Recurrent Processing Drives Perceptual Plasticity

A new predictive coding model for a more comprehensive account of delusions

Attempts to understand psychosis-the experience of profoundly altered perceptions and beliefs-raise questions about how the brain models the world. Standard predictive coding approaches suggest that it does so by minimising mismatches between incoming sensory evidence and predictions. By adjusting predictions, we converge iteratively on a best guess of the nature of the reality. Recent arguments have shown that a modified version of this framework-hybrid predictive coding-provides a better model of how healthy agents make inferences about external reality. We suggest that this more comprehensive model gives us a richer understanding of psychosis compared with standard predictive coding accounts. In this Personal View, we briefly describe the hybrid predictive coding model and show how it offers a more comprehensive account of the phenomenology of delusions, thereby providing a potentially powerful new framework for computational psychiatric approaches to psychosis. We also make suggestions for future work that could be important in formalising this novel perspective.

A multimodal approach connecting cortical and behavioural responses to the visual continuity illusion

In their recently published study, Gil, Valente and Shemesh combined behaviour, functional magnetic resonance imaging, electroencephalography and causal interventions to establish and validate a cortical processing substrate underlying the transition from static to dynamic visual states in the rat. Their research highlights the superior colliculus as the primary mediator of visual temporal discrimination by showing a direct correlation between behavioural and cortically derived flicker fusion frequency thresholds. This work provides the first empirical evidence addressing the previously established disparity between behavioural and cortically derived flicker fusion frequency thresholds. It demonstrates how important convergent multimodal approaches are to mapping and validating previously disputed cortical pathways. Here, we discuss and evaluate their work, suggesting possible future applications in the field of behavioural neuroscience.

Expectation Cues and False Percepts Generate Stimulus-Specific Activity in Distinct Layers of the Early Visual Cortex

Perception has been proposed to result from the integration of feedforward sensory signals with internally generated feedback signals. Feedback signals are believed to play an important role in driving false percepts, that is, seeing things that are not actually there. Feedforward and feedback influences on perception can be studied using layer-specific fMRI, which we used here to interrogate neural activity underlying high-confidence false percepts while healthy human participants (N = 25, male and female) performed a perceptual orientation discrimination task. Auditory cues implicitly signaled the most likely upcoming orientation (referred to here as expectations). These expectations induced orientation-specific templates in the deep and superficial layers of V2, without affecting perception. In contrast, the orientation of falsely perceived stimuli with high confidence was reflected in the middle input layers of V2, suggesting a feedforward signal contributing to false percepts. The prevalence of high-confidence false percepts was related to everyday hallucination severity in a separate online sample (N = 100), suggesting a possible link with abnormal perceptual experiences. These results reveal a potential feedforward mechanism underlying false percepts, reflected by spontaneous stimulus-like activity in the input layers of the visual cortex, independent of top-down signals reflecting cued orientations.SIGNIFICANCE STATEMENT False percepts have been suggested to arise through excessive feedback signals. However, feedforward contributions to false percepts have remained largely understudied. Laminar fMRI has been shown to be useful in distinguishing feedforward from feedback activity as it allows the imaging of different cortical layers. In the present study we demonstrate that although cued orientations are encoded in the feedback layers of the visual cortex, the content of the false percepts are encoded in the feedforward layers and did not rely on these cued orientations. This shows that false percepts can in principle emerge from random feedforward signals in the visual cortex, with possible implications for disorders hallmarked by hallucinations like schizophrenia and Parkinson's disease.

Ultra-High Field Imaging of Human Visual Cognition

Functional magnetic resonance imaging (fMRI), the key methodology for mapping the functions of the human brain in a noninvasive manner, is limited by low temporal and spatial resolution. Recent advances in ultra-high field (UHF) fMRI provide a mesoscopic (i.e., submillimeter resolution) tool that allows us to probe laminar and columnar circuits, distinguish bottom-up versus top-down pathways, and map small subcortical areas. We review recent work demonstrating that UHF fMRI provides a robust methodology for imaging the brain across cortical depths and columns that provides insights into the brain's organization and functions at unprecedented spatial resolution, advancing our understanding of the fine-scale computations and interareal communication that support visual cognition.

