Functional MRI and sensory evaluation of central mechanisms of chronic pain associated with Lyme disease, Stanford University (2018 - 2020)
Lyme disease is an emerging tick-borne infectious disease. It is a multisystem disorder associated with several symptoms including pain, fatigue, depression, and cognitive impairments. Importantly, there can be differences in clinical symptoms, particularly with regard to pain. For some patients, initial pain symptoms resolve early, but for others, chronic pain develops.
In order to understand why some patients develop chronic pain and others do not, we are currently recruiting adults with chronic Lyme disease to participate in a research study investigating the central mechanisms of pain using sensory testing and brain imaging (MRI). If you have been diagnosed with Lyme disease for at least one year, please complete a brief survey by clicking on the "Lyme Survey" link under the For More Information section below.
If you have trouble accessing the link, please email email@example.com or call 650-497-5704 and we will be happy to assist.
Stanford University, Palo Alto, CA.
For More Information:
Investigating the role of GABA and glutamate on anterior cingulate activity associated with hypnosis, Stanford University (1/2017 - 8/2018)
Hypnosis is a powerful evidence-based tool for the treatment of many disorders. Hypnotizability is a stable trait over time suggesting neurophysiological factors underlying hypnotic responsiveness. We have previously shown differential brain activity in the anterior cingulate cortex (ACC) in high vs. low hypnotizable individuals. For this study, we are assessing levels of inhibitory (GABA) and excitatory (glutamate) neurotransmitters in the ACC of healthy individuals to determine if these measures are also associated with level of hypnotizability.
Stanford University, Palo Alto, CA.
Three Dimensions of Association Link Migraine Symptoms and Functional Connectivity.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Migraine is a heterogeneous disorder with variable symptoms and responsiveness to therapy. Due to previous analytic shortcomings, variance in migraine symptoms has been inconsistently related to brain function. In the current analysis we used data from two sites (n=143, male and female humans), and performed Canonical Correlation Analysis (CCA), relating resting-state functional connectivity (RSFC) with a broad range of migraine symptoms ranging from headache characteristics to sleep abnormalities. This identified three dimensions of covariance between symptoms and RSFC. The first dimension related to headache intensity, headache frequency, pain catastrophizing, affect, sleep disturbances, and somatic abnormalities, and was associated with frontoparietal and dorsal attention network connectivity, both of which are major cognitive networks. Additionally, RSFC scores from this dimension - both the baseline value and the change from baseline to post-intervention - were associated with responsiveness to mind-body therapy. The second dimension was related to an inverse association between pain and anxiety, and to default mode network connectivity. The final dimension was related to pain catastrophizing, and salience, sensorimotor and default mode network connectivity. In addition to performing CCA, we evaluated the current clustering of migraine patients into episodic and chronic subtypes, and found no evidence to support this clustering. However, when using RSFC scores from the three significant dimensions, we identified a novel clustering of migraine patients into four biotypes with unique functional connectivity patterns. These findings provide new insight into individual variability in migraine, and could serve as the foundation for novel therapies that take advantage of migraine heterogeneity.SIGNIFICANCE STATEMENTUsing a large multi-site dataset of migraine patients we identified three dimensions of multivariate association between symptoms and functional connectivity. This analysis revealed neural networks that relate to all measured symptoms, but also to specific symptom ensembles, such as patient propensity to catastrophize painful events. Using these three dimensions, we found four biotypes of migraine informed by clinical and neural variation together. Such findings pave the way for precision medicine therapy for migraine.
View details for DOI 10.1523/JNEUROSCI.1796-21.2022
View details for PubMedID 35768210
Altered Functional Network Connectivity in Chronic Migraine: a Replication-Extension Study
LIPPINCOTT WILLIAMS & WILKINS. 2021
View details for Web of Science ID 000729283605040
Insights into chronic migraine pathophysiology - what measures of gray matter reveal.
Cephalalgia : an international journal of headache
View details for DOI 10.1177/0333102420933263
View details for PubMedID 32536267
Association between Anterior Cingulate Neurochemical Concentration and Individual Differences in Hypnotizability.
