- Email: [email protected]
Reduced brain electric activities of frontal lobe in cortical cerebellar atrophy
Clinical Neurophysiology 114 (2003) 740–747 www.elsevier.com/locate/clinph
Reduced brain electric activities of frontal lobe in cortical cerebellar atrophy Mio Araia,*, Hideaki Tanakaa, Roberto D. Pascual-Marquib, Koichi Hirataa a
Department of Neurology, Dokkyo University School of Medicine, Kitakobayashi 880, Mibu, Tochigi 321-0293, Japan b The KEY Institute for Brain–Mind Research, University Hospital of Psychiatry, Zurich, Switzerland Accepted 9 December 2002
Abstract Objective: To assess the relationship between cerebellum and brain cortical activity without motor factors, we recorded the mid-latency auditory evoked responses (MLRs) with simultaneous recording of the electroencephalography (EEG) at rest in patients with ‘pure cortical cerebellar atrophy (CCA)’. Methods: We studied 12 normal control subjects and non-demented ‘pure CCA’ patients determined by quantitative magnetic resonance imaging analysis. A comprehensive neuropsychological test battery assessed intelligence, frontal lobe function and word fluency. Spontaneous eyes-closed resting EEG and MLRs were recorded from 20 scalp electrodes and analysed with low-resolution electromagnetic tomography (LORETA) to compute the 3-dimensional intracerebral distribution of electric activity. Results: Neuropsychological tests revealed no differences between CCA and the control. Analysis of EEG and MLRs using classical methods also did not reveal any differences. LORETA analysis indicated significant decrease of alpha2 activity in the left inferior frontal gyrus in CCA. On MLRs, the most significant difference was observed at P1 component, and CCA patients showed significant decrease at the right superior frontal gyrus. Conclusions: Our results indicated that the frontal lobe and ascending reticular activating system are inhibited in CCA patients, and suggested the involvement of the cerebellum in cortical electric activities irrespective of motor adjunct. Significance: Quantitative EEG and MLR measurements with LORETA pointed out frontal lobe hypoactivities in pure CCA patients. q 2003 International Federation of Clinical Neurophysiology. Published by Elsevier Science Ireland Ltd. All rights reserved. Keywords: Electroencephalography; Mid-latency auditory evoked responses; Low-resolution brain electromagnetic tomography; Cerebellum; Frontal lobe; Cognitive function
1. Introduction The cerebellum has long been known as a structure involved in motor coordination. However, in the mid-1980s, anatomical, behavioural, and, neurophysiological evidence emerged suggesting the involvement of the cerebellum in cognitive function in addition to motor function. Leiner et al. (1986) reviewed the potential roles of the cerebellum in cognition and hypothesized cerebellar projections to prefrontal and other associated cortices in humans. Schmahmann and Sherman (1998) defined the ‘cerebellar cognitive affective syndrome’ based on the analysis of 20 patients with diseases confined to the cerebellum. This syndrome is characterized by impairment of executive * Corresponding author. Tel.: þ81-282-87-2152; fax: þ 81-282-86-5884. E-mail address: [email protected] (M. Arai).
functions, such as planning, set shifting, verbal fluency, abstract reasoning and working memory. On the other hand, Middleton and Strick (1994) suggested that cerebellar output projects via the thalamus to multiple cortical areas, including premotor and prefrontal cortex, as well as the primary motor cortex. They also suggested that neuronal activity within the basal ganglia and cerebellar loops with areas of the prefrontal cortex is related to various aspects of cognitive function. Furthermore, in functional neuroimaging studies such as positron emission tomography (PET) and functional magnetic resonance imaging (MRI), cerebellar activation is often evident in tests of cognitive planning (Kim et al., 1994), shifting attention (Allen et al., 1997) and sustained attention (Pardo et al., 1991). Patients with spinocerebellar degeneration (SCD) may exhibit cognitive impairment. However, there is controversy on whether patients with SCD have cognitive dysfunctions
1388-2457/03/$30.00 q 2003 International Federation of Clinical Neurophysiology. Published by Elsevier Science Ireland Ltd. All rights reserved. doi:10.1016/S1388-2457(02)00423-6
CLINPH 2002160
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
specifically related to the frontal lobe or have cognitive deficits secondary to motor dysfunction. A number of reports indicated that SCD, including olivopontocerebellar atrophy (OPCA), produces cognitive impairment, suggesting possible effect of brainstem atrophy. Grafman and Litvan (1992) reported that patients with ‘pure’ cortical cerebellar atrophy (CCA) performed significantly worse than normal subjects on the Tower of Hanoi task, which required cognitive planning. On the other hand, Daum et al. (1993) showed that there were no significant differences between patients with restricted cerebellar damage and normal subjects on the Wechsler Adult Intelligence ScaleRevised (WAIS-R) and Wisconsin Card Sorting Test (WCST). In the present work, we studied only patients with CCA among patients with SCD, as determined by quantitative MRI analysis, because our aim was to determine the profile of cognitive dysfunction in cerebellar atrophy itself. Previous studies used functional neuroimaging or neurophysiological analysis for the evaluation of cognitive dysfunction in patients with SCD (Tachibana et al., 1995; Kamitani et al., 1998; Yamaguchi et al., 1998). In this regard, neurophysiological studies, especially event-related potentials, are widely used for evaluation of cognitive impairment in patients with neurodegenerative disorders such as Alzheimer’s disease and Parkinson’s disease. However, assessment of cerebellar function related to cognition using tests that do not involve motor function is difficult. In order to avoid any type of motor involvement in the testing procedure, we used the mid-latency auditory evoked responses (MLRs), which are independent of motor function, with simultaneous recording of the electroencephalogram (EEG) at rest.
2. Materials and methods 2.1. Subjects We studied 12 patients with CCA and 12 age-, sex- and education-matched normal controls (Table 1). All CCA patients satisfied following criteria: (1) the primary symptom was that of cerebellar ataxia without pyramidal signs, extrapyramidal signs, or autonomic nervous dysfunction; (2) cerebellar atrophy without brainstem atrophy was confirmed by neuroimaging, and no abnormal signs within cerebral and other brain structures were observed; (3) other causes of cerebellar atrophy were excluded, including longterm alcohol addiction, anticonvulsant poisoning, hypothyroidism, and malignant tumours; (4) absence of a positive family history. Normal control subjects represented healthy individuals who visited our clinic for routine medical check ups and were found to be free of any neurological and psychiatric diseases. Furthermore, neurological examination, including MRI, was normal in these subjects. Neither the control subjects nor CCA subjects were taking any
741
Table 1 Characteristics of subjects participating in this study
N Sex (male/female) Age (years) Duration of disease (years) Duration of education (years) MMSE score WCST score CA PEN WAIS-R score VIQ PIQ TIQ VF score Letter Category
CCA
NC
P value
12 7/5 61.1 ^ 9.0 13.2 ^ 8.0 11.4 ^ 3.3 27.8 ^ 2.2
12 7/5 60.6 ^ 7.7 – 11.9 ^ 2.4 29.1 ^ 1.0
– – 0.89 – 0.71 0.18
3.6 ^ 2.4 6.1 ^ 6.6
3.8 ^ 1.0 4.7 ^ 2.1
0.90 0.57
103.0 ^ 11.8 90.5 ^ 11.2 97.8 ^ 12.7
100 ^ 15 100 ^ 15 100 ^ 15
– – –
20.4 ^ 8.8 40.8 ^ 12.2
23.0 ^ 5.6 48.5 ^ 9.8
0.41 0.12
Patients with cortical cerebellar atrophy (CCA) and normal control (NC) subjects were matched for age, sex and education. Data are mean ^ SD. VF, verbal fluency task. There were no significant differences in MMSE, WCST, WAIS-R and VF task scores between CCA and NC.
central nervous system (CNS)-active drugs at the time of testing. All subjects were right handed, and clinically nondemented having score 24 or above in Mini-Mental State Examination (MMSE) (Folstein et al., 1975). All CCA patients were able to walk without assistance. We studied all subjects after obtaining informed consent. 2.2. Psychological testing The Japanese version of the MMSE (Mori et al., 1985), WAIS-R (Wechsler, 1981; Shinagawa et al., 1990), the new modified WCST (Kashima et al., 1985) and the verbal fluency task (Lezak, 1983) were employed for comprehensive assessment of cognitive function. The test batteries have been used in many clinical areas in Japan and their reliabilities have been confirmed. The results of WAIS-R were expressed in 3 forms of intelligence quotients (IQ): verbal IQ (VIQ), performance IQ (PIQ), and full-scale IQ (FIQ). We adopted standard score (mean ¼ 100, SD ¼ 15) as for IQ scores of normal controls (Wechsler, 1981, Shinagawa et al., 1990). The original WCST developed by Milner (1963) is one of the few tests that detect a clear deficit specific to patients with frontal lobe dysfunction; however, it is too difficult and distressing for many patients. Therefore, a simpler and less ambiguous modification was made. The two main modified points were the order of the reaction cards and the process of providing necessary instructions. This new version has been used successfully in Japan. To evaluate this test, the maximum classification score and the preservative errors reported by Nelson (1976) were used. We also used the verbal fluency task, which has been confirmed to be a sensitive indicator of frontal lobe dysfunction. The patients were instructed to say as many
742
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
words as they could think of that began with a given kana (Japanese syllabic alphabet) letter, and the number of words produced in 120 s for each letter of two letters was recorded. The score was the total number of acceptable words produced during 4 min. The patients were also asked to generate as many words belonging to two categories (‘animal’ and ‘in a house’) as they could think of each 120 s. The total numbers of two sessions were accepted as the score.
