Multivoxel Pattern Research Articles

Combined representation of visual features in the scene-selective cortex

Visual features of separable dimensions conjoin to represent an integrated entity. We investigated how visual features bind to form a complex visual scene. Specifically, we focused on features important for visually guided navigation: direction and distance. Previously, separate works have shown that directions and distances of navigable paths are coded in the occipital place area (OPA). Using functional magnetic resonance imaging (fMRI), we tested how separate features are concurrently represented in the OPA. Participants saw eight types of scenes, in which four of them had one path and the other four had two paths. In single-path scenes, path direction was either to the left or to the right. In double-path scenes, both directions were present. A glass wall was placed in some paths to restrict navigational distance. To test how the OPA represents path directions and distances, we took three approaches. First, the independent-features approach examined whether the OPA codes each direction and distance. Second, the integrated-features approach explored how directions and distances are integrated into path units, as compared to pooled features, using double-path scenes. Finally, the integrated-paths approach asked how separate paths are combined into a scene. Using multi-voxel pattern similarity analysis, we found that the OPA’s representations of single-path scenes were similar to other single-path scenes of either the same direction or the same distance. Representations of double-path scenes were similar to the combination of two constituent single-paths, as a combined unit of direction and distance rather than as a pooled representation of all features. These results show that the OPA combines the two features to form path units, which are then used to build multiple-path scenes. Altogether, these results suggest that visually guided navigation may be supported by the OPA that automatically and efficiently combines multiple features relevant for navigation and represent a navigation file.

Neural correlates of retrieval success and precision: an fMRI study.

Prior studies examining the neural mechanisms underlying retrieval success and precision have yielded inconsistent results. Here, their neural correlates were examined using a memory task that assessed precision for spatial location. A sample of healthy young adults underwent fMRI scanning during a single study-test cycle. At study, participants viewed a series of object images, each placed at a randomly selected location on an imaginary circle. At test, studied images were intermixed with new images and presented to the participants. The requirement was to move a cursor to the location of the studied image, guessing if necessary. Participants then signaled whether the presented image as having been studied. Memory precision was quantified as the angle between the studied location and the location selected by the participant. A precision effect was evident in the left angular gyrus, where BOLD activity covaried across trials with location accuracy. Multi-voxel pattern analysis also revealed a significant item-level reinstatement effect for high-precision trials. There was no evidence of a retrieval success effect in the angular gyrus. BOLD activity in the hippocampus was insensitive to both success and precision. These findings are partially consistent with prior evidence that success and precision are dissociable features of memory retrieval.

Brain Connectomics Improve the Prediction of High-Risk Depression Profiles in the First Year following Breast Cancer Diagnosis

Background. Prediction of high-risk depression trajectories in the first year following breast cancer diagnosis with fMRI-related brain connectomics is unclear. Methods. The Be Resilient to Breast Cancer (BRBC) study is a multicenter trial in which 189/232 participants (81.5%) completed baseline resting-state functional magnetic resonance imaging (rs-fMRI) and four sequential assessments of depression (T0-T3). The latent growth mixture model (LGMM) was utilized to differentiate depression profiles (high vs. low risk) and was followed by multivoxel pattern analysis (MVPA) to recognize distinct brain connectivity patterns. The incremental value of brain connectomics in the prediction model was also estimated. Results. Four depression profiles were recognized and classified into high-risk (delayed and chronic, 14.8% and 12.7%) and low-risk (resilient and recovery, 50.3% and 22.2%). Frontal medial cortex and frontal pole were identified as two important brain areas against the high-risk profile outcome. The prediction model achieved 16.82-76.21% in NRI and 12.63-50.74% in IDI when brain connectomics were included. Conclusion. Brain connectomics can optimize the prediction against high-risk depression profiles in the first year since breast cancer diagnoses.

Aberrant concordance among dynamics of spontaneous brain activity in patients with migraine without aura: A multivariate pattern analysis study

