Mental Rotation Meets the Motion Aftereffect: The Role of hV5/MT+ in Visual Mental Imagery

Visual mental imagery: Evidence for a heterarchical neural architecture

Theories of Visual Mental Imagery (VMI) emphasize the processes of retrieval, modification, and recombination of sensory information from long-term memory. Yet, only few studies have focused on the behavioral mechanisms and neural correlates supporting VMI of stimuli from different semantic domains. Therefore, we currently have a limited understanding of how the brain generates and maintains mental representations of colors, faces, shapes - to name a few. Such an undetermined scenario renders unclear the organizational structure of neural circuits supporting VMI, including the role of the early visual cortex. We aimed to fill this gap by reviewing the scientific literature of five semantic domains: visuospatial, face, colors, shapes, and letters imagery. Linking theory to evidence from over 60 different experimental designs, this review highlights three main points. First, there is no consistent activity in the early visual cortex across all VMI domains, contrary to the prediction of the dominant model. Second, there is consistent activity of the frontoparietal networks and the left hemisphere's fusiform gyrus during voluntary VMI irrespective of the semantic domain investigated. We propose that these structures are part of a domain-general VMI sub-network. Third, domain-specific information engages specific regions of the ventral and dorsal cortical visual pathways. These regions partly overlap with those found in visual perception studies (e.g., fusiform face area for faces imagery; lingual gyrus for color imagery). Altogether, the reviewed evidence suggests the existence of domain-general and domain-specific mechanisms of VMI selectively engaged by stimulus-specific properties (e.g., colors or faces). These mechanisms would be supported by an organizational structure mixing vertical and horizontal connections (heterarchy) between sub-networks for specific stimulus domains. Such a heterarchical organization of VMI makes different predictions from current models of VMI as reversed perception. Our conclusions set the stage for future research, which should aim to characterize the spatiotemporal dynamics and interactions among key regions of this architecture giving rise to visual mental images.

Imaging the Spin: Disentangling the Core Processes Underlying Mental Rotation by Network Mapping of Data From Meta-analysis

Research on the mental rotation task has sparked debate regarding the specific processes that underly the capability of humans to mentally rotate objects. The spread of reported brain activations suggests that mental rotation is subserved by a neural network circle. However, no common network has yet been found that uncovers the crucial processes underlying this ability. We aimed to identify the common network crucial for mental rotation by coordinate-based network mapping of previous neuroimaging findings in mental rotation. A meta-analysis revealed 710 peak activation coordinates from 42 fMRI studies in mental rotation, which include a total 844 participants. The coordinates were mapped to a normative functional connectome (n = 1000) to identify a network of connected regions. To account for experimental factors, we examined this network against two control tasks, action imitation and symbolic number processing. A common and crucial network for mental rotation, centring on dorsal premotor, superior parietal and inferior temporal lobes was revealed. This network, separated from other experimental aspects, suggests that the crucial processes underlying mental rotation are motor rotation, visuospatial processing, and higher order visual object recognition.

Why do imagery and perception look and feel so different?

Despite the past few decades of research providing convincing evidence of the similarities in function and neural mechanisms between imagery and perception, for most of us, the experience of the two are undeniably different, why? Here, we review and discuss the differences between imagery and perception and the possible underlying causes of these differences, from function to neural mechanisms. Specifically, we discuss the directional flow of information (top-down versus bottom-up), the differences in targeted cortical layers in primary visual cortex and possible different neural mechanisms of modulation versus excitation. For the first time in history, neuroscience is beginning to shed light on this long-held mystery of why imagery and perception look and feel so different. This article is part of the theme issue 'Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation'.

