Visual perceptual learning by operant conditioning training follows rules of contingency

Stimulus awareness is necessary for both instrumental learning and instrumental responding to previously learned stimuli

Instrumental conditioning is a crucial part of adaptive behaviour, allowing agents to selectively interact with stimuli in their environment. Recent evidence suggests that instrumental conditioning cannot proceed without stimulus awareness. However, whether accurate unconscious instrumental responding can emerge from consciously acquired knowledge of the stimulus-action-outcome contingencies is unknown. We studied this question using instrumental trace conditioning, where participants learned to make approach/avoid decisions in two within-subject modes: conscious (stimuli in plain view) and unconscious (visually masked). Both tasks were followed by an unconscious-only instrumental performance task. We show that even when the contingencies are reliably learned in the conscious mode, participants fail to act upon them in the unconscious responding task. We also replicate the previous results that no instrumental learning occurs in the unconscious mode. Consequently, the absence of stimulus awareness not only precludes instrumental conditioning, but also precludes any kind of instrumental responding to already known stimuli. This suggests that instrumental behaviour is entirely supported by conscious awareness of the world, and corroborates the proposals that consciousness may be necessary for adaptive behaviours requiring selective action.

Informational feedback accelerates learning in multi-alternative perceptual judgements of orientation

Experience or training can substantially improve perceptual performance through perceptual learning, and the extent and rate of these improvements may be affected by feedback. In this paper, we first developed a neural network model based on the integrated reweighting theory (Dosher et al., 2013) to account for perceptual learning and performance in n-alternative identification tasks and the dependence of learning on different forms of feedback. We then report an experiment comparing the effectiveness of response feedback (RF) versus accuracy feedback (AF) or no feedback (NF) (full versus partial versus no supervision) in learning a challenging eight-alternative visual orientation identification (8AFC) task. Although learning sometimes occurred in the absence of feedback (NF), RF had a clear advantage above AF or NF in this task. Using hybrid supervision learning rules, a new n-alternative identification integrated reweighting theory (I-IRT) explained both the differences in learning curves given different feedback and the dynamic changes in identification confusion data. This study shows that training with more informational feedback (RF) is more effective, though not necessary, in these challenging n-alternative tasks, a result that has implications for developing training paradigms in realistic tasks.

Only cortical prediction error signals are involved in visual learning, despite availability of subcortical prediction error signals

Both the midbrain systems, encompassing the ventral striatum (VS), and the cortical systems, including the dorsal anterior cingulate cortex (dACC), play roles in reinforcing and enhancing learning. However, the specific contributions of signals from these regions in learning remains unclear. To investigate this, we examined how VS and dACC are involved in visual perceptual learning (VPL) through an orientation discrimination task. In the primary experiment, subjects fasted for 5 hours before each of 14 days of training sessions and 3 days of test sessions. Subjects were rewarded with water for accurate trial responses. During the test sessions, BOLD signals were recorded from regions including VS and dACC. Although BOLD signals in both areas were associated with positive and negative RPEs, only those in dACC associated with negative RPE showed a significant correlation with performance improvement. Additionally, no significant correlation was observed between BOLD signals associated with RPEs in VS and dACC. These results suggest that although signals associated with positive and negative RPEs from both midbrain and cortical systems are readily accessible, only RPE signals in the prefrontal system, generated without linking to RPE signals in VS, are utilized for the enhancement of VPL.

The Bright and Dark Sides of Performance-Dependent Monetary Rewards: Evidence From Visual Perception Tasks

Studies have shown that performance-dependent monetary rewards facilitate visual perception. However, no study has examined whether such a positive effect is limited to the rewarded task or may be generalized to other tasks. In the current study, two groups of people were asked to perform two visual perception tasks, one being a reward-relevant task and the other being a reward-irrelevant task. For the reward-relevant task, the experimental group received performance-dependent monetary rewards, whereas the control group did not. For the reward-irrelevant task, both groups were not rewarded. The two tasks were randomly intermixed trial by trial (Experiment 1) or presented block by block (Experiment 2) or session by session (Experiments 3a, 3b, and 3c). Results showed that performance-dependent monetary rewards improved participants' performance on the relevant task in all experiments and impaired their performance on the irrelevant task in Experiments 2, 3a, 3b, and 3c. These results suggested that monetary rewards might incur a cost on reward-irrelevant tasks. Finally, the benefit of monetary rewards disappeared when they were no longer provided during the final session. This is the first study that reveals both the bright and dark sides of the performance-dependent monetary rewards in visual perception.

Reward does not facilitate visual perceptual learning until sleep occurs

A growing body of evidence indicates that visual perceptual learning (VPL) is enhanced by reward provided during training. Another line of studies has shown that sleep following training also plays a role in facilitating VPL, an effect known as the offline performance gain of VPL. However, whether the effects of reward and sleep interact on VPL remains unclear. Here, we show that reward interacts with sleep to facilitate offline performance gains of VPL. First, we demonstrated a significantly larger offline performance gain over a 12-h interval including sleep in a reward group than that in a no-reward group. However, the offline performance gains over the 12-h interval without sleep were not significantly different with or without reward during training, indicating a crucial interaction between reward and sleep in VPL. Next, we tested whether neural activations during posttraining sleep were modulated after reward was provided during training. Reward provided during training enhanced rapid eye movement (REM) sleep time, increased oscillatory activities for reward processing in the prefrontal region during REM sleep, and inhibited neural activation in the untrained region in early visual areas in non-rapid eye movement (NREM) and REM sleep. The offline performance gains were significantly correlated with oscillatory activities of visual processing during NREM sleep and reward processing during REM sleep in the reward group but not in the no-reward group. These results suggest that reward provided during training becomes effective during sleep, with excited reward processing sending inhibitory signals to suppress noise in visual processing, resulting in larger offline performance gains over sleep.