the cerebellum and pons. (2) Maximal width of the frontal horns of the lateral ventricles (A) and frontal width (B) at the caudate nuclei plane on the axial image (Estruch et al., 1997) (Fig. 1). The ratio (A/B) represented the frontal lobe index, a measure of frontal lobe atrophy (Estruch et al., 1997). Each image was digitized using a scanner (EPSON2200, Japan) and analysed quantitatively with the Osiris software (Ligier et al., 1994). 2.4. Brain electric recordings
2.3. Neuroradiology A brain MRI scan was performed at Dokkyo University using a General Electric MR scanner (Milwaukee, WI, USA) with either a 1 or 1.5 T magnet. The T1-weighted images were obtained from the axial and sagittal planes (spin echo, TR ¼ 600 ms, TE ¼ 15 ms, slice thickness 7.5 mm), while the T2-weighted images were obtained from the axial planes (spin echo, TR ¼ 3800 ms, TE ¼ 110 ms, slice thickness 7.5 mm). To measure the degree of atrophy (Table 2) in the cerebellum and its related structures, the following morphometric parameters were measured with T1-weighted images: (1) Areas of the cerebellar vermis, the posterior fossa which is delineated by the tentorium cerebelli and the inner counter of the skull, and the basis pontis on the mid-sagittal image (Nabatame et al., 1988) (Fig. 1). The measured areas of the cerebellar vermis and the basis pontis were divided by the measured area of the posterior fossa to evaluate the relative atrophy of Table 2 The degree of atrophy measured by MRI, global field power (GFP), which represents the generalized EEG amplitude of 7 EEG frequency bands, the peak amplitude and the peak latency for MLRs components
CAI (ratio) PAI (ratio) FLI (ratio) EEG GFP Delta Theta Alpha 1 Alpha 2 Beta 1 Beta 2 Beta 3 MLRs GFP Peak amplitude Pa Nb P1 Peak latency (ms) Pa Nb P1
CCA
NC
P value
0.24 ^ 0.05 0.10 ^ 0.01 0.35 ^ 0.03
0.34 ^ 0.05 0.11 ^ 0.01 0.34 ^ 0.03
,0.01* 0.10 0.58
1.41 ^ 0.46 1.26 ^ 0.69 2.34 ^ 1.14 2.13 ^ 1.56 0.85 ^ 0.29 0.71 ^ 0.22 0.43 ^ 0.11
1.30 ^ 0.24 1.09 ^ 0.24 1.73 ^ 0.52 1.84 ^ 0.93 0.88 ^ 0.28 0.69 ^ 0.16 0.46 ^ 0.11
0.52 0.42 0.11 0.57 0.79 0.83 0.59
0.95 ^ 0.37 0.93 ^ 0.60 0.96 ^ 0.58 36.3 ^ 3.28 47.4 ^ 3.43 66.8 ^ 7.22
0.96 ^ 0.44 0.94 ^ 0.51 1.02 ^ 0.52 34.6 ^ 1.91 47.0 ^ 2.73 68.3 ^ 4.08
0.93 0.96 0.79 0.14 0.77 0.56
Data are mean ^ SD. CAI, cerebellar atrophy index; PAI, Pontine atrophy index; FLI, frontal lobe index. *CAI was significantly reduced in patients with CCA but there were no significant differences PAI and FLI compared with NC. There were no significant differences in GFP of EEG, MLRs.
Subjects lied down on a bed in a sound-attenuated and dimly lit Faraday room. The brain electric data were recorded (Bio-logic Brain Atlas, 0.53 – 30 Hz bandpass) with silver/silver chloride EEG electrodes attached with paste to 20 locations of the international 10/20 system (Fp1/2, Fz, F3/4, F7/8, T3/4, C3/4, Cz, P3/4, Pz, T5/6, O1/2, Oz) using an electrode attached to the earlobe as reference. Electrode impedance was maintained below 5 kW. The recording was performed at 2:00 pm in all subjects to exclude the effects of circadian rhythm. The subjects were asked to relax and close their eyes. This was followed by 5 min recording of spontaneous EEG (128 samples/s), which was monitored visually. After recording, EEG records in epochs of 2 s were carefully inspected for movement, eye and muscle artefacts. The first 20 accepted 2 s epochs were analysed for each subject. For the MLRs measurement, 80 dB clicks at one per second were presented as a sequence of binaural stimuli via earphones and 250 artefact-free stimuli were averaged in each session. The MLRs over 128 ms post-stimulus were averaged on-line (2000 samples/s), using an automatic artefact rejection criterion (for signals with amplitude higher than 136 mV). The MLRs of the two sessions were averaged. All accepted EEG and MLRs data were off-line digitally filtered to 1.5– 30 Hz using a fast Fourier transform (FFT) bandpass. For eye movement rejection, a spatial filtering procedure was employed that removed those spatial principal components of the data that showed a correlation coefficient (r) better than ^ 0.75 with an eye movement template consisting only of activity in the two prefrontal channels Fp1 and Fp2. 2.5. Data analysis Absolute power values at Oz (referenced to linked earlobes) for 7 EEG frequency bands: delta (1.5 – 6.0 Hz), theta (6.5 – 8.0 Hz), alpha1 (8.5 – 10.0 Hz), alpha2 (10.5 – 12.0 Hz), beta1 (12.5 –18.0 Hz), beta2 (18.5 – 21.0 Hz), and beta3 (21.5 – 30.0 Hz) were determined (Kubicki et al., 1979) by FFT and compared between the two groups. For a comprehensive assessment of the 20-channel EEG data, the single global field power (GFP) (Lehmann and Skrandies, 1980) curve was computed for each 2 s epoch. The GFP curves were subjected to conventional power spectral analysis using a Hanning Window, and a mean spectrum
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
743
Fig. 1. Schematic diagram and a representative MRI T1-weighted image demonstrating measurements of brain structures and evaluation of the degree of atrophy.
was computed for each subject over all 20 data epochs. Integrated power was computed for the 7 frequency bands. For the MLRs, latencies and amplitudes of Pa, Nb and P1 components at Cz (referenced to linked earlobes) were measured and compared between the two groups. For each time point of the multichannel data, the amplitude and peak latency of GFP were computed, resulting in a single curve of GFP for each 20-channel ERP average. 2.6. Spatial analysis Low-resolution brain electromagnetic tomograph (LORETA) (Pascual-Marqui et al., 1994, 1999) was used to compute the 3-dimensional intracerebral distribution of electric activity of EEG and MLRs. LORETA determines the distribution of generator activity in the cortex, i.e. it produces an activity strength value for each of many voxels, while employing no constraints on the number of model sources. LORETA solves the so-called inverse problem without a priori knowledge of the number of sources, but applies the constraint of maximal smoothness of the solution. Hence, LORETA results show maximally similar activity in neighbour voxels, consistent with the known electrophysiology of synchronized activity in neighbouring neurons. The LORETA computation determines current density at each voxel as the linear weighted sum of the scalp electric potentials. The results were computed for the cortical areas of the Talairach probability atlas (Talairach and Tournoux, 1988), with a spatial resolution of 7 mm. 2.7. Statistical analysis Differences in parameters derived from EEG, MLRs, psychological tests and neuroradiological measurements were examined for statistical significance using the unpaired
sample t test. These descriptive P values were considered relevant if they appeared in nearly regular patterns associated with numerically relevant differences. Data are expressed as mean ^ SD. LORETA voxel-by-voxel paired t test using non-parametric randomisation tests with correction for multiple testing was used for differences in the regional distribution of activity between conditions. Images were displayed with results of t test analysis and the corrected thresholds were shown in 3 orthogonal brain slices (horizontal, sagittal, coronal). In these images, red colour represents increased activation and blue colour represents reduced activation of CCA compared to the normal subjects.
