Interpreting BOLD: a dialogue between cognitive and cellular neuroscience

09:10-09:40 Uses, misuses, new uses and fundamental limitations of MRI in cognitive science

Professor Robert Turner, Max Planck Institute for Human Cognitive and Brain Sciences, Germany

Abstract

When BOLD contrast was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This presentation will review the following questions:

a) What can structural and functional BOLD MRI reveal about human cognition that other techniques cannot provide? 

b) In which areas of cognitive science has fMRI made major contributions?

c) What are the implicit assumptions underlying now-popular analysis techniques, and what are the flaws in these assumptions?

d) Can MRI-based myeloarchitectural parcellation of the cortex and high resolution fMRI methodology make these assumptions unnecessary?

e) Are there other ways of analyzing MRI/fMRI data that provide deeper insight?

f) Will cortical layer-specific fMRI enable questions of causality to be addressed, and what are the best candidate techniques for such acquisitions?

g) What are the likely fundamental limitations of all MRI and fMRI methods?

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09:50-10:20 Neurovascular coupling: when its reliability as a marker of neuronal activity gets challenged

Professor Edith Hamel, Montreal Neurological Institute, McGill University, Canada

Abstract

Changes in neuronal activity are spatially and temporally coupled to concurrent changes in cerebral blood flow (CBF), a process known as neurovascular coupling (NVC) that forms the basis of several brain imaging techniques. Yet, it is unclear how reliable this coupling remains during altered brain states and, particularly, under pathological conditions. Using the whisker-to-barrel pathway, a well-established model of NVC, we tested whether the coupling between neuronal activity and CBF would be affected by changes in brain states induced by varying the levels of acetylcholine (ACh), a potent modulator of sensory processing. Under acute increases in ACh tone, whisker-evoked hemodynamic responses and neuronal signals (LFPs and band-limited power) were potentiated despite no change in the extent and identity of the neuronal network recruited within the activated barrel. Inversely, chronic ACh deprivation compacted the activated barrel and reduced both sensory-evoked hemodynamic and neuronal responses. Our findings indicate that hemodynamic signals dependably reflect changes in the activity of the neural circuit underlying sensory processing under states of enhanced ACh neurotransmission and in conditions of a cholinergic deprived network as seen in Alzheimer’s disease.

11:00-11:30 Vasomotion: a link from ultra-slow neuronal activity to blood oxygenation

Professor David Kleinfeld, University of California, San Diego, USA

Abstract

The blood-oxygenation-level-dependent (BOLD) fMRI signal is a central technology of modern cognitive neuroscience. An intriguing issue is that ultra-slow variations (~ 0.1 Hz) in the oxygenation of brain tissue appear to be mirrored across conjugate brain areas in the two hemispheres. This is referred to as ‘resting-state’ BOLD fMRI and this finding has been inverted in many studies of human cognition, so that ultra-slow co-fluctuations are interpreted as ‘function connections’. Yet the mechanism to support this interpretation remains to be discovered. Here we address this relation in awake mice through measurements of neuronal activity, tissue oxygenation, and conventional and ultra-large field two-photon imaging of vascular dynamics. We provide evidence that arteriole vasomotion can link ongoing, coordinated neuronal activity with ultra-slow oscillations in blood oxygenation. This result may justify inferring neuronal connections from synchronous ultra-slow vasodynamics between different brain areas.

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11:40-12:10 Model-based approaches that connect BOLD imaging and dopaminergic transmission in humans

Professor Read Montague, Virginia Tech Carilion Research Institute, USA and University College London, UK

Abstract

Using a simple sequential decision task we provide new data showing a cross cohort relationship between BOLD responses during the decision task and sub-second electrochemical estimates of dopamine and serotonin from the dorsal striatum. Not surprisingly the relationship among these three separate measures is not simple even allowing for the possibility that some features of the signaling are unique to the state of the subjects’ brains (i.e. Parkinson’s Disease or Essential Tremors). Dopamine and serotonin appear to correlate with error signals for experienced rewards and one form of counterfactual signals (what might have been gained or loss had the choice been different). Moreover, fluctuations in these two transmitters prospectively encode a subject’s strategy on their next choice (stay or shift) with dopamine carrying this information following a positive prediction error and serotonin carrying it following a negative prediction error. We speculate about the connection between the measured BOLD response and the measured neuromodulator response; however the results do suggest more complexity than is latent is models built solely around the BOLD response.

