The link between pain and memory in the medial temporal lobe
The medial temporal lobe (MTL) is primarily thought to be responsible for memory and cognition. However, several functional neuroimaging studies have shown the involvement of this brain region in both the response to experimental pain in healthy individuals and in patients with chronic pain.
Interestingly, the well-known case of patient H.M., who underwent bilateral MTL resection for epilepsy, had reported an unusually high tolerance for heat pain. These previous findings suggest the involvement of the MTL in nociception and pain modulation, in addition to its well-recognized role in memory.
To further explore the involvement of the MTL in nociceptive processing, researchers at the University of Toronto, led by UTCSP members Lizbeth Ayoub and Dr. Massieh Moayedi, conducted two separate meta-analyses of fMRI studies of pain that indicated MTL engagement, and one original empirical study. The first meta-analysis consisted of studies in healthy individuals undergoing experimental pain and the second consisted of chronic pain patients. The first meta-analysis demonstrated increased activation after a pain-inducing stimulus in the right anterior hippocampus, parahippocampal gyrus, and amygdala compared with each subject’s own, non-painful baseline condition.
The second meta-analysis demonstrated that chronic pain patients demonstrate decreased activation in the right anterior hippocampus compared to healthy individuals. Following the results of these meta-analyses, the authors conducted their own resting-state fMRI study in 77 patients with chronic low-back pain and 79 matched healthy controls, specifically focusing on the functional connections between the right anterior hippocampus and the rest of the brain. They found that patients with chronic low-back pain have significantly decreased functional connectivity between the right anterior hippocampus and the medial prefrontal cortex compared to healthy individuals. Overall, this study points to the important role of the MTL, and in particular the right anterior hippocampus, in both acute and chronic pain.
Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods
The advent of technology and mobile health apps has transformed the way people monitor, manage, and communicate health-related information. For pain, “Manage My Pain” is a mobile health app used by thousands of individuals to measure and manage their pain.
It also has the capacity for large-scale, real-world data collection to advance pain research, treatment, and policy. In particular, data mining and machine learning methods can be used to analyze multimodal and dynamic features as well as build models for prediction. This may ultimately help us understand how pain changes across time within users and to allow for the development of effective coping strategies.
Using data collected from users of the Manage My Pain app, researchers at York University, including UTCSP members Drs. Joel Katz and Hance Clarke, and corresponding author Tahir Janmohamed, defined a new pain volatility measure and used machine learning to predict future pain volatility levels. Pain volatility measures the fluctuation or variability in pain over time and it is important because it takes into account intra- and interindividual differences in pain that may not be captured using the mean or median. In this study, pain volatility was newly defined as the mean of absolute changes in pain severity. A total of 782 users with 329,070 pain records were included in the study.
The authors collected 130 features from the first month of engagement with the app to predict high versus low levels of pain volatility at the sixth month mark of app engagement. They found that the prediction model using Random Forests performed the best – an approximate 70% accuracy level was achieved for both high and low volatility classes. The results of this study point to how large, real-world datasets collected from users of mobile health apps provide an important opportunity to study clinical syndromes and identify strategies to better measure and manage health symptoms. Specifically, the development of prediction models using machine learning may allow earlier intervention to prevent the development of critical health symptoms such as high pain volatility.
Pain volatility measures the fluctuation or variability in pain over time and it is important because it takes into account intra- and interindividual differences in pain that may not be captured using the mean or median. In this study, pain volatility was newly defined as the mean of absolute changes in pain severity.
Gabapentin increases expression of subunit-containing GABAA receptors
Gabapentin (also known as Neurontin) is clinically prescribed for the treatment of seizures, pain, and anxiety. While gabapentin is known to modulate voltage-gated calcium channels, some studies have suggested the effects of gabapentin are also dependent on GABAergic inhibition. However, gabapentin neither binds GABA receptors nor increases GABA release, thus its precise mechanisms of action remain unclear and is what UTCSP scientists, Dr. Beverly Orser, Dr. Robert Bonin, and collaborators, aimed to uncover.
