Neurologic Pain Signature (NPS) as a “common core pain system” that generalizes across pain types

Our new study, Common and distinct neural representations of aversive somatic and visceral stimulation in healthy individuals” is published in Nature Communications.

Understanding the common and distinct brain representations underlying visceral and somatic pain is critical for assessing the neurophysiological mechanisms underlying different forms of pain. While previous studies have pointed to both commonalities and differences, this study identifies brain-wide commonalities that generalize across studies and types of painful stimulation, and brain network-level changes that are robust enough to permit brain-based classification of visceral versus somatic pain in independent participants.

This study shows that Neurologic Pain Signature (NPS) responds robustly to both somatic and visceral aversive stimulation, and correlates with the subjective visceral pain experience. This identifies the NPS as a “common core pain system” that generalizes across pain types, including visceral stimulation. Additionally, the study suggests that, contrary to the NPS, existing signatures for nonpainful affective processes (negative emotion, social rejection, and vicarious pain) do not respond consistently to somatic nor visceral stimulation. This demonstrates the sensitivity of the NPS to pain versus other affective processes and implies that visceral pain does not activate more “emotional” brain patterns compared to somatic pain, as commonly assumed.

Continue reading “Neurologic Pain Signature (NPS) as a “common core pain system” that generalizes across pain types”

Empathic pain share common neural representations

Source: medium.com

Our new study “Empathic pain evoked by sensory and emotional-communicative cues share common and process-specific neural representation” published in eLife suggests that pain empathy evoked by observation of acute pain inflictions and facial expressions of pain share common and pain-specific neural representations. In addition to traditional univariate analyses, we employed extensive multivariate pattern analyses, which highlighted common representations centered largely on the bilateral mid-insula. In a further validation step, we showed that the domain-general vicarious pain pattern did not respond to non-painful high-arousal negative stimuli but predicted self-experienced thermal pain.

Continue reading “Empathic pain share common neural representations”

Can interpersonal synchrony enhance patient-provider interaction outcomes?

Source: UMD RIGHTNOW

“Clinician-patient movement synchrony mediates social group effects on interpersonal trust and perceived pain”

Our new study published in the Journal of Pain suggests that interpersonal movement synchrony between the patient and the provider could mediate concordance effects on trust in the clinician and reduce the pain perceived by the patient. Continue reading “Can interpersonal synchrony enhance patient-provider interaction outcomes?”

Challenges, gaps, and ideas to facilitate the development of biomarkers and end points for pain

“Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges & opportunities”

In 2018, the NIH-led Discovery and Validation of Biomarkers to Develop Non-Addictive Therapeutics for Pain workshop convened scientific leaders from academia, industry, government and patient advocacy groups to discuss progress, challenges, gaps and ideas to facilitate the development of biomarkers and end points for pain. The outcomes of this workshop are outlined in this Consensus Statement.

Continue reading “Challenges, gaps, and ideas to facilitate the development of biomarkers and end points for pain”

A novel approach that could advance the discovery and assessment of analgesic interventions in infancy

“Inferring the infant pain experience: a translational fMRI-based signature study”

This study translates validated adult pain fMRI brain signatures to a nonverbal patient population in which the assessment and management of pain presents a significant clinical challenge. Here we demonstrate that the basic encoding of the sensory discriminative aspects of pain, as represented by the Neurologic Pain Signature (NPS), occurs in both adults and infants, whereas higher-level cognitive modulation of pain, represented by the Stimulus Intensity Independent Pain Signature (SIIPS1) is only present in adults and not observed in infants. This work allows us to use quantitative fMRI observations to make stronger inferences related to pain experience in nonverbal infants. Continue reading “A novel approach that could advance the discovery and assessment of analgesic interventions in infancy”

New Journal of Neuroscience Publication

Image of a brain“Behavioral and neural signatures of working memory in childhood”

The paper establishes associations between working memory, cognitive abilities, and functional MRI activation in data from over 4,000 9–10-year-olds enrolled in the Adolescent Brain Cognitive Development study, an ongoing longitudinal study in the United States. Behavioral analyses reveal robust relationships between working memory, short-term memory, language skills, and fluid intelligence. Continue reading “New Journal of Neuroscience Publication”

How does pain arise from nociceptive input and which brain networks are involved in pain generation?

