Dr Max Garagnani

Staff details

Position

Senior Lecturer in Computer Science

Department

Computing

Email

M.Garagnani (@gold.ac.uk)

Links

Max uses computer modelling and simulations to explore how we learn to speak and how the mind works.

Max is a Senior Lecturer in Computer Science and co-director of the programme. He holds a PhD in Computational Cognitive Neuroscience from the University of Cambridge, UK (2009) and a PhD in Artificial Intelligence from the University of Durham (1999).

Max's research focuses on building and applying biologically realistic, deep neural networks (mimicking structural and functional features of the cortex) to study the spontaneous emergence of cognitive functions, with a particular focus on natural language processing and acquisition, and spontaneous decisions.

His previous posts include Postdoctoral Researcher at the Centre for Robotics & Neural Systems (University of Plymouth), Investigator Scientist at MRC Cognition & Brain Sciences Unit (Cambridge, UK), and Visiting Scholar at the International Computer Science Institute (Berkeley, CA). He is also visiting researcher at the of the Free University of Berlin (Germany).

Academic qualifications

PhD in Computational Cognitive Neuroscience 2009
PhD in Artificial Intelligence 1999
PG Certificate in Teaching and Learning in Higher Education 2023
Laurea (BSc + MSc) in Computer Science 1994

Teaching and supervision

I supervise projects in my areas of interest (see "Research Interests" below).
I teach on the following programmes:

Research interests

My research centres on building and applying biologically realistic neural networks. Specifically, I model the neural mechanisms underlying the emergence of cognitive functions (in particular, language acquisition and processing, spontaneous decision making) in the brain. I simulate the emergence of such higher-level functions starting from an initially randomly connected uniform neural substrate, and by means of unsupervised learning mechanisms closely mimicking synaptic plasticity processes known to exist in the cortex. In parallel to the computational modelling, I also collaborate with experimentalists to apply brain imaging and behavioural methods to test and validate the predictions emerging from the computational models.

Unlike most of the modelling work in this area, the neural architecture I have developed over the past two decades adopts a "first principles" approach, i.e., it is not designed to explain a specific dataset or cognitive function. In fact, while it was originally applied mainly to simulate spoken language acquisition processes, its generality later allowed its successful application to explain the emergence of (and the mechanisms underlying) a range of other cognitive phenomena. These include, prediction error and automatic change-detection responses, attention, the emergence of memory cells and working memory processes, the recruitment of visual cortex in blind individuals, and the emergence of spontaneous (or "free") decisions to act (see list of publications below).

I have worked closely and for several years with the at the Freie Universit盲t Berlin (Germany), directed by Prof. Friedemann Pulverm眉ller, and was co-PI and staff member of the jointly EPSRC/BBSRC-funded interdisciplinary project BABEL, which investigated the neural mechanisms underlying embodied word learning by joint use of neuroimaging, brain-inspired modelling, neuromorphic engineering and real-time implementation on the humanoid robot .

Featured publications

2023:
Philosophical Transactions of the Royal Society B, 378: 20210373.

2023:
Scientific Reports 13:19572.

2017:
The Journal of Neuroscience, 37(11), pp. 3045-3055

2016:
European Journal of Neuroscience, 43(6), pp. 721-737.

2014:
Biological Cybernetics, 108(5), pp. 573-593.

Publications and research outputs

Book Section

; Kirilina, E. and Pulverm眉ller, F.. 2020. Perception-action circuits for word learning and semantic grounding: a neurocomputational model and neuroimaging study. In: Maria Raposo; Paulo Ribeiro; Susanna S茅rio; Antonino Staiano and Angelo Ciaramella, eds. Computational Intelligence Methods for Bioinformatics and Biostatistics: 15th International Meeting, CIBB 2018, Caparica, Portugal, September 6鈥�8, 2018, Revised Selected Papers. Cham, Switzerland: Springer International Publishing. ISBN 9783030345846
. 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
. 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