BackgroundAlterations in the static and dynamic characteristics of spontaneous brain activity have been extensively studied to investigate functional brain changes in migraine without aura (MwoA). However, alterations in concordance among the dynamics of spontaneous brain activity in MwoA remain largely unknown. This study aimed to determine the possibilities of diagnosis based on the concordance indices. MethodsResting-state functional MRI scans were performed on 32 patients with MwoA and 33 matched healthy controls (HCs) in the first cohort, as well as 36 patients with MwoA and 32 HCs in the validation cohort. The dynamic indices including fractional amplitude of low-frequency fluctuation, regional homogeneity, voxel-mirrored homotopic connectivity, degree centrality and global signal connectivity were analyzed. We calculated the concordance of grey matter volume-wise (across voxels) and voxel-wise (across time windows) to quantify the degree of integration among different functional levels represented by these dynamic indices. Subsequently, the voxel-wise concordance alterations were analyzed as features for multi-voxel pattern analysis (MVPA) utilizing the support vector machine. ResultsCompared with that of HCs, patients with MwoA had lower whole-grey matter volume-wise concordance, and the mean value of volume-wise concordance was negatively correlated with the frequency of migraine attacks. The MVPA results revealed that the most discriminative brain regions were the right thalamus, right cerebellar Crus II, left insula, left precentral gyrus, right cuneus, and left inferior occipital gyrus. ConclusionsConcordance alterations in the dynamics of spontaneous brain activity in brain regions could be an important feature in the identification of patients with MwoA.

Use of functional magnetic resonance imaging to identify cortical loci for lower limb movements and their efficacy for individuals after stroke.

Identification of cortical loci for lower limb movements for stroke rehabilitation is crucial for better rehabilitation outcomes via noninvasive brain stimulation by targeting the fine-grained cortical loci of the movements. However, identification of the cortical loci for lower limb movements using functional MRI (fMRI) is challenging due to head motion and difficulty in isolating different types of movement. Therefore, we developed a custom-made MR-compatible footplate and leg cushion to identify the cortical loci for lower limb movements and conducted multivariate analysis on the fMRI data. We evaluated the validity of the identified loci using both fMRI and behavioral data, obtained from healthy participants as well as individuals after stroke. We recruited 33 healthy participants who performed four different lower limb movements (ankle dorsiflexion, ankle rotation, knee extension, and toe flexion) using our custom-built equipment while fMRI data were acquired. A subgroup of these participants (Dataset 1; n = 21) was used to identify the cortical loci associated with each lower limb movement in the paracentral lobule (PCL) using multivoxel pattern analysis and representational similarity analysis. The identified cortical loci were then evaluated using the remaining healthy participants (Dataset 2; n = 11), for whom the laterality index (LI) was calculated for each lower limb movement using the cortical loci identified for the left and right lower limbs. In addition, we acquired a dataset from 15 individuals with chronic stroke for regression analysis using the LI and the Fugl-Meyer Assessment (FMA) scale. The cortical loci associated with the lower limb movements were hierarchically organized in the medial wall of the PCL following the cortical homunculus. The LI was clearer using the identified cortical loci than using the PCL. The healthy participants (mean ± standard deviation: 0.12 ± 0.30; range: -0.63 to 0.91) exhibited a higher contralateral LI than the individuals after stroke (0.07 ± 0.47; -0.83 to 0.97). The corresponding LI scores for individuals after stroke showed a significant positive correlation with the FMA scale for paretic side movement in ankle dorsiflexion (R2 = 0.33, p = 0.025) and toe flexion (R2 = 0.37, p = 0.016). The cortical loci associated with lower limb movements in the PCL identified in healthy participants were validated using independent groups of healthy participants and individuals after stroke. Our findings suggest that these cortical loci may be beneficial for the neurorehabilitation of lower limb movement in individuals after stroke, such as in developing effective rehabilitation interventions guided by the LI scores obtained for neuronal activations calculated from the identified cortical loci across the paretic and non-paretic sides of the brain.

Semantic context-dependent neural representations of odors in the human piriform cortex revealed by 7T MRI.

Olfactory perception depends not only on olfactory inputs but also on semantic context. Although multi-voxel activity patterns of the piriform cortex, a part of the primary olfactory cortex, have been shown to represent odor perception, it remains unclear whether semantic contexts modulate odor representation in this region. Here, we investigated whether multi-voxel activity patterns in the piriform cortex change when semantic context modulates odor perception and, if so, whether the modulated areas communicate with brain regions involved in semantic and memory processing beyond the piriform cortex. We also explored regional differences within the piriform cortex, which are influenced by olfactory input and semantic context. We used 2 × 2 combinations of word labels and odorants that were perceived as congruent and measured piriform activity with a 1-mm isotropic resolution using 7T MRI. We found that identical odorants labeled with different words were perceived differently. This labeling effect was observed in multi-voxel activity patterns in the piriform cortex, as the searchlight decoding analysis distinguished identical odors with different labels for half of the examined stimulus pairs. Significant functional connectivity was observed between parts of the piriform cortex that were modulated by labels and regions associated with semantic and memory processing. While the piriform multi-voxel patterns evoked by different olfactory inputs were also distinguishable, the decoding accuracy was significant for only one stimulus pair, preventing definitive conclusions regarding the locational differences between areas influenced by word labels and olfactory inputs. These results suggest that multi-voxel patterns of piriform activity can be modulated by semantic context, possibly due to communication between the piriform cortex and the semantic and memory regions.

