Pain and the brain: specificity and plasticity of the brain in clinical chronic pain

Abstract

We review recent advances in brain imaging in humans, concentrating on advances in our understanding of the human brain in clinical chronic pain. Understanding regarding anatomical and functional reorganization of the brain in chronic pain is emphasized. We conclude by proposing a brain model for the transition of the human from acute to chronic pain.

Conflict of interest statement

The authors claim no conflict of interest.

Figures

Figure 1

Segregating the cingulate and insular cortices along the stimulus and subjective perception dimensions for acute thermal pain. A: Variability of subjective ratings of pain is illustrated for four subjects. B: Temporal and intensity properties for a constant thermal stimulus that was applied to the skin on the back. C: Variability of correlation between the stimulus and ratings for the 16 subjects in the study. D: Contrasting cingulate gyrus and insula activity between stimulus and perception identifies statistically significant regional differences in each area along these dimensions. Green circles are regions where activity was extracted and correlated either with the stimulus or individual subject perceptions, corresponding bar graphs are in the right, which indicate the sign and extent of difference between representation of stimulus and perception. Anterior cingulate and posterior insula are regions best related to pain perception. All data are derived from the study described in [10].

Figure 2

Insular region that reflects pain perception shows a one-to-one relationship with each epoch where pain is reported. Moreover, this area also just as faithfully encodes perceived magnitudes for bars displayed visually. Thus, the brain area accurately reflecting pain subjectivity seems to be encoding magnitudes in general and thus lacks specificity. A. Illustrates the method used for generating the scattergrams in B. For each epoch of perceived pain, the magnitude of peak pain rating is extracted and correlated to the peak fMRI BOLD activity identified within the thermal stimulus time window (illustrated in red boxes). B. Left figure shows the region of the insula that encodes perceived pain and perceived magnitude of lengths of visual bars (circled region is right magnitude related insula, mag-INS). First scattergram is the epoch-by-epoch pain perception to BOLD relationship, across all subjects. Second scattergram is for the visual magnitude-rating task. Correlation coefficients are indicated and closely match for both sensory dimensions. Data and figure adapted from the study described in [10].

Figure 3

Segregating brain activity for acute thermal pain perception between anticipation, perception and pain relief identifies distinct networks sequentially activated during perception of acute pain. Three vectors separated in time were contrasted for a thermal painful stimulus that was a randomized sequence of stimuli where intensity duration and inter-stimulus intervals were not predictable. The anticipation vector identified increased activity preferentially related to only the start of the stimulus; while perception was identified by subjective ratings of pain; and relief period was identified for increased activity in the time window when the stimulus was returning to baseline. A. Three separate and complimentary networks are identified. B. Differential activity for the three phases of pain perception is illustrated for indicated regions (green circles in A) (A = anticipation, P = perception, R = relief). Data are derived from the study described in [12].

Figure 4

Temporal sequence of brain activity for thermal painful stimuli determined in relation to anticipated peak for the stimulus (vertical line at 10 seconds from stimulus start) and actual reported peak of pain perception (vertical line at 17 seconds). Vertical scale is similarity of brain activity shape to the stimulus and perception shapes (negative values are better correlations to stimulus shape while positive values are better correlations to perception, determined for specific BOLD activity extracted for all regions listed on the right). The anterior cingulate (ACC) and amygdala (Amyg) peak at times prior to the stimulus peak, implying that these regions are more related to anticipation of impending pain. The thalamic activity (Thal) peaks just after the stimulus and best reflects stimulus shape. Nociceptive insula (noci-INS) and magnitude insula (mag-INS) are segregated by time and shape similarity, reflecting their respective functional labels. The blue curve approximates the brain spatio-temporal evolution of nociceptive information being transformed into subjective consciousness of pain. BG = basal ganglia; VPc = ventral prefrontal cortex; IPS = inferior parietal sulcus; SMA =supplementary motor area; DPc = dorsal prefrontal cortex. Adapted from [10].

Figure 5

Brain activity for rating spontaneous fluctuations of back pain in chronic back pain patients show a strong correlation with intensity and duration of the condition across all participating patients. The observed correlations are strong enough that we can assert that the task can be used to predict intensity and duration of chronic back pain in individual subjects within an error of 20%. Figure adapted from [9].

