Journal ofGerontology: MEDICAL SCIENCES Copyright 1999 by The Gerontological Society ofAmerica 1999, Vol. 54A, No.8, M404-M409

Does OldAge or Parkinson's Disease Cause Bradyphrenia?

James G. Phillips, l Tanya Schiffler,' Michael E. R. Nicholls," John L. Bradshaw,' Robert Iansek,' and Lauren L. Saling'

'Departmentof Psychology, MonashUniversity, Clayton, Australia

2Department of Psychology, University of Melbourne, Parkville, Australia. Downloaded from https://academic.oup.com/biomedgerontology/article/54/8/M404/542741 by guest on 30 September 2021 3Geriatric ResearchUnit,Kingston Centre,Cheltenham, Australia.

Background. Age-related declines in intellectual functioning have been linked to slower processing ofinformation. However, any slowness with advancing age could simply reflect slower movement rather than impaired cognition. To assess any age-related decline in cognitive speed, we used an accuracy-based task that does not require a speeded motor response and that measures the time required to acquire information (inspection time). To identify possible biological mechanisms of cogni­ tive slowing, this task was also applied to patients with Parkinson's disease, a disorder that reportedly causes bradyphrenia (slower thought processes).

Methods. In one experiment, 16 young (mean age 22.4 years) and 16 older adults (mean age 71.6 years) matched for intelli­ gence and education completed an inspection time task. The task required judgments as to order of onset oftwo lights, where the interval between onsets ranged from 20-250 msec. A second experiment compared 16 patients diagnosed with idiopathic Parkinson's disease and 16 age-matched controls upon the same task.

Results. Older adults demonstrated significant cognitive slowing compared to younger adults. Medicated nondemented Parkinsonian patients were not impaired on this task compared to age-matched controls.

Conclusions. Clinical and empirical impressions of bradyphrenia in Parkinson's disease may instead reflect advancing age or slower movement, because the effects of age may be greater in some cases than the effects of basal ganglia disease once motor dysfunction has been allowed for.

HERE are problems in addressing any age-related decline in the minimum stimulus exposure duration required to attain a T intellectual functioning. The concept of intelligence is near perfect accuracy (8). Inspection time (9) is correlated with somewhat descriptive (1), and conventional intelligence tests psychometric intelligence (10). However, there are problems may be inappropriate for older age groups (2). Nevertheless, with the few studies that have employed the inspection time any age-related deteriorations of intellectual functioning occur paradigm to investigate cognitive slowing in aged populations. upon performance subscales ofintelligence tests, rather than For instance, Kirby and Nettelbeck (11) found that older adultshad vocabulary subscales (3). Because age-related decline in intel­ longer inspectiontimes and lower intelligencescores;however,this lectual functioning is associated with a slowing ofthe process­ may have reflectedtheircohort's educationalopportunities. ing of information (3), this study addressed mechanisms deter­ To control for some of the factors affecting such cross­ mining information processing rate. To this end, parallels have sectional comparisons (3), the present study matched young been drawn between the slowing of performance in old age and and older adults for estimated verbal intelligence and educa­ that of Parkinson's disease [PD; (4)], as such subcortical syn­ tion. In addition, there have been some previous concerns of dromes exhibit bradyphrenia, a slowing of information process­ participants using post-stimulus apparent motion cues during ing rates (5). This study, therefore, considered whether speed of tachistoscopic stimulus presentation (12), which reduce rela­ information processing declines in older adults and in patients tionships between inspection time and intelligence. To preclude with PD. the use of strategies that use apparent motion, we used a novel version of the inspection time paradigm, where inspection time Experiment One is operationalized as a temporal orderjudgment in which two Age-related cognitive slowing is frequently reported; how­ lights flash on in rapid succession and participants decide which ever, most tests of cognitive function (such as Digit-Symbol illuminated first. Substitution Test [DSST] and reaction time [RTJ) require a The inspection time task employed the method of constant speeded motor response. Because aging often involves motor stimuli where fixed numbers of trials are conducted at each of slowing (6), the use of such tests could lead to spurious impres­ several specific interstimulus intervals (lSI). Response accuracy sions of poor cognitive function. This investigation employed for each lSI was measured, with the knowledge that partici­ an index (inspection time) that is independent of motor involve­ pants with faster mental speeds would require shorter lSI to ment (7) because cognitive speed is inferred from accuracy make accurate judgments of order of onset. The lSI at which rather than speed of response. criterion performance is reached (95% accuracy) was used to Inspection time is defined as the time required to make an derive an index of mental speed (inspection time). Using a task accurate and reliable judgment in a readily discernible task. It is that is not susceptible to motor slowing enabled us to consider