Cerebral cortex (New York, N.Y. : 1991)
Hypnosis is the oldest form of Western psychotherapy and a powerful evidence-based treatment for numerous disorders. Hypnotizability is variable between individuals; however, it is a stable trait throughout adulthood, suggesting that neurophysiological factors may underlie hypnotic responsiveness. One brain region of particular interest in functional neuroimaging studies of hypnotizability is the anterior cingulate cortex (ACC). Here, we examined the relationships between the neurochemicals, GABA, and glutamate, in the ACC and hypnotizability in healthy individuals. Participants underwent a magnetic resonance imaging (MRI) session, whereby T1-weighted anatomical and MEGA-PRESS spectroscopy scans were acquired. Voxel placement over the ACC was guided by a quantitative meta-analysis of functional neuroimaging studies of hypnosis. Hypnotizability was assessed using the Hypnotic Induction Profile (HIP), and self-report questionnaires to assess absorption (TAS), dissociation (DES), and negative affect were completed. ACC GABA concentration was positively associated with HIP scores such that the higher the GABA concentration, the more hypnotizable an individual. An exploratory analysis of questionnaire subscales revealed a negative relationship between glutamate and the absorption and imaginative involvement subscale of the DES. These results provide a putative neurobiological basis for individual differences in hypnotizability and can inform our understanding of treatment response to this growing psychotherapeutic tool.
View details for DOI 10.1093/cercor/bhz332
View details for PubMedID 32108220
MCADNNet: Recognizing Stages of Cognitive Impairment through Efficient Convolutional fMRI and MRI Neural Network Topology Models.
IEEE access : practical innovations, open solutions
2019; 7: 155584-155600
Mild cognitive impairment (MCI) represents the intermediate stage between normal cerebral aging and dementia associated with Alzheimer's disease (AD). Early diagnosis of MCI and AD through artificial intelligence has captured considerable scholarly interest; researchers hope to develop therapies capable of slowing or halting these processes. We developed a state-of-the-art deep learning algorithm based on an optimized convolutional neural network (CNN) topology called MCADNNet that simultaneously recognizes MCI, AD, and normally aging brains in adults over the age of 75 years, using structural and functional magnetic resonance imaging (fMRI) data. Following highly detailed preprocessing, four-dimensional (4D) fMRI and 3D MRI were decomposed to create 2D images using a lossless transformation, which enables maximum preservation of data details. The samples were shuffled and subject-level training and testing datasets were completely independent. The optimized MCADNNet was trained and extracted invariant and hierarchical features through convolutional layers followed by multi-classification in the last layer using a softmax layer. A decision-making algorithm was also designed to stabilize the outcome of the trained models. To measure the performance of classification, the accuracy rates for various pipelines were calculated before and after applying the decision-making algorithm. Accuracy rates of 99.77% 0.36% and 97.5% 1.16% were achieved for MRI and fMRI pipelines, respectively, after applying the decision-making algorithm. In conclusion, a cutting-edge and optimized topology called MCADNNet was designed and preceded a preprocessing pipeline; this was followed by a decision-making step that yielded the highest performance achieved for simultaneous classification of the three cohorts examined.
View details for DOI 10.1109/ACCESS.2019.2949577
View details for PubMedID 32021737
View details for PubMedCentralID PMC6999050
Imaging in CDH
Chronic Headache: A Comprehensive Guide to Evaluation and Management
Springer. 2019; 1st: 157–168
View details for DOI DOI: 10.1007/978-3-319-91491-6_11
Altered structural brain network topology in chronic migraine.
Brain structure & function
Despite its prevalence and high disease burden, the pathophysiological mechanisms underlying chronic migraine (CM) are not well understood. As CM is a complex disorder associated with a range of sensory, cognitive, and affective comorbidities, examining structural network disruption may provide additional insights into CM symptomology beyond studies of focal brain regions. Here, we compared structural interconnections in patients with CM (n = 52) and healthy controls (HC) (n = 48) using MRI measures of cortical thickness and subcortical volume combined with graph theoretical network analyses. The analysis focused on both local (nodal) and global measures of topology to examine network integration, efficiency, centrality, and segregation. Our results indicated that patients with CM had altered global network properties that were characterized as less integrated and efficient (lower global and local efficiency) and more highly segregated (higher transitivity). Patients also demonstrated aberrant local network topology that was less integrated (higher path length), less central (lower closeness centrality), less efficient (lower local efficiency) and less segregated (lower clustering). These network differences not only were most prominent in the limbic and insular cortices but also occurred in frontal, temporal, and brainstem regions, and occurred in the absence of group differences in focal brain regions. Taken together, examining structural correlations between brain areas may be a more sensitive means to detect altered brain structure and understand CM symptomology at the network level. These findings contribute to an increased understanding of structural connectivity in CM and provide a novel approach to potentially track and predict the progression of migraine disorders.This study is registered on ClinicalTrials.gov (Identifier: NCT03304886).
View details for DOI 10.1007/s00429-019-01994-7
View details for PubMedID 31792696
High-dose spaced theta-burst TMS as a rapid-acting antidepressant in highly refractory depression.
