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Психология. Журнал Высшей школы экономики. 2022. Т. 19. № 4. С. 663-683. Psychology. Journal of the Higher School of Economics. 2022. Vol. 19. N 4. P. 663-683. DOI: 10.17323/1813-8918-2022-4-663-683
NEURAL SUBSTRATES THAT MAINTAIN PERCEIVING 3D INFORMATION: AN ALE META-ANALYSIS STUDY
M. FARSHCHIa
a HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation
Нейронные субстраты, лежащие в основе восприятия трехмерной информации: метааналитическое исследование методом оценки вероятности активации (ALE)
М. Фаршчи"
а Национальный исследовательский университет «Высшая школа экономики», 101000, Россия, Москва, ул. Мясницкая, д. 20
Abstract
3D perception is a crucial ability for human existence in the environment. Numerous studies have been focused on the neural mechanisms that are at the core of perceiving 3D information. However, there is no clear consensus on the reported results due to the wide variety of utilized tasks, stimuli, and visual cues. This fMRI meta-analysis study aims to a) define which specific brain areas are more active in processing of different depth cues during perceiving 3D information across the neuroimaging studies, b) explore a map of the functional brain activation associated with perceiving 3D within the brain areas that have received little attention, and c) identify selective areas that are more sensitive to types of stimuli and task paradigms. Data from 26 experiments was included in an Activation Likelihood Estimation analysis (ALE). The findings revealed six clusters of activation including the bilateral occipital, bilateral temporal, right parietal, and left frontal areas associated with the processing of visual depth cues. The
Резюме
Восприятие трехмерной информации — способность, необходимая для нашего существования в окружающей среде. Многочисленные исследования были направлены на изучение нейронных механизмов, лежащих в основе восприятия трехмерной информации. Однако нет четкого консенсуса по представленным результатам из-за большого разнообразия используемых задач, стимулов и визуальных подсказок. Это метааналитическое исследование фМРТ-данных позволит: а) выяснить, какие определенные области мозга более активны во процессе обработки различных признаков глубины изображения во время восприятия трехмерной информации в рамках нейрови-зуализационных исследований, б) изучить карту функциональной активации мозга, связанной с восприятием трехмерного изображения в областях мозга, которым ранее уделялось мало внимания, и в) определить избранные области, которые более чувствительны к определенным типам стимулов и парадигмам, связанным с выполнением задач. Данные 26 исследований были включены в анализ оценки вероятности активации (ALE). Результаты выявили шесть групп активации, включая билатеральную затылочную, билатеральную височную, правую теменную и левую лобную области, связанные с
analyses of task types showed higher activation in the right precuneus, and the left middle, and inferior occipital gyri for the active judgment paradigm and the left fusiform gyrus for passive viewing. The results showed that the left fusiform gyrus is sensitive to static image stimuli. This study for the first time provides a concordant map of activation for the perception process of 3D (rather than 2D) and suggests that perceiving 3D requires increased brain resources.
Keywords: visual 3D perception, ALE meta-analysis, visual depth cues, types of stimuli, task paradigms.
обработкой визуальных признаков глубины. Анализ типов задач показал более высокую активацию в правом предклинье, а также в средней левой и нижней затылочной извилинах во время выполнения парадигмы активного суждения и в левой веретенообразной извилине во время пассивного просмотра. Результаты показали, что левая веретенообразная извилина чувствительна к статичным стимулам. Это исследование впервые предоставляет согласованную карту активации процесса трехмерного, а не двумерного восприятия и предполагает, что для трехмерного восприятия требуются повышенные ресурсы мозга.
Ключевые слова: визуальное трехмерное восприятие, оценка вероятности активации (ALE), мета-анализ ALE, визуальные признаки глубины, типы стимулов, парадигмы на выполнение задач.
Maddex Farshchi — Graduate, Doctoral School of Psychology, HSE University Research Area: visual perception, 3D shape perception, fMRI, meta-analysis. Email: Maddex.farshchi@gmail.com, Mfarshchi@hse.ru
Фаршчи Маддекс — выпускник аспирантуры,
Национальный" исследовательским университет
«Высшая школа экономики».
Сфера научных интересов: визуальное восприятие,
восприятие трехмерной формы, фМРТ, метаанализ.
Контакты: Maddex.farshchi@gmail.com, М£аг-
shchi@hse.ru
Acknowledgments
The author would like to express his most sincere gratitude to Dr. Zachary Yaple for his expert comments and discussion on the manuscript and Dr. Oksana Zinchenko for the valuable suggestions.
