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Review

Electrophysiological measures as potential biomarkers in

Huntington's disease: Review and future directions

Lan Nguyena, John L. Bradshawa, Julie C. Stout a,Rodney J. Croft b, Nellie Georgiou-Karistianisa,⁎

aSchool of Psychology and Psychiatry, Monash University, Clayton, Victoria 3800, Australia

bDepartment of Psychology, University of Wollongong, Northfields Ave, Wollongong 2522, Australia

A R T I C L E I N F O A B S T R A C T

Article history:

Accepted 29 March 2010

Available online 8 April 2010

Neuroimaging is fundamental to identifying quantifiable and objective biomarkers in

symptomatic and pre-diagnostic Huntington's disease (HD). However, the challenge

remains to find reliable biomarkers with high sensitivity and specificity that can be used

to track the functional decline over time and test efficacy of therapeutic intervention. While

many recent studies have focused on neuroimaging techniques based on brain

hemodynamic activity, comparatively fewer have utilized electroencephalography (EEG)

and event-related potentials (ERPs). This review aims to summarise and integrate key

electroencephalographical findings from the last two decades in symptomatic and pre-

diagnostic HD, in context with recent neuroimaging data, and to use this information toidentify promising candidate markers for future research and clinical consideration.

© 2010 Elsevier B.V. All rights reserved.

Keywords:

Huntington's disease

Pre-diagnostic Huntington's disease

Electroencephalography

Event-related potentialsBiomarkers

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178

2. Use of EEG/ERP in identifying potential biomarkers of dysfunction and disease progression . . . . . . . . . . . . . . 178

3. Quantitative EEG markers of Huntington's disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180

3.1. Sleep EEG in Huntington's disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

4. Sensory ERP markers of Huntington's disease. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

4.1. Auditory ERPs in Huntington's disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

4.2. Visual ERPs in Huntington's disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1824.3. Somatosensory ERPs in Huntington's disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182

5. Movement-related potentials in Huntington's disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

6. Long-latency potentials in Huntington's disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184

7. Animal studies of HD and electrophysiology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

8. Conclusions and future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188

B R A I N R E S E A R C H R E V I E W S 6 4 ( 2 0 1 0 ) 1 7 7 – 1 9 4

⁎ Corresponding author. Experimental Neuropsychology Research Unit, School of Psychology and Psychiatry, Monash University, Clayton,Victoria 3800, Australia. Fax: +61 3 9905 3948.

E-mail address: [email protected] (N. Georgiou-Karistianis).

0165-0173/$ – see front matter © 2010 Elsevier B.V. All rights reserved.doi:10.1016/j.brainresrev.2010.03.004

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mailto:[email protected]://dx.doi.org/10.1016/j.brainresrev.2010.03.004http://dx.doi.org/10.1016/j.brainresrev.2010.03.004mailto:[email protected]


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1. Introduction

Huntington's disease (HD) is a dominantly inherited neurode-

generative condition classically characterized by motor dys-

function, cognitive impairment and psychiatric disturbances

(Hayden, 1981; Folstein, 1989). The symptoms do not manifest

systematically and any of the three can predominate in agiven patient. Estimates of the worldwide prevalence of the

disease are about 5 to 10 per 100,000, although there is

considerable variation across geographical regions due to its

hereditary nature (Conneally, 1984; Schilling and Borchelt,

2003). The disease is caused by expansion of 36 or more

trinucleotide (CAG) repeats on chromosome 4 (4p16.3), which

leads to structural and functional alteration of the protein

huntingtin (Harjes and Wanker, 2003; The Huntington's

Disease Collaborative Research Group, 1993). The length of

CAG repeats correlates inversely with age of disease onset,

with higher numbers associated with earlier symptom onset;

onset of illness can occur from infancy to old age and mostly

between the ages of 35 and 50. Upon diagnosis, symptoms are

relentlessly progressive with death occurring on average

within 15 to 20 years. Current pharmacological management

can only alleviate symptoms as at present there is no effective

treatment or cure (for a review, see Phillips et al., 2008).

While the diagnosis of HD is based on the presence of

chorea, accumulating research supports a pre-diagnostic

phase, during which symptoms and signs gradually appear

and progress, hereafter referred to as “pre-HD”. Neuropsycho-

logical studies indicate that subtle motor (Blekher et al., 2004;

de Boo et al., 1997; Kirkwood et al., 1999, 2000a; Paulsen et al.,

2008; Petit and Milbled, 1973; Siemers et al., 1996; Smith et al.,

2000; Snowden et al., 2002; Verny et al., 2007), cognitive

(Diamond et al., 1992; Hahn-Barma et al., 1998; Jason et al.,

1997; Kirkwood et al., 2000b; McCusker et al., 2000; Paulsen et

al., 2001b; Rosenberg et al., 1995; Verny et al., 2007) and

psychiatric signs and/or symptoms (Berrios et al., 2001, 2002;

Brandt et al., 2002; Duff et al., 2007; Kirkwood et al., 2002;

Paulsen et al., 2001a) are present years before clinical

diagnosis. However, changes documented in pre-HD are

subtle and by definition do not fall in the clinically impaired

range (Farrow et al., 2007; Paulsen et al., 2008; Solomon et al.,

2007). Although several neuropsychological studies have

failed to identify pre-HD changes (Blackmore et al., 1995;

Brandtet al., 2002; Campodonico et al., 1996;de Booet al., 1999;

Giordani et al., 1995; Gomez-Tortosa et al., 2001; Rothlind et al.,

1993; Siemers et al., 1996; Strauss and Brandt, 1990; Witjes-Ane

et al., 2003), neuroimaging confirms that structural changes

commence a decade or more prior to diagnosis (for reviews,

see Bohanna et al., 2008; Georgiou-Karistianis, 2009; Paulsen,

2009). Improved understanding of the earliest manifestations

of the illness offers the potential for early therapeutic

intervention (Georgiou-Karistianis, 2009; Phillips et al., 2008).

The identification of quantifiable and objective biomarkers

of early and prodromal disease is pivotal to the acceleration of

possible neuroprotective therapies. However, the challenge

remains to identify reliable biomarkers with high sensitivity

and specificity that can track progressive functional decline.

Many recent pre-HD studies have focused on neuroimaging

techniques based on brain hemodynamic activity such as

positron emission tomography (PET) (Andrews and Brooks,

1998; Ciarmiello et al., 2006; Feigin et al., 2001, 2006; Pavese et

al., 2003), single photon emission tomography (SPET)

(Andrews and Brooks, 1998), magnetic resonance imaging

(MRI) (Aylward, 2007; Aylward et al., 2000; Campodonico et al.,

1998; Kassubek et al., 2004a,b; Paulsen et al., 2006; Peinemann

et al., 2005; Starkstein et al., 1992; Thieben et al., 2002; Wolf et

al., 2008a,b), functional magnetic resonance imaging (fMRI)(Georgiou-Karistianis et al., 2007; Paulsen et al., 2004; Reading

et al., 2004; Thiruvady et al., 2007; Wolf et al., 2007) and

diffusion tensor imaging (DTI) (Reading et al., 2005; Rosas et

al., 2006; Sritharan et al., 2010). Less has been done with

electroencephalography (EEG) and event-related potentials

(ERPs), despite the increase of studies utilizing EEG and ERP to

identify biomarkers in Alzheimer's disease and mild cognitive

impairment ( Jackson and Snyder, 2008; Prichep, 2007). Renewed

interest in EEG stems from significant technical advances and

resultant improvements in the quality and quantification of

data. Electrophysiological data can be collected in high density

recordings(from up to 256 leads or more), permitting imaging of

data topographically in three dimensions and localization

analyses to identify sources of the EEG signals. This review

aims to summarise and integrate key electroencephalographi-

cal findings from the last two decades in symptomatic and pre-

HD, in context with neuroimaging data, and to use this

information to identify promising candidate markers for future

research and clinical consideration.

