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Introduction
Introduction
I love learning new ideas and skills.
For the last 10 years, I have gained a much greater passion for a wide range of disciplines, but especially Clinical Neurological Sciences, and Cognitive & Behavioural Neurosciences – both of these subjects being very important to me, due to personal experiences I have gone through, and those are very empowering to learn about. Computational modelling of these is also a recent interest of mine.
For the next 20 years, I'm aiming to do postdoc work in Neurosciences (in London or elsewhere in the UK), and manage a range of globally-important projects at the highest level.
Main fields of interest
Main fields of interest
Neurosciences
• Neurosciences, from molecules to circuit to whole brains; and especially with regards to cognitive functions.
Medicine
• Helping to cure disorders and living a better life.... this is very personal to me and affects everyone directly and indirectly. I have had plenty of experience in the realm of clinical biomedicine.
• I am also interested in the need to revise entire healthcare systems and the culture of science, especially with mental health, as well as encompassing education (access to information, science education) as a key overlapping concept alongside healthcare.
• I also have an interest in evolutionary applications to medicine.
Computer Technology
• My experience with tech started a long time ago with video games (...), having played competitively (...). I have been doing some little engineering projects here and there since very young (...); since 2012, I became more interested in the state of the art in tech (including AI), and how tech can be used to enhance learning, remotely, and ultimately lead to various other applications....
• I am also keen on brain machine interfaces of all types.
'Interdisciplinarity'
• As with the above, an interdisciplinary mindset has been key to solving small problems in my day-to-day life, and tackling larger long-term problems alongside the help of other people.
• I am also interested in future investments, and being affiliated with companies/organisations that embellish that ethos as well.
Education
• I am very passionate about education, being a student myself and working in the FE/HE sector; as well as producing videos ('Scientifically Org'), and engaging in virtual worlds (as per 'CognTech', open science endeavours, etc).
Societal Impacts
• I have been involved in low-level activism in some capacity for over a decade in a multitude of projects; since 2018, I actively contributed to KCL's jobs as working on many topics related to the above.
• I am also interested in:
• Policy decisions in terms of modelling mathematically behavioural neuro-economics.
• Funding and furthering democratised Open Science.
• In particular, neuroscience-informed (or general-science-informed) policies, and the science of policy and legislative processes.
• Beliefs, and beliefs in beliefs.
Projects:
CCNBS Res Pub (TBC)
Data visualisation (TBC)
Past and current works, and ideas for future applications
Past and current works, and ideas for future applications
Projects - 2018/2019/2020/2021
*Note: If you are interested in sponsoring or funding my work, or working on collaborations, do get in touch with me (but I will only reply if I am able to as I am quite busy at the moment)
KCL-related
Work at KCL IoPPN in Neuroscience / Neuroimaging / Cognitive / Computational Neuroscience
https://www.researchgate.net/project/Kings-College-London-IoPPN-Neuroscience-MSc-2018-2019
https://www.linkedin.com/groups/13617079/
https://github.com/KCL-IoPPN-Neuroscience-MSc
KCL MSc Neuroscience 2018-2020
https://www.facebook.com/KCL-MSc-Neuroscience-2018-2020-103824254330938
https://www.facebook.com/groups/1485840941565408/
KCL IoPPN Postgraduates 2018-2020
https://www.facebook.com/KCL.IOPPN.Postgraduates.2018.2020/
https://www.facebook.com/groups/376186646612591/
MSc Neuroscience PT 2018-2020 - Google Drive
(Private)
For my MSc works: see the insert on other webpages and encrypted docs:
List of Assignments; PDF and figures of selected parts of MSc Works including;
Thesis, Lab-Book, Poster; {screenshots samples}.
BSc and MSc Theses (open-access brief versions - not full versions) :
Independent
My general work in Coding & Program Development, in Research, and in Computational Modelling of Neurobiological Systems.
( https://www.BioNeuroTech.com/ )
( harryfmuzart.wixsite.com/bioneurotech-x redirects to the above )
My general work in Coding & Program Development, in Research, and in Computational Modelling of Neurobiological Systems.
( https://www.Scientifically.Org.uk/ )
( harryfmuzart.wixsite.com/scientificallyorguk redirects to the above )
My Video Tutorials (on YouTube) and other e-Learning Resources in Interdisciplinary & Applied Sciences.
