Received: 15 May 2019 | Revised: 9 September 2019 | Accepted: 10 September 2019 DOI: 10.1002/brb3.1427 ORIGINAL RESEARCH Brain activity during traditional textbook and audiovisual‐3D learning Jesus Pujol1,2 | Laura Blanco‐Hinojo1,2 | Gerard Martínez‐Vilavella1 | Lucila Canu‐Martín1 | Anna Pujol1 | Víctor Pérez‐Sola2,3 | Joan Deus1,4 1 MRI Research Unit, Department of Radiology, Hospital del Mar, Barcelona, Abstract Spain Introduction: Audiovisual educational tools have increasingly been used during the 2 Centro Investigación Biomédica en Red de past years to complement and compete with traditional textbooks. However, little Salud Mental, CIBERSAM G21, Barcelona, Spain is known as to how the brain processes didactic information presented in different 3 Institute of Neuropsychiatry and formats. We directly assessed brain activity during learning using both traditional Addictions, Hospital del Mar, IMIM, Barcelona, Spain textbook and audiovisual‐3D material. 4 Department of Psychobiology Methods: A homogeneous sample of 30 young adults with active study habits was and Methodology in Health assessed. Educational material on the subject of Cardiology was adapted to be pre‐ Sciences, Autonomous University of Barcelona, Barcelona, Spain sented during the acquisition of functional MRI. Results: When tested after image acquisition, participants obtained similar exami‐ Correspondence Jesus Pujol, MRI Department, Hospital nation scores for both formats. Evoked brain activity was robust during both tradi‐ del Mar, Passeig Marítim 25‐29, Barcelona tional textbook and audiovisual‐3D lessons, but a greater number of brain systems 08003, Spain. Email: 21404jpn@comb.cat were implicated in the processing of audiovisual‐3D information, consistent with its multisource sensory nature. However, learning was not associated with group mean Funding information Instituto de Salud Carlos III, Grant/Award brain activations, but was instead predicted by distinct functional MRI signal changes Number: C1589923 ; 3D Tech Omega Zeta, in the frontal lobes and showed distinct cognitive correlates. In the audiovisual‐3D Barcelona version, examination scores were positively correlated with late‐evoked prefrontal cortex activity and working memory, and negatively correlated with language‐related frontal areas and verbal memory. As for the traditional textbook version, the fewer results obtained suggested the opposite pattern, with examination scores negatively correlating with prefrontal cortex activity evoked during the lesson. Conclusions: Overall, the results indicate that a similar level of knowledge may be achieved via different cognitive strategies. In our experiment, audiovisual learning appeared to benefit from prefrontal executive resources (as opposed to memorizing verbal information) more than traditional textbook learning. KEYWORDS education, functional MRI, learning, memory, prefrontal cortex This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc. Brain and Behavior. 2019;9:e01427.  wileyonlinelibrary.com/journal/brb3 | 1 of 13 https://doi.org/10.1002/brb3.1427 2 of 13 | PUJOL et al. 1 | I NTRO D U C TI O N According to outstanding conceptions on the neural bases of learning (Fuster, 2001; Miller & Cohen, 2001; Shallice & Cipolotti, Audiovisual educational tools have increasingly been used during 2018; Wager & Smith, 2003; Wood & Grafman, 2003), we hypoth‐ the past years to complement and compete with traditional text‐ esized that knowledge acquisition would significantly depend on books (Jarvin, 2015; Lewis, 2003; Prakash, Muthuraman, & Anand, the participation of prefrontal lobe structures. Thus, individual dif‐ 2017; Trelease, 2016). However, little is known as to how the brain ferences in examination scores would correspond to a different in‐ processes didactic information presented in different formats. volvement of the prefrontal cortex controlling executive resources Some work has been done to characterize the differences in the during learning. A selection of cognitive tests was also used to evoked brain response to verbal information presented visually or characterize adopted cognitive learning strategies. The assessed aurally (e.g., Buchweitz, Mason, Tomitch, & Just, 2009; Venezia et cognitive domains included working memory, verbal memory, vi‐ al., 2017), and a recent study has explicitly compared brain activ‐ sual memory, incidental visual memory, vocabulary, and cognitive ity during the viewing of complex scenes (movies) and reading its processing speed. screenplay text (scripts) (Tikka, Kauttonen, & Hlushchuk, 2018). Nevertheless, there are no studies directly investigating brain ac‐ 2 | M E TH O DS tivity predicting the learning achieved during both audiovisual and text lessons. 2.1 | Study participants We used functional MRI (fMRI) to assess brain activity during lesson learning in a homogeneous sample of young adults with ac‐ The final study sample involved a total of 30 university students, tive study habits. Educational material on the subject of Cardiology all of whom were studying their final year of Psychology or a post‐ was adapted for presentation within the constrictions of the MRI ex‐ graduate Psychology master. The selected group was therefore perimental environment. The traditional textbook task involved the maximally homogeneous in terms of learning capabilities. The visual presentation of text and high‐quality illustrations. In the audio‐ group included 15 men and 15 women with a mean (±SD) age of visual version, identical verbal information was presented via audio, 24.2 (±3.9) years, range 21–39 years. Participants were not paid for and visual stimuli involved a dynamic 3D illustration of the presented their contribution. educational concepts. The study was conducted in accordance with the principles ex‐ We firstly aimed to identify differences in evoked brain ac‐ pressed in the Declaration of Helsinki. The protocol was approved tivity between both traditional textbook and audiovisual‐3D ver‐ by the Autonomous University of Barcelona's Ethics Commission sions. We presumed that, as a group effect, the audiovisual‐3D