scholarly journals Disambiguating Pharmacodynamic Efficacy from Behavior with Neuroimaging

2016 ◽  
Vol 124 (1) ◽  
pp. 159-168 ◽  
Author(s):  
Vishvarani Wanigasekera ◽  
Melvin Mezue ◽  
Jesper Andersson ◽  
Yazhuo Kong ◽  
Irene Tracey

Abstract Background Attrition rates of new analgesics during drug development are high; poor assay sensitivity with reliance on subjective outcome measures being a crucial factor. Methods The authors assessed the utility of functional magnetic resonance imaging with capsaicin-induced central sensitization, a mechanism relevant in neuropathic pain, for obtaining mechanism-based objective outcome measures that can differentiate an effective analgesic (gabapentin) from an ineffective analgesic (ibuprofen) and both from placebo. The authors used a double-blind, randomized phase I study design (N = 24) with single oral doses. Results Only gabapentin suppressed the secondary mechanical hyperalgesia–evoked neural response in a region of the brainstem’s descending pain modulatory system (right nucleus cuneiformis) and left (contralateral) posterior insular cortex and secondary somatosensory cortex. Similarly, only gabapentin suppressed the resting-state functional connectivity during central sensitization between the thalamus and secondary somatosensory cortex, which was plasma gabapentin level dependent. A power analysis showed that with 12 data sets, when using neural activity from the left posterior insula and right nucleus cuneiformis, a statistically significant difference between placebo and gabapentin was detected with probability ≥ 0.8. When using subjective pain ratings, this reduced to less than or equal to 0.6. Conclusions Functional imaging with central sensitization can be used as a sensitive mechanism–based assay to guide go/no-go decisions on selecting analgesics effective in neuropathic pain in early human drug development. We also show analgesic modulation of neural activity by using resting-state functional connectivity, a less challenging paradigm that is ideally suited for patient studies because it requires no task or pain provocation.

2017 ◽  
Vol 52 (11) ◽  
pp. 1075-1083 ◽  
Author(s):  
Luciano Minuzzi ◽  
Sabrina K Syan ◽  
Mara Smith ◽  
Alexander Hall ◽  
Geoffrey BC Hall ◽  
...  

Objective: Current evidence from neuroimaging data suggests possible dysfunction of the fronto-striatal-limbic circuits in individuals with bipolar disorder. Somatosensory cortical function has been implicated in emotional recognition, risk-taking and affective responses through sensory modalities. This study investigates anatomy and function of the somatosensory cortex in euthymic bipolar women. Methods: In total, 68 right-handed euthymic women (bipolar disorder = 32 and healthy controls = 36) between 16 and 45 years of age underwent high-resolution anatomical and functional magnetic resonance imaging during the mid-follicular menstrual phase. The somatosensory cortex was used as a seed region for resting-state functional connectivity analysis. Voxel-based morphometry was used to evaluate somatosensory cortical gray matter volume between groups. Results: We found increased resting-state functional connectivity between the somatosensory cortex and insular cortex, inferior prefrontal gyrus and frontal orbital cortex in euthymic bipolar disorder subjects compared to healthy controls. Voxel-based morphometry analysis showed decreased gray matter in the left somatosensory cortex in the bipolar disorder group. Whole-brain voxel-based morphometry analysis controlled by age did not reveal any additional significant difference between groups. Conclusion: This study is the first to date to evaluate anatomy and function of the somatosensory cortex in a well-characterized sample of euthymic bipolar disorder females. Anatomical and functional changes in the somatosensory cortex in this population might contribute to the pathophysiology of bipolar disorder.


Diabetologia ◽  
2021 ◽  
Author(s):  
Kevin Teh ◽  
Iain D. Wilkinson ◽  
Francesca Heiberg-Gibbons ◽  
Mohammed Awadh ◽  
Alan Kelsall ◽  
...  

Abstract Aims/hypothesis The aim of this work was to investigate whether different clinical pain phenotypes of diabetic polyneuropathy (DPN) are distinguished by functional connectivity at rest. Methods This was an observational, cohort study of 43 individuals with painful DPN, divided into irritable (IR, n = 10) and non-irritable (NIR, n = 33) nociceptor phenotypes using the German Research Network of Neuropathic Pain quantitative sensory testing protocol. In-situ brain MRI included 3D T1-weighted anatomical and 6 min resting-state functional MRI scans. Subgroup differences in resting-state functional connectivity in brain regions involved with somatic (thalamus, primary somatosensory cortex, motor cortex) and non-somatic (insular and anterior cingulate cortices) pain processing were examined. Multidimensional reduction of MRI datasets was performed using a machine-learning approach to classify individuals into each clinical pain phenotype. Results Individuals with the IR nociceptor phenotype had significantly greater thalamic–insular cortex (p false discovery rate [FDR] = 0.03) and reduced thalamus–somatosensory cortex functional connectivity (p-FDR = 0.03). We observed a double dissociation such that self-reported neuropathic pain score was more associated with greater thalamus–insular cortex functional connectivity (r = 0.41; p = 0.01) whereas more severe nerve function deficits were more related to lower thalamus–somatosensory cortex functional connectivity (r = −0.35; p = 0.03). Machine-learning group classification performance to identify individuals with the NIR nociceptor phenotype achieved an accuracy of 0.92 (95% CI 0.08) and sensitivity of 90%. Conclusions/interpretation This study demonstrates differences in functional connectivity in nociceptive processing brain regions between IR and NIR phenotypes in painful DPN. We also establish proof of concept for the utility of multimodal MRI as a biomarker for painful DPN by using a machine-learning approach to classify individuals into sensory phenotypes. Graphical abstract


2017 ◽  
Author(s):  
Gonzalo M. Rojas ◽  
Carolina Alvarez ◽  
Carlos Montoya ◽  
María de la Iglesia-Vayá ◽  
Jaime Cisternas ◽  
...  

AbstractElectroencephalography (EEG) is the standard diagnosis method for a wide variety of diseases such as epilepsy, sleep disorders, encephalopathies, and coma, among others. Resting-state functional magnetic resonance (rs-fMRI) is currently a technique used in research in both healthy individuals as well as patients. EEG and fMRI are procedures used to obtain direct and indirect measurements of brain neural activity: EEG measures the electrical activity of the brain using electrodes placed on the scalp, and fMRI detects the changes in blood oxygenation that occur in response to neural activity. EEG has a high temporal resolution and low spatial resolution, while fMRI has high spatial resolution and low temporal resolution. Thus, the combination of EEG with rs-fMRI using different methods could be very useful for research and clinical applications. In this article, we describe and show the results of a new methodology for processing rs-fMRI using seeds positioned according to the 10-10 EEG standard. We analyze the functional connectivity and adjacency matrices obtained using 65 seeds based on 10-10 EEG scheme and 21 seeds based on 10-20 EEG. Connectivity networks are created using each 10-20 EEG seeds and are analyzed by comparisons to the seven networks that have been found in recent studies. The proposed method captures high correlation between contralateral seeds, ipsilateral and contralateral occipital seeds, and some in the frontal lobe.


Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1889-P
Author(s):  
ALLISON L.B. SHAPIRO ◽  
SUSAN L. JOHNSON ◽  
BRIANNE MOHL ◽  
GRETA WILKENING ◽  
KRISTINA T. LEGGET ◽  
...  

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