Neurotechnology Webinar Series: Dementia Biodesign

www.ktn-uk.org
Neurotechnology for Dementia
16th September 2020

Webinar Protocol
Due to the large number of people registered all participants will be muted.
If you have any technical problems, please use the chat box to seek advice
from the host (Poonam Phull).
Questions and Answers – Please use the Q&A box to type in your questions
to the presenters during or after the presentation. (Do not use this for
technical problems).
PLEASE NOTE – THE WEBINAR IS BEING RECORDED
The recording will be made available via the KTN website

Agenda
10:00 Welcome and introduction
Dr Charlie Winkworth-Smith, KTN
10:10 Introduction to UK Dementia Research Institute
Prof Paul Matthews, Imperial College London
Q&A
10:30 A clinician’s perspective
Dr Richard Perry, Imperial College Healthcare NHS Trust
Q&A
10:50 Wearable technology as a clinical tool for dementia: from research to practice
Dr Riona McArdle, Newcastle University
Q&A
11:10 In-home measurement of cognitive performance in healthy ageing
Dr Brian Murphy, BrainWaveBank
Q&A
11:30 Panel discussion

The KTN’s Neurotechnology Innovation Newtork
Aims
• Bring together the neurotechnology community in the UK
• Accelerate commercialisation though cross-sector collaboration
• Raise awareness – government and investors
Please get in contact:
charlie.winkworth-smith@ktn-uk.org

Upcoming webinars
4. Neurotechnology Capabilities – 13th October
• The Henry Royce Institute
• The Centre for Process Innovation
• The Manufacture of Active Implant and Surgical Instruments
(MAISI) facility
5. Quantum magnetic sensors for brain imaging - 12th November

©KTN All rights reserved | www.ktn-uk.org
Thank you!
charlie.winkworth-smith@ktn-uk.org
Neurotechnology Innovation Network

ukdri.ac.uk
@UKDRI
An introduction to the UK Dementia
Research Institute
Paul Matthews, MD, D Phil, FMedSci
UK DRI Centre at Imperial College London

The “pandemic” of dementia has not gone away

Meeting the challenge of dementia in the UK
https://ukdri.ac.uk/
https://www.nihr.ac.uk/partners-and-
industry/industry/collaborate-with-
us/dementia.htm
Discovery to translation
Late stage translation
https://www.dementiasplatform.uk/Data integration

The UK Dementia Research Institute

• Re-addressing fundamental questions of
earliest disease pathogenesis
• Novel target discovery
• Human target validation
• Translation
Discovery

UK DRI Centres at Imperial
College London

Understanding the transition from susceptibility to disease
7

Integrative science focused on translation
Centre Support Team
Skene
Bioiformatic approaches to
genomic drug discovery
Genetic
susceptibility
`
Elliott
Holmes (Assoc
Member)/Griffin
Biomarkers and
metabolomics
Matthews
Glal olecular pathology
and experimental medicine
Wisden/
Brancaccio
Sleep and circadian
Homeostasis
Grossman/Barnes
Microcircuit homeostasis
and bioelectronic
medicine
Body-brain health
Sleep
oscillatory
entrainment
Microcuit
homeostatisis and
modulation
Metabolome and
inflammation
Glial circadian
rhythms
Sleep and AD riskPopulation level brain
health
Ye
Therapeutic targeting of
dysfunctional protein
homeostasis
How environment and lifestyle
act on genes: epigenetics
Nativio/Nott/Marzi

Populations
Experimental medicine
Molecular neuropathology
Models
Elliott
Griffin/Holmes
Matthews
Skene
Marzi
Nativio
Nott
Griffin/Holmes
Grossman
Barnes
UK Biobank
FINGER
Nestle
MINDMAPS
DPUK
Invicro Ltd.
Biogen
MIT
Biogen
Broad Institute
BDR
MIT
NTU Singapore
NEWS AND VIEWS
factor 3, which itself led to
of AHR. Genetic ablation of
in astrocytes resulted in a w
autoimmunity consistent wit
Ifnar1-knockdown studies. A
wasshowntoinducetheexpre
sor of cytokine signaling 2 (S
ited activation of NF-κB, a tra
thatdrivestheproductionofp
cytokines. Thus, the AHR
pathway provides a molecula
Brain
Protection against
CNS inflammation
AHR ligands derived from
tryptophan catabolism
AHR ligand
Astrocyte
AHR + ligand
IFNAR1
SOCS2
NF- B
p
Gut E. coli Mutant: Accelerated aging
Partnerships for research integrating tools and biological scales
Matthews
Grossman