Limited but specific engagement of the mature language network during linguistic statistical learning.

Statistical learning (SL) is the ability to detect and learn regularities from input and is foundational to language acquisition. Despite the dominant role of SL as a theoretical construct for language development, there is a lack of direct evidence supporting the shared neural substrates underlying language processing and SL. It is also not clear whether the similarities, if any, are related to linguistic processing, or statistical regularities in general. The current study tests whether the brain regions involved in natural language processing are similarly recruited during auditory, linguistic SL. Twenty-two adults performed an auditory linguistic SL task, an auditory nonlinguistic SL task, and a passive story listening task as their neural activation was monitored. Within the language network, the left posterior temporal gyrus showed sensitivity to embedded speech regularities during auditory, linguistic SL, but not auditory, nonlinguistic SL. Using a multivoxel pattern similarity analysis, we uncovered similarities between the neural representation of auditory, linguistic SL, and language processing within the left posterior temporal gyrus. No other brain regions showed similarities between linguistic SL and language comprehension, suggesting that a shared neurocomputational process for auditory SL and natural language processing within the left posterior temporal gyrus is specific to linguistic stimuli.

Early-stage use of hearing aids preserves auditory cortical structure in children with sensorineural hearing loss.

Hearing is critical to spoken language, cognitive, and social development. Little is known about how early auditory experiences impact the brain structure of children with bilateral sensorineural hearing loss. This study examined the influence of hearing aid use and residual hearing on the auditory cortex of children with severe to profound congenital sensorineural hearing loss. We evaluated cortical preservation in 103 young pediatric cochlear implant candidates (55 females and 48 males) by comparing their multivoxel pattern similarity of auditory cortical structure with that of 78 age-matched children with typical hearing. The results demonstrated that early-stage hearing aid use preserved the auditory cortex of children with bilateral congenital sensorineural hearing loss. Children with less residual hearing experienced a more pronounced advantage from hearing aid use. However, this beneficial effect gradually diminished after 17months of hearing aid use. These findings support timely fitting of hearing aids in conjunction with early implantation to take advantage of neural preservation to maximize auditory and spoken language development.

Neural Representations of Observed Interpersonal Synchrony/Asynchrony in the Social Perception Network.

The visual perception of individuals is thought to be mediated by a network of regions in the occipitotemporal cortex that supports specialized processing of faces, bodies, and actions. In comparison, we know relatively little about the neural mechanisms that support the perception of multiple individuals and the interactions between them. The present study sought to elucidate the visual processing of social interactions by identifying which regions of the social perception network represent interpersonal synchrony. In an fMRI study with 32 human participants (26 female, 6 male), we used multivoxel pattern analysis to investigate whether activity in face-selective, body-selective, and interaction-sensitive regions across the social perception network supports the decoding of synchronous versus asynchronous head-nodding and head-shaking. Several regions were found to support significant decoding of synchrony/asynchrony, including extrastriate body area (EBA), face-selective and interaction-sensitive mid/posterior right superior temporal sulcus, and occipital face area. We also saw robust cross-classification across actions in the EBA, suggestive of movement-invariant representations of synchrony/asynchrony. Exploratory whole-brain analyses also identified a region of the right fusiform cortex that responded more strongly to synchronous than to asynchronous motion. Critically, perceiving interpersonal synchrony/asynchrony requires the simultaneous extraction and integration of dynamic information from more than one person. Hence, the representation of synchrony/asynchrony cannot be attributed to augmented or additive processing of individual actors. Our findings therefore provide important new evidence that social interactions recruit dedicated visual processing within the social perception network that extends beyond that engaged by the faces and bodies of the constituent individuals.

True and false memories for spatial location evoke more similar patterns of brain activity in males than females

ABSTRACT True and false memories recruit a number of shared brain regions; however, they are not completely overlapping. Extensive sex differences have been identified in the brain during true memories and, recently, we identified sex differences in the brain during false memories. In the current fMRI study, we sought to determine whether sex differences existed in the location and extent of overlap between true and false memories. True and false memories activated a number of shared brain regions. Compared to females, males produced a greater number of overlapping brain regions (8 versus 2 activations for males and females, respectively) including the prefrontal cortex, parietal cortex, and early/late visual processing cortices (including V1) in males and prefrontal and parietal cortices in females. Males had significantly higher similarity between true and false memory activation maps, revealed by our novel multi-voxel pattern correlation analysis. Moreover, higher similarity between true and false memory activation maps was associated with higher false memory rates. The current results suggest that true and false memories are more similar in males than females. The significant brain–behavior relationship also suggests that males may be more susceptible to false memory errors due to their highly similar true memory–false memory cortical representations.

