Of the remaining participants, They had an average United States equivalent of Ethnically, the sample was primarily of European background The remaining 4. Performance of subjects in the seven different age groups in Experiment 1. Also shown are the averages of all subjects in Experiments 1 and 2. The regressed z-scores were derived using parameters from Experiment 1.
Participants responded to the target blue P by pressing the left mouse button, and responded to the other three stimuli with a right mouse button press, with responses reversed for participants who preferred to use the mouse with their left hand. The letters P and F appeared in blue or orange colors selected to reduce the influence of possible dichromatic anomalies , with distractors differing from the target in both color and shape orange F , only shape blue F , or only color orange P.
The adaptive visual feature conjunction task. Subjects performed a visual feature conjunction task with colored letters blue P, blue F, orange P, or orange F subtending 0.
Stimulus durations were ms. Stimuli could occur ipsilateral trials 1 and 2 or contralateral trial 3 to the mouse button used for responding. Stimuli were of high contrast orange letters were Stimulus durations were fixed at ms. One-hundred-forty trials were included in the test. CRT testing required approximately 5 min, and occurred midway through a min computerized test battery that included, in order, tests of finger tapping Hubel et al.
Participants sat 0. Reaction time measurements are influenced by the computer hardware used for stimulus display and response monitoring Plant and Turner, ; Neath et al. Therefore, measures of timing precision are necessary to compare results across different computer systems Plant and Quinlan, We measured a delay of Responses were recorded with a high-precision gaming mouse Razer, Copperhead, Carlsbad, CA using an internal driver with a 1. Thus, hardware delays totaled In addition to hardware delays, software interruptions can introduce unpredictable delays that increase CRT latencies and trial-to-trial latency variability.
The frequency and duration of software interruptions depends on both the design of the stimulus-delivery software and on the number and type of extraneous software processes running concurrently.
Timing interruptions must be continuously monitored throughout an experiment to assure timing precision. Presentation software reports event-time uncertainties for each event during an experiment by continuously sampling the kHz programmable clock. CRT measurements were extremely precise: , events showed a median event-time uncertainty of 0.
We quantified mean CRT latencies for each type of stimulus, along with intrasubject trial-to-trial CRT standard deviations and hit rates. A response window of — ms was used, and failure to generate a response during this interval was categorized as an omission. In cases where SOAs were reduced below ms, multiple responses could occur within a response window. In this case, responses were assigned to stimuli in the order in which they occurred. Participants were classified into seven different 7 year wide age ranges e.
Greenhouse-Geisser corrections of degrees of freedom were uniformly used in computing p values in order to correct for covariation within factors or interactions. Correlation analysis was also used to analyze the effects of age and education, and to develop age-regression functions. We first analyzed the results by Age-group with Visual Field and Type of stimulus target, distractor with no target features, distractor with target color, and distractor with target shape as factors. The effects of visual field were also analyzed.
Mean choice reaction times CRTs. Mean CRTs averaged over stimulus types for subjects of different ages from Experiments 1 blue diamonds and 2 open red squares. The linear fit for Experiment 1 data is shown. Further analysis showed that mSOAs were significantly elevated in the youngest and oldest participants, relative to other age groups.
Minimum stimulus onset asynchronies mSOAs. Shown as a function of age for subjects in Experiments 1 and 2. Hit rates averaged Responses were faster to the distractor with no target features ms and to the target ms than to distractors with target-shape ms or distractors with target-color ms.
CRTs to stimuli of different types in Experiment 1. In order to examine the effects of spatial compatibility between stimuli and responses, we performed another ANOVA with Visual field spatially compatible or incompatible with the finger used for responding e.
There were several negative results of note. However, mSOAs were slightly shorter in female participants vs. Mean central processing time CPT. Linear fit is shown for Experiment 1 data. We used additional subtraction procedures to analyze age-related changes in the time required for different processing stages.
CRT latencies in the current experiment reflected the time needed to 1 detect the stimulus; 2 identify the stimulus and select an appropriate response; and 3 depress the button.
Previous SRT and finger-tapping studies of the same participants in the same test session had provided estimates of stage 1, stimulus-detection time SDT; Woods et al. The time required for stage 2 was reflected in the CPT: i. The MCPT stage would therefore include the time needed to discriminate the distractor with no target features from the target relative to the time needed to merely detect the occurrence of a stimulus in the SRT task , as well as the time needed to select the appropriate response.
The duration of the CFPT was estimated from the additional time mean As previously described Woods et al. Of the total age-related CRT slowing Age-related changes in different processing stages for Experiment 1. Changes in ms are shown relative to the duration of each processing stage in the youngest subjects 18—24 years. Stimulus detection time SDT and movement-initiation time MIT had been measured in previous tests performed on the same day.
