Different Dynamics of Performance and Brain Activation in the Time Course of Perceptual Learning

Yotsumoto, Yuko; Watanabe, Takeo; Sasaki, Yuka

doi:10.1016/j.neuron.2008.02.034

Cited by 285 publications

(364 citation statements)

References 31 publications

(51 reference statements)

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“…Interestingly, training on orthogonal contours resulted in a smaller but significant behavioral improvement for collinear contours that was associated with decreased activations for collinear contours in temporal and frontoparietal regions. These results are consistent with previous imaging studies showing decreased fMRI activations for training of salient stimuli for which performance has saturated (Kourtzi et al 2005;Yotsumoto et al 2008) that may relate to a more efficient stimulus representation by smaller neural ensembles. Finally, no significant learning-related changes were observed for acute contours, consistent with the lack of learning transfer for these contour stimuli for the training period used in this study (see also Schwarzkopf and Kourtzi 2008).…”

Section: Training-dependent Changes In Activation Magnitude: Intact Vsupporting

confidence: 92%

Flexible Learning of Natural Statistics in the Human Brain

Schwarzkopf

Zhang²,

Kourtzi³

2009

Journal of Neurophysiology

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Schwarzkopf DS, Zhang J, Kourtzi Z. Flexible learning of natural statistics in the human brain. J Neurophysiol 102: 1854 -1867, 2009. First published July 15, 2009 doi:10.1152/jn.00028.2009. The ability to detect and identify targets in cluttered scenes is a critical skill for survival and interactions. To solve this challenge the brain has optimized mechanisms for capitalizing on frequently occurring regularities in the environment. Although evolution and development have been suggested to shape the brain's architecture in a manner that resembles these natural statistics, we provide novel evidence that short-term experience in adulthood may modify the brain's functional organization to support integration of signals atypical of shape contours in natural scenes. Although collinearity is a prevalent principle for perceptual integration in natural scenes, we show that observers learn to exploit other image regularities (i.e., orthogonal alignments of segments at an angle to the contour path) that typically signify discontinuities. Combining behavioral and functional MRI measurements, we demonstrate that this flexible learning is mediated by changes in the neural representations of behaviorally relevant image regularities primarily in dorsal visual areas. These changes in neural sensitivity are in line with changes in perceptual sensitivity for the detection of orthogonal contours and are evident only in observers that show significant performance improvement. In contrast, changes in the activation extent in frontoparietal regions are evident independent of performance changes, may support the detection of salient regions, and modulate perceptual integration in occipitotemporal areas in a top-down manner. Thus experience at shorter timescales in adulthood supports the adaptive functional optimization of visual circuits for flexible interpretation of natural scenes.

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Section: Training-dependent Changes In Activation Magnitude: Intact Vsupporting

confidence: 92%

Flexible Learning of Natural Statistics in the Human Brain

Schwarzkopf

Zhang²,

Kourtzi³

2009

Journal of Neurophysiology

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“…First, we provide evidence for learning-dependent changes related to neural sensitivity rather than simply overall responsiveness (i.e., increased or decreased fMRI responses) to trained stimuli as reported in previous imaging studies (Kourtzi et al, 2005;Sigman et al, 2005;Op de Beeck et al, 2006;Mukai et al, 2007;Yotsumoto et al, 2008). This previous work does not allow us to discern whether learningdependent changes in fMRI signals relate to changes in the overall magnitude of neural responses or changes in neuronal selectivity of neural populations.…”

Section: Discussionmentioning

confidence: 64%

Learning Alters the Tuning of Functional Magnetic Resonance Imaging Patterns for Visual Forms