Article

. 2024. On the ability of standard and brain-constrained deep neural networks to support cognitive superposition: a position paper. Cognitive Neurodynamics, 18, pp. 3383-3400. ISSN 1871-4080
Gelens, Frank; Aijala, Julio; Roberts, Louis; Komatsu, Misako; Uran, Cem; Jensen, Michael A.; Miller, Kai J.; Ince, Robin A.A.; ; Vinck, Martin and Canales-Johnson, Andres. 2024. Distributed representations of prediction error signals across the cortical hierarchy are synergistic. Nature Communications, 15, 3941. ISSN 2041-1723
Shtyrov, Y.; Efremov, A.; Kuptsova, A.; Wennekers, T.; Gutkin, B. and . 2023. Breakdown of category-specific word representations in a brain-constrained neurocomputational model of semantic dementia. Scientific Reports, 13, 19572. ISSN 2045-2322

Henningsen-Schomers, Malte R.; and Pulverm眉ller, Friedemann. 2023. Influence of language on perception and concept formation in a brain-constrained deep neural network model. Philosophical Transactions of the Royal Society B: Biological Sciences, 378(1870), 20210373. ISSN 0962-8436
; Kirilina, E. and Pulverm眉ller, F. 2021. Semantic grounding of novel spoken words in the primary visual cortex. Frontiers in Human Neuroscience, 15, 581847. ISSN 1662-5161
Tomasello, R.; Wennekers, T.; and Pulverm眉ller, F.. 2019. Visual cortex recruitment during language processing in blind individuals is explained by Hebbian learning. Scientific Reports, 9, 3579. ISSN 2045-2322
Tomasello, R.; ; Wennekers, T. and Pulverm眉ller, F.. 2018. A neurobiologically constrained cortex model of semantic grounding with spiking neurons and brain-like connectivity. Frontiers in Computational Neuroscience, 12(88),
Tomasello, R.; ; Wennekers, T. and Pulverm眉ller, 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
Schomers, M.R.; and Pulvermu虉ller, F.. 2017. Neurocomputational Consequences of Evolutionary Connectivity Changes in Perisylvian Language Cortex. The Journal of Neuroscience, 37(11), pp. 3045-3055. ISSN 0270-6474
; Lucchese, G.; Tomasello, R.; Wennekers, T. and Pulvermu虉ller, 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
and Pulverm眉ller, 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
Pulvermu虉ller, F.; and Wennekers, T.. 2014. Thinking in circuits: toward neurobiological explanation in cognitive neuroscience. Biological Cybernetics, 108(5), pp. 573-593. ISSN 0340-1200
Pulverm眉ller, F. and . 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
Ludlow, A.; Mohr, B.; Whitmore, A.; ; Pulvermu虉ller, 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
and Pulverm眉ller, 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
and Pulverm眉ller, Friedemann. 2011. Investigating cognitive representations with brain-like networks and MEG/EEG. Clinical Neurophysiology, 122, S12. ISSN 1388-2457
and Pulverm眉ller, 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
; Shtyrov, Y. and Pulvermu虉ller, F.. 2009. Effects of attention on what is known and what is not: MEG evidence for functionally discrete memory circuits. Frontiers in Human Neuroscience,
; Wennekers, T. and Pulvermu虉ller, 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
; Wennekers, T. and Pulvermu虉ller, F.. 2008. A neuroanatomically grounded Hebbian-learning model of attention鈥搇anguage interactions in the human brain. European Journal of Neuroscience, 27(2), pp. 492-513. ISSN 0953-816X
; Wennekers, Thomas and Pulverm眉ller, Friedemann. 2007. Explaining the effects of attention on lexical processes using a single Hebbian neuronal model of the language cortex. Neural Plasticity, 2007, pp. 66-67. ISSN 2090-5904
; Wennekers, Thomas and Pulverm眉ller, Friedemann. 2006. A neuronal model of the language cortex. Neurocomputing, 70(10-12), pp. 1914-1919. ISSN 0925-2312
Wennekers, Thomas; and Pulverm眉ller, Friedemann. 2006. Language models based on Hebbian cell assemblies. Journal of Physiology-Paris, 100(1-3), pp. 16-30. ISSN 0928-4257