2. Use of EEG/ERP in identifying potential biomarkers of dysfunction and disease progression

Biomarkers, generally defined as objectively measured char-

acteristics, provide indications of normal biological processes,

pathogenic processes or pharmacological responses to a

therapeutic intervention (The Biomarkers Definitions Work-

ing Group, 2001). In the context of HD, biomarkers could be

used as quantifiable measures of manifest disease to define

conversion from pre-HD to symptomatic disease. Biomarkers

could also potentially be used as a tool to monitor the rate of

disease progression, in both the pre-HD and symptomatic

phase, to better understand the pathogenesis of HD. Further-

more, biomarkers would facilitate an accurate evaluation of

the effectiveness of new therapies and improve efficiency of

clinical trials. Due to the heterogeneity of HD symptoms, it is

possible that a combination of clinical, behavioral and/or

biological biomarkers will be required to provide information

about different aspects of the disease.

EEG is a measurement of the electrical activity of the brain

(Andreassi, 2000; Luck, 2005). It is a non-invasive technique

that could potentially yield relatively low-cost biomarkers.

EEG and ERPs are ideal tools to explore quantifiable and

objective biomarkers of HD neuropathology. Surface EEG

signals, recorded using electrodes applied to the scalp,

represent a summation of billions of individual inhibitory

and excitatory post-synaptic potentials influenced by shared

activity between cortical and subcortical regions (see Fig. 1 for

a summary of EEG/ERP measurement and analyses). Data

generated by these potentials offer millisecond temporal

resolution, a thousand fold faster than hemodynamic

178 B R A I N R E S E A R C H R E V I E W S 6 4 ( 2 0 1 0 ) 1 7 7 – 1 9 4


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measures, though with correspondingly poorer spatial reso-

lution (Andreassi, 2000). ERPs are derived from the EEG signal

by averaging a seriesof EEG segments that are time locked to a

common class of events. As such, ERPs represent voltage

changes in the brain associated with specific processes. There

are several types of ERPs. Sensory ERPs refer to potentials

produced by visual, auditory, somatosensory, and olfactory

stimuli. Motor ERPs precede and accompany voluntary

movement. In contrast to sensory and motor potentials,

long-latency potentials refer to ERP components that occur

at 250 to 900 ms after an event and reflect more subjective

aspects of processing, oftenlinked to cognitive and attentional

functions. All of these potentials can vary in their amplitudes

and latencies, reflecting strength of processes and/or effect of

particular experimental manipulations and the specific pat-

terns of neural activity that these conditions evoke.

The ERP waveform consists of a sequence of positive and

negative voltage fluctuations, referred to as peaks, waves, or

components (Andreassi, 2000; Luck, 2005). Components are

labeled with a P (positive) or N (negative) followed by either

latency (e.g. P105 for a positive peak at 105 ms post-stimulus)

or position of the peak within the waveform (e.g. P1 for the

first major positive peak). The use of latencies can be

misleading as component latencies vary as a function of the

Fig. 1 – Brief summary of EEG and ERP measurement and analyses. For a more detailed introduction to electrophysiology, see

Luck, 2005.

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stimulus and task. For example, the P300 component may

peak as late as 1000 ms under some conditions. Three

measurable aspects of the ERP waveform are amplitude,

latency, and scalp distribution (Luck, 2005). Amplitude pro-

vides an index of the magnitude and strength of neural

activation. Latency refers to the point in time at which the

peak occurs (or the onset of the deflection) and gives

information on timing of the activation. Finally, scalpdistribution is the distribution of voltage over the scalp at

anypoint of time andgives an indication of theoverall pattern

of activated brain areas. The ERP waveforms are thought to

reflect the sequence of neural and cognitive processes;

however, components may be absent from the ERP waveform

if the neural generators do not have the appropriate orienta-

tion relative to the scalp (Luck, 2005). As such, the presence of

two sequentially occurring components in the ERP waveform

does not necessarily indicate sequential stages of processing.

Moreover, it is difficult to determine the exact locations of

generators of ERP components. However, the combination of

high density recordings and sophisticated spatial filtering

techniques can generally provide an indication of the corti-

cally generated activity. Taken together, electrophysiology can

detect sensory, motor, and cognitive processing deficits

related to HD neuropathology. It is a relatively inexpensive

technology that yields high temporal sensitivity also offering a

range of measures as potential biomarkers of disease onset

and progression.

3. Quantitative EEG markers of Huntington's disease

Quantitative EEG studies using power spectral analyses have

documented changes across all frequency bands in HD

(Bylsma et al., 1994; de Tommaso et al., 2003; Streletz et al,

1990). The EEG of HD patients (in a resting state with eyes

closed) was characterized by a marked reduction in raw and

percent alpha power, a decrease in raw and percent theta in

the medial frontal area, increases in percent delta and percent

beta power, and decreased theta frequency (Bylsma et al.,

1994). Conversely, Streletz et al. (1990) and de Tommaso et al.

(2003) both reported theta power to be increased in HD

compared to controls. The most consistent and strongest

electrophysiological abnormality in HD, compared to controls,

is suppression of alpha activity (Bellotti et al., 2004; Bylsma et

al., 1994; de Tommaso et al., 2003; Streletz et al., 1990). Using

artificial neural networks, the abnormality was sourced to

dysfunction of the thalamus (Bellotti et al., 2004; de Tommaso

et al., 2003). In line with these findings, MRI analyses revealed

grey matter differences in the bilateral thalamus in symp-

tomatic (Kassubek et al., 2005) and pre-HD (Wolf et al., 2009).

The relationship between EEG changes and cognitive/

neurological impairment in HD is not well understood. De

Tommaso et al. (2003) reported that reduction in alpha

correlated poorly with severity of illness and cognitive

impairments in symptomatic and pre-HD. Similarly, both

Bylsma et al. (1994) and Sishta et al. (1974) found that duration

of disease was not correlated with any quantified EEG power

measure. However, Streletz et al. (1990) reported a significant

correlation between increased theta and reduced alpha power

and clinical stage of dementia [using the Clinical Dementia

Rating Scale (Burke et al., 1988)]. Bylsma et al. (1994) detailed a

more complex relationship, reporting neurological impair-

ment, including severity of oculomotor impairment, chorea,

and voluntary motor impairment, was associated with higher

beta and delta frequencies, particularly at frontal areas,

whereas poor cognitive performance was related to EEG

abnormalities in frontal and temporal regions.Alpha activity abnormalities have been reported in pre-HD

(de Tommaso et al., 2003; van der Hiele et al., 2007). Reduction

of alpha activity (in a resting state) discriminated pre-HD from

controls, despite the study comprising only a small number of

pre-HD participants (n= 7) (de Tommaso et al., 2003). The

authors suggested that the degree of alpha reduction may

identify those close to clinical symptom onset as correlational

analyses indicated a negative linear relationship between

expected time of clinical onset and alpha neural scores. On the

contrary, van der Hiele et al. (2007) found absolute alpha

power at rest to be similar between pre-HD and controls.

However, during a working memory task, pre-HD had

significantly less alpha power compared to controls, despite

comparable memory performance. Drawing on research

which suggests that alpha power decreases in response to

mental challenge, the authors suggested that compensatory

neuronal activity may keep memory performance intact.

