Article

The neural basis of visual object learning

Laboratory of Biological Psychology, University of Leuven (K.U.Leuven), Tiensestraat 102, 3000 Leuven, Belgium. <>
Trends in Cognitive Sciences (Impact Factor: 21.15). 11/2009; 14(1):22-30. DOI: 10.1016/j.tics.2009.11.002
Source: PubMed

ABSTRACT Object vision in human and nonhuman primates is often cited as a primary example of adult plasticity in neural information processing. It has been hypothesized that visual experience leads to single neurons in the monkey brain with strong selectivity for complex objects, and to regions in the human brain with a preference for particular categories of highly familiar objects. This view suggests that adult visual experience causes dramatic local changes in the response properties of high-level visual cortex. Here, we review the current neurophysiological and neuroimaging evidence and find that the available data support a different conclusion: adult visual experience introduces moderate, relatively distributed effects that modulate a pre-existing, rich and flexible set of neural object representations.

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    • "Human: Schiltz et al., 1999; Schwartz et al., 2002; Furmanski et al., 2004; Yotsumoto et al., 2008; for a recent review see Lu et al., 2011). Further, long-term training with artificial objects in both human (e.g., Op de Beeck et al., 2006; Yue et al., 2006; Wong et al., 2009b; Zhang et al., 2010) and non-human primates (e.g., Kobatake et al., 1998; Op de Beeck et al., 2001; Baker et al., 2002; Woloszyn and Sheinberg, 2012) have revealed specific changes in the response of high-level visual cortex such as increases or decreases in response magnitude and increased selectivity for trained objects and task-relevant stimulus dimensions (for review, see Op de Beeck and Baker, 2010b). For example, Op de Beeck et al. (2006) trained human subjects for approximately 10 h to discriminate between exemplars in one of three novel object classes (“smoothies”, “spikies”, and “cubies”). "
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    ABSTRACT: Real-world expertise provides a valuable opportunity to understand how experience shapes human behavior and neural function. In the visual domain, the study of expert object recognition, such as in car enthusiasts or bird watchers, has produced a large, growing, and often-controversial literature. Here, we synthesize this literature, focusing primarily on results from functional brain imaging, and propose an interactive framework that incorporates the impact of high-level factors, such as attention and conceptual knowledge, in supporting expertise. This framework contrasts with the perceptual view of object expertise that has concentrated largely on stimulus-driven processing in visual cortex. One prominent version of this perceptual account has almost exclusively focused on the relation of expertise to face processing and, in terms of the neural substrates, has centered on face-selective cortical regions such as the Fusiform Face Area (FFA). We discuss the limitations of this face-centric approach as well as the more general perceptual view, and highlight that expert related activity is: (i) found throughout visual cortex, not just FFA, with a strong relationship between neural response and behavioral expertise even in the earliest stages of visual processing, (ii) found outside visual cortex in areas such as parietal and prefrontal cortices, and (iii) modulated by the attentional engagement of the observer suggesting that it is neither automatic nor driven solely by stimulus properties. These findings strongly support a framework in which object expertise emerges from extensive interactions within and between the visual system and other cognitive systems, resulting in widespread, distributed patterns of expertise-related activity across the entire cortex.
    Frontiers in Human Neuroscience 12/2013; 7(10):885. DOI:10.3389/fnhum.2013.00885 · 2.90 Impact Factor
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    • "After training, the mean magnitude of neural activation in a region of interest can be either increased [1], [2], [3], [4], [5], [6], [7], decreased [2], [3], [6], [8], [9], [10], [11] or even unchanged [12]. We argue that one possible interpretation of these inconsistent findings is that learning-induced changes are not homogenous in that the activation of some neurons is increased and the activation of others is decreased (for a review, see [13]). Accordingly, fMRI studies based on the mean magnitudes of neural activation averaged across voxels may show inconsistent findings. "
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    ABSTRACT: Learning to be skillful is an endowed talent of humans, but neural mechanisms underlying behavioral improvement remain largely unknown. Some studies have reported that the mean magnitude of neural activation is increased after learning, whereas others have instead shown decreased activation. In this study, we used functional magnetic resonance imaging (fMRI) to investigate learning-induced changes in the neural activation in the human brain with a classic motor training task. Specifically, instead of comparing the mean magnitudes of activation before and after training, we analyzed the learning-induced changes in multi-voxel spatial patterns of neural activation. We observed that the stability of the activation patterns, or the similarity of the activation patterns between the even and odd runs of the fMRI scans, was significantly increased in the primary motor cortex (M1) after training. By contrast, the mean magnitude of neural activation remained unchanged. Therefore, our study suggests that learning shapes the brain by increasing the stability of the activation patterns, therefore providing a new perspective in understanding the neural mechanisms underlying learning.
    PLoS ONE 01/2013; 8(1):e53555. DOI:10.1371/journal.pone.0053555 · 3.23 Impact Factor
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    • "These divergent findings have been attributed to more unbiased single unit selection procedures, to comparisons within rather than across animals, and to more finely controlled stimulus exposure protocols. Interestingly, while both firing rate increases and decreases can increase single cell selectivity (i.e., narrow the tuning bandwidth), recently reported modulations have been on the order of a few spikes per second (Baker et al., 2002; Cox and DiCarlo, 2008; De Baene et al., 2008; Freedman et al., 2006), leading some to propose that visual experience results only in subtle neuronal plasticity in ITC (Op de Beeck and Baker, 2010). Behavioral data, on the other hand, indicate that the impact of visual experience on recognition behavior can be large (Gauthier and Tarr, 1997; Logothetis et al., 1995; Mruczek and Sheinberg, 2007). "
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    ABSTRACT: Primates can learn to recognize a virtually limitless number of visual objects. A candidate neural substrate for this adult plasticity is the inferior temporal cortex (ITC). Using a large stimulus set, we explored the impact that long-term experience has on the response properties of two classes of neurons in ITC: broad-spiking (putative excitatory) cells and narrow-spiking (putative inhibitory) cells. We found that experience increased maximum responses of putative excitatory neurons but had the opposite effect on maximum responses of putative inhibitory neurons, an observation that helps to reconcile contradictory reports regarding the presence and direction of this effect. In addition, we found that experience reduced the average stimulus-evoked response in both cell classes, but this decrease was much more pronounced in putative inhibitory units. This latter finding supports a potentially critical role of inhibitory neurons in detecting and initiating the cascade of events underlying adult neural plasticity in ITC.
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