (BED) and severe obesity, we compared PLV between inter- and intra-hemispheric NAc subregions for three behavioral conditions: craving (associated with LOC eating), hunger (not associated with LOC), and sleep.In both patients, PLV in the high gamma frequency band was significantly higher for craving compared to sleep and significantly higher for hunger compared to craving. Maximum likelihood classifiers achieved accuracies above 88% when differentiating between the three conditions.High-frequency inter- and intra-hemispheric PLV in the NAc is a promising biomarker for closed-loop DBS that differentiates LOC-associated cravings from physiologic states such as hunger and sleep. Future trials should assess PLV as a LOC biomarker across a larger cohort and a wider patient population transdiagnostically.

  View details for DOI 10.1016/j.brs.2023.09.010

  View details for PubMedID 37734587

• The Hypothalamus, Nucleus Accumbens, and Hippocampus Demonstrate Increased Delta Band Power and Coherence During Reward Anticipation Seilheimer, R., Rolle, C., Vaz, A., Kakusa, B., Huang, Y., Barbosa, D. N., Halpern, C. ELSEVIER SCIENCE INC. 2023: S107-S108

  View details for Web of Science ID 000993018500256

• Appetitive Mapping of the Human Nucleus Accumbens. Biological psychiatry Parker, J. J., Rolle, C. E., Shivacharan, R. S., Barbosa, D. A., Feng, A., Huang, Y., Kakusa, B. W., Prieto, T., Jaffe, R. A., Williams, N. R., Halpern, C. H. 2022

  View details for DOI 10.1016/j.biopsych.2022.09.016

  View details for PubMedID 36509559

• Integrated cognitive and physical fitness training enhances attention abilities in older adults. npj aging Anguera, J. A., Volponi, J. J., Simon, A. J., Gallen, C. L., Rolle, C. E., Anguera-Singla, R., Pitsch, E. A., Thompson, C. J., Gazzaley, A. 2022; 8 (1): 12

  Abstract

  Preserving attention abilities is of great concern to older adults who are motivated to maintain their quality of life. Both cognitive and physical fitness interventions have been utilized in intervention studies to assess maintenance and enhancement of attention abilities in seniors, and a coupling of these approaches is a compelling strategy to buttress both cognitive and physical health in a time- and resource-effective manner. With this perspective, we created a closed-loop, motion-capture video game (Body-Brain Trainer: BBT) that adapts a player's cognitive and physical demands in an integrated approach, thus creating a personalized and cohesive experience across both domains. Older adults who engaged in two months of BBT improved on both physical fitness (measures of blood pressure and balance) and attention (behavioral and neural metrics of attention on a continuous performance task) outcome measures beyond that of an expectancy matched, active, placebo control group, with maintenance of improved attention performance evidenced 1 year later. Following training, the BBT group's improvement on the attention outcome measure exceeded performance levels attained by an untrained group of 20-year olds, and showed age-equilibration of a neural signature of attention shown to decline with age: midline frontal theta power. These findings highlight the potential benefits of an integrated, cognitive-physical, closed-loop training platform as a powerful tool for both cognitive and physical enhancement in older adults.

  View details for DOI 10.1038/s41514-022-00093-y

  View details for PubMedID 36042247

• Pilot study of responsive nucleus accumbens deep brain stimulation for loss-of-control eating. Nature medicine Shivacharan, R. S., Rolle, C. E., Barbosa, D. A., Cunningham, T. N., Feng, A., Johnson, N. D., Safer, D. L., Bohon, C., Keller, C., Buch, V. P., Parker, J. J., Azagury, D. E., Tass, P. A., Bhati, M. T., Malenka, R. C., Lock, J. D., Halpern, C. H. 2022

  Abstract

  Cravings that precede loss of control (LOC) over food consumption present an opportunity for intervention in patients with the binge eating disorder (BED). In this pilot study, we used responsive deep brain stimulation (DBS) to record nucleus accumbens (NAc) electrophysiology during food cravings preceding LOC eating in two patients with BED and severe obesity (trial registration no. NCT03868670). Increased NAc low-frequency oscillations, prominent during food cravings, were used to guide DBS delivery. Over 6 months, we observed improved self-control of food intake and weight loss. These findings provide early support for restoring inhibitory control with electrophysiologically-guided NAc DBS. Further work with increased sample sizes is required to determine the scalability of this approach.