Brain : a journal of neurology
View details for PubMedID 29415152
- Transcranial Magnetic Simulation for Disorders other than Depression Transcranial Magnetic Stimulation: Clinical Appllications for Psychiatric Practice American Psychiatric Association Publishing. 2018: 157–172
Structural Magnetic Resonance Imaging Can Identify Trigeminal System Abnormalities in Classical Trigeminal Neuralgia
FRONTIERS IN NEUROANATOMY
Classical trigeminal neuralgia (TN) is a chronic pain disorder that has been described as one of the most severe pains one can suffer. The most prevalent theory of TN etiology is that the trigeminal nerve is compressed at the root entry zone (REZ) by blood vessels. However, there is significant evidence showing a lack of neurovascular compression (NVC) for many cases of classical TN. Furthermore, a considerable number of patients who are asymptomatic have MR evidence of NVC. Since there is no validated animal model that reproduces the clinical features of TN, our understanding of TN pathology mainly comes from biopsy studies that have limitations. Sophisticated structural MRI techniques including diffusion tensor imaging provide new opportunities to assess the trigeminal nerves and CNS to provide insight into TN etiology and pathogenesis. Specifically, studies have used high-resolution structural MRI methods to visualize patterns of trigeminal nerve-vessel relationships and to detect subtle pathological features at the trigeminal REZ. Structural MRI has also identified CNS abnormalities in cortical and subcortical gray matter and white matter and demonstrated that effective neurosurgical treatment for TN is associated with a reversal of specific nerve and brain abnormalities. In conclusion, this review highlights the advanced structural neuroimaging methods that are valuable tools to assess the trigeminal system in TN and may inform our current understanding of TN pathology. These methods may in the future have clinical utility for the development of neuroimaging-based biomarkers of TN.
View details for DOI 10.3389/finana.2016.0095
View details for Web of Science ID 000385677500001
View details for PubMedID 27807409
View details for PubMedCentralID PMC5070392
Individual Differences in Temporal Summation of Pain Reflect Pronociceptive and Antinociceptive Brain Structure and Function.
The Journal of neuroscience : the official journal of the Society for Neuroscience
2015; 35 (26): 9689-700
Temporal summation of pain (TSP), the perception of increasingly greater pain evoked by repetitive noxious stimuli, is highly variable between individuals. Individuals with facilitated pain processing and/or reduced pain-modulatory capabilities are regarded as pronociceptive, whereas individuals with reduced pain processing capacity are characterized as antinociceptive. Brodmann area (BA) 3a of the primary somatosensory cortex is part of an ascending pathway from the sensory thalamus that mediates TSP. Descending pain modulation involves projections from the subgenual anterior cingulate cortex (sgACC) to the periaqueductal gray to the rostral ventromedial medulla (RVM). Here, we tested the hypothesis that pronociceptive individuals have an enhanced TSP response compared with antinociceptive individuals, marked by facilitated ascending nociceptive processing and/or reduced capacity for descending pain modulation. Eighty healthy humans were tested with a TSP protocol and underwent structural and resting-state functional magnetic resonance imaging. We found large interindividual differences in TSP responses, which were positively correlated with functional connectivity (FC) between individuals' right sensory thalamus with their BA 3a (thal-BA 3a), and with cortical thickness in their insula and medial prefrontal cortex. In contrast, TSP was negatively correlated with FC between individuals' RVM with their sgACC (RVM-sgACC). When subjects were grouped as pronociceptive or antinociceptive based on whether they had greater thal-BA 3a or RVM-sgACC FC respectively, pronociceptive subjects showed greater TSP responses. Furthermore, TSP was positively correlated with the extent of imbalance toward ascending nociceptive processing. Our study indicates that individuals with enhanced TSP have facilitated ascending nociceptive processing and reduced pain-modulatory capacities.This study provides novel evidence that an individual's propensity to experience amplified pain with repeated stimuli [i.e., temporal summation of pain (TSP)] reflects attributes of their "pain connectome," namely stronger ascending nociceptive and weaker descending pain-modulatory components. Understanding the individual neural mechanisms underlying TSP within individuals has implications for developing personalized pain-management strategies for chronic pain.
View details for DOI 10.1523/JNEUROSCI.5039-14.2015
View details for PubMedID 26134651
Reversal of insular and microstructural nerve abnormalities following effective surgical treatment for trigeminal neuralgia.