on Animal and Human Experimentation (CEEAH: 4217). Written in‐ format would be able to capture a greater variety of brain ele‐ formed consent was obtained from all participants. ments due to its multisource sensory nature. Nevertheless, brain group activations may not accurately reflect the neural correlates 2.2 | The learning stimuli of learning (Foulkes & Blakemore, 2018; Friedman & Miyake, 2017; Seghier & Price, 2018), to the extent that large individ‐ The lessons to be learned were based on the subject of Cardiology, ual differences typically exist in learning complex information with which the Psychology students were unfamiliar. Two similarly (Jonassen & Grabowski, 1993). Therefore, a correlation analysis structured lessons were devised, based on coronary arteries and was also conducted with the aim of specifically identifying brain heart valves. Both lessons were adapted to traditional textbook and activity predicting acquired knowledge measured by a multiple‐ audiovisual‐3D formats. The duration of the lessons was 3 m and choice examination. 14 s, and each (coronary arteries and heart valves in both traditional F I G U R E 1 Illustration of the stimuli presented during the fMRI experiment for the audiovisual‐3D format, coronary artery content. The paradigm involved a baseline condition with six point‐fixation blocks and a test condition with six blocks each presenting a lesson fragment. An identical presentation sequence was used for the traditional textbook format PUJOL et al. | 3 of 13 textbook and audiovisual‐3D formats) was segmented into six frag‐ presentation by the examiner. The overall age‐appropriate normed ments of 26–36 s. Lessons in traditional textbook format were (i.e., standardized to have a mean of 10 and a standard deviation of presented using PowerPoint (PPT) slides, whilst the audiovisual‐ 3) score, combining forward and backward performance, was used 3D version was displayed in a movie format. In each case, the six in our analyses. fragments were presented interleaved with a baseline condition, in which a green fixation point was presented for 20 s. Therefore, 2.4.2 | Verbal memory the experiment involved two fMRI runs of 5 m and 14 s (traditional textbook and audiovisual‐3D presented in a counterbalanced order), The classic Verbal Paired Associates test from the Wechsler each including a baseline condition with six point‐fixation blocks al‐ Memory Scale (Wechsler, 1987) was used. The test evaluates ternated with six test‐condition blocks presenting a lesson fragment verbal memory for associated word pairs. After 10 word pairs are (Figure 1). The Videos S1 and S2 (mp4 files), show a fragment of the read to the participant, the first word of each pair is then read coronary artery lesson in both textbook and audiovisual formats. and the subject is requested to provide the corresponding associ‐ All the didactic material was developed in 3D Tech Omega Zeta SL ated word. The test involves three trials based on the same list (Barcelona, Spain) by personnel specialized in developing 3D educa‐ presented in different order. Age‐appropriate normed scores were tional platforms. used. 2.3 | Procedure 2.4.3 | Visual memory Participants were previously given instructions concerning fMRI The Visual Reproduction subtest from the Wechsler Memory Scale testing procedures and the need to remain still during the acquisi‐ (Wechsler, 1987) was used. In this test, a series of three geometric tion. They were specifically requested to try and understand the di‐ pictures of increasing complexity is shown, one at a time, for 10 s dactic material and not simply memorize the presented items. Each each. Immediately after the presentation of each picture, the par‐ participant received one lesson (coronary arteries or heart valves) ticipant is asked to draw it from memory. Each picture is scored by in the traditional textbook format and another (coronary arteries adding up the number of correctly reproduced image components. or heart valves) in the audiovisual‐3D format. Therefore, each par‐ Age‐appropriate normed scores were used. ticipant was exposed to both formats, but the lesson presented was always different. The order of both format (traditional textbook or 2.4.4 | Processing speed and incidental audiovisual‐3D) and topic (coronary arteries or heart valves) was visual memory fully counterbalanced across participants with a pseudorandom allocation. The Digit Symbol subtest of the Wechsler Adult Intelligence Scale Following the fMRI scans, knowledge acquisition was assessed (WAIS) was used as a conventional measure of speed in visuopercep‐ in each participant by means of a multiple‐choice test including 10 tive processing (Wechsler, 2008). The participant is required to copy (in questions on each topic. As an interference task between the fMRI the spaces provided below the rows of numbers) the symbols matching and the examination, the participants were required to read a text each number on the basis of a key located at the top of the page. The (two stories from the Wechsler Memory Scale, 1987). The time participant is given a total of 120 s to copy the symbols as quickly as elapsed between the presentation of the Cardiology lessons and the possible. The number of correct symbols, depicted within the allotted formal examination ranged from 25 to 35 m. time, was measured and subsequently converted into normed scores. In addition, a 101‐point numerical rating scale (NRS) was used The Digit Symbol test also served to measure Incidental Visual for the participants to rate the extent to which the presented di‐ Memory, using the form Digit Symbol—Incidental Learning, pairing dactic material was enjoyable, for both formats. The participants procedure. Immediately after the Digit Symbol test, the participant were also required to express their preference for either the tradi‐ is required to complete two series of Digit Symbol items with not ac‐ tional format or the audiovisual format. Finally, the selected cog‐ cess to the code key. The participants are never informed that their nitive tests were administered in a single session the same day of memory would be tested. Direct scores (i.e., the number of com‐ the MRI experiment. pleted items) were converted into percentile scores. 