Computational Neurosciences

Employ applied mathematics to understand how the brain works.

ABOUT

The Computational Neuroscience group (CN group) was formed in 1996 with the aim to employ applied mathematics to understand how the brain works. The brain is a highly complex piece of biological machinery, compartmentalized into several subsystems and made up of hundreds of billions of cells each one of which can perform complex computations on the basis of which it influences several other cells. The mechanisms that underlie neural processes  (e.g., vision, learning, emotion, action, cognition) have been the object of intense enquiry for hundreds of years. Computational Neuroscientists strive to provide a description of the mechanisms that underlie such processes in the form of realistic models of the brain. Study of the properties and performance of these models allows one to evaluate the epistemic adequacy of available experimental data and the consistency of theoretical formulations. The CN group places particular emphasis on efforts to understand how the brain generates and controls purposeful movements such as orienting the eyes and the head towards objects, reaching for them with an arm and grasping them with an appropriately configured hand. What are the areas of the brain that participate in these processes and how do they generate the signals that control these actions? How are movement variables represented in the spatial and temporal properties of populations of neurons? How do the laws of physics, the geometry of objects manipulated and their mechanical properties influence command signals? To address questions such as these we collect experimental evidence concerning the movement related engagement of brain regions, the behavioral relevance of the discharge patterns of the neurons they contain, the connections they establish with other neurons and the psychophysics of movements generated when the relevant neural networks are activated or lesioned. Finally, we use computer assisted neuronal modeling to evaluate the epistemic adequacy of the data and the consistency of the models they motivate.

RESEARCH AND DEVELOPMENT ACTIVITIES

Neurophysiology of movement and action perception: Neural activity (spike trains and local field potentials) is recorded from animals trained to execute eye and arm movements and analyzed to gain insight into the movement variables coded by single neurons or populations of neurons. We aim to a) understand how the discharge pattern of neurons control the line of sight  and coordinated eye-hand movements, b) understand the neural basis of a fundamental human behavior, grasping, and object manipulation and c) decipher the neural mechanisms of social cognition


Our current efforts focus on:

  • disentangling the role of the dorsal and ventral premotor cortex in the control of hand-grasping actions, assess the intra- and inter-areal dynamics, and examine causal influences in the premotor grasping network.
  • revealing how the brain processes observed actions and the mechanisms whereby we assign meaning to others' actions by investigating the underlying neural dynamics at the micro-, meso-, and macroscopic scales.
  • developing decoders for the real-time control of a dexterous hand able to manipulate objects versatilely using neural signals recorded from the forelimb representations of the dorsal and ventral premotor cortical areas.

Neurophysiology of visual attention and memory: We record and analyze neural activity patterns at different spatial scales (single neurons, neuronal populations, neural networks, anatomically defined areas, distinct cortical layers) to reveal the neural code of cognitive variables in visual attention and working memory.

Our goals are:

  • to clarify how sensory, cognitive and behavioral parameters are represented in distributed patterns of activity across neuronal populations. We employ multi-electrode array recordings, machine-learning algorithms and dimensionality reduction approaches to decode task relevant information from population activity and infer the stationarity, sparsity and population dynamics of the neural code.
  • to elucidate the systems and circuit level mechanisms that underlie long-range communication and large-scale integration across distant brain areas. To this end, we use advanced signal processing methods to study the temporal dynamics of long-range interactions between neuronal populations in prefrontal and visual cortex and assess the functional and anatomical specificity of such interactions in order to reveal the circuit mechanisms of visual attention and working memory. Moreover, we infer directional and causal information flow between distinct network nodes using statistical measures of directional influences for continuous signals and point processes.
Brain imaging of observational learning and attribution of agency: The quantitative, autoradiographic 14C-deoxyglucose technique, image analysis, and two-dimensional reconstruction of the local cerebral glucose utilization is used to investigate: 1) cortical cerebral pathways associated with voluntary arm-reaching movements of monkeys executing learned visuo-skeletomotor tasks and the visual or somatosensory guidance of the arm, 2) cortical and subcortical regions, related to saccadic eye-movements in the monkey brain and how they encode parameters of saccades (direction, amplitude, eye-position and trajectory), 3) cortical areas involved in execution of grasping movements either guided by sensory stimuli or memorized and the observation of actions performed by others.
Neuroanatomy of the mesencephalon and the cerebral cortex: Immunohistochemistry, light/electron microscopy and extracellular tracer injections are used to study the synaptic organization of neural systems in the mammalian brain including cortical and subcortical oculomotor areas/nuclei, the neocortex and hippocampus.
Mathematical modelling of decision processes and central pattern generation: Computer simulations consistent with known anatomy, physiology, neurology and psychophysics are developed to understand the neural control of purposeful action. Decoding of behavioural parameters from activity patterns of neuronal populations using machine learning algorithms.

Computational Neurosciences

Employ applied mathematics to understand how the brain works.

