A brief demonstration of frontostriatal connectivity in OCD patients with intracranial electrodes.

Closed-loop neuromodulation is presumed to be the logical evolution for improving the effectiveness of deep brain stimulation (DBS) treatment protocols (Widge et al., 2018). Identifying symptom-relevant biomarkers that provide meaningful feedback to stimulator devices is an important initial step in this direction. This report demonstrates a technique for assaying neural circuitry hypothesized to contribute to OCD and DBS treatment outcomes. We computed phase-lag connectivity between LFPs and EEGs in thirteen treatment-refractory OCD patients. Simultaneous recordings from scalp EEG and externalized DBS electrodes in the ventral capsule/ventral striatum (VC/VS) were collected at rest during the perioperative treatment stage. Connectivity strength between midfrontal EEG sensors and VC/VS electrodes correlated with baseline OCD symptoms and 12-month posttreatment OCD symptoms. Results are qualified by a relatively small sample size, and limitations regarding the conclusiveness of VS and mPFC as neural generators given some concerns about volume conduction. Nonetheless, findings are consistent with treatment-relevant tractography findings and theories that link frontostriatal hyperconnectivity to the etiopathogenesis of OCD. Findings support the continued investigation of connectivity-based assays for aiding in determination of optimal stimulation location, and are an initial step towards the identification of biomarkers that can guide closed-loop neuromodulation systems.

Theta-Band Functional Connectivity and Single-Trial Cognitive Control in Sports-Related Concussion: Demonstration of Proof-of-Concept for a Potential Biomarker of Concussion.

OBJECTIVES: This report examined theta-band neurodynamics for potential biomarkers of brain health in athletes with concussion. METHODS: Participants included college-age contact/collision athletes with (N=24) and without a history of concussion (N=16) in Study 1. Study 2 (N=10) examined changes over time in contact/collision athletes. There were two primary dependent variables: (1) theta-band phase-synchronization (e.g., functional connectivity) between medial and right-lateral electrodes; and (2) the within-subject correlation between synchronization strength on error trials and post-error reaction time (i.e., operationalization of cognitive control). RESULTS: Head injury history was inversely related with medial-lateral connectivity. Head injury was also related to declines in a neurobehavioral measure of cognitive control (i.e., the single-trial relationship between connectivity and post-error slowing). CONCLUSIONS: Results align with a theory of connectivity-mediated cognitive control. Mild injuries undetectable by behavioral measures may still be apparent on direct measures of neural functioning. This report demonstrates that connectivity and cognitive control measures may be useful for tracking recovery from concussion. Theoretically relevant neuroscientific findings in healthy adults may have applications in patient populations, especially with regard to monitoring brain health. (JINS 2019, 25, 314-323).

Thalamic deep brain stimulation for tourette syndrome increases cortical beta activity.

BACKGROUND: Deep brain stimulation (DBS) of the thalamus can effectively reduce tics in severely affected patients with Tourette syndrome (TS). Its effect on cortical oscillatory activity is currently unknown. OBJECTIVE: We assessed whether DBS modulates beta activity at fronto-central electrodes. We explored concurrent EEG sources and probabilistic stimulation maps. METHODS: Resting state EEG of TS patients treated with thalamic DBS was recorded in repeated DBS-on and DBS-off states. A mixed linear model was employed for statistical evaluation. EEG sources were estimated with eLORETA. Thalamic probabilistic stimulation maps were obtained by assigning beta power difference scores (DBS-on minus DBS-off) to stimulation sites. RESULTS: We observed increased beta power in DBS-on compared to DBS-off states. Modulation of cortical beta activity was localized to the midcingulate cortex. Beta modulation was more pronounced when stimulating the thalamus posteriorly, peaking in the ventral posterior nucleus. CONCLUSION: Thalamic DBS in TS patients modulates beta frequency oscillations presumably important for sensorimotor function and relevant to TS pathophysiology.