  View details for DOI 10.1038/s41591-022-01941-w

  View details for PubMedID 36038628

• Functional Connectivity using high density EEG shows competitive reliability and agreement across test/retest sessions. Journal of neuroscience methods Rolle, C. E., Narayan, M., Wu, W., Toll, R., Johnson, N., Caudle, T., Yan, M., El-Said, D., Waats, M., Eisenberg, M., Etkin, A. 2021: 109424

  View details for DOI 10.1016/j.jneumeth.2021.109424

  View details for PubMedID 34826504

• Anterior-posterior electrophysiological activity characterizes Parkinsonian visual misperceptions NEUROLOGY AND CLINICAL NEUROSCIENCE Muller, A. J., Shine, J. M., Rolle, C. E., Chitty, K., Hall, J. M., Halliday, G. M., Hermens, D. F., Lewis, S. G., O'Callaghan, C. 2021

  View details for DOI 10.1111/ncn3.12508

  View details for Web of Science ID 000650053200001

• Mapping causal circuit dynamics in stroke using simultaneous electroencephalography and transcranial magnetic stimulation. BMC neurology Rolle, C. E., Baumer, F. M., Jordan, J. T., Berry, K., Garcia, M., Monusko, K., Trivedi, H., Wu, W., Toll, R., Buckwalter, M. S., Lansberg, M., Etkin, A. 2021; 21 (1): 280

  Abstract

  Motor impairment after stroke is due not only to direct tissue loss but also to disrupted connectivity within the motor network. Mixed results from studies attempting to enhance motor recovery with Transcranial Magnetic Stimulation (TMS) highlight the need for a better understanding of both connectivity after stroke and the impact of TMS on this connectivity. This study used TMS-EEG to map the causal information flow in the motor network of healthy adult subjects and define how stroke alters these circuits.Fourteen stroke patients and 12 controls received TMS to two sites (bilateral primary motor cortices) during two motor tasks (paretic/dominant hand movement vs. rest) while EEG measured the cortical response to TMS pulses. TMS-EEG based connectivity measurements were derived for each hemisphere and the change in connectivity (ΔC) between the two motor tasks was calculated. We analyzed if ΔC for each hemisphere differed between the stroke and control groups or across TMS sites, and whether ΔC correlated with arm function in stroke patients.Right hand movement increased connectivity in the left compared to the right hemisphere in controls, while hand movement did not significantly change connectivity in either hemisphere in stroke. Stroke patients with the largest increase in healthy hemisphere connectivity during paretic hand movement had the best arm function.TMS-EEG measurements are sensitive to movement-induced changes in brain connectivity. These measurements may characterize clinically meaningful changes in circuit dynamics after stroke, thus providing specific targets for trials of TMS in post-stroke rehabilitation.

  View details for DOI 10.1186/s12883-021-02319-0

  View details for PubMedID 34271872

• Neurocognitive markers of passive suicidal ideation in late-life depression. International psychogeriatrics Jordan, J. T., Chick, C. F., Rolle, C. E., Hantke, N., Gould, C. E., Lutz, J., Kawai, M., Cotto, I., Karna, R., Pirog, S., Berk, M., Sudheimer, K., O'Hara, R., Beaudreau, S. A. 2020: 1–11

