16:30 - 18:00
Parallel sessions 3
16:30 - 18:00
Room: HSZ - N3
Chair/s:
Jack E Taylor, Janos Pauli
Written script, including numbers, letters, and letter-strings, is a recent cultural invention central to letter- and number-literate societies. In such societies, humans learn early on to recognise glyphs and map them fluently onto specific sounds and concepts. This symposium explores how the brain achieves this objective, using multiple complementary lenses to understand the processing of linguistic and mathematical symbols, the degree to which these representations are distinct, and interactions between visual symbol recognition and abstract processes of language and numerosity.

The first talk introduces a predictive coding-motivated computational model of letter recognition, showing how these principles might explain the recognition of letters in noisy environments. This work suggests that predictive coding accounts of word recognition may also apply to isolated letters. The second talk uses an optimal transport framework to model the space of early visual representations of letter symbols revealed by EEG, exploring how such representations may be altered in dyslexia. This work tests whether this learning disorder in reading also results in weaker neural alignment with computational models of letter representations. The third talk presents an analysis of human fMRI and macaque electrocorticography responses to naturalistic images, suggesting a shared prominent representation of stimuli related to both orthography and numerosity. This finding is discussed in relation to the notion of proto-architecture for mathematical cognition in the higher-level visual cortex of non-human primates. The fourth talk examines interactions between the processing of Arabic digits and language. This study exploits the discrepancy between the base-10 system of Arabic numbers and base-20 system of French number words, finding that native French speakers utilise language during a numerical task, even when language is redundant. The fifth talk explores how the brain processes words with varying degrees of misspelling. Using MEG data, it examines connectivity between lower visual areas and the lvOT, suggesting that lvOT processes real words in a feedforward manner but engages feedback mechanisms for misspelled words and pseudowords.

Combining experimental and computational approaches, this symposium advances our understanding of how the brain maps arbitrary visual forms into meaningful symbolic representations, and how these processes interact with language and numerosity.
Submission 388
Separating Feedforward and Feedback Dynamics in Left vOT During Word Reading
SymposiumTalk-05
Presented by: Jiaxin You
Jiaxin You 1, Olaf Hauk 2, Riitta Salmelin 1, Marijn van Vliet 1
1 Department of Neuroscience and Biomedical Engineering, Aalto University, Finland
2 MRC Cognition and Brain Sciences Unit, University of Cambridge, United Kingdom
Left ventral occipitotemporal cortex (vOT) is crucial in reading. \clr{Its} functional role is viewed either as a prelexical feedforward hub or a bidirectional interface between sensory and higher-order linguistic systems. \clr{To consolidate the two views and} comprehensively explain the functional complexity of left vOT, we investigated the temporal and spectral dynamics of information flows involving left vOT during visual word and pseudoword reading using magnetoencephalography (MEG) and two directed connectivity metrics, i.e., phase slope index (PSI) and Granger causality (GC). Specifically, feedforward connectivity from low-level visual areas to vOT was observed for all conditions, with the strength of orthographic information flow to left superior temporal cortex (ST) modulated by stimulus word-likeness. Conversely, feedback flow from left ST to vOT appeared for pseudowords that allow top-down linguistic constraints to facilitate reading, and occurred later for word-like than complete pseudowords. Our findings suggest that left vOT during word reading functions in a hybrid manner: operating in efficient feedforward mode for familiar word recognition while flexibly recruiting bidirectional processing for unfamiliar pseudowords. By disentangling feedforward and feedback dynamics with high temporal and spectral resolution, we empirically reconcile different theories of vOT function.