The influence of perceptual training on working memory in older adults

Anne S Berry, Theodore P Zanto, Wesley C Clapp, Joseph L Hardy, Peter B Delahunt, Henry W Mahncke, Adam Gazzaley, Anne S Berry, Theodore P Zanto, Wesley C Clapp, Joseph L Hardy, Peter B Delahunt, Henry W Mahncke, Adam Gazzaley

Abstract

Normal aging is associated with a degradation of perceptual abilities and a decline in higher-level cognitive functions, notably working memory. To remediate age-related deficits, cognitive training programs are increasingly being developed. However, it is not yet definitively established if, and by what mechanisms, training ameliorates effects of cognitive aging. Furthermore, a major factor impeding the success of training programs is a frequent failure of training to transfer benefits to untrained abilities. Here, we offer the first evidence of direct transfer-of-benefits from perceptual discrimination training to working memory performance in older adults. Moreover, using electroencephalography to evaluate participants before and after training, we reveal neural evidence of functional plasticity in older adult brains, such that training-induced modifications in early visual processing during stimulus encoding predict working memory accuracy improvements. These findings demonstrate the strength of the perceptual discrimination training approach by offering clear psychophysical evidence of transfer-of-benefit and a neural mechanism underlying cognitive improvement.

Conflict of interest statement

Competing Interests: J.L.H., P.B.D., and H.W.M. are or were employees of Posit Science Corporation and have stock or stock options. This does not alter the authors' adherence to all the PLoS ONE policies on sharing data and materials.

Figures

Figure 1. Perceptual discrimination.
Figure 1. Perceptual discrimination.
1a. Perceptual discrimination training paradigm. Gabor pattern filters required a discrimination judgment of whether the stimuli expanded or contracted. Training was adaptive, such that changes in the ISI and stimuli duration scaled with performance. 1b. Training effects on trained task. Trained older adults showed significant improvement over untrained controls at medium and high difficulty tasks (100 ms and 50 ms stimuli and ISI duration, respectively). 1c. Untrained perceptual discrimination paradigm. Discrimination thresholds for direction of 100% coherent motion was tested using moving dot kinetograms. Participants made a judgment as to whether two presented directions of motion matched one another. 1d. Training effects on untrained task. Perceptual discrimination thresholds of trained older adults improved significantly more than untrained controls. * Asterisks indicate significant differences within group from T1 to T2 (paired t-test). Crosses indicates significant group by time interactions (repeated measures ANOVA).
Figure 2. Working memory paradigm.
Figure 2. Working memory paradigm.
Delayed-recognition paradigm. Working memory for the direction of 100% coherent motion was tested using moving dot kinetograms in two tasks. Participants encoded a direction of motion (cue) and after a delay period determined if the probe direction matched the cue direction. In the Interrupting stimuli task (IS), a circular swirl of motion was presented in the middle of delay period. A button press was required if the swirl was fast. A third task was perceptually equivalent to the WM tasks, but participants were instructed to passively view stimuli and press a right or left button at probe depending on the direction of an arrow.
Figure 3. Working memory performance.
Figure 3. Working memory performance.
At T2, WM was tested on the NI and IS tasks at the participant's original perceptual threshold (obtained at T1) and new threshold (obtained at T2). Change in WM accuracy was calculated as T2 – T1. Training led to WM improvement in the NI task compared to controls when tested at their original threshold (training effect). Neither group showed changes in WM performance when tested at their new perceptual threshold. Both groups improved in the IS task at the original threshold (practice effect), but not at the new threshold. * Asterisks indicate significant differences within group from T1 to T2 (paired t-test). Crosses indicates significant group by time interactions (repeated measures ANOVA).
Figure 4. EEG Recordings.
Figure 4. EEG Recordings.
Event-Related Potentials during stimulus encoding. Posterior occipital N1 amplitude (120–220 ms) significantly decreased at T2 for the training, but not control group. Statistics are based on electrode of interest (EOI) clusters selected for each participant. Scalp topographies of T2-T1 at the latency of mean N1 peak +/− 1sd illustrate the location of the training related functional plasticity.
Figure 5. Neural-behavioral correlation.
Figure 5. Neural-behavioral correlation.
Across participants, decreased N1 amplitude during encoding correlated with WM performance improvements in the NI task at the original threshold in the training group (r = 0.82, p

