| | Human brain mechanisms of pain perception and regulation in health and diseaseReceived 31 August 2004; accepted 2 November 2004. Abstract ContextThe perception of pain due to an acute injury or in clinical pain states undergoes substantial processing at supraspinal levels. Supraspinal, brain mechanisms are increasingly recognized as playing a major role in the representation and modulation of pain experience. These neural mechanisms may then contribute to interindividual variations and disabilities associated with chronic pain conditions. ObjectiveTo systematically review the literature regarding how activity in diverse brain regions creates and modulates the experience of acute and chronic pain states, emphasizing the contribution of various imaging techniques to emerging concepts. Data SourcesMEDLINE and PRE-MEDLINE searches were performed to identify all English-language articles that examine human brain activity during pain, using hemodynamic (PET, fMRI), neuroelectrical (EEG, MEG) and neurochemical methods (MRS, receptor binding and neurotransmitter modulation), from January 1, 1988 to March 1, 2003. Additional studies were identified through bibliographies. Study SelectionStudies were selected based on consensus across all four authors. The criteria included well-designed experimental procedures, as well as landmark studies that have significantly advanced the field. Data SynthesisSixty-eight hemodynamic studies of experimental pain in normal subjects, 30 in clinical pain conditions, and 30 using neuroelectrical methods met selection criteria and were used in a meta-analysis. Another 24 articles were identified where brain neurochemistry of pain was examined. Technical issues that may explain differences between studies across laboratories are expounded. The evidence for and the respective incidences of brain areas constituting the brain network for acute pain are presented. The main components of this network are: primary and secondary somatosensory, insular, anterior cingulate, and prefrontal cortices (S1, S2, IC, ACC, PFC) and thalamus (Th). Evidence for somatotopic organization, based on 10 studies, and psychological modulation, based on 20 studies, is discussed, as well as the temporal sequence of the afferent volley to the cortex, based on neuroelectrical studies. A meta-analysis highlights important methodological differences in identifying the brain network underlying acute pain perception. It also shows that the brain network for acute pain perception in normal subjects is at least partially distinct from that seen in chronic clinical pain conditions and that chronic pain engages brain regions critical for cognitive/emotional assessments, implying that this component of pain may be a distinctive feature between chronic and acute pain. The neurochemical studies highlight the role of opiate and catecholamine transmitters and receptors in pain states, and in the modulation of pain with environmental and genetic influences. ConclusionsThe nociceptive system is now recognized as a sensory system in its own right, from primary afferents to multiple brain areas. Pain experience is strongly modulated by interactions of ascending and descending pathways. Understanding these modulatory mechanisms in health and in disease is critical for developing fully effective therapies for the treatment of clinical pain conditions. 1. Introduction  Up to 15 years ago and until the advent of non-invasive human brain imaging methodologies, our understanding of the role of the brain, above the spinal cord, in pain processing was limited and based primarily on animal anatomical and electrophysiological studies. The specific role of the cerebral cortex remained unsettled and heavily influenced by pronouncements of Head and of Penfield that questioned the participation of the cortex in human pain states. There has been a veritable revolution in these concepts, driven mainly by new technologies that have made the human brain available for direct examination and comparison between normal subjects and clinical pain patients. We can now assert the role of the cortex in pain perception and begin to subdivide different cortical and sub-cortical areas as to their specific role in pain perception and modulation. In this systematic review we highlight these advances in the field. We perform a meta-analysis comparing brain regions observed to be active with different brain imaging modalities. Brain imaging technologies available for studying the brain in pain are summarized in Table 1, where spatial and temporal properties of the different methods are indicated as well as their primary impact in pain research. We also perform a meta-analysis for experimental pain in normal subjects as compared to chronic clinical pain conditions. These analyses highlight the advantages of different imaging techniques in identifying distinct properties of the brain network for pain, and show that the brain activity in this network undergoes several changes in chronic clinical pain conditions. Moreover, we review the human brain imaging evidence for somatotopy, psychological modulation, temporal sequence of cortical activity, and the role of opiates and catecholamines in the modulation of pain. | | |  | Method | Energy source | Spatial resolution (mm) | Temporal resolution (s) | Constraints | Output measured | Application in pain studies | |
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| FMRI | Radio waves | 4–5 | 4–10 | Immobilization, loud, cooperation | Relative cerebral blood flow | Most used, mainly for localizing brain activity | | | EEG/MEG | Intrinsic electricity | 10 | 0.001 | Artifact, lack of unique localization | Electrophysiology of brain events | Increasing in use, mainly for detecting temporal sequences | | | Nuclear (PET/SPECT) | Radiation | 5–10 | 60–1000 | Radiation limits, immobilization | Physiology, neurochemistry, absolute values | Decreasing in use, becoming limited to neurochemistry | | | MR spectroscopy | Radio waves | 10 | 10–100 | Immobilization, loud | Relative chemical concentrations | Recently used, for detecting long term changes in brain chemistry | | |
| | | | | | | | | Brain imaging techniques available but rarely or not yet used in pain studies or, not covered in this review | | | Structural MRI | Radio waves | 1 | N/A | Immobilization, loud | Structure, vasculature, white matter | | | | Post mortem | N/A | 0.001 | N/A | Post mortem | Microarchitecture, chemoarchirtecture | | | | Trans-cranial magnetic/electric stimulation | Magnetic/electric fields | 10 | 0.01 | Risk of seizures, immobilization, loud | Electrophysiology, conduction times | | | | Near-infrared spectroscopy and imaging | Near-infrared | 0.05 | 0.05 | Immobilization, surface >depth, limited field of view | Relative cerebral blood flow | | | | Single or multi-unit electrophysiology | Intrinsic electricity | 0.01–1 | 0.01 | Invasive, direct access to brain | Electrophysiology, not covered in this review | | | | | |
2. Methods Papers related to the topic were identified by searching for each technology included in this review, combined with the word pain. Ovid PRE-MEDLINE and MEDLINE databases were searched between January 1, 1988 and March 1, 2003. The search terms were: single photon and SPECT; electroencephalography and EEG; and magnetoencephalography and MEG; laser evoked; magnetic resonance spectroscopy and MRS; positron emission and PET; and functional MRI and fMRI. These terms were combined with the word pain, limiting the outputs to English language and human studies. The terms electroencephalography, magnetoencephalography, MEG and EEG yielded 80,196 articles. Combining these terms with pain for the years 1988–2003, limited to English and Human studies (104,124 articles), resulted in 480 articles. Similarly, the combinations: positron emission, PET and pain identified 274 articles; functional MRI, fMRI and pain identified 88 articles; single photon emission, SPECT, and pain identified 288 articles; magnetic resonance spectroscopy and MRS were combined with the term brain and then with pain resulting in 11 articles. Additional papers were identified from bibliographies. From this set of articles, papers not directly related to pain, case reports, reviews, and studies of acupuncture were eliminated. Of the remaining studies only those that satisfied quality criteria of indicating group responses, having well-defined painful stimuli, or pain conditions, and proper control states or groups were included in the review. We refrained from using more rigid criteria mainly because of the diversity of the studies. eTable 1, eTable 2, eTable 3, eTable 4, eTable 5 list the papers that examine pain related brain activity in normal subjects, using PET, fMRI, and SPECT, for brain areas reported active in pain (eTable 1), for somatotopic organization of pain representation in the brain (eTable 2), psychological modulation of pain (eTable 3), brain areas reported activated for pain when monitored for electrical or magnetic signals, EEG and MEG (eTable 4), and for clinical pain related brain activity in patients, using PET, fMRI, SPECT, perfusion-MRI and MRS, including studies using deep brain stimulation and capsaicin induced allodynia in normal subjects (eTable 5). The review also covers studies of neuroreceptor and neurotransmitter modulation by pain (24 articles), these are only covered in the narrative section. | | | | Source | Scan type | Pain stimulus | Areas activated | |