The new study, “Multiple Brain Networks Mediating Stimulus–Pain Relationships in Humans”, published in the journal of Cerebral Cortex suggests a new high-dimensional mediation analysis technique to estimate distributed, network-level patterns that formally mediate the relationship between stimulus intensity and pain.

Continue reading “How does pain arise from nociceptive input and which brain networks are involved in pain generation?”

A step toward developing biological markers of social emotions…

“A Generalizable Multivariate Brain Pattern for Interpersonal Guilt”

In this paper,  we used a predictive modeling approach to identify a whole-brain pattern that is sensitive and specific to the core antecedent of guilt. This signature, while being a distributed pattern across the entire “Emotion” network, exhibits its highest predictive weight in the anterior/middle cingulate cortex and anterior insula. This signature can be used in future studies for detecting guilt- and transgression related neural processes by applying it to harm-based moral decision-making context, or by testing its response in different clinical populations such as those characterized by excessive or reduced experience of guilt (i.e., internalizing disorders versus psychopathy).

Continue reading “A step toward developing biological markers of social emotions…”

Ethnicity and the Experience of Pain

“Neural and Sociocultural Mediators of Ethnic Differences in Pain”

The common belief that African Americans feel less pain has been related to undertreatment of pain in this ethnic group, which contributes to widespread and persistent racial and ethnic health disparities. Paradoxically, African Americans actually report more pain than White Americans in both clinical and laboratory settings. In this study, we examined nociceptive sensitivity by looking at the activity in brain regions previously linked to nociception in whole-brain analyses and tested responses in a multivariate fMRI activity pattern that closely tracks the intensity and affect of evoked nociceptive pain, termed the neurologic pain signature (NPS). Our findings suggest that the link between chronic pain and ethnic differences in pain sensitivity may lie in the chronic stress associated with discrimination. 

Continue reading “Ethnicity and the Experience of Pain”

Are there effective emotion regulation strategies that do not depend on top-down cognitive control? 

“Let it be: Mindful-acceptance down-regulates pain and negative emotion”

Behavioral studies have shown that mindfulness- or acceptance-based treatments ameliorate depression, anxiety, addiction, and chronic pain; improve functionality and quality of life in cancer and other conditions. Brain imaging studies have examined individuals who were trained or regularly engage in mindfulness meditation. While promising, such studies do not directly address the use of mindful acceptance as an emotion regulation strategy in individuals who do not practice meditation, and findings could depend on cumulative effects of training or characteristics of individuals who seek it. We addressed this using functional magnetic resonance imaging (fMRI) and adapting a well-established emotion regulation task to assess the effects of mindful acceptance on affective and neural responses in meditation-naïve adults. Identifying and understanding the mechanisms supporting such strategies could lead to improved treatments for emotionally vulnerable populations.

Continue reading “Are there effective emotion regulation strategies that do not depend on top-down cognitive control? “

A systematic approach to building machine learning models for neuroimaging

“Interpreting machine learning models in neuroimaging: Towards a unified framework”

Machine Learning (ML) has rapidly increased in popularity in both basic and translational research. The use of ML in neuroimaging experiments has provided new answers to many enduring research questions. However, these models are complex and often hard to interpret, making it difficult to evaluate their neuroscientific validity and contribution to understanding the brain. Therefore, there is a pressing need for methods to help interpret and explain the model decisions and provide neuroscientific validation for neuroimaging ML models. In this protocol, we introduce a unified framework that consists of model-, feature- and biology-level assessments to provide complementary results that support the understanding of how and why a model works. We first propose a unified framework for interpreting ML models in neuroimaging based on model-level, feature-level, and neurobiology-level assessments. Then, we provide a workflow that illustrates how this framework can be employed to predictive models, along with practical examples of analyses for each level of assessment with a sample fMRI dataset (available for download at https://github.com/cocoanlab/interpret_ml_neuroimaging). Continue reading “A systematic approach to building machine learning models for neuroimaging”