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13:30-14:00 Multimodal investigation of the neurovascular unit following focal cerebral ischemia

Dr Bojana Stefanovic, Sunnybrook Research Institute, Canada

Abstract

In recent years, the state of the peri-infarct zone, a meta-stable region of at-risk brain tissue that surrounds the permanently damaged necrotic core, has been identified as a major determinant of functional outcome post stroke. We used BOLD, arterial spin labelling and intra-cortical array electrophysiology to identify the changes in the neurovascular unit in an endothelin-1 rat model of focal cortical ischemia. Two days following ischemic insult, peri-lesional tissue exhibited heightened resting perfusion and increased vascular reactivity to hypercapnia. These hemodynamic alterations were accompanied by changes in phase-amplitude coupling of the neurons. The synchronization of amplitudes of faster rhythms with the phase of slower rhythms was altered in the perilesional tissue, indicating pathophysiological functioning of the neuronal network surrounding the necrosis. These distinct changes in the vascular vs. neuronal reactivity make BOLD fMRI responses particularly hard to interpret and necessitate multi-modal experiments to independently assess the evolution of changes in the respective cellular populations over the course ischemic injury progression.

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14:10-14:40 Deep neural networks: a new framework for understanding how the brain works

Dr Nikolaus Kriegeskorte, Medical Research Council, UK

Abstract

Recent advances in neural network modelling have enabled major strides in computer vision and other artificial intelligence applications. Artificial neural networks are inspired by the brain and their computations could be implemented in biological neurons. Although designed with engineering goals, this technology provides the basis for tomorrow’s computational neuroscience. In order to test such models with massively multivariate brain-activity data, we can characterise the representational spaces in brains and models by matrices of representational dissimilarities among stimuli. Deep convolutional neural nets trained for visual object recognition have internal representational spaces remarkably similar to those of the human and monkey ventral visual pathway. Deep neural networks explain representations of novel images as reflected in both functional magnetic resonance imaging (fMRI) data and neuronal recordings. Current challenges include exploration of alternative neural net models consistent with typically limited neurophysiological data and statistical inference to adjudicate among them while taking into account how the measurement method samples neuronal activity patterns. For fMRI, we need to model how hundreds or thousands of voxels within an area reflect the representations in many millions of neurons. We are entering an exciting new era, in which we will be able to build neurobiologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence including vision.

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15:20-15:50 Imaging the mechanisms of cognition

Professor Tim Behrens, University of Oxford, UK

Abstract

Human imaging approaches have had great success in uncovering cognitive mechanisms associated with brain areas and gross neural signals.  There is, however, a large gap between such studies and studies in animal models which make inferences at the level of cells and synapses.  Recently human imaging work has led to techniques that have the potential to bridge this gap by making inferences at the mesoscopic scale of neural ensembles. I will present two such studies that use coarse brain imaging and interventional tools to try to make inferences about how cognitive associations are stored in synapses and in organised cellular activity. We think it is very important that the field moves towards being able to make such inferences in humans, because it would mean that mechanistic theories of complex cognitive processes and psychiatric conditions that are developed in animal models could be tested directly.

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09:00-09:30 Cellular and molecular determinants of the hemodynamic response

Dr Anna Devor, University of California, San Diego, USA

Abstract

The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use noninvasive technologies. This is in contrast to animal models where a rich, detailed view on the cellular level brain function has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from human noninvasive signals. We will discuss a strategy of addressing this challenge by combining human and animal experiments and computational modeling with the endpoint goal to deliver a quantitative probe for neuronal activity of known cell types in human brain enabling a paradigm shift in human fMRI studies: from a simple mapping of fMRI signal change to the explicit estimation of the relative activity levels of specific neuronal cell types.

