Noninvasive vagus nerve stimulation alters neural response and physiological autonomic tone to noxious thermal challenge.

The mechanisms by which noninvasive vagal nerve stimulation (nVNS) affect central and peripheral neural circuits that subserve pain and autonomic physiology are not clear, and thus remain an area of intense investigation. Effects of nVNS vs sham stimulation on subject responses to five noxious thermal stimuli (applied to left lower extremity), were measured in 30 healthy subjects (n = 15 sham and n = 15 nVNS), with fMRI and physiological galvanic skin response (GSR). With repeated noxious thermal stimuli a group × time analysis showed a significantly (p < .001) decreased response with nVNS in bilateral primary and secondary somatosensory cortices (SI and SII), left dorsoposterior insular cortex, bilateral paracentral lobule, bilateral medial dorsal thalamus, right anterior cingulate cortex, and right orbitofrontal cortex. A group × time × GSR analysis showed a significantly decreased response in the nVNS group (p < .0005) bilaterally in SI, lower and mid medullary brainstem, and inferior occipital cortex. Finally, nVNS treatment showed decreased activity in pronociceptive brainstem nuclei (e.g. the reticular nucleus and rostral ventromedial medulla) and key autonomic integration nuclei (e.g. the rostroventrolateral medulla, nucleus ambiguous, and dorsal motor nucleus of the vagus nerve). In aggregate, noninvasive vagal nerve stimulation reduced the physiological response to noxious thermal stimuli and impacted neural circuits important for pain processing and autonomic output

Toward Composite Pain Biomarkers of Neuropathic Pain—Focus on Peripheral Neuropathic Pain

Chronic pain affects ~10–20% of the U.S. population with an estimated annual cost of $600 billion, the most significant economic cost of any disease to-date. Neuropathic pain is a type of chronic pain that is particularly difficult to manage and leads to significant disability and poor quality of life. Pain biomarkers offer the possibility to develop objective pain-related indicators that may help diagnose, treat, and improve the understanding of neuropathic pain pathophysiology. We review neuropathic pain mechanisms related to opiates, inflammation, and endocannabinoids with the objective of identifying composite biomarkers of neuropathic pain. In the literature, pain biomarkers typically are divided into physiological non-imaging pain biomarkers and brain imaging pain biomarkers. We review both types of biomarker types with the goal of identifying composite pain biomarkers that may improve recognition and treatment of neuropathic pain

The Relationship between Amygdala Activation and Passive Exposure Time to an Aversive Cue during a Continuous Performance Task

The allocation of attention modulates negative emotional processing in the amygdala. However, the role of passive exposure time to emotional signals in the modulation of amygdala activity during active task performance has not been examined. In two functional Magnetic Resonance Imaging (fMRI) experiments conducted in two different groups of healthy human subjects, we examined activation in the amygdala due to cued anticipation of painful stimuli while subjects performed a simple continuous performance task (CPT) with either a fixed or a parametrically varied trial duration. In the first experiment (N = 16), engagement in the CPT during a task with fixed trial duration produced the expected attenuation of amygdala activation, but close analysis suggested that the attenuation occurred during the period of active engagement in CPT, and that amygdala activity increased proportionately during the remainder of each trial, when subjects were passively exposed to the pain cue. In the second experiment (N = 12), the duration of each trial was parametrically varied, and we found that amygdala activation was linearly related to the time of passive exposure to the anticipatory cue. We suggest that amygdala activation during negative anticipatory processing depends directly on the passive exposure time to the negative cue

AI-based dimensional neuroimaging system for characterizing heterogeneity in brain structure and function in major depressive disorder:COORDINATE-MDD consortium design and rationale

BACKGROUND: Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states. METHODS: We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants. RESULTS: We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites. CONCLUSION: We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project

The Parametric, Psychological, Neuropsychological, and Neuroanatomical Properties of Self and World Evaluation