M404 INSPECTION TIME AND BRADYPHRENIA M405

whether age-related differences in performance are largely due als as a familiarization with the required response and exposure to changes in cognitive speed with age or to peripheral factors duration. Each testing session consisted of 20 blocks of 1°trials such as motor slowing. (i.e., 200 trials). Pencil-and-paper tests were administered mid­ way through the session. METHODS RESULTS Participants.-Sixteen young adults (mean age 22.4 years) Mean accuracy for each condition was analyzed using a and 16 older adults (mean age 71.6 years), participated (see mixed model analysis of variance (ANOVA) with a between­ Table 1). There were equal numbers of males and females subjects factor of Group (young vs older adults) and a within­ within each group. Younger and older adults were matched for subjects factor of Interstimulus Interval (20, 40, 60, 80, 100, Downloaded from https://academic.oup.com/biomedgerontology/article/54/8/M404/542741 by guest on 30 September 2021 years of education and intelligence using the National Adult 125, 150, 175,200,250 msec). Reading Test (NART), which is highly correlated with general intelligence (13) and provides a measure of general intellectual Accuracy.-Accuracy scores (out of20) for the different lSI ability uncontaminated by cohort differences in age. Partici­ are shown in Figure 1. As lSI increased in duration, signifi­ pants had normal or corrected-to-normal vision. cantly fewer errors were made [F(9,270) = 43.65, P < .01]. Trend analysis revealed a significant linear component to the Apparatus and task.-The stimulus display consisted of a effect of lSI [F(1,270) = 263.01, p < .01] upon accuracy, indi­ central red light-emitting diode (LED) 7mm in diameter and cating a steady improvement in accuracy as the lSI increased. two lateral green LEDs (10 mm in diameter) mounted on a Younger adults performed at significantly higher levels of matt-black display panel measuring 110 X 195 mm. The two accuracy (mean = 19.0) than older adults (mean = 17.6); lateral LEDs were situated 80 mm to the left and right ofthe [F(1,30) = 15.60, p < .01]. At the smallest lSI, both younger midline of the central LED. The stimulus display was located at and older adults performed at chance levels of accuracy. A sig­ eye level 600 mm away from the seated participant. A Toshiba nificant Group by lSI interaction [F(9,270) = 3.50,p < .001] in­ 486 laptop computer controlled stimulus presentation and data dicated that the two groups differed in the rate of improvement collection. in accuracy with greater intervals between the two stimuli. Participants recorded their responses by pressing one of two buttons mounted on a panel (measuring 110 by 55 mm) situ­ Inspection time.-Accuracy data were used to determine in­ ated 400 mm from the display. Buttons were 15 mm in diame­ spection time (IT). IT is calculated by fitting a cumulative nor­ ter and raised 10 mm from the panel, allowing responses to be mal ogive to each participant's data (8). Because a cumulative made using the forefingers of each hand. normal ogive is an exponential function, a log transform was The task consisted of judging the order of onset of two LEDs applied to accuracy scores (to 1 minus the probability correct), situated on either side of a central fixation point. Participants re­ and then a linear regression was performed upon accuracy and sponded to the LED first illuminated by pressing a button on lSI. The time required for a criterion level (95%) of accuracy the corresponding side. Ifparticipants could not discern which was then determined from the fitted function. Significant fits LED had been activated first, they were required to guess. Each were obtained for 87.5% of functions overall, with no signifi­ trial began with the presentation of a cue (1 msec before stimu­ cant difference in the proportion ofvariance accounted for by lus presentation) that was the activation of the central red LED. the fitted curves for each age group. The stimulus consisted of consecutive activation of the two lat­ Inspection time is the stimulus exposure for accurate perfor­ eral green LEDs. These remained illuminated until a response mance and is an index of speed of information processing. was made, thus masking any apparent motion. The interval be­ Inspection times were significantly shorter for young (82.9 tween the onset of the two lights (lSI) was: 20,40,60, 80, 100, msec) than older (158.6 msec) adults, [t(30) =-4.07,p < .01]. 125, 150, 175, 200, or 250 msec. Young adults required stimulation of briefer duration for accu­ rate judgments. Procedure.-The experiment was conducted in a well-lit The usual significant correlations were found between age room. A black cloth backdrop was used to minimize visual dis­ and DSST (r(30) = - .66, p < .01] such that older adults re­ traction. Participants completed two blocks of eight practice tri- quired more time on this transcription task. As the DSST may be affected by any age-related motor slowing, it is interesting to note a significant correlation between age and IT [r(30) =.62, Table 1.Characteristicsof theYoungerand OlderAdults p < .01], with young adults taking less time to acquire informa­ tion. This suggests that poorer performance on such tests is not Younger Adults Older Adults simply due to slower movement. While IT correlated with Age Mean (SD) Mean (SD) 1tests and tests ofperformance, it did not correlate with estimates of Age (yrs) 22.4 (2.3) 71.6 (6.4) 1(30) =28.77, p < .01 crystallized intelligence [i.e., NART,education; (3)]. Education (yrs) 12.9 (1.8) 12.8 (2.0) 1(30) =0.19,p > .05 National Adult 112.1 (5.5) 112.6 (7.2) 1(30) =0.22, p > .05 DISCUSSION Reading Test Although age-related slowing of performance has been re­ Mini-Mental State 29.8 (0.6) 29.6 (0.7) 1(30) =0.81, p > .05 ported, it has often reflected differences in factors such as edu­ Examination cation, motivation, and intelligence. This study investigated Beck Depression 3.1 (2.1) 4.7 (3.8) 1(30) =-1.50, p > .05 speed of elementary processing operations as indexed by in­ Inventory spection time, unconfounded by factors such as differences in M406 PHILLIPS ETAL.