2015; 156 (6): 1112-23
Classical trigeminal neuralgia (TN) is a severe neuropathic facial pain disorder commonly associated with neurovascular compression at the trigeminal nerve root entry zone (REZ). Neurosurgical interventions can relieve TN pain, but the mechanisms underlying these effects are unknown. We determined whether the abnormalities we previously reported at the REZ of TN patients using diffusion tensor imaging (DTI) and brain gray matter (GM) analyses resolve after effective neurosurgical treatment. Twenty-five patients who underwent either microvascular decompression surgery or Gamma Knife radiosurgery for right-sided TN had magnetic resonance imaging scans before and after treatment and were compared with age-matched controls. Cortical thickness and voxel-based morphometry examined specific brain GM we previously reported as abnormal in TN. White matter metrics of fractional anisotropy (FA), mean, radial, and axial diffusivities (MD, RD, and AD, respectively) were extracted bilaterally from each trigeminal REZ. Before treatment, patients had widespread GM abnormalities including thinner ventral anterior insula (vAI) cortex, and REZ microstructural abnormalities (lower FA, and higher MD, RD, and AD) compared with controls. We considered a 75% reduction in pain as effective treatment. The right vAI was the only GM region that normalized toward the level of healthy controls after effective treatment. At the REZ, effective treatment reversed FA, MD, RD, and AD abnormalities and was correlated with pain relief after treatment. These results demonstrate that treatment can effectively resolve pain by normalizing REZ abnormalities, which may influence vAI abnormalities. Future studies should consider DTI as an adjunct to assess the patient outcome and subtle microstructural changes after treatment.
View details for DOI 10.1097/j.pain.0000000000000156
View details for PubMedID 25782366
Diffusivity signatures characterize trigeminal neuralgia associated with multiple sclerosis.
Multiple sclerosis (Houndmills, Basingstoke, England)
Trigeminal neuralgia secondary to multiple sclerosis (MS-TN) is a facial neuropathic pain syndrome similar to classic trigeminal neuralgia (TN). While TN is caused by neurovascular compression of the fifth cranial nerve (CN V), how MS-related demyelination correlates with pain in MS-TN is not understood.We aim to examine diffusivities along CN V in MS-TN, TN, and controls in order to reveal differential neuroimaging correlates across groups.3T MR diffusion weighted, T1, T2 and FLAIR sequences were acquired for MS-TN, TN, and controls. Multi-tensor tractography was used to delineate CN V across cisternal, root entry zone (REZ), pontine and peri-lesional segments. Diffusion metrics including fractional anisotropy (FA), and radial (RD), axial (AD), and mean diffusivities (MD) were measured from each segment.CN V segments showed distinctive diffusivity patterns. The TN group showed higher FA in the cisternal segment ipsilateral to the side of pain, and lower FA in the ipsilateral REZ segment. The MS-TN group showed lower FA in the ipsilateral peri-lesional segments, suggesting differential microstructural changes along CN V in these conditions.The study demonstrates objective differences in CN V microstrucuture in TN and MS-TN using non-invasive neuroimaging. This represents a significant improvement in the methods currently available to study pain in MS.
View details for DOI 10.1177/1352458515579440
View details for PubMedID 25921052
Abnormal trigeminal nerve microstructure and brain white matter in idiopathic trigeminal neuralgia.
2014; 155 (1): 37-44
Idiopathic trigeminal neuralgia (TN) is classically associated with neurovascular compression (NVC) of the trigeminal nerve at the root entry zone (REZ), but NVC-induced structural alterations are not always apparent on conventional imaging. Previous studies report lower fractional anisotropy (FA) in the affected trigeminal nerves of TN patients using diffusion tensor imaging (DTI). However, it is not known if TN patients have trigeminal nerve abnormalities of mean, radial, or axial diffusivity (MD, RD, AD - metrics linked to neuroinflammation and edema) or brain white matter (WM) abnormalities. DTI scans in 18 right-sided TN patients and 18 healthy controls were retrospectively analyzed to extract FA, RD, AD, and MD from the trigeminal nerve REZ, and Tract-Based Spatial Statistics (TBSS) was used to assess brain WM. In patients, the affected trigeminal nerve had lower FA, and higher RD, AD, and MD was found bilaterally compared to controls. Group TBSS (P<0.05, corrected) showed patients had lower FA and increased RD, MD, and AD in brain WM connecting areas involved in the sensory and cognitive-affective dimensions of pain, attention, and motor functions, including the corpus callosum, cingulum, posterior corona radiata, and superior longitudinal fasciculus. These data indicate that TN patients have abnormal tissue microstructure in their affected trigeminal nerves, and as a possible consequence, WM microstructural alterations in the brain. These findings suggest that trigeminal nerve structural abnormalities occur in TN, even if not apparent on gross imaging. Furthermore, MD and RD findings suggest that neuroinflammation and edema may contribute to TN pathophysiology.
