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