2.4 | Selected cognitive assessment 2.4.5 | Vocabulary The Vocabulary subtest of the Wechsler Adult Intelligence Scale 2.4.1 | Working memory (WAIS) was used (Wechsler, 2008). The participant is required to de‐ The Digit Span subtest of the Wechsler Adult Intelligence Scale fine up to 30 words of increasing difficulty presented orally by the (WAIS) was used as a conventional measure of working memory examiner. This test assesses both language and retrieval of informa‐ (Wechsler, 2008). In this test, the participant is required to repeat tion from long‐term memory. Direct scores (from 0 to 2 points for digits forward and backward in order, immediately after their oral each word) were converted into normed scores. 4 of 13 | PUJOL et al. quality to flag volumes of suspect quality across the run. At points 2.5 | Functional MRI with interframe motion >0.2 mm, we discarded the corresponding volume, together with the preceding volume, and the two succeed‐ 2.5.1 | Functional MRI acquisition ing volumes. Using this procedure, a mean of 2.7 (1%) volumes (range A Philips Achieva 3.0 Tesla magnet (Philips Healthcare), equipped 0–20) was removed from the total of 314 analyzed combining the with an eight‐channel phased‐array head coil and single‐shot two functional MRI sequences obtained in each participant. echoplanar imaging (EPI) software, was used for the MRI assess‐ ment. Stimuli were presented using MRI‐compatible high‐resolution 2.6 | Statistical analysis goggles and audio system (VisuaStim Digital System, Resonance Technology Inc.). Our stimuli presentation system did not include 2.6.1 | Behavioral data the “MR eye tracking” option. Functional sequences consisted of gradient recalled acquisition in Paired Student's t test was used to compare mean differences within the steady state (time of repetition [TR], 2,000 ms; time of echo [TE], the study group in terms of behavioral ratings. A chi‐squared test 35 ms; pulse angle, 70°) within a field of view of 240 × 240 × 128 mm, was used to assess the relationships between categorical variables. with a 64 × 64‐pixel matrix, and a slice thickness of 4 mm (interslice Pearson's product–moment correlations were used to test the as‐ gap, 0 mm) and acquisition voxel size of 3.75 × 3.75 × 4 mm. A total sociation between the participants' examination scores and perfor‐ of 32 interleaved slices were acquired to cover the whole brain. Each mance in cognitive testing. Multiple regression analysis was used to functional time series consisted of 157 consecutive image sets or predict examination scores with a combination of variables including volumes obtained over 5 m and 14 s. The first four (additional) image cognitive testing and extracted measures of brain activity in regions sets in each run were discarded to allow the magnetization to reach of interest (i.e., frontal lobe regions showing significant correlation equilibrium. High‐resolution anatomical images were additionally with examination scores; see below). obtained using a sagittal T1‐weighted three‐dimensional fast spoiled gradient (SPGR) sequence. A total of 160 slices were acquired with 2.6.2 | Functional MRI data repetition time = 8.1 ms; echo time = 3.7 ms; flip angle = 8°, field of view = 240 × 240 × 160 mm; matrix size 256 × 256 pixels, in‐plane To obtain individual maps of brain activity evoked during lesson 2 resolution = 0.94 × 0.94 mm ; and slice thickness = 1 mm. presentation, a boxcar regressor was generated considering the six blocks of the baseline condition and the six blocks of the test Image preprocessing condition and applying a hemodynamic delay of 4 s. The contrasts Imaging data were processed using MATLAB version 2016a (The “baseline < test condition” (activation) and “baseline > test condition” MathWorks Inc) and Statistical Parametric Mapping software (deactivation) were estimated for each participant. The resulting (SPM12; The Wellcome Department of Imaging Neuroscience). first‐level SPM contrast images were carried forward to group‐level Preprocessing involved motion correction, spatial normalization, random‐effects analyses. One‐sample t test designs were used to and smoothing by means of a Gaussian filter (full‐width half‐maxi‐ generate group activation maps. Paired t tests were used to compare mum, 8 mm). Data were normalized to the standard SPM‐EPI brain activity evoked during learning using both traditional textbook template and resliced to 2 mm isotropic resolution in Montreal and audiovisual‐3D formats. Neurological Institute (MNI) space. All image sequences were in‐ In addition, voxel‐wise linear regression was used to test the spected for potential acquisition and normalization artifacts. At association between examinations scores and evoked brain activity this stage, two participants were removed from an initial broader in the corresponding experiment (i.e., separately for the traditional sample of 34 subjects as a result of air/bone‐related magnetic sus‐ textbook format and the audiovisual‐3D format). The results from ceptibility artifacts, a third participant due to excessive motion this correlation analysis were reported in terms of both t‐values (mean interscan motion of 1.9 mm), and a fourth subject showing (SPM default) and Pearson's r‐values (t = r∕ 1 − r2 ∕n − 2). A primary √ incidental MRI findings (white matter hypersignal intensities). analysis tested the correlation with brain activity evoked during the entire lesson. Further analyses tested the correlation at four dif‐ Control of potential head motion effects ferent periods of 6 s (three frames), using data from the beginning, To control for the effects of head motion, we adopted the follow‐ middle, and end of each lesson fragment and immediately (no time ing approach: (a) time series were aligned to the first image volume lap) after the lesson fragment. Data from regions showing significant in each participant using a least squares minimization and a 6‐pa‐ correlation with examination