Figure 6

Figure 6A: Brain activity patterns for various clinical chronic pain conditions. Activity maps: are group-averaged responses for different pain conditions. Activity maps: Thermal pain, knee-pressure induced pain in healthy subjects, and in osteoarthritis patients (OA) show similar patterns of brain activity, implying that all three results correspond to acute pain activity. In contrast, brain activity for spontaneous pain in different clinical conditions (chronic back pain, CBP; osteoarthritis, OA; pelvic pain, CPPS; and post-herpetic neuralgia, PHN) show different activity patterns, engaging to different extents sensory and limbic brain areas. In PHN, tactile allodynia and spontaneous pain evoke relatively distinct brain regions too. Bar graphs: Magnitude of activity in 2 limbic regions (mPFC and Amygdala) and 2 sensory regions (thalamus and insula) are compared for four groups: healthy subjects for thermal pain, Healthy th; chronic back pain patients for spontaneous pain, CBP sp; post-herpetic neuralgia for spontaneous pain, PHN sp, and for tactile allodynia, PHN al). Thermal pain and PHN allodynia show larger activity in the sensory regions, while spontaneous pain in CBP and PHN evoke more limbic activity. Figure 6B: Brain activity in medial prefrontal cortex (mPFC) shows high specificity for chronic back pain. Magnitude of mPFC regional activity (as identified in chronic back pain patients) across five groups of subjects. Each symbol is an individual subject. The threshold indicated by broken green line distinguishes chronic back pain (CBP) from pelvic pain (CPPS), osteoarthritis (OA), post-herpetic neuralgia (PHN) for spontaneous pain, and healthy subjects for acute pain (healthy) at an accuracy > 90%. The number of subjects studied in each group is indicated above.

Figure 6

Figure 6A: Brain activity patterns for various clinical chronic pain conditions. Activity maps: are group-averaged responses for different pain conditions. Activity maps: Thermal pain, knee-pressure induced pain in healthy subjects, and in osteoarthritis patients (OA) show similar patterns of brain activity, implying that all three results correspond to acute pain activity. In contrast, brain activity for spontaneous pain in different clinical conditions (chronic back pain, CBP; osteoarthritis, OA; pelvic pain, CPPS; and post-herpetic neuralgia, PHN) show different activity patterns, engaging to different extents sensory and limbic brain areas. In PHN, tactile allodynia and spontaneous pain evoke relatively distinct brain regions too. Bar graphs: Magnitude of activity in 2 limbic regions (mPFC and Amygdala) and 2 sensory regions (thalamus and insula) are compared for four groups: healthy subjects for thermal pain, Healthy th; chronic back pain patients for spontaneous pain, CBP sp; post-herpetic neuralgia for spontaneous pain, PHN sp, and for tactile allodynia, PHN al). Thermal pain and PHN allodynia show larger activity in the sensory regions, while spontaneous pain in CBP and PHN evoke more limbic activity. Figure 6B: Brain activity in medial prefrontal cortex (mPFC) shows high specificity for chronic back pain. Magnitude of mPFC regional activity (as identified in chronic back pain patients) across five groups of subjects. Each symbol is an individual subject. The threshold indicated by broken green line distinguishes chronic back pain (CBP) from pelvic pain (CPPS), osteoarthritis (OA), post-herpetic neuralgia (PHN) for spontaneous pain, and healthy subjects for acute pain (healthy) at an accuracy > 90%. The number of subjects studied in each group is indicated above.

Figure 7

Intensity of ongoing chronic postherpetic neuropathy pain changes brain activity and thus cognitive processing in a complex pattern, for pain and non-pain tasks. The figure is adapted from a study [40] in which postherpetic neuropathy patients were studied before and after lidocaine application on the painful skin. Each patient was scanned at three time points relative to the drug therapy. In all cases the patients performed two different tasks: in the pain task they continuously rated the fluctuations of their spontaneous pain (left), and in the visual task they rated fluctuations of a bar varying in time (right). The relationship between brain activity and intensity of ongoing pain was determined using a covariate analysis, in which the related pain intensity for each fMRI scan was used to determine the effect of this parameter on brain responses. Across subjects and across all scans, average variation of brain activity is displayed for both tasks. The presence of the chronic pain effects activity in both tasks across large brain areas, rather similarly, increasing activity in some areas (red) and decreasing them in others (blue).