RESEARCH AND DEVELOPMENT PROGRAMS

A. ONGOING PROJECTS

Title: Intra- and Inter-Areal Communication in Primate Brain Networks.
Funding Agency and funding scheme: European Union, H2020-MSCA-ITN-2020 (Marie Skłodowska-Curie Innovative Training Networks)
Duration: 03/2021-02/2025

Title: Micro-and mesoscopic study of neuronal interactions and network dynamics in cognition. The role of distinct prefrontal-temporal circuits in attention and memory.
Funding Agency and funding scheme: Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support faculty members and researchers and the procurement of high-cost research equipment”.
Duration: 20/08/2020-19/02/2024


B. COMPLETED PROJECTS

Title: Layer-specific characterization and modeling of fronto-parietal dynamics in primate cortical networks, Project number: Τ11ΕΡΑ4-00014, MIS: 5070462
Funding Agency and funding scheme: General Secretariat for Research and Technology, Greece, “Call for funding of research projects under the national action ERANETs 2019b - European R&Τ Cooperation – Funding of Greek Hosts that participated successfully in Common Calls to submit proposals in the European Networks ERANETs”.
Duration: 06/08/2020-05/08/2023

Title: Assigning Meaning to the Actions of Other Subjects: Neural Correlates.
Funding Agency and funding scheme: Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support faculty members and researchers and the procurement of high-cost research equipment”.
Duration: 2019-2023

Title: Decoding cognitive information from populations of neurons towards the development of a brain-machine interface.
Funding Agency and funding scheme: Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. research projects to support Postdoctoral Researchers”.
Duration: 2019-2023

Bridging neural activity and perception
Title: Bridging neural activity and perception: correlations and causality between activity of single neurons, neuronal populations, oscillatory dynamics and attentive behavior (2018 – 2019 & 2020-2021)
Funding Framework: Bodossakis Foundation – Research Grant in Biomedicine

Neural mechanisms of attention during visual search
Title: Neural mechanisms of attention during visual search (2015 - 2017)
Funding Framework: Fondation Sante, Research Grant in Biomedical Sciences

Title: Neural Mechanisms of Visual Search (2014 - 2016)
Funding Framework: ΑΡΙΣΤΕΙΑ ΙΙ, Ευρωπαϊκό Κοινωνικό Ταμείο και ΓΓΕΤ

Title: Mental Training in Artificial Agents (2014 - 2016)
Funding Framework: ΑΡΙΣΤΕΙΑ ΙΙ, Ευρωπαϊκό Κοινωνικό Ταμείο και ΓΓΕΤ

Title: Mental Simulation of Action (2014 - 2016)
Funding Framework: ΑΡΙΣΤΕΙΑ ΙΙ, Ευρωπαϊκό Κοινωνικό Ταμείο και ΓΓΕΤ

Title: Neurophysiology and modeling of action observation (2014 - 2015)
Funding Framework: Bilateral S&T Cooperation Program, GSRT

Title: Interactions between prefrontal cortex and area V4 in attention (2010 - 2013)
Funding Framework: EU/Marie Curie FP7-PEOPLE-2009-RG

Title: The role of parietal and prefrontal cortex in visual selection (2010 - 2013)
Funding Framework: Ενίσχυση Μεταδιδακτόρων, ΓΓΕΤ

Title: Attribution of action to the correct agent (2010 - 2013)
Funding Framework: Ενίσχυση Μεταδιδακτόρων, ΓΓΕΤ

PUBLICATIONS

  • 2023

    • F Balci, SB Hamed, T Boraud, S Bouret, T Brochier, C Brun, JY Cohen, E Coutureau, M Deffains, V Doyère, G Gregoriou, J Heimel, B Kilavik, D Lee, E Leuthardt, Z Mainen, M Mathis, I Monosov, J Naudé, A Orsborn, C Padoa-Schioppa, E Procyk, B Sabatini, J Sallet, C Sandi, J Schall, A Soltani, K Svoboda, CWilson, J Zimmermann (2023) A response to claims of emergent intelligence and sentience in a dish, Neuron 111 (5), 604-605
    • Theocharous A., Gregoriou G.G., Sapountzis P., Kontoyiannis I. (2023) Temporally Causal Discovery Tests for Discrete Time Series and Neural Spike Trains, arXiv preprint arXiv:2305.14131

  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014

PEOPLE

RESEARCHERS

TECHNICAL SCIENTISTS
  • Kephaloyianni, Maria, Technical Scientist
STUDENTS
  • Aliprantis Stamatios, PhD candidate
  • Caytan Emile, PhD candidate
  • Paneri Sofia, PhD Candidate
  • Sifaki Aikaterini, PhD Candidate
  • Theodorou, Irene, PhD candidate
  • Tzanou, Athanasia, PhD candidate

CONTACT US

For any information regarding the group please contact:

Computational Neurosciences Group,
Institute of Applied and Computational Mathematics,
Foundation for Research and Technology - Hellas
Nikolaou Plastira 100, Vassilika Vouton,
GR 700 13 Heraklion, Crete
GREECE

Tel: +30 2810 391800
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it. (Mrs. Maria Papadaki - secretary)

Tel.: +30 2810 391805
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it. (Mrs. Yiota Rigopoulou - secretary)