3. Results WAIS-R was not significantly decreased in CCA patients (IQ: more than 80). Furthermore, scores of WCST and verbal fluency test of patients with CCA were not significantly different from those of the control (Table 1). MRI images showed no abnormal intensity areas within the cerebellum, brainstem and other structures of the brain. The relative area of the cerebellum in the patients was significantly smaller than that of the control subjects although there was no significant difference of the relative area of the pons and frontal lobe index (Table 2; Fig. 2). Atrophy was limited to the cerebellum in CCA patients. The EEG at Oz and the mean brain topography maps showed no significant differences between patients with CCA and control. In addition, GFP for each of the 7 frequency bands was not significantly different between the two groups (Table 2; Fig. 3). However, LORETA analysis indicated significant decrease of alpha2 activity (P ¼ 0:006) in the left inferior frontal gyrus centering around Brodmann area 45, where is frontal operculum of prefrontal cortex, in
744
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
Fig. 2. The degree of atrophy measured by MRI. The relative area of the cerebellum (CAI) was significantly reduced in patients with cerebellar cortical atrophy (CCA) but there were no significant differences in the pons (PAI) and frontal lobe index (FLI) compared with the control (NC). This indicates that atrophy is limited to the cerebellum in patients with CCA. Data are mean ^ SD.
patients with CCA compared with the control (Fig. 4). With respect to MLRs, the latencies and amplitudes of each component at Cz and GFP were not significantly different (Table 2; Fig. 5A,B). LORETA-based comparisons, on a timeframe-by-timeframe basis, were performed on the MLRs. The most significant difference was observed at 64 ms after stimulus presentation, corresponding to the P1 component. CCA patients showed significant decrease (P ¼ 0:04) in the right superior frontal gyrus centering around Brodmann area 9, where is lateral dorsal area of prefrontal cortex, compared with control (Fig. 4).
4. Discussion Recent studies have indicated the involvement of the cerebellum in cognitive function in addition to its wellknown role in motor function. Employing various neuropsychological tests, previous reports described impairment of generalized intellect, spatial cognition and frontal lobe function in patients with cerebellar degeneration and atrophy (Wallesch and Horn, 1990; Hirono et al., 1991; Grafman and Litvan, 1992; Appollonio et al., 1993; Kish et al., 1994; Drepper et al., 1999). There is controversy on
Fig. 3. Global field power (GFP), which represents the generalized EEG amplitude of 7 EEG frequency bands. There were no significant differences between patients with CCA and NC. Data are mean ^ SD.
whether patients with SCD have cognitive dysfunctions specifically related to the frontal lobe or have cognitive deficits secondary to motor dysfunction. Many studies are based on single case or very small samples that often include patients with extracerebellar damage, such as patients with Friedreich’s ataxia or OPCA. For example, it is well known that OPCA may be associated with a mild form of dementia, which is characterized by a range of cognitive deficits that are related to the severity of the illness (Leiner et al., 1986; Matthew et al., 1993). In the present work, we limited our study to patients with ‘pure CCA’ as confirmed by quantitative MRI analysis because we wanted to determine the profile of cognitive dysfunction in cerebellar atrophy itself. In previous studies that were also limited to patients with pure cerebellar dysfunction, Drepper et al. (1999) compared the performance of patients with idiopathic cerebellar ataxia in a cognitive associative learning task with control subjects. In their study, such patients were found to have a specific deficit and the results suggested that the cerebellum might contribute to motorindependent processes that were generally involved in associative learning. Furthermore, Grafman and Litvan (1992) reported that patients with ‘pure CCA’ performed significantly worse than normal subjects on the Tower of Hanoi task, which requires cognitive planning. They concluded that the cerebellum played an important role in executive functions such as cognitive planning, and suggested the presence of a functional link between the cerebellum, basal ganglia, and the frontal lobe for specific cognitive processes. On the other hand, Daum et al. (1993) reported that patients with damage to both cerebellum and brainstem, but not those with cerebellar pathology alone, showed memory impairment and poor performance in visuoconstructive tasks, related to frontal lobe dysfunction. Their study showed that there were no significant differences between patients with limited cerebellar damage and normal subjects on the WAIS-R and WCST. The results of the above studies were similar to those of our neuropsychological tests. Assessment of cerebellar function related to cognition using tests that do not require motor function is difficult. In this study, we avoided such motor involvement by recording MLRs and EEG under resting conditions independent of motor function. The majority of previous studies reported no EEG abnormalities in SCD patients (Brown, 1959; Liversedge and Emery, 1961). However, not all studies performed quantitative EEG analysis. In addition, there are only a few reports of EEG in SCD after MRI became commonly used, and hence diagnosis in these studies depended on old classification (Brown, 1959; Liversedge and Emery, 1961). Our quantitative evaluation successfully detected differences between patients with CCA and control subjects. Normal awake, eyes-closed, alpha activity is associated with automatic, routine functioning (PascualMarqui et al., 1999; Frei et al., 2001). The observed decrease in alpha2 activity seems to signify cortical
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
745
Fig. 4. LORETA. The third row shows t-statistics images with corrected thresholds, shown in 3 orthogonal brain slices (horizontal, sagittal, coronal). Red colour represents increased activation and blue colour represents decreased activation in patients with CCA compared with NC. CCA showed significantly decreased activation in the alpha2 band (P ¼ 0:006) in the left inferior frontal gyrus centering around Brodmann area 45. Furthermore, MLRs at 64 ms revealed significant decrease (P ¼ 0:04) at right superior frontal gyrus centering around Brodmann area 9 in CCA compared with NC.
dysfunction of the frontal lobes in CCA patients under resting conditions. MLRs have recently received renewed interest because of the origin of its components and because of its clinical utility. It consists of two positive peaks (Pa, P1) and two negative peaks (Na, Nb). It has been reported that the P1 component of MLRs of the auditory evoked potential can be used to assess abnormal cholinergic neurotransmission in dementia (Buchwald et al., 1989; Green et al., 1992). The P1 component is thought to be generated in the thalamus by the cholinergic component of the reticular activating system.
Fig. 5. (A) Peak amplitude of MLRs components in patients with CCA and NC. There were no significant differences between the two groups. (B) The peak latency for MLRs components was not different between patients with CCA and NC. Data are mean ^ SD.
Furthermore, abnormalities of P1 in Parkinson’s disease (PD) have been reported (Green et al., 1992). Dubois et al. (1990) suggested that the subcorticofrontal behavioural impairment of PD is caused by degeneration of the ascending cholinergic system, which was demonstrated at post-mortem examination. Therefore, it was hypothesized that P1 was related to cortical cholinergic deficiency in the frontal lobes. A search of 1960 –2001 Medline database showed no reports on MLRs in SCD. Our results of LORETA showed decreased cortical activities of frontal lobe at P1 component, suggesting cortical cholinergic deficiency causing frontal behavioural impairment in CCA patients, similar to PD. In this regard, biochemical analysis of the brain of patients with OPCA showed marked cortical cholinergic deficiency evidenced by reduced activity of cholinergic marker enzymes, together with severe loss of nucleus basalis cholinergic neurons (Kish et al., 1987). It was hypothesized that the mild cognitive impairment in OPCA patients was caused by cerebral cortical cholinergic deficiency as in Alzheimer’s dementia (Kish et al., 1988). The studies on neurotransmitter markers suggested that cerebellar atrophy patient had a degeneration of afferent cholinergic projections to the cerebellum, and choline levels in cereberospinal fluid were significantly lower in patients compared with normal controls (Kanazawa et al., 1985,
746
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
Manyam et al., 1990). However, the relation between the cholinergic system and cerebellum is still not clear, and there is no denying that our findings are caused only by dysfunction of the ascending activating system. Further neurochemical and neuropathological investigations may help to resolve this question. Leiner et al. (1986) suggested the existence of a cerebellar projection to higher order areas in the prefrontal cortex, including Brodmann areas 8, 44 and 45 based on the parallel expansion of the dentate nucleus and prefrontal cortex in human and higher primates. Schmahmann and Pandya (1997) showed inputs to the basilar pons from the prefrontal cortices, areas 8, 9, 46 and 10, in rhesus monkey. They suggested the corticopontocerebellar circuit and hypothesized that the cerebellum was an essential node in the distributed corticosubcortical neural circuits subserving cognitive operations. Middleton and Strick (1994, 2001) described a neural circuitry between the dentate nucleus of the cerebellum, the internal segment of the globus pallidus and Brodmann areas 46 and 9 in monkey. In the human brain, areas 46 and 9 are part of a distributed neural circuitry underlying certain aspects of working memory, as demonstrated in a study by Petrides et al. (1993), using PET and MRI. The deficits appeared on the performance of specific types of rule-based language tasks that in normal subjects activate lateral portions of the cerebellar hemispheres and areas 46 and 9 (Petersen et al., 1988; Raichle et al., 1994; Fiez et al., 1996). It was hypothesized that the connection was an anatomical substrate for the cerebellum to be involved in cognitive functions such as working memory, and rule-based learning. Our results of EEG recording and MLRs with LORETA showing significantly reduced activation of CCA in Brodmann areas 45 and 9 are in agreement with these findings from a functional point of view, and they may be interpreted as frontal cortical inhibition caused by cerebellar atrophy. These findings support the hypothesis that the cerebellum is involved in frontal lobe function and cognitive function regardless of the motor adjunct. However, it is often difficult to identify such abnormality with ordinary psychological tests such as WAIS-R and WCST. Classical methods, based on EEG and MLRs features, did not reveal any differences, although LORETA analysis showed significant abnormalities in patients with CCA. It may be argued that LORETA cannot contain more information than is originally contained in the raw EEG. Therefore, if LORETA shows significant differences between patients and controls, then somewhere in the raw EEG there must also be some significant difference. However, it is not obvious which transformation or combination of the EEG features will provide the significant differences. On the other hand, LORETA provides a transform of the raw EEG that is interpretable in terms of localization of brain function. The raw EEG does not explicitly provide this type of information. And it turned out that, in terms of localized brain function, there are
significant differences between patients and controls. Then, LORETA could detect electrical activation changes in regions related to cortical dysfunction in patients with CCA.
