Flexible goal-directed manipulation of representations: computational models of healthy and pathological human cognition
dc.contributor.supervisor | Baldassarre, Gianluca | |
dc.contributor.author | Granato, Giovanni | |
dc.contributor.other | School of Engineering, Computing, and Mathematics | en_US |
dc.date.accessioned | 2022-10-05T14:42:04Z | |
dc.date.issued | 2022 | |
dc.identifier | 10664997 | en_US |
dc.identifier.uri | http://hdl.handle.net/10026.1/19674 | |
dc.description | The theoretical and computational works presented in this thesis have been published at international peer-reviewed conferences and journals. The candidate is the first author of all publications listed below. Indeed, he has personally carried out all the key steps that have led to these publications such as literature reviews, computational models development, data analysis and interpretations, drawing of figures/plots/schemes, manuscript writing and revision until final publication. Supervisors and other co-authors have supported these projects, providing suggestions at every stage. Chapter 2 and 3 are adapted from m Granato & Baldassarre (2021), Granato et al. (2020), Granato et al. (2022b), and Baldassarre & Granato (2020). In particular, chapter 2 is adapted from the theoretical sections of the published papers (e.g., literature reviews and theoretical proposals) while chapter 3 is adapted from the computational sections of the published papers (e.g. experimental task/conditions, models descriptions, results, discussions). Chapter 4 is adapted from m Granato et al. (2022a) and Baldassarre & Granato (2022). In particular, section 4.1 is adapted from the first and section 4.2 is adapted from the second paper. Finally, section 4.2.3 (`Implications of the RIM framework') focuses on similar topics that I have approached in Baldassarre & Granato (2020), i.e. `representations manipulation in AI'. | en_US |
dc.description.abstract |
The brain is able to manipulate itself, adapting its internal world in a changing environment. In particular it continuously manipulates its representations to achieve goals. This competence is supported by many neurocognitive high-order processes that interact during the performance of a goal-directed behaviour (e.g. attention processes, executive functions, motivational systems). Overall, adult humans often face a new problem trough a change of the `perceptual point of view' (i.e. a representational change), rather then an extended research of the correct action to perform. On the other hand, infants and children contemporary develop motor competence and task-directed perceptual representations (e.g. categorical perception). Here I approach the main research question `how the brain manipulates its representations to solve a task that requires cognitive flexibility?'. Moreover, I started to approach the second related research question `how the brain acquires suitable representations to solve a categorisation task?'. First, adopting a synergistic theoretical and computational approach, I identified the systems and basic computational principles that allow the brain to learn, to generate and to manipulate its internal representations in order to achieve a goal. Second, I built a set of computational models and I tested them against experimental human data extracted from already published experimental works. This translational approach corroborates my theoretical proposals and, vice versa, provides scientific and clinical knowledge on the investigated processes. In particular, my models represent a novel computational tool for the investigation of flexible cognition and categorical perception in case of clinical populations (e.g. autistic people). Moreover, they represent a starting point to propose a new theory of conscious cognition showing both scientific implications (e.g new models of consciousness) and technological implications (e.g consciousness-inspired robots). | en_US |
dc.language.iso | en | |
dc.publisher | University of Plymouth | |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | Cognitive flexibility | en_US |
dc.subject | Executive functions | en_US |
dc.subject | Consciousness | en_US |
dc.subject | Computational neuropsychology and psychiatry | en_US |
dc.subject | Machine Learning | en_US |
dc.subject.classification | PhD | en_US |
dc.title | Flexible goal-directed manipulation of representations: computational models of healthy and pathological human cognition | en_US |
dc.type | Thesis | |
plymouth.version | publishable | en_US |
dc.identifier.doi | http://dx.doi.org/10.24382/661 | |
dc.identifier.doi | http://dx.doi.org/10.24382/661 | |
dc.rights.embargodate | 2023-10-05T14:42:04Z | |
dc.rights.embargoperiod | 12 months | en_US |
dc.type.qualification | Doctorate | en_US |
rioxxterms.version | NA |
Files in this item
This item appears in the following Collection(s)
-
01 Research Theses Main Collection
Research Theses Main