Clinical Trial Details
— Status: Not yet recruiting
Administrative data
| NCT number |
NCT04810325 |
| Other study ID # |
296010 |
| Secondary ID |
|
| Status |
Not yet recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
July 1, 2021 |
| Est. completion date |
October 1, 2022 |
Study information
| Verified date |
May 2021 |
| Source |
University College, London |
| Contact |
Patricia Limousin, PhD |
| Phone |
00442034567890 |
| Email |
p.limousin[@]ucl.ac.uk |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
High-frequency deep brain stimulation (DBS) is an effective treatment strategy for a variety
of movement disorders including Parkinson's disease, dystonia and tremor1-5, as well as for
other neurological and psychiatric disorders e.g. obsessive compulsive disorder, depression,
cluster headache, Tourette syndrome, epilepsy and eating disorders6-11. It is currently
applied in a continuous fashion, using parameters set by the treating clinician. This
approach is non-physiological, as it applies a constant, unchanging therapy to a
dysfunctional neuronal system that would normally fluctuate markedly on a moment-by moment
basis, depending on external stressors, cognitive load, physical activity and the timing of
medication administration.
Fluctuations in physical symptoms reflect fluctuations in brain activity. Tracking and
responding in real-time to these would allow personalised approaches to DBS through
stimulating at appropriate intensities and only when necessary, thereby improving therapeutic
efficacy, preserving battery life and potentially limiting side-effects12. Critical to the
development of such adaptive/closed-loop DBS technologies is the identification of robust
signals on which to base the delivery of variable high-frequency deep brain stimulation.
Local field potentials (LFPs), which are recordable through standard DBS electrodes,
represent synchronous neuronal discharges within the basal ganglia. Different LFP signatures
have been identified in different disorders, as well as in different clinical states within
individual disorders. For example, low frequency LFPs in the Alpha/Theta ranges (4-12Hz) are
frequently encountered in patients with Dystonia13,14, while both beta (12-30Hz) gamma
(60-90Hz) band frequencies may be seen in Parkinson's disease, when the patient is OFF and
dyskinetic, respectively15,16. Equally, suppression of these abnormal basal ganglia signals
through medication administration or high-frequency DBS correlates with clinical improvement.
As such, they represent attractive electrophysiologic biomarkers on which to base adaptive
DBS approaches.
Until recently, neurophysiological assessments were purely a research tool, as they could
only be recorded either intra-operatively or for a short period of time post-operatively
using externalised DBS electrodes. However, advances in DBS technology now allow real-time
LFP recordings to be simply and seamlessly obtained from fully implanted DBS systems e.g.
Medtronic Percept PC.
In this study, we will evaluate a cohort of patients with movement disorders and other
disorders of basal ganglia circuitry who have implanted DBS systems. Recordings of LFPs
and/or non-invasive data such as EEG, limb muscle activation and movement (surface EMG and
motion tracking) under various conditions (e.g. voluntary movement, ON/OFF medications,
ON/OFF stimulation) will allow us to evaluate their utility as markers of underlying disease
phenotype and severity and to assess their potential for use as electrophysiological
biomarkers in adaptive DBS approaches. These evaluations in patients with DBS systems with
and without LFP-sensing capabilities will take place during a single or multi-day evaluation
(depending on patient preference and researcher availability). This study will advance not
only the understanding of subcortical physiology in various disorders, but will also provide
information about how neurophysiological and behavioural biomarkers can be used to inform
personalised, precision closed-loop DBS approaches.
Description:
Both hyperkinetic and hypokinetic movement disorders are associated with abnormal
spatiotemporal activity within the basal ganglia circuitry13,16,17. This can be assessed
through measuring local field potentials (LFPs), which represent the product of synchronous
neuronal activity at a given site (unsynchronized, random activity being essentially
cancelled out)13. Numerous other disorders such as obsessive compulsive disorder, major
depression, Tourette's syndrome, epilepsy, eating disorders and cluster headaches are also
amenable to successful modulation using DBS6-11. These disorders likely also have unique,
disease-specific electrophysiological signatures, the exact nature of which remains to be
thoroughly defined. Abnormal electrophysiological activity is useful not only in delineating
the pathophysiologic underpinnings of these disorders, but is central to the future
development of adaptive DBS systems which respond in real-time to ameliorate pathological
brain acticity12. Adaptive DBS may provide further clinical benefit beyond currently employed
continuous DBS approaches, with only a fraction of the energy requirements12.
Studies using microelectrode recordings at the time of DBS lead placement as well as
recordings from externalised DBS electrodes have identified distinct neurophysiological
signatures within different disorders. Examples include excess beta-frequency oscillations in
Parkinsonism, alpha and theta frequency oscillations in dystonia and gamma oscillations in
dyskinesia. These neurophysiologic biomarkers of disease can be affected by the application
of high-frequency DBS. Future closed-loop DBS systems may rely on real-time suppression of
such abnormal basal ganglia activity.
