Cognitive and Neural Computations of Semantics

CONNECTS aims to resolve the paradox of semantic congruity's effects on cognition by developing a unified framework that integrates behavioral, neural, and computational methods.

Subsidie
€ 1.496.563
2025

Projectdetails

Introduction

In our everyday lives, we rely on existing relations among elements in our environment (i.e., semantic information) to interact efficiently with the world. This information can either be used to facilitate understanding by exploiting redundant (congruent) evidence or to signal out salient stimuli by highlighting unexpected (incongruent) elements.

Cognitive Puzzle

This duality raises fundamental questions about how and when our brains utilize stored semantic knowledge, as its influence seems to vary depending on the specific cognitive domain. This seemingly paradoxical state represents a cognitive puzzle that questions whether the presence of (in)congruent contextual information in a given situation has a positive or negative impact on how we perceive, process, and remember information.

Project Overview

CONNECTS seeks to address the paradoxical effects of semantic congruity across various cognitive domains by providing a unified framework. The proposed framework builds on the Transfer Appropriate Processing principle and brings it to a neural representational level.

Neural Representations

By examining the transformations of neural representations, it is possible to quantify the degree of overlap in cognitive computations as a measure of appropriate transfer. Thus, CONNECTS dissolves the paradox by proposing that performance would be optimal when the required cognitive computation is oriented towards the same stimulus properties emphasized by the semantic (in)congruity of the stimulus.

Integrative Aim

This proposal not only reconciles conflicting evidence on specific domains but also provides a domain-agnostic framing of the conundrum that ensures its integrative aim.

Methodology

CONNECTS combines a solid theoretical foundation with cutting-edge neuroscientific techniques. The project's multi-method approach includes:

  1. Behavioural data
  2. Neural data (fMRI and EEG)
  3. Computational data from artificial neural networks

This approach offers a comprehensive exploration of the phenomenon, which is a core requirement for a unifying framework.

Financiële details & Tijdlijn

Financiële details

Subsidiebedrag€ 1.496.563
Totale projectbegroting€ 1.496.563

Tijdlijn

Startdatum1-1-2025
Einddatum31-12-2029
Subsidiejaar2025

Partners & Locaties

Projectpartners

  • UNIVERSIDAD DE GRANADApenvoerder

Land(en)

Spain

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