View details for DOI 10.1016/j.pain.2013.08.029
View details for PubMedID 23999058
Sensorimotor and Pain Modulation Brain Abnormalities in Trigeminal Neuralgia: A Paroxysmal, Sensory-Triggered Neuropathic Pain.
2013; 8 (6): e66340
Idiopathic trigeminal neuralgia (TN) is characterized by paroxysms of severe facial pain but without the major sensory loss that commonly accompanies neuropathic pain. Since neurovascular compression of the trigeminal nerve root entry zone does not fully explain the pathogenesis of TN, we determined whether there were brain gray matter abnormalities in a cohort of idiopathic TN patients. We used structural MRI to test the hypothesis that TN is associated with altered gray matter (GM) in brain areas involved in the sensory and affective aspects of pain, pain modulation, and motor function. We further determined the contribution of long-term TN on GM plasticity.Cortical thickness and subcortical GM volume were measured from high-resolution 3T T1-weighted MRI scans in 24 patients with right-sided TN and 24 healthy control participants.TN patients had increased GM volume in the sensory thalamus, amygdala, periaqueductal gray, and basal ganglia (putamen, caudate, nucleus accumbens) compared to healthy controls. The patients also had greater cortical thickness in the contralateral primary somatosensory cortex and frontal pole compared to controls. In contrast, patients had thinner cortex in the pregenual anterior cingulate cortex, the insula and the orbitofrontal cortex. No relationship was observed between GM abnormalities and TN pain duration.TN is associated with GM abnormalities in areas involved in pain perception, pain modulation and motor function. These findings may reflect increased nociceptive input to the brain, an impaired descending modulation system that does not adequately inhibit pain, and increased motor output to control facial movements to limit pain attacks.
View details for DOI 10.1371/journal.pone.0066340
View details for PubMedID 23823184
View details for PubMedCentralID PMC3688879
OViTAD: Optimized Vision Transformer to Predict Various Stages of Alzheimer's Disease Using Resting-State fMRI and Structural MRI Data.
2023; 13 (2)
Advances in applied machine learning techniques for neuroimaging have encouraged scientists to implement models to diagnose brain disorders such as Alzheimer's disease at early stages. Predicting the exact stage of Alzheimer's disease is challenging; however, complex deep learning techniques can precisely manage this. While successful, these complex architectures are difficult to interrogate and computationally expensive. Therefore, using novel, simpler architectures with more efficient pattern extraction capabilities, such as transformers, is of interest to neuroscientists. This study introduced an optimized vision transformer architecture to predict the group membership by separating healthy adults, mild cognitive impairment, and Alzheimer's brains within the same age group (>75 years) using resting-state functional (rs-fMRI) and structural magnetic resonance imaging (sMRI) data aggressively preprocessed by our pipeline. Our optimized architecture, known as OViTAD is currently the sole vision transformer-based end-to-end pipeline and outperformed the existing transformer models and most state-of-the-art solutions. Our model achieved F1-scores of 97%±0.0 and 99.55%±0.39 from the testing sets for the rs-fMRI and sMRI modalities in the triple-class prediction experiments. Furthermore, our model reached these performances using 30% fewer parameters than a vanilla transformer. Furthermore, the model was robust and repeatable, producing similar estimates across three runs with random data splits (we reported the averaged evaluation metrics). Finally, to challenge the model, we observed how it handled increasing noise levels by inserting varying numbers of healthy brains into the two dementia groups. Our findings suggest that optimized vision transformers are a promising and exciting new approach for neuroimaging applications, especially for Alzheimer's disease prediction.
View details for DOI 10.3390/brainsci13020260
View details for PubMedID 36831803
Screening for Generalized Anxiety Disorder From Acoustic and Linguistic Features of Impromptu Speech: Prediction Model Evaluation Study.
