Higher and deeper:Bringing layer fMRI to association cortex

Recent advances in fMRI have enabled non-invasive measurements of brain function in awake, behaving humans at unprecedented spatial resolutions, allowing us to separate activity in distinct cortical layers. While most layer fMRI studies to date have focused on primary cortices, we argue that the next big steps forward in our understanding of cognition will come from expanding this technology into higher-order association cortex, to characterize depth-dependent activity during increasingly sophisticated mental processes. We outline phenomena and theories ripe for investigation with layer fMRI, including perception and imagery, selective attention, and predictive coding. We discuss practical and theoretical challenges to cognitive applications of layer fMRI, including localizing regions of interest in the face of substantial anatomical heterogeneity across individuals, designing appropriate task paradigms within the confines of acquisition parameters, and generating hypotheses for higher-order brain regions where the laminar circuitry is less well understood. We consider how applying layer fMRI in association cortex may help inform computational models of brain function as well as shed light on consciousness and mental illness, and issue a call to arms to our fellow methodologists and neuroscientists to bring layer fMRI to this next frontier

Indoor Positioning Using Angle of Departure Information

I detta examensarbete undersöks möjligheten att kunna använda en positioneringsmetod som inte enbart förlitar sig på den uppmätta signalstyrkan. Istället används en metod som bestämmer från vilken vinkel en signal uppkommer ifrån. Den här tekniken kallas för direction-finding. När informationen om signalens vinkel fastställts används den i ett positioningsfilter som uppskattar positionen. Två tillvägagångssätt har använts i den här rapporten, ett där enbart vinkeln används och ett där både signalstyrka och vinkel används

Analysis of Functional MRI Data Using Mutual Information

. A new information-theoretic approach is presented for analyzing fMRI data to calculate the brain activation map. The method is based on a formulation of the mutual information between two waveforms-- the fMRI temporal response of a voxel and the experimental protocol timeline. Scores based on mutual information are generated for all voxels and then used to compute the activation map of an experiment. Mutual information for fMRI analysis is employed because it has been shown to be robust in quantifying the relationship between any two waveforms. More importantly, our technique takes a principled approach toward calculating the brain activation map by making few assumptions about the relationship between the protocol timeline and the temporal response of a voxel. This is important especially in fMRI experiments where little is known about the relationship between these two waveforms. Experiments are presented to demonstrate this approach of computing the brain activation ..