This study investigates the effects of noise distraction on the different components and sources of laser-evoked potentials (LEPs) whilst attending to either the spatial component (localisation performance task) or the affective component (unpleasantness rating task) of pain. LEPs elicited by CO2 laser stimulation of the right forearm were recorded from 64 electrodes in 18 consenting healthy volunteers. Subjects reported either pain location or unpleasantness, in the presence and absence of distraction by continuous 85 dBa white noise. Distributed sources of the LEP peaks were identified using Low Resolution Electromagnetic Tomography (LORETA). Pain unpleasantness ratings and P2 (430 ms) peak amplitude were significantly reduced by distraction during the unpleasantness task, whereas the localisation ability and the corresponding N1/N2 (310 ms) peak amplitude remained unchanged. Noise distraction (at 310 ms) reduced activation in the anterior cingulate cortex (ACC) and precuneus during attention to localisation and unpleasantness, respectively. This suggests a complimentary role for these two areas in the control of attention to pain. In contrast, activation of the occipital pole and SII were enhanced by noise during the localisation and unpleasantness task, respectively, suggesting that the presence of noise was associated with increased spatial attentional load. This study has shown selective modulation of affective pain processing by noise distraction, indicated by a reduction in the unpleasantness ratings and P2 peak amplitude and associated activity within the medial pain system. These results show that processing of the affective component of pain can be differentially modulated by top-down processes, providing a potential mechanism for therapeutic intervention.
In recent years, a vertiginous advance has occurred within the Neural Field Theory with the development of the so-called Next Generation Neural Field models. Unlike the phenomenological models, these models manage to describe neuronal activity, macroscopically, from the thermodynamic limit of microscopic laws under the assumption of a homogeneous density of neurons. The study of neural activity during neurodegenerative processes associated to Alzheimer's, Parkinson's or Glioblastomas, should include a variable density of neurons. In this work, we propose an update of the Next Generation Neural Field model, extracted from the thermodynamic limit of the quadratic integration-and-fire model with realistic synaptic coupling and a variable density of neurons at the microscopic level. The thermodynamic limit of the system will allow us to study the patterns of synchronized neural activity that appear as the result of different spatial distribution of neurodegeneration. In particular, we demonstrate that during neurodegenerative processes, the relationship established between the thermodynamic states of the Neural Field and the Kuramoto order parameter (Measure of Neural Synchronization) differs from the classic results of the Next Generation Neural Field literature. Instead, the variation in neuron density directly modifies the Kuramoto order parameter. This might help us explain the diverse patterns of activity that can be found in different neurodegenerative processes and that could become experimental biomarkers of such pathologies.
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