scores were extracted for plotting pur‐ rameter (rigid body) spatial transformation. (b) Six motion‐related poses and to carry out seed analyses to identify co‐activated brain regressors and their six derivatives were included in the first‐level networks. (single‐subject) analysis. (c) Within‐subject, censoring‐based MRI signal artifact removal (scrubbing) (Power et al., 2014) was used to Seed analyses discard motion‐affected volumes. For each participant, interframe As in our previous studies (Pujol et al., 2019, 2016), the seed region motion measurements (Pujol et al., 2014) served as an index of data was defined as a 3.5‐mm radial sphere (sampling ~ 25 voxels in 2 mm PUJOL et al. | 5 of 13 isotropic space) centered in each identified brain region. This was per‐ “Would you use the 3D video format to complement the traditional formed using MarsBaR region of interest (ROI) toolbox in MNI stereo‐ method of study?” In the event of compulsory expression of prefer‐ taxic space. Signals of interest were extracted by calculating the mean ence, 21 of the 30 participants would choose the video format and ROI value at each time point across the time series. To generate the nine the traditional textbook format for the future (χ21,N = 30 = 4.8; seed maps, the signal time course of a selected seed region was used p = .028). as a regressor to be correlated with the signal time course of each brain voxel to generate individual voxel‐wise statistical parametric 3.1.2 | Objective evaluation maps of co‐activated regions. A high‐pass filter set at 128 s was used to remove low‐frequency drifts below ~0.008 Hz. In addition, we de‐ Despite format preferences, the achieved learning was similar fol‐ rived estimates of white matter, CSF, global brain signal fluctuations, lowing both lessons. In the 10‐question examinations, the partici‐ and 12 motion‐related regressors to be included in the analyses as pants’ correct answer mean was 6.1 (SD, 2.3 and range, 1–10) when nuisance variables. The first level of our statistical analysis, therefore, the didactic information was presented using the audiovisual‐3D involved the generation of single‐subject brain maps expressed as format and 5.9 (SD, 1.8 and range 3–9) when using the traditional beta regression estimates. Single‐subject voxel‐wise functional con‐ textbook format. The difference was not statistically significant nectivity maps were then included in second‐level (group) random‐ef‐ t29 = 0.8, and p = .752). Noteworthy are the participants' wide exami‐ fects analyses to test for group effects (one‐sample t tests). nation score ranges denoting large individual differences in lesson learning. Thresholding criteria Regarding the participants' poor success rate, three questions In whole‐brain analyses, clusters >1.26 ml (158 voxels) at a height were identified as highly difficult (i.e., correct answers < 15% when threshold of p < .005 were considered, which satisfied the family‐ presented using the traditional textbook format). Interestingly, when wise error (FWE) rate correction of pFWE < .05, according to Monte considering only such highly difficult questions (questions 1, 2, and 9 Carlo simulations. In analyses within the frontal lobe, the corre‐ of the heart valve examination), better examination outcomes were sponding cluster size considered was 0.94 ml (118 voxels). obtained with the audiovisual‐3D format (33% of correct answers) than with the traditional textbook format (12% correct answers), with t29 = 2.4 and p = .024. 3 | R E S U LT S 3.1 | Behavioral results 3.1.3 | Cognitive testing Table 1 reports the participants' performance in selected memory and 3.1.1 | Subjective evaluation cognitive tests and the pattern of correlations with their scores on The audiovisual‐3D format was considered by the participants to be learning Cardiology lessons. Examination scores for lessons presented significantly more enjoyable than the traditional textbook format with the audiovisual‐3D format positively correlated with working (group mean score ± SD; 88.3 ± 10.9 vs. 69.3 ± 19.3; t29 = 5.0, and memory and negatively correlated with verbal memory. Significantly, p = .00003). All 30 participants (100%) answered “yes” to the question working memory and verbal memory performance jointly explained TA B L E 1 Cognitive testing (N = 30) Correlation with examination scores Performance Audiovisual‐3D Traditional Textbook Mean ± SD r (p) r (p) Working memory (nor‐ 9.8 ± 2.5 .43 (.019) −.14 (.468) med scores) Verbal memory (normed 12.3 ± 1.6 −.42 (.020) .34 (.066) scores) Visual memory (normed 12.1 ± 1.5 .33 (.077) −.04 (.851) scores) Incidental visual memory 60.2 ± 29.9 −.12 (.514) .13 (.487) (percentiles) Vocabulary (normed 14.2 ± 2.3 .04 (.831) .22 (.242) scores) Processing speed (normed 11.5 ± 2.4 .13 (.482) −.11 (.561) scores) Note: Degrees of freedom (df), 28. Significant p values are indicated in bold font. 6 of 13 | PUJOL et al. 24% of the audiovisual‐3D examination score variance when included the traditional textbook lesson, the strongest activations were 2 in a multiple regression analysis (Multiple R = 0.54, r = 0.30, adjusted identified in the ventral and dorsal aspects of the visual cortex, hip‐ r2 = 0.24, F2,27 = 5.6, p = .009). Figure 2 illustrates such an association pocampi, and dorsal parietal association cortex including the intra‐ between memory domains and audiovisual examination scores. parietal sulci, frontal eye fields, and left premotor cortex extending to Broca's area and Wernicke's area. During the audiovisual‐3D lesson, all these brain regions were 3.2 | Imaging results also activated (Figure 3, Figure S1 and Table S2), but the changes were more extensive and additionally involved other areas. Direct 3.2.1 | Brain activation comparison between both data sets indeed showed significantly Brain activation was robust in both experiments (Figure 3 and Table higher activation during the audiovisual‐3D lesson in the audi‐ S1), which otherwise showed highly significant differences. During tory cortex and related areas of the temporal lobe, ventral aspect F I G U R E 2 Plots showing the associations