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000279036 1001_ $$00000-0002-3291-2202$$aHuber, Laurentius Renzo$$b0
000279036 245__ $$aShort-term gradient imperfections in high-resolution EPI lead to Fuzzy Ripple artifacts.
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000279036 520__ $$aHigh-resolution fMRI is a rapidly growing research field focused on capturing functional signal changes across cortical layers. However, the data acquisition is limited by low spatial frequency EPI artifacts; termed here as Fuzzy Ripples. These artifacts limit the practical applicability of acquisition protocols with higher spatial resolution, faster acquisition speed, and they challenge imaging in inferior regions of the brain.We characterize Fuzzy Ripple artifacts across commonly used sequences and distinguish them from conventional EPI Nyquist ghosts and off-resonance effects. To investigate their origin, we employ dual-polarity readouts.Our findings indicate that Fuzzy Ripples are primarily caused by readout-specific imperfections in k-space trajectories, which can be exacerbated by short-term eddy current, and by inductive coupling between third-order shims and readout gradients. We also find that these artifacts can be mitigated through complex-valued averaging of dual-polarity EPI or by disconnecting the third-order shim coils.The proposed mitigation strategies allow overcoming current limitations in layer-fMRI protocols: Achieving resolutions beyond 0.8 mm is feasible, and even at 3T, we achieved 0.53 mm voxel functional connectivity mapping. Sub-millimeter sampling acceleration can be increased to allow sub-second TRs and laminar whole brain protocols with up to GRAPPA 8. Sub-millimeter fMRI is achievable in lower brain areas, including the cerebellum.
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000279036 650_7 $$2Other$$a7 T acquisition
000279036 650_7 $$2Other$$aFuzzy Ripples
000279036 650_7 $$2Other$$alayer‐fMRI
000279036 650_7 $$2Other$$aventral brain
000279036 650_2 $$2MeSH$$aArtifacts
000279036 650_2 $$2MeSH$$aHumans
000279036 650_2 $$2MeSH$$aBrain: diagnostic imaging
000279036 650_2 $$2MeSH$$aImage Processing, Computer-Assisted: methods
000279036 650_2 $$2MeSH$$aAlgorithms
000279036 650_2 $$2MeSH$$aEcho-Planar Imaging: methods
000279036 650_2 $$2MeSH$$aBrain Mapping: methods
000279036 650_2 $$2MeSH$$aPhantoms, Imaging
000279036 650_2 $$2MeSH$$aMagnetic Resonance Imaging
000279036 7001_ $$0P:(DE-2719)2810697$$aStirnberg, Rüdiger$$b1
000279036 7001_ $$0P:(DE-HGF)0$$aMorgan, A Tyler$$b2
000279036 7001_ $$00009-0002-5016-9165$$aFeinberg, David A$$b3
000279036 7001_ $$0P:(DE-2719)2812222$$aEhses, Philipp$$b4
000279036 7001_ $$aKnudsen, Lasse$$b5
000279036 7001_ $$00000-0001-7761-3727$$aGulban, Omer Faruk$$b6
000279036 7001_ $$00000-0001-5931-6294$$aKoiso, Kenshu$$b7
000279036 7001_ $$aGephart, Isabel$$b8
000279036 7001_ $$00009-0002-6579-3972$$aSwegle, Stephanie$$b9
000279036 7001_ $$00000-0003-2216-7461$$aWardle, Susan G$$b10
000279036 7001_ $$00000-0002-1580-8497$$aPersichetti, Andrew S$$b11
000279036 7001_ $$00000-0002-7123-9559$$aBeckett, Alexander J S$$b12
000279036 7001_ $$0P:(DE-2719)2810538$$aStöcker, Tony$$b13
000279036 7001_ $$00000-0003-2144-2484$$aBoulant, Nicolas$$b14
000279036 7001_ $$00000-0001-8190-4367$$aPoser, Benedikt A$$b15
000279036 7001_ $$00000-0001-9038-4746$$aBandettini, Peter A$$b16
000279036 773__ $$0PERI:(DE-600)1493786-4$$a10.1002/mrm.30489$$gVol. 94, no. 2, p. 571 - 587$$n2$$p571 - 587$$tMagnetic resonance in medicine$$v94$$x1522-2594$$y2025
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