Благодарности
Автор выражает благодарность Захарию Яплу за экспертные замечания и возможность обсуж-дить рукопись, а также Оксане Зинченко за ценные предложения.
We live in a three-dimensional (3D) environment and we have the ability to perceive the spatial relationship of 3D objects. The ability to have a 3D perception is crucial for us to navigate our environment, recognize objects, and interact with them. Our brain is extremely rapid in detecting, processing, and categorizing objects (Kirchner & Thorpe, 2006; Fabre-Thorpe, 2011) and is noteworthy for its ability to recognize the shapes of 3D objects (Cyr & Kimia, 2001; Gauthier et al., 2002).
Our understanding of the neural mechanism that supports the perception of 3D information has dramatically increased. The brain can recover the 3D information from the 2D retinal images using visual depth cues such as binocular disparity, shading, texture, motion, and perspective (Andersen & Bradley, 1998; Todd, 2004; Norman et al., 2004; Welchman, 2016). The visual depth cues can provide salient information for the perception of 3D shapes (Todd, 2004). These sources of visual information can facilitate the unambiguous determination of the 3D shape of an
object. These depth cues can be processed separately using different mechanisms in the brain and they can be combined to achieve a perceptual judgment (Welchman, 2016). Numerous studies using functional magnetic resonance imaging (fMRI) and single-cell recording have been conducted to identify the neural mechanisms of perceiving 3D information from depth cues resources in humans and primates. Studies of monkeys have shown that numerous areas, including early visual areas and several temporal and parietal areas, are engaged in processing of different visual depth cues such as disparity, motion, texture, and shading (Bradley et al., 1998; Vanduffel et al., 2002; Sakata et al., 2005; Durand et al., 2007; Mysore et al., 2010; for review, Orban, 2011). Correspondingly, human studies' findings suggest that a broad range of areas in ventral and dorsal visual streams are involved in this process: the occipital lobe (Welchman et al., 2005; Chandrasekaran et al., 2007; Dovencioglu et al., 2013), temporal lobe (Sarkheil et al., 2008; Ogawa et al., 2013), and parietal lobe (Taira et al., 2001; Iwami et al., 2002). A study by Georgieva et al. (2008) showed that higher activation in inferior temporal, occipital, and several areas in intraparietal areas is associated with the processing of 3D shapes from texture and shading cues. Moreover, this group's later study (Georgieva et al., 2009) confirmed the role of human occipital (specifically V3 and V3A), inferior temporal, and intraparietal areas in the processing of 3D shapes from disparity cues (for review, Welchman, 2016). Interestingly, a study by Durand et al. (2007) using homologous stimuli showed the role of intraparietal areas in the processing of 3D shapes from disparity cues in monkeys. In line with these results, studies reported that patients with lesions in occipitoparietal areas demonstrated problems with depth cues such as motion and binocular disparity and the impairment of 3D perception ability (Rothstein & Sacks, 1972; Vaina, 1989). These results emphasize the important role of these areas in perceiving 3D information based on depth cues.
Despite these valuable findings, it is important to note that the results across different neuroimaging studies regarding perceiving 3D are not always consistent. This inconsistency can be due to several reasons, including the individual differences in the sample, data acquisition techniques, data processing, and analyzing methods (Oakes et al., 2005; Eklund et al., 2012). One way to deal with such inconsistencies is by performing a meta-analysis to achieve a congruent brain map across different neuroimaging studies (Botvinik-Nezer et al., 2020). Surprisingly, according to a search in the scientific databases, no meta-analysis review has been found allocated to the 3D perception process. Thus, the first aim of this meta-analysis is to address these issues and investigate the brain regions most likely to be active during processing depth cues that underlie perceiving 3D information. Considering the different mechanisms for processing each visual depth cue in the brain, this analysis provides a better understanding of the brain areas that may be engaged during the integration of the visual cues and overlap in the course of the different visual depth cues processing. As well as for the first time calculate a concordant map of brain activation associated with this process across the neuroimaging studies.
The majority of the literature in the visual perception field emphasize the specific brain areas including the early visual areas and occipitotemporal networks. Such region-of-interest (ROI) analyses might lead to the negligence of other brain
regions that can be part of the visual perception process. In this meta-analysis using whole-brain neuroimaging studies, the second aim is to explore a map of functional brain activation associated with perceiving 3D information within brain areas that have received little attention in visual studies.
