Decision-making processes in perceptual learning depend on effectors

Visual perceptual learning is traditionally thought to arise in visual cortex. However, typical perceptual learning tasks also involve systematic mapping of visual information onto motor actions. Because the motor system contains both effector-specific and effector-unspecific representations, the question arises whether visual perceptual learning is effector-specific itself, or not. Here, we study this question in an orientation discrimination task. Subjects learn to indicate their choices either with joystick movements or with manual reaches. After training, we challenge them to perform the same task with eye movements. We dissect the decision-making process using the drift diffusion model. We find that learning effects on the rate of evidence accumulation depend on effectors, albeit not fully. This suggests that during perceptual learning, visual information is mapped onto effector-specific integrators. Overlap of the populations of neurons encoding motor plans for these effectors may explain partial generalization. Taken together, visual perceptual learning is not limited to visual cortex, but also affects sensorimotor mapping at the interface of visual processing and decision making.

Category representation in primary visual cortex after visual perceptual learning

The visual perceptual learning (VPL) leads to long-term enhancement of visual task performance. The subjects are often trained to link different visual stimuli to several options, such as the widely used two-alternative forced choice (2AFC) task, which involves an implicit categorical decision. The enhancement of performance has been related to the specific changes of neural activities, but few studies investigate the effects of categorical responding on the changes of neural activities. Here we investigated whether the neural activities would exhibit the categorical characteristics if the subjects are requested to respond visual stimuli in a categorical manner during VPL. We analyzed the neural activities of two monkeys in a contour detection VPL. We found that the neural activities in primary visual cortex (V1) converge to one pattern if the contour can be detected by monkey and another pattern if the contour cannot be detected, exhibiting a kind of category learning that the neural representations of detectable contour become less selective for number of bars forming contour and diverge from the representations of undetectable contour.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09926-8.

Neural ensembles in the murine medial prefrontal cortex process distinct information during visual perceptual learning

BACKGROUND

Perceptual learning refers to an augmentation of an organism's ability to respond to external stimuli, which has been described in most sensory modalities. Visual perceptual learning (VPL) is a manifestation of plasticity in visual information processing that occurs in the adult brain, and can be used to ameliorate the ability of patients with visual defects mainly based on an improvement of detection or discrimination of features in visual tasks. While some brain regions such as the primary visual cortex have been described to participate in VPL, the way more general high-level cognitive brain areas are involved in this process remains unclear. Here, we showed that the medial prefrontal cortex (mPFC) was essential for both the training and maintenance processes of VPL in mouse models.

RESULTS

We built a new VPL model in a custom-designed training chamber to enable the utilization of miniScopes when mice freely executed the VPL task. We found that pyramidal neurons in the mPFC participate in both the training process and maintenance of VPL. By recording the calcium activity of mPFC pyramidal neurons while mice freely executed the task, distinct ON and OFF neural ensembles tuned to different behaviors were identified, which might encode different cognitive information. Decoding analysis showed that mouse behaviors could be well predicted using the activity of each ON ensemble. Furthermore, VPL recruited more reward-related components in the mPFC.

CONCLUSION

We revealed the neural mechanism underlying vision improvement following VPL and identify distinct ON and OFF neural ensembles in the mPFC that tuned to different information during visual perceptual training. These results uncover an important role of the mPFC in VPL, with more reward-related components being also involved, and pave the way for future clarification of the reward signal coding rules in VPL.

Posttraining anodal tDCS improves early consolidation of visual perceptual learning

OBJECTIVE

We aimed to investigate the transcranial direct current stimulation (tDCS)-induced facilitation of early consolidation over a period of extended training sessions and explored the effect of tDCS on visual perceptual learning (VPL) improvement during online learning and offline consolidation.

METHODS

In the current double-blind sham-controlled study, twenty-four healthy participants were trained on coherent motion direction identification for 5 consecutive sessions. Performance was assessed at the pre- and posttests. Anodal or sham tDCS of the left human middle temporal region (hMT+) was applied immediately after the completion of daily training (termed early consolidation).

RESULTS

The magnitude of improvement between anodal and sham tDCS was marginally significant, supporting the beneficial effect of anodal tDCS on VPL by stimulating early consolidation. Additionally, anodal tDCS induced a larger improvement between the first two training sessions than sham tDCS. No effect of anodal tDCS was found on the within-session improvement.

CONCLUSIONS

The above results indicated that anodal tDCS facilitates offline consolidation during the early period of the whole training series, not online learning. The possible neural mechanisms and limitations (sample size and persistent effects) were discussed.

SIGNIFICANCE

Our findings support the use of the combination of tDCS and behavioral training in facilitating visual rehabilitation and contribute to a deeper understanding of learning processes by neuromodulation procedures.

Testing the efficacy of vision training for presbyopia: alternating-distance training does not facilitate vision improvement compared to fixed-distance training

PURPOSE

Current evidence demonstrates the effectiveness of vision training for presbyopia. We developed and examined a training program to test the effectiveness of alternating focal distances as a training method.

METHODS

We devised a sharpness discrimination task, in which participants judged whether the stimulus was a sine- or square-wave grating, and tested in two training groups and one control group. In the alternating-distance training group (N = 8, age 49-64), participants had to alternate the fixation between a near- and far-screen. In the fixed-distance training group (N=8, age 47-65), participants fixated on the same-distance target for the whole block. Before and after the 20 training sessions, we measured the near- and far-visual acuity (VA) using the Landolt C and Early Treatment Diabetic Retinopathy Study (ETDRS) tasks and contrast sensitivity using the qCSF procedure. The control group (N=8, age 49-65) participated only in the pre- and post-tests.