Acknowledgements This work was supported by Grant-in-Aid for Scientific Research (C) from the Ministry of Education Science and Culture of Japan (no. 13670664). The authors thank M. Saito and K. Iwata for their skillful and dedicated technical support.
References Allen G, Buxton RB, Wong EC, Courchesne E. Attentional activation of the cerebellum independent of motor involvement. Science 1997;275: 1940–3. Appollonio IM, Grafman J, Schwartz V, Massaquoi S, Hallett M. Memory in patients with cerebellar degeneration. Neurology 1993;43:1536 –44. Brown JR. Degenerative cerebellar ataxias. Neurology 1959;9:799–805. Buchwald JS, Erwin RJ, Read S, Van Lancker D, Cummings JL. Midlatency auditory evoked responses: differential abnormality of P1 in Alzheimer’s disease. Electroencephalography 1989;74:378 –84. Daum I, Ackermann H, Schugens MM, Reimold C, Dichgans J, Birbaumer N. The cerebellum and cognitive functions in humans. Behav Neurosci 1993;107:411–9. Drepper J, Timmann D, Kolb FP, Diener HC. Non-motor associative learning in patients with isolated degenerative cerebellar disease. Brain 1999;122:87–97. Dubois B, Pillon B, Lhermitte F, Agid Y. Cholinergic deficiency and frontal dysfunction in Parkinson’s disease. Ann Neurol 1990;28:117–21. Estruch R, Nicolas JM, Salamero M, Aragon C, Sacanella E, FernandezSola J, Urbano-Marquez A. Atrophy of the corpus callosum in chronic alcoholism. J Neurol Sci 1997;146:145–51. Fiez JA, Raife EA, Balota DA, Schwarz HP, Raichle ME, Petersen SE. A positron emission tomography study of the short-term maintenance of verbal information. J Neurosci 1996;16:808–22. Folstein MF, Folstein SE, McHugh PR. Mini-mental state. J Psychiatr Res 1975;12:189–98. Frei E, Gamma A, Pascual-Marqui R, Lehmann D, Hell D, Vollenweider FX. Localization of MDMA-induced brain activity in healthy volunteers using low resolution brain electromagnetic tomography (LORETA). Hum Brain Mapp 2001;14:152 –65. Grafman J, Litvan I. Cognitive planning deficit in patients with cerebellar atrophy. Neurology 1992;42:1493–6. Green JB, Flagg L, Freed DM, Schwankhaus JD. The middle latency auditory evoked potential may be abnormal in dementia. Neurology 1992;42:1034–6. Hirono N, Yamadori A, Kameyama M, Mezaki T, Abe K. Spinocerebellar degeneration: cognitive disturbances. Acta Neurol Scand 1991;84: 226 –30. Kamitani T, Kuroiwa Y, Wang L. Visual event-related potentials in patients with spinocerebellar degeneration. In: Hashimoto I, Kakigi R, editors. Recent advances in human neurophysiology. Amsterdam: Elsevier, 1998. p. 515 –26. Kanazawa I, Kwak S, Sasaki H, et al. Studies on neurotransmitter markers and neuronal cell density in the cerebellar system in olivopontocerebellar atrophy. J Neurol Sci 1985;71:193–208. Kashima H, Kato M, Handa T, et al. A Modified Wisconsin Card Sorting
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747 Test – a comparison of the chronic schizophrenics to the patients with frontal lesions. Folia Psychiatr Neurol Jpn 1985;39:97. Kim SG, Ugurbil K, Strick PL. Activation of a cerebellar output nucleus during cognitive processing. Science 1994;265:949– 51. Kish SJ, Currier RD, Schut L, Perry T, Morito C. Brain choline acetylcholinesterase is markedly reduced in dominantly inherited olivopontocerebellar atrophy. Ann Neurol 1987;22:272 –5. Kish SJ, El-Anwar M, Schut L, Leach L, Oscar-Berman M, Freedman M. Cognitive deficits in olivopontocerebellar atrophy: implications for the cholinergic hypotheses of Alzheimer’s dementia. Ann Neurol 1988;24: 200–6. Kish SJ, El-Awar M, Stuss D, Nobrega J, Currier R, Aita JF, Schut L, Zoghbi HY, Freedman M. Neuropsychological test performance in patients with dominantly inherited spinocerebellar ataxia: relationship to ataxia severity. Neurology 1994;44:1738 –46. Kubicki St, Herrmann WM, Fichte K, Freund G. Reflections on the topics: EEG frequency bands and regulation of vigilance. Pharmakopsychiatry 1979;12:237 –45. Lehmann D, Skrandies W. Reference-free identification of components of checkerboard evoked multichannel potentials fields. Electroenceph clin Neurophysiol 1980;48:609– 21. Leiner HC, Leiner AL, Dow RS. Does the cerebellum contribute to mental skills? Behav Neurosci 1986;100:443–54. Lezak MD, editor. Neuropsychological assessment. New York, NY: Oxford Press, 1983. Ligier Y, Ratib O, Logean M, Girard C. OSIRIS: a medical image manipulation system. MD Computing J 1994;11:212–8. Liversedge LA, Emery V. Electroencephalographic changes in cerebellar degenerative lesions. J Neurol Neurosurg Psychiatry 1961;24:326–30. Manyam BV, Giacobini E, Ferraro TN, Hare TA. Cereberospinal fluid as a reflector of central cholinergic and amino acid neurotransmitter activity in cerebellar ataxia. Arch Neurol 1990;47:1194–9. Matthew W, Nordahl T, Schut L, King AC, Cohen R. Metabolic and cognitive changes in hereditary ataxia. J Neurol Sci 1993;119:134–40. Middleton FA, Strick PL. Anatomical evidence for cerebellar and basal ganglia involvement in higher cognitive function. Science 1994;266: 458–61. Middleton FA, Strick PL. Cerebellar projections to the prefrontal cortex of the primate. J Neurosci 2001;21:700–12. Milner B. Effects of different brain lesions on card sorting. Arch Neurol 1963;9:90– 100. Mori E, Mitani Y, Yamadori A. Usefulness of a Japanese version of the Mini-Mental State Test in neurological patients. Jpn J Neuropsychol 1985;1:82– 90. Nabatame H, Fukuyama H, Akiguchi I, Kameyama M, Nishimura K,
747
Nakano Y. Spinocerebellar degeneration: qualitative and quantitative MR analysis of atrophy. J Comput Assist Tomogr 1988;12:298 –303. Nelson HE. A modified card sorting test sensitive of frontal lobe defects. Cortex 1976;12:313 –324. Pardo JV, Fox PT, Raichle ME. Localization of a human system for sustained attention by positron emission tomography. Nature 1991;349: 61– 4. Pascual-Marqui RD, Lehmann D, Koenig T, Kochi K, Merlo MCG, Hell D, Koukkou M. Low resolution brain electromagnetic tomography (LORETA) functional imaging in acute, neuroleptic-naive, firstepisode, productive schizophrenia. Psychiatry Res Neuroimaging 1999;90:169–79. Pascual-Marqui RD, Michel CM, Lehmann D. Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol 1994;18:49 –65. Petersen SE, Fox PT, Posner MI, Mintum M, Raichle ME. Positron emission tomographic studies of the cortical anatomy of single-word processing. Nature 1988;331:585–9. Petrides M, Alivisatos B, Evans AC, Mayer E. Dissociation of human middorsolateral from posterior dorsolateral frontal cortex in memory processing. Proc Natl Acad Sci USA 1993;90:873– 7. Raichle ME, Fiez JA, Videen TO, MacLeod AM, Pardo JV, Fox PT, Petersen SE. Practice-related changes in human brain functional anatomy during nonmotor learning. Cereb Cortex 1994;4:6 –8. Schmahmann JD, Pandya DN. Anatomic organization of the basilar pontine projections from prefrontal cortices in Rhesus monkey. J Neurosci 1997;17:438–58. Schmahmann JD, Sherman JC. The cerebellar cognitive affective syndrome. Brain 1998;121:561–79. Shinagawa F, Kobayashi S, Fujita K, Maekawa H, editors. Japanese Wechsler Adult Intelligence Scale – Revised. Tokyo: Nihon Bunka Kagakusha Co. Ltd, 1990. Tachibana H, Aragane K, Sugita M. Event-related potentials in patients with cerebellar degeneration: electrophysiological evidence for cognitive impairment. Cogn Brain Res 1995;2:173–80. Talairach J, Tournoux P, editors. Co-planar stereotactic atlas of the human brain – 3-dimensional proportional system: an approach to cerebral imaging. Stuttgart: Verlag, 1988. Wallesch CW, Horn A. Long-term effects of cerebellar pathology on cognitive functions. Brain Cogn 1990;14:19–25. Wechsler D. WAIS-R manual. New York, NY: Psychological Corporation, 1981. Yamaguchi S, Tsuchiya H, Kobayashi S. Visuospatial attention shift and motor responses in cerebellar disorders. J Cogn Neurosci 1998;10: 95– 107.
