http://journal.frontiersin.org/article/10.3389/fneur.2017.00029/full?
Variability and Lack of Reliability of tDCS Studies in Individuals with Stroke
The variable effects of tDCS on motor performance may be
due to the lack of standardization of the technical parameters used
across sites. More likely, however, it is also due to (1) the
heterogeneity of the populations involved in the studies (43) and (2) the variability of the motor paradigms used.
Heterogeneity of the Involved Populations
The heterogeneity of each study population is a potential
source of variability for tDCS effects. However, researchers have had
difficulty in finding consistent sources of variability. Studies
typically examine the effects of (1) individual biological variability
(e.g., metabolic/genetic variants), or, factors specific to the stroke
such as, (2) time since stroke, (3) the nature and location of the
stroke, and finally (4) the level of motor impairment.
Individual Biological Variability
Intrinsic individual differences in neurotransmitter
levels, metabolic factors, and genetic variants provide a complex source
of variability when it comes to tDCS responsiveness. For instance, one
study found a relationship between individual differences in baseline
measures of GABA and anodal stimulation outcomes. However, this
relationship was not found between GABA and cathodal or bi-hemispheric
stimulation outcomes (46).
Another study showed that individual differences in the level of
dopamine receptor (D1) activity influenced the excitatory effects of
anodal tDCS on M1 (47).
These studies suggest that there is a complex, but influential,
relationship between biological factors and stimulation response.
Another factor that has been widely explored is the role
of an individual’s genetic variability on tDCS response. The secretion
of brain-derived neurotrophic factor (BDNF), which is involved in the
synaptic plasticity, neuronal growth, long-term potentiation (LTP)
formation, and long-term memory storage (48–50), seems to be enhanced by the application of tDCS (51). Moreover, an individuals’ level of BDNF seems to influence the response to NIBS and especially to tDCS (28, 52).
The most common form of BDNF polymorphisms, in which an amino acid
substitution between a Valine and a Methionine at position 66 on the
BDNF gene [Val66Met (53)],
modulate the level of BDNF expression and are thus associated with a
differential modulation of brain plasticity and altered motor plasticity
(54).
The Val66Met polymorphism, which induces less BDNF expression, has also
been shown to be associated with less-efficient motor learning and
reduced responsiveness to all forms of NIBS (28, 54, 55).
However, this finding is not always consistent. For
example, one study did not find any impact of the BDNF polymorphism on
the neuroplastic changes induced by anodal tDCS in older adults (56),
while a second one failed to find any impact of the BDNF polymorphism
on the neuroplastic-induced changes associated with either tDCS,
transcranial random noise stimulation, or theta burst stimulation (57).
Another study demonstrated that the BDNF polymorphism did not predict
responses to tDCS in patients suffering from depression but that a
serotonin transporter polymorphism did (58).
This suggests that the impact of the BDNF polymorphism, or more
globally, genetic polymorphisms on NIBS-related effects, may be disease
or task dependent.
Time after Stroke
There are also a number of factors specific to
individuals with stroke that may affect stimulation efficacy. One
variable is that stimulation may be delivered at different times after
stroke, during which different neural plasticity mechanisms (59, 60)
are active, making it difficult to compare effects across time points.
In addition, the categorical definitions of “time after stroke” may be
variable as well. For instance, the “chronic phase” of stroke is defined
across studies as patients anywhere from 3 months or more (up to many
years) after stroke (61, 62).
This means that within one “category” of patients with stroke, there
may be enormous variability in the plasticity processes and thus the
potential tDCS effects and interactions with those processes. More
precise clarification of time after stroke, using absolute terms such as
months, may be useful for comparing post-stroke tDCS results.
Nature and Location of the Stroke
The location of the stroke lesion (i.e., cortical or subcortical lesion) is similarly mixed or omitted in some tDCS studies (61, 63–66).
However, neural plasticity processes and cortical reorganization
inducing differential recruitment of different brain regions may be
dependent of the size and location of the stroke (67).
Another source of stroke-specific variability is the nature of the
stroke (i.e., ischemic or hemorrhagic), with some studies mixing both
populations together (18, 65, 66, 68).
This could also be a potential confound as the deficits and brain
plasticity processes associated with cortical/subcortical localization
or ischemic or hemorrhagic stroke (69–71) could be different.
Level of Motor Impairment after Stroke
Finally, the level of impairment after stroke should be
carefully considered. There is a wealth of literature that suggests that
patterns of neural recovery may differ for individuals based on the
severity of their stroke (72–76).
The recruitment of different brain regions, such as the contralesional
hemisphere, may also play a different role based on the level of motor
impairment. Most of the tDCS studies in patients after stroke mixed
patients with different level of impairments (from mild to severe) (18, 65, 77).
However, it may be important to consider an individual’s level of motor
impairment and optimal pattern of recovery when applying tDCS.
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