between examination scores from lessons presented with the audiovisual‐3D format and memory performance PUJOL et al. | 7 of 13 F I G U R E 3 Group activation results (one‐sample t tests) for both traditional textbook and audiovisual‐3D lessons F I G U R E 4 Deactivated brain areas during textbook and audiovisual‐3D lessons of the occipito‐temporal cortex, supramarginal gyrus/parietal 3.2.2 | Deactivation pattern opercular region, and right frontal cortex (Figure 3, Figure S2 and Table S2). The analysis of brain deactivations (i.e., higher activity during baseline In the opposite contrast, activation during the traditional text‐ than test condition) also showed robust group results (Figure 4 and book lesson showed significantly higher activation in the primary Table S3). In both experiments, the pattern was dominated by changes visual cortex at the occipital pole, right prefrontal cortex in the mid‐ in the dorsolateral prefrontal cortex, inferior parietal lobule (involving dle frontal gyrus, supplementary motor area, and cerebellar vermis both the angular and supramarginal gyri), and brain medial wall struc‐ (Figure S2 and Table S2). tures (medial frontal and posterior cingulate cortex). 8 of 13 | PUJOL et al. F I G U R E 5 Correlation between audiovisual‐3D examination scores and brain activity during audiovisual‐3D lessons (left panels). The central panels illustrate the network of regions (seed analyses) co‐activated with the identified frontal regions. The right panels show how the regions co‐activated with the left dorsal prefrontal region overlap (yellow) with deactivated brain areas, and the regions co‐activated with the left ventral frontal region overlap (yellow) with activated brain areas. Numbers indicate MNI coordinates the left ventral frontal region adjacent to Broca's area network 3.2.3 | Correlation analysis—Audiovisual‐3D lesson mostly overlap with activated regions. Therefore, higher exam‐ Examination scores for the lessons presented with the audiovisual‐ ination scores are seen to be achieved by participants capable 3D format showed a dual pattern of correlations with fMRI signal of recruiting, as opposed to deactivating, the prefrontal cortex changes evoked during exposure to stimuli (Figure 5). Specifically, during the lesson. This is evident in the plots (Figure 6), where all brain activity in a left dorsal prefrontal region predicted higher ex‐ participants activating this region showed examination scores ≥5. amination scores, whilst brain activity in a left ventral frontal region Also, higher scores corresponded to individuals with less Broca's adjacent to Broca's area predicted lower scores (see also Table S4). area activation, as examination scores negatively correlated with That is, examination scores increases as dorsal prefrontal activation activity in this region. increases and ventral frontal activation decreases. These two op‐ To this end, we observed that the audiovisual presentation of posite effects were independent and complementary in accounting educational material generated an extensive and robust pattern for examination scores (Figure 6). That is, in a multiple regression of activation that did not, however, positively predict examination analysis both imaging variables jointly explained 57% of audiovisual scores. Examination success was instead associated with fMRI signal examination score variance (multiple R = 0.77, r2 = 0.60, adjusted changes in circumscribed frontal areas. r2 = 0.57, F2,27 = 20.1, p = .000005). To characterize the temporal evolution of the learning process, To illustrate the meaning of the identified associations, we we further analyzed the correlation with examination scores at four mapped the networks of regions co‐activated with the frontal re‐ different times (beginning, middle, end of each lesson fragment, and gions showing positive and negative correlations with examination immediately after the lesson fragment). Significant correlations were scores (seed analyses). Overlapping displays (Figure 5) interest‐ observed only upon completion of and after the lesson. During the ingly show that the regions co‐activated with the left dorsal pre‐ final period, brain activity in the left dorsal prefrontal cortex once frontal region during the audiovisual‐3D lesson correspond mostly again predicted higher examination scores (Table S4). However, the to deactivated brain areas. By contrast, regions co‐activated with most extensive correlation findings were observed after the lesson, PUJOL et al. | 9 of 13 F I G U R E 6 Plots showing the associations between examination scores from lessons presented with the audiovisual‐3D format and brain activity in frontal areas once the audiovisual stimuli were no longer present, and involved 4 | D I S CU S S I O N ventral prefrontal cortex bilaterally and the left sensorimotor cortex (Figure 7 and Table S4). Educational medical topics were adapted to be presented in both traditional textbook and audiovisual‐3D lesson formats. On the basis of the test scores, students gained a similar level of knowl‐ 3.2.4 | Correlation analysis—Traditional textbook edge in both formats. Imaging results, however, interestingly Examination scores in lessons presented with the traditional textbook suggest that similar learning may be obtained via different brain format showed a negative correlation with fMRI signal change in a right resources. Evoked brain activity was robust during both the tra‐ dorsal prefrontal region (Figure 8). This correlation interestingly shows ditional textbook and audiovisual‐3D lessons, but a larger number the opposite direction to the association observed in the audiovisual‐ of brain systems were implicated in the processing of audiovisual‐ 3D analysis, which would further support the adoption of different 3D information, consistent with its multisensory nature and higher mechanisms for learning material presented in different formats. The stimulus complexity. Significantly, learning was not associated temporal analysis showed a significant association between examina‐ with group mean brain activations, but was instead