Traits that Affect Response to a Placebo Pill in Chronic Pain

Post by Amanda McFarlan

What's the science?

The placebo response is a phenomenon whereby an individual perceives or experiences an improvement in symptoms after receiving an inactive treatment. The relief of pain after exposure to placebo is of particular interest in the study of chronic pain, since many treatments for pain can have long-term adverse effects or addictive properties. So, the question remains – why do some people experience analgesia (pain relief) in response to an inert treatment? Efforts to study the underlying mechanisms of the placebo effect have been achieved using randomized placebo-controlled trials in chronic pain patients. These studies have provided evidence that individuals with chronic pain may exhibit different brain connectivity that predispose them to respond to a placebo treatment. This week in Nature Communications, Vachon-Presseau and colleagues examined the psychological and neural traits among individuals with chronic back pain to determine what traits predispose an individual to respond to a placebo.

How did they do it?

The authors analyzed a total of 63 participants in their randomized placebo-controlled clinical trial on placebo response. Participants were separated into three groups: placebo pill responding, placebo pill non-responding  and no treatment. The authors asked participants to visit the lab 6 times over an 8-week period for pain assessments, including verbal recall of pain ratings and questionnaires, and brain imaging using resting state fMRI. Participants received the placebo treatment during the second and fourth visits, both followed by a washout period in which no treatment was administered. In addition to assessments in the lab, participants used a smartphone app to rate their back-pain intensity twice a day in their natural environment. The participants’ pain ratings, questionnaire scores (for pain rating as well as psychological measures) and MRI scans were used to determine whether psychological, structural and functional differences were present in placebo responding individuals.

What did they find?

The authors determined that the placebo pill responding group had psychological, structural and functional differences in the brain compared to the placebo pill non-responding and no treatment groups. First, the participants’ daily pain rating using the smartphone app revealed that participants taking the placebo pill reported significantly lower levels of pain compared to those in the no treatment group, indicating the placebo pill was sufficient to induce analgesia. Second, the magnitude of analgesic response was found to be correlated with four sub-scales from the Multidimensional Assessment of Interoceptive Awareness questionnaire, including Emotional Awareness and Not Distracting, and the quality of ‘openness’ from the Neo-5 Personality Dimensions, suggesting these traits may be psychological factors predisposing an individual to a placebo pill response. Third, brain scans (structural MRI) obtained prior to the first placebo pill treatment revealed that the volume in limbic (subcortical) regions of the brain was asymmetric in patients who responded to placebo compared to non-responding individuals and that this asymmetry remained consistent in all four brain scans throughout the trial. Additionally, measurements of cortical thickness revealed that non-responding participants had thicker cortex in the prefrontal cortex (right superior frontal gyrus) compared to responding participants. Finally, an analysis of functional connectivity in the brain prior to the first treatment revealed that the patients who responded to placebo, compared to the non-responding group, had stronger connections between the ventrolateral prefrontal cortex and the precentral gyrus and weaker connections between the ventrolateral prefrontal cortex and the rostral anterior cingulate gyrus (these regions of the brain are generally involved in cognition, emotion, and movement). These differences in connections remained consistent throughout the trial, suggesting they may be predisposing factors to a placebo response. Anatomical and functional brain measurements in the no treatment group remained consistent throughout the trial.  


What's the impact?

This is the first study in chronic pain to compare a placebo-receiving group with a non-treatment group in a brain imaging randomized placebo-controlled clinical trial. The authors in this study found that there are psychological traits as well as structural and functional brain differences between individuals who respond to the placebo pill and individuals who do not. These findings suggest these factors are predisposing to the placebo pill response and may be used in computational models to predict the likelihood that an individual will respond to a placebo.


Vachon-Presseau et al. Brain and psychological determinants of placebo pill response in chronic pain patients. Nature Communications (2018). Access the original scientific publication here.

Shared Narratives are Associated with Similar Neural Responses

Post by Shireen Parimoo

What’s the science?

People can understand narratives presented in a wide variety of formats, ranging from a series of gestures and speech, to entire movies, and simple animations of geometric shapes. When people view the same narrative, such as a movie, their brain activation patterns are correlated. This neural similarity is particularly evident in regions of the default mode network (DMN), a brain network involved in processing complex narratives, among other things. However, it is unclear whether this neural similarity would be observed when a narrative has multiple interpretations. This week in NeuroImage, Nguyen and colleagues used functional magnetic resonance imaging (fMRI) to examine neural similarity across individuals, particularly in DMN regions, when they were presented with an ambiguous narrative.

How did they do it?