Visual mental imagery engages the left fusiform gyrus, but not the early visual cortex: A meta-analysis of neuroimaging evidence

The dominant neural model of visual mental imagery (VMI) stipulates that memories from the medial temporal lobe acquire sensory features in early visual areas. However, neurological patients with damage restricted to the occipital cortex typically show perfectly vivid VMI, while more anterior damages extending into the temporal lobe, especially in the left hemisphere, often cause VMI impairments. Here we present two major results reconciling neuroimaging findings in neurotypical subjects with the performance of brain-damaged patients: (1) A large-scale meta-analysis of 46 fMRI studies, of which 27 investigated specifically visual mental imagery, revealed that VMI engages fronto-parietal networks and a well-delimited region in the left fusiform gyrus. (2) A Bayesian analysis showed no evidence for imagery-related activity in early visual cortices. We propose a revised neural model of VMI that draws inspiration from recent cytoarchitectonic and lesion studies, whereby fronto-parietal networks initiate, modulate, and maintain activity in a core temporal network centered on the fusiform imagery node, a high-level visual region in the left fusiform gyrus.

Acoustic Neurofeedback Increases Beta ERD During Mental Rotation Task

The purpose of the present study was to identify the effect of acoustic neurofeedback on brain activity during consecutive stages of mental rotation of 3D objects. Given the fact that the process of mental rotation of objects is associated with desynchronisation of beta rhythm (beta ERD), it was expected that suppression in this band would be greater in the experimental group than in the controls. Thirty-three participants were randomly allocated to two groups performing the classic Shepard-Metzler mental rotation task (1971). The experimental group received auditory stimuli when the level of concentration fell below the threshold value determined separately for each participant based on the engagement index [β/(α + Θ)]. The level of concentration in the control group was not stimulated. Compared to the controls, the experimental group was found with greater beta-band suppression recorded above the left parietal cortex during the early stage and above the right parietal cortex during the late stage of mental rotation task. At the late stage of mental rotation, only the experimental group was found with differences in beta ERD related to varied degrees of the rotation angle and the control condition (zero angles, no rotation) recorded above the right parietal cortex and the central area of cerebral cortex. The present findings suggest that acoustic feedback might improve the process of mental rotation.

Gender Differences in Large-Scale and Small-Scale Spatial Ability: A Systematic Review Based on Behavioral and Neuroimaging Research

Background: As we human beings are living in a multidimensional space all the time. Therefore, spatial ability is vital for the survival and development of individuals. However, males and females show gender differences in this ability. So, are these gender differences influenced by the scale type of spatial ability? It's not well specified. Therefore, to tackle this issue, we conducted the current research from the behavioral and neural level. Methods: Study 1 used the general meta-analysis method to explore whether individuals display the same gender differences in large- and small-scale spatial ability. Study 2 used the method of Activation Likelihood Estimation to identify the commonalities and distinctions of the brain activity between males and females on large- and small-scale spatial ability. Results: Study 1 showed that in behavior performance, males outperformed females in both large-scale and small-scale spatial ability, but the effect size of the gender difference in large-scale spatial ability is significantly greater than that in small-scale spatial ability. In addition, Study 2 showed that in terms of neural activity, males and females exhibited both similarities and differences no matter in large-scale or small-scale spatial ability. Especially, the contrast analysis between females and males demonstrated a stronger activation in the brain regions of bilateral lentiform nucleus and bilateral parahippocampal gyrus in large-scale spatial ability, and correspondence in right sub-gyral, right precuneus, and left middle frontal gyrus in small-scale spatial ability. Conclusions: The results indicated that the reason why females performed not so well in large-scale spatial ability was that they were more susceptible to emotions and their parahippocampal gyrus worked less efficiently than males; females performed not so well in small-scale spatial ability because they mostly adopted the egocentric strategy and their sub-gyral also worked less efficiently than males. The two different reasons have made for gender differences in favor of males in terms of spatial ability and such gender differences have different manifestations in large-scale and small-scale spatial ability. Possible implications of the results for understanding the issue of gender differences in spatial ability are discussed.