A further source of inconsistency of the results of studies of visual perception can be due to utilized stimuli and task paradigms. Studies in this field employ diverse types of stimuli including static images or dynamic videos, with different visual cues such as texture, shading, or motion, using monocular or stereo viewing. It is important to note that different types of stimuli can impact the results of a study. For example, dynamic as compared to static stimuli can potentially engage more motion-related brain areas in the occipital lobe (V3B/KO) (Vanduffel et al., 2002; Klaver et al., 2008), or different visual cues of stimuli can recruit a different brain mechanism to be processed (Welchman, 2016). Likewise, task paradigms that include passive viewing or some form of active judgment tasks can potentially lead to different brain activations. Various types of active judgment paradigms such as depth judgment tasks, recognition/detection tasks, or mental rotation tasks require more cognitive effort. Most visual tasks involve an increased level of arousal, require sustained attention, task preparation, and response selection (Shulman et al., 1997). Since the visual cortex activation depends not only on types of stimuli and visual cues but also on the nature of the task (Orban et al., 1997), the third aim of this study is to investigate the specific brain areas engaged in different types of task paradigms (active and passive) and stimuli (static and dynamic). This analysis can improve our understanding of the neural network associated with types of utilized stimuli and task paradigms in neuroimaging studies in the course of perceiving 3D information.
According to the literature, the first hypothesis of this meta-analysis study predicts that perceiving 3D compared to 2D information requires more activation in the areas that are involved in the processing of each or integrating depth cues such as binocular disparity (e.g. bilateral occipital areas, occipitotemporal areas, and superior parietal areas) (Iwami et al., 2002; Georgieva et al., 2009), motion (e.g. occipital areas) (Orban et al., 1999; Sarkheil et al., 2008), shading and texture (e.g. bilateral occipitotemporal areas) (Taira et al., 2001; Georgieva et al., 2008). The second hypothesis predicts that this meta-analysis can reveal brain activations in less-studied areas such as superior and middle frontal gyri that are involved in the processing of motion (Paradis et al., 2008), and mental rotation (Halari et al., 2006; Schöning et al., 2007). The third hypothesis of this study consists of two sections. First, since different types of active judgment tasks require mental rotation, recognition, and categorization process, it can potentially activate associated brain areas specifically in parietal areas and bilateral occipitotemporal areas (Alivisatos & Petrides, 1997; Gerlach et al., 2000; Gauthier et al., 2002). Therefore, a higher level of activation is predicted for active judgment task paradigms compared to passive viewing paradigms within these areas. Secondly, when comparing dynamic videos with static image stimuli, a higher level of activation is predicted in motion processing areas including bilateral middle occipital gyri for dynamic stimuli (Vanduffel et al., 2002; Klaver et al., 2008).
Materials and Methods
Study Selection
A literature search was performed by entering keywords "3D" AND "perception" AND "fMRI" into Scopus (https://www.scopus.com/) and Web of Science (http://www.webofknowledge.com/) databases in September 2019. After removing duplicates and limiting to articles published in English, the search identified 199 studies. A PRISMA flowchart in Figure 1 shows the steps taken to identify eligible
Figure 1
The PRISMA Flowchart For Steps of This Study Consisted of Identification, Screening, Eligibility, and Included Articles to This Meta-Analysis Based on Moher et al. (2009) Suggested Template
articles. To identify eligible articles, the following studies were excluded: 1) did not investigate visual perception (e.g. auditory or tactile study), 2) did not report fMRI data, 3) focused on clinical, special populations, or non-human subjects, 4) did not use whole-brain analysis or used ROI analysis, 5) did not report fMRI foci or did not report foci in standard stereotactic coordinate atlas either of Talairach (Talairach & Tournoux, 1988) or Montreal Neurological Institute (MNI) (Evans et al., 1993), and 6) used human facial stimuli. Studies using visual stimuli of human faces were excluded because the processing of faces has been linked with different networks in the brain (McCarthy et al., 1997; Haxby et al., 2000). The remaining articles underwent a full-text review to check for the task, stimuli, methodology, and contrast eligibility. During the full-text review stage, articles were excluded if they did not report enough information about the procedure of the experiment, focused on the resting state of imaging, or had mixed methodological procedures such as visual-tactile brain imaging studies. Regarding the task and stimuli, articles were discarded if they involved irrelevant tasks (e.g. grasping) that may engage the other brain mechanisms, or if they did not include 3D stimuli. Additionally, studies that did not compare 3D and 2D conditions were also excluded from this meta-analysis. By comparing 3D and 2D conditions, we can find the brain areas that are more sensitive to 3D than 2D, which would then lead to a better understanding of the brain mechanisms that underlie perceiving 3D information (Todd, 2004). All the contrasts selected for this meta-analysis study have compared the 3D conditions to the 2D conditions. Please note that the 2D conditions lacked the depth cues that elicit 3D perception. Data from a total of 26 experiments in 16 articles were extracted and included in the meta-analysis. The detailed information of these studies and the participant demographics information are shown in Table 1.