However, Cooper et al. (2003) showed that once sensory

stimulation was controlled, alpha increased with difficulty

level. In fact, a number of studies indicate that alpha activity

involves a complex thalamo-cortical network and can index a

range of possible functions while yet playing an active role in

the inhibitory control and timing of cortical processes

(Klimesch et al., 2006; 2007). Nevertheless, functional connec-

tivity, based on correlations of fMRI blood-oxygen level-

dependent signal responses between brain regions, has

revealed dysfunction in prefrontal regions in both symptom-

atic (Thiruvady et al., 2007; Wolf et al., 2009) and pre-HD (Wolf

et al., 2007, 2008a,b) during a working memory task. In line

with van der Hiele et al. (2007), working memory performance

did not significantly differ between pre-HD and controls (Wolf

et al., 2007, 2008a,b). Furthermore, a number of studies

consistently find that pre-HD participants show increased

functional activation in cortical brain regions during task

performance despite comparable behavioral performance to

controls (Paulsen et al., 2004; Reading et al., 2004; Wolf et al.,

2007). Despite conflicting results, the findings of de Tommaso

et al. (2003) and van der Hiele et al. (2007) are suggestive of

alpha changes in pre-HD. Further research is required to

clarify the mechanisms of alpha at rest and during cognitive

processing in pre-HD.

In summary, several studies corroborate that alpha

amplitude reduction is a discriminating feature in HD, with

recent preliminary findings of changes in pre-HD (de

Tommaso et al., 2003; van der Hiele et al., 2007 ). However,

alpha oscillations have multiple functional correlates in-

cluding sensory, motor, and memory processes (for a review,

see Basar et al., 1997; Klimesch et al., 2007 ), and there is

limited understanding of their relationship with HD. Further

investigation in large-scale studies with both symptomatic

and pre-HD is required to better understand the basis of

the electrophysiological abnormality, and longitudinal



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opportunities will enable examination of the reliability of

these measures in indexing disease progression.

3.1. Sleep EEG in Huntington's disease

Sleep disturbances including insomnia, nocturnal waking, and

daytime sleepiness are commonly reported in HD (Taylor and

Bramble, 1997); however, polysomnographic sleep studiesprovide mixed findings. The most consistently reported

sleep abnormality in HD compared with controls is reduced

sleep efficiency (Arnulf et al., 2008; Hansotia et al., 1985;

Morton et al., 2005; Silvestri et al., 1995; Wiegand et al., 1991a,

b). Other abnormalities include prolonged sleep latency

(Cuturic et al., 2009; Wiegand et al., 1991a), reduced slow-

wave sleep (Wiegand et al., 1991a; Silvestri et al., 1995), and

increased density of sleep spindles (Emser et al., 1988;

Wiegand et al., 1991a). Rapid eye movement abnormalities

have also been suggested (Arnulf et al., 2008; Hansotia et al.,

1985; Silvestri et al., 1995; Starr, 1967) although this account is

not supported by a number of studies (Cuturic et al., 2009;

Emseret al., 1988; Wiegand, et al., 1991a,b).In fact, a numberof

studies have found only one sleep variable to be abnormal in

HD compared to controls. For example, Cuturic et al. (2009)

found that only sleep latency was significantly longer in the

HD group. Wiegand et al. (1991b) found that only sleep

efficiency was significantly reduced in HD compared to

controls, although there was a trend for reduced slow-wave

sleep and longer sleep onset latency. Emser et al. (1988) found

no sleep abnormalities in HD, except for an increased spindle

density. In an in vivo PET study, HD disturbances in the wake–

sleep cycle were partly attributed to significant D2 receptor

loss and microglia activation in the hypothalamus (Politis et

al., 2008). Variationin EEGresults maybe related to differences

in study design including small sample sizes, single (Arnulf et

al., 2008; Cuturic et al., 2009) or two night (Silvestri et al., 1995;

Wiegand et al., 1991a,b; Emser et al., 1988) polysomnogram, as

well as the variety of sleep variables measured. A number of

studies did not indicate medication status or control for the

possible effect of medication on sleep (Arnulf et al., 2008;

Emser et al., 1988; Silvestri et al., 1995; Starr, 1967). In

conclusion, although a number of polysomnographic sleep

abnormalities have been reported in HD, there is great

variability in findings. Sleep disturbances can be affected by

many extraneous variables such as medication, levels of

stress, and mood (Brotini and Gigli, 2004). To ascertain reliable

sleep EEG abnormalities in HD as well as their reliability and

sensitivity as measures of disease onset and progression, a

well-controlled standardized study is required offering signif-

icantly larger sample sizes than those conducted previously.

4. Sensory ERP markers of Huntington'sdisease

4.1. Auditory ERPs in Huntington's disease

ERPs have been utilized to investigate whether auditory

processing is affected in HD. Studies of brainstem auditory

evoked potential (BAEP) collectively indicate that early proces-

sing of auditory stimuli (circa 0–12 ms) is normal in HD,

signifying intact peripheral and central auditory pathways

(Bollenet al., 1986; Ehle et al., 1984; Scott et al., 1972). However,

HD patients showreduced amplitude and prolonged latency of

the P50 auditory ERP (AERP) (Uc et al., 2003). Abnormal

manifestations of the P50 potential are suggestive of distur-

bances in the control of states of arousal and sleep–wake

regulation by the cholinergic arm of the reticular activating

system (Skinner et al., 2002). This is consistent with sleep

deregulation in HD (Wiegand et al., 1991a). In the paired-clickparadigm, when twoclicks arepresented 500 ms apart,the P50

response to the second of the clicks undergoes active

inhibition from cholinergic hippocampal inputs (Uc et al.,

2003); the reduction in P50 amplitude can index sensory

gating. Using this paired-click paradigm, Uc et al. (2003) found

that HD patients show reduced P50 sensory gating relative to

normal controls. This is consistent with findings that HD

patients failed to inhibit a normal reflex response to intense

auditory and tactile stimuli (Swerdlow et al., 1995). Sensory

gating impairment has beenassociated in other disorderswith

reduced sustained attention and increased anxiety such as

schizophrenia (Cullum et al., 1993; Geyer et al., 2001),

obsessive compulsive disorder (Swerdlow et al., 1993), and

Tourette's syndrome (Castellanos et al., 1996); Uc et al. (2003)

suggested that sensory gating deficits may possibly underlie

disordered attention (Sprengelmeyer et al., 1995) and/or

anxiety (Paulsen et al., 2001a) mechanisms in HD.

In contrast to an expected global cognitive deterioration,

HD patients displayed enhanced performance in auditory

sensory memory, with lower error rates and shorter reaction

time compared to pre-HDand controls (Beste et al., 2008a). The

behavioral data were accompanied with higher amplitude of

the mismatch negativity (MMN); this ERP is evoked by rare

(deviant) stimuli and is thought to reflect an automatic

discrimination of stimulus change (Andreassi, 2000). Beal

and Ferrante (2004) indicated superior performance in HD may

be due to increased receptiveness of voltage-dependent

NMDA receptors to endogenous levels of glutamate. Increas-

ing evidence suggests that excitotoxicity, excessive action of

glutamate receptors by excitatory amino acids leading to cell

dysfunction/death, may play a role in the selective neuronal

degeneration in HD (for a review, see Ferrante, 2009).

Excitotoxin-induced neuronal damage is inhibited by NMDA

receptor antagonists (Ferrante et al., 1993). On the other hand,

a number of studies collectively indicate that MMN is

modulated by NMDA receptors since administration of

NMDA antagonists can abolish the MMN (for a review, see

Kujala et al., 2007; Naatanen et al., 2007). Taken together and

in line with suggestions by Beste et al. (2008a), enhanced

performance in sensory memory in symptomatic HD is likely

to be related to sensitivity of MMN to NMDA receptors and

increased receptiveness to glutamate in HD.

Additional AERP abnormalities in HD include significant

delays in N1, P2, and N2 components (circa 100–250 ms)

(Goodin and Aminoff, 1986; Homberg et al., 1986). However,

conflicting results have been reported, with other studies

reporting significant differences only in N1 latency ( Josiassen

et al., 1984), N2 latency (Filipovic et al., 1990), and P2 latency

(Rosenberg et al., 1985). Furthermore, Josiassen et al. (1984)

and Homberg et al. (1986) reported that the main AERP

abnormality in HD was a general reduction in amplitude,

rather than latency of components.