Reduced brain electric activities of frontal lobe in cortical cerebellar atrophy Mio Araia,*, Hideaki Tanakaa, Roberto D. Pascual-Marquib, Koichi Hirataa a
Department of Neurology, Dokkyo University School of Medicine, Kitakobayashi 880, Mibu, Tochigi 321-0293, Japan b The KEY Institute for Brain–Mind Research, University Hospital of Psychiatry, Zurich, Switzerland Accepted 9 December 2002
Abstract Objective: To assess the relationship between cerebellum and brain cortical activity without motor factors, we recorded the mid-latency auditory evoked responses (MLRs) with simultaneous recording of the electroencephalography (EEG) at rest in patients with ‘pure cortical cerebellar atrophy (CCA)’. Methods: We studied 12 normal control subjects and non-demented ‘pure CCA’ patients determined by quantitative magnetic resonance imaging analysis. A comprehensive neuropsychological test battery assessed intelligence, frontal lobe function and word fluency. Spontaneous eyes-closed resting EEG and MLRs were recorded from 20 scalp electrodes and analysed with low-resolution electromagnetic tomography (LORETA) to compute the 3-dimensional intracerebral distribution of electric activity. Results: Neuropsychological tests revealed no differences between CCA and the control. Analysis of EEG and MLRs using classical methods also did not reveal any differences. LORETA analysis indicated significant decrease of alpha2 activity in the left inferior frontal gyrus in CCA. On MLRs, the most significant difference was observed at P1 component, and CCA patients showed significant decrease at the right superior frontal gyrus. Conclusions: Our results indicated that the frontal lobe and ascending reticular activating system are inhibited in CCA patients, and suggested the involvement of the cerebellum in cortical electric activities irrespective of motor adjunct. Significance: Quantitative EEG and MLR measurements with LORETA pointed out frontal lobe hypoactivities in pure CCA patients. q 2003 International Federation of Clinical Neurophysiology. Published by Elsevier Science Ireland Ltd. All rights reserved. Keywords: Electroencephalography; Mid-latency auditory evoked responses; Low-resolution brain electromagnetic tomography; Cerebellum; Frontal lobe; Cognitive function
1. Introduction The cerebellum has long been known as a structure involved in motor coordination. However, in the mid-1980s, anatomical, behavioural, and, neurophysiological evidence emerged suggesting the involvement of the cerebellum in cognitive function in addition to motor function. Leiner et al. (1986) reviewed the potential roles of the cerebellum in cognition and hypothesized cerebellar projections to prefrontal and other associated cortices in humans. Schmahmann and Sherman (1998) defined the ‘cerebellar cognitive affective syndrome’ based on the analysis of 20 patients with diseases confined to the cerebellum. This syndrome is characterized by impairment of executive * Corresponding author. Tel.: þ81-282-87-2152; fax: þ 81-282-86-5884. E-mail address: [email protected] (M. Arai).
functions, such as planning, set shifting, verbal fluency, abstract reasoning and working memory. On the other hand, Middleton and Strick (1994) suggested that cerebellar output projects via the thalamus to multiple cortical areas, including premotor and prefrontal cortex, as well as the primary motor cortex. They also suggested that neuronal activity within the basal ganglia and cerebellar loops with areas of the prefrontal cortex is related to various aspects of cognitive function. Furthermore, in functional neuroimaging studies such as positron emission tomography (PET) and functional magnetic resonance imaging (MRI), cerebellar activation is often evident in tests of cognitive planning (Kim et al., 1994), shifting attention (Allen et al., 1997) and sustained attention (Pardo et al., 1991). Patients with spinocerebellar degeneration (SCD) may exhibit cognitive impairment. However, there is controversy on whether patients with SCD have cognitive dysfunctions
1388-2457/03/$30.00 q 2003 International Federation of Clinical Neurophysiology. Published by Elsevier Science Ireland Ltd. All rights reserved. doi:10.1016/S1388-2457(02)00423-6
CLINPH 2002160
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
specifically related to the frontal lobe or have cognitive deficits secondary to motor dysfunction. A number of reports indicated that SCD, including olivopontocerebellar atrophy (OPCA), produces cognitive impairment, suggesting possible effect of brainstem atrophy. Grafman and Litvan (1992) reported that patients with ‘pure’ cortical cerebellar atrophy (CCA) performed significantly worse than normal subjects on the Tower of Hanoi task, which required cognitive planning. On the other hand, Daum et al. (1993) showed that there were no significant differences between patients with restricted cerebellar damage and normal subjects on the Wechsler Adult Intelligence ScaleRevised (WAIS-R) and Wisconsin Card Sorting Test (WCST). In the present work, we studied only patients with CCA among patients with SCD, as determined by quantitative MRI analysis, because our aim was to determine the profile of cognitive dysfunction in cerebellar atrophy itself. Previous studies used functional neuroimaging or neurophysiological analysis for the evaluation of cognitive dysfunction in patients with SCD (Tachibana et al., 1995; Kamitani et al., 1998; Yamaguchi et al., 1998). In this regard, neurophysiological studies, especially event-related potentials, are widely used for evaluation of cognitive impairment in patients with neurodegenerative disorders such as Alzheimer’s disease and Parkinson’s disease. However, assessment of cerebellar function related to cognition using tests that do not involve motor function is difficult. In order to avoid any type of motor involvement in the testing procedure, we used the mid-latency auditory evoked responses (MLRs), which are independent of motor function, with simultaneous recording of the electroencephalogram (EEG) at rest.
2. Materials and methods 2.1. Subjects We studied 12 patients with CCA and 12 age-, sex- and education-matched normal controls (Table 1). All CCA patients satisfied following criteria: (1) the primary symptom was that of cerebellar ataxia without pyramidal signs, extrapyramidal signs, or autonomic nervous dysfunction; (2) cerebellar atrophy without brainstem atrophy was confirmed by neuroimaging, and no abnormal signs within cerebral and other brain structures were observed; (3) other causes of cerebellar atrophy were excluded, including longterm alcohol addiction, anticonvulsant poisoning, hypothyroidism, and malignant tumours; (4) absence of a positive family history. Normal control subjects represented healthy individuals who visited our clinic for routine medical check ups and were found to be free of any neurological and psychiatric diseases. Furthermore, neurological examination, including MRI, was normal in these subjects. Neither the control subjects nor CCA subjects were taking any
741
Table 1 Characteristics of subjects participating in this study
N Sex (male/female) Age (years) Duration of disease (years) Duration of education (years) MMSE score WCST score CA PEN WAIS-R score VIQ PIQ TIQ VF score Letter Category
CCA
NC
P value
12 7/5 61.1 ^ 9.0 13.2 ^ 8.0 11.4 ^ 3.3 27.8 ^ 2.2
12 7/5 60.6 ^ 7.7 – 11.9 ^ 2.4 29.1 ^ 1.0
– – 0.89 – 0.71 0.18
3.6 ^ 2.4 6.1 ^ 6.6
3.8 ^ 1.0 4.7 ^ 2.1
0.90 0.57
103.0 ^ 11.8 90.5 ^ 11.2 97.8 ^ 12.7
100 ^ 15 100 ^ 15 100 ^ 15
– – –
20.4 ^ 8.8 40.8 ^ 12.2
23.0 ^ 5.6 48.5 ^ 9.8
0.41 0.12
Patients with cortical cerebellar atrophy (CCA) and normal control (NC) subjects were matched for age, sex and education. Data are mean ^ SD. VF, verbal fluency task. There were no significant differences in MMSE, WCST, WAIS-R and VF task scores between CCA and NC.
central nervous system (CNS)-active drugs at the time of testing. All subjects were right handed, and clinically nondemented having score 24 or above in Mini-Mental State Examination (MMSE) (Folstein et al., 1975). All CCA patients were able to walk without assistance. We studied all subjects after obtaining informed consent. 2.2. Psychological testing The Japanese version of the MMSE (Mori et al., 1985), WAIS-R (Wechsler, 1981; Shinagawa et al., 1990), the new modified WCST (Kashima et al., 1985) and the verbal fluency task (Lezak, 1983) were employed for comprehensive assessment of cognitive function. The test batteries have been used in many clinical areas in Japan and their reliabilities have been confirmed. The results of WAIS-R were expressed in 3 forms of intelligence quotients (IQ): verbal IQ (VIQ), performance IQ (PIQ), and full-scale IQ (FIQ). We adopted standard score (mean ¼ 100, SD ¼ 15) as for IQ scores of normal controls (Wechsler, 1981, Shinagawa et al., 1990). The original WCST developed by Milner (1963) is one of the few tests that detect a clear deficit specific to patients with frontal lobe dysfunction; however, it is too difficult and distressing for many patients. Therefore, a simpler and less ambiguous modification was made. The two main modified points were the order of the reaction cards and the process of providing necessary instructions. This new version has been used successfully in Japan. To evaluate this test, the maximum classification score and the preservative errors reported by Nelson (1976) were used. We also used the verbal fluency task, which has been confirmed to be a sensitive indicator of frontal lobe dysfunction. The patients were instructed to say as many
742
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
words as they could think of that began with a given kana (Japanese syllabic alphabet) letter, and the number of words produced in 120 s for each letter of two letters was recorded. The score was the total number of acceptable words produced during 4 min. The patients were also asked to generate as many words belonging to two categories (‘animal’ and ‘in a house’) as they could think of each 120 s. The total numbers of two sessions were accepted as the score.