Shared and Distinct Neural Bases of Large- and Small-Scale Spatial Ability: A Coordinate-Based Activation Likelihood Estimation Meta-Analysis

Background: Spatial ability is vital for human survival and development. However, the relationship between large-scale and small-scale spatial ability remains poorly understood. To address this issue from a novel perspective, we performed an activation likelihood estimation (ALE) meta-analysis of neuroimaging studies to determine the shared and distinct neural bases of these two forms of spatial ability. Methods: We searched Web of Science, PubMed, PsycINFO, and Google Scholar for studies regarding "spatial ability" published within the last 20 years (January 1988 through June 2018). A final total of 103 studies (Table 1) involving 2,085 participants (male = 1,116) and 2,586 foci were incorporated into the meta-analysis. Results: Large-scale spatial ability was associated with activation in the limbic lobe, posterior lobe, occipital lobe, parietal lobe, right anterior lobe, frontal lobe, and right sub-lobar area. Small-scale spatial ability was associated with activation in the parietal lobe, occipital lobe, frontal lobe, right posterior lobe, and left sub-lobar area. Furthermore, conjunction analysis revealed overlapping regions in the sub-gyrus, right superior frontal gyrus, right superior parietal lobule, right middle occipital gyrus, right superior occipital gyrus, left inferior occipital gyrus, and precuneus. The contrast analysis demonstrated that the parahippocampal gyrus, left lingual gyrus, culmen, right middle temporal gyrus, left declive, left superior occipital gyrus, and right lentiform nucleus were more strongly activated during large-scale spatial tasks. In contrast, the precuneus, right inferior frontal gyrus, right precentral gyrus, left inferior parietal lobule, left supramarginal gyrus, left superior parietal lobule, right inferior occipital gyrus, and left middle frontal gyrus were more strongly activated during small-scale spatial tasks. Our results further indicated that there is no absolute difference in the cognitive strategies associated with the two forms of spatial ability (egocentric/allocentric). Conclusion: The results of the present study verify and expand upon the theoretical model of spatial ability proposed by Hegarty et al. Our analysis revealed a shared neural basis between large- and small-scale spatial abilities, as well as specific yet independent neural bases underlying each. Based on these findings, we proposed a more comprehensive version of the behavioral model.

Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI

In fMRI research, one often aims to examine activation in specific functional regions of interest (fROIs). Current statistical methods tend to localize fROIs inconsistently, focusing on avoiding detection of false activation. Not missing true activation is however equally important in this context. In this study, we explored the potential of an alternative-based thresholding (ABT) procedure, where evidence against the null hypothesis of no effect and evidence against a prespecified alternative hypothesis is measured to control both false positives and false negatives directly. The procedure was validated in the context of localizer tasks on simulated brain images and using a real data set of 100 runs per subject. Voxels categorized as active with ABT can be confidently included in the definition of the fROI, while inactive voxels can be confidently excluded. Additionally, the ABT method complements classic null hypothesis significance testing with valuable information by making a distinction between voxels that show evidence against both the null and alternative and voxels for which the alternative hypothesis cannot be rejected despite lack of evidence against the null.

Effects of Stimulus Type and Strategy on Mental Rotation Network: An Activation Likelihood Estimation Meta-Analysis

We can predict how an object would look like if we were to see it from different viewpoints. The brain network governing mental rotation (MR) has been studied using a variety of stimuli and tasks instructions. By using activation likelihood estimation (ALE) meta-analysis we tested whether different MR networks can be modulated by the type of stimulus (body vs. non-body parts) or by the type of tasks instructions (motor imagery-based vs. non-motor imagery-based MR instructions). Testing for the bodily and non-bodily stimulus axis revealed a bilateral sensorimotor activation for bodily-related as compared to non-bodily-related stimuli and a posterior right lateralized activation for non-bodily-related as compared to bodily-related stimuli. A top-down modulation of the network was exerted by the MR tasks instructions with a bilateral (preferentially sensorimotor left) network for motor imagery- vs. non-motor imagery-based MR instructions and the latter activating a preferentially posterior right occipito-temporal-parietal network. The present quantitative meta-analysis summarizes and amends previous descriptions of the brain network related to MR and shows how it is modulated by top-down and bottom-up experimental factors.