References

    1. Nacke LE, Nacke A, Lindley CA. Brain training for silver gamers: effects of age and game form on effectiveness, efficiency, self-assessment, and gameplay experience. Cyberpsychol Behav. 2009;12:493–499.
    1. Mahncke HW, Bronstone A, Merzenich MM. Brain plasticity and functional losses in the aged: scientific bases for a novel intervention. Prog Brain Res. 2006;157:81–109.
    1. Fahle M. Perceptual learning: specificity versus generalization. Curr Opin Neurobiol. 2005;15:154–160.
    1. Ball K, Sekuler R. Direction-specific improvement in motion discrimination. Vision Res. 1987;27:953–965.
    1. Fiorentini A, Berardi N. Learning in grating waveform discrimination: specificity for orientation and spatial frequency. Vision Res. 1981;21:1149–1158.
    1. Schoups AA, Vogels R, Orban GA. Human perceptual learning in identifying the oblique orientation: retinotopy, orientation specificity and monocularity. J Physiol. 1995;483 (Pt 3):797–810.
    1. Sigman M, Gilbert CD. Learning to find a shape. Nat Neurosci. 2000;3:264–269.
    1. Ramachandran VS, Braddick O. Orientation-specific learning in stereopsis. Perception. 1973;2:371–376.
    1. Crist RE, Kapadia MK, Westheimer G, Gilbert CD. Perceptual learning of spatial localization: specificity for orientation, position, and context. J Neurophysiol. 1997;78:2889–2894.
    1. Fiorentini A, Berardi N. Perceptual learning specific for orientation and spatial frequency. Nature. 1980;287:43–44.
    1. Vaina LM, Sundareswaran V, Harris JG. Learning to ignore: psychophysics and computational modeling of fast learning of direction in noisy motion stimuli. Brain Res Cogn Brain Res. 1995;2:155–163.
    1. Karni A, Sagi D. Where practice makes perfect in texture discrimination: evidence for primary visual cortex plasticity. Proc Natl Acad Sci U S A. 1991;88:4966–4970.
    1. Shiu LP, Pashler H. Improvement in line orientation discrimination is retinally local but dependent on cognitive set. Percept Psychophys. 1992;52:582–588.
    1. Fahle M, Daum I. Visual learning and memory as functions of age. Neuropsychologia. 1997;35:1583–1589.
    1. Alain C, McDonald KL, Ostroff JM, Schneider B. Age-related changes in detecting a mistuned harmonic. J Acoust Soc Am. 2001;109:2211–2216.
    1. Craik F, TA S. Handbook of Aging and Cogntion II Mahwah, NJ: Erlbaum 2000
    1. Schneider B, Pichora-Fuller M. Craik F, Salthouse T, Mahwah N, editors. Implications of perceptual deterioration of cognitive aging research. The Handbook of Aging and Cognition: Lawrence Erlbaum Associates. 2000. pp. 155–219.
    1. Wigfield R, Gilbert R, Fleming PJ. SIDS: risk reduction measures. Early Hum Dev. 1994;38:161–164.
    1. Zanto TP, Toy B, Gazzaley A. Delays in neural processing during working memory encoding in normal aging. Neuropsychologia. 48:13–25.
    1. King-Smith PE, Grigsby SS, Vingrys AJ, Benes SC, Supowit A. Efficient and unbiased modifications of the QUEST threshold method: theory, simulations, experimental evaluation and practical implementation. Vision Res. 1994;34:885–912.
    1. Karni A, Sagi D. The time course of learning a visual skill. Nature. 1993;365:250–252.
    1. Fahle M, Daum I. Visual learning and memory as functions of age. Neuropsychologia. 1997;12
    1. Berry AS, Zanto TP, Rutman AM, Clapp WC, Gazzaley A. Practice-related improvement in working memory is modulated by changes in processing external interference. J Neurophysiol. 2009;102:1779–1789.
    1. Crassini B, Brown B, Bowman K. Age-related changes in contrast sensitivity in central and peripheral retina. Perception. 1988;17:315–332.
    1. Clapp WC, Rubens MT, Gazzaley A. Mechanisms of Working Memory Disruption by External Interference. Cereb Cortex 2009