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Taken overall, although these studies are suggestive of

auditory processing deficits in HD, the electrophysiological

data are limited, with none published in pre-HD. Recent MRI

data in early HD indicate significant thinning of primary

auditory cortex and cortical areas adjacent (Rosas et al., 2008).

Furthermore, recent fMRI data indicate an altered pattern of

auditory processing mechanisms, dependent on the progres-

sion of neuronal dysfunction in both symptomatic andpre-HD(Saft et al., 2008).

4.2. Visual ERPs in Huntington's disease

Visual processing disturbances have been frequently de-

scribed in symptomatic and pre-HD (Gomez-Tortosa et al.,

1996; Lawrence et al., 2000; Mohr et al., 1991 ). For example,

MRI data indicate that very early onset HD participants

show cortical thinning of visual regions (Rosas et al., 2008).

With disease progression, participants show more extensive

thinning of the occipital cortex. Other changes include

altered metabolism of the occipital cortex (Feigin et al.,

2001; Jenkins et al., 2005) and significant atrophy of the

occipital lobe (Lange et al., 1976). The early P1 and N1

components of the visual ERP (VERP) have been shown to

emanate from secondary visual areas, and these compo-

nents provide the opportunity to examine time course of

neuronal alterations in early visual processing (Luck, 2005).

HD patients are generally characterized by a non-specific

amplitude reduction of VERP components in response to

light flashes or checkerboard reversal stimulation (Ellenber-

ger et al., 1978; Josiassen et al., 1984; Oepen et al., 1981), with

abnormalities correlated to severity and duration of symp-

toms (Ellenberger et al., 1978). However, a number of studies

have also reported that VERPs in HD were not significantly

different in amplitude (Ehle et al., 1984; Munte et al., 1997;

Rosenberg et al., 1985; Scott et al., 1972 ) or latency (Ehle et

al., 1984; Rosenberg et al., 1985; Scott et al., 1972 ) compared

to controls. Recent VERP studies have utilized more complex

task paradigms to delineate visual processing abnormalities

in HD (Antal et al., 2003; Beste et al., 2008b). Antal et al.

(2003) found that HD patients showed reduced amplitude of

the N1 component for animal and non-animal images

compared with controls and pre-HD, suggesting of disrup-

tions in early perceptual categorization in HD. As difference

in the N1 component was only found at the temporal

electrode sites, the authors attributed likely pathological

changes of the circuits between the basal ganglia and the

temporal cortex, known to influence higher-order visual

processing. In another study, the N1 VERP was used to

examine processes of attention and response selection

(Beste et al., 2008b). The flanker and target stimuli were

separated by 100 ms; this enables a separate N1 to be elicited

during occurrence of a flanker and on the occurrence of a

target. Results indicated the N1 to the flankers, but not the

target, was significantly attenuated in HD patients. These

results suggest that HD patients attended less to the flanker

but normally to the target, supporting previous findings of a

dysfunction in spatial visual attention in HD (Georgiou et al.,

1995, 1996; Georgiou-Karistianis et al., 2002). The authors

proposed that selective attenuation exclusively of the

flanker N1 reflects an alternation of visuospatial attention

or, more likely, a strategy by the patients to reduce

distraction from the flankers so as to enhance performance

on target presentation.

VERP abnormalities in pre-HD are difficult to interpret as

most studies were conducted prior to gene localization

(Ellenberger et al., 1978; Josiassen et al., 1984; Oepen et al.,

1981). Only two studies to date have explored visual proces-

sing using ERPs in genetically confirmed pre-HD. Antal et al.(2003) found that although the N1 component to animal and

non-animal stimuli was significantly reduced in amplitude in

symptomatic HD, no differences were found in pre-HD

compared to controls. However, Beste et al. (2008b) suggested

that visual attentional processing may be affected electro-

physiologically but not behaviorally in pre-HD. The pre-HD

group produced a flanker N1 that was significantly reduced in

amplitude compared to controls, despite no reaction time

differences between the groups. The magnitude of reduction

in pre-HD was not as strong compared to symptomatic HD,

which suggests that visual attentional processing is only

mildly affected and may decline as disease progresses.

In summary, general visual processing deficits in HD, as

indicated by ERP in response to light flashes or checkerboard

reversal, are conflicting. However, the N1 VERP applied to

specific tasks of visual processing (perceptual categorization

and attention/response selection) has been shown to be

valuable in separating pre-HD, symptomatic HD, and controls.

It is possible that visual processing deficits in HD are task

specific, particularly in pre-HD. Future longitudinal research

is required to validate reliability of N1 VERP in both pre-HD

and HD.

4.3. Somatosensory ERPs in Huntington's disease

Although at the behavioral level sensory deficits are not a

characteristic feature of HD symptomatology, somatosensory

ERP (SERP) abnormalities are consistently reported following

electrical nerve stimulation (Abbruzzese et al., 1990; Beniczky

et al., 2002; Bollen et al., 1985; Ehle et al., 1984; Huttunen et al.,

1993; Josiassen et al., 1982; Kuwert et al., 1993; Lefaucheur et

al., 2002, 2006; Noth et al., 1984; Oepen et al., 1981; Seiss et al.,

2003; Thompson et al., 1988; Topper et al., 1993). The majority

of studies report a reduction in amplitude of early SERP

components, particularly the parietal N20 and P25 compo-

nents, as well as in precentral frontal P22 and N30 compo-

nents, despite varying methods and definitions of cortical

components (Abbruzzese et al., 1990; Beniczky et al., 2002;

Bollen et al., 1985; Ehle et al., 1984; Kuwert et al., 1993;

Lefaucheur et al., 2002, 2006; Noth et al., 1984;Thompson et al.,

1988; Topper et al., 1993). SERP changes in HD, particularly N20

and N30, are thought to reflect abnormal transmission from

the basal ganglia–thalamic complex to the sensory cortex

(Abbruzzese and Berardelli, 2003). The parietal N20 peak

corresponds to the primary somatosensory cortex receiving

cutaneous inputs via the lemniscal pathway, and the frontal

N30has been proposed to reflect activity in thesupplementary

motor areas (Rossini et al., 1989). Disruption of these neural

circuits may interfere with sensory information integration,

movement preparation, and control (Abbruzzese and Berar-

delli, 2003). SERP components have been closely linked to HD

pathology, with significant correlations to CAG repeat length



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(Beniczky et al., 2002) and Unified Huntington's Disease Rating

Scale (UHDRS) (Lefaucheur et al., 2002). Both Ehle et al. (1984)

and Lefaucheur et al. (2006) found that the N20 component

progressively decreased in amplitude over a 2-year period and

correlated with functional decline, suggesting it may be a

suitable candidate marker for disease progression. Supporting

the ERP findings, significant neuronal loss has been found in

the primary somatosensory cortex (Lange et al., 1976; Mann etal., 1993; Heinsen et al., 1994), and MRI data indicate cortical

thinning of the primary sensory cortical regions in very early

stages (Rosas et al., 2008). Moreover, PET revealed altered

cortical activation on passive sensory stimulation in HD

(Boecker et al., 1999).

Limited SERP research has been conducted in pre-HD, but

several early studies reported reduction of SERP amplitudes in

individuals at risk ( Josiassen et al., 1982; 1986; Kuwert et al.,

1993; Oepen et al., 1981). Surprisingly, only one study to date

has been conducted on genetically confirmed pre-HD and

reported a significant reduction in amplitudeof the tibial SERP

components, although only five participants were included

(Beniczky et al., 2002). The authors indicated that the tibial

SERP wasmore sensitivethan the medianSERP, which is more

commonly investigated. These findings suggest that somato-

sensory changes are highly specific prior to symptom onset,

and both the median and the tibial nerve SERP need to be

considered when investigating SERP in pre-HD.

In summary, SERP studies in HD consistently show

amplitude reductions of early components with significant

correlations with CAG repeats and cognitive and behavioral

symptoms. Based on preliminary data of early SERP changes

prior to disease onset (Beniczky et al., 2002) and longitudinally

(Ehle et al., 1984; Lefaucheur et al., 2006), SERP shows promise

as a potential biomarker of bothdiseaseonsetand progression.