Repetition Suppression Reveals Cue-Specific Spatial Representations for Landmarks and Self-Motion Cues in the Human Retrosplenial Cortex.

The efficient use of various spatial cues within a setting is crucial for successful navigation. Two fundamental forms of spatial navigation, landmark-based and self-motion-based, engage distinct cognitive mechanisms. The question of whether these modes invoke shared or separate spatial representations in the brain remains unresolved. While nonhuman animal studies have yielded inconsistent results, human investigation is limited. In our previous work (Chen et al., 2019), we introduced a novel spatial navigation paradigm utilizing ultra-high field fMRI to explore neural coding of positional information. We found that different entorhinal subregions in the right hemisphere encode positional information for landmarks and self-motion cues. The present study tested the generalizability of our previous finding with a modified navigation paradigm. Although we did not replicate our previous finding in the entorhinal cortex, we identified adaptation-based allocentric positional codes for both cue types in the retrosplenial cortex (RSC), which were not confounded by the path to the spatial location. Crucially, the multi-voxel patterns of these spatial codes differed between the cue types, suggesting cue-specific positional coding. The parahippocampal cortex exhibited positional coding for self-motion cues, which was not dissociable from path length. Finally, the brain regions involved in successful navigation differed from our previous study, indicating overall distinct neural mechanisms recruited in our two studies. Taken together, the current findings demonstrate cue-specific allocentric positional coding in the human RSC in the same navigation task for the first time and that spatial representations in the brain are contingent on specific experimental conditions.

Mechanisms of Action Anticipation in Table Tennis Players: A Multivoxel Pattern Analysis Study

An exceptional ability to accurately anticipate an opponent’s action is paramount for competitive athletes and highlights their experiential mastery. Despite conventional associations of action observation with specific brain regions, neuroimaging discrepancies persist. To explore the brain regions and neural mechanisms undergirding action anticipation, we compared distinct brain activation patterns involved in table tennis serve anticipation of expert table tennis athletes vs. non-experts by using both univariate analysis and multivoxel pattern analysis (MVPA). We collected functional magnetic resonance imaging data from 29 table tennis experts and 34 non-experts as they pressed a button to predict the trajectory of a ball in a table tennis serve video truncated at the moment of racket-ball contact vs. pressing any button while viewing a static image of the first video frame. MVPA was applied to assess whether it could accurately differentiate experts from non-experts. MVPA results indicated moderate accuracy (90.48%) for differentiating experts from non-experts. Brain regions contributing most to the differentiation included the left cerebellum, the vermis, the right middle temporal pole, the inferior parietal cortex, the bilateral paracentral lobule, and the left supplementary motor area. The findings suggest that brain regions associated with cognitive conflict monitoring and motor cognition contribute to the action anticipation ability of expert table tennis players.

Decoding auditory deprivation: resting-state fMRI insights into deafness and brain plasticity.

Deafness, as a profound manifestation of sensory deprivation, prompts a cascade of intricate cerebral adaptations. In this study, involving 35 deaf individuals and 35 hearing controls, we utilized resting-state functional magnetic resonance imaging (rs-fMRI) to delve into the depths of functional connectivity nuances distinguishing deaf individuals from their hearing counterparts. Leading our analytical approach was the application of multi-voxel pattern analysis (fc-MVPA). This advanced method provided a refined perspective, revealing amplified neural connectivity within the deaf population. Notably, regions such as the left postcentral somatosensory association cortex, the anterior and posterior corridors of the left superior temporal gyrus (STG), and the left mid-temporal lobe were identified as hotspots of heightened connectivity. Further, fc-MVPA shed light on intricate interaction effects, which became more pronounced when examining variables such as the duration of auditory deprivation and the extent of sign language exposure. These interactions were particularly evident in the premotor and left frontal mid-orbital regions. Complementing this, seed-based connectivity assessments illuminated pronounced coupling dynamics within the left STG spectrum. Concurrently, local correlation (LCOR) value analysis in the deaf group revealed significant shifts in the right superior STG and bilateral precuneus. In addition, amplitude of low-frequency fluctuation (ALFF) evaluations indicated modulations in the bilateral mid cingulum and left superior mid frontal gyrus. This comprehensive, fc-MVPA-driven exploration uncovers the multifaceted functional adaptations resulting from deafness, highlighting the profound plasticity of the human brain and its potential implications for targeted rehabilitative strategies.