In this meta-analysis study, utilized stimuli in studies were divided into two groups: a) static images including all types of static images, shapes, patterns, and dots (n = 16 experiments: Taira et al., 2001; Creem-Regehr & Lee, 2005; Halari et al., 2006; Hayashi et al., 2007; Schöning et al., 2007; Kawamichi et al., 2007; Georgieva et al., 2008; Sarkheil et al., 2008; Chen et al., 2017; Uji et al., 2019), and b) dynamic videos including all types of dynamic videos and dots (n = 10 experiments: Paradis et al., 2008; Katsuyama et al., 2011; Freeman et al., 2012; Ogawa et al., 2013; Gaebler et al., 2014; Jastorff et al., 2016). The task paradigms were also categorized into two groups: a) passive viewing paradigms (n = 9 experiments: Creem-Regehr & Lee, 2005; Hayashi et al., 2007; Ogawa et al., 2013; Gaebler et al., 2014; Chen et al., 2017; Uji et al., 2019), and b) active judgment paradigms including all types of active judgment tasks such as depth judgment, recognition, detection, and mental rotation (n = 17 experiments: Taira et al., 2001; Halari et al., 2006; Schöning et al., 2007; Kawamichi et al., 2007; Georgieva et al., 2008; Sarkheil et al., 2008; Paradis et al., 2008; Katsuyama et al., 2011; Freeman et al., 2012; Jastorff et al., 2016).
Software and Analysis
The meta-analysis was performed using GingerALE software version 3.0.2 (http://brainmap.org/ale) to apply the activation likelihood estimation (ALE)
Table 1
Descriptive Information of the 26 Experiments that Were Included in This Meta-Analysis
First author, Year N M Age Handedness Stimuli Task Contrast Foci
Chen et. al„ 2017 20 10 19 24 (22.3) N/A Static Images Passive viewing Block design: 3D images > 2D images 6
20 10 Event-related design: 3D images > 2D images 2
Creem-Regehr & Lee, 2005 12 7 21 36 R Static Images Passive viewing Tool > scrambled Tool 10
12 7 Shape > scrambled Shape 1
Freeman et. al., 2012 8 5 24 36 N/A Dynamic Videos Judgment, task Event-related: cylindrical > flat. 2
8 5 Block-related: cylindrical > flat. 2
Gaebler et al., 2014 25 12 21-35 (26.7) R Dynamic Videos Passive viewing Component. 1: 3D videos > 2D videos 6
25 12 Component. 2: 3D videos > 2D videos 6
Georgieva et. al., 2008 18 8 20-33 (25) R Static Images Judgment, task/ Passive viewing Shape-from-t.ext.ure: 3D shape > 2D shape 14
18 8 Shape-from-shading: 3D shape > 2D shape 2
Halari et. al., 2006 9 9 20-30 (25.78) R Static Images Judgment, task Men: Rotation > No rotation (control) 6
10 - (24.9) Women: Rotation > No rotation (control) 6
Hayashi et al., 2007 10 4 19-23 N/A Static Images/objects Passive viewing Reversed prospective > 2D 5
Jastorffetal., 2016 21 10 19-29(23) R Dynamic Videos Judgment, task Main effect, kinematics 4
21 10 Main effect, configuration 6
Katsuyama et. al., 2011 31 21 19 32 (21.8) R Dynamic Videos Judgment, task/ Passive viewing Normal shadow > unusual shadow 1
31 21 Normal shadow > no shadow 6
Kawamichi et. al., 2007 12 12 18-33 R Static Images Judgment, task 3D rotation > 2D rotation 3
Table 1 (ending)
First author, Year N M Age Handedness Stimuli Task Contrast Foci
Ogawaet.al., 2013 16 4 21-39 (27.3) N/A Dynamic Videos Passive viewing EXP1: 3D > 2D 5
Paradis et. al„ 2008 10 5 21-28 R Dynamic Videos Judgment, task 3D motion transition (stimulus-driven): motion > form 7
Sarkheil et. al„ 2008 19 12 21-32 (24.8) N/A Static Images Judgment, task Motion > form 5
Schöning et. al„ 2007 12 12 (32 ± 5.63) R Static Images Judgment, task Males: mental rotation > passive viewing 30
12 - Early Follicular Females: mental rotation > passive viewing 34
12 - Midlut.eal Females: mental rotation > passive viewing 32
Taira et. al„ 2001 6 6 28 R Static Images Judgment, task St.ruct.ure-from-shading > Similar stimuli (control) 17
Ujiet.al., 2019 7 5 (23.8 ± 7.5) R Static Images Passive viewing St.ereopsis disparity > no-disparit.y 5
Note. N= sample size; M= number of male subjects; R= right, handed; NA= not available; EXP= experiment; 3D= three-dimensional; 2D= two-dimensional.