predicted by tion scores and signal changes in this right dorsal prefrontal region only distinct fMRI signal changes in the frontal lobes. In the audiovis‐ in the middle period (Table S4). ual‐3D version, examination scores positively correlated with late 10 of 13 | PUJOL et al. F I G U R E 7 Correlation between audiovisual‐3D examination scores and brain activity immediately after exposure to audiovisual‐3D material F I G U R E 8 Correlation between traditional textbook scores and brain activity during traditional textbook lessons (left panel). The central panel illustrates the network of regions (seed analysis) co‐activated with the identified frontal region. The right panel shows the association between examination scores and brain activity in the frontal area. Numbers indicate MNI coordinates prefrontal cortex activity and working memory, and correlated particularly involving the superior temporal sulcus likely reflecting negatively with language‐related frontal areas and verbal memory. multisensory integration (Beauchamp, Yasar, Frye, & Ro, 2008), In the traditional textbook version, the fewer results recorded the lateral aspect of the occipito‐temporal cortex subserving com‐ suggested the opposite pattern. plex visual processes and motion perception (Lingnau & Downing, During traditional textbook learning, the identified pattern 2015), the supramarginal gyrus/parietal opercular region criti‐ of brain activation accurately reflected the expected changes cal to cross‐modal abstractions and spatial cognition (Leichnetz, for natural reading and verbal information encoding (Choi, Desai, 2011), and right frontal cortex. Paradoxically, the larger number & Henderson, 2014; Schuster, Hawelka, Hutzler, Kronbichler, & of brain resources employed to process more complex audiovisual Richlan, 2016; Wandell & Le, 2017), with activation of the visual information was not necessarily associated with greater learning, cortex, hippocampi, frontal eye fields, intraparietal sulci, Broca's as, indeed, our participants actually obtained similar examination area, and Wernicke's area. In addition, strong activation was scores with both formats. identified in both the ventral and dorsal visual streams, which is The issue of stimulus complexity in encoding information has consistent with neural operations related to processing object previously been discussed in the context of advertising. Some features and spatial relationships in the illustrating images pre‐ data indicate that a higher sensory intensity of audio and visual sented along with the text (Goodale & Milner, 1992; Ungerleider features brings increased attention and cognitive processing, & Haxby, 1994). leading to a greater advertising impact (Langleben et al., 2009). In the audiovisual version, the verbal input was aural and the Dynamic motion and audio features may indeed be effective in visual stimulation involved more complex dynamic 3D representa‐ making ads more memorable (Han et al., 2015). However, stim‐ tions. Accordingly, brain activation was more extensive and impli‐ uli wealth and complexity may otherwise exceed the capacity to cated the pertinent areas in each brain lobe. Additional activations assimilate information and result in reduced message retention were thus identified in the auditory cortex processing speech (Langleben et al., 2009; Seelig et al., 2014; Wang et al., 2013). and related areas of the temporal lobe (Venezia et al., 2017), In our audiovisual experiment, some balance may exist between PUJOL et al. | 11 of 13 the advantages and disadvantages of providing more complex of conventional college lessons and lesson duration in our exper‐ information. iment. Therefore, our results cannot be generalized at this level. The amount and complexity of the information is obviously Also, both textbook and audiovisual formats may potentially be an important factor to consider when designing audiovisual ed‐ more or less advantageous depending on the topics to be learned. ucational material, as is the tempo with which the information is We recorded the students' preference for the audiovisual ver‐ presented. In our study, examination scores were predicted by sion of the lesson, but with no clear advantage in the context brain changes at the end‐of‐lesson fragments and after‐lesson of examination results. Previous studies generally coincide on fragments when presented in the audiovisual‐3D format, which reporting higher student satisfaction when using audiovisual would indicate that information perception and assimilation do material (Ahmad, Sleiman, Thomas, Kashani, & Ditmyer, 2016; not temporally coincide, thus reinforcing the notion that the Drapkin, Lindgren, Lopez, & Stabio, 2015; Murgitroyd, Madurska, tempo should be adequately adjusted when planning education. Gonzalez, & Watson, 2015; Ozer, Govsa, & Bati, 2017; Prakash et By contrast, in the case of using the traditional textbook format, al., 2017; Trelease, 2016), and some studies also report objective examination scores were predicted by brain changes at the mid‐ advantages based on examination scores (e.g., Ahmad et al., 2016; dle‐of‐lesson fragments suggesting a different learning strategy, Drapkin et al., 2015; and revised in Trelease, 2016). As might be in which information may be more directly recorded at the per‐ expected, the topic that more clearly benefits from audiovisual ception stage. and 3D material is Anatomy (Ahmad et al., 2016; Drapkin et al., Activity in the prefrontal cortex significantly accounted for the 2015; Trelease, 2016). Our study is also limited due to its rela‐ notable interindividual differences of our participants when assimi‐ tively reduced cognitive evaluation and a lack of long‐term lesson lating didactic information presented in the audiovisual‐3D format. learning assessments. Successful participants activated prefrontal cortex areas typically In conclusion, this is a novel functional MRI study characteriz‐ concerned with executive functions (Fuster, 2001; Wood & Grafman, ing the pattern of brain activity evoked during the assimilation of 2003). These participants also showed