  Abstract

  OBJECTIVES: (1) To delineate whether cognitive flexibility and inhibitory ability are neurocognitive markers of passive suicidal ideation (PSI), an early stage of suicide risk in depression and (2) to determine whether PSI is associated with volumetric differences in regions of the prefrontal cortex (PFC) in middle-aged and older adults with depression.DESIGN: Cross-sectional study.SETTING: University medical school.PARTICIPANTS: Forty community-dwelling middle-aged and older adults with depression from a larger study of depression and anxiety (NIMH R01 MH091342-05 PI: O'Hara).MEASUREMENTS: Psychiatric measures were assessed for the presence of a DSM-5 depressive disorder and PSI. A neurocognitive battery assessed cognitive flexibility, inhibitory ability, as well as other neurocognitive domains.RESULTS: The PSI group (n = 18) performed significantly worse on cognitive flexibility and inhibitory ability, but not on other neurocognitive tasks, compared to the group without PSI (n = 22). The group with PSI had larger left mid-frontal gyri (MFG) than the no-PSI group. There was no association between cognitive flexibility/inhibitory ability and left MFG volume.CONCLUSIONS: Findings implicate a neurocognitive signature of PSI: poorer cognitive flexibility and poor inhibitory ability not better accounted for by other domains of cognitive dysfunction and not associated with volumetric differences in the left MFG. This suggests that there are two specific but independent risk factors of PSI in middle- and older-aged adults.

  View details for DOI 10.1017/S1041610220003610

  View details for PubMedID 33118918

• An electroencephalographic signature predicts antidepressant response in major depression. Nature biotechnology Wu, W., Zhang, Y., Jiang, J., Lucas, M. V., Fonzo, G. A., Rolle, C. E., Cooper, C., Chin-Fatt, C., Krepel, N., Cornelssen, C. A., Wright, R., Toll, R. T., Trivedi, H. M., Monuszko, K., Caudle, T. L., Sarhadi, K., Jha, M. K., Trombello, J. M., Deckersbach, T., Adams, P., McGrath, P. J., Weissman, M. M., Fava, M., Pizzagalli, D. A., Arns, M., Trivedi, M. H., Etkin, A. 2020

  Abstract

  Antidepressants are widely prescribed, but their efficacy relative to placebo is modest, in part because the clinical diagnosis of major depression encompasses biologically heterogeneous conditions. Here, we sought to identify a neurobiological signature of response to antidepressant treatment as compared to placebo. We designed a latent-space machine-learning algorithm tailored for resting-state electroencephalography (EEG) and applied it to data from the largest imaging-coupled, placebo-controlled antidepressant study (n=309). Symptom improvement was robustly predicted in a manner both specific for the antidepressant sertraline (versus placebo) and generalizable across different study sites and EEG equipment. This sertraline-predictive EEG signature generalized to two depression samples, wherein it reflected general antidepressant medication responsivity and related differentially to a repetitive transcranial magnetic stimulation treatment outcome. Furthermore, we found that the sertraline resting-state EEG signature indexed prefrontal neural responsivity, as measured by concurrent transcranial magnetic stimulation and EEG. Our findings advance the neurobiological understanding of antidepressant treatment through an EEG-tailored computational model and provide a clinical avenue for personalized treatment of depression.

  View details for DOI 10.1038/s41587-019-0397-3

  View details for PubMedID 32042166

• Cortical Connectivity Moderators of Antidepressant vs Placebo Treatment Response in Major Depressive Disorder: Secondary Analysis of a Randomized Clinical Trial. JAMA psychiatry Rolle, C. E., Fonzo, G. A., Wu, W., Toll, R., Jha, M. K., Cooper, C., Chin-Fatt, C., Pizzagalli, D. A., Trombello, J. M., Deckersbach, T., Fava, M., Weissman, M. M., Trivedi, M. H., Etkin, A. 2020

