Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS)


Paul Verschure | Group Leader / ICREA Research Professor
Anna Mura | Senior Researcher
Riccardo Zucca | Postdoctoral Researcher
Maria Blancas Muñoz | PhD Student
Martina Maier | PhD Student
Giovanni Maffei | Research Assistant
Daniel Pacheco | Research Assistant
Diogo Pata Santos | Research Assistant
Sytse Baldwin Wierenga | Laboratory Technician

About

SPECS uses synthetic methods to study and synthesize the neuronal, psychological and behavioural principles underlying perception, emotion and cognition.

SPECS activities are organized around three complementary dimensions:

• Theory of mind and brain
• Biomimetic real-world artefacts
• Brain repair and quality of life technologies

SPECS is also very much involved in the development of scientific co-operation in the field of Biomimetics and Neurotechnology, as well as in Educational and Outreach activities.

Cognitive Systems Laboratory

The Cognitive Systems Laboratory is a multidisciplinary environment that supports research in the following areas:

  • Distributed Adaptive Control
  • Multi-robot exploration and coordination
  • Classical conditioning, operant conditioning and learning models based on the Distributed Adaptive Control framework, which has become a standard in the field of artificial intelligence and behavior based robotics (McFarland and Bosser, 1993; Hendriks-Jansen, 1996; Arkin, 1998; Pfeifer and Scheier, 1999; Clancey 1996; Cordeschi, 2002).

Robotic Systems Laboratory

The Robotic Systems Laboratory is a multidisciplinary environment that supports research in the following areas:

  • Classical conditioning, operant conditioning and learning models based on the Distributed Adaptive Control framework, which has become a standard in the field of artificial intelligence and behavior based robotics
  • Multi-robot exploration and coordination
  • Navigation in human and animal behavior
  • Implementation in robots of brain models of the hippocampus, cerebellum, talamus/cortex
  • Rule learning VR robots/avatars
  • Fast and reliable insect-based visual navigation models for flying vehicles
    Investigation of the neuronal substrates of chemical sensing and their application to odor discrimination and localization

Hybrid Systems laboratory (HLB)

The HLB is primary involved in the development, implementation and analysis of machine-brain-machine interfaces.
The interdisciplinary nature of the study of hybrid systems lies at the intersection of different research areas, namely:

  • computational neuroscience
  • electronics
  • robotics
  • artificial intelligence
  • neuromorphic engineering

The HLB was involved in the ReNaChip FP7 project, whose overarching goal is to build s neuroprosthetic neuromorphic chip recovering a learning function lost in the aged cerebellum.

Digital Heritage

By using advanced digital humanities technologies, and making it accessible online, we can conserve, develop and preserve the memory of Europe’s cultural heritage, and in particular the Holocaust, for future generations.

Existing memorial sites or museums offer a traditional historiographical approach. We propose to use virtual and augmented reality techniques to reconstruct sites of WW-II crimes and their interrelated structures. SPECS’s approach combines virtual and augmented reality with integrated databases of graphical reconstructions and historical sources to allow us to actively explore and try to comprehend the incomprehensible: the massive scale of the crimes Nazi Germany perpetrated on the world and the depth of the destruction and suffering it caused.

The SPECS research group has been pioneering this approach over the last 15 years and grounded it in its fundamental research in psychology and neuroscience. In close collaboration with the Bergen-Belsen memorial site and Prof. Habbo Knoch this paradigm has been elaborated to conserve and present the history of the Bergen Belsen concentration camp.

Educational Robotics

Technology evolves and advances faster then ever in all aspects of our society. Thus, it is important that the next generations of students learn as much as possible about emerging technology and stay competitive.

SPECS contributes to the education of the next genartions by combining platforms for training and outreach activities, facitlitating multidisciplinary education and innovation by sharing the value of convergent science, excellence and societal impact. We have developed Educational Robotics programs for students of primary and secondary school, as well as courses to train teachers and young adults.

Interaction Technology

There is a growing interest in understanding creativity from a more neuroscientific point of view, so to say, to disclose the neural basis of creativity we will need great insights on how the brain elaborates the process of human thought.

Our approach to understand the process of creativity is to use Art & Technology to create high impact, sophisticated man-machine interaction tools.