better working memory, which educational information presented in two distinct formats. Brain is a prototypical executive function (Diamond, 2013; Wager & Smith, activation was robust in both cases, but notable differences were 2003). On the other hand, examination scores negatively correlated identified that may well suggest the advantages of either model. It with activity in language‐related cortex and verbal memory. Such a is relevant, however, that the actual learning success, measured by scenario would therefore indicate that audiovisual learning may ben‐ a multiple‐choice examination, was not directly related to the most efit from executive prefrontal operations, whereas verbal process‐ obvious brain activations. Examination scores were instead associ‐ ing, to some extent, interfered with information assimilation in our ated with fMRI signal changes in the frontal lobes. Learning during experiment. In other words, audiovisual learning of the presented the audiovisual version was specifically predicted by a combination material may be more closely related to the proper use of perceived of more activity in the dorsal prefrontal cortex and less participation information to integrate knowledge than to the verbal memorization of the language‐related ventral frontal cortex. Consistently, exam‐ of didactic material, that is to say learning through understanding as ination scores positively correlated with performance in executive opposed to memorizing. functioning and negatively with verbal memory. Overall, our results On the whole, our results suggest notable differences between suggest that audiovisual learning relies more on the proper use of traditional textbook and audiovisual learning of an identical amount perceived information and less on basic verbal memory processes. of didactic information. The limited results obtained from the tra‐ Further research would be necessary for a more complete charac‐ ditional textbook task analysis were in the opposite direction, with terization of imaging correlates in the context of traditional textbook a negative correlation between examination scores and prefrontal learning. cortex activity suggesting a lower involvement of executive opera‐ tions. Moreover, the dorsal prefrontal cortex is one of the few struc‐ AC K N OW L E D G M E N T S tures showing significantly higher activation during the traditional textbook lesson (Figure S2), as a result of being less deactivated This work was supported by 3D Tech Omega Zeta, Barcelona and (Figure 4). The overall pattern of results (i.e., activation/deactiva‐ the Institute of Health Carlos III‐CIBER, Government of Spain, refer‐ tion and the direction of the correlation with examination scores) ence number 1589923. may therefore support the notion that prefrontal cortex activity to some extent interferes with learning during textbook lessons. C O N FL I C T O F I N T E R E S T Unfortunately, we found no positive correlation to complete the pattern and, thus, the analysis is less informative as to how learning The authors have no conflict of interest to declare. takes place in such a situation. Further research is needed to support the proposal that traditional textbook learning is based more on lan‐ DATA AVA I L A B I L I T Y S TAT E M E N T guage processing and verbal memory. A limitation in our study concerns the generalization of re‐ The data that support the findings of this study are available from sults. Firstly, there is a notable difference between the duration the corresponding author upon reasonable request. 12 of 13 | PUJOL et al. ORCID Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202. Jesus Pujol https://orcid.org/0000-0002-9946-4547 Murgitroyd, E., Madurska, M., Gonzalez, J., & Watson, A. (2015). 3D dig‐ ital anatomy modelling – Practical or pretty? Surgeon, 13, 177–180. https​://doi.org/10.1016/j.surge.2014.10.007 REFERENCES Ozer, M. A., Govsa, F., & Bati, A. H. (2017). Web‐based teaching video packages on anatomical education. Surgical and Radiologic Anatomy, Ahmad, M., Sleiman, N. H., Thomas, M., Kashani, N., & Ditmyer, M. M. 39(11), 1253–1261. (2016). Use of high‐definition audiovisual technology in a gross anat‐ Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & omy laboratory: Effect on dental students' learning outcomes and Petersen, S. E. (2014). Methods to detect, characterize, and remove satisfaction. Journal of Dental Education, 80, 128–132. motion artifact in resting state fMRI. NeuroImage, 84, 320–341. https​ Beauchamp, M. S., Yasar, N. E., Frye, R. E., & Ro, T. (2008). Touch, sound ://doi.org/10.1016/j.neuro​image.2013.08.048 and vision in human superior temporal sulcus. NeuroImage, 41, 1011– Prakash, S. S., Muthuraman, N., & Anand, R. (2017). Short‐duration 1020. https​://doi.org/10.1016/j.neuro​image.2008.03.015 podcasts as a supplementary learning tool: Perceptions of medi‐ Buchweitz, A., Mason, R. A., Tomitch, L. M., & Just, M. A. (2009). Brain cal students and impact on assessment performance. BMC Medical activation for reading and listening comprehension: An fMRI study Education, 17, 167. https​://doi.org/10.1186/s12909-017-1001-5 of modality effects and individual differences in language com‐ Pujol, J., Blanco‐Hinojo, L., Macia, D., Alonso, P., Harrison, B. J., Martínez‐ prehension. Psychology & Neuroscience, 2, 111–123. https​://doi. Vilavella, G., … Soriano‐Mas, C. (2019). Mapping alterations of the org/10.3922/j.psns.2009.2.003 functional structure of the cerebral cortex in obsessive‐compulsive Choi, W., Desai, R. H., & Henderson, J. M. (2014). The neural substrates disorder. Cerebral Cortex, https​://doi.org/10.1093/cerco​r/bhz008 of natural reading: A comparison of normal and nonword text using Pujol, J., Macià, D., Blanco‐Hinojo, L., Martínez‐Vilavella, G., Sunyer, J., eyetracking and fMRI. Frontiers in Human Neuroscience, 8, 1024. https​ de la Torre, R., … Harrison, B. J. (2014). Does motion‐related brain ://doi.org/10.3389/fnhum.2014.01024​ functional connectivity reflect both artifacts and genuine neural Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64, activity? NeuroImage, 101, 