Winners of the 2020 Call for Research Projects
Bitbrain's mission is to boost real-world neurotechnology research and applications that enhance people's lives. For this reason, we opened a Call for Research Projects to support research teams that are exploring neuroscience in real-world settings.
A total of 236 teams submitted their proposals for the 2020 Call for Research Projects in the topics of human behavior (Topic 1) and brain-computer interface (Topic 2 ).
We have received many outstanding projects, which have made this call highly competitive leading to a 2.3% of acceptance rate. Due to the quality of the proposals, Bitbrain, Tobii Pro, and Psychology Software Tools increased the total amount of the sponsorship over 170K€, which allowed to fund a total of 6 projects that will start in 2021.
More information about the Call can be found here: https://www.bitbrain.com/call-for-projects-2020.
Topic 1 - Human Behavior Research
Research projects that expand the understanding of human behavior using multimodal approaches.
Practicing plasticity: How collective rituals promote neurocognitive flexibility
- Research team: Michael Lifshitz, Guillaume Dumas, Alexandre Lehmann, Samuel Veissière and Joshua Brahinsky.
- Research Institutions: Lady Davis Institute / McGill University, Montreal, Canada; University of Montreal, Montreal, Canada; Stanford University, Palo Alto, California, United States.
- Abstract: The ethnographic record suggests that collective rituals serve one of two key cultural functions. On the one hand, many rituals are designed to relax habitual constraints and open a space for novel patterns of thought and action to emerge. On the other hand, some rituals promote social conformity and uniformity of thought. Their proposed study will examine the relationship between intersubjective synchrony during collective rituals and the processes of flexibility or rigidity that emerge. Advances in mobile neuroimaging and computational neuroscience provide new tools for characterizing the brain states associated with ritual practices, which until recently have mostly evaded scientific study. They propose an onsite multimodal hyperscanning study to examine how two collective cultural rituals (charismatic prayer and jazz improvisation) induce a transient state of intersubjective synchrony, cognitive flexibility, and brain plasticity. The research team will compare these flexible rituals to rigid rituals from the same practice traditions: charismatic vs rehearsed prayer and improvised vs rehearsed jazz performance. They will predict that all of these rituals will promote intersubjective synchrony as measured by self-reports, EEG hyperscanning, and cardiovascular monitoring, but that only the flexible rituals will increase cognitive plasticity and brain entropy. This multimodal study will advance neuroscientific knowledge of real-world collective rituals.
Establishing Signatures of Mind Wandering in the Real World: A Multi-Modal Approach
- Research team: Julia W. Y. Kam and Robert T. Knight.
- Research Institutions: University of Calgary, Alberta, Canada; University of California, Berkeley, California, United States.
- Abstract: As you read a book, you may occasionally find yourself reminiscing your last summer vacation. This mind-wandering state is a prominent aspect of our everyday cognition that involves attending internally to cognitive processes such as autobiographical memory recall. It is often associated with maladaptive consequences such as performance deficits and negative affect.
Although it occupies up to half of our awake time in our daily life, the signatures of mind wandering in real-world settings remain largely unknown. To that end, the current proposal seeks to identify the behavioral, oculometry, and electroencephalography signatures of mind wandering in ecological settings. In two experiments, the aim is to reveal features that are observed within and across individuals. Together, these two experiments promise to establish the behavioral and neural signatures of mind wandering in real-world settings at the individual and group level. In particular, this project would reveal the potential differences in mind wandering signatures between in-lab and ecological settings, and underscore the importance of acknowledging individual differences in signatures of mind wandering. The research team envisions that these rich datasets can be subsequently used to predict mind wandering via machine learning analyses, which may ultimately drive the development of tools that optimize attentional control. Their findings have important implications for society at large, in particular for situations (e.g. air traffic controllers monitoring airspace; students attending lectures) in which the automatic detection of mind wandering in real-time can prevent undesirable outcomes.
Context-dependent predictive gaze in natural behaviors
- Research team: Neerav Goswami and Leslie C Osborne.
- Research institutions: Graduate Program in Biomedical Engineering, Duke University, Durham NC, United States; Department of Neurobiology, Duke University, Durham NC, United States.
