Biology subjects

Ostarek, M.

Publications and source records attributed to Ostarek, M..

5 recordsLinked to original sources

bioRxiv2024

Neural Encoding of Semantic StructuresDuring Sentence Production

The neural representations for compositional processing have so far been mostly studied during sentence comprehension. In an fMRI study of sentence production, we investigated the brain representations for compositional processing during speaking. We used a rapid serial visual presentation sentence recall paradigm to elicit sentence production from the conceptual memory of an event. With voxel-wise encoding models, we probed the specificity of the compositional structure built during the production of each sentence, comparing an unstructured model of word meaning without relational information with a model that encodes abstract thematic relations and a model encoding event-specific relational structure. Whole-brain analyses revealed that sentence meaning at different levels of specificity was encoded in a large left fronto-parieto-temporal network. A comparison with semantic structures composed during the comprehension of the same sentences showed similarly distributed brain activity patterns. An ROI analysis over left fronto-temporal language parcels showed that event-specific relational structure above word-specific information was encoded in the left inferior frontal gyrus (LIFG). Overall, we found evidence for the encoding of semantic meaning during sentence production in a distributed brain network and for the encoding event-specific semantic structures in the LIFG.

neuroscience↗

bioRxiv2022

Diverging Neural Dynamics for Syntactic Structure Building in Naturalistic Speaking and Listening

The neural correlates of sentence production have been mostly studied with constraining task paradigms that introduce artificial task effects. In this study, we aimed to gain a better understanding of syntactic processing in spontaneous production vs. naturalistic comprehension. We extracted word-by-word metrics of phrase-structure building with top-down and bottom-up parsers that make different hypotheses about the timing of structure building. In comprehension, structure building proceeded in an integratory fashion and led to an increase in activity in posterior temporal and inferior frontal areas. In production, structure building was anticipatory and predicted an increase in activity in the inferior frontal gyrus. Newly developed production-specific parsers highlighted the anticipatory and incremental nature of structure building in production, which was confirmed by a converging analysis of the pausing patterns in speech. Overall, the results showed that the unfolding of syntactic processing diverges between speaking and listening.

neuroscience↗

bioRxiv2020

Oscillatory responses to generated and perceived rhythms

Neural oscillations have been proposed as a mechanism for structure building in language and music. In music, this idea is appealing because of the intuitive mapping between perceptual and neural rhythms. The strongest evidence has come from studies in which participants listened to isochronous sequences of identical tones and were asked to imagine hearing them in binary (march) or ternary meter (waltz). The critical finding was that in addition to increased signal at the frequency corresponding to the tone rate there was increased signal at the imagined meter frequencies. While it is striking that meter tracking was observed without any acoustic cues in the input, rhythm perception was confounded with rhythm imagery involving active generation of rhythmic structure. We conducted two electroencephalography experiments with musicians and non-musicians, teasing apart the effects of rhythm perception and rhythm generation. Evidence for meter-related neural oscillations was only observed in situations where rhythmic structure was actively generated, either via rhythm imagery or in the form of overt behavior (tapping). Thus, our data suggest that mere rhythm perception is not sufficient to elicit oscillations at the meter frequency and that they are instead driven by the active generation of rhythm. This undermines the proposal that neural oscillations constitute a basic structure building mechanism in rhythm perception and raises questions about the role of oscillations in language processing.

neuroscience↗

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↗