  Abstract

  Importance: Despite the widespread awareness of functional magnetic resonance imaging findings suggesting a role for cortical connectivity networks in treatment selection for major depressive disorder, its clinical utility remains limited. Recent methodological advances have revealed functional magnetic resonance imaging-like connectivity networks using electroencephalography (EEG), a tool more easily implemented in clinical practice.Objective: To determine whether EEG connectivity could reveal neural moderators of antidepressant treatment.Design, Setting, and Participants: In this nonprespecified secondary analysis, data were analyzed from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinic Care study, a placebo-controlled, double-blinded randomized clinical trial. Recruitment began July 29, 2011, and was completed December 15, 2015. A random sample of 221 outpatients with depression aged 18 to 65 years who were not taking medication for depression was recruited and assessed at 4 clinical sites. Analysis was performed on an intent-to-treat basis. Statistical analysis was performed from November 16, 2018, to May 23, 2019.Interventions: Patients received either the selective serotonin reuptake inhibitor sertraline hydrochloride or placebo for 8 weeks.Main Outcomes and Measures: Electroencephalographic orthogonalized power envelope connectivity analyses were applied to resting-state EEG data. Intent-to-treat prediction linear mixed models were used to determine which pretreatment connectivity patterns were associated with response to sertraline vs placebo. The primary clinical outcome was the total score on the 17-item Hamilton Rating Scale for Depression, administered at each study visit.Results: Of the participants recruited, 9 withdrew after first dose owing to reported adverse effects, and 221 participants (150 women; mean [SD] age, 37.8 [12.7] years) underwent EEG recordings and had high-quality pretreatment EEG data. After correction for multiple comparisons, connectome-wide analyses revealed moderation by connections within and between widespread cortical regions-most prominently parietal-for both the antidepressant and placebo groups. Greater alpha-band and lower gamma-band connectivity predicted better placebo outcomes and worse antidepressant outcomes. Lower connectivity levels in these moderating connections were associated with higher levels of anhedonia. Connectivity features that moderate treatment response differentially by treatment group were distinct from connectivity features that change from baseline to 1 week into treatment. The group mean (SD) score on the 17-item Hamilton Rating Scale for Depression was 18.35 (4.58) at baseline and 26.14 (30.37) across all time points.Conclusions and Relevance: These findings establish the utility of EEG-based network functional connectivity analyses for differentiating between responses to an antidepressant vs placebo. A role emerged for parietal cortical regions in predicting placebo outcome. From a treatment perspective, capitalizing on the therapeutic components leading to placebo response differentially from antidepressant response should provide an alternative direction toward establishing a placebo signature in clinical trials, thereby enhancing the signal detection in randomized clinical trials.Trial Registration: ClinicalTrials.gov identifier: NCT01407094.

  View details for DOI 10.1001/jamapsychiatry.2019.3867

  View details for PubMedID 31895437

• Cortical Excitability, Synaptic Plasticity, and Cognition in Benign Epilepsy With Centrotemporal Spikes: A Pilot TMS-EMG-EEG Study. Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society Baumer, F. M., Pfeifer, K. n., Fogarty, A. n., Pena-Solorzano, D. n., Rolle, C. E., Wallace, J. L., Rotenberg, A. n., Fisher, R. S. 2020; 37 (2): 170–80

  Abstract

  Children with benign epilepsy with centrotemporal spikes have rare seizures emerging from the motor cortex, which they outgrow in adolescence, and additionally may have language deficits of unclear etiology. We piloted the use of transcranial magnetic stimulation paired with EMG and EEG (TMS-EMG, TMS-EEG) to test the hypotheses that net cortical excitability decreases with age and that use-dependent plasticity predicts learning.We assessed language and motor learning in 14 right-handed children with benign epilepsy with centrotemporal spikes. We quantified two TMS metrics of left motor cortex excitability: the resting motor threshold (measure of neuronal membrane excitability) and amplitude of the N100-evoked potential (an EEG measure of GABAergic tone). To test plasticity, we applied 1 Hz repetitive TMS to the motor cortex to induce long-term depression-like changes in EMG- and EEG-evoked potentials.Children with benign epilepsy with centrotemporal spikes tolerate TMS; no seizures were provoked. Resting motor threshold decreases with age but is elevated above maximal stimulator output for half the group. N100 amplitude decreases with age after controlling for resting motor threshold. Motor cortex plasticity correlates significantly with language learning and at a trend level with motor learning.Transcranial magnetic stimulation is safe and feasible for children with benign epilepsy with centrotemporal spikes, and TMS-EEG provides more reliable outcome measures than TMS-EMG in this group because many children have unmeasurably high resting motor thresholds. Net cortical excitability decreases with age, and motor cortex plasticity predicts not only motor learning but also language learning, suggesting a mechanism by which motor cortex seizures may interact with language development.