5. Movement-related potentials inHuntington's disease

Motor disturbance is a hallmark of HD, and analysis of

movement-related potentials (MRPs) enables the temporal

breakdown of cortical activity involved in both movement

preparation and execution (Colebatch, 2007). MRPs associated

with movement preparation, performed, and imagined move-

ments were significantly reduced in HD compared to controls in

a simple sequential finger-tapping task guided by visual cues

( Johnson et al.,2001). No differences were foundwith movement

execution, suggestive of normal primary motor cortex activity.

Based on these results, the authors supported the proposal by

Thompson et al.(1988) andPhillips et al.(1994) thatitmaybethe

construction of the motor program for a particular movement

ratherthan theproduction of theactual movement itself,which

is affected in HD. Interestingly, Johnson et al. (2002) found that

withan attentional strategyto internallytime andanticipatethe

extinction of the cue, there wasa significant increase in the pre-

movement activity in both HD and control groups. Without the

attentional strategy, the control group, but not the HD group,

stillproduced a rising pre-movement potential.The researchers

suggested that HD patients may have deficient automatic

control, reflected by a lack of pre-movement activity; the

strategy may serve to place the task under attentional control.

Georgiou et al. (1997) also found that a concurrent task, during

performance of a kinematic task, was likely to evoke a strategy

which resulted in improved motor performance in HD com-

pared to when there was no concurrenttask.On theotherhand,

Beste et al. (2009a) found no differences in MRPs preceding the

motor response in HD and controls, suggesting that neurophys-

iological processes occurring during voluntary response execu-

tion are normal in HD. However, MRPs after the responsediffered dramatically between the groups. After the motor

response, HD participants, but not controls, produced a second

contralateral activation followed shortly by an ipsilateral

activation over the motor area, which is normally inhibited.

Only one study to date has investigated MRPs in pre-HD and

found that despite absence of behavioral differences from

controls, there was an increased inhibition of the ipsilateral

hemisphere during right hand movements (Beste et al., 2009a).

This positive MRP in the hemisphere ipsilateral to the effector

(in this case theright hand) is thought to reflectinhibition of the

alternative response, mediated by transcallosal fibers targeting

GABAergic interneurons (Daskalakis et al., 2002; Ferbert et al.,

1992). Pre-HD participants produced stronger inhibitory poten-

tials than controls for the right dominant hand, suggesting that

transcallosal inhibition and GABAergic neural transmission are

increased in pre-HD (Beste et al., 2009a). Moreover, pre-HD

individuals failed to exhibit a difference in reaction time

between hands, whereas in controls the reaction time of the

right hand was significantly shorter than that of the left hand

(right-handedness scores were also comparable with controls).

The authors proposed that compensatory processes in pre-HD,

mediated via adenosine receptors, may help to maintain a

normal level of task performance behaviorally. They explained

that adenosine A2A receptors are involved in the control of

movements (Chase et al., 2003; Svenningsson et al., 1999) and

increased activity of the adenosine receptor system may

stimulate GABAergic neurotransmission, leading to increased

inhibition of the ipsilateral hemisphere and symmetrical

pattern of reaction time. Indeed, several pieces of evidence

indicate that adenosine A2A receptors are implicated in HD

pathogenesis (fora review, seeChenet al., 2007and Popoli et al.,

2007). However, the roleof adenosine in compensatory process-

es is not clear, and further studies are needed to clarify the

complexities of adenosine A2A receptor pharmacology and its

relation to HD pathogenesis.

Closely related to MRPs is the contingent negative variation

(CNV),a steadypotential shift,thought to be related to sensory

motor integration and planning or execution of voluntary

movements (Andreassi, 2000). It is a slow negative potential

occurring between two successive but mutually associated

stimuli. De Tommaso et al. (2007) found that the early CNV

was reduced in amplitude in HD compared with controls; this

was accompanied by significantly prolonged reaction times.

No differences were found in the late CNV. The early CNV is

thought to be related more to attention and expectancy

stimulus processing, while the late CNV is perhaps associated

with cognition and motor preparation (Ikeda et al., 1997). The

amplitude reduction of early CNV correlated significantly with

delay in motor responses and bradykinesia. Based on these

findings, the authors suggested that motor impairments in HD

may be linked to a deficit in attention to external stimuli

rather than a problem with motor preparation.



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Dysfunction of motor regions and brain networks is

confirmed with postmortem studies (de la Monte et al., 1988;

Mann et al., 1993; Macdonald and Halliday, 2002; Diprospero et

al., 2004), MRI (Rosas et al., 2008; Bigland et al., 2009;

Peinemann et al., 2005), PET (Bartenstein et al., 1997) and

TMS (Nardone et al., 2007; Schippling et al., 2009), with strong

evidence that degeneration occurs early and progressively

increases with disease severity (Rosas et al., 2008). Althoughfewer in number, similar motor dysfunctions have been

reported in pre-HD using fMRI (Kloppel et al., 2009), TMS

(Schippling et al., 2009),PET(Feigin et al., 2006), and DTI (Rosas

et al., 2006). MRPs indicate abnormalities prior ( Johnson et al.,

2001) and subsequent to (Beste et al., 2009a) hand movements.

However, motor impairments have also been attributed to

dysfunction of attention (de Tommaso et al., 2007; Johnson et

al., 2002). These results suggest that motor dysfunction in HD

is complex and involves multiple facets, likely also to depend

on stage of disease. In pre-HD, further cross-sectional and

longitudinal MRP studies are needed.

6. Long-latency potentials inHuntington's disease

Long-latency potentials take more time to develop than sensory

and motor potentials and are strongly influenced by subjective

factors (Andreassi, 2000). One of the most commonly investi-

gated long-latency potentials is the P3. The P3 potential has

been associated with a variety of cognitive processes related to

information processing, including decision making, signal

probability, context updating, attention, discrimination, uncer-

tain resolution, stimulus relevance, and information delivery

(Andreassi, 2000). Using oddball paradigms, whereby a target

stimulus is presented amongst more frequent standard back-

ground stimuli, several studies have found HD patients were

significantly delayed in P3 latencies to auditory (Filipovic et al.,

1990; Goodin andAminoff,1986;Homberg et al.,1986; Rosenberg

etal., 1985)andvisual(Rosenberget al.,1985) stimuli,even in the

absence of behavioral differences to controls (Rosenberg et al.,

1985). As discussed earlier, although significant differences

between HD and controls were found in AERP components,

Homberg et al. (1986) found that the difference between the

groupswas most markedfor theP3. This suggests that cognitive

processing of auditory stimuli is more strongly affected than

sensory processing. Less consistent data are available for

correlations of P3 to HD symptomatology. Homberg et al.

(1986) found that P3 latency was significantly correlated with

psychometric measures including selective attention, short-

term memory, and vulnerability to distraction. On the contrary,

Rosenberg et al. (1985) found that P3 latency did not correlate

with cerebral or caudate atrophy or abnormalities in neuropsy-

chologicaltesting.Movingaway fromoddball paradigms,Munte

et al. (1997) employed a visual search paradigm to better

correlate electrophysiological parameters with cognitive defi-

cits known to be affected in HD. HD patients were slower and

less accurate in responding to target stimuli and corresponding

electrophysiological data indicate the P3 for target stimuli were

attenuated in HD. The researchers suggested that HD patients

lack ability to move and engage the attentional spotlight across

the visual field.