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| Jones et al. (1991) | PET | Contact heat | ACC, Th, BG | | | Talbot et al. (1991) | PET | Contact heat | S1, S2, ACC | | | Apkarian et al. (1992) | SPECT | Contact heat | S1 decrease | | | Crawford et al. (1993) | SPECT | Ischemia | S1 | | | Casey et al. (1994) | PET | Contact heat | S1, S2, IC, ACC, Th, BS, CB | | | Davis et al. (1995) | fMRI | Electric shock | S1, ACC | | | Casey et al. (1996) | PET | Contact heat | S2, IC, ACC, Th, PFC, PMC, PCC, BG, BS, CB | | | Craig et al. (1996) | PET | Contact heat | S1, S2, IC, ACC | | | Craig et al. (1996) | PET | Cold | S1, S2, IC, ACC | | | Craig et al. (1996) | PET | Thermal grill illusion | S1, S2, IC, ACC | | | Vogt et al. (1996) | PET | Contact heat | ACC | | | Aziz et al. (1997) | PET | Painful esophagus distention | S1, S2, IC, ACC | | | Davis et al. (1997) | fMRI | Electric shock | ACC | | | Derbyshire et al. (1997) | PET | Contact heat | S1, ACC, Th, PFC, PMC, PP, Hippo, Amyg decrease | | | Rainville et al. (1997) | PET | Contact heat | S1, S2, IC, ACC, | | | Silverman et al. (1997) | PET | Rectal distension | ACC | | | Svensson et al. (1997) | PET | Laser heat | S2, IC, Th, PFC, PP, PMC, CB | | | Svensson et al. (1997) | PET | Muscular electric shock | S1, S2, IC, ACC, Th, PP, CB, BG | | | Binkofski et al. (1998) | fMRI | Esophagus distension | S1, S2, IC, ACC, PMC | | | Coghill et al. (1998) | PET | Capsaicin | Global decrease | | | Davis et al. (1998) | fMRI | Cold | S2, IC, Th | | | Davis et al. (1998) | fMRI | Contact heat | S2, IC, Th | | | Disbrow et al. (1998) | fMRI | Electric shock | S1, S2, CB | | | Iadarola et al. (1998) | PET | Capsaicin | S1, IC, ACC, Th, CB, BG, SMA, PAG, superior colliculus | | | Jones et al. (1998) | fMRI | Cold | ACC, PFC, parieto-occipital | | | Derbyshire and Jones (1998) | PET | Contact heat tonic | IC, ACC, Th, PFC, BG | | | Derbyshire et al. (1998) | PET | Contact heat | ACC | | | Oshiro et al. (1998) | fMRI | Electric shock | S2, IC | | | Paulson et al. (1998) | PET | Contact heat | IC, ACC, PMC, PFC, CB | | | Porro et al. (1998) | fMRI | Ascorbic acid | S1, ACC, PMC, M1 | | | Svensson et al. (1998) | PET | Contact heat | S1, S2, IC, ACC, | | | Apkarian et al. (1999) | fMRI | Contact heat | IC, PP | | | Baciu et al. (1999) | fMRI | Rectal distension | S1, S2, IC, ACC, PFC, PCC, PP, occipital | | | Becerra et al. (1999) | fMRI | Contact heat | S1, S2, IC, PFC, CB Amyg, Hypo decrease | | | Gelnar et al. (1999) | fMRI | Contact heat | S1, S2, IC, PCC, M1 | | | Coghill et al. (1999) | PET | Contact heat | S1, S2, IC, ACC, Th, PFC, BG, CB | | | Peyron et al. (1999) | PET | Contact heat | S1, S2, IC, ACC, Th, PFC | | | Tolle et al. (1999) | PET | Contact heat | Th, ACC, PFC, PCC, PVG | | | Apkarian et al. (2000) | fMRI | Contact heat | S1, S2, IC, M1 | | | Creac’h et al. (2000) | fMRI | Cutaneous pressure | S1, S2, IC, ACC, Th, PFC, PCC, temporal | | | Kwan et al. (2000) | fMRI | Contact heat | ACC | | | Kwan et al. (2000) | fMRI | Cold | ACC | | | Mertz et al. (2000) | fMRI | Rectal distension (normal subjects) | IC, ACC, Th, PFC | | | Tracey et al. (2000) | fMRI | Contact heat | S1, IC, ACC, Th, PFC, M1, PMC, PP, BG | | | Tracey et al. (2000) | fMRI | Cold | S1, IC, ACC, Th, PFC, M1, PMC, PP, BG | | | Becerra et al. (2001) | fMRI | Contact heat | S1, IC, Th, CB, Amyg, PAG, VT | | | Casey et al. (2001) | PET | Contact heat | S1, S2, IC, ACC, Th, CB | | | Coghill et al. (2001) | PET | Contact heat | S1, S2, IC, ACC, Th, PFC, CB, BG | | | Fulbright et al. (2001) | fMRI | Cold | S1, S2, ACC, IC, Th, PFC | | | Hofbauer et al. (2001) | PET | Contact heat | S1, S2, IC, ACC | | | Ladabaum et al. (2001) | PET | Gastric distension | IC, Th, ACC, BG, CB, occipital | | | Bingel et al. (2002) | fMRI | Laser heat | BG, CB, Amyg, BS, Hippo | | | Buchel et al. (2002) | fMRI | Laser heat | S1, S2, IC, Amyg | | | Buchel et al. (2002) | fMRI | Laser heat | ACC | | | Chang et al. (2002) | fMRI | Contact heat | S1, S2 | | | Davis et al. (2002) | fMRI | Cold prickle | S2, IC, ACC, Th, PFC, PMC, BG | | | Fabri et al. (2002) | fMRI | Cutaneous pressure | S1, S2, IC, ACC | | | Korotkov et al. (2002) | PET | Muscular hypertonic saline | IC, BG | | | Kurata et al. (2002) | fMRI | Contact heat | S2, IC, ACC, PFC, BG, PMC | | | Niddam et al. (2002) | fMRI | Muscular electric shock | S2, IC, ACC, Th, PFC, BG, PCC, | | | Peyron et al. (2002) | PET and fMRI | Laser heat | S2, IC | | | Petrovic et al. (2002b) | PET | Cold | S1 | | | Bingel et al. (2003) | fMRI | Laser heat | S1, S2, IC, Th | | | Helmchen et al. (2003) | fMRI | Contact heat | CB | | | Rolls et al. (2003) | fMRI | Cutaneous pressure | IC, ACC, PFC | | | Strigo et al. (2003) | fMRI | Contact heat | S1, S2, IC, ACC, Th, PFC, BG, CB | | | Strigo et al. (2003) | fMRI | Esophagus distension | S1, S2, IC, ACC, Th, BG, CB | | | | |
| | | | Source | Scan type | Pain stimulus | Stimulated sites | Brain region | Organization | |
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| Tarkka and Treede (1993) | EEG | Laser heat | Hand, foot | S1 | Foot medial, hand lateral | | | Tarkka and Treede (1993) | EEG | Laser heat | Hand, foot | S2, ACC | No organization | | | Andersson et al. (1997) | PET | Capsaicin | Hand, foot | S1 | Foot medial, hand lateral | | | Xu et al. (1997) | PET | Laser heat | Hand, foot | S2 | No organization | | | Xu et al. (1997) | PET | Laser heat | Hand, foot | IC | No organization | | | DaSilva et al. (2002) | fMRI | Contact heat | V1, V2, V3, thumb | BS | rostrocaudal | | | DaSilva et al. (2002) | fMRI | Contact heat | V1, V2, V3, thumb | Th | Medio-lateral | | | DaSilva et al. (2002) | fMRI | Contact heat | V1, V2, V3 | S1 | Rostro-caudal, medio-lateral | | | Strigo et al. (2003) | fMRI | Contact heat and esophagus distension | Chest, esophagus | S1 | Medio-lateral | | | Vogel et al. (2003) | EEG | Laser heat | Face, hand | S2 | Face anterior, hand posterior | | | | |
| | | | Source | Scan type | Task | Brain regions | Findings | |
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| Rainville et al. (1997) | PET | Hypnotic suggestions for unpleasantness | ACC | Pain-evoked activity modulated by suggestions for increased or decreased unpleasantness | | | Bushnell et al. (1999) | PET | Attention, distraction | S1 | Pain-evoked activity reduced when attending auditory stimulus | | | Hsieh et al. (1999b) | PET | Anticipation | PFC, ACC, PAG | Activated during anticipation of pain | | | Ploghaus et al. (1999) | fMRI | Anticipation | PFC, IC, CB | Activated during anticipation of pain | | | Petrovic et al. (2000) | PET | Attention, distraction | PFC, PAG | Pain-evoked activity reduced when performing cognitive task | | | Petrovic et al. (2000) | PET | Attention, distraction | PFC | Pain-evoked activity increased when performing cognitive task | | | Faymonville et al. (2000) | PET | Hypnotic suggestions for reduced pain | ACC | Pain-evoked activity reduced during hypnotic suggestions | | | Ploghaus et al. (2000) | fMRI | Expectation | Hippo, PFC, CB | Activated during expected pain that was omitted | | | Sawamoto et al. (2000) | fMRI | Expectation | S2, IC, ACC | Enhanced activation to warm stimulus when expecting pain | | | Frankenstein et al. (2001) | fMRI | Attention, distraction | ACC | Verbal task distracter reduced pain-evoked ACC area 24 activation, and activated area 32 | | | Hofbauer et al. (2001) | PET | Hypnotic suggestions for pain sensation | S1 | Pain-evoked activation modulated by suggestions for increased or decreased pain sensation | | | Longe et al. (2001) | fMRI | Attention, distraction | ACC, IC, Th | Distracting vibratory stimulus reduced pain-evoked activity | | | Ploghaus et al. (2001) | fMRI | Anxiety | Hippo, peri-genual ACC, mid-IC | Anxiety amplified pain-related responses | | | Bantick et al. (2002) | fMRI | Attention, distraction | ACC, IC, Th | Pain-evoked activity reduced during Stroop counting task | | | Bantick et al. (2002) | fMRI | Attention, distraction | ACC, PFC | Activated during Stroop counting task distraction | | | Brooks et al. (2002) | fMRI | Attention, distraction | IC | Pain-evoked activity reduced when attending visual stimulus | | | Petrovic et al. (2002a) | PET | Placebo | Rostral ACC | Activated during placebo analgesia | | | Porro et al. (2002) | fMRI | Anticipation | S1, rostral ACC | Modulated during anticipation of pain | | | Tracey et al. (2002) | fMRI | Attention, distraction | PAG | Activated during distraction from pain | | | Phillips et al. (2003) | fMRI | Emotions | ACC, IC | Larger pain-evoked activation during fearful faces than neutral faces | | | | |
