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Brief Communications

Beyond Feeling: Chronic Pain Hurts the Brain, Disrupting the Default-Mode Network Dynamics

Marwan N. Baliki, Paul Y. Geha, A. Vania Apkarian and Dante R. Chialvo
Journal of Neuroscience 6 February 2008, 28 (6) 1398-1403; DOI: https://doi.org/10.1523/JNEUROSCI.4123-07.2008
Marwan N. Baliki
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Paul Y. Geha
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A. Vania Apkarian
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Dante R. Chialvo
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    Figure 1.

    Task design and brain activity differences between CBP patients and normal controls. a, Illustration of the changing vertical height of the target (gray trace) and an example of its height tracking with the modified joystick (black trace; shifted 10 units for ease of visualization) in a subject performing the visual attention tracking task. The active/rest time plot shown below represents the vector (after convolving with the hemodynamic response function) used to identify brain regions where the BOLD signal was activated or deactivated during the task. Periods of active tracking were modeled either as +1 or −1 to identify task-activated or task-deactivated regions respectively, relative to periods of rest, which were modeled as 0. Right inset, Group-averaged correlation coefficients ± SD between the target course and its tracking demonstrate that the two groups performed the task similarly. b, Group-averaged activations (red–yellow) and deactivations (blue–green) in CBP and healthy controls (random effects z > 2.3, cluster p < 0.01; overlaid on standard space). Activations were comparable between the two groups, whereas deactivations were more extensive in the controls. The last column shows the contrast (t test; p < 0.01) between controls and CBP patients. CBP patients exhibit less deactivation than normal subjects mainly in mPFC, amygdala, and PCC, all of which are considered part of the DMN.

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    Figure 2.

    Differences in time course of BOLD signal between CBP patients and healthy controls. a, Group-averaged BOLD signals from mPFC (blue) and LIPS (red) for controls (top) and CBP patients (bottom) are shown superimposed on the respective group-averaged tracking time courses (gray). The main result illustrated here is that mPFC BOLD signal is more deactivated in normal subjects than in CBP patients each time the subject engages in tracking. The arrow indicates a time in which these differences can be appreciated even by simple inspection of the traces. b, Time course of average BOLD responses for mPFC (top) and LIPS (bottom) relative to transition from rest to tracking. Task-triggered BOLD signals averaged over 135 tracking events were significantly smaller in mPFC of CBP patients selectively in the deactivation phase (*p < 0.01), at times of peak tracking (10–20 s from start of tracking), whereas task performance (magnitude tracking) did not differ between the two groups (top right). The LIPS responses were similar between the groups. Middle, Cross-correlations between BOLD signal and tracking time course for each group for different time lags (−10 to 10 s) revealed that the mPFC BOLD signal was anticorrelated to the task time course in normal subjects (mean r = −0.35 ± 0.2, SEM, at lag = 2.5 s), and that this anticorrelation was significantly attenuated (mean r = −0.11 ± 0.20, SEM, at lag = −2.5 s; p < 0.001) in CBP patients. LIPS signal was positively correlated to task execution and did not differ between the groups.

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    Figure 3.

    Disrupted correlation maps in CBP patients. Group-averaged z-score maps (n = 15 in each group) showing regions with significant correlations with the six seed regions (small circles) in normal controls (left) and in CBP patients (right). Results are shown for the three task-negative seed regions (mPFC, PCC, and LP) and three task-positive seed regions (IPS, FEF, and MT). Regions with positive correlations (red–yellow) have z scores >2.3 (p < 0.01), and those with negative correlations (blue–green) have z scores less than −2.3 (p < 0.01). Notice that in the CBP patients' map, the majority of regions identified in the control subjects as being negatively correlated (i.e., blue colored) are missing.

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    Figure 4.

    The ratio between the number of voxels with positive versus negative correlations (means ± SEM) is close to unity in healthy subjects for all the seeds but significantly larger in CBP patients (*p < 0.01, two-sampled t test).