The complexity of the P3 renders application to a variety of

parameters. Consistent with findings of olfactory impairment

inHD(Bacon Moore et al., 1999; Bylsma et al., 1997;Hamiltonet

al., 1999; Lazic et al., 2007;Moberg and Doty, 1997; Nordinet al.,

1995; Pirogovsky et al., 2007), Wetter et al. (2005) found a

significant delay of approximately 250 ms on the P3 compo-

nent of the olfactory ERP (OERP) in HD compared with controls,

confirming deficits in the ability to process and classifyolfactory stimuli. The delay of the P3 correlated with CAG

repeat length and UHDRS motor scores. As well as being more

robust than AERP latency, the P3 OERP latency delay was

substantially larger in effect size and more accurate at

classifying individuals with or without HD than psychophys-

ical and cognitive measures. The authors suggested that

compromise of the orbitofrontal cortex as the P3 OERP

abnormality was strongest at frontal sites. However, they did

not perform source localization techniques to confirm this.

MRI data indicate that olfactory deficits in HD were signifi-

cantly correlated with degeneration of the entorhinal cortex,

thalamus, parahippocampal gyrus, and caudate nucleus

(Barrios et al., 2007). These areas have been previously

shown to be involved in olfaction in healthy individuals

(Levy et al., 1997; Savic et al., 2000).

Similar P3 OERP deficits were also reported in pre-HD

patients who were on average 4.7 years from predicted likely

onset of diagnosis (Wetter et al., 2006, as cited in Pirogovsky et

al., 2007). Normal latencies were found for earlier sensory

OERP components, suggesting that cognitive processing of

olfactory stimuli deteriorates before sensory processing of

odors. Consistent with findings in symptomatic HD, Wetter et

al. (2006, as cited in Pirogovsky et al., 2007) found that OERP

amplitudes were strongly correlated to CAG repeats, particu-

larly at frontal electrode sites. The authors consequently

suggested that the olfactory deficits in pre-HD may be related

to dysfunction in the frontal cortex or in frontal–striatal

circuits.

The P3 has also been used to examine processes related to

inhibition in Go/No-go paradigms (Beste et al., 2008c). The go/

no-go paradigm involves a continuously presented series of

stimuli composed of frequent “go” cues to which participants

respond to as rapidly as possible and infrequent “no-go” cues

to which participants do not respond. No-go stimuli elicit a

fronto-central, negative–positive ERP complex, labeled as

Nogo-N2 and Nogo-P3 (Bokura et al., 2001; Falkenstein et al.,

1999). TheNogo-N2 is thought to be associated with pre-motor

inhibitory processes (Falkenstein et al., 1999) or conflict

processes (Nieuwenhuis et al., 2003) and the Nogo-P3 is likely

to be related to evaluation of the inhibitory processes (Band

and van Boxtel, 1999; Roche et al., 2005). In line with other

behavioral studies (Aron et al., 2003; Fielding et al., 2006), Beste

et al. (2008c) found HD participants to be significantly

impaired in their ability to inhibit responses compared to

controls. Corresponding electrophysiological data indicate

there was a strong selective attenuation of the Nogo-P3, but

notthe Nogo-N2, in HD compared to controls.Reduction of the

Nogo-P3 was found to correlate with CAG index, with higher

CAG repeat length associated with stronger attenuation of the

Nogo-P3. Consistent with reports of dysfunctional anterior

cingulate cortex (ACC) in HD (Bartenstein et al., 1997; Beste et

al., 2006, 2007; Reading et al., 2004; van Dellen et al., 2005 ),



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source localization suggests significant hypo-activations in

the prefrontal cortex and ACC (Beste et al., 2008c). As the ACC

and basal ganglia are intimately interconnected (Chudasama

and Robbins, 2006), Beste et al. (2008c) suggested that basal

ganglia damage may result in partial dysfunction of neural

circuits and subsequent impairment of ACC, leading to an

attenuated Nogo-P3 and not Nogo-N2. This is the only ERP

study addressing inhibitory processesin HD,and no studies todate have been conducted in pre-HD. Future electrophysio-

logical research in pre-HD is encouraged, with recent data

suggesting that pre-HD individuals may have a deficit in

inhibitory control, being on average three times more likely

than control participants to commit anticipation errors

(Farrow et al., 2007). In an fMRI study, automatic inhibitory

motor control in HD was related to significant modulation of

both the caudate and thalamus (Aron et al., 2003).

Several studies have shown electrophysiological differ-

ences related to processing of errors in HD compared to

controls (Beste et al., 2006, 2008a,b). Error processing is

reflected in the ERP error negativity (Ne) or error-related

negativity (ERN) (Falkenstein et al., 1999), which occurs as a

negative deflection just after an incorrect response. The Ne

has been hypothesized to reflect error detection (Falkenstein

et al., 1999; Leuthold and Sommer, 1999) and shown to depend

on the dopamine (DA) system and medial prefrontal areas,

particularly the ACC (for a review, see Holroyd and Coles,

2002). Holroyd and Coles (2002) propose that following an

error, in a reaction time task, the mesencephalic dopamine

system conveys a negative reinforcement learning signal to

the frontal cortex, where it generates the ERN by disinhibiting

the apical dendrites of motor neurons in theACC. Accordingly,

Schulz and colleagues have suggested that the responsesseen

in the dopamine neurons in prediction of the goodness of

ongoing events might serve as error signals (for a review, see

Schulz and Dickinson, 2000). Compared with controls and pre-

HD, symptomatic HD patients exhibited a reduction in Ne

amplitude for error trials, despite no significant differences in

false reaction time or frequency of errors (Beste et al., 2006,

2008d, 2009b). As HD is accompanied by alterations in the DA

system with a reduction in D1 and D2 receptor density (Pavese

et al., 2003) and as Ne is associated with the DA system, the

authors suggested impaired functioning of striatal DA system

to be a possible cause for Ne reduction in HD.

Contrary to findings in symptomatic HD, no amplitude

differences in Ne were found in pre-HD (Beste et al., 2009a).

Instead, data in pre-HD suggest a selective impairment in Ne.

The Ne consists of two subcomponents: error-specific moni-

toring at the cognitive level and motor response monitoring,

expressed via the delta frequency band and the theta frequent

band, respectively (Yordanova et al., 2004). Time-frequency

decomposition of the Ne revealed that the pre-HD group

showed a significant selective increase in power of the delta

band of the Ne compared to controls (Beste et al., 2007). No

differences were seen in the theta band. These results suggest

that pre-HD differed with respect to behavioral/cognitive

monitoring, but not in motor response monitoring compared

to controls.In line with studies from Predict-HD (Paulsen et al.,

2008), the authors found the increase in power in the delta

band of the Ne was stronger in those pre-HD participants with

an earlier estimated age of disease onset. Although the Ne has

been consistently shown to be reduced in amplitude in

symptomatic HD, no data are available on time-frequency

decomposition of Ne to enable cross-sectional examination of

Ne changes with disease progression.

Finally, the N400, an ERP related to memory processes,

particularly in the establishment and retrieval of memory

(Andreassi, 2000), is also affected in HD. Munte et al. (1997)

employed a word-recognition memory task in which partici-pants were required to decide whether the word was a first

presentation (new word) or a second presentation (old word).

HD participants showed recognition accuracy deficits as well

as reduction of the N400 component, suggesting that they

engaged in less semantic elaboration and integration. Another

closely related ERP is the P600, a measure of episodic memory

encoding, which are found to be affected in early stages of

cognitive impairment ( Jackson and Snyder, 2008) but has not

been investigated in HD.

7. Animal studies of HD and electrophysiology

Animal toxin and genetic models are crucial to the ongoing

investigation of HD pathogenesis as well as in the develop-

ment and implementation of treatments and novel therapeu-

tic strategies. Animal models include toxin models of HD, for

example, instrastriatal injection of quinolinic acid (QA) and

genetic models such as R6/2 transgenic mice and knock-in

mouse models (for a review, see Ferrante, 2009). EEG enables

understanding of neuronal information processing in HD mice

models, and there is ample published evidence of altered

electrophysiological processing in animal models of HD. A

complete review of EEG studies in animal studies is beyond

the scope of this review; however, a few studies will be

reviewed to highlightanother possible role of theutility of EEG

in HD research.