| | | | Source | Scan type | Pain stimulus | Areas activated | |
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| Joseph et al. (1991) | MEG | Electrical, skin | S1, frontal operculum | | | Tarkka and Treede (1993) | EEG | Radiant heat | S1, S2, ACC | | | Bromm and Chen (1995) | EEG | Radiant heat | S2, ACC, frontal lobe | | | Kakigi et al. (1995) | MEG | Radiant heat | S2 | | | Kitamura et al. (1995) | MEG | Electrical, skin | S1, S2 | | | Valeriani et al. (1996) | EEG | Radiant heat | S2, IC-anterior temporal lobe, ACC | | | Hari et al. (1997) | MEG | Acid, nasal mucosa | S1, S2 | | | Kitamura et al. (1997) | MEG | Electrical, nerve | S1, S2, ACC | | | Watanabe et al. (1998) | MEG | Radiant heat | S2, medial anterior temporal lobe | | | Arendt-Nielsen et al. (1999) | MEG | Mechanical, skin | S2 | | | Dowman and Schell (1999) | EEG | Electrical, nerve | ACC, SMA | | | Loose et al. (1999) | MEG | Mechanical, esophagus | S2, frontal lobe | | | Ploner et al. (1999) | MEG | Radiant heat | S1, S2 | | | Yamasaki et al. (1999) | MEG | Radiant heat | S2–IC, ACC | | | Druschky et al. (2000) | MEG | Mechanical, skin | S1, S2, ACC | | | Kanda et al. (2000) | MEG | Radiant heat | S1, S2 | | | Ploner et al. (2000) | MEG | Radiant heat | S1, S2 | | | Valeriani et al. (2000) | EEG | Radiant heat | S2, ACC, IC-temporal cortex, | | | Bentley et al. (2002) | EEG | Radiant heat | Anterior IC, PP, PCC | | | Dowman (2001) | EEG | Electrical, nerve | ACC, SMA | | | Ninomiya et al. (2001) | MEG | Electrical, skin | S1, S2, ACC | | | Opsommer et al. (2001) | EEG | Radiant heat | S2, ACC | | | Timmermann et al. (2001) | MEG | Radiant heat | S1, S2 | | | Bentley et al. (2002) | EEG | Radiant heat | Caudal ACC | | | Inui et al. (2002) | MEG | Electrical, skin | S1, S2 | | | Maihofner et al. (2002) | MEG | Noxious cold | S2, posterior IC, ACC | | | Ploner et al. (2002b) | MEG | Radiant heat | S1, S2, ACC | | | Torquati et al. (2002) | MEG | Electrical, nerve | S1, S2 | | | Tran et al. (2002) | MEG | Radiant heat | S1, S2 | | | Valeriani et al. (2002) | EEG | Contact heat | S2, ACC, anterior temporal lobe | | | | |
| | | | Source | Scan type | Patient group | Stimulus | Areas activated | |
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| Di Piero et al. (1991) | PET | Cancer pain | Pre- vs. post-cordotomy pain relief | Th blood flow decreased during cancer pain | | | Hsieh et al. (1996) | PET | Cluster headache | Nitroglycerin | IC, ACC, PFC, BG, PP, M1, occipital, temporal | | | May et al. (1998) | PET | Cluster headache | Nitroglycerin | IC, ACC, Th, CB, BG, Hyp | | | May et al. (2000) | PET | Cluster headache | Nitroglycerin | S1/M1, IC, Th, ACC, PFC, BG, Hyp | | | May et al. (2000) | PET | Cluster headache | Nitroglycerin | IC, Th, ACC, PFC, BG, temporal | | | Weiller et al. (1995) | PET | Migraine | Spontaneous migraine | Cingulate, auditory, and visual association | | | Andersson (1998) | PET | Migraine | Aura, headache, and post Sumatriptan | Primary visual cortex blood flow decreased during headache | | | Cutrer et al. (1998) | Perfusion MRI | Migraine | Visual aura | Contralateral occipital decreased blood flow and blood volume | | | Cao et al. (1999) | fMRI | Migraine | Visually triggered headache; Checkerboard stimulus | Occipital cortex decreased stimulus responses | | | Sanchez et al. (1999) | Perfusion MRI | Migraine | Spontaneous migraine, with or without aura | Occipital cortex decreased blood flow during aura | | | Rosen et al. (1994) | PET | Cardiac pain | Dobutamine | Th, PFC, BS, Hippo | | | Rosen et al. (1996) | PET | Cardiac pain | Dobutamine | Th, PFC, BS, Hippo | | | Rosen et al. (1996) | PET | Cardiac pain | Dobutamine | Th, ACC, PFC, Hyp, occipital | | | Rosen et al. (1996) | PET | Cardiac pain | Dobutamine | ACC, PFC, temporal | | | Rosen et al. (1996) | PET | Cardiac pain | Dobutamine | IC, Th, PFC, BG, CB | | | Rosen et al. (1996) | PET | Cardiac pain, syndrome X | Dobutamine | IC, PFC | | | Rosen et al. (2002) | PET | Cardiac pain, syndrome X | Dobutamine | IC, Th, PFC, BG, CB | | | Silverman et al. (1997) | PET | IBS | Rectal distension pain, pain anticipation | PFC; in normal subjects ACC related to pain; in IBS ACC is not related to pain | | | Mertz et al. (2000) | fMRI | IBS | Rectal distension 15, 30, 50 mmHg; 50 mmHg is painful | ACC, Th for pain; in normal subjects ACC related to pain; in IBS ACC is not related to perceived pain | | | Naliboff et al. (2001) | PET | IBS | Rectosigmoid distension pain, pain anticipation | ACC, PFC, PCC | | | Bonaz et al. (2002) | fMRI | IBS | Rectal distension | None | | | Berman et al. (2002) | PET | IBS | Gastric distension, placebo-Alosetran | ACC, PFC, Hyp, BG, Amyg | | | Bernstein et al. (2002) | fMRI | IBS, IBD | Rectal distension | ACC | | | Wik et al. (1999) | PET | FM | Patients – normals | PCC PFC, parieto-temporal decreased | | | Gracely et al. (2002) | fMRI | FM | Mechanical pressure | S1, S2, IC, PP, BG S2, Th, PFC, BG decreased | | | Gracely et al. (2002) | fMRI | FM | Mechanical pressure, equated perceptually | S1, S2, IC, ACC, PP, CB | | | Fukumoto et al. (1999) | SPECT | CRPS | Blood flow | Contralateral/ipsilateral Th hyperperfusion in early CRPS; hypoperfusion in prolonged CRPS | | | Apkarian et al. (2001) | fMRI | CRPS | Contact heat, sympathetic blocks | CRPS pain associated with ACC, PFC; Th decreased | | | Willoch et al. (2000) | PET | Phantom pain | Phantom pain induced by hypnosis | S1/M1, ACC, Th, PFC | | | Iadarola et al. (1998) | PET | Normal subjects, capsaicin injury | Allodynia – touch | S1, S2, PFC, BG, CB, BS, Hippo | | | Baron et al. (1999) | fMRI | Normal subjects, capsaicin injury | Allodynia vs. touch | PFC; no change in S1, S2, ACC | | | Witting et al. (2001) | PET | Normal subjects, capsaicin injury | Allodynia – touch | S1, IC, Th, PFC, CB | | | Lorenz et al. (2002) | PET | Normal subjects, capsaicin injury | Allodynia – heat, equated perceptually | IC, Th, PFC, BG, BS | | | Hsieh et al. (1995) | PET | Mono-neuropathy | Painful state – nerve block | IC, ACC, PFC, PP Th decreased | | | Iadarola et al. (1995) | PET | Neuropathy | Neuropathy vs. normal subjects | Th decreased | | | Petrovic et al. (1999) | PET | Mono-neuropathy | Allodynia – rest | S1, S2, IC, ACC, Th, BS, CB | | | Duncan et al. (1998) | PET | Neuropathy | Deep brain stimulation Th | S1, S2, IC, Th, PFC | | | Davis et al. (2000) | fMRI | Chronic pain | Deep brain stimulation Th | ACC not related to pain relief | | | Hsieh et al. (1999a) | PET | Trigeminal neuropathy | M1 cortex electrical stimulation for pain relief | PCC PFC decreased in pain vs. pain relief | | | Grachev et al. (2000) | MRS | Chronic back pain | Chronic back pain vs. normal subjects | Decreased PFC chemistry in patients related to chronic pain | | | Grachev et al. (2001) | MRS | Chronic back pain | Chronic back pain vs. normal subjects | Decreased PFC chemistry in patients distinguished pain from anxiety | | | Grachev et al. (2002) | MRS | Chronic back pain | Chronic back pain vs. normal subjects | Decreased PFC chemistry in patients distinguished pain from anxiety | | | Grachev et al. (2003) | MRS | Chronic back pain | Chronic back pain vs. normal subjects | Decreased PFC chemistry in patients distinguished pain from depression | | | Pattany et al. (2002) | MRS | Spinal cord injury | Spinal cord injury vs. normal subjects | Decreased Th chemistry in patients | | | | |