  • Narrative in interactive mixed reality environment
  • Multimedia installations: affect-based self-generated media content

Mixed-reality lab

The Mixed-reality lab serves a threefold research agenda:

  • Understand human behavior in a mixed-reality context
  • Build mixed-reality applications based on neurobiological understanding and methodologies see iqr and Brainx3
  • Test neurobiological models by deploying them in control of mixed-reality systems

Neuro-Rehabilitation

Over the past 15 years SPECS has been developing science-based technology tools to drive perceptual, cognitive, affective and motor systems of the brain to facilitate functional recovery after damage. By means of novel interaction paradigms such as Virtual Reality or music therapy, and based on the Distributed Adaptive Control theory of mind and brain DAC developed by Paul Verschure, SPECS studies the brain and the mechanisms underlying loss of function and its rehabilitation and recovery after stroke, and other brain diseases (see Verschure Conf Proc IEEE Eng Med Biol Soc. 2011, Mónica S. Cameirão et al. Restor Neurol Neurosci 2011 and Stroke 2012 )

Psychophysiology lab

The Psychophysiology lab studies how human react to various uni- and multisensory signals – visual, auditory and tactile stimuli. We assess human responses at different levels using subjective ratings, behavioral data, physiological and brain wave recordings. This data help us to understand human perception and cognition mechanisms, with particular stress on the novel methods for diagnosis and treatment of varios brain disorders (chronic pain, migraine, autism, depression, Alzheimer’s disease).

  • affective chronometry (such parameters as the rise time to peak and the recovery time of the emotional waveform)
  • multisensory perception (sound, vision, touch)
  • multisensory interactions for emotional stimuli (custom sound and video databases are created)
  • sonification of EEG signals
  • neurofeedback using mixed reality environments processing of eye-gaze in autistic children


News/Jobs

Nobel Laureate is special guest speaker at IBEC event
05/09/17

IBEC welcomed Prof. Edvard Moser, Nobel Prize in Medicine or Physiology 2014, as the keynote speaker in a special event to mark the move of ICREA professor and ERC grantee Prof. Paul Verschure to the institute.


New research group boosts neuroengineering focus at IBEC
03/07/17

The Institute for Bioengineering of Catalonia (IBEC) gains a world-renowned neuroscientist and psychologist with the move this week of ICREA professor Paul Verschure and his Synthetic Perceptive, Emotive and Cognitive Systems group (SPECS) from the Universitat Pompeu Fabra to the institute.


Projects

EU-funded projects
CDAC  The role of consciousness in adaptive behavior: A combined empirical, computational and robot based approach (2014-2019) ERC Advanced Grant Paul Verschure
iC-ACCESS  Accessing Campscapes: Inclusive Strategies for Using European Conflicted Heritage (2016-2019) HERA Joint Research Programme Uses of the Past, REFLECTIVE-1-2014 Paul Verschure
socSMCs  Socialising Sensori-Motor Contingencies (2015-2018) Future Emerging Technologies (FET), H2020 Paul Verschure
WYSIWYD  What You Say Is What You Did (2014-2017) FP7-ICT-2013-10, grant agreement n° 612139 Paul Verschure
EASEL  Expressive Agents for Symbiotic Education and Learning (2013-2017) FP7-ICT-2013-10, grant agreement n° 611971 Paul Verschure
CSNII  Convergent Science Network of Biomimetics and Neurotechnology (2013-2016) FP7-ICT-601167 Paul Verschure
National projects
DAC-CHM Distributed Adaptive Control of Consciousness in Humans and Machines Paul Verschure
INSOCO (2015-2018) Paul Verschure
SANaR Smart Autonomous Neuro-Rehabilitation System MINECO, Retos Investigación 2013 Paul Verschure
TECNIO (2016-2019) Generalitat of Catalonia Paul Verschure

Publications


Puigbò, J. Y., Maffei, G., Herreros, I., Ceresa, M., González Ballester, M. A., Verschure, P. F. M. J., (2017). Cholinergic behavior state-dependent mechanisms of neocortical gain control: A neurocomputational study Molecular Neurobiology in press

The embodied mammalian brain evolved to adapt to an only partially known and knowable world. The adaptive labeling of the world is critically dependent on the neocortex which in turn is modulated by a range of subcortical systems such as the thalamus, ventral striatum, and the amygdala. A particular case in point is the learning paradigm of classical conditioning where acquired representations of states of the world such as sounds and visual features are associated with predefined discrete behavioral responses such as eye blinks and freezing. Learning progresses in a very specific order, where the animal first identifies the features of the task that are predictive of a motivational state and then forms the association of the current sensory state with a particular action and shapes this action to the specific contingency. This adaptive feature selection has both attentional and memory components, i.e., a behaviorally relevant state must be detected while its representation must be stabilized to allow its interfacing to output systems. Here, we present a computational model of the neocortical systems that underlie this feature detection process and its state-dependent modulation mediated by the amygdala and its downstream target the nucleus basalis of Meynert. In particular, we analyze the role of different populations of inhibitory interneurons in the regulation of cortical activity and their state-dependent gating of sensory signals. In our model, we show that the neuromodulator acetylcholine (ACh), which is in turn under control of the amygdala, plays a distinct role in the dynamics of each population and their associated gating function serving the detection of novel sensory features not captured in the state of the network, facilitating the adjustment of cortical sensory representations and regulating the switching between modes of attention and learning.