Background: As an individual moves from adolescence to adulthood, they need to form a new sense of self as their environment changes from a limited to a more expansive structure. During this critical stage in development the last dramatic steps of neural development occur and numerous psychiatric conditions begin to manifest. Currently, there is no measure that aids in the quantification of how the individual is adapting to, and conceptualizing their role in, these new structures. To fill this gap we created the Self and World Evaluation Expressions Test(SWEET). Method: Sixty-five young adults (20.6 years-old), 36 with a history of drug use, completed the SWEET. A factor analysis was performed on the SWEET and the resultant factors were correlated with psychological, neuropsychological, and neuroanatomical battery that included both T1-wieghted and diffusion tensor magnetic resonance imaging scans. Results: We derived four factors: Self, Social-Emotional, Financial-Intellectual, and Spirituality. While showing limited relationships to psychological and neuropsychological measures, both white matter integrity and gray matter density showed significant relationships with SWEET factors. Conclusions: These findings suggest that while individual responses may not be indicative of psychological or cognitive processes they may relate to changes in brain structure. Several of these structures, such as the negative correlation of the affective impact of world with the dorsal anterior corpus callosum white matter integrity have been observed in psychiatri

Dynamical Principles of Emotion-Cognition Interaction: Mathematical Images of Mental Disorders

The key contribution of this work is to introduce a mathematical framework to understand self-organized dynamics in the brain that can explain certain aspects of itinerant behavior. Specifically, we introduce a model based upon the coupling of generalized Lotka-Volterra systems. This coupling is based upon competition for common resources. The system can be regarded as a normal or canonical form for any distributed system that shows self-organized dynamics that entail winnerless competition. Crucially, we will show that some of the fundamental instabilities that arise in these coupled systems are remarkably similar to endogenous activity seen in the brain (using EEG and fMRI). Furthermore, by changing a small subset of the system's parameters we can produce bifurcations and metastable sequential dynamics changing, which bear a remarkable similarity to pathological brain states seen in psychiatry. In what follows, we will consider the coupling of two macroscopic modes of brain activity, which, in a purely descriptive fashion, we will label as cognitive and emotional modes. Our aim is to examine the dynamical structures that emerge when coupling these two modes and relate them tentatively to brain activity in normal and non-normal states

Visceral and cutaneous pain : neural correlates and pharmacological intervention

Our brain is involved in processing pain, whether it is superficial cutaneous pain, caused by a scratch or a burn, or deep internal pain, caused by heartburn or gas in the intestines. Moreover, activation of a common cortical network is suggested during different types of pain in humans, implying that as long as the stimulus is painful it will be processed similarly in the cerebral cortex. However, no one has yet made direct comparison between superficial and deep pain of similar intensity and location; direct comparison is necessary in order to see how superficial pain relates to a more clinically relevant deep pain and to further our understanding of the latter.In three separate studies, the perception of visceral and cutaneous pain in humans was examined using psychophysical, brain imaging and pharmacological approaches, respectively. The first study revealed that for a similar given intensity, duration and location, visceral pain is more unpleasant, more varied qualitatively, more diffuse and more persistent after stimulation has ended, suggesting that there are some significant distinctions in the neural processes of external and internal pain in humans. The second study examined such processes with functional magnetic resonance imaging (fMRI), disclosing substantial differences in cortical processing of sensory information from skin and viscera, including limbic areas associated with the emotional component of pain (anterior cingulate and insular cortices), and sensory areas (primary somatosensory cortex). In addition, several similar cortical areas were activated by both superficial and deep pain, consistent with the existence of a common pain network independent of the nature of pain. The final study examined a possible divergence in pharmacological processes underlying deep and superficial pain, which could arise from differences in neuronal processing. The findings revealed that NMDA-receptors mediate both visceral and cutaneous pain in humans, yet the affect of visceral pain might be more susceptible to their blockers, which may be a potential explanation for different treatments of visceral and cutaneous pains.Together these studies provide direct evidence of the differences and similarities between visceral and cutaneous pain in humans within the perceptual, physiological and pharmacological domains