Items Authored/Edited by Garagnani, M.
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Number of items: 46.
Garagnani, M..
2024.
On the ability of standard and brain-constrained deep neural networks to support cognitive superposition: a position paper.
Cognitive Neurodynamics,
ISSN 1871-4080
[Article]
(In Press)
Shtyrov, Y.; Efremov, A.; Kuptsova, A.; Wennekers, T.; Gutkin, B. and Garagnani, M..
2023.
Breakdown of category-specific word representations in a brain-constrained neurocomputational model of semantic dementia.
Scientific Reports, 13,
19572.
ISSN 2045-2322
[Article]
Bourne, Josh; Rosas, Fernando, E. and Garagnani, M..
2023.
'Using information theory to measure the emergence of artificial free will in a spiking brain-constrained model of the human cortex'.
In: 32nd Annual Computational Neuroscience Meeting. Leipzig, Germany 15 - 19 July 2023.
[Conference or Workshop Item]
Ušacka, A.; Schurger, A. and Garagnani, M..
2023.
'A brain-constrained deep neural-network model that can account for the readiness potential in self-initiated volitional action'.
In: 32nd Annual Computational Neuroscience Meeting. Leipzig, Germany 15 - 19 July 2023.
[Conference or Workshop Item]
Vanegdom, A.; Nikolaev, N. and Garagnani, M..
2022.
'Standard feedforward neural networks with backprop cannot support cognitive superposition'.
In: Bernstein Conference 2022. Berlin, Germany 13-16 September 2022.
[Conference or Workshop Item]
Henningsen-Schomers, M.; Garagnani, M. and Pulvermüller, F..
2022.
'Influence of language on concept formation and perception in a brain-constrained deep neural network model'.
In: TABU Dag 2022. Groningen, Netherlands 9 - 22 June 2022.
[Conference or Workshop Item]
Garagnani, M. and Lucchese, G..
2021.
'Reconciling forgetting and memory consolidation: simulating the dissociable effects of neuronal noise levels on cortical memory traces.'.
In: 30th Annual Computational Neuroscience Meeting (CNS-2021). Online 3 - 7 July 2021.
[Conference or Workshop Item]
Garagnani, M.; Kirilina, E. and Pulvermüller, F.
2021.
Semantic grounding of novel spoken words in the primary visual cortex.
Frontiers in Human Neuroscience, 15,
581847.
ISSN 1662-5161
[Article]
Garagnani, M.; Kirilina, E. and Pulvermüller, F..
2020.
Perception-action circuits for word learning and semantic grounding: a neurocomputational model and neuroimaging study.
In: Maria Raposo; Paulo Ribeiro; Susanna Sério; Antonino Staiano and Angelo Ciaramella, eds.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 15th International Meeting, CIBB 2018, Caparica, Portugal, September 6–8, 2018, Revised Selected Papers.
Cham, Switzerland: Springer International Publishing.
ISBN 9783030345846
[Book Section]
Henningsen-Schomers, M.; Garagnani, M. and Pulvermüller, F..
2020.
'Influence of verbal labels on concept formation and perception in a deep unsupervised neural network model'.
In: 14th International Conference of Cognitive Neuroscience (ICON 2022). Helsinki, Finland 18 - 22 May 2022.
[Conference or Workshop Item]
(Forthcoming)
Tomasello, R.; Wennekers, T.; Garagnani, M. and Pulvermüller, F..
2019.
Visual cortex recruitment during language processing in blind individuals is explained by Hebbian learning.
Scientific Reports, 9,
3579.
ISSN 2045-2322
[Article]
Tomasello, R.; Wennekers, T.; Garagnani, M. and Pulvermüller, F..
2019.
'Recruitment of visual cortex for language processing in blind individuals: A neurobiological model'.
In: 2019 Annual meeting of the Cognitive Neuroscience Society (CNS 2019). San Francisco, United States 25 March 2019.
[Conference or Workshop Item]
Tomasello, R.; Garagnani, M.; Wennekers, T. and Pulvermüller, F..
2018.
A neurobiologically constrained cortex model of semantic grounding with spiking neurons and brain-like connectivity.
Frontiers in Computational Neuroscience, 12(88),
[Article]
Tomasello, R.; Garagnani, M.; Wennekers, T. and Pulvermüller, F..
2017.
Brain connections of words, perceptions and actions: A neurobiological model of spatio-temporal semantic activation in the human cortex.
Neuropsychologia, 98,
pp. 111-129.
ISSN 0028-3932
[Article]
Schomers, M.R.; Garagnani, M. and Pulvermüller, F..
2017.
Neurocomputational Consequences of Evolutionary Connectivity Changes in Perisylvian Language Cortex.
The Journal of Neuroscience, 37(11),
pp. 3045-3055.
ISSN 0270-6474
[Article]
Garagnani, M.; Lucchese, G.; Tomasello, R.; Wennekers, T. and Pulvermüller, F..
2017.
A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords.
Frontiers in Computational Neuroscience, 10,
145.
ISSN 1662-5188
[Article]
Garagnani, M. and Pulvermüller, F..
2016.
Conceptual grounding of language in action and perception: a neurocomputational model of the emergence of category specificity and semantic hubs.
European Journal of Neuroscience, 43(6),
pp. 721-737.
ISSN 0953-816X
[Article]
Adams, S.V.; Wennekers, T.; Cangelosi, A.; Garagnani, M. and Pulvermüller, F..
2015.
