The 2018 International Conference on Brain Informatics (BI 2018)

BI’18 Tracks and Topics


Track 1: Cognitive and Computational Foundations of Brain Science

  • Brain dynamics
  • Structural and functional connectome
  • Neural foundations of intelligent behavior
  • Learning mechanisms (e.g., stability, personalized user/student models)
  • Multi-perception mechanisms and visual, auditory, and tactile information processing
  • Reasoning mechanisms (e.g., principles of deductive/inductive reasoning, common-sense reasoning, decision making, and problem solving)
  • Neural basis of decision-making
  • Models of executive function & prefrontal cortex
  • Higher-order cognitive functions and their relationships
  • Adaptation and self-organization
  • Digital, data, and computational brain
  • Methodologies for systematic design of cognitive experiments
  • Neuroeconomics and neuromarketing
  • Neuroeducation, neurolinguistics, and neuroinstrumentation

Track 2: Investigations of Human Information Processing Systems (HIPS)

  • Bayesian models of the brain, and causal modeling of behaviour for neurology
  • Cognitive architectures and their relations to fMRI/EEG/MEG
  • Computational mechanisms of learning and memory
  • Computational models of sensory-motor control
  • Conscious mental functions and subconscious information processing
  • Emotion, heuristic search, information granularity, and autonomy related issues in reasoning and problem solving
  • HIPS complex systems
  • Investigating spatiotemporal characteristics and flow in HIPS and the related neural structures and neurobiological process
  • Modeling brain information processing mechanisms (e.g., information organization, neuro mechanism, mathematical, cognitive and computational models of HIPS)
  • Social brain communication

Track 3: Brain Big Data Analytics, Curation and Management

  • Big-neuron, neuron morphology and neuron reconstruction
  • Brain data collection, pre-processing, management, and analysis methodologies
  • Brain connectome, functional connectivity, and multi-level brain networks
  • Brain data grids and brain research support services
  • Brain informatics provenances
  • Brain mapping and visualization
  • Cyber-individuals and individual differences
  • Data brain modeling and formal conceptual models of brain data
  • Databasing the brain, curating big data, and constructing brain data centers
  • Development of data-driven markers of diseases, and behavioral biomarkers of neurological diseases
  • fMRI and PET imaging registration and analysis
  • Information technologies for simulating brain data
  • Integrating multiple forms of brain big data obtained from atomic and molecular levels to the entire brain
  • Knowledge representation and discovery in neuroimaging
  • Large scale models and simulation of brains
  • Machine learning algorithms for brain data analysis
  • Measuring scale thresholds of brain big data
  • Multi-aspect analysis in fMRI/DTI/EEG/ERP/MEG/PET/Eye-tracking data
  • Multimedia brain data mining and reasoning
  • Multimodal and combinatorial fusion for brain informatics
  • Optogenetics and in-vivo cell imaging analytics
  • Real-time fMRI and neurofeedback
  • Remote neurological assessment
  • Semantic technology for brain data integration
  • Simulating and analyzing spatiotemporal structure, characteristics and flows in HIPS and neural data
  • Statistical analysis and pattern recognition in neuroimaging
  • Cloud and semantic brain data services

Track 4: Informatics Paradigms for Brain and Mental Health Research

  • e-Science, e-Health, and e-Medicine
  • Mental healthcare knowledge abstraction, classification, representation, and summarization
  • Mental healthcare knowledge computerization, execution, inference, and management
  • Mental health risk evaluation and modeling
  • Personal, wearable, ubiquitous, micro and nano devices for mental healthcare
  • Remote neurological assessment
  • Social networks, social media, and e-learning for spreading mental health awareness
  • WaaS (Wisdom as a Service) and active services for mental healthcare
  • Computational approaches to rehabilitation
  • Computational intelligence methodologies for mental healthcare
  • Computational psychiatry
  • Brain repair models and stimulations
  • Clinical diagnosis and pathology of brain and mind/mental-related diseases (e.g., mild cognitive impairment, alzheimers, dementia & neuro-degeneration, depression, epilepsy, autism, Parkinson’s disease, and cerebral palsy)

Track 5: Brain-Machine Intelligence and Brain-Inspired Computing

  • Brain-inspired artificial intelligence
  • Brain-inspired cognitive computation and modeling
  • Brain-inspired artificial neural networks
  • Brain-inspired information processing
  • Brain-inspired evolutionary systems
  • Brain-inspired machine learning
  • Brain-inspired / cognitive neuro robotics
  • Brain-inspired / neuromorphic computing
  • Affective computing and applications
  • Brain-computer interaction and brain-robot interaction
  • Brains connecting to the internet of things