Keywords: Acetylcholine, Inhibitory network, Neocortical circuits, Neuromodulation


Moulin-Frier, C., Fischer, T., Petit, M., Pointeau, G., Puigbo, J., Pattacini, U., Low, S. C., Camilleri, D., Nguyen, P., Hoffmann, M., Chang, H. J., Zambelli, M., Mealier, A., Damianou, A., Metta, G., Prescott, T. J., Demiris, Y., Dominey, P. F., Verschure, P. F. M. J., (2017). DAC-h3: A proactive robot cognitive architecture to acquire and express knowledge about the world and the self IEEE Transactions on Cognitive and Developmental Systems in press

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users.

Keywords: Autobiographical Memory., Biology, Cognition, Cognitive Robotics, Computer architecture, Distributed Adaptive Control, Grounding, Human-Robot Interaction, Humanoid robots, Robot sensing systems, Symbol Grounding


Santos-Pata, D., Zucca, R., Low, S. C., Verschure, P. F. M. J., (2017). Size matters: How scaling affects the interaction between grid and border cells Frontiers in Computational Neuroscience 11, Article 65

Many hippocampal cell types are characterized by a progressive increase in scale along the dorsal-to-ventral axis, such as in the cases of head-direction, grid and place cells. Also located in the medial entorhinal cortex (MEC), border cells would be expected to benefit from such scale modulations. However, this phenomenon has not been experimentally observed. Grid cells in the MEC of mammals integrate velocity related signals to map the environment with characteristic hexagonal tessellation patterns. Due to the noisy nature of these input signals, path integration processes tend to accumulate errors as animals explore the environment, leading to a loss of grid-like activity. It has been suggested that border-to-grid cells' associations minimize the accumulated grid cells' error when rodents explore enclosures. Thus, the border-grid interaction for error minimization is a suitable scenario to study the effects of border cell scaling within the context of spatial representation. In this study, we computationally address the question of (i) border cells' scale from the perspective of their role in maintaining the regularity of grid cells' firing fields, as well as (ii) what are the underlying mechanisms of grid-border associations relative to the scales of both grid and border cells. Our results suggest that for optimal contribution to grid cells' error minimization, border cells should express smaller firing fields relative to those of the associated grid cells, which is consistent with the hypothesis of border cells functioning as spatial anchoring signals.

Keywords: Border cells, Error minimization, Grid cells, Navigation, Path integration


Pacheco, D., Sánchez-Fibla, M., Duff, A., Verschure, P. F. M. J., (2017). A spatial-context effect in recognition memory Frontiers in Behavioral Neuroscience 11, Article 143

We designed a novel experiment to investigate the modulation of human recognition memory by environmental context. Human participants were asked to navigate through a four-arm Virtual Reality (VR) maze in order to find and memorize discrete items presented at specific locations in the environment. They were later on tested on their ability to recognize items as previously presented or new. By manipulating the spatial position of half of the studied items during the testing phase of our experiment, we could assess differences in performance related to the congruency of environmental information at encoding and retrieval. Our results revealed that spatial context had a significant effect on the quality of memory. In particular, we found that recognition performance was significantly better in trials in which contextual information was congruent as opposed to those in which it was different. Our results are in line with previous studies that have reported spatial-context effects in recognition memory, further characterizing their magnitude under ecologically valid experimental conditions.

Keywords: Context effects, Recognition memory, Spatial behavior, Spatial memory and navigation, Virtual reality



(See full publication list in ORCID)

Equipment

  • EXperience Induction Machine (XIM), an immersive room equipped with a number of sensors and effectors that has been constructed to conduct experiment in mixed-reality.
  • Robotics lab
  • Codi-Bot, the musical robot that teaches you how to program
  • iqr: simulator for large scale neural systems
  • Collective machine cognition: Autonomous dynamic mapping and planning using a hybrid team of aerial and ground based robots
  • Humanoid robots: iCub
  • Quality of Life technologies

Collaborations

In 2014, SPECS created the spin-off company “Eodyne“.

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