Elsevier

Neurobiology of Aging

Volume 46, October 2016, Pages 96-106
Neurobiology of Aging

Regular article
Contrasting neural effects of aging on proactive and reactive response inhibition

https://doi.org/10.1016/j.neurobiolaging.2016.06.007Get rights and content

Abstract

Two distinct forms of response inhibition may underlie observed deficits in response inhibition in aging. We assessed whether age-related neurocognitive impairments in response inhibition reflect deficient reactive inhibition (outright stopping) or also deficient proactive inhibition (anticipatory response slowing), which might be particularly evident with high information load. We used functional magnetic resonance imaging in young (n = 25, age range 18–32) and older adults (n = 23, 61–74) with a stop-signal task. Relative to young adults, older adults exhibited impaired reactive inhibition (i.e., longer stop-signal reaction time) and increased blood oxygen level-dependent (BOLD) signal for successful versus unsuccessful inhibition in the left frontal cortex and cerebellum. Furthermore, older adults also exhibited impaired proactive slowing, but only as a function of information load. This load-dependent behavioral deficit was accompanied by a failure to increase blood oxygen level-dependent (BOLD) signal under high information load in lateral frontal cortex, presupplementary motor area and striatum. Our findings suggest that inhibitory deficits in older adults are caused both by reduced stopping abilities and by diminished preparation capacity during information overload.

Introduction

Older adults can have trouble stopping an action. Indeed, relative to young adults, older adults have been shown to exhibit impaired response inhibition in classic stop-signal paradigms; that is they need more time to stop a response when presented with a stop signal (Bedard et al., 2002, Kramer et al., 1994, van de Laar et al., 2011). At the neural level, older adults are known to exhibit attenuated blood oxygen level-dependent (BOLD) signal as well as reduced tract strength between brain regions involved in response inhibition (Coxon et al., 2012, Coxon et al., 2016). However, the processes underlying these age-related behavioral and neural deficits in response inhibition are unclear. Two forms of response inhibition have been distinguished: reactive response inhibition is the process of canceling an ongoing response at the moment this is needed (i.e., outright stopping), whereas proactive response inhibition entails the preparation for stopping when this may become necessary. Experimental designs in previous studies on aging did not enable the separate investigation of reactive and proactive response inhibition. Thus, it remains unclear whether the effects of aging on response inhibition, both neurally and behaviorally, reflect deficient reactive or also altered proactive processing. This issue is particularly pertinent given recent proposals that an understanding of cognitive control deficits in aging requires taking into account dual—reactive and proactive—mechanisms of control (Braver et al., 2007) and evidence indicating deficient proactive but intact reactive control with age (Bugg, 2014, Jimura and Braver, 2010, Paxton et al., 2008).

Cautious response slowing in preparation for the possible upcoming need to stop increases the probability of successful stopping. Older adults might lack the cognitive capacity to process preparatory cues during information overload. Indeed, there is clear evidence for (load-dependent) reductions in working memory capacity due to deficits in prefrontal cortex functioning (Gazzaley et al., 2005, Nagel et al., 2009, Nyberg et al., 2010). By analogy, work with patients with schizophrenia has demonstrated an association between poor proactive response inhibition and low working memory capacity as well as reduced BOLD responses in frontal cortex (Zandbelt et al., 2011). Here, we investigated whether diminished response inhibition in older adults is accompanied by altered behavioral and neural preparation for inhibition and whether this is particularly evident in situations of information overload.

To address these questions, young and older adults were scanned using event-related functional magnetic resonance imaging (fMRI) during the performance of an adapted version of a stop-signal task that allowed us to disentangle proactive and reactive response inhibition (Zandbelt and Vink., 2010). To assess whether response inhibition in aging varies as a function of information load, we manipulated the information processing demands required for interpreting the stop-signal probability cues.

A simple go task required a button press on every trial, unless a stop signal appeared indicating that the initiated button press had to be canceled. A measure of reactive response inhibition was obtained based on the race model (Logan and Cowan, 1984) by calculating the time needed to cancel an initiated response (i.e., the stop-signal reaction time [SSRT]). In addition, proactive slowing was indexed by the degree of preparatory response slowing of reaction times in response to cues signaling stop-signal probability (Chikazoe et al., 2009, Jahfari et al., 2010, Verbruggen and Logan, 2009c, Vink et al., 2005, Zandbelt and Vink, 2010). This stop-signal probability was manipulated parametrically, so that higher stop-signal likelihood would elicit greater proactive slowing. Critically, we also manipulated the information processing demands for interpreting these stop-signal probability cues, thus allowing us to assess our key hypothesis that besides behavioral and neural impairments during reactive response inhibition (as previously discussed), aging is accompanied also by deficits in proactive inhibition and associated prefrontal cortex signaling. Specifically, the effect of aging on proactive inhibition may vary as a function of information load because increased information load places greater weight on prefrontal resources that are vulnerable to aging.

