BCBT is project oriented

A significant amount of time will be dedicated to applying the knowledge acquired during the school - and hopefully before - to realize pilot studies using different tools and technologies. All registered students will work in small teams - including other participants - to complete a project by the end of the school. Projects can be chosen from a list of predefined projects (see pdf below) or proposals can be made on the first day of the school. Everybody is invited to bring their own equipment and tools. These projects are supposed to be realizing new ideas and not to be a continuation of work already performed.
BCBT Awards: BCBT will award a prize for the best projects.




Implicit motor learning, like adaptation to visuomotor rotation, seems to be resilient to explicit cognitive strategies, when the visual feedback mismatches with the planned motor command (Mazzoni & Krakauer 2006).  This finding confirms the strong influence of visual feedback on unconscious processes. The Rehabilitation Gaming System (RGS), a VR-based rehabilitation tool that integrates a paradigm of action execution and action observation, allows the user to control a virtual avatar seen from a first-person perspective in a virtual environment. By manipulating the mapping between the patients real and virtual arm the system aims to positively reinforce the usage of the affected limb and therefore induce implicit motor learning.
Although builds on a large body of studies confirming that ownership can be induced through presentation of virtual limbs, the assumption that this is superior to simple cursor representation in motor learning has never been tested. We therefore want to investigate the difference between observing virtual limbs versus observing a cursor by designing a virtual reality task that requires subjects to explicitly adapt their motor behavior to a perturbation. We will use an optical pen for accurate movement measurements. We expect to see that the visibility of virtual limbs fosters implicit learning more than the visibility of only a cursor representation of the limb, making it resilient to cognitive strategies.


Mazzoni, P., Krakauer, J. W., (2006). An implicit plan overrides an explicit strategy during visuomotor adaptation. The Journal of Neuroscience, 26(14), 3642-3645

- Design experimental protocol
- Design a simple virtual reality scenario
- Run experiments with subjects
- Data analysis

KNOWLEDGE: statistical analysis Basic C# is a plus Basic knowledge about Unity 3D is a plus
SUPERVISORS: Belén Rubio, Klaudia Grechuta, Martina Maier



Intelligent artifacts and robots are expected to operate in complex physical and social environments. Whereas robots are slowly but surely being readied for the physical world, the social world is still at the horizon. The deployment of service and companion robots, however, requires that humans and robots do can understand each other and can communicate.
During BCBT this year, members of the WYSIWYD European project ( will advance the transparency of HRI by building on an advanced and recently developed paradigm comprising a humanoid robot iCub, a European standard platform for humanoid robotics (Metta, Sandini et al. 2008) and a tangible table top interface system (the ReacTable (Jorda, Kaltenbrunner et al. 2005)), that allows to exercise various levels of interaction between human users and a humanoid robot. The integration of the different components of the WYSIWYD project is based on the Distributed Adaptive Control (DAC) theory of mind, brain and behaviour (Verschure 2012).
Students motivated to participate in this adventure during the summer school are encouraged to enter in contact with members of the WYSIWYD team to define a project together.

Metta, G., G. Sandini, et al. (2008). The iCub humanoid robot: an open platform for research in embodied cognition. Proceedings of the 8th workshop on performance metrics for intelligent systems, ACM.
Jorda, S., M. Kaltenbrunner, et al. (2005). The reactable. Proceedings of the international computer music conference (ICMC 2005), Barcelona, Spain.
Verschure, P. F. M. J. (2012). "The Distributed Adaptive Control Theory of the Mind, Brain, Body Nexus." Biologically Inspired Cognitive Architecture - BICA

TASK: This will have to be defined from the respective interests of the student and the WYSIWYD team. Possible tasks include: attention selection, action recognition, behavior regulation, expression recognition.
KNOWLEDGE: Good practical knowledge in C++. Basic knowledge about YARP is a plus. Basic knowledge about iCub is a plus.
The WYSIWYD team, including Clément Moulin-Frier and Jordi Puigbò from SPECS@UPF.


One of the key challenges of affective computing is to extend the expression of emotion to machines. Recent technological improvements in virtual reality systems and wearable devices are leading to a gradual shift in research towards natural-world experimental settings. This is precisely why we built the eXperience Induction Machine (XIM), an immersive space specifically designed to conduct ecologically-valid experiments using virtual and mixed reality. Using XIM we will design and implement a case scenario with the goal of investigating emotion in life-like contexts that go beyond standard laboratory setups, while, at the same time, maintaining a high degree of control over the measured variables.