A number of studies usingR6/2 transgenic andHD knock-in

(KI) line have identified deficits in information processing at

the single-neuron and population levels. At the single-unit

level, R6/2, but not KI mice, showed significantly elevated

spontaneous firing rates and spike-train variability, an index

of overall activation, compared to wild-type controls, in

pyramidal neurons within the prefrontal cortex (Walker et

al., 2008) and in medium size spiny neurons (MSSNs) (Miller et

al., 2008). Reduced bursting, associated with information

transmission and synaptic plasticity (Lisman, 1997; Izhikevich

et al., 2003), was also noted in the R6/2 compared to wild-type

controls (Miller et al., 2008; Walker et al., 2008) and is

consistent with compromised cortical plasticity in HD (Cum-

mings et al., 2006, 2007; Crupi et al., 2008; Mazarakis et al.,

2005). The authors corroborate that abnormalities at the

single-unit level may reflect symptom severity since differ-

ences were only found in R6/2 mice, who exhibited robust

behavioral signs, and not KI mice who express relatively mild

behavioral signs (Ferrante, 2009). Both R6/2 and KI mice

exhibited impaired activity at the neuronal population level,

as indicated by reduced synchronous activity between simul-

taneously recorded neurons (Walker et al., 2008) and reduced

correlated spikes (Miller et al., 2008), suggesting reduced

functional connectivity of networks. As abnormalities were

consistent across both models, Miller et al. (2008) and Walker



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et al. (2008) suggested that activity at the population level is

perhaps more reflectiveof the underlying cellular pathologyof

HD than firing rate or bursting at the single-neuron level.

In line with the above electrophysiological abnormalities in

mice models of HD, increasing evidence supports that

dysfunction of MSSNs and corticostriatal inputs is likely to

trigger onset and progression of the behavioral phenotype in

HD (for a review, see Cepeda et al., 2007). Changes in neuronalpathways can be elucidated with EEG. One of the first signs of

corticostriatal dysfunction is that symptomatic R6/2 and

Tg100 transgenic mice require a significant increase in

stimulus intensity in order to evoke an excitatory post-

synaptic potential in MSSNs (Klapstein et al., 2001; Laforet et

al., 2001). In addition to alterations in evoked synaptic

responses, Cepeda et al. (2003) also report a transient and

progressive reduction in frequency of spontaneous excitatory

post-synaptic currents in striatal MSSNs in slices from R6/2

mice. The reduction was apparent with onset of overt

symptoms (5–7 weeks) and most pronounced in older mice

(11–15 weeks), when symptoms were severe. The authors

suggested a progressive disconnection between the striatum

and its cortical inputs (Cepeda et al., 2003).

Corroborating EEG findings in patients with HD, cortical

electrophysiological studies in the QA-lesioned rats report a

marked reduction in voltage amplitude in the frontal cortex

(Popoli et al., 1994). More recent reports indicate that

intrastriatal QA has specific alterations in relative EEG power

distribution in therat frontal cortexsimilar to that observed in

HD patients (Reggio et al., 1999). QA-lesioned rats showed

significant reduction in voltage amplitude and in total EEG

power, increased percent delta power, and decreased percent

alpha power. Reduced amplitude of parietal and frontal

somatosensory potentials has also been reported in QA-

lesioned rats (Schwarz et al., 1992). Taken together, these

findings support growing evidence that phenotypes from HD

mouse models closely correlate with human symptomatology

and offer new ways to validate biomarkers of disease onset,

progression, and effectiveness of CNS drug therapies. Cur-

rently very few affective and cognitive assessments have been

validated in mouse models. EEG and ERPs offer additional

measures of intracellular dynamics and neuronal and cortical

information processing in both human and animal models

which could help yield common biomarkers between species

of both disease onset and progression, invaluable for future

clinical drug trials.

8. Conclusions and future directions

Tables 1 and 2 report the key EEG and ERP measures and

deficits in symptomatic and pre-HD, respectively. In sum-

mary, EEG and ERP research to date has revealed sensory,

motor, and cognitive abnormalities in both pre-HD and

symptomatic HD. The majority of HD studies conducted

prior to localization of the Huntington gene in 1993

compared sensory ERPs and P3 potential using simple

oddball paradigms. Although these studies suggest sensory

and cognitive processing deficits in HD, the electrophysio-

logical data are extremely weak and inconsistent. Since

1993, most studies have utilized the sensitivity and speci-

ficity of EEG/ERP and have tended to focus on processes

known to be affected in HD. Consistent with what we know

about the HD phenotype as well as abnormalities noted from

neuroimaging studies, ERP data indicate auditory, visual,

somatosensory, and motor electrophysiological deficits.

Furthermore, specific cognitive dysfunction has been

reported in sensory motor integration, inhibitory processes,

processing of errors, and memory processes. Only eightstudies have been conducted to date in genetically con-

firmed pre-HD, indicating visual, somatosensory, and motor

electrophysiological abnormalities. Moreover, cognitive def-

icits have been reported in olfaction, error processing, and

working memory. One of the largest limitations of EEG/ERP

research in HD is that very few studies have replicated

abnormal findings, limiting reliability and generalizability of

results, and only two have employed a longitudinal design

(Ehle et al., 1984; Lefaucheur et al., 2006). Future studies need

to do much more than simply show significant differences

between groups; they should build and extend current

knowledge and investigate longitudinally the most sensitive

measures over sufficient time to track the utility of

electrophysiological measures as potential markers of dis-

ease onset and progression. Currently, comparisons across

studies are difficult due to lack of standardization in details

of patient information including CAG repeat length, duration

of disease, and medication status. Spectrum of the disease

varies across studies and may account for the mixed

findings. Severity (and/or stage) of disease must be clearly

defined since the degenerative process can span many years.

Moreover, EEG and ERP data are complex and often generate

a wealth of data. As such, standardized reporting of

equipment type, electrophysiological and statistical analy-

ses, and results are essential for comparison across studies.

Few studies have reported effect sizes which would facilitate

comparison among studies and help to identify robust and

reliable markers, and small sample sizes limit statistical

power. Better standardization of study protocol with much

larger sample sizes is required to better understand electro-

physiological abnormalities in pre-HD and symptomatic HD.

Of the key measures listed in Tables 1 and 2, several

variables show substantial sensitivity to quantify manifest

disease. We recommend that the following should be priori-

tized for longitudinal research in pre-HD as these measures

show potential as reliable and sensitive measures of disease

onset and progression.

1) Somatosensory ERPs. In line with MRI (Rosas et al., 2008)

and PET (Boecker et al., 1999) studies, SERP studies

consistently show amplitude reductions of early compo-

nents which significantly correlate with CAG repeats and

cognitive and behavioral symptoms. Preliminary studies in

pre-HD individuals suggest early SERP changes prior to

disease diagnosis.

2) Olfactory P3. Olfactory deficits in HD have been confirmed

with MRI (Barrios et al., 2007). The olfactory P3 had the

largest effect size and was more robust than other

electrophysiological, psychophysical, and cognitive mea-

sures(Wetter et al., 2005). Similar P3 OERP deficits were also

reported in pre-HD (Wetter et al., 2006, as cited in

Pirogovsky et al., 2007).



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3) Error negativity—

Ne. A number of studies consistentlyshow reduced amplitude of the Ne potential in HD during

processing of errors (Beste et al., 2006, 2008a, 2009b). Subtle

deficits have also beendemonstrated in pre-HD individuals

(Beste et al., 2009a).

4) Movement-related potentials and CNV. MRPs have been

shown to be abnormal in both symptomatic ( Johnson et al.,

2001; Beste et al., 2009a,b) and pre-HD(Beste et al., 2009a,b).

Sensory motor integration via the CNV is also worth

exploring to ascertain possible mechanisms of motor

dysfunction in HD.

5) Quantitative EEG at rest and during cognitive processing.