Table2. ClinicalDatafor Patientswith Parkinson'sDisease

Disease Duration Disease Dose Patient Age Sex (years) Severity* Medication (mg/day) 62 F 12 14 Sinemet 1500/150 SinemetCR 200/50 2 61 M 17 14 Madopar 100/25 Permax 1.875

SinemetCR 400/100 Downloaded from https://academic.oup.com/biomedgerontology/article/54/8/M404/542741 by guest on 30 September 2021 3 78 M 5 12 Madopar 800/200 4 74 F 10 8 Sinemet 725/100 SinemetCR 300n5 5 69 F 6 9 Sinemet 50/12.5 SinemetCR 800/200 6 73 F 20 13 Madopar 300n5 7 71 F 5 13 Eldepryl 5 Madopar 600/150 8 74 F 5 7 Eldepryl 5 Madopar 300n5 SinemetCR 500/125 9 52 F 6 5 -t 10 67 M 13 11 MadoparQ 250/62.5 11 66 M 12 7 Sinemet WOO 12 67 M 5 3 Madopar 600/150 13 48 M 8 9 Sinemet WOO SinemetCR 100/25 14 55 M 6 7 Artane 6 Deprenyl 10 Madopar 1000/250 15 49 F 10 10 Madopar 150/37.5 SinemetCR 100/25 16 71 F 15 6 Cogentin 6 Madopar 400/100

*Rating of Parkinsonian symptons using Webster scale (16). tPredominantly tremorous patient not medicated.