Meta-analysis was done to calculate an incidence measure for six brain regions, to contrast between imaging modalities (Table 2) and, between brain regions active for pain in normal subjects in comparison to pain in clinical conditions (Table 3); data derived from eTable 1, eTable 4, eTable 5. Incidence for each brain region was calculated based on the inclusion of an area in the given study or given contrast and the area showing statistically significant involvement in the condition or contrast. eTable 1 lists 32 PET and 36 fMRI studies; all used in the incidence measures. One study (Iadarola et al., 1998) is listed in eTable 1, eTable 5; in the former the results for capsaicin pain is included while in the latter only results for allodynia are listed. eTable 3 lists 10 EEG studies and 20 MEG studies; all are used in the incidence comparisons in Table 2. eTable 5 lists the studies indicating brain areas involved in clinical pain conditions. Of those, only 30 PET and fMRI studies were used in the incidence calculations, perfusion-MRI, MRS, deep brain stimulation, and studies of allodynia in normal subjects were excluded from incidence measures. Thus, the eTables provide all the data used for incidence calculations. 3. Results 3.1. Acute pain 3.1.1. Defining a pain network: hemodynamic studies Hemodynamic correlates of pain were first imaged in the human brain in the 1970s by Lassen and colleagues (Lassen et al., 1978) using the radioisotope 133Xe. This technique provided little spatial resolution, but suggested that there was an increased blood flow to the frontal lobes during pain. The first three human brain imaging studies of pain using modern technologies were published in the early 1990s by Talbot et al. (1991) and Jones et al. (1991), using PET, and Apkarian et al. (1992), using SPECT. All three studies used heat pain, and although there were differences in the results of these studies, together they indicated that multiple cortical and sub-cortical regions are activated during short-duration painful cutaneous heat stimuli presented to normal subjects. Since these first experiments, many other PET and fMRI studies have been conducted examining the neural processing of painful cutaneous heat in humans and confirm that multiple brain regions are activated (eTable 1). Both primary somatosensory cortex (S1) and secondary somatosensory cortex (S2) are commonly activated in heat pain studies. Evidence suggests that the nociceptive input into these regions at least partially underlies the perception of sensory features of pain (Coghill et al., 1999, Peyron et al., 1999, Bushnell et al., 1999, Chen et al., 2002). Anterior cingulate (ACC) and insular (IC) cortices, both components of the limbic system, are activated during the majority of PET or fMRI studies of heat pain, and these regions have been implicated in the affective processing of pain (Rainville et al., 1997, Tolle et al., 1999, Fulbright et al., 2001). Prefrontal cortical areas, as well as parietal association areas, are also sometimes activated by heat pain and may be related to cognitive variables, such as memory or stimulus evaluation (Coghill et al., 1999, Strigo et al., 2003). Motor and pre-motor cortical areas are on occasion activated by heat pain, but these activations are less reliable, suggesting they may be related to pain epiphenomena, such as suppression of movement or actual pain-evoked movements themselves. Motor cortex activation may be interpreted or obscured as S1 activity, and some midcinglate areas activated by painful stimuli can be confounded by supplementary motor activity. Subcortical activations are also observed, most notably in thalamus (Th), basal ganglia, and cerebellum (eTable 1). Fig. 1 illustrates the brain regions most commonly reported activated in pain studies. The indicated locations approximate the brain regions discussed in this review and should be used only as a general guide because within and across imaging studies there are important differences in specific activation sites. For example, we illustrate prefrontal activity mainly within the medial prefrontal cortex, although recent studies indicate important interactions between medial and lateral prefrontal areas. Other brain areas that we think are importantly involved in pain perception are also included in the figure even though their roles are not covered in this review. In examining eTable 1, it becomes evident that there are many differences, as well as similarities, in brain regions that are reported to be activated. Some of these differences can be explained by variations in technical procedures and differences in statistical analyses and power: some analyses use simple subtractions others use regression comparisons; methods and assumptions for calculating variance differ among laboratories and analysis techniques; methods of accounting for multiple comparisons varies; number of subjects used and hence the power of a statistical test varies greatly among experiments. It must be remembered that, as with any statistical test, a negative result does not mean that there is no neuronal activity in the specific region; it only means that no activation was detected using a stringent statistical requirement that biases results towards many more false negative than false positive findings. Many differences most probably reflect the fact that different individuals have dissimilar experiences when presented with a painful stimulus. Both gender and genetic factors are important determinants of pain, and imaging studies confirm these differences (Paulson et al., 1998, Zubieta et al., 1999). Further, for any individual, the pain experience will vary in different experiments, depending upon the environment, experimenter, instructions, stimulus and procedural design. However, not surprisingly, even within a single experiment, in which all of the factors are standardized, there are large individual differences in the subjective pain experience, which is reflected in distinctive patterns of brain activity (Davis et al., 1998). Despite of these important differences across studies, our meta-analysis indicates that incidence for the six most commonly reported areas (ACC, S1, S2, IC, Th, PFC, Table 2) are similar between hemodynamic imaging modalities PET and fMRI. The borderline difference in incidence for PFC activation between PET and fMRI seems to be due to reduced PFC activation reports in older PET studies, most likely due to the lower sensitivity of the earlier PET studies (note that this bias is naturally adjusted by the number of PET studies included in the comparison between normal subjects and patients, see below). 3.1.2. Defining a pain network: pain-evoked potentials and magnetic fields The first evoked potentials in response to brief painful stimuli were published in the 1960s (Spreng and Ichioka, 1964) and corresponding magnetic fields in the 1980s (Hari et al., 1983). Detailed analysis of the cortical representation of pain by electrophysiological measures (see eTable 4), however, was greatly advanced by the independent evidence from the first PET studies (Jones et al., 1991, Talbot et al., 1991). Subsequent EEG and MEG source analyses documented electrical activity in S1, S2, and its vicinity in the frontoparietal operculum, IC or adjacent anterior temporal lobe, and ACC (Joseph et al., 1991, Tarkka and Treede, 1993, Kakigi et al., 1995, Bromm and Chen, 1995, Ploner et al., 1999, Dowman and Schell, 1999, Valeriani et al., 2003). Intracranial recordings as part of the presurgical evaluation in epilepsy patients confirmed the sources in S1, S2, IC, and ACC (Lenz et al., 1998a, Lenz et al., 1998b, Kanda et al., 2000, Vogel et al., 2003). Our meta-analysis (Table 2) indicates that there are important differences between EEG and MEG based studies regarding the detection of responses to painful stimuli in S1, S2, and ACC: MEG is more sensitive to determine the sources in S1 and S2 that are oriented tangentially to the scalp, while the radially oriented current flow in ACC activity is more frequently detected by EEG. The MEG technique is intrinsically insensitive to radially oriented current flow. EEG source analysis is sensitive to any orientation of the underlying dipole, which on the other hand may make it more difficult to separate multiple sources than in the restricted view of MEG. Very few EEG or MEG studies demonstrate activity in IC and neither method shows activation of Th or PFC. IC and Th may be missed due to their position deep inside the brain, since location accuracy of both techniques deteriorates with increasing distance from the scalp. Compared with hemodynamic imaging studies, electrical and magnetic recordings are highly sensitive to describe activity in the S2 region, but outside this region hemodynamic methods seem to be more sensitive. The temporal resolution of EEG and MEG, however, is unsurpassed. For example, the dual pain sensation elicited by a single brief painful stimulus that is due to the different conduction times in nociceptive A- and C-fibers (about 1 s difference) is reflected in two sequential brain activations in EEG and MEG recordings from S1, S2 and ACC (Bromm and Treede, 1983, Arendt-Nielsen, 1990, Bragard et al., 1996, Magerl et al., 1999, Opsommer et al., 2001, Tran et al., 2002, Ploner et al., 2002a, Iannetti et al., 2003). The first, A fiber mediated, brain activation can further be subdivided into an early (100–200 ms after stimulus onset) and a late EEG/MEG response (beyond 200 ms latency; Treede et al., 1988). EEG mapping studies (Kunde and Treede, 1993, Miyazaki et al., 1994), source analysis (Tarkka and Treede, 1993, Valeriani et al., 1996, Ploner et al., 1999), and intracranial recordings (Lenz et al., 1998a, Frot et al., 