87–95. https​://doi.org/10.1016/j.neuro​ 135–168. https​://doi.org/10.1146/annur​ev-psych-113011-143750 image.2014.06.065 Drapkin, Z. A., Lindgren, K. A., Lopez, M. J., & Stabio, M. E. (2015). Pujol, J., Martínez‐Vilavella, G., Macià, D., Fenoll, R., Alvarez‐Pedrerol, Development and assessment of a new 3D neuroanatomy teaching M., Rivas, I., … Sunyer, J. (2016). Traffic pollution exposure is associ‐ tool for MRI training. Anatomical Sciences Education, 8, 502–509. ated with altered brain connectivity in school children. NeuroImage, https​://doi.org/10.1002/ase.1509 129, 175–184. Foulkes, L., & Blakemore, S. J. (2018). Studying individual differences in Schuster, S., Hawelka, S., Hutzler, F., Kronbichler, M., & Richlan, F. (2016). human adolescent brain development. Nature Neuroscience, 21, 315– Words in context: The effects of length, frequency, and predictabil‐ 323. https​://doi.org/10.1038/s41593-018-0078-4 ity on brain responses during natural reading. Cerebral Cortex, 26, Friedman, N. P., & Miyake, A. (2017). Unity and diversity of executive 3889–3904. https​://doi.org/10.1093/cerco​r/bhw184 functions: Individual differences as a window on cognitive structure. Seelig, D., Wang, A.‐L., Jaganathan, K., Loughead, J. W., Blady, S. J., Cortex, 86, 186–204. https​://doi.org/10.1016/j.cortex.2016.04.023 Childress, A. R., … Langleben, D. D. (2014). Low message sensa‐ Fuster, J. M. (2001). The prefrontal cortex–an update: Time is of tion health promotion videos are better remembered and activate the essence. Neuron, 30, 319–333. https​://doi.org/10.1016/ areas of the brain associated with memory encoding. PLoS ONE, 9, S0896-6273(01)00285-9 e113256. https​://doi.org/10.1371/journ​al.pone.0113256 Goodale, M. A., & Milner, A. D. (1992). Separate visual pathways for per‐ Seghier, M. L., & Price, C. J. (2018). Interpreting and utilising intersubject ception and action. Trends in Neurosciences, 15, 20–25. https​://doi. variability in brain function. Trends in Cognitive Sciences, 22, 517–530. org/10.1016/0166-2236(92)90344-8 https​://doi.org/10.1016/j.tics.2018.03.003 Han, J., Chen, C., Shao, L., Hu, X., Han, J., & Liu, T. (2015). Learning Shallice, T., & Cipolotti, L. (2018). The prefrontal cortex and neurologi‐ computational models of video memorability from fMRI brain im‐ cal impairments of active thought. Annual Review of Psychology, 69, aging. IEEE Transactions on Cybernetics, 45, 1692–1703. https​://doi. 157–180. https​://doi.org/10.1146/annur​ev-psych-010416-044123 org/10.1109/TCYB.2014.2358647 Tikka, P., Kauttonen, J., & Hlushchuk, Y. (2018). Narrative comprehension Jarvin, L. (2015). Edutainment, games, and the future of education in a beyond language: Common brain networks activated by a movie and digital world. In E. L. Grigorenko (Ed.), The global context for new di‐ its script. PLoS ONE, 13, e0200134. https​://doi.org/10.1371/journ​ rections for child and adolescent development. New Directions for Child al.pone.0200134 and Adolescent Development, 147 (pp. 33–40). Hoboken, NJ: Wiley Trelease, R. B. (2016). From chalkboard, slides, and paper to e‐learning: Periodicals, Inc. How computing technologies have transformed anatomical sciences Jonassen, D., & Grabowski, B. (1993). Handbook of individual differences, education. Anatomical Sciences Education, 9, 583–602. https​://doi. learning, and instruction. New York, NY: Routledge. org/10.1002/ase.1620 Langleben, D. D., Loughead, J. W., Ruparel, K., Hakun, J. G., Busch‐Winokur, Ungerleider, L. G., & Haxby, J. V. (1994). 'What' and 'where' in the human S., Holloway, M. B., … Lerman, C. (2009). Reduced prefrontal and tempo‐ brain. Current Opinion in Neurobiology, 4, 157–165. https​://doi. ral processing and recall of high "sensation value" ads. NeuroImage, 46, org/10.1016/0959-4388(94)90066-3 219–225. https​://doi.org/10.1016/j.neuro​image.2008.12.062 Venezia, J. H., Vaden, K. I. Jr, Rong, F., Maddox, D., Saberi, K., & Hickok, G. Leichnetz, G. R. (2011). Supramarginal Gyrus. In J. S. Kreutzer, J. DeLuca, (2017). Auditory, visual and audiovisual speech processing streams in & B. Caplan (Eds.), Encyclopedia of clinical neuropsychology (pp. 180– superior temporal sulcus. Frontiers in Human Neuroscience, 11, 174. 203). New York, NY: Springer. https​://doi.org/10.3389/fnhum.2017.00174​ Lewis, M. J. (2003). Computer‐assisted learning for teaching anatomy Wager, T. D., & Smith, E. E. (2003). Neuroimaging studies of work‐ and physiology in subjects allied to medicine. Medical Teacher, 25, ing memory: A meta‐analysis. Cognitive, Affective, & Behavioural 204–206. https​://doi.org/10.1080/00000​0 0000​0 0000​0 000a​ Neuroscience, 3, 255–274. https​://doi.org/10.3758/CABN.3.4.255 Lingnau, A., & Downing, P. E. (2015). The lateral occipitotemporal cor‐ Wandell, B. A., & Le, R. K. (2017). Diagnosing the neural circuitry tex in action. Trends in Cognitive Sciences, 19, 268–277. https​://doi. of reading. Neuron, 96, 298–311. https​://doi.org/10.1016/j. org/10.1016/j.tics.2015.03.006 neuron.2017.08.007 PUJOL et al. | 13 of 13 Wang, A. L., Ruparel, K., Loughead, J. W., Strasser, A. A., Blady, S. S U P P O R T I N G I N FO R M AT I O N J., Lynch, K. G., … Langleben, D. D. (2013). Content matters: Neuroimaging investigation of brain and behavioral impact of Additional supporting information may be found online in the televised anti‐tobacco public service announcements. Journal of Supporting Information section at the end of the article.    Neuroscience, 33, 7420–7427. https​://doi.org/10.1523/JNEUR​ OSCI.3840-12.2013 Wechsler, D. (1987). Wechsler memory scale‐revised manual. San Antonio, TX: Psychological Corporation. How to cite this article: Pujol J, Blanco‐Hinojo L, Martínez‐ Wechsler, D. (2008). Wechsler adult intelligence scale, 4th ed. San Antonio, Vilavella G, et al. Brain activity during traditional textbook TX: Pearson Assessment. and audiovisual‐3D learning. Brain Behav. 2019;9:e01427. Wood, J. N., & Grafman, J. (2003). Human prefrontal cortex: Processing and representational perspectives. Nature Reviews Neuroscience, 4, https​://doi.org/10.1002/brb3.1427 139–147. https​://doi.org/10.1038/nrn1033