A systematic data-driven approach to analyze sensor-level EEG connectivity: Identifying robust phase-synchronized network components using surface Laplacian with spectral-spatial PCA.

Although conventional averaging across predefined frequency bands reduces the complexity of EEG functional connectivity (FC), it obscures the identification of resting-state brain networks (RSN) and impedes accurate estimation of FC reliability. Extending prior work, we combined scalp current source density (CSD; spherical spline surface Laplacian) and spectral-spatial PCA to identify FC components. Phase-based FC was estimated via debiased-weighted phase-locking index from CSD-transformed resting EEGs (71 sensors, 8 min, eyes open/closed, 35 healthy adults, 1-week retest). Spectral PCA extracted six robust alpha and theta components (86.6% variance). Subsequent spatial PCA for each spectral component revealed seven robust regionally focused (posterior, central, and frontal) and long-range (posterior-anterior) alpha components (peaks at 8, 10, and 13 Hz) and a midfrontal theta (6 Hz) component, accounting for 37.0% of FC variance. These spatial FC components were consistent with well-known networks (e.g., default mode, visual, and sensorimotor), and four were sensitive to eyes open/closed conditions. Most FC components had good-to-excellent internal consistency (odd/even epochs, eyes open/closed) and test-retest reliability (ICCs ≥ .8). Moreover, the FC component structure was generally present in subsamples (session × odd/even epoch, or smaller subgroups [n = 7-10]), as indicated by high similarity of component loadings across PCA solutions. Apart from systematically reducing FC dimensionality, our approach avoids arbitrary thresholds and allows quantification of meaningful and reliable network components that may prove to be of high relevance for basic and clinical research applications.

Time-frequency signatures evoked by single-pulse deep brain stimulation to the subcallosal cingulate.

Precision targeting of specific white matter bundles that traverse the subcallosal cingulate (SCC) has been linked to efficacy of deep brain stimulation (DBS) for treatment resistant depression (TRD). Methods to confirm optimal target engagement in this heterogenous region are now critical to establish an objective treatment protocol. As yet unexamined are the time-frequency features of the SCC evoked potential (SCC-EP), including spectral power and phase-clustering. We examined these spectral features-evoked power and phase clustering-in a sample of TRD patients (n = 8) with implanted SCC stimulators. Electroencephalogram (EEG) was recorded during wakeful rest. Location of electrical stimulation in the SCC target region was the experimental manipulation. EEG was analyzed at the surface level with an average reference for a cluster of frontal sensors and at a time window identified by prior study (50-150 ms). Morlet wavelets generated indices of evoked power and inter-trial phase clustering. Enhanced phase clustering at theta frequency (4-7 Hz) was observed in every subject and was significantly correlated with SCC-EP magnitude, but only during left SCC stimulation. Stimulation to dorsal SCC evinced stronger phase clustering than ventral SCC. There was a weak correlation between phase clustering and white matter density. An increase in evoked delta power (2-4 Hz) was also coincident with SCC-EP, but was less consistent across participants. DBS evoked time-frequency features index mm-scale changes to the location of stimulation in the SCC target region and correlate with structural characteristics implicated in treatment optimization. Results also imply a shared generative mechanism (inter-trial phase clustering) between evoked potentials evinced by electrical stimulation and evoked potentials evinced by auditory/visual stimuli and behavioral tasks. Understanding how current injection impacts downstream cortical activity is essential to building new technologies that adapt treatment parameters to individual differences in neurophysiology.

Performance monitoring in obsessive-compulsive disorder: Insights from internal capsule/nucleus accumbens deep brain stimulation.

