CognTech = Cognition/Cognitive + Technology/Technologies
This website outlines the use of various computational tools (in terms of new interdisciplinary applications) to explore human cognitive functions, their neurobiological underpinnings, and artificial intelligent systems; as well as the building of novel computer programs; all for scientific research, educational purposes, open science, and potential commercial purposes.
Past and Present Works in Progress, and Future Works:
Cognitive & Psycho-Behavioural Functions with e-Science
The human mind is incredibly complex, but how can we understand it? Do electronic 'e-Science' computational tools help for this type of scientific research? And can recent theories of the mind help us understand ourselves and make sense of the data?
Psychological Experimental Stimuli: Building 2D & 3D naturalistic/dynamic digital simulations (e.g. using the Unity 3.0 engine) for animals/humans and A.I. agents. These use multi-sensory visual and auditory cues, to test for learning & memory components, spatial navigation, emotional processes, decision-making, meta-cognitive functions, etc., and their psychiatric equivalents.
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Reviewing and Coding/Building novel e-Apps (apps) (portable/mobile & desktop devices) (on Window OS, Android, internet browsers, etc) for human entertainment, education, scientific research, e-Health/m-Health, and general wellbeing.
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Administering novel cognitive stimuli and collecting human data. Using computer interaction (e.g. using PsychoJS/Pavlovia, Google Sites features, MS Forms, etc) to test human cognition.
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Exploring ways of combining experiments with oculomotor gaze tracking, biopsychometrics, and other measurements.
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e-Learning and Applied Cognitive Neuroscience
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Testing augmented reality (AR) apps in diverse real-world environments, and using virtual reality (VR).
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Artificial Intelligence
Fitting and modelling data to dynamic models (e.g. in Matlab) for psychology/psychiatry. (not necessarily AI)
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Building my own basic A.I. agents. Deep machine learning general-purpose A.I. (RL, etc) to model animal/human cognition (using tools such as Python-based modules, Matlab-based modules, etc).
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Applications of existing deep machine learning models (visual objection recognition, face processing, linguistic processing, sentiment analysis, etc). Here, pre-built and pre-trained algorithms (e.g. Tensorflow-based programs) are used with new stimuli.
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Models of Biological Neural Networks
Modelling networks of biological neurons with with artificial neural networks (in SimBrain 3.0, Emergent PDP++, and other simulators), in relation to cognitive paradigms and neural systems.
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Relating cognitive paradigms to computationally generated neural (e.g. BOLD signals, LFPs) data.
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Digitising Molecular & Cellular Neuroscience
Showcasing open-source computational tools (by other organisations) in genetics/genomics, bionanotech, pharmaco-tech, neuroinformatics, biochemistry and molecular neurobiology.
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A new personalised histological & neurohistological set-up to acquire new images and and creating a novel database.
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Organismal Neuroanatomy, Neurophysiology, Neuro-engineering
Analysing existing clinical and non-clinical (cognitive) neuroimaging (MRI, fMRI, EEG, MEG, ...) data from other experiments, using various software tools (Matlab-based and other).
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Using software that displays 2D/3D brains, for presentational purposes; and software for building/designing new ones (structural & functional) from bio-imaging data; for research & development, dissemination.
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Exploring the potential use and democratisation of non-invasive Brain-Machine Interfaces (Brain-Computer Interfaces) components.
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Working on prototypes in basic robotics and basic neuro-robotics.
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For Neurological & Neurophysiological Assessments , see section 'Other' at the end of Psychophysics Biophysiological Metrics .
Societal Systems
Exploring models that explore societal-wide macro-issues.
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Other General Domains
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Experimenting with 2D and 3D graphical data visualisation for ubiquitous applications in any type of data.
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Miscellaneous works in computing not specifically related to any of the above sections.
Promoting novel content in interdisciplinary science and neurosciences, via electronic learning tools and applied educational psychology; and furthering this process with web analytics. Also, engaging in open-source 'citizen science' (democratised research).
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Contributions to other projects that are external, but related, to CognTech/BioNeuroTech
