Unlearning pain can reverse brain changes

Here are two articles investigating the effects of pain exposure on the brain, and how these can be reversed. The 2nd article below includes many links to related studies.

Cognitive behavioral training reverses the effect of pain exposure on brain-network activity. – PubMed – NCBI – Abstract

Repeated sensory exposures shape the brain’s function and its responses to environmental stimuli.

An important clinical and scientific question is how exposure to pain affects brain network activity and whether that activity is modifiable with training.  

We sought to determine whether repeated pain exposure would impact brain-network activity and whether these effects can be reversed by cognitive behavioral training (CBT).

Healthy subjects underwent 8 experimental sessions on separate days where they received painful thermal stimuli. They were randomly assigned to groups receiving either CBT (Regulate group, n=17) or a non-pain-focused treatment (Control group, n=13). Before and after these sessions, participants underwent functional MRI (fMRI) during painful stimulation and at rest.

The effect of repeated pain over time in the Control group was a decrease in the neurotypical pain-evoked default mode network (DMN) deactivation.

The Regulate group did not show these DMN effects but rather had decreased deactivation of the right ventrolateral prefrontal cortex (R vlPFC) of the executive control network.

In the Regulate group, reduced pain-evoked DMN deactivation was associated with greater individual reduction in pain intensity and unpleasantness over time.

Finally, the Regulate group showed enhanced resting functional connectivity between areas of the DMN and executive control network over time, compared to the Control group

Our study demonstrates that trainable cognitive states can alter the effect of repeated sensory exposure on the brain.

The findings point to the potential utility of cognitive training to prevent changes in brain network connectivity that occur with repeated pain experience.

This sounds good,  it seems to be only preventive. If a person has chronic pain, the changes have already taken effect.


Unlearning chronic pain: A randomized controlled trial to investigate changes in intrinsic brain connectivity following Cognitive Behavioral Therapy – 2014 Jul – Free full text PMC

This article contains dozens of links to other studies about learning mechanisms contributing to chronic pain.

Introduction

Chronic pain is a complex physiological and psychological phenomenon.

A variety of implicit learning mechanisms contribute to the development of chronic pain and to persistent changes in the central nervous system (Apkarian 2011, Flor 2012).

Although chronic musculoskeletal pain was originally conceptualized as a purely bottom-up perceptual process, there is now mounting physiological evidence in support of the involvement of central mechanisms.

This evidence includes documented functional (Apkarian et al. 2004, Baliki, Baria, and Apkarian 2011a, Baliki et al. 2008, Bingel, and Tracey 2008, Buffington, Hanlon, and McKeown 2005, Cauda et al. 2010, Cauda et al. 2009, Geha et al. 2007, Giesecke et al. 2004, Gracely et al. 2002, Napadow et al. 2010, Otti et al. 2013, Parks et al. 2011, Weissman-Fogel et al. 2011) and structural (Baliki et al. 2011b, Buckalew et al. 2008, Ceko et al. 2013, May 2011, Moayedi et al. 2011, Schweinhardt et al. 2008, Seminowicz et al. 2010, Seminowicz et al. 2011, Valet et al. 2009) abnormalities in chronic pain populations, relative to pain-free controls, and even points to specific brain predispositions that can lead to chronification of pain. (Baliki et al. 2012, Mansour et al. 2013)

It is thus not surprising that pain-related maladaptive perceptual and behavioral patterns can be mitigated by non-pharmacological interventions such as Cognitive Behavioral Therapy (CBT) (Bernardy et al. 2010, Veehof et al. 2011, Vickers et al. 2012, Williams, Eccleston, and Morley 2012), particularly in combination with relapse prevention programs (Naylor et al. 2002, Naylor et al. 2008)

The neural mechanisms underlying non-pharmacological remediation of the maladaptive behavioral and cognitive patterns of chronic pain remain poorly understood.

Recently investigations of the neural underpinnings of chronic pain have adopted resting state functional magnetic resonance imaging (R-fMRI) and intrinsic (resting state) functional connectivity (iFC) methods, which are advantageous in that they permit the interrogation of multiple functional networks without the need for targeted tasks

Development of reliable R-fMRI biomarkers for chronic pain holds promise for diagnostic, prognostic, and outcome evaluation purposes because of the relative ease of implementation in clinical and research settings

It’s very dangerous to determine pain by imaging. (See We Cannot Explain Pain with Brain Scans)

At least two longitudinal studies of iFC (intrinsic functional connectivity) in chronic pain exist (Baliki et al. 2012, Napadow et al. 2012)

Studies of chronic pain populations often implicate changes within the Default Mode Network (DMN), including anterior portions of the DMN (Baliki et al. 2008, Loggia et al. 2013, Napadow et al. 2008, Napadow et al. 2012, Otti et al. 2013).