the cerebellum and pons. (2) Maximal width of the frontal horns of the lateral ventricles (A) and frontal width (B) at the caudate nuclei plane on the axial image (Estruch et al., 1997) (Fig. 1). The ratio (A/B) represented the frontal lobe index, a measure of frontal lobe atrophy (Estruch et al., 1997). Each image was digitized using a scanner (EPSON2200, Japan) and analysed quantitatively with the Osiris software (Ligier et al., 1994). 2.4. Brain electric recordings
2.3. Neuroradiology A brain MRI scan was performed at Dokkyo University using a General Electric MR scanner (Milwaukee, WI, USA) with either a 1 or 1.5 T magnet. The T1-weighted images were obtained from the axial and sagittal planes (spin echo, TR ¼ 600 ms, TE ¼ 15 ms, slice thickness 7.5 mm), while the T2-weighted images were obtained from the axial planes (spin echo, TR ¼ 3800 ms, TE ¼ 110 ms, slice thickness 7.5 mm). To measure the degree of atrophy (Table 2) in the cerebellum and its related structures, the following morphometric parameters were measured with T1-weighted images: (1) Areas of the cerebellar vermis, the posterior fossa which is delineated by the tentorium cerebelli and the inner counter of the skull, and the basis pontis on the mid-sagittal image (Nabatame et al., 1988) (Fig. 1). The measured areas of the cerebellar vermis and the basis pontis were divided by the measured area of the posterior fossa to evaluate the relative atrophy of Table 2 The degree of atrophy measured by MRI, global field power (GFP), which represents the generalized EEG amplitude of 7 EEG frequency bands, the peak amplitude and the peak latency for MLRs components
CAI (ratio) PAI (ratio) FLI (ratio) EEG GFP Delta Theta Alpha 1 Alpha 2 Beta 1 Beta 2 Beta 3 MLRs GFP Peak amplitude Pa Nb P1 Peak latency (ms) Pa Nb P1
CCA
NC
P value
0.24 ^ 0.05 0.10 ^ 0.01 0.35 ^ 0.03
0.34 ^ 0.05 0.11 ^ 0.01 0.34 ^ 0.03
,0.01* 0.10 0.58
1.41 ^ 0.46 1.26 ^ 0.69 2.34 ^ 1.14 2.13 ^ 1.56 0.85 ^ 0.29 0.71 ^ 0.22 0.43 ^ 0.11
1.30 ^ 0.24 1.09 ^ 0.24 1.73 ^ 0.52 1.84 ^ 0.93 0.88 ^ 0.28 0.69 ^ 0.16 0.46 ^ 0.11
0.52 0.42 0.11 0.57 0.79 0.83 0.59
0.95 ^ 0.37 0.93 ^ 0.60 0.96 ^ 0.58 36.3 ^ 3.28 47.4 ^ 3.43 66.8 ^ 7.22
0.96 ^ 0.44 0.94 ^ 0.51 1.02 ^ 0.52 34.6 ^ 1.91 47.0 ^ 2.73 68.3 ^ 4.08
0.93 0.96 0.79 0.14 0.77 0.56
Data are mean ^ SD. CAI, cerebellar atrophy index; PAI, Pontine atrophy index; FLI, frontal lobe index. *CAI was significantly reduced in patients with CCA but there were no significant differences PAI and FLI compared with NC. There were no significant differences in GFP of EEG, MLRs.
Subjects lied down on a bed in a sound-attenuated and dimly lit Faraday room. The brain electric data were recorded (Bio-logic Brain Atlas, 0.53 – 30 Hz bandpass) with silver/silver chloride EEG electrodes attached with paste to 20 locations of the international 10/20 system (Fp1/2, Fz, F3/4, F7/8, T3/4, C3/4, Cz, P3/4, Pz, T5/6, O1/2, Oz) using an electrode attached to the earlobe as reference. Electrode impedance was maintained below 5 kW. The recording was performed at 2:00 pm in all subjects to exclude the effects of circadian rhythm. The subjects were asked to relax and close their eyes. This was followed by 5 min recording of spontaneous EEG (128 samples/s), which was monitored visually. After recording, EEG records in epochs of 2 s were carefully inspected for movement, eye and muscle artefacts. The first 20 accepted 2 s epochs were analysed for each subject. For the MLRs measurement, 80 dB clicks at one per second were presented as a sequence of binaural stimuli via earphones and 250 artefact-free stimuli were averaged in each session. The MLRs over 128 ms post-stimulus were averaged on-line (2000 samples/s), using an automatic artefact rejection criterion (for signals with amplitude higher than 136 mV). The MLRs of the two sessions were averaged. All accepted EEG and MLRs data were off-line digitally filtered to 1.5– 30 Hz using a fast Fourier transform (FFT) bandpass. For eye movement rejection, a spatial filtering procedure was employed that removed those spatial principal components of the data that showed a correlation coefficient (r) better than ^ 0.75 with an eye movement template consisting only of activity in the two prefrontal channels Fp1 and Fp2. 2.5. Data analysis Absolute power values at Oz (referenced to linked earlobes) for 7 EEG frequency bands: delta (1.5 – 6.0 Hz), theta (6.5 – 8.0 Hz), alpha1 (8.5 – 10.0 Hz), alpha2 (10.5 – 12.0 Hz), beta1 (12.5 –18.0 Hz), beta2 (18.5 – 21.0 Hz), and beta3 (21.5 – 30.0 Hz) were determined (Kubicki et al., 1979) by FFT and compared between the two groups. For a comprehensive assessment of the 20-channel EEG data, the single global field power (GFP) (Lehmann and Skrandies, 1980) curve was computed for each 2 s epoch. The GFP curves were subjected to conventional power spectral analysis using a Hanning Window, and a mean spectrum
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
743
Fig. 1. Schematic diagram and a representative MRI T1-weighted image demonstrating measurements of brain structures and evaluation of the degree of atrophy.
was computed for each subject over all 20 data epochs. Integrated power was computed for the 7 frequency bands. For the MLRs, latencies and amplitudes of Pa, Nb and P1 components at Cz (referenced to linked earlobes) were measured and compared between the two groups. For each time point of the multichannel data, the amplitude and peak latency of GFP were computed, resulting in a single curve of GFP for each 20-channel ERP average. 2.6. Spatial analysis Low-resolution brain electromagnetic tomograph (LORETA) (Pascual-Marqui et al., 1994, 1999) was used to compute the 3-dimensional intracerebral distribution of electric activity of EEG and MLRs. LORETA determines the distribution of generator activity in the cortex, i.e. it produces an activity strength value for each of many voxels, while employing no constraints on the number of model sources. LORETA solves the so-called inverse problem without a priori knowledge of the number of sources, but applies the constraint of maximal smoothness of the solution. Hence, LORETA results show maximally similar activity in neighbour voxels, consistent with the known electrophysiology of synchronized activity in neighbouring neurons. The LORETA computation determines current density at each voxel as the linear weighted sum of the scalp electric potentials. The results were computed for the cortical areas of the Talairach probability atlas (Talairach and Tournoux, 1988), with a spatial resolution of 7 mm. 2.7. Statistical analysis Differences in parameters derived from EEG, MLRs, psychological tests and neuroradiological measurements were examined for statistical significance using the unpaired
sample t test. These descriptive P values were considered relevant if they appeared in nearly regular patterns associated with numerically relevant differences. Data are expressed as mean ^ SD. LORETA voxel-by-voxel paired t test using non-parametric randomisation tests with correction for multiple testing was used for differences in the regional distribution of activity between conditions. Images were displayed with results of t test analysis and the corrected thresholds were shown in 3 orthogonal brain slices (horizontal, sagittal, coronal). In these images, red colour represents increased activation and blue colour represents reduced activation of CCA compared to the normal subjects.
3. Results WAIS-R was not significantly decreased in CCA patients (IQ: more than 80). Furthermore, scores of WCST and verbal fluency test of patients with CCA were not significantly different from those of the control (Table 1). MRI images showed no abnormal intensity areas within the cerebellum, brainstem and other structures of the brain. The relative area of the cerebellum in the patients was significantly smaller than that of the control subjects although there was no significant difference of the relative area of the pons and frontal lobe index (Table 2; Fig. 2). Atrophy was limited to the cerebellum in CCA patients. The EEG at Oz and the mean brain topography maps showed no significant differences between patients with CCA and control. In addition, GFP for each of the 7 frequency bands was not significantly different between the two groups (Table 2; Fig. 3). However, LORETA analysis indicated significant decrease of alpha2 activity (P ¼ 0:006) in the left inferior frontal gyrus centering around Brodmann area 45, where is frontal operculum of prefrontal cortex, in
744
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
Fig. 2. The degree of atrophy measured by MRI. The relative area of the cerebellum (CAI) was significantly reduced in patients with cerebellar cortical atrophy (CCA) but there were no significant differences in the pons (PAI) and frontal lobe index (FLI) compared with the control (NC). This indicates that atrophy is limited to the cerebellum in patients with CCA. Data are mean ^ SD.
patients with CCA compared with the control (Fig. 4). With respect to MLRs, the latencies and amplitudes of each component at Cz and GFP were not significantly different (Table 2; Fig. 5A,B). LORETA-based comparisons, on a timeframe-by-timeframe basis, were performed on the MLRs. The most significant difference was observed at 64 ms after stimulus presentation, corresponding to the P1 component. CCA patients showed significant decrease (P ¼ 0:04) in the right superior frontal gyrus centering around Brodmann area 9, where is lateral dorsal area of prefrontal cortex, compared with control (Fig. 4).