1999) show that the earliest pain-induced brain activity originates in the vicinity of S2. In contrast, tactile stimuli activate this region only after processing in the primary somatosensory cortex (Ploner et al., 2000). The adjacent dorsal IC is activated slightly but significantly later than the operculum (Frot and Mauguiere, 2003). These observations support the suggestion derived from anatomical studies that the S2 region and adjacent IC are a primary receiving area for nociceptive input to the brain (Apkarian and Shi, 1994, Craig, 2002). The sources for later EEG and MEG signals (beyond 200 ms peak latency) have been localized in ACC, close to the border between its anterior and posterior parts (Bentley et al., 2002, Peyron et al., 2002). This relatively posterior location may be related to the phasic nature of the stimuli used. Late EEG and MEG signals correlate more closely with perceived pain intensity than with stimulus strength (Beydoun et al., 1993). This correlation pattern as well as the long latency of its activation suggests a role of ACC in cognitive-evaluative stages of pain processing. All EEG and MEG studies in eTable 4 exploit the high signal-to-noise ratio of evoked potentials. Changes in ongoing EEG patterns or coherences following tonic painful stimuli, in contrast, are more subtle and their specificity for nociceptive processing is still being debated (Backonja et al., 1991, Ferracuti et al., 1994, Chen et al., 1998, Chang et al., 2002). 3.1.3. Neural correlates of different types of pain Cortical activation patterns related to many types of painful stimuli have now been studied. As shown in eTable 1, these stimuli include cutaneous noxious cold, muscle stimulation using electric shock or hypertonic saline, capsaicin, colonic distension, rectal distension, gastric distension, esophageal distension, ischemia, cutaneous electric shock, ascorbic acid, laser heat, as well as an illusion of pain evoked by combinations of innocuous temperatures. As observed when comparing data across studies of cutaneous contact heat stimulation, these varying types of pain produce many similarities and differences in cortical and sub-cortical sites that show significant activation. The differences could be attributed to technical and statistical differences, as discussed above, varying pain intensities, different cognitive states or variations specifically related to the modality of pain. Without comparing the different modalities in the same subjects and acquiring detailed evaluations of independent aspects of the individuals’ cognitive state, the source of the variability in results cannot be determined. For example, Strigo et al. (2003) compared in the same subjects cortical activations produced by esophageal distension and contact heat on the chest, with the perceived pain intensity matched between stimuli for each subject. For these subjects the visceral and cutaneous pain both led to activations in S1, S2, ACC and IC, but the exact loci within the regions differed for the two types of pain, thus supporting the idea that there may be sub-regional differences in the processing of different types of pain. eTable 1 also shows many similarities across these studies. The ACC appears to have a particularly robust activation across different stimulus modalities and measurement techniques (81% with fMRI, 94% with PET, 100% with EEG, Table 1), although the locus of this activation varies among studies. Vogt et al. (1996) initially subdivided the ACC into four components and suggested that affective reactions to pain would be localized to perigenual (or rostral) ACC, while cognitive processes to mid-cingulate (at or around supplementary motor region) activations. Recently, Derbyshire (2003) further subdivided ACC to six components, proposing differential responses to different visceral stimuli (for an alternative viewpoint, see Peyron et al., 2000). In earlier studies S1 cortex showed a less reliable pain-related activation (see Bushnell et al., 1999), even though single nociceptive neurons have been identified in this region in monkey (Kenshalo and Isensee, 1983, Kenshalo et al., 1988). The current analysis shows that similar numbers of studies report S1 activity as S2 activity using PET or fMRI imaging methods; with an overall rate of reporting being 75% for both (Table 2). Previous reviews argued that the lower incidence in observing activity in S1 as compared to S2 was most likely due to technical difficulties (Bushnell et al., 1999, Peyron et al., 2000); mainly due to differences in spatial extent of activity as compared to spatial resolution of brain imaging techniques. It seems that more recent studies have overcome such difficulties. Unexpectedly, IC shows the highest incidence of activity (94% in Table 2). This area of the cortex is anatomically heterogeneous (Mesulam and Mufson, 1982) and activations in its posterior portion may be more related to sensory aspects of pain. The more anterior IC is anatomically more continuous with PFC and as a result it may be more important in emotional, cognitive and memory related aspects of pain perception. 3.2. Somatotopic organization of pain in the brain Although studies of hemodynamic changes related to pain provide imprecise spatial resolution, ranging from 2 to 15 mm, some information has been obtained related to somatotopic organization of pain in the human brain. eTable 2 shows that such organization has been primarily observed in S1 cortex, with the organization following the same somatotopy as observed for tactile input. No clear somatotopic organization has been reported for painful input into S2 cortex, but a number of fMRI and MEG studies have found a topographic organization of S2 for non-painful somatosensory input (Maeda et al., 1999, Del Gratta et al., 2000, Disbrow et al., 2000, Del Gratta et al., 2002), suggesting that such organization may also exist for nociceptive input. Within S1, somatotopic arrangement of EEG and MEG sources was found to be consistent with the tactile homunculus for hand and foot stimulation (Tarkka and Treede, 1993, Ploner et al., 1999), while the face region was too far lateral to be distinguishable from S2 and IC (Bromm and Chen, 1995). Within the S2–IC region, the face was represented anterior of the foot (Vogel et al., 2003), which is in contrast to the mediolateral tactile representation in that region. This difference in somatotopy argues for a separation of tactile and nociceptive areas within the region. 3.3. Psychological modulation of pain The advent of human brain imaging has provided an important new avenue for understanding the neural basis of psychological modulation of pain. Brain imaging experiments have explored mechanisms underlying attentional and emotional modulation of pain, as well as activity related to expectation and anticipation of pain (see eTable 3). Studies examining the effects of distraction show modulation of pain-evoked activity in S1, ACC, IC, and Th. Other regions, including PAG, parts of ACC, and orbitofrontal cortex (within PFC) are activated when subjects are distracted from pain, suggesting that these regions may be involved in the modulatory circuitry related to attention. Hypnotic suggestions also alter pain-evoked activity, but the specific regions involved depend on the nature of the suggestions (Rainville et al., 1997, Faymonville et al., 2000, Hofbauer et al., 2001). Similarly, emotional state can influence pain perception, and a recent study shows that negative emotional states enhance pain-evoked activity in limbic regions, such as ACC and IC (Phillips et al., 2003). Finally, the anticipation or expectation of pain can activate pain-related areas, regions such as S1, ACC, PAG, IC, PFC and cerebellum, in the absence of a physical pain stimulus (Beydoun et al., 1993, Ploghaus et al., 1999, Hsieh et al., 1999b, Sawamoto et al., 2000, Porro et al., 2002, Villemure and Bushnell, 2002). EEG and MEG studies have shown that cognitive modulation of pain by attention involves early sensory processing in S2–IC (Legrain et al., 2002, Nakamura et al., 2002) and later processing in ACC (Beydoun et al., 1993, Kanda et al., 1996, Siedenberg and Treede, 1996, Garcia-Larrea et al., 1997). Attentional modulation may in part reflect a change in cortical processing and in part a decrease in ascending afferent input from the spinal cord due to activation of descending noxious inhibitory controls. EEG signals can document this type of inhibitory control in humans (Plaghki et al., 1994, Reinert et al., 2000, Hoshiyama and Kakigi, 2000). In contrast to distraction paradigms, hypnotic suggestion influenced pain perception (Arendt-Nielsen et al., 1990) but did not affect the EEG signals (Meier et al., 1993, Friederich et al., 2001). Anticipation of painful stimuli, or priming with pain-related adjectives, significantly enhanced the EEG signals (Miyazaki et al., 1994, Dillmann et al., 2000). In turn, interference of chronic pain with the performance of cognitive functions has also been shown in EEG studies (Lorenz and Bromm, 1997, Lorenz et al., 1997). 