BACKGROUND: Symptoms of obsessive-compulsive disorder (OCD) are partly related to impaired cognitive control processes and theta modulations constitute an important electrophysiological marker for cognitive control processes such as signaling negative performance feedback in a fronto-striatal network. Deep brain stimulation (DBS) targeting the anterior limb of the internal capsule (ALIC)/nucleus accumbens (NAc) shows clinical efficacy in OCD, while the exact influence on the performance monitoring system remains largely unknown. METHODS: Seventeen patients with treatment-refractory OCD performed a probabilistic reinforcement learning task. Analyses were focused on 4-8 Hz (theta) power, intertrial phase coherence (ITPC) and debiased weighted Phase-Lag Index (dwPLI) in response to negative performance feedback. Combined EEG and local field potential (LFP) recordings were obtained shortly after DBS electrode implantation to investigate fronto-striatal network modulations. To assess the impact of clinically effective DBS on negative performance feedback modulations, EEG recordings were obtained pre-surgery and at follow-up with DBS on and off. RESULTS: Medial frontal cortex ITPC, striatal ITPC and striato-frontal dwPLI were increased following negative performance feedback. Decreased right-lateralized dwPLI was associated with pre-surgery symptom severity. ITPC was globally decreased during DBS-off. CONCLUSION: We observed a theta phase coherence mediated fronto-striatal performance monitoring network. Within this network, decreased connectivity was related to increased OCD symptomatology, consistent with the idea of impaired cognitive control in OCD. While ALIC/NAc DBS decreased theta network activity globally, this effect was unrelated to clinical efficacy and performance monitoring.

Transcranial Focused Ultrasound to the Right Prefrontal Cortex Improves Mood and Alters Functional Connectivity in Humans.

Transcranial focused ultrasound (tFUS) is an emerging method for non-invasive neuromodulation akin to transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). tFUS offers several advantages over electromagnetic methods including high spatial resolution and the ability to reach deep brain targets. Here we describe two experiments assessing whether tFUS could modulate mood in healthy human volunteers by targeting the right inferior frontal gyrus (rIFG), an area implicated in mood and emotional regulation. In a randomized, placebo-controlled, double-blind study, participants received 30 s of 500 kHz tFUS or a placebo control. Visual Analog Mood Scales (VAMS) assessed mood four times within an hour (baseline and three times after tFUS). Participants who received tFUS reported an overall increase in Global Affect (GA), an aggregate score from the VAMS scale, indicating a positive shift in mood. Experiment 2 examined resting-state functional (FC) connectivity using functional magnetic resonance imaging (fMRI) following 2 min of 500 kHz tFUS at the rIFG. As in Experiment 1, tFUS enhanced self-reported mood states and also decreased FC in resting state networks related to emotion and mood regulation. These results suggest that tFUS can be used to modulate mood and emotional regulation networks in the prefrontal cortex.

Frontal theta and posterior alpha in resting EEG: A critical examination of convergent and discriminant validity.

Prior research has identified two resting EEG biomarkers with potential for predicting functional outcomes in depression: theta current density in frontal brain regions (especially rostral anterior cingulate cortex) and alpha power over posterior scalp regions. As little is known about the discriminant and convergent validity of these putative biomarkers, a thorough evaluation of these psychometric properties was conducted toward the goal of improving clinical utility of these markers. Resting 71-channel EEG recorded from 35 healthy adults at two sessions (1-week retest) were used to systematically compare different quantification techniques for theta and alpha sources at scalp (surface Laplacian or current source density [CSD]) and brain (distributed inverse; exact low resolution electromagnetic tomography [eLORETA]) level. Signal quality was evaluated with signal-to-noise ratio, participant-level spectra, and frequency PCA covariance decomposition. Convergent and discriminant validity were assessed within a multitrait-multimethod framework. Posterior alpha was reliably identified as two spectral components, each with unique spatial patterns and condition effects (eyes open/closed), high signal quality, and good convergent and discriminant validity. In contrast, frontal theta was characterized by one low-variance component, low signal quality, lack of a distinct spectral peak, and mixed validity. Correlations between candidate biomarkers suggest that posterior alpha components constitute reliable, convergent, and discriminant biometrics in healthy adults. Component-based identification of spectral activity (CSD/eLORETA-fPCA) was superior to fixed, a priori frequency bands. Improved quantification and conceptualization of frontal theta is necessary to determine clinical utility.

