Single session imaging of cerebellum at 7 tesla: Obtaining structure and function of multiple motor subsystems in individual subjects

The recent increase in the use of high field MR systems is accompanied by a demand for acquisition techniques and coil systems that can take advantage of increased power and accuracy without being susceptible to increased noise. Physical location and anatomical complexity of targeted regions must be considered when attempting to image deeper structures with small nuclei and/or complex cytoarchitechtonics (i.e. small microvasculature and deep nuclei), such as the brainstem and the cerebellum (Cb). Once these obstacles are overcome, the concomitant increase in signal strength at higher field strength should allow for faster acquisition of MR images. Here we show that it is technically feasible to quickly and accurately detect blood oxygen level dependent (BOLD) signal changes and obtain anatomical images of Cb at high spatial resolutions in individual subjects at 7 Tesla in a single one-hour session. Images were obtained using two high-density multi-element surface coils (32 channels in total) placed beneath the head at the level of Cb, two channel transmission, and three-dimensional sensitivity encoded (3D, SENSE) acquisitions to investigate sensorimotor activations in Cb. Two classic sensorimotor tasks were used to detect Cb activations. BOLD signal changes during motor activity resulted in concentrated clusters of activity within the Cb lobules associated with each task, observed consistently and independently in each subject: Oculomotor vermis (VI/VII) and CrusI/II for pro- and anti-saccades; ipsilateral hemispheres IV-VI for finger tapping; and topographical separation of eye- and hand- activations in hemispheres VI and VIIb/VIII. Though fast temporal resolution was not attempted here, these functional patches of highly specific BOLD signal changes may reflect small-scale shunting of blood in the microvasculature of Cb. The observed improvements in acquisition time and signal detection are ideal for individualized investigations such as differentiation of functional zones prior to surgery. Copyright

Serial Correlations in Single-Subject fMRI with Sub-Second TR

When performing statistical analysis of single-subject fMRI data, serial correlations need to be taken into account to allow for valid inference. Otherwise, the variability in the parameter estimates might be under-estimated resulting in increased false-positive rates. Serial correlations in fMRI data are commonly characterized in terms of a first-order autoregressive (AR) process and then removed via pre-whitening. The required noise model for the pre-whitening depends on a number of parameters, particularly the repetition time (TR). Here we investigate how the sub-second temporal resolution provided by simultaneous multislice (SMS) imaging changes the noise structure in fMRI time series. We fit a higher-order AR model and then estimate the optimal AR model order for a sequence with a TR of less than 600 ms providing whole brain coverage. We show that physiological noise modelling successfully reduces the required AR model order, but remaining serial correlations necessitate an advanced noise model. We conclude that commonly used noise models, such as the AR(1) model, are inadequate for modelling serial correlations in fMRI using sub-second TRs. Rather, physiological noise modelling in combination with advanced pre-whitening schemes enable valid inference in single-subject analysis using fast fMRI sequences

Imaging of epileptic activity using EEG-correlated functional MRI.

This thesis describes the method of EEG-correlated fMRI and its application to patients with epilepsy. First, an introduction on MRI and functional imaging methods in the field of epilepsy is provided. Then, the present and future role of EEG-correlated fMRI in the investigation of the epilepsies is discussed. The fourth chapter reviews the important practicalities of EEG-correlated fMRI that were addressed in this project. These included patient safety, EEG quality and MRI artifacts during EEG-correlated fMRI. Technical solutions to enable safe, good quality EEG recordings inside the MR scanner are presented, including optimisation of the EEG recording techniques and algorithms for the on-line subtraction of pulse and image artifact. In chapter five, a study applying spike-triggered fMRI to patients with focal epilepsy (n = 24) is presented. Using statistical parametric mapping (SPM), cortical Blood Oxygen Level-Dependent (BOLD) activations corresponding to the presumed generators of the interictal epileptiform discharges (IED) were identified in twelve patients. The results were reproducible in repeated experiments in eight patients. In the remaining patients no significant activation (n = 10) was present or the activation did not correspond to the presumed epileptic focus (n = 2). The clinical implications of this finding are discussed. In a second study it was demonstrated that in selected patients, individual (as opposed to averaged) IED could also be associated with hemodynamic changes detectable with fMRI. Chapter six gives examples of combination of EEG-correlated fMRI with other modalities to obtain complementary information on interictal epileptiform activity and epileptic foci. One study compared spike-triggered fMRI activation maps with EEG source analysis based on 64-channel scalp EEG recordings of interictal spikes using co-registration of both modalities. In all but one patient, source analysis solutions were anatomically concordant with the BOLD activation. Further, the combination of spike- triggered fMRI with diffusion tensor and chemical shift imaging is demonstrated in a patient with localisation-related epilepsy. In chapter seven, applications of EEG-correlated fMRI in different areas of neuroscience are discussed. Finally, the initial imaging findings with the novel technique for the simultaneous and continuous acquisition of fMRI and EEG data are presented as an outlook to future applications of EEG-correlated fMRI. In conclusion, the technical problems of both EEG-triggered fMRI and simultaneous EEG-correlated fMRI are now largely solved. The method has proved useful to provide new insights into the generation of epileptiform activity and other pathological and physiological brain activity. Currently, its utility in clinical epileptology remains unknown