3.4. Measures of neuroreceptors and neurotransmitters Two main approaches have been used to study the neurochemistry of pain: examination of brain metabolic function in response to relevant pharmacological agents, and direct measurement of receptors for neurotransmitters. The latter involves the use of radiolabeled pharmaceuticals introduced at tracer doses. Acquisition of data over time, as the radiotracer binds to specific receptor sites, together with appropriate kinetic models, allows for the quantification of receptor sites and enzyme function in human subjects with PET or SPECT. The majority of studies have examined the endogenous opioid system and its receptors, with the μ-opioid receptor type being the one primarily mediating the effect of clinically utilized opiate medications. More recently, other neurotransmitter systems, such as dopamine, have also been examined. The exogenous administration of μ-opioid receptor agonist drugs has been shown to dose-dependently increase rCBF, and by extension metabolic activity, in regions rich in μ-opioid receptors, such as ACC, PFC, Th, basal ganglia and amygdala (Firestone et al., 1996, Schlaepfer et al., 1998, Wagner et al., 2001). Additional areas of change in blood flow responses, both increases and reductions depending on the regions, were also found in areas with relatively low content of μ-opioid receptors, possibly reflecting indirect effects of the opioid agonists activating and inhibiting neuronal systems projecting to these regions. An initial study on the effects of the μ-opioid agonist, fentanyl, on rCBF responses to heat pain did not show clear effects (Adler et al., 1997). Subsequent work using painful cold showed that the enhancements in rCBF elicited by this stimulus were prominently reduced by the μ-opioid agonist in most regions, confirming an inhibitory effect of fentanyl on measures of pain-induced neuronal activity (Casey et al., 2000). Utilizing similar methodology, rCBF responses to a μ-opioid agonist, remifentanil, were compared to that elicited by a placebo (Petrovic et al., 2002a). The two effects overlapped in terms of rCBF increases in dorsal ACC, suggesting that this brain region may be involved in placebo effects. Perhaps more notably, placebo responders showed responses to remifentanil that were more prominent than non-responders. These data suggest that the placebo effect on pain responses may be mediated by inter-individual variations in the ability to activate this neurotransmitter system, as hypothesized by others (Amanzio and Benedetti, 1999). Direct measures of opioid neurotransmission have been obtained using both non-selective radiotracers for opioid receptors (e.g., diphrenorphine) and μ-opioid receptor selective radiotracers (e.g., carfentanil). Utilizing [11C]diphrenorphine, the in vivo availability of opioid receptors was examined in a small group of patients diagnosed with rheumatoid arthritis (Jones et al., 1994), and in six patients diagnosed with trigeminal neuralgia (Jones et al., 1999). Relief of pain was associated with increases in the concentration of opioid receptors binding the radiolabeled tracer in a number of brain regions, which included ACC, IC, PFC, Th, and basal ganglia. The absence of a control group in these studies did not allow the investigators to determine whether the increases in opioid receptor binding after pain relief were comparable to those of individuals free of painful conditions. Dynamic changes in the activity of endogenous opioid system and μ-opioid receptors have been recently described utilizing a selective μ-opioid radiotracer, [11C]carfentanil, and a model of sustained muscular pain in healthy subjects. Reductions in the in vivo availability of μ-opioid receptors, reflecting the activation of this neurotransmitter system, were observed in ACC, PFC, IC, Th, ventral basal ganglia, amygdala and periaqueductal gray. The activation of this neurotransmitter system was also correlated with suppression of sensory and affective qualities of the pain with distinct neuroanatomical localizations (Zubieta et al., 2001). An area uniquely associated with the suppression of pain affect scores, as measured with the McGill Pain Questionnaire pain affect subscale, was the dorsal ACC, which was localized, for this type of scale and sustained pain model, in a region just posterior to a region identified to be involved in acute pain unpleasantness (Rainville et al., 1997, Tolle et al., 1999). Substantial interindividual differences were also observed in both receptor-binding levels and in the magnitude of activation of this neurotransmitter system. Gender differences in the concentration of μ-opioid receptors had been previously described in human subjects, with women showing higher binding than men in most brain regions. Interestingly, these gender differences were less prominent in the amygdala and thalamus of post-menopausal women, compared to men of the same age, an effect that may be related to the effects of estrogen on μ-opioid receptor concentrations and endogenous opioid neurotransmission (Smith et al., 1998, Zubieta et al., 1999). Higher concentrations of μ-opioid receptors in women would explain the observations of a higher sensitivity to μ-opioid agonists in women in pharmacological challenge studies (Zacny, 2001). Gender differences in the capacity to activate μ-opioid receptor-mediated neurotransmission were subsequently explored using [11C]carfentanil and the sustained muscular pain model. Women studied during the early follicular phase of the menstrual cycle, when estradiol and progesterone are lowest, demonstrated lower magnitudes of endogenous opioid system activation than men, at comparable levels of pain intensity. In some brain areas, such as the nucleus accumbens, most women also demonstrated changes in the opposite direction, a deactivation of μ-opioid receptor-mediated neurotransmission, an effect associated with higher ratings of pain during pain challenge (Zubieta et al., 2002). However, even after accounting for gender differences in μ-opioid receptor binding and endogenous opioid system activity, and controlling for menstrual cycle phase in women, substantial inter-individual variations in these measures were still observed. An additional contribution to the observed variability in μ-opioid receptor binding and the capacity to activate this neurotransmitter system in response to sustained pain was described as a function of a common polymorphism of the catechol-O-methyl transferase enzyme (COMT). The substitution of valine (val) by methionine (met) at codon 158 of the COMT gene is associated with a 3–4-fold reduction in the capacity to metabolize catecholamines. These alterations in catecholaminergic neurotransmission resulted in downstream changes in the capacity to activate μ-opioid system responses to sustained pain, with lowest function in met/met, intermediate in met/val, and highest in val/val subjects (Zubieta et al., 2003). Aside from the importance of this work in understanding inter-individual variations in the regulation of pain, it also describes a point of interaction between neurotransmitter systems, such as the noradrenergic and dopaminergic, involved in responses to stress, salient stimuli and reward, with pain regulatory mechanisms. Reductions in presynaptic dopaminergic function in the basal ganglia have been reported in idiopathic burning mouth syndrome, as measured by the dopamine precursor [18F]fluorodopa (FDOPA) and PET (Jaaskelainen et al., 2001). These data seem consistent with findings by the same group of increases in dopamine D2, but not D1, receptor binding in the same brain regions of these patients (Hagelberg et al., 2003). The increases in D2 receptor binding were interpreted as reflecting a reduction in dopamine activity in the basal ganglia, in agreement with the FDOPA findings initially reported. The possible involvement of dopamine D2 receptors in pain regulatory mechanisms was also supported by findings that the concentration of D2 receptors in the basal ganglia of healthy controls was correlated with the tolerance to a tonic pain challenge (Hagelberg et al., 2002). Reciprocal interactions between catecholaminergic and opioid mechanisms are therefore emerging as important factors in the regulation of responses to pain and their interaction with other environmental and genetic influences (Hagelberg et al., 2002, Zubieta et al., 2003). 