Figure 8

In chronic pain patients and in the absence of any specific task (resting state) activity in the insula and anterior cingulate, but not in the precuneus/visual cortex, fluctuate at higher frequencies than in control subjects. Power spectral density as a function of frequency is shown for each individual subject. Figure from [68].

Figure 9

Distinct functional connectivity between nucleus accumbens and the rest of the brain are observed in chronic pain patients in contrast to healthy subjects. This shift in connectivity is tightly correlated to the magnitude of back pain reported by the patients. A. Healthy: Functional connectivity between nucleus accumbens and the rest of the brain in healthy subjects. We observe extensive bilateral insula involvement. A. CBP: Functional connectivity for nucleus accumbens in chronic back pain patients. Functional connectivity is shifted away from the insula to medial prefrontal cortex. B. Strength of connectivity between nucleus accumbens and medial prefrontal cortex in relation to the magnitude of back pain reported. Each red symbol is an individual chronic back pain patient; blue circles are healthy controls. The higher the magnitude of spontaneous pain of back pain the stronger is the correlation between mPFC and NAc, implying more information sharing between these two brain regions. Figure adapted from [12].

Figure 10

Chronic back pain patients report a decrease in the magnitude of their back pain during a thermal painful stimulus applied to the skin on their back. They seem to only realize this fact when they are specifically instructed to attend to their own back pain. A. Group average ratings of either the magnitude of thermal painful stimulus (red) or spontaneous fluctuations of back pain (blue), for a stimulus pattern shown below (grey) that is unpredictable in intensity and duration. Every time the stimulus is felt painful it seems to induce a decrease in spontaneous pain. B. Average stimulus pain perception (red) and spontaneous back pain perception (blue) relative to start and end of thermal stimulus (black). Rating of the stimulus intensity and back pain were done separately. C. When the back pain patients rate the stimulus, they judge the experience as unpleasant (red). But for the same stimulus when they rate their own back pain the experience is judged to be significantly more pleasant (blue). Figure adapted from [12].

Figure 11

Brain regional grey matter decreases in a number of chronic pain conditions. A. Bilateral dorsolateral prefrontal cortex and unilateral thalamic grey matter decreases in chronic back pain, from [8]. B. Insula and cingulate cortex grey matter decreases in irritable bowel syndrome, from [27]. Multiple brain regions show decrease grey matter density in C. fibromyalgia, from [58], and in D. tension headache, from [93]. The illustrated data are the earliest reports of brain morphological changes in various pain conditions. The list of additional pain conditions impacting brain anatomy is expanding very quickly.

Figure 12

Evidence for brain grey matter density recovery with cessation of chronic pain. A: Left panel shows brain regions decreased in grey matter density in chronic osteoarthritis patients. Right panel shows brain regions where grey matter density increases following joint replacement and cessation of pain in osteoarthritis patients. Generally similar brain regions seem to changes with the presence and cessation of chronic pain. Adapted from [89]. B: Brain regional morphometry changes in post-traumatic headache. Grey matter density changes are shown for two brain regions in patients that develop chronic pain (3 months) and one year later when the pain subsided (1 year). In both areas grey matter signal recovers to original levels when pain symptoms subside. Adapted from [80].

Figure 13

Whole-brain relationship between grey and white matter is disrupted in chronic complex regional pain syndrome subjects. Left panel shows that white matter fractional anisotropy (FA; measured for group average skeleton which insures that the tissue examined has 95% probability of being white matter) is correlated to total neocortical volume of the brain (after correcting for age effects). The right panel is similar data in complex regional pain syndrome patients, and shows that the relationship is destroyed. In both panels each symbol is the brain of a subject, red = healthy controls, blue = patients. Adapted from [41].

Figure 14

A model regarding brain circuitry involved in the transition from acute to chronic pain. Nociceptive information, perhaps distorted by peripheral and spinal cord sensitization processes, impinges on limbic circuitry (Hippo, hippocampus; NAc, nucleus accumbens; and Amyg, amygdala). The interaction of limbic circuitry with prefrontal processes determines the level at which a certain pain condition transitions to a more emotional state. The limbic circuitry also provides learning/modulation signals to the rest of the cortex inducing functional and anatomical distortions that reflect the suffering and coping strategies of specific chronic pain conditions. Nociceptive signals also provide the brain with modulatory signals, and are in turn controlled by the state of suffering of the individual as well as limbic changes in arousal and motivation, through descending modulatory pathways.