Biology subjects

Ostarek, M.

Publications and source records attributed to Ostarek, M..

2 recordsLinked to original sources

bioRxiv2018

Cross-decoding reveals shared brain activity patterns between saccadic eye-movements and semantic processing of implicitly spatial words

Processing words with referents that are typically observed up or down in space (up/down words) influences the subsequent identification of visual targets in congruent locations. Eye-tracking studies have shown that up/down word comprehension shortens launch times of subsequent saccades to congruent locations and modulates concurrent saccade trajectories. This can be explained by a task-dependent interaction of semantic processing and oculomotor programs or by a direct recruitment of direction-specific processes in oculomotor and spatial systems as part of semantic processing. To test the latter possibility, we conducted a functional magnetic resonance imaging experiment and used multi-voxel pattern analysis to assess 1) whether the typical location of word referents can be decoded from the fronto-parietal spatial network and 2) whether activity patterns are shared between up/down words and up/down saccadic eye movements. In line with these hypotheses, significant decoding of up vs. down words and cross-decoding between up/down saccades and up/down words were observed in the frontal eye field region in the superior frontal sulcus and the inferior parietal lobule. Beyond these spatial attention areas, typical location of word referents could be decoded from a set of occipital, temporal, and frontal areas, indicating that interactions between high-level regions typically implicated with lexical-semantic processing and spatial/oculomotor regions constitute the neural basis for access to spatial aspects of word meanings.

neuroscience↗

bioRxiv2017

Inferential Pitfalls In Decoding Neural Representations

A key challenge for cognitive neuroscience is to decipher the representational schemes of the brain. A recent class of decoding algorithms for fMRI data, stimulus-feature-based encoding models, is becoming increasingly popular for inferring the dimensions of neural representational spaces from stimulus-feature spaces. We argue that such inferences are not always valid, because decoding can occur even if the neural representational space and the stimulus-feature space use different representational schemes. This can happen when there is a systematic mapping between them, as shown by two simulations. In one simulation, we successfully decoded the binary representation of numbers from their decimal features. Since binary and decimal number systems use different representations, we cannot conclude that the binary representation encodes decimal features. In the second simulation, we successfully decoded the HSV color representation from the RGB representation of colors, even though these color spaces have different geometries and their dimensions have different interpretations. Detailed analysis of the predicted colors showed systematic deviations from the ground truth despite the high decoding accuracy, indicating that decoding accuracy on its own is not sufficient for making representational inferences. The same argument applies to the decoding of neural patterns from stimulus-feature spaces and we urge caution in inferring the nature of the neural code from such methods. We discuss ways to overcome these inferential limitations.

neuroscience↗