AR-CRTs had a residual standard deviation of Finally, to quantify overall performance on the visual feature conjunction task for comparison with other populations, we created an Omnibus z -score by combining AR-CRT z -scores and log-transformed mSOA z -scores from each participant.
The increase in CRT latencies with age in the current study 2. Highly significant effects of aging were found: mean CRT latencies in 59—65 year old participants were increased by more than ms 1. This is in agreement with many studies that find larger absolute and relative age-related increases in CRT latencies than SRTs Yordanova et al.
Finally, The magnitude of CRT slowing was similar to the age-related increases in search asymptotes observed in both feature search and conjunction search conditions Plude and Doussard-Roosevelt, ; Hommel et al. In accord with previous studies, we found that aging increased both inter-subject standard deviations Bugg et al.
However, in contrast to previous studies Dykiert et al. Among the many methodological differences between previous large-scale studies and the current experiment, we gathered data from more trials and provided more training, suggesting that older participants may require a longer training period to achieve stable performance. We found no sex differences in CRT latencies, nor did we find significant sex differences in intrasubject reaction time variance or hit-rate. These results also agree with some previous studies Deary and Der, , but conflict with others Houx and Jolles, ; Dykiert et al.
The remaining age-related delay was due largely to slowed motor responses. Plude and Doussard-Roosevelt found that older participants required Thus, their reported age-related increase in the time needed to integrate visual features e. Aging also slows response selection due, in part, to increases in intrahemispheric van der Lubbe and Verleger, ; Rabbitt et al. In addition, aging delays response generation in motor cortex Falkenstein et al. However, age-related changes are not uniform for different processing stages.
Simple reaction time SRT latencies, which engage stimulus detection and response production stages, increase by 20—40 ms from age 20—65 Woods et al. In contrast, CRT latencies, which include the additional processing stages of stimulus discrimination and response selection, slow by 90— ms over the same age range see Table 1.
Thus, age-related slowing in stimulus perception and motor responses would appear to account for only a small percentage of the age-related slowing of CRT latencies; i. Age-related changes in visual discrimination have been examined extensively in visual search tasks Plude and Doussard-Roosevelt, ; Schialfa et al. Older participants, like their younger counterparts, have flat search slopes as a function of display size in feature search tasks where targets are distinguished from distractors by color or shape Plude and Doussard-Roosevelt, However, in feature-conjunction conditions, where targets are distinguished from distractors by a combination of features e.
Here, we analyzed CRT latencies in a population sample of adults ranging in age from 18—65 years using a serial feature-conjunction task.
In order to optimize the utility of the normative data for subsequent clinical test applications, individual stimuli were presented serially to the left or right visual field and stimulus onset asynchronies SOAs were adaptively reduced based on participant accuracy. We expected to find significant age-related slowing because each trial required the participant to integrate color and shape information before choosing an appropriate response.
We anticipated that CRT latencies would be faster for distractors with no target features than for distractors that shared either target color or shape, and that this difference would increase with age, reflecting an increase in sensory processing time Habekost et al.
Finally, we anticipated that participants would respond more rapidly when the stimulus and response button were spatially compatible, and that this spatial-compatibility effect would also increase with age van der Lubbe and Verleger, In order to clarify the processing stages affected by aging, we included estimates of stimulus detection time SDT, the time needed to detect a visual stimulus , measured in the same participants in an SRT task Woods et al.
We studied a subset of community volunteers in Rotorua, New Zealand, who participated in a study of the health effects of environmental exposure to varying levels of naturally-occurring hydrogen sulfide H 2 S Reed et al. Written informed consent was obtained from all participants following Institutional Review Board study procedures for the University of California, Berkeley and the Northern Ethics Committee in New Zealand.
Because we wanted to analyze age-related changes in different processing stages through a comparison of results across tests, we eliminated participants who lacked complete data sets in either a finger-tapping test Hubel et al. Of the remaining participants, They had an average United States equivalent of Ethnically, the sample was primarily of European background The remaining 4.
Table 2. Performance of subjects in the seven different age groups in Experiment 1. Figure 1 shows the stimuli. Participants responded to the target blue P by pressing the left mouse button, and responded to the other three stimuli with a right mouse button press, with responses reversed for participants who preferred to use the mouse with their left hand. The letters P and F appeared in blue or orange colors selected to reduce the influence of possible dichromatic anomalies , with distractors differing from the target in both color and shape orange F , only shape blue F , or only color orange P.