4. Discussion Recent studies have indicated the involvement of the cerebellum in cognitive function in addition to its wellknown role in motor function. Employing various neuropsychological tests, previous reports described impairment of generalized intellect, spatial cognition and frontal lobe function in patients with cerebellar degeneration and atrophy (Wallesch and Horn, 1990; Hirono et al., 1991; Grafman and Litvan, 1992; Appollonio et al., 1993; Kish et al., 1994; Drepper et al., 1999). There is controversy on
Fig. 3. Global field power (GFP), which represents the generalized EEG amplitude of 7 EEG frequency bands. There were no significant differences between patients with CCA and NC. Data are mean ^ SD.
whether patients with SCD have cognitive dysfunctions specifically related to the frontal lobe or have cognitive deficits secondary to motor dysfunction. Many studies are based on single case or very small samples that often include patients with extracerebellar damage, such as patients with Friedreich’s ataxia or OPCA. For example, it is well known that OPCA may be associated with a mild form of dementia, which is characterized by a range of cognitive deficits that are related to the severity of the illness (Leiner et al., 1986; Matthew et al., 1993). In the present work, we limited our study to patients with ‘pure CCA’ as confirmed by quantitative MRI analysis because we wanted to determine the profile of cognitive dysfunction in cerebellar atrophy itself. In previous studies that were also limited to patients with pure cerebellar dysfunction, Drepper et al. (1999) compared the performance of patients with idiopathic cerebellar ataxia in a cognitive associative learning task with control subjects. In their study, such patients were found to have a specific deficit and the results suggested that the cerebellum might contribute to motorindependent processes that were generally involved in associative learning. Furthermore, Grafman and Litvan (1992) reported that patients with ‘pure CCA’ performed significantly worse than normal subjects on the Tower of Hanoi task, which requires cognitive planning. They concluded that the cerebellum played an important role in executive functions such as cognitive planning, and suggested the presence of a functional link between the cerebellum, basal ganglia, and the frontal lobe for specific cognitive processes. On the other hand, Daum et al. (1993) reported that patients with damage to both cerebellum and brainstem, but not those with cerebellar pathology alone, showed memory impairment and poor performance in visuoconstructive tasks, related to frontal lobe dysfunction. Their study showed that there were no significant differences between patients with limited cerebellar damage and normal subjects on the WAIS-R and WCST. The results of the above studies were similar to those of our neuropsychological tests. Assessment of cerebellar function related to cognition using tests that do not require motor function is difficult. In this study, we avoided such motor involvement by recording MLRs and EEG under resting conditions independent of motor function. The majority of previous studies reported no EEG abnormalities in SCD patients (Brown, 1959; Liversedge and Emery, 1961). However, not all studies performed quantitative EEG analysis. In addition, there are only a few reports of EEG in SCD after MRI became commonly used, and hence diagnosis in these studies depended on old classification (Brown, 1959; Liversedge and Emery, 1961). Our quantitative evaluation successfully detected differences between patients with CCA and control subjects. Normal awake, eyes-closed, alpha activity is associated with automatic, routine functioning (PascualMarqui et al., 1999; Frei et al., 2001). The observed decrease in alpha2 activity seems to signify cortical
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
745
Fig. 4. LORETA. The third row shows t-statistics images with corrected thresholds, shown in 3 orthogonal brain slices (horizontal, sagittal, coronal). Red colour represents increased activation and blue colour represents decreased activation in patients with CCA compared with NC. CCA showed significantly decreased activation in the alpha2 band (P ¼ 0:006) in the left inferior frontal gyrus centering around Brodmann area 45. Furthermore, MLRs at 64 ms revealed significant decrease (P ¼ 0:04) at right superior frontal gyrus centering around Brodmann area 9 in CCA compared with NC.
dysfunction of the frontal lobes in CCA patients under resting conditions. MLRs have recently received renewed interest because of the origin of its components and because of its clinical utility. It consists of two positive peaks (Pa, P1) and two negative peaks (Na, Nb). It has been reported that the P1 component of MLRs of the auditory evoked potential can be used to assess abnormal cholinergic neurotransmission in dementia (Buchwald et al., 1989; Green et al., 1992). The P1 component is thought to be generated in the thalamus by the cholinergic component of the reticular activating system.
Fig. 5. (A) Peak amplitude of MLRs components in patients with CCA and NC. There were no significant differences between the two groups. (B) The peak latency for MLRs components was not different between patients with CCA and NC. Data are mean ^ SD.
Furthermore, abnormalities of P1 in Parkinson’s disease (PD) have been reported (Green et al., 1992). Dubois et al. (1990) suggested that the subcorticofrontal behavioural impairment of PD is caused by degeneration of the ascending cholinergic system, which was demonstrated at post-mortem examination. Therefore, it was hypothesized that P1 was related to cortical cholinergic deficiency in the frontal lobes. A search of 1960 –2001 Medline database showed no reports on MLRs in SCD. Our results of LORETA showed decreased cortical activities of frontal lobe at P1 component, suggesting cortical cholinergic deficiency causing frontal behavioural impairment in CCA patients, similar to PD. In this regard, biochemical analysis of the brain of patients with OPCA showed marked cortical cholinergic deficiency evidenced by reduced activity of cholinergic marker enzymes, together with severe loss of nucleus basalis cholinergic neurons (Kish et al., 1987). It was hypothesized that the mild cognitive impairment in OPCA patients was caused by cerebral cortical cholinergic deficiency as in Alzheimer’s dementia (Kish et al., 1988). The studies on neurotransmitter markers suggested that cerebellar atrophy patient had a degeneration of afferent cholinergic projections to the cerebellum, and choline levels in cereberospinal fluid were significantly lower in patients compared with normal controls (Kanazawa et al., 1985,
746
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747
Manyam et al., 1990). However, the relation between the cholinergic system and cerebellum is still not clear, and there is no denying that our findings are caused only by dysfunction of the ascending activating system. Further neurochemical and neuropathological investigations may help to resolve this question. Leiner et al. (1986) suggested the existence of a cerebellar projection to higher order areas in the prefrontal cortex, including Brodmann areas 8, 44 and 45 based on the parallel expansion of the dentate nucleus and prefrontal cortex in human and higher primates. Schmahmann and Pandya (1997) showed inputs to the basilar pons from the prefrontal cortices, areas 8, 9, 46 and 10, in rhesus monkey. They suggested the corticopontocerebellar circuit and hypothesized that the cerebellum was an essential node in the distributed corticosubcortical neural circuits subserving cognitive operations. Middleton and Strick (1994, 2001) described a neural circuitry between the dentate nucleus of the cerebellum, the internal segment of the globus pallidus and Brodmann areas 46 and 9 in monkey. In the human brain, areas 46 and 9 are part of a distributed neural circuitry underlying certain aspects of working memory, as demonstrated in a study by Petrides et al. (1993), using PET and MRI. The deficits appeared on the performance of specific types of rule-based language tasks that in normal subjects activate lateral portions of the cerebellar hemispheres and areas 46 and 9 (Petersen et al., 1988; Raichle et al., 1994; Fiez et al., 1996). It was hypothesized that the connection was an anatomical substrate for the cerebellum to be involved in cognitive functions such as working memory, and rule-based learning. Our results of EEG recording and MLRs with LORETA showing significantly reduced activation of CCA in Brodmann areas 45 and 9 are in agreement with these findings from a functional point of view, and they may be interpreted as frontal cortical inhibition caused by cerebellar atrophy. These findings support the hypothesis that the cerebellum is involved in frontal lobe function and cognitive function regardless of the motor adjunct. However, it is often difficult to identify such abnormality with ordinary psychological tests such as WAIS-R and WCST. Classical methods, based on EEG and MLRs features, did not reveal any differences, although LORETA analysis showed significant abnormalities in patients with CCA. It may be argued that LORETA cannot contain more information than is originally contained in the raw EEG. Therefore, if LORETA shows significant differences between patients and controls, then somewhere in the raw EEG there must also be some significant difference. However, it is not obvious which transformation or combination of the EEG features will provide the significant differences. On the other hand, LORETA provides a transform of the raw EEG that is interpretable in terms of localization of brain function. The raw EEG does not explicitly provide this type of information. And it turned out that, in terms of localized brain function, there are
significant differences between patients and controls. Then, LORETA could detect electrical activation changes in regions related to cortical dysfunction in patients with CCA.
