Unified probabilistic modelling of adaptive spatial-temporal structures in the human brain.
Peter Tino, School of Computer Science, University of Birmingham

Learning from experience and adapting our behaviour to new situations is a fundamental skill for our everyday interactions. But what are the brain plasticity mechanisms that mediate an individual's ability to make progress during training on complex tasks? What is it that differentiates `good' from `poor' learners in their ability to adapt? Recent advances in functional brain imaging technology provide us with the unique opportunity to study how the human brain changes with learning. However, the existing methods focus predominantly on modelling brain activity data within a single session rather than across training sessions. As such, these methods are not capable of capturing larger scale dependencies emerging in brain activity as training progresses. We will develop a novel methodology that allows holistic unified modelling of a series of brain imaging data measured during the course of learning. Using this methodology we will study brain changes that result from extensive training on complex visual tasks.

Neural basis of 3D perception in the human brain.
Andrew Welchman , University of Birmingham

Binocular disparity,the slight differences between the images registered by our two eyes,provides an important cue when estimating the three-dimensional (3D) structure of the complex environment we inhabit. Sensitivity to binocular disparity is evident at multiple levels of the visual hierarchy in the primate brain, from early visual cortex to parietal and temporal areas. However, the relationship between activity in these areas and key perceptual functions that exploit disparity information for 3D shape perception remains an important open question. Using concurrent behavioural and fMRI measurements we investigate the link between human cortical activity and the perception of disparity-defined shape.

Learning shapes the processing of biological movements in the human visual cortex
Martin Giese , University of Tuebingen

Recognizing biological movements is a fundamental skill for survival and social interactions. Using combined psychophysics and fMRI, we provide novel evidence that learning shapes biological motion processing across stages of visual analysis in the human brain. We report improved performance after training in discriminating biological movements whose similarity varied parametrically along a spatio-temporal morphing continuum, coupled with increased fMRI selective adaptation to the movement differences. Learning novel human-like movements shaped higher-level processing of known action categories: global movement analysis in hMT+/V5, V3B/KO and generalization of existing representations for prototypical actions to novel exemplars in STSp, FFA. However, learning artificial movements bolstered the formation of novel category representations: integration of local configurations in retinotopic areas, global movement analysis in hMT+/V5, V3B/KO, and processing of biological properties in STSp, FFA. These findings propose distributed experience-based plasticity mechanisms that mediate recognition of complex movements and action understanding in the human visual cortex.

Uncertainty and Invariance in the Human Visual Cortex
Bosco Tjan, USC

The way in which input noise perturbs the behavior of a system depends on the internal processing structure of the system. In visual psychophysics, there is a long tradition of using external noise methods (i.e. adding noise to visual stimuli) as tools for system identification. Here, we demonstrate that external noise affects processing of visual scenes at different cortical areas along the human ventral visual pathway, from retinotopic regions to higher occipitotemporal areas implicated in visual shape processing. We found that, when the contrast of the stimulus was held constant, the further away from the retinal input a cortical area was the more its activity, as measured with fMRI, depended on the signal-to-noise ratio (SNR) of the visual stimulus. A similar pattern of results was observed when trials with correct and incorrect responses were analyzed separately. We interpret these findings by extending signal detection theory to fMRI data analysis. This approach reveals the sequential ordering of decision stages in the cortex by exploiting the relation between fMRI response and stimulus SNR. In particular, our findings provide novel evidence that occipitotemporal areas in the ventral visual pathway form a cascade of decision stages with increasing degree of signal uncertainty and feature invariance.

Development of visually evoked cortical activity in infant macaque monkeys studied longitudinally with fMRI.
Lynne Kiorpes , NYU
J. Anthony Movshon , NYU
Nikos K. Logothetis , MPI Tuebingen

We studied the development of visual activation longitudinally in two infant monkeys aged 103–561 days using the BOLD fMRI technique under opiate anesthesia and compared the results with those obtained in three adult animals studied under identical conditions. Visual activation in primary visual cortex, V1, was strong and reliable in monkeys of the youngest and oldest ages, showing that functional imaging techniques give qualitatively similar results in infants and adults. Visual activation in extrastriate areas involved in processing motion (MT/V5) and form (V4) was not evident in the younger animals, but became more adult-like in the older animals. This delayed onset of measurable BOLD responses in extrastriate visual cortex may reflect delayed development of visual responses in these areas, although at this stage it is not possible to rule out either effects of anesthesia or of changes in cerebral vascular response mechanisms as the cause. The demonstration of visually evoked BOLD responses in young monkeys shows that the BOLD fMRI technique can usefully be employed to address functional questions of brain development.