Causal Mapping of Emotion Networks in the Human Brain: Framework and Initial Findings

Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI

Resting state fMRI connectivity is sensitive to laminar connectional architecture in the human brain

Previous invasive studies indicate that human neocortical graymatter contains cytoarchitectonically distinct layers, with notable differences in their structural connectivity with the rest of the brain. Given recent improvements in the spatial resolution of anatomical and functional magnetic resonance imaging (fMRI), we hypothesize that resting state functional connectivity (FC) derived from fMRI is sensitive to layer-specific thalamo-cortical and cortico-cortical microcircuits. Using sub-millimeter resting state fMRI data obtained at 7 T, we found that: (1) FC between the entire thalamus and cortical layers I and VI was significantly stronger than between the thalamus and other layers. Furthermore, FC between somatosensory thalamus (ventral posterolateral nucleus, VPL) and layers IV, VI of the primary somatosensory cortex were stronger than with other layers; (2) Inter-hemispheric cortico-cortical FC between homologous regions in superficial layers (layers I–III) was stronger compared to deep layers (layers V–VI). These findings are in agreement with structural connections inferred from previous invasive studies that showed that: (i) M-type neurons in the entire thalamus project to layer-I; (ii) Pyramidal neurons in layer-VI target all thalamic nuclei, (iii) C-type neurons in the VPL project to layer-IV and receive inputs from layer-VI of the primary somatosensory cortex, and (iv) 80% of collosal projecting neurons between homologous cortical regions connect superficial layers. Our results demonstrate for the first time that resting state fMRI is sensitive to structural connections between cortical layers (previously inferred through invasive studies), specifically in thalamo-cortical and cortico-cortical networks

Coordination of Brain-Wide Activity Dynamics by Dopaminergic Neurons

Several neuropsychiatric conditions, such as addiction and schizophrenia, may arise in part from dysregulated activity of ventral tegmental area dopaminergic (THVTA) neurons, as well as from more global maladaptation in neurocircuit function. However, whether THVTA activity affects large-scale brain-wide function remains unknown. Here we selectively activated THVTA neurons in transgenic rats and measured resulting changes in whole-brain activity using stimulus-evoked functional magnetic resonance imaging. Applying a standard generalized linear model analysis approach, our results indicate that selective optogenetic stimulation of THVTA neurons enhanced cerebral blood volume signals in striatal target regions in a dopamine receptor-dependent manner. However, brain-wide voxel-based principal component analysis of the same data set revealed that dopaminergic modulation activates several additional anatomically distinct regions throughout the brain, not typically associated with dopamine release events. Furthermore, explicit pairing of THVTA neuronal activation with a forepaw stimulus of a particular frequency expanded the sensory representation of that stimulus, not exclusively within the somatosensory cortices, but brain-wide. These data suggest that modulation of THVTA neurons can impact brain dynamics across many distributed anatomically distinct regions, even those that receive little to no direct THVTA input

The Unconscious Formation of Motor and Abstract Intentions

Three separate fMRI studies were conducted to study the neural dynamics of free decision formation. In Study 1, we first searched across the brain for spatiotemporal patterns that could predict the specific outcome and timing of free motor decisions to make a left or right button press (Soon et al., 2008). In Study 2, we replicated Study 1 using ultra-high field fMRI for improved temporal and spatial resolution to more accurately characterize the evolution of decision-predictive information in prefrontal cortex (Bode et al., 2011). In Study 3, to unequivocally dissociate high-level intentions from motor preparation and execution, we investigated the neural precursors of abstract intentions as participants spontaneously decided to perform either of two mental arithmetic tasks: addition or subtraction (Soon et al., 2013). Across the three studies, we consistently found that upcoming decisions could be predicted with ~60% accuracy from fine-grained spatial activation patterns occurring a few seconds before the decisions reached awareness, with very similar profiles for both motor and abstract intentions. The content and timing of the decisions appeared to be encoded in two functionally dissociable sets of regions: frontopolar and posterior cingulate/ precuneus cortex encoded the content but not the timing of the decisions, while the pre-supplementary motor area encoded the timing but not the content of the decisions. The choice-predictive regions in both motor and abstract decision tasks overlapped partially with the default mode network. High-resolution imaging in Study 2 further revealed that as the time-point of conscious decision approached, activity patterns in frontopolar cortex became increasingly stable with respect to the final choice.:Abstract 1 1. General Introduction 5 2. Study 1: Decoding the Unconscious Formation of Motor Intentions 21 3. Study 2: Temporal Stability of Neural Patterns Involved in Intention Formation 56 4. Study 3: Decoding the Unconscious Formation of Abstract Intentions 89 5. General Discussion 119 References 14