The UK DRI Brain Atlas
Image modified from https://ki.se/sites/default/files/mech_imm_image.jpg
Clinical
phenotype
Genome
(Epigenome)
Towards a molecular description of disease trajectory

New technologies : Desorption electrospray ionization–mass
spectrometry (DESI-MS) for spatial metabolomics/lipidomics
Raw Data (Ion image)
Pixel size:
75 µm * 75 µm
m/z
100 200 300 400 500 600 700 800 900 1000
%
0
100
2019-08-27_APP_12M_M_N05_0812_SLIDE262_75UM_NEG_MEOH Analyte 1 7874 (134.102) TOF MS ES-
1.47e5834.5140
790.5237
766.5238
96.9576
747.4951
303.2269
281.2475
722.4991
552.2648327.2287
885.5304
886.5363
887.5427
m/z
100 200 300 400 500 600 700 800 900 1000
%
0
100
2019-08-27_APP_12M_M_N05_0812_SLIDE262_75UM_NEG_MEOH Analyte 1 1896 (32.238) TOF MS ES-
3.63e6834.5140
790.5237747.4951
746.5043
835.5201
885.5365
886.5363
887.5366
PCA images after pre-processing
Reproducibility
.
Methods described in Inglese P, Correia G, Takats Z, Nicholson JK, Glen RCet al., 2019, SPUTNIK: an R package for filtering of spatially related peaks in mass spectrometry imaging
data, Bioinformatics, Vol: 35, Pages: 178-180, ISSN: 1367-4803

N. Grossman et al., Cell. 2017, N. Grossman Science, 2018
Brain Stimulation
Invasive, but focal and deep Non-invasive, but dispersed and
superficial
Temporal interference (TI) brain stimulation
Development of non-invasive, deep brain stimulation technology

Whisker
contralateral
Forelimb
contralateral
Whisker
ipsilateral
Amplitude ratio (𝐸!: 𝐸")
𝐸! 𝐸"
Whisker
contralateral Whisker
ipsilateral
Forelimb
contralateral
Mapping motor cortex activation with fixed electrodes
Validation 2. Steerable site activation (mouse cortex)
𝐸 <
1
𝑒
𝐸!"#
ROI frontal
ROI dorsal
Validation 3. Steerable site activation (human cortex)
Steerable activation of resting-state BOLD fMRI in humans (unpublished)
TI (1:3) 2.01 kHz, 0.5 mA, 2 kHz, 1.5 mA TI (3:1) 2.01 kHz, 1.5 mA + 2 kHz, 0.5 mA
Validation 1. Noninvasive deep brain stimulation (mouse hippocampus)
Hippocampus
NormalTI
Overlaying cortex
NormalTI
***
Overlaying cortex
Hippocampus
Active cells
(c-fos positive)
Hippocampus stimulation without overlaying cortex
Overlaying cortex
Hippocampus
Electrodes
Representative slice
Translational proof of principle for non-
invasive interference transcranial alternating
current brain stimulation (iTACS)

Phase IIa clinical trial of iTACS
Network Dynamics Cognitive Function
spatiotemporal
framework
activity regulation
homeostasis Contextual input
dys
Breakdown of
Pathological
failure
Aberrant
TI brain stimulation
Targeting neural bioenergetics
25 August 2020
Credits: Nature Reviews Drug Discovery 2018

The UK DRI Care and Technology Centre: transforming dementia
care
• Cost-effective, practical continuous monitoring technologies for key dementia
monitoring
• Reliable, safe and secure artificial intelligence (AI) systems to improve health
autonomy
• Robotic devices for improved safety and patient quality of life
• Moving the point-of-care into the home for personalised, predictive and
preventative healthcare
• A commitment to producing safe, usable and cost-effective technology that
fosters discovery science.

