Chronic pain is a frequent component of many neurological disorders, affecting 20-40% of patients for many primary neurological diseases. These diseases result from a wide range of pathophysiologies including traumatic injury to the central nervous system, neurodegeneration and neuroinflammation, and exploring the aetiology of pain in these disorders is an opportunity to achieve new insight into pain processing. Whether pain originates in the central or peripheral nervous system, it frequently becomes centralized through maladaptive responses within the central nervous system that can profoundly alter brain systems and thereby behaviour (e.g. depression). Chronic pain should thus be considered a brain disease in which alterations in neural networks affect multiple aspects of brain function, structure and chemistry. The study and treatment of this disease is greatly complicated by the lack of objective measures for either the symptoms or the underlying mechanisms of chronic pain. In pain associated with neurological disease, it is sometimes difficult to obtain even a subjective evaluation of pain, as is the case for patients in a vegetative state or end-stage Alzheimer's disease. It is critical that neurologists become more involved in chronic pain treatment and research (already significant in the fields of migraine and peripheral neuropathies). To achieve this goal, greater efforts are needed to enhance training for neurologists in pain treatment and promote greater interest in the field. This review describes examples of pain in different neurological diseases including primary neurological pain conditions, discusses the therapeutic potential of brain-targeted therapies and highlights the need for objective measures of pain.

Neurological diseases and pain.

Synaptic transmission initiates a cascade of signal transduction events that couple neuronal activity to local changes in blood flow and oxygenation. Although a number of vasoactive molecules and specific cell types have been implicated, the transformation of stimulus-induced activation of neuronal circuits to hemodynamic changes is still unclear. We use somatosensory stimulation and a suite of in vivo imaging tools to study neurovascular coupling in rat primary somatosensory cortex. Our stimulus evoked a central region of net neuronal depolarization surrounded by net hyperpolarization. Hemodynamic measurements revealed that predominant depolarization corresponded to an increase in oxygenation, whereas predominant hyperpolarization corresponded to a decrease in oxygenation. On the microscopic level of single surface arterioles, the response was composed of a combination of dilatory and constrictive phases. Critically, the relative strength of vasoconstriction covaried with the relative strength of oxygenation decrease and neuronal hyperpolarization. These results suggest that a neuronal inhibition and concurrent arteriolar vasoconstriction correspond to a decrease in blood oxygenation, which would be consistent with a negative blood oxygenation level-dependent functional magnetic resonance imaging signal.

Correction: In the artide Suppressed Neuronal Activity and Concurrent Arteriolar Vasoconstriction May Explain Negative Blood Oxygenation Level-Dependent Signal

Near infrared spectroscopy (NIRS) is rapidly gaining popularity for functional brain imaging. It is well suited to studies of patients or children; however, in these populations particularly, motion artifacts can present a problem. Here, we propose the use of imaging channels with negligible distance between light source and detector to detect subject motion, without the need for an additional motion sensor. Datasets containing deliberate motion artifacts were obtained from three subjects. Motion artifacts could be detected in the signal from the co-located channels with a minimum sensitivity of 0.75 and specificity of 0.98. Five techniques for removing motion artifact from the functional signals were compared, namely two-input recursive least squares (RLS) adaptive filtering, wavelet-based filtering, independent component analysis (ICA), and two-channel and multiple-channel regression. In most datasets, the median change in SNR across all channels was the greatest using ICA or multiple-channel regression. RLS adaptive filtering produced the smallest increase in SNR. Where sharp spikes were present, wavelet filtering produced the largest SNR increase. ICA and multiple-channel regression are promising ways to reduce motion artifact in functional NIRS without requiring time-consuming manual techniques.

https://www.researchgate.net/profile/Tania_Douglas/publication/224116075_Motion_Artifact_Removal_for_Functional_Near_Infrared_Spectroscopy_A_Comparison_of_Methods/links/553676040cf218056e95052d.pdf

Motion Artifact Removal for Functional Near Infrared Spectroscopy: A Comparison of Methods

Cognitive impairment of prefrontal-dependent decision-making in rats after the onset of chronic pain

Objective: To investigate cerebral activations underlying touch-evoked pain (dynamic–mechanical allodynia) in patients with neuropathic pain. Methods: fMRI was used in 12 patients with complex regional pain syndromes (CRPSs). Allodynia was elicited by gently brushing the affected CRPS hand. Elicited pain ratings were recorded online to obtain pain-weighted predictors. Both activations and deactivations of blood oxygenation level–dependent signals were investigated. Results: Nonpainful stimulation on the nonaffected hand activated contralateral primary somatosensory cortex (S1), bilateral insula, and secondary somatosensory cortices (S2). In contrast, allodynia led to widespread cerebral activations, including contralateral S1 and motor cortex (M1), parietal association cortices (PA), bilateral S2, insula, frontal cortices, and both anterior and posterior parts of the cingulate cortex (aACC and pACC). Deactivations were detected in the visual, vestibular, and temporal cortices. When rating-weighted predictors were implemented, only few activations remained (S1/PA cortex, bilateral S2/insular cortices, pACC). Conclusions: Allodynic stimulation recruits a complex cortical network. Activations include not only nociceptive but also motor and cognitive processing. Using a covariance approach (i.e., implementation of rating-weighted predictors) facilitates the detection of a neuronal matrix involved in the encoding of allodynia. The pattern of cortical deactivation during allodynia may hint at a shift of activation from tonically active sensory systems, like visual and vestibular cortices, into somatosensory-related brain areas.

Functional imaging of allodynia in complex regional pain syndrome. Authors' reply

Diffuse optical tomography of pain and tactile stimulation: activation in cortical sensory and emotional systems.

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Diffuse optical tomography of pain and tactile stimulation: activation in cortical sensory and emotional systems.