3.5. Brain activity in clinical pain states The advent of non-invasive brain imaging techniques afforded the new opportunity of examining brain processes in clinical pain conditions, and now significant progress has been made in this direction. The earliest hemodynamic studies attempted to identify brain activity that would differentiate clinical pain states from acute pain (Cesaro et al., 1991, Di Piero et al., 1991). Since these early reports, many clinical pain conditions have been examined (eTable 5). Given the success of identifying a unique, fairly reproducible, brain activity pattern for painful stimuli in normal subjects (see above), one early approach in the attempt to study clinical pain states was the application of the same method to various pain patient populations. In a series of studies, brain activity to thermal stimuli was reported to be abnormal in rheumatoid arthritis, in patients with atypical facial pain, and patients with post-tooth extraction pain (Derbyshire et al., 1999, Derbyshire et al., 1994, Jones and Derbyshire, 1997). These studies generally showed decreased activity in various components of the brain regions activated in normal subjects for thermal pain. Thermal stimuli were usually applied to the hand, a site remote from the body part where the clinical pain was felt, and it was usually not accompanied with psychophysical tests to measure differences in thermal pain thresholds at the injury site or at the test site. Thus, these results have remained mostly un-interpretable mainly because one is not sure whether the changes reflect properties fundamental to the condition or if they are a reflection of non-specific effects such as reduced attention to the stimulus. A recent comprehensive study, where a large group of low back pain patients was compared to matched normal controls, failed to demonstrate significant changes in brain responses to thermal stimuli applied to the hand between the groups (Derbyshire et al., 2002), lending support to the suspicion that the earlier reports were based on small non-specific differences. Another recent study demonstrated that thermal stimulation in complex regional pain syndrome (CRPS) patients gives rise to activity that closely matches that observed in normal subjects. However, this pattern changes dramatically when the ongoing pain of CRPS is isolated, by comparing brain activity before and after sympathetic blocks that reduce the ongoing CRPS pain but do not change the thermal stimulus pain (Apkarian et al., 2001). Thus, there is no compelling evidence that examining brain responses to experimental painful stimuli can predict the pattern of brain responses in chronic clinical pain states. A direct approach to studying clinical pain states is to provoke the condition and examine underlying brain activity (eTable 5). This is readily doable by drugs in headaches and in cardiac pain. As a result there are now high quality studies in both fields, and in both fields the results force the conclusion that the brain plays an active, if not a central, role in these conditions. There is also now good evidence that migraine with aura is accompanied with decreased blood flow and decreased activity in the occipital cortex. Gastrointestinal disorders can be studied directly by distending parts of the organ and examining related brain activity. A number of groups have adopted this strategy with varying success. Again the results have prompted a debate regarding the importance of central activity in irritable bowel syndrome (IBS). Given that IBS has a strong predominance in women and serotonin (5-HT) is suspected to be part of its pathophysiology, a recent study examined 5-HT binding in the brain of patients with IBS and showed 5-HT synthesis was greater in female IBS patients, thus linking brain neuromodulators to IBS (Nakai et al., 2003). Fibromyalgia and chronic neuropathic pain conditions have posed a tougher challenge, mainly because neither the experimenter nor the patient has the ability to systematically manipulate the properties of the condition. An elegant approach was demonstrated recently for studying fibromyalgia (Gracely et al., 2002), where the authors equated stimulus intensities and perception intensities between patients and normal subjects by rigorous psychophysical measurements, and thus were able to pinpoint brain abnormalities after equating perception. A number of groups have used allodynia induced by intradermal capsaicin injection as a model for studying central activity related to chronic pain (eTable 5). One study (Lorenz et al., 2002) examined thermal allodynia by equating stimulus and perception during allodynia to the normal state, a similar design as the fibromyalgia study (Gracely et al., 2002), and demonstrated that after equating for perceptions the brain activity for thermal pain during allodynia is different from that observed for the equivalent stimulus in normal skin. Another approach for documenting the impact of chronic pain on the brain is the examination of brain chemistry using non-invasive 1H MR spectroscopy (MRS, eTable 5). The advantage of the method is the stability of the signals analyzed since chemicals examined by this technique are independent of the cognitive state of the person at scan time. Thus, when changes in chemical concentrations are uncovered they are presumed to reflect long-term plasticity. Concentrations relative to an internal standard have been used to probe brain chemistry of chronic back pain. These studies show that brain chemistry is abnormal mainly in PFC. Moreover, different subregions within this cortex differentially correlate with various characteristics of the chronic pain, such as sensory and affective dimensions, anxiety and depression. These studies also show that interrelationships of chemicals across brain areas are disrupted in the patients as compared to normal subjects. Thalamic chemistry abnormalities have also been reported in patients with central, spinal cord injury, pain. These chemical changes are compelling evidence that the presence of chronic pain has an underlying brain chemical basis, may be reflecting the long-term plasticity that one suspects to accompany chronic pain. We tested whether brain activity in clinical conditions shows the same or a different pattern as brain activity evoked by experimental pain in normal subjects, by comparing incidences of significant activation of several brain areas across these two conditions (Table 2; derived from eTable 1, eTable 5). The included clinical studies are those where the authors attempted to isolate brain activity specifically related to the condition. The comparison shows that chronic clinical pain conditions more frequently involve PFC (81% in clinical conditions vs. 55% in normal subjects, Table 3), while in normal subjects perception of experimental pain more frequently involves S1, S2, Th, and ACC (average incidence across the five areas is 42% in clinical conditions vs. 82% in normal subjects, Table 3). Consistent with this pattern is the observation that in normal subjects ACC activity is correlated with pain intensity or perceived pain intensity due to rectal distension, and this correlation disappears in irritable bowel syndrome patients (Silverman et al., 1997, Mertz et al., 2000), and in heat allodynia (Lorenz et al., 2002) . In contrast to experimentally induced pain in normal subjects, chronic clinical pain conditions are often associated with decreased baseline activity or decreased stimulus related activity in the thalamus (six studies in eTable 5). A SPECT blood flow study (Fukumoto et al., 1999) has shown a strong relationship between time of onset of CRPS symptoms and thalamic activity. The ratio between contralateral to ipsilateral thalamic perfusion was larger than 1.0, indicating hyperperfusion, for patients with symptoms for only 3–7 months, and smaller than 1.0, indicating hypoperfusion, for patients with longer-term symptoms (24–36 months), with a correlation coefficient of 0.97 (normal subjects had a thalamic perfusion ratio of about 1.0). These data strongly imply that the thalamus undergoes adaptive changes in the course of CRPS. Thus, we can assert that brain activity for pain in chronic clinical conditions is different from brain activity for acute painful stimuli in normal subjects. We add the caution that this does not imply that all clinical pain conditions have a homogeneous underlying brain activity pattern. On the contrary, most likely the patterns involving different clinical conditions are unique but with the current available data we cannot test this at a meta-analysis level. EEG signals can show impaired function of the nociceptive pathways in a variety of disorders (Bromm et al., 1991, Treede et al., 1991, Kakigi et al., 1992, Kanda et al., 1996, Cruccu et al., 1999, Truini et al., 2003). Most of these studies use laser-evoked potentials, which are reliably detected in