Representation and selection of relative position

Learning efficient visual search for stimuli containing diagnostic spatial configurations and color-shape conjunctions

Visual search is often slow and difficult for complex stimuli such as feature conjunctions. Search efficiency, however, can improve with training. Search for stimuli that can be identified by the spatial configuration of two elements (e.g., the relative position of two colored shapes) improves dramatically within a few hundred trials of practice. Several recent imaging studies have identified neural correlates of this learning, but it remains unclear what stimulus properties participants learn to use to search efficiently. Influential models, such as reverse hierarchy theory, propose two major possibilities: learning to use information contained in low-level image statistics (e.g., single features at particular retinotopic locations) or in high-level characteristics (e.g., feature conjunctions) of the task-relevant stimuli. In a series of experiments, we tested these two hypotheses, which make different predictions about the effect of various stimulus manipulations after training. We find relatively small effects of manipulating low-level properties of the stimuli (e.g., changing their retinotopic location) and some conjunctive properties (e.g., color-position), whereas the effects of manipulating other conjunctive properties (e.g., color-shape) are larger. Overall, the findings suggest conjunction learning involving such stimuli might be an emergent phenomenon that reflects multiple different learning processes, each of which capitalizes on different types of information contained in the stimuli. We also show that both targets and distractors are learned, and that reversing learned target and distractor identities impairs performance. This suggests that participants do not merely learn to discriminate target and distractor stimuli, they also learn stimulus identity mappings that contribute to performance improvements.

Neural correlates of context-dependent feature conjunction learning in visual search tasks

Many perceptual learning experiments show that repeated exposure to a basic visual feature such as a specific orientation or spatial frequency can modify perception of that feature, and that those perceptual changes are associated with changes in neural tuning early in visual processing. Such perceptual learning effects thus exert a bottom-up influence on subsequent stimulus processing, independent of task-demands or endogenous influences (e.g., volitional attention). However, it is unclear whether such bottom-up changes in perception can occur as more complex stimuli such as conjunctions of visual features are learned. It is not known whether changes in the efficiency with which people learn to process feature conjunctions in a task (e.g., visual search) reflect true bottom-up perceptual learning versus top-down, task-related learning (e.g., learning better control of endogenous attention). Here we show that feature conjunction learning in visual search leads to bottom-up changes in stimulus processing. First, using fMRI, we demonstrate that conjunction learning in visual search has a distinct neural signature: an increase in target-evoked activity relative to distractor-evoked activity (i.e., a relative increase in target salience). Second, we demonstrate that after learning, this neural signature is still evident even when participants passively view learned stimuli while performing an unrelated, attention-demanding task. This suggests that conjunction learning results in altered bottom-up perceptual processing of the learned conjunction stimuli (i.e., a perceptual change independent of the task). We further show that the acquired change in target-evoked activity is contextually dependent on the presence of distractors, suggesting that search array Gestalts are learned. Hum Brain Mapp 37:2319-2330, 2016. © 2016 Wiley Periodicals, Inc.

Neural mechanisms of feature conjunction learning: enduring changes in occipital cortex after a week of training

Most visual activities, whether reading, driving, or playing video games, require rapid detection and identification of learned patterns defined by arbitrary conjunctions of visual features. Initially, such detection is slow and inefficient, but it can become fast and efficient with training. To determine how the brain learns to process conjunctions of visual features efficiently, we trained participants over eight consecutive days to search for a target defined by an arbitrary conjunction of color and location among distractors with a different conjunction of the same features. During each training session, we measured brain activity with functional magnetic resonance imaging (fMRI). The speed of visual search for feature conjunctions improved dramatically within just a few days. These behavioral improvements were correlated with increased neural responses to the stimuli in visual cortex. This suggests that changes in neural processing in visual cortex contribute to the speeding up of visual feature conjunction search. We find evidence that this effect is driven by an increase in the signal-to-noise ratio (SNR) of the BOLD signal for search targets over distractors. In a control condition where target and distractor identities were exchanged after training, learned search efficiency was abolished, suggesting that the primary improvement was perceptual learning for the search stimuli, not task-learning. Moreover, when participants were retested on the original task after nine months without further training, the acquired changes in behavior and brain activity were still present, showing that this can be an enduring form of learning and neural reorganization.

Crowding follows the binding of relative position and orientation

Crowding--the deleterious influence of clutter on object recognition--disrupts the identification of visual features as diverse as orientation, motion, and color. It is unclear whether this occurs via independent feature-specific crowding processes (preceding the feature binding process) or via a singular (late) mechanism tuned for combined features. To examine the relationship between feature binding and crowding, we measured interactions between the crowding of relative position and orientation. Stimuli were a target cross and two flanker crosses (each composed of two near-orthogonal lines), 15 degrees in the periphery. Observers judged either the orientation (clockwise/counterclockwise) of the near-horizontal target line, its position (up/down relative to the stimulus center), or both. For single-feature judgments, crowding affected position and orientation similarly: thresholds were elevated and responses biased in a manner suggesting that the target appeared more like the flankers. These effects were tuned for orientation, with near-orthogonal elements producing little crowding. This tuning allowed us to separate the predictions of independent (feature specific) and combined (singular) models: for an independent model, reduced crowding for one feature has no effect on crowding for other features, whereas a combined process affects either all features or none. When observers made conjoint judgments, a reduction of orientation crowding (by increasing target-flanker orientation differences) increased the rate of correct responses for both position and orientation, as predicted by our combined model. In contrast, our independent model incorrectly predicted a high rate of position errors, since the probability of positional crowding would be unaffected by changes in orientation. Thus, at least for these features, crowding is a singular process that affects bound position and orientation values in an all-or-none fashion.