The three websites above partly operate under:
www.Multidisc-Neurosci-Tech-Ltd.com / .org
( http://www.Multidisc-Neurosci-Tech-Ltd.com )
( the above redirects to: https://sites.google.com/view/mul..........echltd/home )
My start-up company - products and services.
Some of my Scientific Research Interests for postgrad research
(Last Updated: Jan 2020)
Topics – Interdisciplinary/Multidisciplinary ; and Main Specialist Domains
■ Nervous System, Central NS / Brain
■ Organism : Human (rather than other animals).
■ Functions --- Sensorimotor, Cognitive & Behavioural ---
--- Learning & Memory, all types/systems; short-term/long-term. Episodic, and others.
--- Also: Sensory (mainly Vision, but also auditory and tactile); Visuo-Spatial; Emotion/Reward/Motivation, environmental drives; (top-down conscious) Decision & Action; Imagination & Innovative Thinking/Intellect; language, and other functions.
So I will choose one major (eg. xxxxxx), and other as minors; focus on one and still relate others/explore.
■ Mainly normal ‘healthy’ physiology , (but will also explore clinical aspects (diseases/disorders) as useful models)
■ Brain Structures --- (Bilateral) MTL(medial temporal lobe)/Hippocampus, connections with Visual Cortex (V1/4/5), Limbic/Amygdala/OFC, PFC (prefrontal cortex), Somatosensory & Somatomotor Cortex. Frontal Parietal Temporal Occipital, other, ..... Also association white matter tracts.
■ Scale Level ---
--- Some biochemical/molecular/cellular will be very relevant.
--- But mainly neural networks small-scale (10^2 neurons, 10^3 connections) to larger scale (10^9 neurons, 10^12 connections); Neural networks (from neuro-histology and computational modelling).
--- And some whole brain regions.
■ Anatomy & Physiology, rather than Development or Evolution.
■ Nervous System in adults (rather than infants/children or elderly senescence).
■ Experiment Techniques and Apparatus ---
Neuroimaging: high-resolution fMRI (& DTT?) and fMRI-related, combined with EEG-realated, (also maybe MEG).
Simultaneous or seperately.
All the gear, equipment, hardware and software involved.
(So many techniques…., I still need to look up these, and other techniques as well) (maybe TDCS stimulation?)
Also: Psychometric and Cognitive-Behavioural Tests. Use of 3D VR, use of computer-based visual simulations.
■ Neuroimaging: mainly applications of the technology, not necc develop the technology itself (hardware and software), but I could get into that.
■ All the above points, with an emphasis on Computational Modelling:
--- Data Analysis / statistical models
--- Computational Modelling / Virtual Simulations
--- Connectomics, Neurodynamics, Systems Neuro-computations
--- Biological/Artificial Neural Networks
--- Deep Machine Learning / Intelligent Algorithms
--- Big Data / Informatics
--- Python/Matlab/Other packages and associated developmental toolkits and application programming environments
--- (open-source e-projects collabs)
I may want to concentrate on that if there are issues with the main experimental techniques.
***
■ Implications / Translational Applications / Business Cases:
To justify external investments into my work. The research for my MSc/PhD I need to apply practically to aspect of real-life complex problems, and capitalise from those. From my research, predictions are made for market demands in 1/5/10/20 years in the future:
Neuroimaging and modelling neural networks and neurons.
--- Need not just better hardware and software (created by physicists/engineers, advised/motivated by clinical cases), but new innovative revolutionary techniques. Processing power & better machine learning algorithms for statistical analysis / interactive dynamic modelling.
--- Coping with extremely large datasets in neurobioinformatics.
--- Computer simulation models to save money in live experiments, pharmaco drug testing effects without animals, behavioural learning, etc
--- Connectivity analyses, tracts - Informing neurosurgery procedures.
--- Steps within visual system pathways
--- Reverse engineering simulated BOLD and other responses.
Neuroscience-inspired Artificial Intelligence:
--- Visual system and deep convolutional neural networks for object recognition: used in histology samples disease classification, brain scan imaging tumour detection, facial sentiment comprehension
--- Finding out what someone sees or thinks by only looking at neuroimaging data; reverse supervised learning trained and tested on new data.
--- Speech recognition (language). Human voice synthesis.
--- Realistic reconstruction in 3D of face/head from only 2D images at few angles, with no depth information. Then control of reconstructed avatar via live actions. Transposing aspects of one audio-video file to are place aspects of another completely different.