Section snippets

Participants

Forty-eight participants were included in the analyses: 25 young (mean age: 22.7 years, range 18–29, 14 men) and 23 older adults (mean age: 67.6 years, range 61–74, 14 men). Participants met the following inclusion criteria: normal or corrected-to-normal vision, right handed, functioning within normal limits of general cognitive function with the mini-mental state examination (Folstein et al., 1975) (cutoff > 27 of 30), estimated verbal intelligence quotient (IQ) >85 (Schmand et al., 1991), no

Behavioral results

Demographics and neuropsychological test scores from both age groups are presented in Table 1; an overview of task performance is given in Table 2. Response times of the participants followed the assumptions of the independent race model (Supplementary Materials 1.1, Table S1, and Fig. S1).

Discussion

We investigated how aging and information load impact inhibitory control. To this end, older and young individuals performed a stop-signal task designed to measure reactive inhibition (outright stopping) and proactive inhibition (anticipatory response slowing) across low, intermediate, and high levels of information load while being scanned with fMRI. We report 3 main findings.

First, reactive stopping was slower in older than young adults and was accompanied by more age-related activation of

Disclosure statement

The authors have no actual or potential conflicts of interest.

Acknowledgements

The authors would like to thank Ilke van Loon, Sanne Tops, and Ratigha Varatheeswaran for their help with data collection and data processing. This work is part of the FOCOM project, which was supported by the European Regional Development Fund (European Union) and the Dutch provinces Gelderland and Overijssel (grant number 2011-017004). The author Esther Aarts was supported by a VENI grant of the Netherlands Organisation for Scientific Research (NWO) (016.135.023).

References (53)

  • F. Verbruggen et al.

    Response inhibition in the stop-signal paradigm

    Trends Cogn. Sci.

    (2008)
  • F. Verbruggen et al.

    Models of response inhibition in the stop-signal and stop-change paradigms

    Neurosci. Biobehav. Rev.

    (2009)
  • B.B. Zandbelt et al.

    Reduced proactive inhibition in schizophrenia is related to corticostriatal dysfunction and poor working memory

    Biol. Psychiatry

    (2011)
  • A.R. Aron et al.

    Cortical and subcortical contributions to Stop signal response inhibition: role of the subthalamic nucleus

    J. Neurosci.

    (2006)
  • A. Bedard et al.

    Developmental neuropsychology the development of selective inhibitory control across the life span

    Dev. Neuropsychol.

    (2002)
  • Braver, T.S., Gray, J., Burgess, G., 2007. Explaining the Many Varieties of Working Memory Variation: Dual Mechanisms...
  • J.M. Bugg

    Evidence for the sparing of reactive cognitive control with age

    Psychol. Aging

    (2014)
  • J. Chikazoe et al.

    Preparation to inhibit a response complements response inhibition during performance of a stop-signal task

    J. Neurosci.

    (2009)
  • J.P. Coxon et al.

    Functional brain activation associated with inhibitory control deficits in older adults

    Cereb. Cortex

    (2014)
  • J.P. Coxon et al.

    Aging and inhibitory control of action: cortico-subthalamic connection strength predicts stopping performance

    J. Neurosci.

    (2012)
  • M. D'Esposito et al.

    Alterations in the BOLD fMRI signal with ageing and disease: a challenge for neuroimaging

    Nat. Rev. Neurosci.

    (2003)
  • B.U. Forstmann et al.

    The speed-accuracy tradeoff in the elderly brain: a structural model-based approach

    J. Neurosci.

    (2011)
  • A. Gazzaley et al.

    Top-down suppression deficit underlies working memory impairment in normal aging

    Nat. Neurosci.

    (2005)
  • H.M. Huizenga et al.

    Muscle or motivation? A stop-signal study on the effects of sequential cognitive control

    Front. Psychol.

    (2012)
  • M. Jahanshahi et al.

    A fronto–striato–subthalamic–pallidal network for goal-directed and habitual inhibition

    Nat. Rev. Neurosci.

    (2015)
  • S. Jahfari et al.

    Responding with restraint: what are the neurocognitive mechanisms?

    J. Cogn. Neurosci.

    (2010)
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