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09:40-10:10 Neural-metabolic coupling in the central visual pathway

Professor Ralph Freeman, University of California, Berkeley, USA

Abstract

Noninvasive neural imaging of the brain has become a primary neuroscience tool. Different techniques have been used but functional magnetic resonance imaging (fMRI) is currently the dominant procedure by which hemodynamic processes are monitored to infer properties of neural activity. A fundamental question concerns the functional relationship between the local hemodynamic changes that are measured and the implications for neuronal function. In a series of studies, we have measured an important metabolic parameter, tissue oxygen concentration, along with activated neural activity in the central visual pathway. Tissue oxygen changes are directly related to the blood oxygen level-dependent (BOLD) signal that is used in fMRI. We have employed a sensor that provides simultaneous co-localized measurements of oxygen concentration and neural activity from single cells to characteristics of the oxygen response including spatial, temporal and scaling parameters. We have also investigated changes in oxygen concentration with single cell, multiple unit, and local field potential activity. Finally, we have used specialized sensors to measure neurometabolic coupling between neural activity, glucose, and lactate in activated visual cortex. Findings of these studies will be described.

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11:00-11:30 A BOLD look at the brain's intrinsic activity

Mr Anish Mitra, Washington University, USA

Abstract

Initially regarded as ‘noise’, spontaneous (intrinsic) activity accounts for a large portion of the brain’s metabolic cost. Moreover, it is now widely known that infra-slow (< 0.1 Hz) spontaneous activity, measured using resting state functional magnetic resonance imaging (rs-fMRI) of the blood oxygen level dependent (BOLD) signal, is spatially correlated within resting state networks (RSNs). However, despite these advances, the temporal organisation of spontaneous BOLD fluctuations among RNSs has remained elusive. By studying temporal lags in the resting state BOLD signal, we have recently shown spontaneous BOLD fluctuations consist of remarkably reproducible patterns of whole-brain propagation. Embedded in these propagation patterns are ‘motifs’ which, in turn, give rise to RSNs. Additionally, propagation patterns are markedly altered as a function of state, whether physiological or pathological. Thus, a deeper understanding of the temporal organisation of the BOLD signal may yield insights into the roles spontaneous activity plays in brain function.

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11:40-12:10 Modeling the microvascular origin of BOLD fMRI from first principles

Dr Louis Gagnon, Laval University, Canada

Abstract

The blood oxygenation level-dependent (BOLD) contrast is widely used in functional magnetic resonance imaging (fMRI) studies aimed at investigating neuronal activity. However, the BOLD signal reflects changes in blood volume and oxygenation rather than neuronal activity per se. Therefore, understanding the transformation of microscopic vascular behavior into macroscopic BOLD signals is at the foundation of physiologically informed noninvasive neuroimaging. We present a new method that uses oxygen-sensitive two-photon microscopy to measure the BOLD-relevant microvascular physiology occurring within a typical rodent fMRI voxel and that predicts the BOLD signal from first principles using those measurements. The predictive power of the approach is illustrated by quantifying variations in the BOLD signal induced by the morphological folding of the human cortex. This framework is then used to quantify the contribution of individual vascular compartments and other factors to the BOLD signal for different magnet strengths and pulse sequences. Finally, this method is used to validate and optimize the Calibrated fMRI approach used to recover the cerebral metabolic rate of oxygen CMRO2 in human studies.