Planning Ahead: Object-Directed Sequential Actions Decoded from Human Frontoparietal and Occipitotemporal Networks

Object-manipulation tasks (e.g., drinking from a cup) typically involve sequencing together a series of distinct motor acts (e.g., reaching toward, grasping, lifting, and transporting the cup) in order to accomplish some overarching goal (e.g., quenching thirst). Although several studies in humans have investigated the neural mechanisms supporting the planning of visually guided movements directed toward objects (such as reaching or pointing), only a handful have examined how manipulatory sequences of actions-those that occur after an object has been grasped-are planned and represented in the brain. Here, using event-related functional MRI and pattern decoding methods, we investigated the neural basis of real-object manipulation using a delayed-movement task in which participants first prepared and then executed different object-directed action sequences that varied either in their complexity or final spatial goals. Consistent with previous reports of preparatory brain activity in non-human primates, we found that activity patterns in several frontoparietal areas reliably predicted entire action sequences in advance of movement. Notably, we found that similar sequence-related information could also be decoded from pre-movement signals in object- and body-selective occipitotemporal cortex (OTC). These findings suggest that both frontoparietal and occipitotemporal circuits are engaged in transforming object-related information into complex, goal-directed movements.

Adaptive smoothing as inference strategy: more specificity for unequally sized or neighbouring regions

Although spatial smoothing of fMRI data can serve multiple purposes, increasing the sensitivity of activation detection is probably its greatest benefit. However, this increased detection power comes with a loss of specificity when non-adaptive smoothing (i.e. the standard in most software packages) is used. Simulation studies and analysis of experimental data was performed using the R packages neuRosim and fmri. In these studies, we systematically investigated the effect of spatial smoothing on the power and number of false positives in two particular cases that are often encountered in fMRI research: (1) Single condition activation detection for regions that differ in size, and (2) multiple condition activation detection for neighbouring regions. Our results demonstrate that adaptive smoothing is superior in both cases because less false positives are introduced by the spatial smoothing process compared to standard Gaussian smoothing or FDR inference of unsmoothed data.

Dynamic Parieto-premotor Network for Mental Image Transformation Revealed by Simultaneous EEG and fMRI Measurement

Previous studies have suggested that the posterior parietal cortices and premotor areas are involved in mental image transformation. However, it remains unknown whether these regions really cooperate to realize mental image transformation. In this study, simultaneous EEG and fMRI were performed to clarify the spatio-temporal properties of neural networks engaged in mental image transformation. We adopted a modified version of the mental clock task used by Sack et al. [Sack, A. T., Camprodon, J. A., Pascual-Leone, A., & Goebel, R. The dynamics of interhemispheric compensatory processes in mental imagery. Science, 308, 702–704, 2005; Sack, A. T., Sperling, J. M., Prvulovic, D., Formisano, E., Goebel, R., Di Salle, F., et al. Tracking the mind's image in the brain II: Transcranial magnetic stimulation reveals parietal asymmetry in visuospatial imagery. Neuron, 35, 195–204, 2002]. In the modified mental clock task, participants mentally rotated clock hands from the position initially presented at a learned speed for various durations. Subsequently, they matched the position to the visually presented clock hands. During mental rotation of the clock hands, we observed significant beta EEG suppression with respect to the amount of mental rotation at the right parietal electrode. The beta EEG suppression accompanied activity in the bilateral parietal cortices and left premotor cortex, representing a dynamic cortical network for mental image transformation. These results suggest that motor signals from the premotor area were utilized for mental image transformation in the parietal areas and for updating the imagined clock hands represented in the right posterior parietal cortex.

Neural pathways conveying novisual information to the visual cortex

The visual cortex has been traditionally considered as a stimulus-driven, unimodal system with a hierarchical organization. However, recent animal and human studies have shown that the visual cortex responds to non-visual stimuli, especially in individuals with visual deprivation congenitally, indicating the supramodal nature of the functional representation in the visual cortex. To understand the neural substrates of the cross-modal processing of the non-visual signals in the visual cortex, we firstly showed the supramodal nature of the visual cortex. We then reviewed how the nonvisual signals reach the visual cortex. Moreover, we discussed if these non-visual pathways are reshaped by early visual deprivation. Finally, the open question about the nature (stimulus-driven or top-down) of non-visual signals is also discussed.