- Inference of human affective states from psychophysiological measurements extracted under ecologically valid conditions:
- Non-anthropomorphic Expression of Affective States through Parametrized Abstract Motifs
"The affective slider" (the manuscript will be provided by the supervisor)

TASKS: 1) Research on the state of the art in the field. Generation of an hypothesis grounded on the existing literature. 2) Design and implementation of an experimental setup 4) Conduction of an empirical validation.
KNOWLEDGE: Basic programming skills. Knowledge of MATLAB or R is strongly recommended. Basic knowledge of statistics.
KEYWORDS: XIM, emotions, measure, affective states, mixed reality, virtual reality
CONTACT: Alberto Betella



Rate remapping is a neuronal code that enables hippocampal place cells to encode spatial and sensory inputs conjunctively. Remapping has been hypothesised to be a mechanism for pattern separation (Colgin et al, 2008), a fundamental neuronal process for the differentiation of similar memories.
A key hypothesis that follows is that remapped representations should be associated with different memories and therefore detectable changes behaviour in memory tasks.
Studies with rodents have shown that spatial memory decreases after experiencing remapping (Jeffery et al. 2003, Lenck-Santini, P.P. et al. 2002, Lenck-Santini, P.P. et al. 2001).
Is human spatial behaviour affected in the same way? Can we manipulate spatial cues using VR and detect changes in spatial memory performance that are coherent with the changes in neural coding reported in the literature?
We designed a modified version of the traditional Water Morris task, to evaluate how progressive modifications environmental cues may affect episodic memory in humans.

Colgin, L. L., Moser, E. I., & Moser, M. B. (2008). Understanding memory through hippocampal remapping. Trends in neurosciences, 31(9), 469-477.
Colgin, L. L., Leutgeb, S., Jezek, K., Leutgeb, J. K., Moser, E. I., McNaughton, B. L., & Moser, M. B. (2010). Attractor-map versus autoassociation based attractor dynamics in the hippocampal network. Journal of neurophysiology, 104(1), 35-50.
Anderson, M. I., & Jeffery, K. J. (2003). Heterogeneous modulation of place cell firing by changes in context. The Journal of neuroscience, 23(26), 8827-8835.
Lenck-Santini, P.P. et al. (2002) Relationships between place cell firing fields and navigational decisions by rats. J. Neurosci. 22, 9035–9047
Lenck-Santini, P.P. et al. (2001) Evidence for a relationship between place-cell spatial firing and spatial memory performance. Hippocampus 11, 377–390
Kubie, J.L. et al. (2007) Changes in goal selection induced by cue conflicts are in register with predictions from changes in place cell field locations. Behav. Neurosci. 121, 751–763

- Design a VR application to test the effect of small morphs in the environment on the spatial behaviour of participants.
- Record navigation information (position, orientation, timings), as well as users responses to memory tests.
- Statistical analysis of the data and presentation of the results.
KNOWLEDGE: Episodic Memory / Hippocampus Literature, Spatial Navigation, Programming skills (C#, Javascript) is a plus.
SUPERVISOR: Daniel Pacheco // Monica Sanchez / Martí Sanchez-Fibla


The current field of neuroscience has seen an explosion of raw data production. With whole-brain modeling capturing many aspects of multi-scale processes in the brain, overwhelming amounts of data in the order of terabytes or greater are gathered, bringing new challenges such as how to analyse or processes this sort of data. One solution has been the development of the Brain X3 platform (Arsiwalla et al., 2015a). BrainX3 is a large-scale simulation of the human brain with real-time interaction, rendered in 3D in a virtual reality environment. In addition to the structural model of the brain (e.g., the connectome), a semantic layer (e.g., the semantome) was added (Arsiwalla et al. 2015b). Using a database of available information on brain regions, functions and disease, we can now present targeted and relevant information while interacting with the connectome model.  Being only recently developed, many improvement to the system can be made. This project focusses on improving the connectome-semantomic interaction, answering questions such as: (i) What information should we present? (ii) What is the best format of delivery? (iii) How do we maintain an accurate and up-to-date database? (iv) What other features could improve the agent’s interaction with the system?

- Arsiwalla, X. D., Zucca, R., Betella, A., Martinez, E., Dalmazzo, D., Omedas, P., & Verschure, P. F. (2015a).
Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction. Frontiers in neuroinformatics, 9.
- Arsiwalla, X. D., Dalmazzo, D., Zucca, R., Betella, A., Brandi, S., Martinez, E., ... & Verschure, P. (2015b).
Connectomics to Semantomics: Addressing the Brain's Big Data Challenge. Procedia Computer Science, 53, 48-55.