JMIR formative research
2022; 6 (10): e39998
BACKGROUND: Frequent interaction with mental health professionals is required to screen, diagnose, and track mental health disorders. However, high costs and insufficient access can make frequent interactions difficult. The ability to assess a mental health disorder passively and at frequent intervals could be a useful complement to the conventional treatment. It may be possible to passively assess clinical symptoms with high frequency by characterizing speech alterations collected using personal smartphones or other wearable devices. The association between speech features and mental health disorders can be leveraged as an objective screening tool.OBJECTIVE: This study aimed to evaluate the performance of a model that predicts the presence of generalized anxiety disorder (GAD) from acoustic and linguistic features of impromptu speech on a larger and more generalizable scale than prior studies did.METHODS: A total of 2000 participants were recruited, and they participated in a single web-based session. They completed the Generalized Anxiety Disorder-7 item scale assessment and provided an impromptu speech sample in response to a modified version of the Trier Social Stress Test. We used the linguistic and acoustic features that were found to be associated with anxiety disorders in previous studies along with demographic information to predict whether participants fell above or below the screening threshold for GAD based on the Generalized Anxiety Disorder-7 item scale threshold of 10. Separate models for each sex were also evaluated. We reported the mean area under the receiver operating characteristic (AUROC) from a repeated 5-fold cross-validation to evaluate the performance of the models.RESULTS: A logistic regression model using only acoustic and linguistic speech features achieved a significantly greater prediction accuracy than a random model did (mean AUROC 0.57, SD 0.03; P<.001). When separately assessing samples from female participants, we observed a mean AUROC of 0.55 (SD 0.05; P=.01). The model constructed from the samples from male participants achieved a mean AUROC of 0.57 (SD 0.07; P=.002). The mean AUROC increased to 0.62 (SD 0.03; P<.001) on the all-sample data set when demographic information (age, sex, and income) was included, indicating the importance of demographics when screening for anxiety disorders. The performance also increased for the female sample to a mean of 0.62 (SD 0.04; P<.001) when using demographic information (age and income). An increase in performance was not observed when demographic information was added to the model constructed from the male samples.CONCLUSIONS: A logistic regression model using acoustic and linguistic speech features, which have been suggested to be associated with anxiety disorders in prior studies, can achieve above-random accuracy for predicting GAD. Importantly, the addition of basic demographic variables further improves model performance, suggesting a role for speech and demographic information to be used as automated, objective screeners of GAD.
View details for DOI 10.2196/39998
View details for PubMedID 36306165
Acoustic and Linguistic Features of Impromptu Speech and Their Association With Anxiety: Validation Study
JMIR MENTAL HEALTH
2022; 9 (7): e36828
The measurement and monitoring of generalized anxiety disorder requires frequent interaction with psychiatrists or psychologists. Access to mental health professionals is often difficult because of high costs or insufficient availability. The ability to assess generalized anxiety disorder passively and at frequent intervals could be a useful complement to conventional treatment and help with relapse monitoring. Prior work suggests that higher anxiety levels are associated with features of human speech. As such, monitoring speech using personal smartphones or other wearable devices may be a means to achieve passive anxiety monitoring.This study aims to validate the association of previously suggested acoustic and linguistic features of speech with anxiety severity.A large number of participants (n=2000) were recruited and participated in a single web-based study session. Participants completed the Generalized Anxiety Disorder 7-item scale assessment and provided an impromptu speech sample in response to a modified version of the Trier Social Stress Test. Acoustic and linguistic speech features were a priori selected based on the existing speech and anxiety literature, along with related features. Associations between speech features and anxiety levels were assessed using age and personal income as covariates.Word count and speaking duration were negatively correlated with anxiety scores (r=-0.12; P<.001), indicating that participants with higher anxiety scores spoke less. Several acoustic features were also significantly (P<.05) associated with anxiety, including the mel-frequency cepstral coefficients, linear prediction cepstral coefficients, shimmer, fundamental frequency, and first formant. In contrast to previous literature, second and third formant, jitter, and zero crossing rate for the z score of the power spectral density acoustic features were not significantly associated with anxiety. Linguistic features, including negative-emotion words, were also associated with anxiety (r=0.10; P<.001). In addition, some linguistic relationships were sex dependent. For example, the count of words related to power was positively associated with anxiety in women (r=0.07; P=.03), whereas it was negatively associated with anxiety in men (r=-0.09; P=.01).Both acoustic and linguistic speech measures are associated with anxiety scores. The amount of speech, acoustic quality of speech, and gender-specific linguistic characteristics of speech may be useful as part of a system to screen for anxiety, detect relapse, or monitor treatment.
View details for DOI 10.2196/36828
View details for Web of Science ID 000848666800002
View details for PubMedID 35802401
View details for PubMedCentralID PMC9308078
Who does what to whom? graph representations of action-predication in speech relate to psychopathological dimensions of psychosis.
Schizophrenia (Heidelberg, Germany)
2022; 8 (1): 58
Graphical representations of speech generate powerful computational measures related to psychosis. Previous studies have mostly relied on structural relations between words as the basis of graph formation, i.e., connecting each word to the next in a sequence of words. Here, we introduced a method of graph formation grounded in semantic relationships by identifying elements that act upon each other (action relation) and the contents of those actions (predication relation). Speech from picture descriptions and open-ended narrative tasks were collected from a cross-diagnostic group of healthy volunteers and people with psychotic or non-psychotic disorders. Recordings were transcribed and underwent automated language processing, including semantic role labeling to identify action and predication relations. Structural and semantic graph features were computed using static and dynamic (moving-window) techniques. Compared to structural graphs, semantic graphs were more strongly correlated with dimensional psychosis symptoms. Dynamic features also outperformed static features, and samples from picture descriptions yielded larger effect sizes than narrative responses for psychosis diagnoses and symptom dimensions. Overall, semantic graphs captured unique and clinically meaningful information about psychosis and related symptom dimensions. These features, particularly when derived from semi-structured tasks using dynamic measurement, are meaningful additions to the repertoire of computational linguistic methods in psychiatry.
