Detta projekt går ut på att skapa en analog effektpedal, från kretsdesign till montering på kretskort. Vi har designat en krets som förändrar en signal på ett sätt som bäst beskrivs som en phaser-pedal. Den ursprungliga signalen, tänkt att vara från ett elektriskt instrument, superpositioneras med en fasskiftad kopia. Fasskiftet görs genom fyra steg med allpassfilter, dessa lämnar amplituden oförändrad men fasskiftar beroende på frekvens. Hur mycket olika frekvenser fasskiftas regleras med Junction Field Effect Transistors (JFETs) som variabla motstånd. Fyra allpassfilter ger fullständig negativ interferens för två frekvenser, dessa kommer i rapporten refereras till som gropar. Groparna flyttas i frekvensspektrat över tid med hjälp av en lågfrekvensoscillator (LFO). Frekvensen på denna oscillator bestäms med ett variabelt motstånd och ligger mellan 0.1 och 10 Hz. LFO-signalen går in i Gate-kanalen på JFETsen och har en direkt koppling till deras resistans. Hela kretsen drivs av ett 9V-batteri och är designad för att behandla amplitudsspannet från elektriska instrument, från 1-1000mV. Kretsen ska inte heller förändra amplituden för någon frekvens mellan 41Hz och 20kHz. Kretsen har simulerats i LTspice, testats på kopplingsplatta och sist har ett mönsterkort skapats i KiCad där delarna lötts fast.

<p>    </p> <p>Cerebrovascular diseases, such as stroke, constitute the most common life-threatening neurological disease in the United States. To support normal brain function, maintaining adequate brain perfusion (i.e., cerebral blood flow (CBF)) is important. Therefore, it is crucial to assess the brain perfusion so that early intervention in cerebrovascular diseases can be applied if abnormal perfusion is observed. The goal of my study is to develop metrics to measure the brain perfusion through modeling brain physiology using resting-state and task-based blood-oxygenation-level- dependent (BOLD) functional MRI (fMRI). My first and second chapters focused on deriving the blood arrival time using the resting-state BOLD signal. In the first chapters, we extracted the systemic low-frequency oscillations (sLFOs) in the fMRI signal from the internal carotid arteries (ICA) and the superior sagittal sinus (SSS). Consistent and robust results were obtained across 400 scans showing the ICA signals leading the SSS signals by about 5 seconds. This delay time could be considered as an effective perfusion biomarker that is associate with the cerebral circulation time (CCT). To further explore sLFOs in assessing dynamic blood flow changes during the scan, in my second chapter, a “carpet plot” (a 2-dimensional plot time vs. voxel) of scaled fMRI signal intensity was reconstructed and paired with a developed slope-detection algorithm. Tilted vertical edges across which a sudden signal intensity change took place were successfully detected by the algorithm and the averaged propagation time derived from the carpet plot matches the cerebral circulation time. Given that CO₂ is a vasodilator, controlling of inhaled CO₂ is able to modulate the BOLD signal, therefore, as a follow-up study, we focused on investigating the feasibility of using a CO₂ modulated sLFO signal as a “natural” bolus to track CBF with the tool developed from the second chapter. Meaningful transit times were derived from the CO₂-MRI carpet plots. Not only the timing, the BOLD signal deformation (the waveform change) under CO₂ challenge also reveals very useful perfusion information, representing how the brain react to stimulus. Therefore, my fourth chapter focused on characterizing the brain reaction to the CO₂ stimulus to better measure the brain health using BOLD fMRI. Overall, these studies deepen our understanding of fMRI signal and the derived perfusion parameters can potentially be used to assess some cerebrovascular diseases, such as stroke, ischemic brain damage, and steno-occlusive arterial disease in addition to functional activations. </p>