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Sensory and emotional systems normally interact in a manner that optimizes an organism's ability to survive using conscious and unconscious processing. Pain and analgesia are interpreted by the nervous system as aversive and rewarding processes that trigger specific behavioral responses. Under normal physiological conditions these processes are adaptive. However, under chronic pain conditions, functional alterations of the central nervous system frequently result in maladaptive behaviors. In this review, we examine: (a) the interactions between sensory and emotional systems involved in processing pain and analgesia in the physiological state; (b) the role of reward/aversion circuitry in pain and analgesia; and (c) the role of alterations in reward/aversion circuitry in the development of chronic pain and co-morbid psychiatric disorders. These underlying features have implications for understanding the neurobiology of functional illnesses such as depression and anxiety and for the development and evaluation of novel therapeutic interventions.

IntroductionAlthough mild cognitive impairment (MCI) diagnosis is mainly based on cognitive assessment, reliable estimates of structural changes in specific brain regions, that could be contrasted against normal brain aging and inform diagnosis, are lacking. This study aimed to systematically review the literature reporting on MCI-related brain changes.MethodsThe MEDLINE database was searched for studies investigating longitudinal structural changes in MCI. Studies with compatible data were included in the meta-analyses. A qualitative review was conducted for studies excluded from meta-analyses.ResultsThe analyses revealed a 2.2-fold higher volume loss in the hippocampus, 1.8-fold in the whole brain, and 1.5-fold in the entorhinal cortex in MCI participants.DiscussionAlthough the medial temporal lobe is likely to be more vulnerable to MCI pathology, atrophy in this brain area represents a relatively small proportion of whole brain loss, suggesting that future investigations are needed to identify the source of unaccounted volume loss in MCI.

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