View details for DOI 10.1038/s41537-022-00263-7
View details for PubMedID 35853912
The burgeoning role of speech and language assessment in schizophrenia spectrum disorders.
View details for DOI 10.1017/S0033291722001325
View details for PubMedID 35582882
Brain and Physiological Markers of Autonomic Function Are Associated With Treatment-Related Improvements in Self-Reported Autonomic Dysfunction in Veterans With Gulf War Illness: An Exploratory Pilot Study.
Global advances in health and medicine
2020; 9: 2164956120922812
Background: Gulf War Illness (GWI) is a poorly understood condition characterized by a constellation of mood, cognitive, and physical symptoms. A growing body of evidence demonstrates autonomic nervous system (ANS) dysfunction. Few published treatment studies exist for GWI.Method: We recently completed a randomized controlled trial comparing a 10-week group yoga intervention to 10-week group cognitive behavioral therapy (CBT) for veterans with GWI. Here, we present exploratory data on ANS biomarkers of treatment response from a small pilot exploratory neurophysiological add-on study (n=13) within that larger study.Results: Findings suggest that veterans with GWI receiving either yoga or CBT for pain improved following treatment and that changes in biological ANS-especially for the yoga group-moved in the direction of healthy profiles: lower heart rate, higher square root of the mean squared differences between successive R-R intervals (RMSSD), greater parasympathetic activation/dominance (increased high-frequency heart rate variability [HF-HRV], decreased low-frequency/high-frequency [LF/HF] ratio), reduced right amygdala volume, and stronger amygdala-default mode/amygdala-salience network connectivity, both immediately posttreatment and at 6-month follow-up. Biological mechanisms of CBT appeared to underlie improvements in more psychologically loaded symptoms such as self-reported fatigue and energy. Higher tonic arousal and/or more sympathetic dominance (higher skin conductance, lower RMSSD, lower HF-HRV, higher LF/HF ratio) pretreatment predicted greater treatment-related improvements in self-reported ANS for both the yoga and CBT group.Conclusion: These exploratory pilot data provide preliminary support for the suggestion that treatment (yoga, CBT) is associated with improvements in both biological and self-reported ANS dysfunctions in GWI. The major limitation for these findings is the small sample size. Larger and more controlled studies are needed to replicate these findings and directly compare biomarkers of yoga versus CBT.
View details for DOI 10.1177/2164956120922812
View details for PubMedID 32426178
Aberrant Structural Network Architecture in Chronic Migraine
SAGE PUBLICATIONS LTD. 2019: 392
View details for Web of Science ID 000491167100058
Clinical Features Contributing to Cortical Thickness Changes in Chronic Migraine - A Pilot Study
2019; 59 (2): 180–91
View details for DOI 10.1111/head.13452
View details for Web of Science ID 000457474500004
High-Dose Spaced Theta-Burst Transcranial Magnetic Stimulation as a Rapid-Acting Anti- Depressant in Highly Refractory Depression
ELSEVIER SCIENCE INC. 2018: S191
View details for Web of Science ID 000432466300476
High-Dose Theta-Burst Transcranial Magnetic Stimulation Modulates Heart Rate Variability
ELSEVIER SCIENCE INC. 2018: S189
View details for Web of Science ID 000432466300472
Modulation of the Neural Circuitry Underlying Trait Hypnotizability With Spaced Continuous Theta-Burst Stimulation
NATURE PUBLISHING GROUP. 2017: S508–S509
View details for Web of Science ID 000416846303052
Comparison of Diffusion-Weighted MRI Reconstruction Methods for Visualization of Cranial Nerves in Posterior Fossa Surgery.
