The neurophysiological basis of prolonged negative BOLD signals

A technique called blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) can determine levels of different activity in parts of the living human brain and how malfunctions can occur in disease. However, this technique relies on changes in local blood oxygenation rather than measuring the electrical activity in the brain directly. How increases in brain activity results in blood changes has started to be understood, but how and if decreases in activity affect brain blood oxygen is not at all characterised making neuroimaging data very difficult to interpret in terms of decreases in brain activity. Despite this uncertainty, scientists are stating to use FMRI to infer decreases in brain activity and if this inference is correct their studies suggest that the majority of psychiatric (e.g. schizophrenia, major depressive disorder), neuro-developmental (e.g. Autism) neurological (e.g. Alzheimer?s) brain diseases are characterised an inability to ?turn-off? rather ?turn-on? specific brain regions during mental tasks. By directly measuring reductions brain activity, neuroimaging signals and blood oxygen content at the same time we hope to understand the relationships between them and allow this vital aspect of neuroimaging to further our understanding of brain function and its malfunction in disease states.

The changes in cerebral blood flow, volume and oxygenation that accompany increases in neural activity form the basis of non-invasive neuroimaging techniques such as blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) which allow human brain mapping. Understanding the relationship between cerebral hemodynamics and the underlying evoked neural activity is therefore vital for the interpretation of neuroimaging data. With a unique combination of optical, electrophysiological and MR techniques in a rodent model we have previously explored the quantitative relationships between increases in activity and the accompanying hemodynamics and positive fMRI signals. However, increasingly deactivations are inferred from prolonged negative BOLD signal changes with little evidence that negative neuroimaging signals ubiquitously reflect reductions in electrical activity. If correct, studies using negative signals to infer reductions in activity suggest that an inability to deactivate specific brain regions appears to be the hallmark of all major neurological and psychiatric conditions. Our recently established dedicated 7T rodent MRI has afforded the signal to noise ratio required to detect prolonged negative BOLD signals following presentation of somatosensory stimuli. Thus the current proposal seeks to use combinations of our established techniques to characterise negative BOLD responses. Concurrent optical imaging spectroscopy and fMRI will allow examination of spatio-temporal concordance between negative BOLD signals and the underlying hemodynamics and further parameterisation of models linking the magnitude of hemodynamics to actual fMRI signal changes. Combinations of optical imaging and laser Doppler techniques will provide multi-modal data with which to explore relationships between decreases in blood flow, volume and oxygen consumption. Quantitative ?negative? neurovascular coupling will be compared from cortical regions signals immediately adjacent to those exhibiting positive BOLD and with negative BOLD responses in the opposite cortex. This will reveal whether re-distribution of local vascular resources is in part responsible for negative BOLD responses in cortical areas that share a common local vasculature. Ex-vivo histological and anatomical tracing techniques will inform the underlying cortical connectivity required for stimulus evoked decreases in activity. We will also perform a series of experiments in the awake animal preparation to assess the effects of anaesthesia on the evoked responses. Finally concurrent measure of ?negative? hemodynamics response and reductions in electrical activity will be used to make dynamic models to predict the entire time series of the CBF response from the underlying neural activity.