Detecting functional magnetic resonance imaging activation in white matter: Interhemispheric transfer across the corpus callosum

<p>Abstract</p> <p>Background</p> <p>It is generally believed that activation in functional magnetic resonance imaging (fMRI) is restricted to gray matter. Despite this, a number of studies have reported white matter activation, particularly when the corpus callosum is targeted using interhemispheric transfer tasks. These findings suggest that fMRI signals may not be neatly confined to gray matter tissue. In the current experiment, 4 T fMRI was employed to evaluate whether it is possible to detect white matter activation. We used an interhemispheric transfer task modelled after neurological studies of callosal disconnection. It was hypothesized that white matter activation could be detected using fMRI.</p> <p>Results</p> <p>Both group and individual data were considered. At liberal statistical thresholds (p < 0.005, uncorrected), group level activation was detected in the isthmus of the corpus callosum. This region connects the superior parietal cortices, which have been implicated previously in interhemispheric transfer. At the individual level, five of the 24 subjects (21%) had activation clusters that were located primarily within the corpus callosum. Consistent with the group results, the clusters of all five subjects were located in posterior callosal regions. The signal time courses for these clusters were comparable to those observed for task related gray matter activation.</p> <p>Conclusion</p> <p>The findings support the idea that, despite the inherent challenges, fMRI activation can be detected in the corpus callosum at the individual level. Future work is needed to determine whether the detection of this activation can be improved by utilizing higher spatial resolution, optimizing acquisition parameters, and analyzing the data with tissue specific models of the hemodynamic response. The ability to detect white matter fMRI activation expands the scope of basic and clinical brain mapping research, and provides a new approach for understanding brain connectivity.</p

Temporal properties of human information processing: Tests of discrete versus continuous models,

Cognitive psychologists have characterized the temporal properties of human information processing in terms of discrete and continuous models. Discrete models postulate that component mental processes transmit a finite number of intermittent outputs (quanta) of information over time, whereas continuous models postulate that information is transmitted in a gradual fashion. These postulates may be tested by using an adaptive response-priming procedure and analysis of reaction-time mixture distributions. Three experiments based on this procedure and analysis are reported. The experiments involved varying the temporal interval between the onsets of a prime stimulus and a subsequent test stimulus to which a response had to be made. Reaction time was measured as a function of the duration of the priming interval and the type of prime stimulus. Discrete models predict that manipulations of the priming interval should yield a family of reaction-time mixture distributions formed from a finite number of underlying basis distributions, corresponding to distinct preparatory states. Continuous models make a different prediction. Goodness-of-fit tests between these predictions and the data supported either the discrete or the continuous models, depending on the nature of the stimuli and responses being used. When there were only two alternative responses and the stimulus-response mapping was a compatible one, discrete models with two or three states of preparation fit the results best. For larger response sets with an incompatible stimulus-response mapping, a continuous model fit some of the data better. These results are relevant to the interpretation of reaction-time data in a variety of contexts and to the analysis of speed-accuracy trade-offs in mental processes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/25558/1/0000100.pd

Computational motor control and human factors: Modeling movements in real and possible environments

Contains fulltext : 63088.pdf (publisher's version ) (Closed access)An aim of human factors research is to have models that allow for the advance design of user-friendly environments. This is still a distant dream because existing models are not yet sufficiently sophisticated. Models in the domain of motor control are a case in point, but recent developments in computational motor control suggest that the gap between the current state of modeling in this area and the desired state is shrinking. To illustrate this point, we review principles of motor control research that any model of motor control must accommodate. Then we describe a model that captures many of the capacities of actors in the everyday world, including the capacity to reach for objects in different ways depending on factors such as the ease with which different joints can rotate, the required speed of movement, and whether obstacles are present. The model relies on the ideas that goal postures are internally specified before movements are generated, that tasks are defined with flexibly ordered constraint hierarchies, and that movements can be shaped according to task demands. Actual or potential applications of this research include designing and testing possible environments where motor components play a key role