Figure 1. The adaptive visual feature conjunction task. Subjects performed a visual feature conjunction task with colored letters blue P, blue F, orange P, or orange F subtending 0. Stimulus durations were ms.
Stimuli could occur ipsilateral trials 1 and 2 or contralateral trial 3 to the mouse button used for responding. Stimuli were of high contrast orange letters were Stimulus durations were fixed at ms. One-hundred-forty trials were included in the test. CRT testing required approximately 5 min, and occurred midway through a min computerized test battery that included, in order, tests of finger tapping Hubel et al.
Participants sat 0. Reaction time measurements are influenced by the computer hardware used for stimulus display and response monitoring Plant and Turner, ; Neath et al. Therefore, measures of timing precision are necessary to compare results across different computer systems Plant and Quinlan, We measured a delay of Responses were recorded with a high-precision gaming mouse Razer, Copperhead, Carlsbad, CA using an internal driver with a 1.
Thus, hardware delays totaled In addition to hardware delays, software interruptions can introduce unpredictable delays that increase CRT latencies and trial-to-trial latency variability. The frequency and duration of software interruptions depends on both the design of the stimulus-delivery software and on the number and type of extraneous software processes running concurrently. Timing interruptions must be continuously monitored throughout an experiment to assure timing precision.
Presentation software reports event-time uncertainties for each event during an experiment by continuously sampling the kHz programmable clock. CRT measurements were extremely precise: , events showed a median event-time uncertainty of 0. We quantified mean CRT latencies for each type of stimulus, along with intrasubject trial-to-trial CRT standard deviations and hit rates.
A response window of — ms was used, and failure to generate a response during this interval was categorized as an omission. In cases where SOAs were reduced below ms, multiple responses could occur within a response window. In this case, responses were assigned to stimuli in the order in which they occurred.
Participants were classified into seven different 7 year wide age ranges e. Greenhouse-Geisser corrections of degrees of freedom were uniformly used in computing p values in order to correct for covariation within factors or interactions. Correlation analysis was also used to analyze the effects of age and education, and to develop age-regression functions. Figure 2 blue diamonds shows a scatter plot of mean CRT latencies as a function of participant age, and Table 2 provides a summary of demographic information and performance data including CRT latencies and additional metrics that are described below.
We first analyzed the results by Age-group with Visual Field and Type of stimulus target, distractor with no target features, distractor with target color, and distractor with target shape as factors. The effects of visual field were also analyzed. Figure 2. Mean choice reaction times CRTs. Mean CRTs averaged over stimulus types for subjects of different ages from Experiments 1 blue diamonds and 2 open red squares.
The linear fit for Experiment 1 data is shown. Table 3 shows the correlations of age and education with different performance metrics discussed below. Further analysis showed that mSOAs were significantly elevated in the youngest and oldest participants, relative to other age groups. Figure 3. Minimum stimulus onset asynchronies mSOAs. Shown as a function of age for subjects in Experiments 1 and 2.
Hit rates averaged Responses were faster to the distractor with no target features ms and to the target ms than to distractors with target-shape ms or distractors with target-color ms. Figure 4. CRTs to stimuli of different types in Experiment 1. In order to examine the effects of spatial compatibility between stimuli and responses, we performed another ANOVA with Visual field spatially compatible or incompatible with the finger used for responding e. There were several negative results of note.
However, mSOAs were slightly shorter in female participants vs. As shown in Figure 5 blue diamonds , CPTs mean Figure 5. Mean central processing time CPT. Linear fit is shown for Experiment 1 data. We used additional subtraction procedures to analyze age-related changes in the time required for different processing stages. CRT latencies in the current experiment reflected the time needed to 1 detect the stimulus; 2 identify the stimulus and select an appropriate response; and 3 depress the button.
Previous SRT and finger-tapping studies of the same participants in the same test session had provided estimates of stage 1, stimulus-detection time SDT; Woods et al. The time required for stage 2 was reflected in the CPT: i. The MCPT stage would therefore include the time needed to discriminate the distractor with no target features from the target relative to the time needed to merely detect the occurrence of a stimulus in the SRT task , as well as the time needed to select the appropriate response.
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Variability Within Persons. Relationships to Cognitive Performance. Hultsch , David F. Oxford Academic. Google Scholar. Stuart W. Roger A. Cite Cite David F. Select Format Select format. Permissions Icon Permissions.
Seidler and her colleagues are developing and piloting motor training studies that might rebuild or maintain the corpus callosum to limit overflow between hemispheres, she said. A previous study done by another group showed that doing aerobic training for three months helped to rebuild the corpus callosum, she said, which suggests that physical activity can help to counteract the effects of the age-related degeneration.
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