healthy subjects (Spiegel et al., 2000, Devos et al., 2000). This approach, however, is less sensitive in detecting clinical pain conditions (Gibson et al., 1994, Lorenz et al., 1996, Garcia-Larrea et al., 2002). Recent EEG and MEG studies have advanced our understanding of phantom limb pain. Animal experiments had demonstrated that the receptive fields of neurons in the primary somatosensory cortex move to adjacent skin areas when nerve lesions or amputations interrupted their original input. This reorganization of receptive fields of deafferented neurons was originally thought to be a protective mechanism against the development of phantom sensations. When this prediction was tested in human amputees, however, the opposite relationship was observed: the amount of phantom limb pain was positively (not negatively) correlated with the amount of cortical reorganization (Flor et al., 1995, Knecht et al., 1998, Montoya et al., 1998, Grusser et al., 2001, Karl et al., 2001). Although the correlation of cortical reorganization and phantom limb pain was also valid during pain relief by adequate treatment, the relationship between the two phenomena is unclear, because the reorganization is observed for tactile (not nociceptive) inputs to the primary somatosensory cortex. Thus, these findings do not represent a cortical pain mechanism, but may be relevant for our general understanding of the somatosensory system. A recent PET study may be more salient to identifying brain regions involved in phantom limb pain: by hypnotic suggestions of painful vs. painless phantom limb positions, the authors were able to show a brain activity pattern similar to other pain conditions (Willoch et al., 2000). 4. Comments The brain imaging studies reviewed here indicate the cortical and sub-cortical substrate that underlies pain perception. Instead of locating a singular “pain center” in the brain, neuroimaging studies identify a network of somatosensory (S1, S2, IC), limbic (IC, ACC) and associative (PFC) structures receiving parallel inputs from multiple nociceptive pathways (Fig. 1). In contrast to touch, pain invokes an early activation of S2 and IC that may play a prominent role in sensory-discriminative functions of pain. The strong affective-motivational character of pain is exemplified by the participation of regions of the cingulate gyrus. The intensity and affective quality of perceived pain is the net result of the interaction between ascending nociceptive inputs and antinociceptive controls. Dysregulations in the function of these networks may underlie vulnerability factors for the development of chronic pain and comorbid conditions. The review also highlights the types of information that has been garnered regarding this pain network by the different imaging modalities. The meta-analysis indicates that the members of the pain network are best identified by hemodynamic imaging methods, while the temporal sequence and time delays to activating different cortical regions are best studied with EEG and MEG methods. Brain regions involved in modulating pain perception seem identified best with studies involving neurotransmitter and neuroreceptor changes, although psychological modulation of pain is also being examined with fMRI, PET, and EEG/MEG studies. There seems to be good evidence for somatotopic organization for pain representation in some brain areas, with divergent views when studied with hemodynamic methods or with EEG or MEG methods. Our meta-analysis shows that experimental pain in normal subjects and chronic clinical pain conditions have distinct but overlapping brain activation patterns. Studies in normal subjects tend to emphasize transmission through the spinothalamic pathway, which transmits afferent nociceptive information through Th to S1, S2, IC and ACC. The meta-analysis indicates that the primary brain areas accessed through this pathway decrease in their activation incidence in chronic clinical pain. In contrast, the PFC activity seems to increase in incidence in clinical pain conditions. Since pathways outside of the spinothalamic tract, such as spinoparabrachial, spinohypothalamic and spinoreticular projections, may activate PFC, we propose that nociceptive information transmission through those pathways may become more important in chronic clinical pain conditions. A similar conclusion was arrived at by Hunt and Mantyh (2001) based on studying peripheral and spinal cord changes that accompany neuropathic pain-like behavior in rodents. It should be emphasized that the PFC is a heterogeneous brain area, where different subdivisions are thought to play specific roles in various cognitive, emotional and memory functions. In this review, we have not distinguished between the different components of PFC, although various studies do show distinct portions of PFC activated. We presume that different clinical pain conditions may in fact involve various components of PFC, but these await future studies. The preferential activation of PFC in clinical conditions suggests the simple hypothesis that chronic pain states have stronger cognitive, emotional, and introspective components than acute pain conditions. Decreased incidence of activity across ACC, S1, S2, IC, and Th in chronic pain conditions as compared to brain activity for pain in normal subjects has been observed in an earlier meta-analysis (Derbyshire, 1999) (decreased incidence of ACC and Th in chronic pain in contrast to pain in normal subjects was also noted by Peyron et al., 2000). On the other hand, the increase in incidence in PFC in clinical conditions was not observed. This resulted in the author stating that his analysis reveals ‘a generally reduced response to noxious stimulation in patients with concomitant clinical pain’ and concluding that ‘the most parsimonious explanation being increased response variability in patients’ (Derbyshire, 1999). Our analysis, instead, suggests that chronic pain conditions may be a reflection of decreased sensory processing and enhanced emotional/cognitive processing. The clinical pain states studied were heterogeneous, including cancer pain, headache, visceral pain and neuropathic pain. Other than being chronic and of high personal salience for the afflicted patient, these conditions probably have little in common that may explain the concordant activation of PFC. Craig et al., 1994, Craig et al., 1996 proposed that central pain may be a consequence of disinhibition within the spinothalamic pathway. Given that central pain has similar characteristics to the more general chronic neuropathic pain condition, the present results can be used to test Craig’s hypothesis. The decreased incidence of activity in ACC and Th, coupled with decreased coding for perceived pain in ACC, as well as increased incidence of activity in PFC in chronic pain conditions all contradict Craig’s hypothesis. Thus, we can state that his hypothesis does not apply to chronic pain in general. It is possible however that the common assumption that central pain and neuropathic pain are similar entities may simply be false, keeping Craig’s hypothesis unchallenged in the specific example where it was formulated, see Casey (2004) for a more thorough discussion of central pain, new relevant data, and alternative hypotheses. The format and organization of this review require commenting. We attempted to review the literature in the field using a systematic approach. To this end, we used eTables to present the literature and the salient results used in our analyses. To perform quantitative meta-analysis, we restricted the brain regions and the decision as to the presence of activity in a given region to very simple binary criteria. The results from these decisions are also included in the eTables. By simplifying the decisions regarding activity in a given brain region, we were able to construct testable hypotheses as to efficacy of imaging brain activity with different methods and for pain representation in normal subjects in comparison to clinical conditions. Because of the heterogeneity of the included studies, our quantitative findings are less stringent than e.g. systematic reviews of post-operative pain treatment, and hence should be interpreted with caution. Still, a large portion of this review remains descriptive due to the limited number of studies and due to our bias that good individual studies usually provide more reliable information than more inclusive meta-analyses of everything published in the field. The same limitations apply to other systematic reviews in the field (Derbyshire, 1999, Derbyshire, 2003, Peyron et al., 2000). 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PII: S1090-3801(04)00148-X doi:10.1016/j.ejpain.2004.11.001 © 2004 Published by Elsevier Inc. |
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