--- Bayesian inference over time.
--- 'Objects that sound'.
--- Reinforcement learning and curiosity-based exploration (executive episodic control) for long-term goal planning (in solving maze problems to superhuman level, and also any problem)
--- Sentiment analysis from speech content.
--- Pose estimation – visually-guided motor actions.
--- Novel creativity.
AI applications to:
--- Neuroscience
--- Healthcare, personalised (general practice, psychiatry, neuroimaging, pharmac, biomed sci)
--- Scientific/Medical Research
--- Communications/Marketting
--- Finance/Economics, stocks
--- Security & safety
--- intuitive experiences
--- Other
--- Everything…
Brain-Machine Interfaces (recordings) (non-invasive) (wireless/portable)
Device fits on scalp.
For clinical patients or normal people to enhance functions
eg. Amputees (robotic arm/hand controlled by muscle MEG, or nerve, or directly CNS ‘thought’/motor command)
Normal individual (virtual objects in a 3D computer simulations) – intense training is required for this.
Individual dual fMRI/MRI/EEG/MEG/fNIRS and visual screen VR senses.
--- Clinical Neurology (phantom limbs; motor rehabilitation following stroke)
--- Scientific research experiments (in cogn, neuro, comp)
--- Cognitive AI extension, internet, augmented reality glasses.
--- Educational
--- Entertainment (VR video gaming)
--- This could provide training for specialised professions, from a young age.. eg. Training simulations for distance surgery, distance pilot.
--- Neurofeedback learning process (conscious and unconscious)
--- Meditation, wellbeing, art, CBT, psychiatrics, addiction
--- Similar advances in 'portable MRI' and 'portable MEG' technology.
Robotics/Extended Self
--- Endoskeletons, exoskeletons – prevent injuries and enhance strength in manual labour work, people with paralysis.
--- Computational problem of human hand dexterity and facial expressions
--- Plasticity cognition. Create phantom limbs in non-amputees by long-term conditioning with mind-controlled bionic/prosthetic 6th hand digit or 3rd upper limb, and then removing it.
--- Sensory substitution. Convert any sensory modality to any other modality. (sound > visual (text/images). Visual to sound, sound or visual to touch – in real-time. Learning process). Multidimensional data Visual is limited by single bits of attention
Brain-machine interfaces (invasive) (wireless/portable)
--- Humans are currently large input and throughput for few bits of output (finger searching internet). Need BMI to maintain high-bandwidth output as speed of thought.
--- Predict epileptic seizures with ML and then reboot hippocampus just before.
--- Alzheimer’s/other neurodegen: emotional, memory, motor effects more in conscious control.
--- BMI with optional connection to external fixed computer interface – upload and download memories.
Brain-machine interfaces (stimulating) (non-invasive) (wireless/portable)
--- Neuro-stimulators for migraines?
--- Enhanced learning?
--- Testing motor and sensory research.?
Brain-machine interfaces (input-based) (invasive) (wireless/portable)
--- External TMS, TDCS, TACS, other, … too sparse. Need invasive multichannel electrode sheets.
--- Robotic arm that can feel (detect temperature, pressure, texture, vibrations; then feed to these signals to nerve tract to somatosensory cortical areas) – need sensory feedback for motor actions.
--- Phone app
Haptic feedback – touch
Neuro-addiction and behavioural neuro-economics of apps/stores, visual, sound, smell etc
Integration with advances in molecular/cellular engineering
--- Framework for optogenetics and in vivo channel stimul.
--- Integrative with in vitro artificial petri dish – development of neural networks from stem cells, then transplantation to spinal cord or damage area.
--- Stem cells and organoids in restoring CNS, eye and ear neural cells.
--- Synthetic grafts
--- Non-metallic, non-magnetic, biomaterials for cochlear implant.
--- Neural-like tissue engineering and immune-compatibility
--- Bionanotech chips or fluid nanomachines – blood brain barrier and into brain blood vessels
Motivations:
--- Solving complex problems: EEG source localisation, parametric morphometry, forward inference, backward inference.
--- Online digitised open-source home-based mobile DIY democratisation of these techs.
Code and data, 3D printing parts. Distance based research with participants/patients. Inc innovation rate (better product) and bring cost down.
Open access and open source publishing.
Peer-to-peer decentralised systems.
Personal labs.
Constant updates/downloads.
Customisable in indefinite ways.
Commercially affordable.
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