- Abstract: Here the research team proposes to advance human behavior research by quantifying the efficiency and timescales of prediction in human eye movements during visuomotor tasks. Using a combination of eye-tracking and EEG technology, they will measure the mutual information between current eye position and future eye or target position as a function of temporal delay. By comparing predictive gaze to how predictive the target is of its own future movements, it can be quantified the efficiency of human prediction over time scales of around 10 sec. The team will begin with subjects playing a Pong-like video game where optimal prediction can be precisely computed. The team then proposes to leverage this approach to study predictive gaze in freely moving subjects engaged in everyday activities where we will quantify the predictive information in gaze about future eye movements without reference to an explicit target. This will be a transformative yet achievable series of experiments that combine Bitbrain and Tobii Pro technologies with the experience of the research team in information theory-based behavioral analysis to advance understanding of human behaviors in natural environments.
Topic 2: Brain-computer interface
Research projects that expand the introduction or usage of brain-computer interfaces.
Predicting neuropathic pain episodes in spinal cord injury patients through BCI
- Research team: Carmen Carrasco-López, Dario Salvi, Carl Magnus Olsson, Vanesa Soto-León, and Antonio Oliviero.
- Research Institutions: IoTap, Malmö University, Sweden; FENNSI group, National Hospital for Paraplegics, Spain.
- Abstract: Neuropathic pain (NP) is a common symptom arising as a direct consequence of a lesion or disease affecting the somatosensory system, often the case in patients with spinal cord injury. The traditional treatment of NP patients is conservative pharmacological therapy before interventional strategies. However, current first-line drug treatments have shown modest efficacy in pain relief. In this project, the research team will employ state-of-the-art digital health technology (a portable EEG and a smartphone app) to collect data from spinal cord injury patients. Home-based EEG recording and analysis of pain episodes features will allow us to better understand NP. Altogether, this project will help improve the quality of life of spinal cord injury patients with NP.
B2B: Brain-to-Brain Connectivity for the Real-time Monitoring of Social Interactions
- Research team: Laura Astolfi, Jlenia Toppi, Maria Grazia Puxeddu, Febo Cincotti, Donatella Mattia.
- Research Institutions: Dept of Computer, Control and Management Engineering, Sapienza University of Rome, Italy; IRCCS Fondazione Santa Lucia, Rome, Italy.
- Abstract: The aim of this EEG hyperscanning project is to provide a tool for the real-time monitoring of neurophysiological correlates of the reciprocal adaptation between two individuals during social interaction. The team aims to overcome current methodological limitations that hinder the investigation of multi-subject models on short time segments, by means of penalized regression techniques applied to Vector Autoregressive models. If successful, this project will permit to study social interactions by allowing the analysis in conditions of data paucity, thus expanding the understanding of human behavior in ecological and natural conditions.
CyberBrain: Cybersecurity in BCI for Advanced Driver Assistance
- Research team: Enrique Tomás Martínez Beltrán, Mario Quiles Pérez, Sergio López Bernal, Alberto Huertas Celdrán and Gregorio Martínez Pérez.
- Research Institutions: University of Murcia, Murcia, Spain; Waterford Institute of Technology, Waterford, Ireland; University of Zurich, Zurich, Switzerland.
- Abstract: Cybersecurity in BCI has barely been studied in the literature, counting only with few and limited works implementing proofs of concept in marginal scenarios. Based on that, the main objective of CyberBrain is to design and implement a framework able to detect cyberattacks affecting the BCI lifecycle while using Bitbrain products. After analyzing the BCI and Bitbrain vulnerabilities and proposing a list of countermeasures, CyberBrain will design and deploy a set of cyberattacks targeting three challenging use cases that integrate Bitbrain products with an advanced driver assistance scenario. The cyberattacks impact will be measured by the framework through a set of metrics defined during the project and provided as an outcome of CyberBrain. Finally, the previous contributions and additional private and public documents, paper, software, and videos will benefit Bitbrain and the BCI community, respectively.
- Check out this article to know more details about the CyberBrain Project.