Programmes
Measure behaviour in the
home and supporting
activities that are key to
an individual's life.
Behaviour &
Cognition
Produce new approaches to
monitoring sleep and
circadian rhythms in the
home.
Integrate robotic devices
into the home to improve
safety and improve quality
of life.
PoC Diagnostics
Synthetic Biology
Develop new approaches to
infection diagnosis and
neurodegenerative
biomarkers.
Biosensors
Electrical Eng.
Low-cost continuous
monitoring devices that
provide measures of
behaviour.
Sleep & Circadian
Disruption
AI agent interface
Robotics
Derk-Jan Dijk David SharpRavi VaidyanathanPaul FreemontTim Constandinou

Cloud Computing
AI/Machine Learning
Limited, Secure
Private
Personalised
Intervention
Data Integration
& Intelligent decision-making
DataBox
Encrypted home storage
Medication
Behavior
Sleep
Robotics
Infection
EEG
Home Monitoring
The UK DRI Home Digital Care Platform
Payam Barnaghi

Pathology of Alzheimer’s Disease
Amyloid
Tau
Inflammation
Neuronal and synaptic
loss

- Short term memory loss typical early
symptom in AD
- Forgetting appointments
- Forgetting conversations
- Repetitive
- Difficulty route finding
- ? Impact on activities of daily living

Wearable technology as a
clinical tool for dementia: from
research to practice
Dr Ríona Mc Ardle
Supervisors: Dr Brook Galna, Prof Alan Thomas, Prof Lynn
Rochester
@RionaMcArdle

Pace Variability
Rhythm Asymmetry
Step velocity (m/s)
Step length (m)
Step time (s)
Swing time (s)
Stance time (s)
Step time variability (s)
Swing time variability (s)
Stance time variability (s)
Step velocity variability (m/s)
Step length variability (m)
Step time asymmetry (s)
Swing time asymmetry (s)
Stance time asymmetry (s)
Step Length asymmetry (m)
Lord et al, 2013

Buckley et al., 2019/ Del Din et al., 2016 for review

AD
Memory
DLB
Visual
Hallucinations
Attentional
fluctuations
REM sleep
behavior
disorder
Parkinsonism

Del Din et al., 2016 / Hickey et al., 2016

ü 125 participants recruited
ü 119 feasible for gait assessment
Ò 1 person discounted for festination
Ò 1 person discounted for using a stick
Ò 7 discounted as they had vascular dementia
Ò 14 discounted as they have Parkinson’s disease dementia
Ò 8 discounted due to data processing problems in lab
Ò 3 discounted due to quality checks in freeliving
85 participants analysed
ü 25 Controls
ü 32 Alzheimer’s disease
ü 28 Dementia with Lewy bodies
@RionaMcArdle

-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
Step Velocity
Step Length
Step Time Var
Swing Time Var
Stance Time Var
Step Length Var
Step Velocity Var
Step Time
Swing Time
Stance Time
Step Time Asy
Swing Time Asy
Stance Time Asy
Step Length Asy
Controls
Alzheimer's Disease
Dementia with Lewy bodies
Lab-based Gait
Assessment
Mc Ardle et al., 2020

-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
Step Velocity
Step Length
Step Time Var
Swing Time Var
Stance Time Var
Step Length Var
Step Velocity Var
Step Time
Swing Time
Stance Time
Step Time Asy
Swing Time Asy
Stance Time Asy
Step Length Asy
Controls
Alzheimer's Disease
Lab-based Gait
DLB vs AD
p ≤ .01

-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
Step Velocity
Step Length
Step Time Var
Swing Time Var
Stance Time Var
Step Length Var
Step Velocity Var
Step Time
Swing Time
Stance Time
Step Time Asy
Swing Time Asy
Stance Time Asy
Step Length Asy
Controls
Alzheimer's Disease
Lab-based Gait
AD&DLB vs controls
p ≤ .01