'Learning Visual-Motor Cell Assemblies for the iCub Robot using a Neuroanatomically Grounded Neural Network'.
In: IEEE Symposium Series on Computational Intelligence, Cognitive Algorithms, Mind and Brain (SSCI-CCMB 2014). Orlando, United States 9-12 December 2014.
[Conference or Workshop Item]
Pulvermüller, F.; Garagnani, M. and Wennekers, T..
2014.
Thinking in circuits: toward neurobiological explanation in cognitive neuroscience.
Biological Cybernetics, 108(5),
pp. 573-593.
ISSN 0340-1200
[Article]
Pulvermüller, F. and Garagnani, M..
2014.
From sensorimotor learning to memory cells in prefrontal and temporal association cortex: A neurocomputational study of disembodiment.
Cortex, 57,
pp. 1-21.
ISSN 0010-9452
[Article]
Shtyrov, Y.; Kimppa, L. and Garagnani, M..
2014.
'Electrophysiological and haemodynamic biomarkers of rapid acquisition of novel wordforms'.
In: Microstructures of Learning: Novel methods and approaches for assessing structural and functional changes underlying knowledge acquisition in the brain. Lund, Sweden 23 May, 2014.
[Conference or Workshop Item]
Ludlow, A.; Mohr, B.; Whitmore, A.; Garagnani, M.; Pulvermüller, F. and Gutierrez, R..
2014.
Auditory processing and sensory behaviours in children with autism
spectrum disorders as revealed by mismatch negativity.
Brain and Cognition, 86,
pp. 55-63.
ISSN 0278-2626
[Article]
Garagnani, M. and Pulvermüller, F..
2013.
Neuronal correlates of decisions to speak and act: Spontaneous emergence and dynamic topographies in a computational model of frontal and temporal areas.
Brain & Language, 127(1),
pp. 75-85.
ISSN 0093-934X
[Article]
Garagnani, M. and Pulvermüller, F..
2011.
From sounds to words: A neurocomputational model of adaptation, inhibition and memory processes in auditory change detection.
Neuroimage, 54(1),
pp. 170-181.
ISSN 1053-8119
[Article]
Garagnani, M.; Shtyrov, Y. and Pulvermüller, F..
2009.
Effects of attention on what is known and what is not: MEG evidence for functionally discrete memory circuits.
Frontiers in Human Neuroscience,
[Article]
Garagnani, M.; Wennekers, T. and Pulvermüller, F..
2009.
Recruitment and Consolidation of Cell Assemblies for Words by Way of Hebbian Learning and Competition in a Multi-Layer Neural Network.
Cognitive Computation, 1(2),
pp. 160-176.
ISSN 1866-9956
[Article]
Garagnani, M.; Wennekers, T. and Pulvermüller, F..
2008.
A neuroanatomically grounded Hebbian-learning model of attention–language interactions in the human brain.
European Journal of Neuroscience, 27(2),
pp. 492-513.
ISSN 0953-816X
[Article]
Garagnani, M..
2005.
A Diagrammatic Inter-Lingua for Planning Domain Descriptions.
In: Luis Castillo; Daniel Borrajo; Miguel A. Salido and Angelo Oddi, eds.
Planning, Scheduling and Constraint Satisfaction: From Theory to Practice.
117
Amsterdam: IOS Press, pp. 129-138.
ISBN 9781586034849
[Book Section]
Garagnani, M..
2005.
A Framework for Hybrid Planning.
In: Max Bramer; Frans Coenen and Tony Allen, eds.
Research and Development in Intelligent Systems XXI: Proceedings of AI-2004, the Twenty-fourth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence.
London: Springer, pp. 214-227.
ISBN 9781852339074
[Book Section]
Garagnani, M..
2005.
A Framework for Hybrid and Analogical Planning.
In: Ioannis Vlahavas and Dimitris Vrakas, eds.
Intelligent Techniques for Planning.
Hershey, Pennsylvania: Idea Group Publishing, pp. 35-89.
ISBN 9781591404507
[Book Section]
Garagnani, M..
2004.
Model-based Planning in Physical domains using SetGraphs.
In: Frans Coenen; Alun Preece and Ann L. Macintosh, eds.
Research and Development in Intelligent Systems XX: Proceedings of AI2003, the Twenty-third SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence.
London: Springer, pp. 295-308.
ISBN 9781852337803
[Book Section]
Garagnani, M.; Shastri, Lokendra and Wendelken, Carter.
2002.
'A Connectionist model of Planning via Back-chaining Search'.
In: 24th Annual Meeting of the Cognitive Science Society (CogSci 2002). Fairfax, VA, United States 7-10 August 2002.
[Conference or Workshop Item]
Garagnani, M..
2001.
A Correct Algorithm for Efficient Planning with Preprocessed Domain Axioms.
In: Max Bramer; Alun Preece and Frans Coenen, eds.
Research and Development in Intelligent Systems XVII: Proceedings of ES2000, the Twentieth SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, Cambridge, December 2000.
London: Springer, pp. 363-374.
ISBN 9781852334031
[Book Section]
Reed, C.; Long, D.; Fox, M. and Garagnani, M..
1997.
Persuasion as a form of inter-agent negotiation.
In: Chengqi Zhang and Dickson Lukose, eds.
Multi-Agent Systems Methodologies and Applications: Second Australian Workshop on Distributed Artificial Intelligence Cairns, QLD, Australia, August 27, 1996 Selected Papers.
Berlin: Springer, pp. 120-136.
ISBN 9783540634126
[Book Section]