Frontiers in neuroscience
2017; 11: 554
Diffusion-weighted imaging (DWI)-based tractography has gained increasing popularity as a method for detailed visualization of white matter (WM) tracts. Different imaging techniques, and more novel, advanced imaging methods provide significant WM structural detail. While there has been greater focus on improving tract visualization for larger WM pathways, the relative value of each method for cranial nerve reconstruction and how this methodology can assist surgical decision-making is still understudied. Images from 10 patients with posterior fossa tumors (4 male, mean age: 63.5), affecting either the trigeminal nerve (CN V) or the facial/vestibular complex (CN VII/VIII), were employed. Three distinct reconstruction methods [two tensor-based methods: single diffusion tensor tractography (SDT) (3D Slicer), eXtended streamline tractography (XST), and one fiber orientation distribution (FOD)-based method: streamline tractography using constrained spherical deconvolution (CSD)-derived estimates (MRtrix3)], were compared to determine which of these was best suited for use in a neurosurgical setting in terms of processing speed, anatomical accuracy, and accurate depiction of the relationship between the tumor and affected CN. Computation of the tensor map was faster when compared to the implementation of CSD to provide estimates of FOD. Both XST and CSD-based reconstruction methods tended to give more detailed representations of the projections of CN V and CN VII/VIII compared to SDT. These reconstruction methods were able to more accurately delineate the course of CN V and CN VII/VIII, differentiate CN V from the cerebellar peduncle, and delineate compression of CN VII/VIII in situations where SDT could not. However, CSD-based reconstruction methods tended to generate more invalid streamlines. XST offers the best combination of anatomical accuracy and speed of reconstruction of cranial nerves within this patient population. Given the possible anatomical limitations of single tensor models, supplementation with more advanced tensor-based reconstruction methods might be beneficial.
View details for PubMedID 29062268
View details for PubMedCentralID PMC5640769
Journal Club: Exacerbation of headache during dihydroergotamine for chronic migraine does not alter outcome.
2016; 87 (16): e196-e198
Transient headache exacerbation during IV dihydroergotamine (DHE) therapy of migraine may prompt clinicians to prematurely discontinue DHE therapy, potentially depriving patients of the full benefit of DHE infusion. In a recent Neurology® article, Eller et al. evaluated whether or not worsening headache during DHE infusion was associated with suboptimal medium-term headache outcomes.
View details for PubMedID 27754915
Journal Club: Change in brain network connectivity during PACAP38-induced migraine attacks.
2016; 87 (16): e199-e202
View details for PubMedID 27754916
Discriminating neural representations of physical and social pains: how multivariate statistics challenge the 'shared representation' theory of pain.
Journal of neurophysiology
Overlapping functional magnetic resonance imaging (fMRI) activity elicited by physical pain and social rejection has posited a common neural representation between the two experiences. However, Woo and colleagues (Woo et al., 2014) recently used multivariate statistics to challenge the 'shared representation' theory of pain. This study has implications in the way results from fMRI studies are interpreted, and has the potential of broadening our understanding of different pain states and future development of personalized medicine.
View details for DOI 10.1152/jn.00075.2015
View details for PubMedID 25787949
Diffusion imaging in trigeminal neuralgia reveals abnormal trigeminal nerve and brain white matter.
2014; 155 (9): 1905-1906
View details for DOI 10.1016/j.pain.2014.05.026
View details for PubMedID 24880116
Making Sense of Gray Matter Abnormalities in Chronic Orofacial Pain-Synthesizing Divergent Findings
JOURNAL OF NEUROSCIENCE
2011; 31 (35): 12396-12397
View details for DOI 10.1523/JNEUROSCI.3103-11.2011
View details for Web of Science ID 000294451900002
View details for PubMedID 21880900
Use of Diffusion Tensor Imaging to Examine Subacute White Matter Injury Progression in Moderate to Severe Traumatic Brain Injury
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
2008; 89 (12): S45-S50
To demonstrate subacute progression of white matter (WM) injury (4.5mo-2.5y postinjury) in patients with traumatic brain injury using diffusion-tensor imaging.Prospective, repeated-measures, within-subjects design.Inpatient neurorehabilitation program and teaching hospital MRI department.Brain-injured adults (N=13) with a mean Glasgow Coma Scale score of 7.67+/-4.16.Not applicable.Fractional anisotropy (FA) values were measured at 4.5 and 29 months postinjury in right and left frontal and temporal deep WM tracts and the anterior and posterior corpus callosum.FA significantly decreased in frontal and temporal tracts: right frontal (.38+/-.06 to .30+/-.06; P<.005), left frontal (.37+/-.06 to .32+/-.06; P<.05), right temporal (.28+/-.05 to .22+/-.018; P<.005), and left temporal (.28+/-.05 to .24+/-.02; P<.05). No significant changes were in the corpus callosum.Preliminary results demonstrate progression of WM damage as evidenced by interval changes in diffusion anisotropy. Future research should examine the relationship between decreased FA and long-term clinical outcome.
View details for DOI 10.1016/j.apmr.2008.08.211
View details for Web of Science ID 000261999400006
View details for PubMedID 19081441