movement speed. Older adults were significantly slower than ExperimentTwo younger adults at processing simple temporal order informa­ Experiment One supported clinical impressions of a slowing tion, and required longer interstimulus intervals to accumulate of information processing with age. Indeed, parallels have been sufficient evidence to make an accurate judgment about the drawn between the slowness of age and Parkinson's disease (4). order in which two LEDs were activated. Although primarily a affecting the basal Older adults were less able to judge order of stimulus onset, ganglia (BG), PD is also characterized by bradyphrenia (5), and implying that they had slower "mental clocks." However, these up to 40% ofpatients (14) are reported to be demented. An in­ age differences in mental speed were not due to cohort differ­ vestigation of Parkinsonian bradyphrenia may contribute to an ences in educational level or intelligence, as participants were understanding of information processing rates and potentially matched on these variables. Cognitive slowing in older adults identify biological mechanisms underlying cognitive slowing. was also not attributable to impaired cognitive status, as partici­ Experiment Two considered whether the disturbances ofBG pants were screened for . Participants were also function caused by PD affect the speed of information process­ screened for , , head injuries, and psychiatric disor­ ing, over and above that ofnormal aging. Because inspection ders; thus, these factors did not influence age-related differences time measures cognitive speed independently of motor involve­ in mental speed. Because the estimate of mental speed (IT) was ment, this task is useful in studying PD, which reportedly derived from accuracy, our data indicate that a sizable cause of causes bradyphrenia. As we were specifically interested in the slowing is of central rather than a peripheral (motor) origin. contribution of the BG to cognitive speed, we excluded PD pa- INSPECTION TIME AND BRADYPHRENIA M407

tients exhibiting dementia, as other structures are implicated in group and lSI [F(9,270) = 1.22,p > .05], indicating that the rate such patients (15). of improvement in accuracy with greater intervals between the Hitherto, speed of information processing in PD has typi­ two stimuli was similar for both groups. cally been assessed with tasks involving a motor component; as PD is primarily a motor disorder, such procedures may overes­ Inspectiontime.-Measures of IT were derived from the ac­ timate cognitive impairments in this population. IfPD causes curacy data. Significant fits were obtained for 90% of functions bradyphrenia, PD patients will require longer ITs even when in this sample, with no significant difference in the degree of fit controlling for motor impairments. On the other hand, if obtained for PD and control groups. There were no appreciable bradyphrenia in PD is merely an artifact of aging and slower differences in mean IT between the PD group (mean = 206.1 Downloaded from https://academic.oup.com/biomedgerontology/article/54/8/M404/542741 by guest on 30 September 2021 movements of these patients, then PD patients will not require msec) and controls [mean = 204.1 msec; t(30) = .03,p > .05]. longer ITs. A significant correlation between IT and MMSE [r(30) = -.42, p < .05] indicated that poorer mental status was associated METHOD with slower cognitive speed. The relationships between clinical measures of disease severity and IT were also examined. There Participants.-Participants were screened for prior head in­ were, however, no significant correlations between IT and jury, stroke, and other neurological or psychiatric conditions in symptom severity [r(l4) =-.25,p > .05] or disease duration addition to Parkinson's disease. Sixteen patients (7 male, 9 fe­ [r(l4) = -.29, p > .05], indicating that changes in cognitive male) diagnosed with idiopathic Parkinson's disease partici­ speed when uncontaminated by motor slowing were unrelated pated. Mean duration of disease was 9.7 years (SD =4.8); to severity of PD symptoms. symptom severity was measured using the Webster Scale (16); clinical characteristics may be seen in Table 2. As outlined in Table 3, 16 control participants were matched to PD patients for age, sex, years of education, and premorbid intelligence [es­ timated using NART (13)]. Participants had normal or cor­ rected-to-normal vision. 20 All participants were screened for dementia using the Mini­ Mental State Examination [MMSE; (17)]. While no partici­ ,-.. ~ 18 pants were excluded on the grounds of dementia, a significant independent sample t test indicated the PD group (mean = 28.6) x" o 16 had slightly poorer mental status than the controls [mean = E 29.6; t(30) = -2.18,p < .05]. ~ 14 o Apparatus, task, and procedure.-The apparatus and task L :::J were the same as in Experiment One. The procedure was also ~ 12 the same except that Webster scales were administered at the -c beginning of each testing session, and the DSST was not ad­ 10 L-__L-__L-__.L.-..__.L.-_---l ministered because its large motor-component potentially inval­ o 50 100 150 200 250 idates its use as a test of cognitive function in the PD group. Interstimulus Interval (ms)