Intracranial source activity (eLORETA) related to scalp-level asymmetry scores and depression status.

Frontal EEG alpha asymmetry provides a promising index of depression risk, yet very little is known about the neural sources of alpha asymmetry. To identify these sources, this study examined alpha asymmetry using a distributed inverse solution: exact low resolution brain electromagnetic tomography (eLORETA). Findings implicated a generator in lateral midfrontal regions that contributed to both surface asymmetry and depression risk. Participants with any lifetime history of depressive episodes were characterized by less left than right activity in the precentral gyrus and midfrontal gyrus. Anhedonia accounted for a significant portion of the relationship between alpha asymmetry and lifetime major depressive disorder. Results are suggestive of convergence between motivational and capability models of asymmetry and replicate results from experimental studies in a large resting-state data set. The capability model of frontal alpha asymmetry is contextualized in terms of motor preparedness following emotional mobilization.

Assessing and conceptualizing frontal EEG asymmetry: An updated primer on recording, processing, analyzing, and interpreting frontal alpha asymmetry.

Frontal electroencephalographic (EEG) alpha asymmetry is widely researched in studies of emotion, motivation, and psychopathology, yet it is a metric that has been quantified and analyzed using diverse procedures, and diversity in procedures muddles cross-study interpretation. The aim of this article is to provide an updated tutorial for EEG alpha asymmetry recording, processing, analysis, and interpretation, with an eye towards improving consistency of results across studies. First, a brief background in alpha asymmetry findings is provided. Then, some guidelines for recording, processing, and analyzing alpha asymmetry are presented with an emphasis on the creation of asymmetry scores, referencing choices, and artifact removal. Processing steps are explained in detail, and references to MATLAB-based toolboxes that are helpful for creating and investigating alpha asymmetry are noted. Then, conceptual challenges and interpretative issues are reviewed, including a discussion of alpha asymmetry as a mediator/moderator of emotion and psychopathology. Finally, the effects of two automated component-based artifact correction algorithms-MARA and ADJUST-on frontal alpha asymmetry are evaluated.

Patterns of alpha asymmetry in those with elevated worry, trait anxiety, and obsessive-compulsive symptoms: A test of the worry and avoidance models of alpha asymmetry.

Some authors have argued that worry cues lateralization of frontal brain activity leftward, whereas other varieties of avoidance motivation cue lateralization of frontal brain activity rightward. By comparison, more right-than-left parietal activity correlates with anxious arousal. The purpose of the present report was to test two models of brain lateralization and anxiety: one model that proposed that worry correlates with more left-frontal activity and another model that proposed that avoidance motivation (including worry) correlates with more right-frontal activity. Undergraduate students were selected for worry, obsessive-compulsive symptoms, and trait anxiety using self-report questionnaires. A subset of participants also met DSM-IV criteria for Generalized Anxiety Disorder (GAD) or Obsessive-Compulsive Disorder (OCD). Alpha asymmetry and also a global-power-adjusted metric of alpha power were calculated from each participant's resting-state EEG. It was expected that participants with elevated worry and participants meeting criteria for GAD would show more left-than-right frontal activity. In contrast, participants with elevated trait anxiety, obsessive-compulsive symptoms, and those with an OCD diagnosis were expected to exhibit more right-than-left frontal activity. Participants with elevated worry, participants with a GAD diagnosis, and participants with elevated obsessive-compulsive symptoms, had more left frontal activity than low symptom individuals. Those with high scores on trait anxiety, but low worry, had greater right frontal and parietal activity compared to controls. The present results suggest that brain lateralization is not solely related to avoidance motivation, and suggest that facets of anxiety may cut across dimensions not well-represented by DSM-based categories.