Two groups of participants were presented with either a movie or audio narrative while undergoing fMRI scanning. In one group, 36 adults watched a movie clip of geometric shapes with an ambiguous narrative that contained music to set the mood but no speech. In the other group, 18 adults listened to an audio clip that dictated the narrative corresponding to the movie clip. All participants recalled their respective narratives in detail. In the first analysis, the authors examined whether neural activity was correlated (related) across different participants based on the modality and interpretation of the narrative. Two analyses were performed: 1) Latent Semantic Analysis (LSA) was used to measure similarity of recall among participants within the movie and audio groups, and between the two groups. Participants in the movie group were further split into ‘high’ and ‘low’ recall similarity sub-groups based on their LSA similarity score. Participants in the movie group were also split into ‘high’ and ‘low’ interpretation similarity sub-groups based how correlated their LSA score was to that of participants in the audio group. The neural activity of participants within each of the recall similarity groups was correlated with each other to yield between-participant correlations; likewise, neural activity of participants in the two interpretation similarity groups was correlated with that of participants in the audio group to yield cross-modality between-participant correlations. 2) the authors used between-participant representational similarity analysis (RSA) to identify brain regions where more similar interpretations of the narrative elicited more similar patterns of activity, both within and across the two modalities.

What did they find?

Participants whose recall of the movie was similar (high recall similarity group) had high between-participant correlations in visual and auditory brain areas, as well as in regions involved in complex cognitive processing like the angular gyrus. Importantly, neural similarity in the primary visual cortex and most DMN regions such as the posterior medial cortex and angular gyrus was greater in the high recall similarity than in the low recall similarity group. This suggests that when recall of the movie was very similar across participants, the neural responses in the DMN were more correlated across participants.

When neural responses were compared across modalities, participants who interpreted the movie in a similar way to participants in the audio group (high interpretation similarity group) showed neural similarity in the inferior temporal gyrus. On the other hand, neural responses of participants whose interpretation of the movie was different from that of the audio group (low interpretation similarity group) were correlated in the right angular gyrus. Neural similarity in the posterior medial cortex, angular gyrus, and left medial temporal gyrus was greater in the high interpretation similarity group compared to the low interpretation similarity group, indicating that activity in these regions is more correlated when the people derive similar meaning from a narrative. Finally, the similarity of participants’ interpretation of the narrative was correlated with neural similarity in the right dorsolateral prefrontal cortex, posterior medial cortex, and right angular gyrus.  


What’s the impact?

This is the first study to show that when people’s spontaneous understanding of a narrative is similar, so is their brain activity— particularly in the default mode network. Importantly, this neural similarity was modality-invariant, suggesting that the meaning of the narrative, rather than the form in which it was presented, activated those brain regions. This study provides further insight into how social narratives are processed in the brain.


Nguyen et al. Shared understanding of narratives is correlated with shared neural responses. NeuroImage (2018). Access the original scientific publication here.

Glial Fibrillary Acidic Protein as a Marker for Mild Traumatic Brain Injury

What's the science?

Millions of cases of mild traumatic brain injury occur each year. Computed tomography (CT) scans are used to detect mild traumatic brain injury, and MRI can be used to detect subtle changes in the brain like neuron axonal injury, however these are costly and time-consuming. There is a need for a blood-based biomarker that can detect milder forms of brain injury to ensure proper treatment for these patients. This week in Neurology, Ori and colleagues test whether blood-based biomarkers are associated with neuroimaging changes (on CT and MRI scans) and can successfully detect mild traumatic brain injury. 

How did they do it?

Four blood-based biomarkers have previously been associated with brain changes that follow traumatic brain injury of varying severities: Tau (a neuronal injury marker), Glial Fibrillary Acidic protein, ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1) and neurofilament light. The authors aimed to assess whether any of these biomarkers would be elevated in mild traumatic brain injury and whether they were also associated with subtle structural changes shown on an MRI scan (using diffusion tensor imaging). A group of 277 patients seeking care for a mild brain injury were enrolled in the study. Blood was drawn to measure plasma concentrations of biomarkers and CT and MRI scans were performed within 48 hours of the injury. A control group of 49 healthy participants (with well-matched demographics) was included for comparison.

What did they find?

Glial Fibrillary Acidic protein, Tau and Neurofilament light were all higher in patients with mild traumatic brain injury compared to controls. Glial Fibrillary Acidic protein was the best predictor of mild traumatic brain injury (diagnosis). When patients with mild brain injury were stratified into those with and without changes on their CT scans, Glial Fibrillary Acidic protein, Tau and neurofilament light concentrations were all higher in patients with detectable changes. However, Glial Fibrillary Acidic protein concentration was the only biomarker that significantly predicted trauma-related CT scan changes. Glial Fibrillary Acidic protein, Tau and Neurofilament light all predicted structural MRI changes, however Glial Fibrillary Acidic protein was the strongest predictor of structural MRI changes related to mile traumatic brain injury.


What's the impact?

This is the first study to examine whether blood-based biomarkers can be used to detect mild traumatic brain injury. Glial Fibrillary Acidic protein concentration is a sensitive predictor of mild traumatic brain injury and is also closely associated with neuroimaging changes. CT and MRI scans are expensive and time-consuming, so having methods to detect the presence and severity of brain injury early on is important for proper and effective treatment.


Gill et al., Glial fibrillary acidic protein elevations relate to neuroimaging abnormalities acutely following a mild traumatic brain injury. Neurology (2018). Access the original scientific publication here.