    1. Mercier M, Schwartz S, Michel CM, Blanke O. Motion direction tuning in human visual cortex. Eur J Neurosci. 2009;29:424–434.
    1. Bundo M, Kaneoke Y, Inao S, Yoshida J, Nakamura A, et al. Human visual motion areas determined individually by magnetoencephalography and 3D magnetic resonance imaging. Hum Brain Mapp. 2000;11:33–45.
    1. Ahlfors SP, Simpson GV, Dale AM, Belliveau JW, Liu AK, et al. Spatiotemporal activity of a cortical network for processing visual motion revealed by MEG and fMRI. J Neurophysiol. 1999;82:2545–2555.
    1. Mangun GR. Neural mechanisms of visual selective attention. Psychophysiology. 1995;32:4–18.
    1. Motter BC. Focal attention produces spatially selective processing in visual cortical areas V1, V2, and V4 in the presence of competing stimuli. J Neurophysiol. 1993;70:909–919.
    1. Berry AS, Zanto TP, Rutman AM, Clapp WC, Gazzaley A. Practice- Related Improvement in Working Memory is Modulated by Changes in Processing External Interference. J Neurophysiol 2009
    1. Yang T, Maunsell JH. The effect of perceptual learning on neuronal responses in monkey visual area V4. J Neurosci. 2004;24:1617–1626.
    1. Ding Y, Song Y, Fan S, Qu Z, Chen L. Specificity and generalization of visual perceptual learning in humans: an event-related potential study. Neuroreport. 2003;14:587–590.
    1. Alain C, Snyder JS. Age-related differences in auditory evoked responses during rapid perceptual learning. Clin Neurophysiol. 2008;119:356–366.
    1. Mukai I, Kim D, Fukunaga M, Japee S, Marrett S, et al. Activations in visual and attention-related areas predict and correlate with the degree of perceptual learning. J Neurosci. 2007;27:11401–11411.
    1. Gilbert CD. Early perceptual learning. Proc Natl Acad Sci U S A. 1994;91:1195–1197.
    1. Doniger GM, Zucker DM, Schweiger A, Dwolatzky T, Chertkow H, et al. Towards practical cognitive assessment for detection of early dementia: a 30-minute computerized battery discriminates as well as longer testing. Curr Alzheimer Res. 2005;2:117–124.
    1. Dwolatzky T, Whitehead V, Doniger GM, Simon ES, Schweiger A, et al. Validity of a novel computerized cognitive battery for mild cognitive impairment. BMC Geriatr. 2003;3:4.
    1. Appelle S. Perception and discrimination as a function of stimulus orientation: the “oblique effect” in man and animals. Psychol Bull. 1972;78:266–278.
    1. Gazzaley A, Clapp W, Kelley J, McEvoy K, Knight RT, et al. Age-related top-down suppression deficit in the early stages of cortical visual memory processing. Proc Natl Acad Sci U S A. 2008;105:13122–13126.
    1. Rutman AM, Clapp WC, Chadick JZ, Gazzaley A. Early top-down control of visual processing predicts working memory performance. J Cogn Neurosci. 22:1224–1234.
    1. Bach M, Hoffmann MB. Visual motion detection in man is governed by non-retinal mechanisms. Vision Res. 2000;40:2379–2385.
    1. Heinrich SP, van der Smagt MJ, Bach M, Hoffmann MB. Electrophysiological evidence for independent speed channels in human motion processing. J Vis. 2004;4:469–475.
    1. Hoffmann M, Dorn TJ, Bach M. Time course of motion adaptation: motion-onset visual evoked potentials and subjective estimates. Vision Res. 1999;39:437–444.
    1. Hoffmann MB, Unsold AS, Bach M. Directional tuning of human motion adaptation as reflected by the motion VEP. Vision Res. 2001;41:2187–2194.
    1. Maurer JP, Bach M. Isolating motion responses in visual evoked potentials by preadapting flicker-sensitive mechanisms. Exp Brain Res. 2003;151:536–541.
    1. Benjamini Y. Controlling the false discovery rate—a practical and powerful approach to multiple testing . J Roy Statist Soc B Methodol. 1995;57:289–300.

Source: PubMed

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