Calibration of peripheral perception of shape with and without saccadic eye movements

The cortical representations of a visual object differ radically across saccades. Several studies claim that the visual system adapts the peripheral percept to better match the subsequent foveal view. Recently, Herwig, Weiß, and Schneider (2015, Annals of the New York Academy of Sciences, 1339(1), 97-105) found that the perception of shape demonstrates a saccade-dependent learning effect. Here, we ask whether this learning actually requires saccades. We replicated Herwig et al.'s (2015) study and introduced a fixation condition. In a learning phase, participants were exposed to objects whose shape systematically changed during a saccade, or during a displacement from peripheral to foveal vision (without a saccade). In a subsequent test, objects were perceived as less (more) curved if they previously changed from more circular (triangular) in the periphery to more triangular (circular) in the fovea. Importantly, this pattern was seen both with and without saccades. We then tested whether a variable delay between the presentations of the peripheral and foveal objects would affect their association-hypothetically weakening it at longer delays. Again, we found that shape judgments depended on the changes experienced during the learning phase and that they were similar in both the saccade and fixation conditions. Surprisingly, they were not affected by the delay between the peripheral and foveal presentations over the range we tested. These results suggest that a general associative process, independent of saccade execution, contributes to the perception of shape across viewpoints.

Perceptual learning of task-irrelevant features depends on the sensory context

The brain has evolved to extract behaviourally meaningful information from the environment. For example, it has been shown that visual perceptual learning (VPL) can occur for task-irrelevant stimulus features when those features are consistently paired with internal or external reinforcement signals. It is, however, unclear whether or not task-irrelevant VPL is influenced by stimulus features that are unrelated to reinforcement in a given sensory context. To address this question, we exposed participants to task-irrelevant and subliminal coherent motion stimuli in the background while they performed a central character identification task. A specific motion direction was consistently paired with the task-targets, while two other directions occurred only with distractors and, thus, were unrelated to reinforcement. We found that the magnitude of VPL of the target-paired direction was significantly greater when the distractor-paired directions were close to the target-paired direction, compared to when they were farther. Thus, even very weak signals that are both subliminal and unrelated to reinforcement are processed and exert an influence on VPL. This finding suggests that the outcome of VPL depends on the sensory context in which learning takes place and calls for a refinement of VPL theories to incorporate exposure-based influences on learning.

Top-down modulation of sensory cortex gates perceptual learning

Practice sharpens our perceptual judgments, a process known as perceptual learning. Although several brain regions and neural mechanisms have been proposed to support perceptual learning, formal tests of causality are lacking. Furthermore, the temporal relationship between neural and behavioral plasticity remains uncertain. To address these issues, we recorded the activity of auditory cortical neurons as gerbils trained on a sound detection task. Training led to improvements in cortical and behavioral sensitivity that were closely matched in terms of magnitude and time course. Surprisingly, the degree of neural improvement was behaviorally gated. During task performance, cortical improvements were large and predicted behavioral outcomes. In contrast, during nontask listening sessions, cortical improvements were weak and uncorrelated with perceptual performance. Targeted reduction of auditory cortical activity during training diminished perceptual learning while leaving psychometric performance largely unaffected. Collectively, our findings suggest that training facilitates perceptual learning by strengthening both bottom-up sensory encoding and top-down modulation of auditory cortex.

Cholinergic Potentiation Improves Perceptual-Cognitive Training of Healthy Young Adults in Three Dimensional Multiple Object Tracking

A large body of literature supports cognitive enhancement as an effect of cholinergic potentiation. However, it remains elusive whether pharmacological manipulations of cholinergic neurotransmission enhance complex visual processing in healthy individuals. To test this hypothesis, we randomly administered either the cholinergic transmission enhancer donepezil (DPZ; 5 mg P.O.) or placebo (lactose) to young adults (n = 17) 3 h before each session of the three-dimensional (3D) multiple object tracking (3D-MOT) task. This multi-focal attention task evaluates perceptual-cognitive learning over five sessions conducted 7 days apart. A significant amount of learning was observed in the DPZ group but not the placebo group in the fourth session. In the fifth session, this learning effect was observed in both groups. Furthermore, preliminary results for a subgroup of participants (n = 9) 4–14 months later suggested the cholinergic enhancement effect was long lasting. On the other hand, DPZ had no effect on basic visual processing as measured by a motion and orientation discrimination task performed as an independent one-time, pre-post drug study without placebo control (n = 10). The results support the construct that cholinergic enhancement facilitates the encoding of a highly demanding perceptual-cognitive task although there were no significant drug effects on the performance levels compared to placebo.

Dual mechanisms governing reward-driven perceptual learning

In this review, we explore how reward signals shape perceptual learning in animals and humans. Perceptual learning is the well-established phenomenon by which extensive practice elicits selective improvement in one’s perceptual discrimination of basic visual features, such as oriented lines or moving stimuli. While perceptual learning has long been thought to rely on ‘top-down’ processes, such as attention and decision-making, a wave of recent findings suggests that these higher-level processes are, in fact, not necessary.  Rather, these recent findings indicate that reward signals alone, in the absence of the contribution of higher-level cognitive processes, are sufficient to drive the benefits of perceptual learning. Here, we will review the literature tying reward signals to perceptual learning. Based on these findings, we propose dual underlying mechanisms that give rise to perceptual learning: one mechanism that operates ‘automatically’ and is tied directly to reward signals, and another mechanism that involves more ‘top-down’, goal-directed computations.