A "Bandwidth" in cortical representations of multiple faces

The human ability to process multiple items simultaneously can be constrained by the extent to which those items are represented by distinct neural populations. In the current study, we used fMRI to investigate the cortical representation of multiple faces. We found that the addition of a second face to occupy both visual hemifields led to an increased response, whereas a further addition of faces within the same visual hemifield resulted in a decreased response. This pattern was widely observed in the occipital visual cortex, the intraparietal sulcus, and extended to the posterior inferotemporal cortex. A parallel trend was found in a behavioral change-detection task, revealing a perceptual "bandwidth" of multiface processing. The sensitivity to face clutter gradually decreased along the ventral pathway, supporting the notion of a buildup of clutter-tolerance representation. These cortical response patterns to face clutters suggest that adding signals with nonoverlapping cortical representation enhanced perception, while adding signals that competed for representation resources impaired perception.

Reactivation-induced memory integration prevents proactive interference in perceptual learning

We acquire perceptual skills through experience to adapt ourselves to the changing environment. Accomplishing an effective skill acquisition is a main purpose of perceptual learning research. Given the often observed learning effect specificity, multiple perceptual learnings with shared parameters could serve to improve the generalization of the learning effect. However, the interference between the overlapping memory traces of different learnings may impede this effort. Here, we trained human participants on an orientation discrimination task. We observed a proactive interference effect that the first training blocked the second training at its untrained location. This was a more pronounced effect than the well-known location specificity in perceptual learning. We introduced a short reactivation of the first training before the second training and successfully eliminated the proactive interference when the second training was inside the reconsolidation time window of the reactivated first training. Interestingly, we found that practicing an irrelevant task at the location of the second training immediately after the reactivation of the first training could also restore the effect of the second training but in a smaller magnitude, even if the second training was conducted outside of the reconsolidation window. We proposed a two-level mechanism of reactivation-induced memory integration to account for these results. The reactivation-based procedure could integrate either the previously trained and untrained locations or the two trainings at these locations, depending on the activated representations during the reconsolidation process. The findings provide us with new insight into the roles of long-term memory mechanisms in perceptual learning.

What multiplexing means for the interpretation of functional MRI data

Despite technology advances that have enabled routine acquisition of functional MRI data with sub-millimeter resolution, the inferences that cognitive neuroscientists must make to link fMRI data to behavior are complicated. Thus, a single dataset subjected to different analyses can be interpreted in different ways. This article presents two optical analogies that can be useful for framing fMRI analyses in a way that allows for multiple interpretations of fMRI data to be valid simultaneously without undermining each other. The first is reflection: when an object is reflected in a mirrored surface, it appears as if the reflected object is sharing space with the mirrored object, but of course it is not. This analogy can be a good guide for interpreting the fMRI signal, since even at sub-millimeter resolutions the signal is determined by a mixture of local and long-range neural computations. The second is refraction. If we view an object through a multi-faceted prism or gemstone, our view will change-sometimes dramatically-depending on our viewing angle. In the same way, interpretation of fMRI data (inference of underlying neuronal activity) can and should be different depending on the analysis approach. Rather than representing a weakness of the methodology, or the superiority of one approach over the other (for example, simple regression analysis versus multi-voxel pattern analysis), this is an expected consequence of how information is multiplexed in the neural networks of the brain: multiple streams of information are simultaneously present in each location. The fact that any one analysis typically shows only one view of the data also puts some parentheses around fMRI practitioners' constant search for ground truth against which to compare their data. By holding our interpretations lightly and understanding that many interpretations of the data can all be true at the same time, we do a better job of preparing ourselves to appreciate, and eventually understand, the complexity of the brain and the behavior it produces.

Perceptual learning: Breaking specificity by variability

A new psychophysical study in humans suggests that increasing the variability of task-irrelevant features during training enhances the generalization of visual perceptual learning to untrained stimuli and locations.