method that is a coordinate-based meta-analysis approach (Eickhoff et al., 2009; Turkeltaub et al., 2012; Eickhoff et al., 2017). This approach applies a likelihood estimation algorithm that compares coordinates compiled from multiple articles and estimates the magnitude of overlap, yielding clusters most likely to become active across studies. The algorithm minimizes within-group effects and provides increased power by allowing for the inclusion of all possible relevant experiments (Turkeltaub et al., 2012; Eickhoff et al., 2017). In this study, all the coordinates reported in the MNI format were converted to Talairach format using the tal2icbm transformation (Lancaster et al., 2007). GingerALE provides the final results and anatomical labels in the Talairach space. The significance level was assessed using a cluster-level family-wise error (FWE) threshold for multiple comparisons at p = .05 with a cluster-forming threshold set to p = 0.001 (Eickhoff et al., 2012; Eickhoff et al., 2017). To reach a maximal statistical power, it is recommended to use FWE thresholding and a minimum number of 17-20 experiments (Eickhoff et al., 2017).
The contrast analysis allows for identifying the common aspects (conjunction) and the differences (contrasts) between two meta-analyses. Two contrast analyses were performed to compare the thresholded ALE maps of a) active judgment task paradigms with passive viewing paradigms, and b) static images and dynamic video stimuli, as done in a previous meta-analysis (Zinchenko et al., 2018). The significance level of ALE maps was defined with the cluster-level FWE threshold for multiple comparisons at p = .05 with a cluster-forming threshold of p = .001. For the contrast analyses, uncorrected p = .01 threshold with 5000 permutations and a minimum volume of 50 mm3 were used in the next step. In this study, the activation map figures were prepared using Mango software v. 4.1 (Research Imaging Institute, http://rii.uthscsa.edu/mango).
Results
Main Analysis
The main analysis across all 26 experiments revealed six major significant clusters of activation associated with perceiving 3D compared to 2D (Figure 2; Table 2). The largest cluster was found in the left middle occipital gyrus and extended to the left cuneus (4,152 mm3). The second, third, and fourth biggest clusters were found in the right hemisphere, respectively, from the precuneus extended to the right middle occipital gyrus (2576 mm3), right fusiform gyrus (2,480 mm3), and right superior parietal lobule to the right precuneus (1416 mm3). Other clusters consisted of the left fusiform gyrus and the left declive of the cerebellum (1,024 mm3) and the left middle frontal gyrus extended to the left precentral gyrus (872 mm3).
Contrast Analyses
The thresholded ALE maps were calculated separately for the active judgment task paradigm (n = 17 experiments) and passive viewing paradigms (n = 9 experiments) in the course of perceiving 3D information. The results of the contrast
Table 2
The General Result of ALE Meta-Analysis: The Details of the Main Analysis Results Related to Perceiving 3D Information Based on Visual Depth Cues Across All the Studies
Cluster Regions BA Volume (mm3) Talairach ALE Score
x y Z
1 Left Middle Occipital Gyrus 18 4152 -32 -82 0 0.02357
Left Cuneus 19 -26 -78 24 0.02242
Left Cuneus 17 -24 -80 10 0.02217
Left Middle Occipital Gyrus 18 -38 -80 -10 0.01401
2 Right Precuneus 31 2576 24 -80 24 0.02129
Right Cuneus 17 24 -80 14 0.01927
Right Middle Occipital Gyrus 18 28 -84 0 0.01637
3 Right Fusiform Gyrus 19 2480 40 -64 -8 0.02490
Right Fusiform Gyrus 19 40 -76 -10 0.01810
4 Right Superior Parietal Lobule 7 1416 22 -58 56 0.01624
Right Superior Parietal Lobule 7 30 -64 48 0.01523
Right Precuneus 7 18 -64 50 0.01179
5 Left Declive - 1024 -44 -70 -16 0.01551
Left Fusiform Gyrus 37 -40 -62 -8 0.01304
6 Left Middle Frontal Gyrus 6 872 -22 -10 56 0.01855
Left Precentral Gyrus 6 -22 -18 60 0.01280
Note. BA= Brodmann area; ALE= Activation likelihood estimate.