  View details for DOI 10.1097/WNP.0000000000000662

  View details for PubMedID 32142025

• REWARD PROCESSING IN DEPRESSED AND OBESE CHILDREN Angal, S., Fischer, A. S., Bohon, C., Nimarko, A. F., Rolle, C. E., Lu, Y., Pan, T., Kuramkote, S. R., Rasgon, N. L., Singh, M. K. ELSEVIER SCIENCE INC. 2019: S274

  View details for DOI 10.1016/j.jaac.2019.08.402

  View details for Web of Science ID 000518857302223

• Transcranial magnetic stimulation demonstrates a role for the ventrolateral prefrontal cortex in emotion perception. Psychiatry research Chick, C. F., Rolle, C., Trivedi, H. M., Monuszko, K., Etkin, A. 2019: 112515

  Abstract

  The lateral prefrontal cortex, a region with both structural and functional connectivity to the amygdala, has been consistently implicated in the downregulation of subcortical-generated emotional responses. Although previous work has demonstrated that the ventral lateral prefrontal cortex (vlPFC) is important to emotion processing, no study has interrupted vlPFC function in order to test is role in emotion perception. In the current study, we acutely disrupted vlPFC function in twenty healthy adult participants by administering sham stimulation and transcranial magnetic stimulation (TMS), in randomized order, during performance of an emotional perception task. During sham stimulation, participants demonstrated increased perceptual sensitivity for happy faces compared to angry faces. Disruption of the vlPFC eliminated this difference: in this condition, perceptual sensitivity did not differ between happy and angry faces. Reaction times and response bias did not differ between emotions or TMS conditions. This pattern of perceptual bias is consistent with effects observed in a wide range of affective disorders, in which vlPFC dysfunction has also been reported. This study provides insight into a possible mechanism through which the vlPFC may contribute to emotion perception.

  View details for DOI 10.1016/j.psychres.2019.112515

  View details for PubMedID 31831202

• Causal Role of the Dorsal-Lateral Prefrontal Cortex in Approach-Avoidance Conflict Johnson, N., Rolle, C., Caudle, T., Yan, M., Etkin, A. ELSEVIER SCIENCE INC. 2019: S137

  View details for DOI 10.1016/j.biopsych.2019.03.344

  View details for Web of Science ID 000472661000329

• A "Primate-Approach" to Studying Approach-Avoidance Conflict in Humans Rolle, C., Johnson, N., Caudle, T., Yan, M., Etkin, A. ELSEVIER SCIENCE INC. 2019: S140

  View details for DOI 10.1016/j.biopsych.2019.03.351

  View details for Web of Science ID 000472661000336

• State-Dependency of the Stimulation-Induced Evoked Response in EEG Yan, M., Rolle, C., Caudle, T., Johnson, N., Etkin, A. ELSEVIER SCIENCE INC. 2019: S139

  View details for DOI 10.1016/j.biopsych.2019.03.348

  View details for Web of Science ID 000472661000333

• Closed-loop digital meditation improves sustained attention in young adults. Nature human behaviour Ziegler, D. A., Simon, A. J., Gallen, C. L., Skinner, S. n., Janowich, J. R., Volponi, J. J., Rolle, C. E., Mishra, J. n., Kornfield, J. n., Anguera, J. A., Gazzaley, A. n. 2019

  Abstract

  Attention is a fundamental cognitive process that is critical for essentially all aspects of higher-order cognition and real-world activities. Younger generations have deeply embraced information technology and multitasking in their personal lives, school and the workplace, creating myriad challenges to their attention. While improving sustained attention in healthy young adults would be beneficial, enhancing this ability has proven notoriously difficult in this age group. Here we show that 6 weeks of engagement with a meditation-inspired, closed-loop software program (MediTrain) delivered on mobile devices led to gains in both sustained attention and working memory in healthy young adults. These improvements were associated with positive changes in key neural signatures of attentional control (frontal theta inter-trial coherence and parietal P3b latency), as measured by electroencephalography. Our findings suggest the utility of delivering aspects of the ancient practice of focused-attention meditation in a modern, technology-based approach and its benefits on enhancing sustained attention.