RESULTS

Both training groups showed a significant improvement between the pre- and post-tests in the Landolt C task, and the improvement sizes were not significantly different between the groups. In the ETDRS task, only the fixed-distance training group showed significant improvement, although there was no significant difference between the two groups. Neither group showed improvement in the contrast sensitivity task compared to the control group.

CONCLUSION

The novel sharpness discrimination task can be an effective training method for presbyopia to prevent the deterioration of VA; however, contrary to popular belief, the effect of alternating-distance training was comparable to or even weaker than that of fixed-distance training.

Perceptual learning induces changes in early and late visual evoked potentials

Studies of visual cortical responses following visual perceptual learning (VPL) have produced diverse results, revealing neural changes in early and/or higher-level visual cortex as well as changes in regions responsible for higher cognitive processes such as attentional control. In this study, we investigated substrates of VPL in the human brain by recording visual evoked potentials with high-density electroencephalography (hdEEG) before (Session 1) and after (Session 2) training on a texture discrimination task (TDT), with two full nights of sleep between sessions. We studied the following event-related potential (ERP) components: C1 (early sensory processing), P1 and N1 (later sensory processing, modulated by top-down spatial attention), and P3 (cognitive processing). Our results showed a significant decrease in C1 amplitude at Session 2 relative to Session 1 that was positively correlated with the magnitude of improvement in behavioral performance. Although we observed no significant changes in P1 amplitude with VPL, both N1 amplitude and latency were significantly decreased in Session 2. Moreover, the difference in N1 latency between Session 1 and Session 2 was negatively correlated with behavioral improvement. We also found a significant increase in P3 amplitude following training. Our results suggest that VPL of the TDT task may be due to plasticity in early visual cortical areas as well as changes in top-down attentional control and cognitive processing.

Effects of regular aerobic exercise on visual perceptual learning

This study investigated the influence of five days of moderate intensity aerobic exercise on the acquisition and consolidation of visual perceptual learning using a motion direction discrimination (MDD) task. The timing of exercise relative to learning was manipulated by administering exercise either before or after perceptual training. Within a matched-subjects design, twenty-seven healthy participants (n = 9 per group) completed five consecutive days of perceptual training on a MDD task under one of three interventions: no exercise, exercise before the MDD task, or exercise after the MDD task. MDD task accuracy improved in all groups over the five-day period, but there was a trend for impaired learning when exercise was performed before visual perceptual training. MDD task accuracy (mean ± SD) increased in exercise before by 4.5 ± 6.5%; exercise after by 11.8 ± 6.4%; and no exercise by 11.3 ± 7.2%. All intervention groups displayed similar MDD threshold reductions for the trained and untrained motion axes after training. These findings suggest that moderate daily exercise does not enhance the rate of visual perceptual learning for an MDD task or the transfer of learning to an untrained motion axis. Furthermore, exercise performed immediately prior to a visual perceptual learning task may impair learning. Further research with larger groups is required in order to better understand these effects.

Time course influences transfer of visual perceptual learning across spatial location

Visual perceptual learning describes the improvement of visual perception with repeated practice. Previous research has established that the learning effects of perceptual training may be transferable to untrained stimulus attributes such as spatial location under certain circumstances. However, the mechanisms involved in transfer have not yet been fully elucidated. Here, we investigated the effect of altering training time course on the transferability of learning effects. Participants were trained on a motion direction discrimination task or a sinusoidal grating orientation discrimination task in a single visual hemifield. The 4000 training trials were either condensed into one day, or spread evenly across five training days. When participants were trained over a five-day period, there was transfer of learning to both the untrained visual hemifield and the untrained task. In contrast, when the same amount of training was condensed into a single day, participants did not show any transfer of learning. Thus, learning time course may influence the transferability of perceptual learning effects.

Visual perceptual learning by operant conditioning training follows rules of contingency

Visual perceptual learning (VPL) can occur as a result of a repetitive stimulus-reward pairing in the absence of any task. This suggests that rules that guide Conditioning, such as stimulus-reward contingency (e.g. that stimulus predicts the likelihood of reward), may also guide the formation of VPL. To address this question, we trained subjects with an operant conditioning task in which there were contingencies between the response to one of three orientations and the presence of reward. Results showed that VPL only occurred for positive contingencies, but not for neutral or negative contingencies. These results suggest that the formation of VPL is influenced by similar rules that guide the process of Conditioning.

Location specific sleep spindle activity in the early visual areas and perceptual learning

Visual perceptual learning (VPL) is consolidated during sleep. However, the underlying neuronal mechanisms of consolidation are not yet fully understood. It has been suggested that the spontaneous brain oscillations that characterize sleep stages are indicative of the consolidation of learning and memory. We investigated whether sleep spindles and/or slow-waves are associated with consolidation of VPL during non-rapid eye movement (NREM) sleep during the first sleep cycle, using magnetoencephalography (MEG), magnetic resonance imaging (MRI), and polysomnography (PSG). We hypothesized that after training, early visual areas will show an increase in slow sigma, fast sigma and/or delta activity, corresponding to slow/fast sleep spindles and slow-waves, respectively. We found that during sleep stage 2, but not during slow-wave sleep, the slow sigma power within the trained region of early visual areas was larger after training compared to baseline, and that the increase was larger in the trained region than in the untrained region. However, neither fast sigma nor delta band power increased significantly after training in either sleep stage. Importantly, performance gains for the trained task were correlated with the difference of power increases in slow sigma activity between the trained and untrained regions. This finding suggests that slow sigma activity plays a critical role in the consolidation of VPL, at least in sleep stage 2 during the first sleep cycle.