Figure 2
ALE Map Shows Six Significant Clusters of Brain Areas That Are More Sensitive to Perceiving 3D Compared to 2D Across the Studies
Note. The cluster-level FWE for multiple comparisons at p = .05 with a cluster-forming p < .001. The color bar represents the ALE score related to levels of activation (0 < ALE Score < 0.025). P = posterior view; S= superior view; L = left view; R = right view
analyses are demonstrated in Figure 3. As revealed by conjunction analysis, these two paradigms have a small conjoint activity in the right fusiform gyrus (BA 37; 64 mm3). Contrasting active judgment versus passive viewing paradigms shows a greater activation in two clusters including left middle and inferior occipital gyri (BA 18; 912 mm3), and right precuneus (BA 7; 88 mm3). However, passive viewing shows greater activation in the left fusiform gyrus (BA 37; 120 mm3).
In the same vein, to perform a contrast analysis between static images (n = 16 experiments) and dynamic videos (n = 10 experiments), first, separate ALE analyses were run on the two datasets to examine for statistically significant differences. The results of this contrast analysis show a greater activation for the static images in the left declive and the fusiform gyrus (BA 19; 944 mm3) and right precuneus (BA 7; 80 mm3) than with the dynamic video stimuli (Figure 3). Surprisingly, the contrasting analysis did not find any cluster of activation associated with dynamic videos. Also, no common clusters survived the conjunction analysis between static and dynamic stimuli (Figure 3).
Figure 3
Brain Maps Show Significant Clusters of Activation in the Contrast Analyses S S
TiPCUh 1
•C
Note. a) The comparison of task paradigm types revealed: Blue = a common area of activation for all types of task paradigm in the right fusiform gyrus. Red = activation in the left middle and inferior occipital gyri and the right precuneus related to the active judgment task paradigm. Green = activation in the left fusiform gyrus related to the passive viewing paradigm. b) The comparison of types of stimuli revealed: Purple = activation in the left fusiform gyrus, left declive and right precuneus related to static image stimuli compared to dynamic video stimuli. LFG = left fusiform gyrus; RFG = right fusiform.
Discussion
This study used ALE meta-analyses to quantitatively examine the neural substrates that underlie perceiving 3D information based on visual cues in the human brain. This fMRI meta-analysis aimed to: a) identify specific regions of the brain that are most likely to be active during the processing of different depth cues in the course of perceiving 3D information across neuroimaging studies in this field, b) explore a map of functional brain activation associated with perceiving 3D within the brain areas which have received little attention in visual studies, and c) identify brain regions that are more sensitive to different types of visual stimuli and task paradigms.
The first hypothesis of this study predicted that perceiving 3D compared to 2D would elicit more activation in bilateral occipital areas, bilateral occipitotemporal areas, and parietal areas, all of which are associated with the processing of visual cues. The results of the main analysis support this hypothesis. These results suggest that these areas can become more active during the integrating process of depth cues and overlap in the course of different visual cues processing for perceiving 3D information (Welchman et al., 2005; Ban et al., 2012; for review, Welchman, 2016). Additionally, these results confirmed that many brain resources are allocated to the processing of 3D compared to 2D. In the following section, the functional role of these brain areas for processing depth cues associated with perceiving 3D information will be discussed.
Occipital areas
These early visual areas are involved in the processing of different depth cues such as binocular disparity (Backus et al., 2001; Tsao et al., 2003; Ogawa et al., 2013), and motion (Orban et al., 1999; Vanduffel et al., 2002; Klaver et al., 2008). The results of this meta-analysis showed broad sites of activation in bilateral occipital areas associated with the processing of different depth cues. The activity in these areas can be due to the concentration of cells that are sensitive to the disparity. This claim has been confirmed by Tsao et al. (2003). They compared disparity-related activity in humans and monkeys. Their results showed the highest disparity-related activities in V3A, V4d, V7, and some parts of IPS areas in the human dorsal stream. They found the V3A as a common disparity-related area for humans and monkeys. Moreover, the V3 and V3A areas have been linked to the shape extraction and detection of disparity edges and contours (Tsao et al., 2003; Chandrasekaran et al., 2007). It has been suggested that activities in V3, hMT+/V5 areas (match with the occipital activation in this study) can be related to the merging role of these areas for disparity information (Chandrasekaran et al., 2007). These early occipital areas can play an important role in merging the binocular disparity and shading (Dцvencio lu et al., 2013), binocular disparity and relative motion (Ban et al., 2012), and form and motion (Murray et al., 2003; Sarkheil et al., 2008).