-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
Step Velocity
Step Length
Step Time Var
Swing Time Var
Stance Time Var
Step Length Var
Step Velocity Var
Step Time
Swing Time
Stance Time
Step Time Asy
Swing Time Asy
Stance Time Asy
Step Length Asy
Controls
Alzheimer's Disease
Lab-based Gait
DLB vs controls
p ≤ .01

Lab
Reality

Performance capacity
True function

-1.5
-1
-0.5
0
0.5
1
1.5
Step Velocity
Step Length
Step Time Var
Swing Time Var
Stance Time Var
Step Length Var
Step Velocity Var
Step Time
Swing Time
Stance Time
Step Time Asy
Swing Time Asy
Stance Time Asy
Step Length Asy
Controls
Alzheimer's Disease
Real World Gait
Mc Ardle et al., In revision

-1.5
-1
-0.5
0
0.5
1
1.5
Step Velocity
Step Length
Step Time Var
Swing Time Var
Stance Time Var
Step Length Var
Step Velocity Var
Step Time
Swing Time
Stance Time
Step Time Asy
Swing Time Asy
Stance Time Asy
Step Length Asy
Controls
Alzheimer's Disease
DLB vs AD
p ≤ .01
Real World Gait

-1.5
-1
-0.5
0
0.5
1
1.5
Step Velocity
Step Length
Step Time Var
Swing Time Var
Stance Time Var
Step Length Var
Step Velocity Var
Step Time
Swing Time
Stance Time
Step Time Asy
Swing Time Asy
Stance Time Asy
Step Length Asy
Controls
Alzheimer's Disease
DLB vs controls
p ≤ .01
Real World Gait

Role of context in patterns of gait impairment?
@Ríona Mc Ardle

Short bout lengths show trends of distinguishing AD and DLB
@Ríona Mc Ardle Mc Ardle et al., Under Review

AD and DLB have similar patterns of gait in longer bout lengths
@Ríona Mc Ardle Mc Ardle et al., Under Review

Take home messages
• In clinical environments, gait analysis conducted with wearable
technology may be a useful clinical tool for dementia diagnosis
• More work is required to translate these findings to real-world gait
- understanding the impact of context and environment
- improving algorithms
- collaborative efforts to encourage “best-practice” standards

UK NIHR Biomedical
Research Unit for
Lewy Body Dementia
award to the
Newcastle upon Tyne
Hospitals NHS
Foundation Trust
All my wonderful
participants!
Funding bodies!
My Supervisory Team:
Professor Lynn Rochester
Professor Alan Thomas
Dr. Brook Galna
Brain and Movement Research Group,
Director: Professor Lynn Rochester
Heather Hunter
Aisha Islam
Dr. Rachael Lawson
Dr. Ríona McArdle
Isabel Neatrour
Dr. Annette Pantall
Michael Dunne-Willows
Dr. Encarna Micó Amigo
Dr Lisa Alcock
Dr. Brook Galna
Rana Zia Ur Rehman
Dr. Hilmar P. Sigurdsson
Jo Wilson
Dr. Alison Yarnall
Philip Brown
Dr. Chris Buckley
Dr. Silvia Del Din

@RionaMcArdle
Riona.mcardle@ncl.ac.uk
https://bam-ncl.co.uk/

BrainWaveBank aims to make objective
assessment of neurocognitive function
convenient, affordable, and available to
anyone, anywhere
Brian Murphy
CSO & Co-Founder

Founded 2015
Offices in Belfast & Dublin
Team of 20
8 PhDs across a range of disciplines
Funded to £6m
through equity & grants
BrainWaveBank
by the Numbers

The Challenge of Diagnosis
and Progression Monitoring
in CNS Disorders

The Challenge of Diagnosis and
Progression Monitoring in CNS
Subtle progressive
impairment of select
neurocognitive
functions
Speed of Processing
Executive Function
Episodic Memory
Vocabulary
Adapted from Park et al 2009

