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Alexandra Krugliak

Publications and source records attributed to Alexandra Krugliak.

2 recordsLinked to original sources

Local opposite orientation preferences in V1: fMRI sensitivity to fine-grained pattern information

The orientation of a visual grating can be decoded from human primary visual cortex (V1) using functional magnetic resonance imaging (fMRI) at conventional resolutions (2-3 mm voxel width, 3T scanner). It is unclear to what extent this information originates from different spatial scales of neuronal selectivity, ranging from orientation columns to global areal maps. According to the global-areal-map account, fMRI orientation decoding relies exclusively on fMRI voxels in V1 exhibiting a radial or vertical preference. Here we show, by contrast, that 2-mm isotropic voxels in a small patch of V1 within a quarterfield representation exhibit reliable opposite selectivities. Sets of voxels with opposite selectivities are locally intermingled and each set can support orientation decoding. This indicates that global areal maps cannot fully account for orientation information in fMRI and demonstrates that fMRI also reflects fine-grained patterns of neuronal selectivity.\n\nSignificance statementConventional (3T) functional magnetic resonance imaging (fMRI) allows one measure brain activity at a spatial resolution of 2-3 mm. Brain response patterns in the primary visual cortex (V1) measured with fMRI have been shown to contain robust information about the orientation of visual grating stimuli. However, it is unclear whether this information arises only from global-areal patterns or also from more fine-grained patterns. Here we show that opposite orientation preferences are present and replicable within small V1 patches. This finding demonstrates that fine-grained fMRI patterns contribute to the orientation information present in fMRI data.

Neuroscience

Mind the drift - improving sensitivity to fMRI pattern information by accounting for temporal pattern drift

Analyzing functional magnetic resonance imaging (fMRI) pattern similarity is becoming increasingly popular because it allows one to relate distributed patterns of voxel activity to continuous perceptual and cognitive states of the human brain. Here we show that fMRI pattern similarity estimates are severely affected by temporal pattern drifts in fMRI data - even after voxel-wise detrending. For this particular dataset, the drift effect obscures orientation information as measured by fMRI pattern dissimilarities. We demonstrate that orientation information can be recovered using three different methods: 1. Regressing out the drift component through linear modeling; 2. Computing representational distances between conditions measured in independent imaging runs; 3. Crossvalidation of pattern distance estimates. One possible source of temporal pattern drift could be random walk like fluctuations -- physiological or scanner related -- occurring within single voxel timecourses. This explanation is consistent with voxel-wise detrending not alleviating pattern drift effects. In addition, this would explain why crossvalidated pattern distances are robust to temporal drift because a random walk process is expected to give rise to non-replicable drift directions. Given these findings, we recommend that future fMRI studies take pattern drift into account when analyzing pattern similarity as this can greatly enhance the sensitivity to experimental effects of interest.

Neuroscience