Zhang

Meeson²,

Welchman³

et al. 2010

J. Neurosci.

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Learning is thought to facilitate the recognition of objects by optimizing the tuning of visual neurons to behaviorally relevant features. However, the learning mechanisms that shape neural selectivity for visual forms in the human brain remain essentially unknown. Here, we combine behavioral and functional magnetic resonance imaging (fMRI) measurements to test the mechanisms that mediate enhanced behavioral sensitivity in the discrimination of visual forms after training. In particular, we used high-resolution fMRI and multivoxel pattern classification methods to investigate fine learning-dependent changes in neural preference for global forms. We measured the observers' choices when discriminating between concentric and radial patterns presented in noise before and after training. Similarly, we measured the choices of a pattern classifier when predicting each stimulus from fMRI activity. Comparing the performance of human observers and classifiers demonstrated that learning alters the observers' sensitivity to visual forms and the tuning of fMRI activation patterns in visual areas selective for task-relevant features. In particular, training on low-signal stimuli enhanced the amplitude but reduced the width of pattern-based tuning functions in higher dorsal and ventral visual areas. Thus, our findings suggest that learning of visual patterns is implemented by enhancing the response to the preferred stimulus category and reducing the response to nonpreferred stimuli in higher extrastriate visual cortex.

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“…We suggest that, because of this, large neural networks that include low-to high-level areas may play a role in offline consolidation from the beginning of learning (Lewis et al, 2009). Reports of changes in stimulus-driven activation observed with fMRI early in visual skill learning (Schwartz et al, 2002;Mukai et al, 2007;Yotsumoto et al, 2008), of reverberating activity in large functional networks after a learning experience (Hoffman and McNaughton, 2002;Ji and Wilson, 2007;Tambini et al, 2010), and of behavioral interference early in visual learning (Seitz et al, 2005) all support this possibility. Interfering input, such as delivered by TMS, may reset the synaptic weights of readout routines more easily when the network that maintains them is smaller (Buonomano and Maass, 2009) and does not include high-level areas that during offline consolidation may help strengthening the synaptic weights appropriate for the task (Fig.…”

Section: Discussionmentioning

confidence: 98%

“…Training-induced response changes have been shown after prolonged training (Schoups et al, 2001) but also after a single training session (Schwartz et al, 2002;Yotsumoto et al, 2008). Moreover, human neuroimaging (Yotsumoto et al, 2009) has revealed offline V1 activity during sleep 6 h after a single session of visual skill learning, implicating V1 in offline consolidation after a small amount of training.…”

Section: Introductionmentioning

confidence: 99%

Posttraining Transcranial Magnetic Stimulation of Striate Cortex Disrupts Consolidation Early in Visual Skill Learning

et al. 2012

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Practice-induced improvements in skilled performance reflect "offline " consolidation processes extending beyond daily training sessions. According to visual learning theories, an early, fast learning phase driven by high-level areas is followed by a late, asymptotic learning phase driven by low-level, retinotopic areas when higher resolution is required. Thus, low-level areas would not contribute to learning and offline consolidation until late learning. Recent studies have challenged this notion, demonstrating modified responses to trained stimuli in primary visual cortex (V1) and offline activity after very limited training. However, the behavioral relevance of modified V1 activity for offline consolidation of visual skill memory in V1 after early training sessions remains unclear. Here, we used neuronavigated transcranial magnetic stimulation (TMS) directed to a trained retinotopic V1 location to test for behaviorally relevant consolidation in human low-level visual cortex. Applying TMS to the trained V1 location within 45 min of the first or second training session strongly interfered with learning, as measured by impaired performance the next day. The interference was conditional on task context and occurred only when training in the location targeted by TMS was followed by training in a second location before TMS. In this condition, high-level areas may become coupled to the second location and uncoupled from the previously trained low-level representation, thereby rendering consolidation vulnerable to interference. Our data show that, during the earliest phases of skill learning in the lowest-level visual areas, a behaviorally relevant form of consolidation exists of which the robustness is controlled by high-level, contextual factors.

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Different Dynamics of Performance and Brain Activation in the Time Course of Perceptual Learning

Cited by 285 publications

References 31 publications

Flexible Learning of Natural Statistics in the Human Brain

Flexible Learning of Natural Statistics in the Human Brain

Learning Alters the Tuning of Functional Magnetic Resonance Imaging Patterns for Visual Forms

Posttraining Transcranial Magnetic Stimulation of Striate Cortex Disrupts Consolidation Early in Visual Skill Learning

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