Many Roads Lead to Rome: Differential Learning Processes for the Same Perceptual Improvement

Repeatedly exercising a perceptual ability usually leads to improvement, yet it is unclear whether the mechanisms supporting the same perceptual learning could be flexibly adjusted according to the training settings. Here, we trained adult observers in an orientation-discrimination task at either a single (focused) retinal location or multiple (distributed) retinal locations. We examined the observers' discriminability (N = 52) and bias (N = 20) in orientation perception at the trained and untrained locations. The focused and distributed training enhanced orientation discriminability by the same amount and induced a bias in perceived orientation at the trained locations. Nevertheless, the distributed training promoted location generalization of both practice effects, whereas the focused training resulted in specificity. The two training tactics also differed in long-term retention of the training effects. Our results suggest that, depending on the training settings of the same task, the same discrimination learning could differentially engage location-specific and location-invariant representations of the learned stimulus feature.

Visual Plasticity in Adulthood: Perspectives from Hebbian and Homeostatic Plasticity

The visual system retains profound plastic potential in adulthood. In the current review, we summarize the evidence of preserved plasticity in the adult visual system during visual perceptual learning as well as both monocular and binocular visual deprivation. In each condition, we discuss how such evidence reflects two major cellular mechanisms of plasticity: Hebbian and homeostatic processes. We focus on how these two mechanisms work together to shape plasticity in the visual system. In addition, we discuss how these two mechanisms could be further revealed in future studies investigating cross-modal plasticity in the visual system.

Simple contextual cueing prevents retroactive interference in short-term perceptual training of orientation detection tasks

Perceptual training of multiple tasks suffers from interference between the trained tasks. Here, we conducted five psychophysical experiments with separate groups of participants to investigate the possibility of preventing the interference in short-term perceptual training. We trained the participants to detect two orientations of Gabor stimuli in two adjacent days at the same retinal location and examined the interference of training effects between the two orientations. The results showed significant retroactive interference from the second orientation to the first orientation (Experiment 1 and Experiment 2). Introducing a 6-h interval between the pre-test and training of the second orientation did not eliminate the interference effect, excluding the interpretation of disrupted reconsolidation as the pre-test of the second orientation may reactivate and destabilize the representation of the first orientation (Experiment 3). Finally, the training of the two orientations was accompanied by fixations in two colors, each serving as a contextual cue for one orientation. The results showed that the retroactive interference was not evident if the participants passively perceived contextual cues during the training and test sessions (Experiment 4). Importantly, this facilitation effect could be observed if the contextual cues appeared only during the training, demonstrating the robustness of the effect (Experiment 5). Our findings suggest that the retroactive interference effect in short-term perceptual training of orientation detection tasks was likely the result of higher-level factors such as shared contextual cues embedded in the tasks. The efficiency of multiple perceptual trainings could be facilitated by associating the trained tasks with different contextual cues.

Sleep affects higher-level categorization of speech sounds, but not frequency encoding

Sleep can increase consolidation of new knowledge and skills. It is less clear whether sleep plays a role in other aspects of experience-dependent neuroplasticity, which underlie important human capabilities such as spoken language processing. Theories of sensory learning differ in their predictions; some imply rapid learning at early sensory levels, while other propose a slow, progressive timecourse such that higher-level categorical representations guide immediate, novice learning, while lower-level sensory changes do not emerge until later stages. In this study, we investigated the role of sleep across both behavioural and physiological indices of auditory neuroplasticity. Forty healthy young human adults (23 female) who did not speak a tonal language participated in the study. They learned to categorize non-native Mandarin lexical tones using a sound-to-category training paradigm, and were then randomly assigned to a Nap or Wake condition. Polysomnographic data were recorded to quantify sleep during a 3 h afternoon nap opportunity, or equivalent period of quiet wakeful activity. Measures of behavioural performance accuracy revealed a significant improvement in learning the sound-to-category training paradigm between Nap and Wake groups. Conversely, a neural index of fine sound encoding fidelity of speech sounds known as the frequency-following response (FFR) suggested no change due to sleep, and a null model was supported, using Bayesian statistics. Together, these results support theories that propose a slow, progressive and hierarchical timecourse for sensory learning. Sleep's effect may play the biggest role in the higher-level learning, although contributions to more protracted processes of plasticity that exceed the study duration cannot be ruled out.