LFPs in Parkinson's disease
A significant body of work has confirmed that beta-frequency oscillations, recorded from both
the subthalamic nucleus and the internal portion of the globus pallidus, correlate with
severity of bradykinesia and rigidity in Parkinson's disease13,16-18. These beta-frequency
oscillations are coherent across simultaneous recordings in different nuclei of the same
patient, implying that these represent a network-level dysfunction in Parkinson's
disease16,19. The amplitude/power of abnormal beta-frequency LFPs correlates with the
severity of motor impairment in Parkinson's disease15,18. Moreover, beta-frequency LFPs can
be suppressed both by levodopa administration, or by the application of high-frequency
DBS20,21; in both scenarios the degree of suppression in beta-oscillations correlates with
the degree of clinical motor improvement. Beta oscillations may therefore represent an
electrophysiological parkinsonian symptom correlate which can act as a biomarker of the motor
state. Hence, they may be useful signals on which to base stimulation using adaptive DBS
technologies. However, some observations, such as the suppression of beta frequency
oscillations during periods of tremor, have cast doubt on the robustness of this potential
biomarker.
Other LFP frequency alterations have also been observed to correlate with clinical
symptomatology in PD. For instance, synchronisation at frequencies in the gamma range
(60-90Hz) have been correlated with dyskinesia, as have synchronisation at lower frequencies
(4-8Hz)22,23. High-frequency oscillations in the 250Hz range have also been found to
associate with parkinsonian clinical states and to shift to even higher frequencies (350Hz)
following levodopa administration24. In contrast to beta-frequencies, changes in
high-frequency LFPs do appear to correlate with tremor25.
Aside from pure frequency characteristics, the temporal distribution of beta-frequency
oscillations has also been examined in different disease states. It is suggested that
prolonged periods of beta synchronisation (beta bursts) may be responsible for the overall
increase in beta power in patients with Parkinson's disease in the OFF state, and that a move
to shorter durations of synchronisation may occur in the ON state26.
LFPs in dystonia
Patients with dystonia display a distinct pattern of LFP alterations in the pallidum13,14,
particularly an excess of synchronized oscillatory activity in the low frequency 3-12 Hz
band13. Not only is pallidal LFP power prominent in the 3-12Hz band in patients with
dystonia13,27 but it correlates with28 and may be coherent with (especially contralateral)
dystonic muscular activity29. Moreover, there is a direct association between pallidal
low-frequency oscillations and dystonia severity30.
Increased LFP power in the low-frequency band is seen across a variety of dystonia
phenotypes. In cervical dystonia, inter-hemispheric differences in LFPs have been
demonstrated, though clear correlations with directional head movements have not been
established31,32. In myoclonus-dystonia patients, increased pallidal LFP in the 3-15Hz range
correlate with dystonic muscle activity33. Oscillatory activity may be different in secondary
or combined dystonia, and may also differ according to genetic makeup 34-36.
LFPs in essential tremor
LFP recordings from patients undergoing thalamic DBS in ET have identified distinct thalamic
LFP frequency characteristics, often coherent with surface EMG recordings in these groups, at
frequencies which are either harmonics or subharmonics of the tremor frequency37.
LFPs in other conditions Electrophysiologic recordings from patients with Tourette's syndrome
have shown an excess of low-frequency activity(2-13Hz) in both thalamic and pallidal
targets38 and that spontaneous tics in Tourette's syndrome are preceded by coherent
thalamo-cortical discharges39. Unique, disease specific LFP patterns have also been
identified in a number of neuropsychiatric disorders. For example, prominent alpha activity
in the basal ganglia has been suggested as an electrophysiologic correlate of major
depressive disorders40
Continuous recording from fully implanted DBS systems has only recently become possible, for
example using the Medtronic Percept PC battery system. The quality of signals recorded using
this system as well as the correlation with clinical features, and coherence with cortical
and motor activity however remain largely unexplored. Moreover, the number of patients on
which previous LFP studies has been based is small. Hence, their utility in the future
development of closed-loop DBS systems remains uncertain.
Our study will address a number of unanswered questions relating to the utility of LFP
recordings in neurological disorders including:
1. Is it possible to replicate the previous findings concerning LFP signatures in various
movement disorders using currently available DBS systems with LFP sensing capabilities
e.g. Medtronic Percept PC?
2. Do LFP signatures persist many years after initiation of deep brain stimulation (most
previous studies have evaluated patients only at the time of DBS implantation)?
3. How are LFP signatures related to modulations of wider brain networks as assessed by
EEG?
4. Can non-invasive recording methods such as EEG provide alternative or complementary
biomarkers for closed-loop DBS?
5. What is the influence of medications, body movements, sensory inputs and differential
stimulation parameters on LFPs?
6. How robust are LFP signatures within and between individuals with similar disease
states?
7. Do robust LFP signatures exist for non movement disorder basal ganglia network
pathologies, and how do these correlate with symptoms severity?