In addition to changes in DMN iFC, prior studies of iFC in chronic pain also implicate the salience (Loggia et al. 2013, Malinen et al. 2010, Napadow et al. 2012, Napadow et al. 2010, Baliki et al. 2010, Baliki et al. 2012, Yuan et al. 2013) and basal ganglia (BG) networks (Baliki et al. 2010, Baliki et al. 2012, Yuan et al. 2013).

Here, we sought to build on these findings, to gain a better understanding of treatment-related functional neuroplasticity, and to better define biomarkers of recovery from chronic pain.

We thus compared pre- and post-intervention changes in the iFC of default, salience and BG networks between the CBT and EDU groups.

Since emotional regulation has been associated with negative connectivity between anterior DMN and limbic regions across studies (Etkin et al., 2011), we hypothesized decreased iFC between anterior DMN and limbic regions following CBT.

Results

Groups were well-matched in terms of their baseline clinical characteristics with no significant differences in any of the measures tested with the exception of pain duration, where participants in the CBT group had on average longer pain duration).

CBT patients improved on all ten clinical measures of interest, and on five of these measures (Mental Composite Score, Pain Symptoms, Self-Efficacy for Pain Management and Self-Efficacy for Coping with Symptoms and Passive Coping), they showed significant improvement over the EDU group.

The most consistent results were observed in measures of Self-Efficacy, which has been established as a good predictor of pain management success (Denison et al., 2004).

Discussion

Notably, treatment-related changes in the iFC of nodes of the DMN emerged across several analyses. Further, CBT-related changes were observed in BG functional connectivity, as well as in the amplitude of intrinsic fluctuations in the cerebellum

Initial clues regarding the behavioral significance of these CBT-related alterations were provided by brain–behavior correlations demonstrating that patients showing the greatest treatment-related change in self-efficacy and pain symptoms exhibited the greatest treatment-related change in iFC.

We discuss these findings in more detail below

  • Decreased aDMN–amygdala connectivity and its putative role in extinction
  • Decreased aDMN–PAG connectivity and its putative role in descending pain modulation and homeostatic regulation
  • CBT-related changes in the sensory-discriminative aspects of chronic pain as indexed by increased BG–S2 connectivity
  • Exploratory analyses: fALFF changes in the cerebellum and the PCC

Each of these areas is explained in detail in the full article: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4749849/

Appendix 1

I find it unbelievable that just a handful of questions can determine such a complex phenomenon as catastrophizing, especially since the questions seem so very simple.

Questions taken from Coping Strategies Questionnaire (0, never do that; 3 sometimes do that; 6 always do that).

  • I worry all the time about whether it will end.
  • I feel like I cannot go on.
  • It’s terrible and I feel it’s never going to get any better.
  • It’s awful and I feel that it overwhelms me.
  • I feel I cannot stand it anymore.

Questions taken from Pain Catastrophizing Scale (0, Not at all; 1, To a slight degree; 2, To a moderate degree; 3, To a great degree; 4, All the time).

  • I worry all the time about whether it will end.
  • I feel like I cannot go on.
  • It’s terrible and I feel it’s never going to get any better.
  • It’s awful and I feel that it overwhelms me.
  • I feel I cannot stand it anymore.

Number of participants (N) and average doses of medications taken before and after both interventions. Non-opioid analgesics are expressed as mg aspirin per day, opioid medications as mg of morphine per day, antidepressants as mg of fluoxetine per day, benzodiazepines as mg of valium per day, sleeping aids as mg of zolpidem per day.  

Medication Class

N pre

N post

Mean (SD) dose pre (mg/day)

Mean (SD) dose post (mg/day)

Non-opioid analgesics

28

25

2027 (2351)

1545 (2020)

Opioids

5

6

18 (23)

25 (21)

Antidepressants

8

12

22 (26)

32 (28)

Benzodiazepines

6

6

5 (4)

7 (8)

Sleeping aids

4

0

5 (5)

0

 

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