Neurochemical and functional interactions for improved perceptual decisions through training

Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task. Using magnetic resonance spectroscopy (MRS), we measure neurotransmitters (i.e., glutamate, GABA) that are known to be involved in visual processing and learning in sensory [early visual cortex (EV)] and decision-related [dorsolateral prefrontal cortex (DLPFC)] brain regions. Using resting-state functional magnetic resonance imaging (rs-fMRI), we test for functional interactions between these regions that relate to decision processes. We demonstrate that training improves perceptual judgments (i.e., orientation identification), as indicated by faster rates of evidence accumulation after training. These learning-dependent changes in decision processes relate to lower EV glutamate levels and EV-DLPFC connectivity, suggesting that glutamatergic excitation and functional interactions between visual and dorsolateral prefrontal cortex facilitate perceptual decisions. Further, anodal transcranial direct current stimulation (tDCS) in EV impairs learning, suggesting a direct link between visual cortex excitation and perceptual decisions. Our findings advance our understanding of the role of learning in perceptual decision making, suggesting that glutamatergic excitation for efficient sensory processing and functional interactions between sensory and decision-related regions support improved perceptual decisions.NEW & NOTEWORTHY Combining multimodal brain imaging [magnetic resonance spectroscopy (MRS), functional connectivity] with interventions [transcranial direct current stimulation (tDCS)], we demonstrate that glutamatergic excitation and functional interactions between sensory (visual) and decision-related (dorsolateral prefrontal cortex) areas support our ability to optimize perceptual decisions through training.

Exogenous attention generalizes location transfer of perceptual learning in adults with amblyopia

Visual perceptual learning (VPL) is a behavioral manifestation of brain neuroplasticity. However, its practical effectiveness is limited because improvements are often specific to the trained conditions and require significant time and effort. It is critical to understand the conditions that promote learning and transfer. Covert endogenous (voluntary) and exogenous (involuntary) spatial attention help overcome VPL location specificity in neurotypical adults, but whether they also do so for people with atypical visual development is unknown. This study investigates the role of exogenous attention during VPL in adults with amblyopia, an ideal population given their asymmetrically developed, but highly plastic, visual cortex. Here we show that training on a discrimination task leads to improvements in foveal contrast sensitivity, acuity, and stereoacuity. Notably, exogenous attention helps generalize learning beyond trained spatial locations. Future large-scale studies can verify the extent to which attention enhances the effectiveness of perceptual learning during rehabilitation of visual disorders.

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Contrast sensitivity (CS)-based VPL in amblyopes improves CS, acuity and stereoacuity

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Similar improvement in trained amblyopic eye and untrained fellow eye

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Exogenous spatial attention facilitates location transfer of VPL in amblyopic adults

Perceptual learning as a result of concerted changes in prefrontal and visual cortex

Our perceptual ability remarkably improves with training. Some studies on visual perceptual learning have shown refined neural representation of the trained stimulus in the visual cortex, whereas others have exclusively argued for improved readout and decision-making processes in the frontoparietal cortex. The mixed results have rendered the underlying neural mechanisms puzzling and hotly debated. By simultaneously recording from monkey visual area V4 and ventrolateral prefrontal cortex (PFC) implanted with microelectrode arrays, we dissected learning-induced cortical changes over the course of training the monkeys in a global form detection task. Decoding analysis dissociated two distinct components of neuronal population codes that were progressively and markedly enhanced in both V4 and PFC. One component was closely related to the target stimulus feature and was subject to task-dependent top-down modulation; it emerged earlier in V4 than PFC and its enhancement was specific to the trained configuration of the target stimulus. The other component of the neural code was entirely related to the animal's behavioral choice; it emerged earlier in PFC than V4 and its enhancement completely generalized to an untrained stimulus configuration. These results implicate two concurrent and synergistic learning processes: a perceptual process that is specific to the details of the trained stimulus feature and a cognitive process that is dependent on the total amount of learning experience in the trained task. When combined, these two learning processes were well predictive of the animal's learning behavior.