Acknowledgements This work was supported by Grant-in-Aid for Scientific Research (C) from the Ministry of Education Science and Culture of Japan (no. 13670664). The authors thank M. Saito and K. Iwata for their skillful and dedicated technical support.
References Allen G, Buxton RB, Wong EC, Courchesne E. Attentional activation of the cerebellum independent of motor involvement. Science 1997;275: 1940–3. Appollonio IM, Grafman J, Schwartz V, Massaquoi S, Hallett M. Memory in patients with cerebellar degeneration. Neurology 1993;43:1536 –44. Brown JR. Degenerative cerebellar ataxias. Neurology 1959;9:799–805. Buchwald JS, Erwin RJ, Read S, Van Lancker D, Cummings JL. Midlatency auditory evoked responses: differential abnormality of P1 in Alzheimer’s disease. Electroencephalography 1989;74:378 –84. Daum I, Ackermann H, Schugens MM, Reimold C, Dichgans J, Birbaumer N. The cerebellum and cognitive functions in humans. Behav Neurosci 1993;107:411–9. Drepper J, Timmann D, Kolb FP, Diener HC. Non-motor associative learning in patients with isolated degenerative cerebellar disease. Brain 1999;122:87–97. Dubois B, Pillon B, Lhermitte F, Agid Y. Cholinergic deficiency and frontal dysfunction in Parkinson’s disease. Ann Neurol 1990;28:117–21. Estruch R, Nicolas JM, Salamero M, Aragon C, Sacanella E, FernandezSola J, Urbano-Marquez A. Atrophy of the corpus callosum in chronic alcoholism. J Neurol Sci 1997;146:145–51. Fiez JA, Raife EA, Balota DA, Schwarz HP, Raichle ME, Petersen SE. A positron emission tomography study of the short-term maintenance of verbal information. J Neurosci 1996;16:808–22. Folstein MF, Folstein SE, McHugh PR. Mini-mental state. J Psychiatr Res 1975;12:189–98. Frei E, Gamma A, Pascual-Marqui R, Lehmann D, Hell D, Vollenweider FX. Localization of MDMA-induced brain activity in healthy volunteers using low resolution brain electromagnetic tomography (LORETA). Hum Brain Mapp 2001;14:152 –65. Grafman J, Litvan I. Cognitive planning deficit in patients with cerebellar atrophy. Neurology 1992;42:1493–6. Green JB, Flagg L, Freed DM, Schwankhaus JD. The middle latency auditory evoked potential may be abnormal in dementia. Neurology 1992;42:1034–6. Hirono N, Yamadori A, Kameyama M, Mezaki T, Abe K. Spinocerebellar degeneration: cognitive disturbances. Acta Neurol Scand 1991;84: 226 –30. Kamitani T, Kuroiwa Y, Wang L. Visual event-related potentials in patients with spinocerebellar degeneration. In: Hashimoto I, Kakigi R, editors. Recent advances in human neurophysiology. Amsterdam: Elsevier, 1998. p. 515 –26. Kanazawa I, Kwak S, Sasaki H, et al. Studies on neurotransmitter markers and neuronal cell density in the cerebellar system in olivopontocerebellar atrophy. J Neurol Sci 1985;71:193–208. Kashima H, Kato M, Handa T, et al. A Modified Wisconsin Card Sorting
M. Arai et al. / Clinical Neurophysiology 114 (2003) 740–747 Test – a comparison of the chronic schizophrenics to the patients with frontal lesions. Folia Psychiatr Neurol Jpn 1985;39:97. Kim SG, Ugurbil K, Strick PL. Activation of a cerebellar output nucleus during cognitive processing. Science 1994;265:949– 51. Kish SJ, Currier RD, Schut L, Perry T, Morito C. Brain choline acetylcholinesterase is markedly reduced in dominantly inherited olivopontocerebellar atrophy. Ann Neurol 1987;22:272 –5. Kish SJ, El-Anwar M, Schut L, Leach L, Oscar-Berman M, Freedman M. Cognitive deficits in olivopontocerebellar atrophy: implications for the cholinergic hypotheses of Alzheimer’s dementia. Ann Neurol 1988;24: 200–6. Kish SJ, El-Awar M, Stuss D, Nobrega J, Currier R, Aita JF, Schut L, Zoghbi HY, Freedman M. Neuropsychological test performance in patients with dominantly inherited spinocerebellar ataxia: relationship to ataxia severity. Neurology 1994;44:1738 –46. Kubicki St, Herrmann WM, Fichte K, Freund G. Reflections on the topics: EEG frequency bands and regulation of vigilance. Pharmakopsychiatry 1979;12:237 –45. Lehmann D, Skrandies W. Reference-free identification of components of checkerboard evoked multichannel potentials fields. Electroenceph clin Neurophysiol 1980;48:609– 21. Leiner HC, Leiner AL, Dow RS. Does the cerebellum contribute to mental skills? Behav Neurosci 1986;100:443–54. Lezak MD, editor. Neuropsychological assessment. New York, NY: Oxford Press, 1983. Ligier Y, Ratib O, Logean M, Girard C. OSIRIS: a medical image manipulation system. MD Computing J 1994;11:212–8. Liversedge LA, Emery V. Electroencephalographic changes in cerebellar degenerative lesions. J Neurol Neurosurg Psychiatry 1961;24:326–30. Manyam BV, Giacobini E, Ferraro TN, Hare TA. Cereberospinal fluid as a reflector of central cholinergic and amino acid neurotransmitter activity in cerebellar ataxia. Arch Neurol 1990;47:1194–9. Matthew W, Nordahl T, Schut L, King AC, Cohen R. Metabolic and cognitive changes in hereditary ataxia. J Neurol Sci 1993;119:134–40. Middleton FA, Strick PL. Anatomical evidence for cerebellar and basal ganglia involvement in higher cognitive function. Science 1994;266: 458–61. Middleton FA, Strick PL. Cerebellar projections to the prefrontal cortex of the primate. J Neurosci 2001;21:700–12. Milner B. Effects of different brain lesions on card sorting. Arch Neurol 1963;9:90– 100. Mori E, Mitani Y, Yamadori A. Usefulness of a Japanese version of the Mini-Mental State Test in neurological patients. Jpn J Neuropsychol 1985;1:82– 90. Nabatame H, Fukuyama H, Akiguchi I, Kameyama M, Nishimura K,
747
Nakano Y. Spinocerebellar degeneration: qualitative and quantitative MR analysis of atrophy. J Comput Assist Tomogr 1988;12:298 –303. Nelson HE. A modified card sorting test sensitive of frontal lobe defects. Cortex 1976;12:313 –324. Pardo JV, Fox PT, Raichle ME. Localization of a human system for sustained attention by positron emission tomography. Nature 1991;349: 61– 4. Pascual-Marqui RD, Lehmann D, Koenig T, Kochi K, Merlo MCG, Hell D, Koukkou M. Low resolution brain electromagnetic tomography (LORETA) functional imaging in acute, neuroleptic-naive, firstepisode, productive schizophrenia. Psychiatry Res Neuroimaging 1999;90:169–79. Pascual-Marqui RD, Michel CM, Lehmann D. Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol 1994;18:49 –65. Petersen SE, Fox PT, Posner MI, Mintum M, Raichle ME. Positron emission tomographic studies of the cortical anatomy of single-word processing. Nature 1988;331:585–9. Petrides M, Alivisatos B, Evans AC, Mayer E. Dissociation of human middorsolateral from posterior dorsolateral frontal cortex in memory processing. Proc Natl Acad Sci USA 1993;90:873– 7. Raichle ME, Fiez JA, Videen TO, MacLeod AM, Pardo JV, Fox PT, Petersen SE. Practice-related changes in human brain functional anatomy during nonmotor learning. Cereb Cortex 1994;4:6 –8. Schmahmann JD, Pandya DN. Anatomic organization of the basilar pontine projections from prefrontal cortices in Rhesus monkey. J Neurosci 1997;17:438–58. Schmahmann JD, Sherman JC. The cerebellar cognitive affective syndrome. Brain 1998;121:561–79. Shinagawa F, Kobayashi S, Fujita K, Maekawa H, editors. Japanese Wechsler Adult Intelligence Scale – Revised. Tokyo: Nihon Bunka Kagakusha Co. Ltd, 1990. Tachibana H, Aragane K, Sugita M. Event-related potentials in patients with cerebellar degeneration: electrophysiological evidence for cognitive impairment. Cogn Brain Res 1995;2:173–80. Talairach J, Tournoux P, editors. Co-planar stereotactic atlas of the human brain – 3-dimensional proportional system: an approach to cerebral imaging. Stuttgart: Verlag, 1988. Wallesch CW, Horn A. Long-term effects of cerebellar pathology on cognitive functions. Brain Cogn 1990;14:19–25. Wechsler D. WAIS-R manual. New York, NY: Psychological Corporation, 1981. Yamaguchi S, Tsuchiya H, Kobayashi S. Visuospatial attention shift and motor responses in cerebellar disorders. J Cogn Neurosci 1998;10: 95– 107.