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13:30-14:00 The role of the vascular endothelium in functional neurovascular coupling and the BOLD signal

Professor Elizabeth Hillman, Columbia University, USA

Abstract

Understanding the cellular mechanisms of neurovascular coupling should lead to improved understanding of the spatiotemporal properties of the BOLD response, the dependence of the response on neural activity, and the sensitivities of neurovascular coupling to different disease states. Here, we describe the previously overlooked importance of the vascular endothelium as route for the conduction of vasodilation during functional hyperemia. Dependence of the response on an endothelial pathway introduces new interpretations of earlier pharmacological results, explains mismatches in timing between astrocyte responses and vasodilation at the level of diving arterioles, introduces the possibility of multiple mechanisms with slow and fast components contributing to the non-linearities of the BOLD response, and introduces new explanations for the effects of drugs and disease states on brain function and cognitive decline. Through high-speed imaging of both neural activity and hemodynamics across the cortices of the awake, behaving mouse brain, we are exploring the broad consequences of endothelial involvement in neurovascular coupling, in stimulus-evoked and resting state conditions, during longitudinal disease progression, under different pharmacological conditions, and during early post-natal development. These results are important for both understanding how neurovascular coupling can influence brain health, and for improving interpretation of the BOLD signal in health and disease.

14:10-14:40 Spatial limits of imaging human brain function and connectivity: whole brain to cortical columns and layers

Professor Kâmil Uğurbil, University of Minnesota, USA

Abstract

In the last two and a half decades, magnetic resonance methods aimed at imaging neuronal activity have transformed our ability to study the human brain, going from early experiments demonstrating relatively course functional images in the visual cortex to functional mapping with laminar differentiation of neuronal ensembles that perform elementary computations. This development relied on an extensive set of experiments that examined the mechanisms underpinning the functional imaging signals, tackling questions about the spatial specificity of the neurovascular coupling and the connection between hemodynamic and metabolic consequences of neuronal activity and the perturbations on MR detected signals. These studies, conducted on animal models as well as in humans, have provided a rigorous, albeit as of yet incomplete, understanding of the mechanisms underlying the functional mapping signals that reflect neuronal activity, leading to the use of ever increasing magnetic fields to gain accuracy and resolution and to new imaging and image reconstruction methods to map functional activity at the level of cortical columns and layers, and connectivity with ever increasing spatial and temporal resolution.

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15:20-15:50 Functional MRI and the connectome

Professor Ed Bullmore, University of Cambridge, UK

Abstract

Functional MRI has many significant disadvantages as a source of information about nervous systems. It does not directly represent neuronal activity; it has coarse spatial and temporal resolution compared to the range of scales of space and time that brains subtend; it is not measured in SI units; experimental recordings are at least 80% noise; etc. Nonetheless, the patterns of between-regional correlation in slowly oscillating fMRI time series have turned out to be robustly replicable and not trivially explained. Graph theoretical models of human fMRI networks, derived from association matrices of pair-wise functional connectivity estimated for all possible pairs of ~300 regional nodes, demonstrate complex topology: small-worldness, hubs, modules, core/periphery, etc. These features are replicable and heritable. The topological and spatial or geometrical organization of fMRI networks is consistent with the theory that their formation is largely determined by the trade-off between a few competitive factors or conservation laws. Hypothetically, an economic trade-off between the biological cost and the topological value of network components could drive the formation of fMRI networks. To test the generality of this and other hypotheses generated by connectomic analysis of ‘resting state’ fMRI data, graph theoretical methods can be used to make comparable measurements in many other neuroscientific datasets. Meta-analysis of large scale libraries (N~1000 primary papers) of fMRI activation studies demonstrated that more expensive topological features (hubs, rich club) were associated with domain-general, ‘higher-order’ cognitive functions; and that high cost / high value network hubs were hotspots for structural brain deficits associated with many different brain disorders (including Alzheimer’s disease and schizophrenia). Many of the complex topological characteristics of large-scale human fMRI networks are qualitatively reproduced at the microscopic scale of functional networks derived from multi-electrode array recordings of growing neuronal cultures in vitro. The economical model of a trade-off between biological cost and topological value has been specifically re-affirmed by analysis of viral tract tracing data (~400 anterograde tracer injection experiments) on the anatomical connectivity of the mouse brain. We conclude that despite the well-known limitations of fMRI, it has emerged as almost uniquely capable of measuring the complex network organisation of human brain function in a way that is physically, neurobiologically, cognitively, and clinically meaningful.

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16:00-17:00 Overview and panel discussion

Professor David Attwell FRS, University College London, UK