Correcting for Superficial Bias in 7T Gradient Echo fMRI

The arrival of submillimeter ultra high-field fMRI makes it possible to compare activation profiles across cortical layers. However, the blood oxygenation level dependent (BOLD) signal measured by gradient echo (GE) fMRI is biased toward superficial layers of the cortex, which is a serious confound for laminar analysis. Several univariate and multivariate analysis methods have been proposed to correct this bias. We compare these methods using computational simulations of 7T fMRI data from regions of interest (ROI) during a visual attention paradigm. We also tested the methods on a pilot dataset of human 7T fMRI data. The simulations show that two methods–the ratio of ROI means across conditions and a novel application of Deming regression–offer the most robust correction for superficial bias. Deming regression has the additional advantage that it does not require that the conditions differ in their mean activation over voxels within an ROI. When applied to the pilot dataset, we observed strikingly different layer profiles when different attention metrics were used, but were unable to discern any differences in laminar attention across layers when Deming regression or ROI ratio was applied. Our simulations demonstrates that accurate correction of superficial bias is crucial to avoid drawing erroneous conclusions from laminar analyses of GE fMRI data, and this is affirmed by the results from our pilot 7T fMRI data.

Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception

Binocular disparity provides critical information about three-dimensional (3D) structures to support perception and action. In the past decade significant progress has been made in uncovering human brain areas engaged in the processing of binocular disparity signals. Yet, the fine-scale brain processing underlying 3D perception remains unknown. Here, we use ultra-high-field (7T) functional imaging at submillimeter resolution to examine fine-scale BOLD fMRI signals involved in 3D perception. In particular, we sought to interrogate the local circuitry involved in disparity processing by sampling fMRI responses at different positions relative to the cortical surface (i.e., across cortical depths corresponding to layers). We tested for representations related to 3D perception by presenting participants (male and female, N = 8) with stimuli that enable stable stereoscopic perception [i.e., correlated random dot stereograms (RDS)] versus those that do not (i.e., anticorrelated RDS). Using multivoxel pattern analysis (MVPA), we demonstrate cortical depth-specific representations in areas V3A and V7 as indicated by stronger pattern responses for correlated than for anticorrelated stimuli in upper rather than deeper layers. Examining informational connectivity, we find higher feedforward layer-to-layer connectivity for correlated than anticorrelated stimuli between V3A and V7. Further, we observe disparity-specific feedback from V3A to V1 and from V7 to V3A. Our findings provide evidence for the role of V3A as a key nexus for disparity processing, which is implicated in feedforward and feedback signals related to the perceptual estimation of 3D structures.SIGNIFICANCE STATEMENT Binocular vision plays a significant role in supporting our interactions with the surrounding environment. The fine-scale neural mechanisms that underlie the brain's skill in extracting 3D structures from binocular signals are poorly understood. Here, we capitalize on recent advances in ultra-high-field functional imaging to interrogate human brain circuits involved in 3D perception at submillimeter resolution. We provide evidence for the role of area V3A as a key nexus for disparity processing, which is implicated in feedforward and feedback signals related to the perceptual estimation of 3D structures from binocular signals. These fine-scale measurements help bridge the gap between animal neurophysiology and human fMRI studies investigating cross-scale circuits, from micro circuits to global brain networks for 3D perception.

Feature-based attention enables robust, long-lasting location transfer in human perceptual learning

Visual perceptual learning (VPL) is typically specific to the trained location and feature. However, the degree of specificity depends upon particular training protocols. Manipulating covert spatial attention during training facilitates learning transfer to other locations. Here we investigated whether feature-based attention (FBA), which enhances the representation of particular features throughout the visual field, facilitates VPL transfer, and how long such an effect would last. To do so, we implemented a novel task in which observers discriminated a stimulus orientation relative to two reference angles presented simultaneously before each block. We found that training with FBA enabled remarkable location transfer, reminiscent of its global effect across the visual field, but preserved orientation specificity in VPL. Critically, both the perceptual improvement and location transfer persisted after 1 year. Our results reveal robust, long-lasting benefits induced by FBA in VPL, and have translational implications for improving generalization of training protocols in visual rehabilitation.

A protocol for ultra-high field laminar fMRI in the human brain

Ultra-high field (UHF) neuroimaging affords the sub-millimeter resolution that allows researchers to interrogate brain computations at a finer scale than that afforded by standard fMRI techniques. Here, we present a step-by-step protocol for using UHF imaging (Siemens Terra 7T scanner) to measure activity in the human brain. We outline how to preprocess the data using a pipeline that combines tools from SPM, FreeSurfer, ITK-SNAP, and BrainVoyager and correct for vasculature-related confounders to improve the spatial accuracy of the fMRI signal. For complete details on the use and execution of this protocol, please refer to Jia et al. (2020) and Zamboni et al. (2020).