Hemispheric Differences within the Fronto-Parietal Network Dynamics Underlying Spatial Imagery

Spatial imagery refers to the inspection and evaluation of spatial features (e.g., distance, relative position, configuration) and/or the spatial manipulation (e.g., rotation, shifting, reorienting) of mentally generated visual images. In the past few decades, psychophysical as well as functional brain imaging studies have indicated that any such processing of spatially coded information and/or manipulation based on mental images (i) is subject to similar behavioral demands and limitations as in the case of spatial processing based on real visual images, and (ii) consistently activates several nodes of widely distributed cortical networks in the brain. These nodes include areas within both, the dorsal fronto-parietal as well as ventral occipito-temporal visual processing pathway, representing the “what” versus “where” aspects of spatial imagery. We here describe evidence from functional brain imaging and brain interference studies indicating systematic hemispheric differences within the dorsal fronto-parietal networks during the execution of spatial imagery. Importantly, such hemispheric differences and functional lateralization principles are also found in the effective brain network connectivity within and across these networks, with a direction of information flow from anterior frontal/premotor regions to posterior parietal cortices. In an attempt to integrate these findings of hemispheric lateralization and fronto-to-parietal interactions, we argue that spatial imagery constitutes a multifaceted cognitive construct that can be segregated in several distinct mental sub processes, each associated with activity within specific lateralized fronto-parietal (sub) networks, forming the basis of the here proposed dynamic network model of spatial imagery.

Task-dependent interaction between parietal and contralateral primary motor cortex during explicit versus implicit motor imagery

Both mental rotation (MR) and motor imagery (MI) involve an internalization of movement within motor and parietal cortex. Transcranial magnetic stimulation (TMS) techniques allow for a task-dependent investigation of the interhemispheric interaction between these areas. We used image-guided dual-coil TMS to investigate interactions between right inferior parietal lobe (rIPL) and left primary motor cortex (M1) in 11 healthy participants. They performed MI (right index-thumb pinching in time with a 1 Hz metronome) or hand MR tasks, while motor evoked potentials (MEPs) were recorded from right first dorsal interosseous. At rest, rIPL conditioning 6 ms prior to M1 stimulation facilitated MEPs in all participants, whereas this facilitation was abolished during MR. While rIPL conditioning 12 ms prior to M1 stimulation had no effect on MEPs at rest, it suppressed corticomotor excitability during MI. These results support the idea that rIPL forms part of a distinct inhibitory network that may prevent unwanted movement during imagery tasks.

Disambiguation of Necker cube rotation by monocular and binocular depth cues: relative effectiveness for establishing long-term bias

The apparent direction of rotation of perceptually bistable wire-frame (Necker) cubes can be conditioned to depend on retinal location by interleaving their presentation with cubes that are disambiguated by depth cues (Haijiang, Saunders, Stone, & Backus, 2006; Harrison & Backus, 2010a). The long-term nature of the learned bias is demonstrated by resistance to counter-conditioning on a consecutive day. In previous work, either binocular disparity and occlusion, or a combination of monocular depth cues that included occlusion, internal occlusion, haze, and depth-from-shading, were used to control the rotation direction of disambiguated cubes. Here, we test the relative effectiveness of these two sets of depth cues in establishing the retinal location bias. Both cue sets were highly effective in establishing a perceptual bias on Day 1 as measured by the perceived rotation direction of ambiguous cubes. The effect of counter-conditioning on Day 2, on perceptual outcome for ambiguous cubes, was independent of whether the cue set was the same or different as Day 1. This invariance suggests that a common neural population instantiates the bias for rotation direction, regardless of the cue set used. However, in a further experiment where only disambiguated cubes were presented on Day 1, perceptual outcome of ambiguous cubes during Day 2 counter-conditioning showed that the monocular-only cue set was in fact more effective than disparity-plus-occlusion for causing long-term learning of the bias. These results can be reconciled if the conditioning effect of Day 1 ambiguous trials in the first experiment is taken into account (Harrison & Backus, 2010b). We suggest that monocular disambiguation leads to stronger bias either because it more strongly activates a single neural population that is necessary for perceiving rotation, or because ambiguous stimuli engage cortical areas that are also engaged by monocularly disambiguated stimuli but not by disparity-disambiguated stimuli.