Human cortical perfusion and the arterial pulse: a near-infrared spectroscopy study

BACKGROUND: The pulsatile nature of the arterial pulse induces a pulsatile perfusion pattern which can be observed in human cerebral cortex with non-invasive near-infrared spectroscopy. The present study attempts to establish a quantitative relation between these two events, even in situations of very weak signal-to-noise ratio in the cortical perfusion signal. The arterial pulse pattern was extracted from the left middle finger by means of plethesmographic techniques. Changes in cortical perfusion were detected with a continuous-wave reflectance spectrophotometer on the scalp overlying the left prefrontal cortex. Cross-correlation analysis was performed to provide evidence for a causal relation between the arterial pulse and relative changes in cortical total hemoglobin. In addition, the determination of the statistical significance of this relation was established by the use of phase-randomized surrogates. RESULTS: The results showed statistically significant cross correlation between the arterial and perfusion signals. CONCLUSIONS: The approach designed in the present study can be utilized for a quantitative and continuous assessment of the perfusion states of the cerebral cortex in experimental and clinical settings even in situations of extremely low signal-to-noise ratio

Evolutionary autonomous agents and the nature of apraxia

BACKGROUND: Evolutionary autonomous agents are robots or robot simulations whose controller is a dynamical neural network and whose evolution occurs autonomously under the guidance of a fitness function without the detailed or explicit direction of an external programmer. They are embodied agents with a simple neural network controller and as such they provide the optimal forum by which sensorimotor interactions in a specified environment can be studied without the computational assumptions inherent in standard neuroscience. METHODS: Evolutionary autonomous agents were evolved that were able to perform identical movements under two different contexts, one which represented an automatic movement and one which had a symbolic context. In an attempt to model the automatic-voluntary dissociation frequently seen in ideomotor apraxia, lesions were introduced into the neural network controllers resulting in a behavioral dissociation with loss of the ability to perform the movement which had a symbolic context and preservation of the simpler, automatic movement. RESULTS: Analysis of the changes in the hierarchical organization of the networks in the apractic EAAs demonstrated consistent changes in the network dynamics across all agents with loss of longer duration time scales in the network dynamics. CONCLUSION: The concepts of determinate motor programs and perceptual representations that are implicit in the present day understanding of ideomotor apraxia are assumptions inherent in the computational understanding of brain function. The strength of the present study using EAAs to model one aspect of ideomotor apraxia is the absence of these assumptions and a grounding of all sensorimotor interactions in an embodied, autonomous agent. The consistency of the hierarchical changes in the network dynamics across all apractic agents demonstrates that this technique is tenable and will be a valuable adjunct to a computational formalism in the understanding of the physical basis of neurological disorders

Chaos game representation of human pallidal spike trains

Many studies have demonstrated the presence of scale invariance and long-range correlation in animal and human neuronal spike trains. The methodologies to extract the fractal or scale-invariant properties, however, do not address the issue as to the existence within the train of fine temporal structures embedded in the global fractal organisation. The present study addresses this question in human spike trains by the chaos game representation (CGR) approach, a graphical analysis with which specific temporal sequences reveal themselves as geometric structures in the graphical representation. The neuronal spike train data were obtained from patients whilst undergoing pallidotomy. Using this approach, we observed highly structured regions in the representation, indicating the presence of specific preferred sequences of interspike intervals within the train. Furthermore, we observed that for a given spike train, the higher the magnitude of its scaling exponent, the more pronounced the geometric patterns in the representation and, hence, higher probability of occurrence of specific subsequences. Given its ability to detect and specify in detail the preferred sequences of interspike intervals, we believe that CGR is a useful adjunct to the existing set of methodologies for spike train analysis