Stable perception of external stimuli over time: oculo-motor and visual processing mechanisms

When the animals populating the floor of the ocean started moving 600 million years ago, they faced an important evolutionary challenge: on one hand self-motion carry clear advantages: for example, finding new sources of food and escaping predators. On the other hand, it introduces ambiguity about the source of a sensory input.
When you are crossing the street, you need to differentiate whether a motion is caused by a movement of a car (that need to be avoided), or a passive movement caused by you crossing the street (which can be ignored).
Any animal that failed to correctly recognize the source of a sensory stimulation would have faced an evolutionary disadvantage, with devastating consequences.
The species that successfully solved this problem did so by keeping track of their movement commands and informing the sensory system about forthcoming movements.
Eye movements are a paradigmatic example of a specific sensory change, induced by the motor system. If we were to perceive the world exactly as it is displayed if front of our eyes, the visual scene would seem a sequence of frequent and large jumps, making any matching attempts between them impossible. It is crucial for the visual system to be able to distinguish 'jumps' that are due to saccades as opposed to changes in the external world. It is believed that the motor system provides the sensory system with a warning of an upcoming movement, to which the central nervous system responds with a compensatory mechanism.
Evidence from monkey neurophysiology shows that several brain locations are particularly involved in the interaction between the oculo-motor system and vision, namely: the frontal and supplementary eye fields in monkey frontal cortex, several portions of the parietal cortex and motion sensitive areas.
We have a general understanding of the fine organizational principles of these areas in monkey neocortex, but the same principles have not been tested in homologue areas of human cortex, so far.
This reflects limitations intrinsic to standard human neuroimaging techniques. The spatial resolution in standard human neuroimaging studies is too coarse to characterize the detailed spatial organization typically observed in monkey neurophysiology. Ultra-high field imaging (7Tesla) helps overcoming these technical limitations, providing better and more detailed signal than standard neuroimaging acquisition. These advantages allow for a more detailed investigation that is not possible to image at lower fields (1.5 and 3Tesla), opening the possibility to test in humans, in vivo, the fine oculomotor-processing principles described in monkey neurophysiology.

The goal of this project is to investigate the human homologue of 3 distinct brain locations involved in oculomotor processing and active vision, building on findings from monkey neurophysiology. I am going to test for the first time whether the fine, within-area organization and computational principles described in monkeys can be observed in humans. I will use a combination of ultra-high field acquisition using functional and structural data. Each brain area will be targeted with a specific experimental design and analysis strategy aimed at characterizing the principles outlined in homologue locations in monkey neocortex.

First, I will test how the oculomotor signal is represented in human neocortex, focusing on human frontal and supplementary eye-fields (FEF/SEF). The laminar and columnar organization of kinematic properties of FEF and SEF in humans is unknown. My goal is to provide a detailed description of this sub-millimeter organization of human FEF and SEF at the structural and functional level.

The parietal lobe will be the focus of the second part. Visual responses from portions of the parietal cortex are modulated by eye position (gain fields). My aim is to identify the locations in parietal cortex where static eye-position is encoded with a gain-field mechanism, providing a first step toward a more comprehensive understanding of the coordinate transformation in human parietal cortex.

Third, I will investigate where and how eye movements are integrated with a dynamic visual input, focusing on the human motion complex. I want to elucidate how the oculomotor signal is implemented, distinguishing between three possibilities: (i) a simple ON-OFF signal, (ii) a scattered representation of the oculomotor signal, (iii) a topographic representation, mapping the kinematics of the movement over the cortex surface.

The proposed research will act as a bridge between research from monkey neurophysiology and human neuroscience. High-resolution imaging allows researchers to test functional and structural hypotheses in humans, in vivo, at a sub-millimetre scale. The specific hypotheses tested in this proposal are derived from neurophysiology; human neuroimaging and monkey neurophysiology meet in the middle thanks to the high-resolution capabilities of modern ultra-high field imaging. The proposed work will benefit both the field of neuroimaging and neurophysiology, as results from the latter will be tested in vivo, in humans, and data from the former can provide new exiting functional hypotheses for neurophysiology.
Furthermore, the proposed research will increase our understanding of healthy brain functioning, specifically related to eye-movement behaviour and vision.

Several members of staff at the Centre for Cognitive Neuroimaging (CCNi) have established links to imaging-related industries and will benefit from the results and methods developed in this project.
From an economic and societal perspective, the development and implementation of high-resolution (7T) scanners and imaging techniques is one of the recent technological developments that puts into practice the concept of personalized medicine: tailoring treatment for the specific needs of the single patient.
In this regard, recent advances in ultra-high field imaging facilitate non-invasive imaging of the whole brain at an unprecedented level of detail. Standard neuroimaging software is not suited for processing such images and there is a growing need for dedicated tools and analysis strategies that can take ad-vantage of the new data. The analytical approaches used in the proposed projects are thought and im-plemented with the individual participant in mind, characterizing individual idiosyncrasies from the functional and structural perspective, that otherwise would get inevitably lost in the averaging process.
The individual-based approach proposed in this project share the same principles described in individ-ualized medicine and provides the tools to put these principles in practice from a brainimaging perspective.
Benefit from this work will be achieved by publishing and disseminating the work in high impact journals and international conferences as well as news media.
Overall, the fundamental research proposed in this project will contribute to the position of the United Kingdom as a leader in high resolution brain imaging and fundamental research.