RESULTS Figure 1. Accuracy as a function of interstimulus intervals for both younger (closed circles) and older adults (open circles). Accuracy.-Mean accuracy scores for the different lSI are shown in Figure 2. A two-way ANOVA (Group X lSI) revealed a significant effect of lSI [F(9,270) = 35.41,p < .01], with both 20 groups responding more accurately as the lSI increased. ,-.. Control Although controls (17.4) tended to be more accurate for each 0 18 lSI than PD patients (16.9), there was no significant group ef­ N fect [F(1,30) =0.81,p < .05]. There was no interaction between X 1/ " 0" 16 E V,'1 >- 1:,/1 Table3. Characteristics of PatientsWith o 14 ,~ PD 0 I L I Parkinson's Disease (PD) and the Controls :::J , o o 12 PDPatients Controls -c y Mean (SD) Mean (SD) t tests 10 L-__.L.-__.L.-__.L.-__.L..--_-----J Age (yrs) 66.1 (11.0) 66.4 (11.4) t (30) =~.08, p > .05 o 50 100 150 200 250 Education (yrs) 10.9 (2.7) 11.3 (2.7) t (30) ~.33, p > .05 = Interstimulus Interval (ms) Verbal Intelligence 110.7 (7.7) 112.4 (5.2) t(30) =~.81,p > .05 (National Adult Figure 2. Accuracy as a function of interstimulus intervals for both Reading Test) Parkinsons's disease [PD (open circles); and contol (closed circles) groups]. M408 PHILLIPS ETAL

DISCUSSION CONCLUSION Although Parkinson's disease is clinically reported to cause The speed of information processing may underlie age­ bradyphrenia (5), the assessment ofcognitive slowing may re­ related differences in measured intelligence. Information pro­ flect the behavioral measures employed, as cognitive speed is cessing rate is typically inferred from behavioral measures of typically inferred from movements when performing cognitive performance. Most tasks purporting to measure information tasks. Given that PD is a motor disorder, clinical impressions of processing rate involve a motor component reducing their con­ bradyphrenia in PD may to some extent reflect the diminished struct validity as measures of cognitive speed. A substantial capacity of these patients to express themselves. slowing in information processing rate was found in older This study investigated information processing speed in a adults compared to younger adults matched for education and Downloaded from https://academic.oup.com/biomedgerontology/article/54/8/M404/542741 by guest on 30 September 2021 group ofnondemented PD patients using a task that measured intelligence. Age-related differences in cognitive speed were cognitive speed independently of movement. Results indicated also not influenced by requirements for a speeded motor re­ that nondemented Parkinsonian patients did not exhibit a cogni­ sponse, as our index of cognitive speed was inferred from accu­ tive slowing beyond that found in normal aging when control­ racy rather than reaction time. ling for motor impairment. In other words, PD patients did not Cognitive slowing exists in older adults independent of dif­ exhibit bradyphrenia when controlling for akinesia (difficulty ferences in educational or motor capacity. As cognitive slowing initiating movement), bradykinesia (difficulty maintaining was not salient in PD, the mechanisms ofage-related cognitive movement), or dementia. slowing are unlikely to originate from basal ganglia dysfunc­ Disorders ofthe basal ganglia are thought to cause a subcor­ tion. A generalized slowing ofinformation processing was not tical dementia (5). Parkinson's disease affects apparent in these patients with Parkinson's disease. There is a cells in the Pars Compacta (SNc) regulating need to consider age and motor infirmity when addressing clin­ the basal ganglia circuits (18). While the central and caudal end ical manifestations of bradyphrenia. ofthe SNc, which projects to the , is predominantly af­ fected, the disorder is not so localized that other structures are ACKNOWLEDGMENTS uninvolved. Indeed, the juxtaposition of motor and cognitive circuits and the involvement of other structures suggest that This study was supported by grants from the Australian Research Council and the Alzheimer's Association of Australia. cognitive dysfunction is likely. Nevertheless, reports of cognitive impairment in Parkinson's We are grateful for the assistance of the people with Parkinson's disease who gave so freely of their time and the Kingston Centre for the use of their facilities. disease remain controversial. Some studies report a slowing of thought processes (19,20), while others do not (21,22). Given this Address correspondence to Dr. James G. Phillips, Department of Psychology, Monash University, Clayton VIC 3168, Australia. 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