Abnormalities in QEEG (particular alpha power) are

reported in both pre-HD and symptomatic HD (Bellotti etal., 2004; Bylsma et al., 1994; de Tommaso et al., 2003;

Streletz et al., 1990), with suggestions of a compensatory

network in pre-HD during a working memory task (van der

Hiele et al., 2007). Further research is needed to clarify the

utility of EEG during manifestation and progression as well

as its phenomenology during other cognitive, motor, and

psychomotor functioning.

Despite the recommendations, it should be noted that

there are a number of other electrophysiological parameters

yet to be explored in HD, such as for example time course of

emotional processing; this will help to clarify behavioralreports of impaired emotional recognition ( Johnson et al.,

2007).

The studies summarized in this review highlight for the

first time the potential of EEG and ERP measures as possible

biomarkers in HD. Michell et al. (2004) recommend a list of

ideal biomarker characteristics, for example, that the bio-

marker should have first degree association with the clinical

trait, that it should be sensitive to reflect small changes, and

relatively cheap and non-invasive (for a comprehensive

review, see Michell et al., 2004). In line with Michell et al.'s

(2004) recommendations, EEG is a direct measure of brain

activity, without reliance on intermediate variables, and

minimizes risk of secondary variables. It has millisecondtemporal resolution which can sensitively reflect even small

changes in disease phenotype. It is inexpensive, non-invasive,

and available in many hospital and research centers world-

wide. Importantly, in thecontextof HD,EEG andERP measures

could serve as potential biological biomarkers to quantify

onset of manifest disease and monitor rate of progression and

clinical response to therapeutic intervention. Each of these

will be discussed in turn. Firstly, in animal models, EEG can

elucidate changes of intracellular dynamics at the single-

neuron level, functional connectivity of networks and neuro-

nal pathways. Further research into neuronal information

Table 2 – Key EEG and ERP markers and findings in pre-diagnostic HD with references.

EEG/ERP makers Key Findings Key references

EEG Alpha power (resting state) Suppression of alpha activity de Tommaso et al. (2003)

Alpha power (during working memory) Reduction of alpha activity

during working memory

van der Hiele et al. (2007)

Visual ERP N1 Reduced amplitude Beste et al. (2008b)

Somatosensory ERP Early SERP components Reduced amplitude of the

tibial SERP components

Beniczky et al. (2002)

Movement-related potentials MRPs after the response Increased inhibition of the

ipsilateral hemisphere

Beste et al. (2009a,b)

Long-latency potentials P3 (olfactory) Delay of approximately 250 ms Beste et al. (2009a,b)

Ne (error processing) Increase in power of the delta band Beste et al. (2007)

Table 1 – Key EEG and ERP markers and findings in symptomatic HD with references.

EEG/ERP makers Key findings Key references

EEG Alpha power (resting state) Suppression of alpha activity Bellotti et al. (2004); Bylsma et al. (1994);

de Tommaso et al. (2003); Streletz et al. (1990)

Auditory ERP P50 potential Reduced amplitude and

prolonged latency

Uc et al. (2003)

Visual ERP N1 Reduced amplitude Antal et al. (2003); Beste et al. (2008b)

Somatosensory ERP Early components Reduced amplitude Ehle et al. (1984)⁎ Lefaucheur et al. (2002, 2006)⁎

Movement-related potentials Movement preparation Reduced amplitude Johnson et al. (2001)

Potentials after the response Lack of inhibition Beste et al. (2009a,b)

Long-latency potentials Contingent negative variation Reduced amplitude De Tommaso et al. (2007)

Olfactory P3 Significant delay of

approximately 250 ms

Wetter et al. (2005)

No-go P3 (inhibitory processes) Reduced amplitude Beste et al. (2008d)

Ne (error processing) Reduced amplitude Beste et al. (2006, 2008a, 2009)

N400 (memory processes) Reduced amplitude Munte et al. (1997)

⁎ Longitudinal study.



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processing is essential as there is increasing evidence for

dysfunction of neurons and neuronal circuits that precede

symptoms (Cepeda et al., 2007). In humans, ongoing EEG and

averaged ERPs can provide millisecond data on changes in

time course of information processing with onset of manifest

disease. Importantly, like fMRI, both EEG and ERP can be used

to elucidate processing specific to sensory, motor, and

cognitive processes which may be more sensitive to theearliest changes in HD. Secondly, the powerful time resolution

of EEG/ERP enables detection of subtle abnormalities in pre-

HD which could be used as a tool to monitor rate of disease

progression. Only two ERP studies have been conducted

longitudinally; both corroborate that somatosensory ERPs

progressively deteriorate over time and correlate with disease

severity (Ehle et al., 1984; Lefaucheur et al., 2006). Finally,

electrophysiological biomarkers can also be applied to mon-

itor clinical responses to therapeutic intervention. For exam-

ple, improvements of somatosensory ERPs have been found in

small preliminary clinical drug trials (Bachoud-Levi et al.,

2000; Bloch et al., 2004). These studies indicate that ERP

measures change linearly with clinical stability of symptoms

following treatment. Furthermore, increasing studies indicate

that the loudness-dependent auditory ERP and resting state

QEEG can help identify particular medications that are most

likely to lead to a response and/or remission in major

depression (for a review, see Leuchter et al., 2009). However,

before this is possible in HD, more studies are required to

validate, clarify consistency, reliability, and replicability of

these markers in order to better understand the pattern of

electrophysiological deterioration over time and with treat-

ment. At present, existing clinical drug trials in manifest HD

disease (for reviews, see Mason and Barker, 2009; Mestre et al.,

2009) are currently based on changes over time in the total

functional capacity (TFC) score (Shoulson, 1981). We urgently

require morereliableand sensitive biomarkers of disease onset

and progression, and with much better statistical properties

thanthe TFCscore.Currently,however, there areveryfew EEG/

ERP longitudinal studies in manifest HD. This makes it

challenging to recommend, or make an estimate, as to which

measure/method, as described in this review, would yield the

most promising properties that would make it more sensitive,

less variable, and/or show greater magnitude of change over

time than the current TFC score. We do however recommend

that in order to derive a better measure, future planning of

longitudinal study designs should, as the first requirement,

perform effect size analyses on existing cross-sectional EEG

data to determine which measure/s yields the highest effect

size between groups; these measure/s could then be incorpo-

rated into large-scale longitudinal studies to ascertain the

most sensitive and reliable biomarker of progression.

There is great variability in the expression of even the most

characteristic features of HD. Specific clinical, behavioral, and

biological biomarkers of disease phenotype with concomitant

underlying neurophysiology may be required at all stages of

disease. For example, the temporal variability in activation

patterns may indicate critical points during the pre-HD neuro-

degenerative process, involving the onset or worsening of more

than one pathological process (e.g., axon or myelin degenera-

tion, neuronal dysfunction or death) that could potentially be

captured with electrophysiological techniques (Bohanna et al.,

2008; Georgiou-Karistianis, 2009). The wide range of ERP

parameters is well suited to investigating subtle and specific

dysfunctions in HD across a number of domains. A noteworthy

advantage of EEG/ERP is its ability to be applied to both humans

and animals, enabling parallel investigation across species.

A common limitation of current EEG/ERP research is the

difficulty determining the exact locations of cortical genera-

tors from the scalp data. A new approach, which may help toovercome this limitation, is the combination of EEG/ERP

simultaneously with fMRI (for a review, see Mulert et al.,

2008). Simultaneous acquisition of both EEG and fMRI is now

gradually more accessible (Bregadze and Lavric, 2006; Debener

et al., 2005; Eichele et al., 2005); however, the acquisition of

ERPs concurrent with fMRI in cognitive paradigms is yet to be

explored in HD. These methods will enable enhanced infor-

mation on spatial localization of brain structures as well as

precise time course of neural activity in HD. This will not only

accelerate our understanding of mechanisms associated with

disease onset and progression but could also identify sensitive

biomarkers to test efficacy of therapeutic intervention.

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