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The Journal of Neuroscience: 28 (6)
Journal of Neuroscience
Vol. 28, Issue 6
6 Feb 2008
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Beyond Feeling: Chronic Pain Hurts the Brain, Disrupting the Default-Mode Network Dynamics
Marwan N. Baliki, Paul Y. Geha, A. Vania Apkarian, Dante R. Chialvo
Journal of Neuroscience 6 February 2008, 28 (6) 1398-1403; DOI: 10.1523/JNEUROSCI.4123-07.2008

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Beyond Feeling: Chronic Pain Hurts the Brain, Disrupting the Default-Mode Network Dynamics
Marwan N. Baliki, Paul Y. Geha, A. Vania Apkarian, Dante R. Chialvo
Journal of Neuroscience 6 February 2008, 28 (6) 1398-1403; DOI: 10.1523/JNEUROSCI.4123-07.2008
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  • The pain is mainly in the brain (once again)
    Patrick B. Wood
    Published on: 11 February 2008
  • Published on: (11 February 2008)
    Page navigation anchor for The pain is mainly in the brain (once again)
    The pain is mainly in the brain (once again)
    • Patrick B. Wood, Chief Medical Officer

    I have read with great interest the report by Baliki and colleagues describing increased prefrontal activity (“decreased deactivation”) during a cognitive paradigm in patients with chronic low back pain (Baliki et al., 2008). While the authors suggest their findings indicate that chronic pain alters brain function, by their own admission, study design disallows definitive mechanistic explanations. Excitatory prefronta...

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    I have read with great interest the report by Baliki and colleagues describing increased prefrontal activity (“decreased deactivation”) during a cognitive paradigm in patients with chronic low back pain (Baliki et al., 2008). While the authors suggest their findings indicate that chronic pain alters brain function, by their own admission, study design disallows definitive mechanistic explanations. Excitatory prefrontal afferents preferentially target interneurons that inhibit mesolimbic projections (Carr & Sesack, 2000), while attenuated dopaminergic activity within the striatum augments nociceptive behavior (Altier & Stewart, 1999; Saadé et al, 1997). One would therefore anticipate that a predisposition towards increased prefrontal activity (i.e. “hyperfrontality”) would produce a proportional decrease in mesolimbic activity thereby augmenting nociception and, ostensibly, placing one at increased risk for developing chronic pain. Indeed, relative increases in prefrontal activity among healthy subjects correlate with increased subjective pain ratings (Coghill et al., 2003), and clinical pain states are likewise associated with prefrontal hyperactivity (Apkarian et al, 2001; Cook et al., 2004). Conversely, the inverse relationship between prefrontal activation and mesolimbic reactivity may underlie the observation that schizophrenia, which is associated with both hypofrontality (Andreasen et al., 1997) and mesolimbic hyperactivity (Bertolino et al., 1999), is also associated with hypoalgesia (Potvin & Marchand, 2007). Thus, chronic pain might be the result of increased prefrontal activity rather than its cause.

    References

    Altier N, Stewart J (1999) The role of dopamine in the nucleus accumbens in analgesia. Life Sci. 65:2269-2287.

    Andreasen NC, O'Leary DS, Flaum M, Nopoulos P, Watkins GL, Boles Ponto LL, Hichwa RD (1997) Hypofrontality in schizophrenia: distributed dysfunctional circuits in neuroleptic-naïve patients. Lancet 349:1730- 1734.

    Apkarian AV, Thomas PS, Krauss BR, Szeverenyi NM (2001) Prefrontal cortical hyperactivity in patients with sympathetically mediated chronic pain. Neurosci Lett 311:193-197.

    Baliki MN, Geha PY, Apkarian AV, Chialvo DR (2008) Beyond feeling: chronic pain hurts the brain, disrupting the default-mode network dynamics. J Neurosci 28:1398-1403.

    Bertolino A, Knable MB, Saunders RC, Callicott JH, Kolachana B, Mattay VS, Bachevalier J, Frank JA, Egan M, Weinberger DR (1999) The relationship between dorsolateral prefrontal N-acetylaspartate measures and striatal dopamine activity in schizophrenia. Biol Psychiatry 45:660- 667.

    Carr DB, Sesack SR (2000) Projections from the rat prefrontal cortex to the ventral tegmental area: target specificity in the synaptic associations with mesoaccumbens and mesocortical neurons. J Neurosci 20:3864-3873.

    Coghill RC, McHaffie JG, Yen YF (2003) Neural correlates of interindividual differences in the subjective experience of pain. Proc Natl Acad Sci U S A. 100:8538-8542.

    Cook DB, Lange G, Ciccone DS, Liu WC, Steffener J, Natelson BH (2004) Functional imaging of pain in patients with primary fibromyalgia. J Rheumatol 31:364-378.

    Potvin S, Marchand S (2007) Hypoalgesia in schizophrenia is independent of antipsychotic drugs: A systematic quantitative review of experimental studies. Pain [in press]

    Saadé NE, Atweh SF, Bahuth NB, Jabbur SJ (1997) Augmentation of nociceptive reflexes and chronic deafferentation pain by chemical lesions of either dopaminergic terminals or midbrain dopaminergic neurons. Brain Res 751:1-12.

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    Competing Interests: None declared.

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