Conference or Workshop Item

; and . 2025. 'Simulating the point of no return in human volitional action in a brain-constrained model of sensory and motor areas.'. In: 34th Annual Computational Neuroscience Meeting (CNS*2025). Florence, Italy 5-9 July 2025.
; Schurger, Aaron and . 2025. 'Spontaneous emergence of slow ramping prior to decision states in a brain-constrained model of fronto-temporal cortical areas'. In: 34th Annual Computational Neuroscience Meeting (CNS*2025). Florence, Italy 5-9 July 2025.
. 2025. 'Concept superposition and learning in standard and brain-constrained deep neural networks'. In: 34th Annual Computational Neuroscience Meeting (CNS 2025), Workshop on "Brains and AI". Florence, Italy 9 July 2025.

; Rosas, Fernando, E. and . 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.
U拧acka, A.; Schurger, A. and . 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.
; and . 2022. 'Standard feedforward neural networks with backprop cannot support cognitive superposition'. In: Bernstein Conference 2022. Berlin, Germany 13-16 September 2022.
Henningsen-Schomers, M.; and Pulverm眉ller, 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.
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.
. 2020. 'Action-perception circuits for word learning and semantic grounding'. In: NAACL Workshop on Visually-Grounded Interaction and Language (ViGIL). Mexico City, Mexico 10 June 2021.
Henningsen-Schomers, M.; and Pulverm眉ller, 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.
Tomasello, R.; Wennekers, T.; and Pulverm眉ller, 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.
. 2017. 'Simulating word learning and high-frequency brain responses to linguistic items in a neurobiologically realistic model of the cortex'. In: 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL/EPIROB 2017) 鈥� 2nd Workshop on Language Learning. Lisbon, Portugal 18-21 September 2017.
Tomasello, Rosario; ; Wennekers, Thomas and Pulverm眉ller, Friedemann. 2017. 'Semantic grounding in a neurobiologically-constrained cortex-model with realistic connectivity and spiking neurons'. In: 24th Annual Meeting of the Cognitive Neuroscience Society (CNS 2017). San Francisco, United States 25-28 March 2017.
. 2016. 'Word acquisition and semantic grounding in a neuroanatomically realistic, Hebbian-learning, spiking neural network model of the cortex'. In: Neuroinformatics 2016. Reading, United Kingdom 3-4 September 2016.
Schomers, M.R.; and Pulverm眉ller, F.. 2015. 'Highway to (verbal) memory: Neurocomputational consequences of specifically human connectivity in perisylvian cortex.'. In: 23rd Annual Meeting of the Cognitive Neuroscience Society (CNS 2016). New York, United States.
Adams, S.V.; Wennekers, T.; Cangelosi, A.; and Pulverm眉ller, 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.
Shtyrov, Y.; Kimppa, L. and . 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.
; Shtyrov, Y. and Davis, M.. 2012. 'Effects of sleep and number of repetitions on novel spoken word learning: fMRI evidence.'. In: 20th Annual Meeting of the Cognitive Neuroscience Society (CNS 2013). San Francisco, United States.
; Wennekers, Thomas and Pulverm眉ller, Friedemann. 2009. 'MMN reflections of language and attention: a neurocomputational model'. In: MMN 09 Fifth Conference on Mismatch Negativity (MMN) and its Clinical and Scientific Applications. Budapest, Hungary 4-7 April 2009.
; Shtyrov, Yury and Pulverm眉ller, Friedemann. 2009. 'Explaining Attention and Language interactions: magnetic MMN validation of neurocomputational predictions'. In: MMN 09 Fifth Conference on Mismatch Negativity (MMN) and its Clinical and Scientific Applications. Budapest, Hungary 4-7 April 2009.
; 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.

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