  View details for DOI 10.1038/s41562-019-0611-9

  View details for PubMedID 31160812

• Characterizing Cognitive and Visuomotor Control in Children With Sensory Processing Dysfunction and Autism Spectrum Disorders NEUROPSYCHOLOGY Brandes-Aitken, A., Anguera, J. A., Rolle, C. E., Desai, S. S., Demopoulos, C., Skinner, S. N., Gazzaley, A., Marco, E. J. 2018; 32 (2): 148–60

  Abstract

  Children with autism spectrum disorders (ASD) and sensory processing dysfunction (SPD) are reported to show difficulties involving cognitive and visuomotor control. We sought to determine whether performance on computerized, behavioral measures of cognitive control aimed at assessing selective attention, as well as visuomotor abilities differentiated children with ASD (n = 14), SPD (n = 14) and typically developing controls (TDC; n = 28).Cognitive control differences were measured by assessing selective attention-based abilities both with and without distracting stimuli, and visuomotor differences were measured by characterizing visuomotor tracking and tracing skills. Performance in cognitive control and visuomotor domains were investigated globally as composite scores, and specifically within each task.Our results indicated that though the ASD group showed the most impaired selective attention performance, the SPD group had intermediate abilities-performing above the ASD group but below the TDC group. Furthermore, both the SPD and ASD groups demonstrated equally impaired visuomotor abilities relative to the TDC group. A correlational analysis between cognitive and visuomotor control suggest a relationship between these overlapping control networks.This study supports the importance of direct, phenotypic characterizations of control-based abilities in children with ASD and SPD to personalize characterization and treatment interventions for at-risk children. (PsycINFO Database Record

  View details for DOI 10.1037/neu0000404

  View details for Web of Science ID 000427044500003

  View details for PubMedID 29376661

• ARTIST: A fully automated artifact rejection algorithm for single-pulse TMS-EEG data. Human brain mapping Wu, W. n., Keller, C. J., Rogasch, N. C., Longwell, P. n., Shpigel, E. n., Rolle, C. E., Etkin, A. n. 2018

  Abstract

  Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings.

  View details for PubMedID 29331054

• Repetitive Brain Stimulation Induces Long-term Plasticity Across Patient Populations and Spatial Scales Keller, C. J., Wu, W., Wright, R., Rolle, C., Sarhadi, K., Ichikawa, N., Huemer, J., Wong, M., Yee, A., McTeague, L., Fini, M., Du, V., Honey, C., Lado, F., Mehta, A., Etkin, A. ELSEVIER SCIENCE INC. 2016: 276S

  View details for Web of Science ID 000432440803183

• Neural plasticity underlying visual perceptual learning in aging BRAIN RESEARCH Mishra, J., Rolle, C., Gazzaley, A. 2015; 1612: 140–51

  Abstract

  Healthy aging is associated with a decline in basic perceptual abilities, as well as higher-level cognitive functions such as working memory. In a recent perceptual training study using moving sweeps of Gabor stimuli, Berry et al. (2010) observed that older adults significantly improved discrimination abilities on the most challenging perceptual tasks that presented paired sweeps at rapid rates of 5 and 10 Hz. Berry et al. further showed that this perceptual training engendered transfer-of-benefit to an untrained working memory task. Here, we investigated the neural underpinnings of the improvements in these perceptual tasks, as assessed by event-related potential (ERP) recordings. Early visual ERP components time-locked to stimulus onset were compared pre- and post-training, as well as relative to a no-contact control group. The visual N1 and N2 components were significantly enhanced after training, and the N1 change correlated with improvements in perceptual discrimination on the task. Further, the change observed for the N1 and N2 was associated with the rapidity of the perceptual challenge; the visual N1 (120-150 ms) was enhanced post-training for 10 Hz sweep pairs, while the N2 (240-280 ms) was enhanced for the 5 Hz sweep pairs. We speculate that these observed post-training neural enhancements reflect improvements by older adults in the allocation of attention that is required to accurately dissociate perceptually overlapping stimuli when presented in rapid sequence. This article is part of a Special Issue entitled SI: Memory Å.

  View details for DOI 10.1016/j.brainres.2014.09.009

  View details for Web of Science ID 000356551700012

  View details for PubMedID 25218557

  View details for PubMedCentralID PMC4362864