Moreover, these early and midlevel visual areas play a crucial role in the extraction of depth from motion in both humans (Vanduffel et al., 2002; Kriegeskorte et
al., 2003; Klaver et al., 2008) and monkeys (Vanduffel et al., 2001, 2002; Orban et al., 2004). However, there are differences in activity in the V3A areas related to processing of motion in these two species. Vanduffel et al. (2002) reported that only humans show V3A and intraparietal cortex activation associated with the processing of structure from motion, whereas these areas are not sensitive in monkeys. The lack of sensitivity in monkeys can be due to the existence of an additional motion processing network in humans within the V3A and intraparietal areas. Human studies showed that these areas are sensitive to motion and stereo contours (Tyler et al., 2006) and are involved in integrating shape contours and motion cues (Murray et al., 2003). These findings together with the results of this meta-analysis study suggest that the bilateral occipital regions can play an important role as the primary depth representation center (Welchman et al., 2005; Tyler et al., 2006).
Occipitotemporal areas
These areas are known for their involvement in the high-level visual perception in humans including the processing of face and body (McCarthy et al., 1997; Haxby et al., 2000; Schwarzlose et al., 2005), and object recognition (Bar et al., 2001; Grill-Spector et al., 2001; Grill-Spector, 2003). This meta-analysis study found bilateral activation linked to perceiving 3D information within the ventral stream, specifically fusiform gyri. This result suggests that these occipitotemporal ventral areas are involved in the perception process of 3D from different visual depth cues. The functional role of these areas in 3D shape perception from depth cues has been confirmed in both humans and monkeys (Bradley et al., 1998; Vanduffel et al., 2001, 2002; Tsao et al., 2003; Welchman, 2016). It has been shown that bilateral activations in inferior temporal gyri are associated with processing the 3D structure of a surface based on both texture and shading cues (Georgieva et al., 2008; Peuskens et al., 2004; Taira et al., 2001). The occipitotemporal areas involved in perceiving 3D from shading and texture largely overlap with those from motion (Orban et al., 1999; Vanduffel et al., 2002), and disparity effect (Iwami et al., 2002; Georgieva et al., 2009). As expected from the monkey studies (Bradley et al., 1998; Vanduffel et al., 2002), the human studies show a higher activation level for the perception of 3D structure from motion in MT/V5 (hMT/V5), and lateral occipital areas (Orban et al., 1999; Murray et al., 2003). The lesion studies of humans confirmed that patients with damage to these areas have problems with the perception of motion (Zihl et al., 1983; Newsome & Pare, 1988). However, this activation can mostly be due to the interaction of motion and stereo stimuli. Studies using dynamic stereo stimuli have revealed a broad range of activation in the superior, middle, and inferior temporal areas for 3D dynamic compared to the 2D stimuli (Iwami et al., 2002; Gaebler et al., 2014), whereas it has been shown that the static stereo stimuli activate only some part of the inferior temporal gyrus (Georgieva et al., 2009). Accordingly, these results suggest that the occipitotempo-ral areas can play a role in the combining process of the depth cues for perceiving 3D information.
Parietal areas
A growing body of evidence suggests that parietal areas, specifically intraparietal and superior parietal areas, are involved in the processing of different depth cues including binocular disparity, motion, and texture (Vanduffel et al., 2002; Iwami et al., 2002; Georgieva et al., 2008; Durand et al., 2009). Due to the remarkable expansion of intraparietal areas in humans in comparison with monkeys (Orban et al., 2004), humans' and primates' studies showed differences in activation for depth cues within these areas. It has been suggested that only a small area in the intraparietal sulcus of monkeys (specifically, VIP) is sensitive to motion (Vanduffel et al., 2001; Orban et al., 2004), while humans neuroimaging studies suggest a more extended activation during processing motion in these areas (Orban et al., 1999; Vanduffel et al., 2002; Murray et al., 2003). Moreover, these parietal areas can play a role in extracting 3D shape representation to support motor functions as suggested by Buckthought & Mendola (2011). Lesions to these areas may lead to impairment in the 3D perception ability (Carmon & Bechtoldt, 1969; Schaadt et al., 2015).