To determine whether GABA receptors are involved in gabapentin’s action the authors started by measuring levels of the GABAA receptor, as changes in cell surface expression of ion channels is a key way to modulating neuronal activity. In this study, they found that gabapentin treatment increased surface expression of the δ subunit of GABAA receptor in the cerebellum and hippocampus. The δ subunit is typically expressed outside of synapses and accordingly, neurons from mice pretreated with gabapentin displayed increased tonic GABAA receptor-dependent inhibitory currents.
They next sought to test whether the GABAA receptor δ subunit was required for known behavioural effects of gabapentin, such as ataxia, anxiolysis, and analgesia, by conducting behaviour assays with mice lacking GABAA receptor δ subunit expression (Gabrd-/-). Unlike wild type mice that exhibit reduced motor coordination (tested with Rotarod) and reduced anxiety behaviour (tested with elevated plus maze) following gabapentin administration, Gabrd-/- mice given gabapentin showed no change in these behaviours. However, gabapentin remained effective in reducing pain behaviour after formalin injection in Gabrd-/- mice, similar to wild type mice.
Together, these results suggest that the ataxic and anxiolytic effects of gabapentin are dependent on the δ subunit of GABAA receptors, but its analgesic properties are δ subunit-independent. Since diminished GABAA receptor δ subunit expression is observed in certain psychiatric disorders, such as depression, gabapentin’s ability to upregulate δ subunit expression may serve as a potential novel therapeutic for such conditions.
These results suggest that the ataxic and anxiolytic effects of gabapentin are dependent on the δ subunit of GABAA receptors, but its analgesic properties are δ subunit-independent.
Conditioned pain modulation is not unidirectional: both hyper- and hypoalgesia can arise depending on the stimulus
Conditioned pain modulation (CPM) is the phenomenon in which one painful stimulus (the conditioning stimulus) affects the pain perception of a second stimulus (the test stimulus) at a different site.
Hypoalgesic CPM, in which the conditioning stimulus reduces pain response to the test stimulus, is known as diffuse noxious inhibitory control (DNIC), or simply put – “pain inhibits pain”. However, numerous human studies have found highly variable and contradictory results to DNIC, where some observe hypoalgesia after conditioned stimulus and others show hyperalgesia. To understand the variability of CPM response a team led by Dr. Jeffrey Mogil, in collaboration with UTCSP scientist Dr. Loren Martin, used rodent models to systematically test the effects of CPM using multiple conditioning and test stimuli.
Using CD-1 mice given acetic acid as the conditioning stimulus, they observed hyperalgesia in response to thermal and mechanical test stimuli, contradicting DNIC. This controversial observation was reproduced in DBA/2J mice and Sprague-Dawley rats, and also using a different conditioning stimulus – orofacial formalin. They next showed that increasing the intensity of the conditioning stimulus (i.e., increased acetic acid concentration) only exacerbated the hyperalgesic response to the test stimuli.
Nonetheless, hypoalgesic CPM (or DNIC) was observed under some scenarios: mice given a highly noxious test stimulus were more tolerant. For example, while acetic acid injection in mice increased their sensitivity to 46oC (low-intensity thermal stimulus), it reduced their sensitivity to 52oC (high-intensity). Hypoalgesia from CPM was also observed after peripheral nerve injury, where neuropathic mice showed higher tolerance to mechanical test stimuli after receiving an acetic acid conditioning stimulus.
The results of this study suggest that the effects of CPM are dependent on test stimulus intensity and can be bidirectional, resulting in either a hyperalgesic or hypoalgesic effect. This paper also demonstrates that fully understanding a phenomenon requires studying it under varying conditions.
The results of this study suggest that the effects of CPM are dependent on test stimulus intensity and can be bidirectional, resulting in either a hyperalgesic or hypoalgesic effect. This paper also demonstrates that fully understanding a phenomenon requires studying it under varying conditions.