Subtle progressive
impairment of select
neurocognitive
functions
Speed of Processing
Executive Function
Episodic Memory
Vocabulary
Adapted from Park et al 2009

Detectable cognitive
impairments trail
neuronal disfunction
EEG may detect neural
dysfunction when not
manifest in external
behaviour

Seeking a new
approach to objective
and scalable
assessment of brain
function
Neuroimaging (MRI, PET)
CSF analysis
Plasma analysis
Computerised testing
Clinical opinion, paper tests
Self-Reports

— 16-channel wireless dry EEG headset
— Gamified functional cognitive assessment
— Fast user-friendly setup in home and clinic
— State-of-the-art signal quality
— Cloud-based storage and remote trial management
— Machine-learning powered processing and analysis

Other Platform Features/Capabilities
Headset
Raw EEG & Accelerometer
Tablet
Game Data & Self-Reports
Data Upload
Data
Preprocessing
Feature Extraction
and Generation Data Modelling Predictive Results
Fitness Trackers
Sleep Quality & Step Count
Other Data Streams
Demographics, Health, etc.
Trial Monitoring Dashboards Conventional EEG analysis
Batch and individual
Session export
BrainWaveBank Platform Architecture
BrainWaveBank’s automated pipeline cleans and evaluates brainwave activity and behavioural
measures, combines with other data streams, and enables easy exploration and download of data

Users
>250
Hours of
EEG Recorded
>3,000
Total Daily Sessions
>8,000
Total Task-Specific
EEG Datasets
>25,000
Total Individual
Trial Samples
>3,000,000
Easy to Use
& Field-Proven
Collection of Real-World Data

Feasibility field study in
healthy aging

Collecting clinically
relevant data in the
clinic and beyond
Usability and Adherence
90 Healthy older adults, 40-80 yrs
Regularly record gamified EEG,
unsupervised in the home, with
daily lifestyle factors
Requested 20mins per day, 5 days
per week, for three months
No compensation

Average weekly
adherence of participants
over the trial duration
Aged 65-80 yrs
Signal reliability
Aged 65-80 yrs
High Compliance
High data quantity and
integrity, unsupervised in the
home, even with oldest users
Usability and Adherence
No.ofDailySessions

Time (s)
Magnitude(uV)
-7.5
-5.0
-2.5
-0.0
-2.5
5.0
7.5
-0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0
Gamified replication
of lab-based task
Gamification of Task-Driven EEG
Home-recorded 2-Stimulus
Oddball Target P300, an index of
attention and decision making.
P300 Target at sensor Cz
Magnitude(uV)
0.0 0.25 0.50
Alien appears here
“Textbook” P300

Group-based Validation
Oddball P300 amplitude and speed diminishes with age
Target P300 (at sensor Cz) by age band (<55yrs vs >60yrs), from 90-person older adult study
Validation in Age Cohorts
Time (s)
ERP(uV)
-6.00
-0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00
0.00
2.00
4.00
6.00
40-55
60-80
-4.00
8.00
-2.00

Validation in Impaired
Memory Cohort
50 healthy older adults, 55-80 yrs
Half were low memory performers
for their age/education
Requested 20mins per day, 5 days
per week, for six weeks
No compensation

Late parietal activity modulated by memory performance on Cantab
delayed pattern recognition memory
Validation in Impaired Memory Cohort
Late Parietal Potential (at sensor Pz) by memory performance terciles
Time (s)
ERP(uV)
-2.00
-0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00
0.00
2.00
4.00
6.00
High Memory Performer
Low Memory Performer

Measuring Human
Neuropharmacology on a
Larger Scale

Proving Out Low-burden EEG in the Clinic and in the Home
Double-blinded cross-over design, sub-anesthetic infusion of racemic ketamine vs saline control
30 healthy young adults
Continuous infusion of 0.5mg/kg
racemic ketamine/saline control
Resting state EEG and passive
Mismatch Negativity ERPs during
infusion
Suite of gamified active tasks in hours
before and after, in-lab
At-home sampling of same in week
before and after infusion day