Other significant areas
In line with the second hypothesis, the results of this meta-analysis found activation in frontal areas and the cerebellar declive related to perceiving 3D information. The foci of activation in the frontal cortex were located in the left middle frontal and precentral gyri. These areas in the frontal cortex are known for their role in attention modulation (Kastner & Ungerleider, 2000; Corbetta & Shulman, 2002), and processing motion (Paradis et al., 2008; Sarkheil et al., 2008). Furthermore, studies have revealed mental rotation-related activities in these frontal areas (Halari et al., 2006; Schöning et al., 2007). However, these activities can be associated with the attentional system (Cohen et al., 1996).
Moreover, this study found activation in the cerebellar declive associated with perceiving 3D information. Interestingly, only one study has been found to mention the role of the declive in perceiving 3D stimuli compared to 2D stimuli (Dores et al., 2013). This area has received little attention from neuroimaging studies into visual perception despite its role in attention (Courchesne et al., 1994; Haarmeier & Their, 2007), and motion (Glickstein, 2007; Becker-Bense et al., 2012). Moreover, the activation of the cerebellum declive can be due to its involvement in the saccadic eye movements (Stephan et al., 2002; Mottolese et al., 2013). Note that visual depth cues such as binocular disparity can modify basic eye movement properties (Jansen et al., 2009).
Task paradigm
As to the third hypothesis regarding task paradigms, the results of the contrast analysis for the task paradigm partially confirmed the hypothesis. The results showed clusters of activation within the left hemisphere of occipital areas and right
hemisphere of parietal areas associated with different types of active judgment tasks including depth perception, mental rotation, recognition, and discrimination tasks. These activations can be due to the involvement of these areas in the processing of 3D mental rotation tasks (Alivisatos & Petrides, 1997; Kawamichi et al., 2007). The mental rotation-related activations within the parietal areas have been attributed to the visual attention process (Cohen et al., 1996; Vandenberghe et al., 1997). These activations can result from the higher level of information processing and required attention associated with the difficulty of 3D mental rotation tasks (Cohen et al., 1996; Kawamichi et al., 2007). Moreover, parietal activation has been found during discrimination tasks (Claeys et al., 2004; Georgieva et al., 2008). This effect can be due to the sensory-motor processing of the decision-making during the discrimination task (Georgieva et al., 2008).
Additionally, this meta-analysis found a higher level of activation in the left fusiform gyrus for passive viewing paradigms compared to active judgment paradigms, and a higher level of activation in the right fusiform gyrus across both active and passive task paradigms. The bilateral activation in fusiform areas during passive viewing paradigms has been shown in previous findings (Farah & Aguirre, 1999; Creem-Regehr & Lee, 2005). However, the fusiform is sensitive to both active and passive task paradigms (Orban et al., 1997). This sensitivity suggests that these areas are recruited for the semantic processing of different types of stimuli regardless of the paradigms (Joseph, 2001).
Stimuli type
The second part of the third hypothesis predicted a higher activation level for dynamic video stimuli than static image stimuli in motion-sensitive areas. Surprisingly, the results of the stimuli contrast analysis did not find any activation associated with dynamic videos. The lack of activation for dynamic stimuli in motion processing-related areas is difficult to interpret. One possible explanation can be the type of stimuli. Note that the activation in motion processing-related areas is highly determined by the nature of the motion stimuli (Murray et al., 2003). A study by Klaver et al. (2008) reported different patterns of brain activation for structure-from-motion and random motion conditions. Interestingly, they did not find any activation in motion processing-related areas associated with the structure-from-motion condition. The lack of activation for dynamic stimuli needs further investigation in future studies. Moreover, this meta-analysis found activation in left fusiform areas and right parietal areas related to static image stimuli. This activation can be due to the involvement of this area in the integration of 3D shape information. Previous studies have shown that this area is sensitive to the binding of the features of scenes and objects (Schoenfeld et al., 2003; Goh et al., 2004).
Conclusion and limitation
This meta-analysis for the first time provides a concordant map of activation for perceiving 3D information based on visual depth cues across whole-brain neuroimaging
studies. This investigation yields six major clusters in occipital, temporal, parietal, and frontal areas that are more active during the processing of different visual cues and integrating depth cues in the course of perceiving 3D information. The observed findings suggest that perceiving 3D requires increased resources of the brain. One primary limitation of this study is the small number of studies that use the whole-brain analysis. The majority of neuroimaging studies of the 3D perception field have devoted their analyses to specific brain areas. This might potentially lead researchers to inaccurate results and interpretations of such results.
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