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BICS 2018 : The 9th International Conference on Brain Inspired Cognitive System


Conference Series : Brain Inspired Cognitive Systems
When Jul 7, 2018 - Jul 8, 2018
Where Xi'an China
Submission Deadline May 10, 2018
Notification Due May 31, 2018
Final Version Due Jun 10, 2018
Categories    biologically inspired systems   cognitive neuroscience   models of consciousness   neural computation

Call For Papers

Topics of interest for submission include, but are not limited to:

Biologically Inspired Systems (BICS-BIS):
Brain inspired systems
Brain inspired vision
Brain inspired audition and sound processing
Brain inspired other sensory modalities
Brain inspired motion processing
Brain inspired robotics
Brain inspired adaptive and control systems
Brain inspired evolutionary systems
Brain inspired oscillatory systems
Brain inspired signal processing
Brain inspired learning
Neuromorphic systems

Cognitive Neuroscience (BICS-CNS):
Cognitive neuroscience
Cognitive neuroscience of vision
Cognitive neuroscience of non-vision sensory modalities
Cognitive neuroscience of volition
Systems neuroscience
Attentional mechanisms
Affective systems
Cortical models
Sub-cortical models
Cerebellar models
Neural correlates

Models of Consciousness (BICS-MoC):
World awareness
Global workspace theory
Qualia models
Virtual machine approaches
Formal models fo consciousness
Control theoretical models
Developmental/Infant models
Will and volition
Emotion and affect
Philosophical implications
Neurophysiological grounding
Enactive approaches
Analyitic/Synthetic phenomenology

Neural Computation (BICS-NC):
Neuro-computational systems
Hybrid neural systems
Neural learning
Neural control systems
Neural signal processing
Architectures of neural computation
Neural devices
Neural perception and pattern classifiers
Neuro-fuzzy systems
Evolutionary neural networks
Biological neural network models

We also have an IEEE BDB Competition
The IEEE Brain Initiative has sponsored several challenges and competitions during 2017 to analyse a range of brain/neuro datasets. The first IEEE Brain Data Bank (BDB) Challenge was held in June at St. Petersburg, as part of the IEEE SPCN 2017 Symposium ( Other challenges were held in Glasgow, Scotland, October 31, 2017, during the IEEE SENSORS Conference (, followed by the IEEE BDB Competition in Boston, USA, December 9, 2017 (

Following the success of BDB Challenges in 2017, there are new activities planned in 2018. Apart from last year’s global events, the BDB will be held for the first time in China in July 2018, in conjunction with the 9th International Brain-Inspired Cognitive Systems (BICS) Conference. You are cordially invited to participate in the Xi’an competition, and to exercise your curiosity and creativity to make sense of your chosen datasets (see details on our website:

Entries will be judged in three categories:

Data analysis including well-justified, innovative, and rigorous methodologies
Data visualization including novel, highly informative, and aesthetically appealing visualization techniques
Presentation and interpretation of findings including clear, informative delivery and compelling investigation and interpretation

There will be 3 awards given:
1st place: $600-$1000.00
2nd place: $400-$500.00
3rd place: $200-$300.00

Related Resources

12th IEEE MCSOC 2018   IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC-2018)
BICA 2018   Ninth Annual International Conference on Biologically Inspired Cognitive Architectures
NLPCS 2018   13th International Workshop on Natural Language Processing and Cognitive Science
BRAIN 2018   BRAIN : Broad Research in Artificial Intelligence and Neuroscience
ICONIP 2018   25th International Conference on Neural Information Processing
Brain Stimulation 2019   3rd International Brain Stimulation Conference
ICCC 2018   The 2018 International Conference on Cognitive Computing
SCSSS 2018   6th Scandinavian Conference System and Software Safety
BI 2018   The 11th International Conference on Brain Informatics
NICDL 2018   Nature-Inspired Computation in Data Mining and Machine Learning