Proving Out Low-burden EEG in the Clinic and in the Home
Double-blinded cross-over design, sub-anesthetic infusion of racemic ketamine vs saline control
Resting EEG exhibits depressed lower
frequencies, and enhanced higher
frequencies, as in literature
Novel enhancement of P300 ERP,
time-locked to decision making
during app-based task
In-clinic resting EEG during acute ketamine
Frequency (Hz)
-0.5
0 5
0.00
-1.0
0.5
1.0
10 15 20 25 30 35 40
-1.5
Ketamine
Saline
At-home task EEG in week after ketamine
7.5
5.0
2.5
0.0
-2.5
-5.0
-7.5
10.0
-0.4 -0.2 0.0 0.2 0.4 0.6 0.8
Time (s)
ERP(uV)

BrainWaveBank
Publications
Barbey, F., Dyer, J. F., McWilliams, E. C., Nolan, H., & Murphy, B. (2020 - accepted). Conventional wet EEG vs dry-sensor wireless EEG:
comparing signal reliability through measures of neuronal integrity. In Proceedings of the 15th Advances in Alzheimer’s and
Parkinson’s Therapies (ADPD) Focus Meeting. Vienna.
Buick, A. R., Watson, L., McGuinness, B., Passmore, A. P., & Murphy, B. (2018). In Home Screening for Cognitive Ageing to Enable
Improved Patient Outcomes. In Advances in Alzheimer’s and Parkinson’s Therapies: An AAT- AD/PD Focus Meeting, Turin.
Dyer, J. F., Barbey, F., Barrett, S. L., Buick, A. R., Mulholland, C., Shannon, C., & Murphy, B. (2019). Feasibility of mobile dry-EEG for
early detection of psychotic disorders: a usability study and pilot field trial. In Proceedings of the 32nd Congress of the European
College of Neuropsychopharmacology (ECNP). Copenhagen.
Dyer, J. F., Barbey, F., Barrett, S. L., Pickering, E. C., Buick, A. R., Mulholland, C., Shannon, C., Murphy, B. (2019). Gamified mobile EEG
for early detection of psychotic disorders: identifying needs from clinicians and end-users. In D. Nutt & P. Blier (Eds.), British
Association for Psychopharmacology Summer Meeting, 14-17 July, Manchester (p. A53). https://doi.org/10.13140/RG.2.2.15467.49442
Murphy, B., Aleni, A., Belaoucha, B., Dyer, J. F., & Nolan, H. (2018). Quantifying cognitive aging and performance with at-home
gamified mobile EEG. In 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI) (pp. 1–4). Singapore: IEEE.
https://doi.org/10.1109/PRNI.2018.8423954
Murphy, B., Barbey, F., Buick, A. R., Dyer, J., Farina, F., McGuinness, B., Passmore, A.P., Whelan, R. (2019). Replicating lab
electrophysiology with older users in the home, using gamified dry EEG. Presented at AAIC’19. Alzheimer’s & Dementia, 15(7), P867.
https://doi.org/10.1016/j.jalz.2019.06.4606
Murphy, B., Buick, A. R., Dyer, J. F., Nolan, H., McGuinness, B., & Passmore, A. P. (2018). Measuring Cognitive Decline with Home-
Based Gamified Mobile EEG. Presented at AAIC’18. Alzheimer's & Dementia, 14(7), P1579. https://doi.org/10.1016/j.jalz.2018.07.140

CONTACT
Brian Murphy PhD
CSO & Founder
E: brian@brainwavebank.com
Ronan Cunningham
CEO & Founder
E: ronan@brainwavebank.com
Tim Davison PhD
CTO
E: tim@brainwavebank.com
Alison Buick PhD
Head of Clinical Programmes
E: alison@brainwavebank.com
brainwavebank.com

Neurotechnology Webinar Series: Dementia Biodesign

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Neurotechnology Webinar Series: Dementia Biodesign

Similar to Neurotechnology Webinar Series: Dementia Biodesign (20)

More from KTN

More from KTN (20)

Recently uploaded

Recently uploaded (20)

Neurotechnology Webinar Series: Dementia Biodesign