The form of consciousness

A model of consciousness is proposed, in which the experience attributable to a single neuron is related to its instantaneous firing rate. In that the experience afforded by a sensory neuron can only be quantified within statistical limits from the incidence of spikes across multiple presentations of a stimulus, consciousness remains inaccessible to direct measurement on a single trial. In this way, the model disambiguates subjective experience from objective neural properties. The model adopts a quantum mechanical formalism, in which the state of the neuron is represented as a vector in A complex vector space, or as a projector from the space onto that vector. Extension of this formalism to more realistic neural systems merely requires the assimilation of the quantum mechanical principles applicable in this broader context. Initially, a mathematical expression for the smooth evolution of a single dimension of perceptual experience will be derived for the single neuron case. There follows a description of how the neural state itself might evolve in this process, utilising the quantum operations formalism of amplitude damping. This approach reveals how smooth evolution of conscious experience might arise from discrete spikes and discontinuous synaptic interaction between neurons. A tensor product formalism will be used to describe the combination of state spaces of individual neurons to form a composite neural space, in which a pure 'mental state' would represent unified conscious experience. The binding of elementary features in this non-local mental state would be reflected in specific patterns of correlated neural firing between remote brain regions. In contrast, the conventional neuron doctrine is classical and local realistic. Local realistic constraints, expressed as Bell Inequalities, limit potential correlations in firing between remote neurons, presenting an opportunity for the experimental test of the scheme in a neurophysiologic thought experiment

Disgust and happiness recognition correlate with anteroventral insula and amygdala volume respectively in preclinical Huntington's disease

Patients with Huntington's disease (HD) can show disproportionate impairments in recognizing facial signals of disgust, but the neural basis of this deficit remains unclear. Functional imaging studies have implicated the anterior insula in the ability to recognize disgust, but have identified other structures as well, including the basal ganglia. In view of variable insula and basal ganglia volume changes in HD, we used voxel-based morphometry to map regional variations in gray matter (GM) volume in participants carrying the mutation for HD, and correlated this with their performance on a test of facial emotion recognition for six basic emotions (disgust, fear, anger, happiness, sadness, surprise). The volume of the anteroventral insula was strongly correlated with performance on the disgust recognition task. The amygdala volume (bilaterally) correlated with the ability to recognize happy facial expressions. There was marked specificity of the regional correlations for the emotion involved. Recognition of other emotion expressions, or more general cognitive or motor performance as measured by a standardized rating scale, did not correlate with regional brain volume in this group. Control participants showed no effect for any measure. The strong linear correlations for disgust and happiness recognition imply direct involvement of the anterior insula in disgust appreciation, and a similar role for the amygdala in recognizing happy facial expressions. The absence of a significant correlation with the basal ganglia suggests a less critical role for these structures in disgust recognition than has previously been suggested. The findings also highlight the role of neurodegenerative diseases combined with statistical imaging techniques in elucidating the brain basis of behavior and cognition

Progression of structural neuropathology in preclinical Huntington's disease: a tensor based morphometry study

Background and objectives: regional cerebral atrophy occurs in carriers of the Huntington’s disease (HD) gene mutation before clinical diagnosis is possible. The current inability to reliably measure progression of pathology in this preclinical phase impedes development of therapies to delay clinical onset. We hypothesised that longitudinal statistical imaging would detect progression of structural pathology in preclinical carriers of the HD gene mutation, in the absence of measurable clinical change.Methods: thirty subjects (17 preclinical mutation positive, 13 mutation negative) underwent serial clinical and magnetic resonance imaging (MRI) assessments over an interval of 2 years. Statistically significant changes in regional grey and white matter volume on MRI were analysed using tensor based morphometry (TBM). This technique derives a voxel-wise estimation of regional tissue volume change from the deformation field required to warp a subject’s early to late T1 images.Results: over 2 years, there was progressive regional grey matter atrophy in mutation-positive relative to negative subjects, without significant clinical progression of disease. Significant grey matter volume loss was limited to bilateral putamen and globus pallidus externa (GPe), left caudate nucleus, and left ventral midbrain in the region of the substantia nigra.Conclusions: while these results are consistent with previous cross sectional pathologic and morphometric studies, significant progression of atrophy in HD before the onset of significant clinical decline is now demonstrable with longitudinal statistical imaging. Such measures could be used to assess the efficacy of potential disease modifying drugs in slowing the progression of pathology before confirmed clinical onset of HD