TASKS: Improve current link between connectomics and semantomics. Add new features to improve brain X3 tool in XIM. Design experiment to test effectiveness of functionalities.
KNOWLEDGE: Understanding and experience with R/Matlab. Statistical analysis. Experience with computational modeling is a plus.
SUPERVISORS: Xerxes Arsiwalla, Riccardo Zucca & Joeri van Wijngaarden



Smartphones and tablets have become very common in our daily life and in educational settings. Hand-held devices can do nearly anything a computer can do and are relatively cheap. Naturally, people from the field of education saw great potential in these devices, as they provide many benefits (accessibility, mobility, creativity, interactivity, etc) and they seem very promising (Dwyer et al, 1995). Using hand-held devices may therefore contribute to aid students during the learning process.  The purpose of this project is to examine the usage of the so called “EASELscope”, a hand-held device that will act as a tool to aid kids to learn the set of rules behind the classic balance beam task (Piaget, as cited in Schapiro, 2009). Following the concept of inquired based learning and self-determination, we suggest that learning environments should provide the students the possibility to request help as needed. On demand help provides the possibility for individualized learning and allows learning to become an active process in which students practice self-paced knowledge acquisition. Here we aim at exploring different ways of presenting information (solutions, hints, etc) and whether self-requesting help or automatically provided help improves the performance in solving the task while enhances knowledge understanding.

- Dwyer, Dan, Kathy Barbieri, and Helen M. Doerr. "Creating a virtual classroom for interactive education on the web." Computer Networks and ISDN Systems 27.6 (1995): 897-904. APA
- Schapiro, A. C., & McClelland, J. L. (2009). A connectionist model of a continuous developmental transition in the balance scale task. Cognition, 110(3), 395-411.

- Design the experimental protocol
- Implementation of a simple educational task on a hand held device
- Run a pilot experiment with subjects
- Data analysis

KEYWORDS: education, human-robot interaction, adaptation, learning mechanisms
REQUIREMENTS: interest in educational methods and augmented/virtual reality, programming skills (Unity and hand-held devices programming), data analysis.
SUPERVISOR: Vicky Vouloutsi, Maria Blancas, Riccardo Zucca



Perception of very simple stimuli, such as lines with different orientation was traditionally believed to happen in early stages of visual processing. These early stages were proposed to operate independently and often without involvement of higher cognitive processes such as attention, expectations or memory. To this day the relationship between the lower- perceptual and higher – cognitive information processing in the visual system is not yet understood. Certain evidence, coming from blindsight sight or hemineglect studies suggest the independence of two processes (Leopold, 2012). Other theories, for example predictive coding view suggest that higher-level cognitive processes, such as expectation, determine perceptual processing (Friston et al, 2012). The effects on neural correlates of perception proposed by this view, i.e. silencing of low-level neural responses by higher-level influences (for example in priming) are often reversed when selective visual attention is involved (Kok et al, 2012). In this study we will investigate the relation between attention and expectation in a psychophysical task, to determine how different top-down signals affect bottom up perceptual processes. The experimental protocol will be replicated from a previous fMRI study (Kok et al, 2012)in order to contrast the result with a sample of hemineglect patients. During BCBT we will add to the fMRI results our eye tracking measures and prepare the setup for a hemineglect replication study.


- Friston, K., Adams, R. a, Perrinet, L., & Breakspear, M. (2012). Perceptions as hypotheses: saccades as experiments. Frontiers in Psychology, 3(May), 151.
- Leopold, D. A. (2012). Primary Visual Cortex : Awareness and Blindsight, Annual Review of Neuroscience, 35, 91–109. doi:10.1146/annurev-neuro-062111-150356
- Kok, P., Rahnev, D., Jehee, J. F. M., Lau, H. C., & de Lange, F. P. (2012). Attention reverses the effect of prediction in silencing sensory signals. Cerebral Cortex, 22(9), 2197–206.

TASKS: Experiment design and setup, Eyetracking and experimental data analysis,
SKILLS: Experiment Design (Matlab – psychotoolbox,) Eye Tracking software (Python), Data analysis (Python or Matlab)
SUPERVISOR: Ryszard Cetnarski, Laura Serra-Oliva



Anticipatory postural adjustments are predictive movements or changes in posture that aim at facilitating maintaining body equilibrium in face of predictable disturbances. In this project we aim to use our custom made self-balancing robot #1 and perturbator® to test a combined anticipatory/compensatory architecture.
The architecture incorporates adaptive modules, that with decorrelation/Widrow-Hoff learning acquire are able to iteratively learn a given target function. Such modules can be regarded as high-level abstractions of the cerebellar circuitry. We have already shown that such architecture allows the robot to acquire anticipatory responses that allow reducing the error in performance induced by a predictable disturbance (namely, being hit with a weight). Now we want to study how different architectures are more or less robust in face of changes on the plant dynamics. That is, how well a previously acquired anticipatory response generalizes once the properties of the controlled object change.

TASKS: The basic task in this project is to test the robustness of the anticipatory responses in face of a perturbation of the plant dynamics (e.g., adding a extra-weigth to the robot can be a possibility). For this the students are expected to translate into the real-robot results that have already been advanced in simulations.

KNOWLEDGE: Python, Arduino.
SUPERVISORS: Ivan Herreros, Martí Sanchez, Giovanni Maffei
STUDENTS: Maximilian Ruck