发表一篇学和医学成像类SCI论文
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Abstract:
:To efficiently learn optimal behavior in complex environments, humans rely on an interplay of learning and attention. Healthy aging has been shown to independently affect both of these functions. Here, we investigate how reinforcement learning and selective attention interact during learning from trial and error across age groups. We acquired behavioral and fMRI data from older and younger adults (male and female) performing two probabilistic learning tasks with varying attention demands. Although learning in the unidimensional task did not differ across age groups, older adults performed worse than younger adults in the multidimensional task, which required high levels of selective attention. Computational modeling showed that choices of older adults are better predicted by reinforcement learning than Bayesian inference, and that older adults rely more on reinforcement learning-based predictions than younger adults. Conversely, a higher proportion of younger adults' choices was predicted by a computationally demanding Bayesian approach. In line with the behavioral findings, we observed no group differences in reinforcement-learning related fMRI activation. Specifically, prediction-error activation in the nucleus accumbens was similar across age groups, and numerically higher in older adults. However, activation in the default mode was less suppressed in older adults in for higher attentional task demands, and the level of suppression correlated with behavioral performance. Our results indicate that healthy aging does not significantly impair simple reinforcement learning. However, in complex environments, older adults rely more heavily on suboptimal reinforcement-learning strategies supported by the ventral striatum, whereas younger adults use attention processes supported by cortical networks.SIGNIFICANCE STATEMENT Changes in the way that healthy human aging affects how we learn to optimally behave are not well understood; it has been suggested that age-related declines in dopaminergic function may impair older adult's ability to learn from reinforcement. In the present fMRI experiment, we show that learning and nucleus accumbens activation in a simple unidimensional reinforcement-learning task was not significantly affected by age. However, in a more complex multidimensional task, older adults showed worse performance and relied more on reinforcement-learning strategies than younger adults, while failing to disengage their default-mode network during learning. These results imply that older adults are only impaired in reinforcement learning if they additionally need to learn which dimensions of the environment are currently important.
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最新影响因子:6.709 | 期刊ISSN:0270-6474 | CiteScore:5.89 |
出版周期:Weekly | 是否OA:YES | 出版年份:1981 |
期刊官方网址:http://www.jneurosci.org/
自引率:5.50% | 研究方向:医学-神经科学 |
出版地区:UNITED STATES |
SCI期刊coverage:Science Citation Index Expanded(科学引文索引扩展)
专业编辑在线一对一答疑及时解决您的问题
The official journal of the Society for Neuroscience, available in full text 1996 forward with plans to archive five years of full text issues. Tables of contents for future issues. Publication precedes receipt of print edition. Available free to Society members and selected librarians for 1997. Available for subscription in 1998. Includes thumbnail expandable graphics.
神经科学学会的官方期刊,1996年出版全文,计划存档5年的全文。未来问题的目录。出版先于收到印刷版。1997年免费提供给社会成员和选定的图书馆员。于一九九八年可供订阅。包括缩略图可扩展的图形。
大类(学科) | 小类(学科) | 学科排名 |
医学 |
NEUROSCIENCES (神经科学) 2区 |
30/261 |
年度总发文量 | 年度论文发表量 | 年度综述发表量 |
931 | 931 | 0 |
引文计数(2018)
文献(2015-2017)
24720次引用
4194篇文献
序号 | 类别 | 排名 | 百分位 |
1 |
大类(学科):Neuroscience
小类(学科):General Neuroscience
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#12/111
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研究方向:生命科学 遗传学 生物信息学 动物遗传学
审稿时间: 1个月内
影响因子:2.995
ISSN:0028-3940
研究方向:医学-核医学
影响因子:2.324
ISSN:1051-2284
研究方向:医学-核医学
影响因子:3.156
ISSN:1869-1439
研究方向:CLINICAL NEUROLOGY-RADIOLOGY, NUCLEAR MEDICINE & M
影响因子:4.6
ISSN:0150-9861
研究方向:医学-核医学
影响因子:1.764
ISSN:1591-0199
研究方向:CLINICAL NEUROLOGY-RADIOLOGY, NUCLEAR MEDICINE & M
影响因子:4.966
ISSN:0195-6108
研究方向:医学-核医学
影响因子:3.005
ISSN:0301-0449
研究方向:医学-核医学
影响因子:2.396
ISSN:1793-5458
研究方向:OPTICS-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGI
影响因子:3.632
ISSN:1084-9785
研究方向:医学-核医学
发表一篇学和医学成像类SCI论文
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