Finger-specific representations are sharpened during a fatiguing motor task

Introduction
 Motor fatigability is a limiting factor in any kind of setting, in which physical performance is required. Motor fatigability can be quantified through the decrease in movement speed, when low-force movements are performed repeatedly with maximal speed. In this study, we measure motor fatigability in healthy participants through fast finger tapping for 30s. Previous research has shown that the decrease in movement speed, also called motor slowing, is associated with a rise in brain activity, a reduction in surround inhibition in the primary sensorimotor cortex (SM1), and an increase in co-activation of antagonistic muscle groups involved in the movement (Bächinger et al., 2019). However, it remains an open question of whether motor slowing and the associated release of inhibition causes a reduction of signal-to-noise ratio for movement-specific information. Here, we aim to answer this question by assessing finger representations using representational similarity analysis (RSA) when participants perform fatiguing tapping with either the index or middle finger. We hypothesized that a reduction of movement-specific information would be associated with the index and middle finger representations in SM1 getting “blurred” over time due to a gradual break-down of surround inhibition. Thus, if the signal-to-noise ratio of movement-specific information decreases in parallel with motor slowing, we would expect finger representations to become more overlapping. Vice-versa, if the signal-to-noise ratio of movement-specific information increases despite motor slowing, we would expect sharper finger representation.
 Methods
 26 healthy young participants performed a motor slowing task during functional MRI. The participants performed 30s of maximal speed finger tapping with the index and the middle finger, alternating between trials. To quantify motor slowing from the behaviour, we performed a linear regression analysis. For the first-level general linear model of the fMRI data, the fingers were regressed separately and the 30s of tapping were further split into 3 x 10s regressors (time bin 1, bin 2, bin 3). We performed RSA separately on each 10s regressor for the anatomically defined regions of interest M1 and S1 hand area (Diedrichsen et al., 2013; Walther et al., 2016) and therefore obtained a dissimilarity measure for each time bin. A mixed effects model with the factor time was used to test whether dissimilarity changed across time bins.
 Results
 On the behavioural level, motor slowing could be observed, as tapping speed significantly decreased in each finger over time (F(1, 76) >= 5.78, p <=.05). Concerning the dissimilarity measure, we found an increase over time for S1 as well as M1 (F(2, 50) >= 17.41, p <=.001).
 Discussion/Conclusion
 We conclude that the finger representations in the sensorimotor cortex become more distinct with motor slowing. This suggests that the signal-to-noise ratio of movement-specific information is increased, potentially to compensate for supraspinal changes caused by fatigability.
 References
 Bächinger, M., Lehner, R., Thomas, F., Hanimann, S., Balsters, J., & Wenderoth, N. (2019). Human motor fatigability as evoked by repetitive movements results from a gradual breakdown of surround inhibition. eLife, 8, Article e46750. https://doi.org/10.7554/eLife.46750
 Diedrichsen, J., Wiestler, T., & Krakauer, J. W. (2013). Two distinct ipsilateral cortical representations for individuated finger movements. Cerebral Cortex, 23(6), 1362–1377. https://doi.org/10.1093/cercor/bhs120
 Walther, A., Nili, H., Ejaz, N., Alink, A., Kriegeskorte, N., & Diedrichsen, J. (2016). Reliability of dissimilarity measures for multi-voxel pattern analysis. NeuroImage, 137, 188–200. https://doi.org/10.1016/j.neuroimage.2015.12.012

Characterizing the discriminability of visual categorical information in strongly connected voxels

Functional brain responses are strongly influenced by connectivity. Recently, we demonstrated a major example of this: category discriminability within occipitotemporal cortex (OTC) is enhanced for voxel sets that share strong functional connectivity to distal brain areas, relative to those that share lesser connectivity. That is, within OTC regions, sets of ‘most-connected’ voxels show improved multivoxel pattern discriminability for tool-, face-, and place stimuli relative to voxels with weaker connectivity to the wider brain. However, understanding whether these effects generalize to other domains (e.g. body perception network), and across different levels of the visual processing streams (e.g. dorsal as well as ventral stream areas) is an important extension of this work. Here, we show that this so-called connectivity-guided decoding (CGD) effect broadly generalizes across a wide range of categories (tools, faces, bodies, hands, places). This effect is robust across dorsal stream areas, but less consistent in earlier ventral stream areas. In the latter regions, category discriminability is generally very high, suggesting that extraction of category-relevant visual properties is less reliant on connectivity to downstream areas. Further, CGD effects are primarily expressed in a category-specific manner: For example, within the network of tool regions, discriminability of tool information is greater than non-tool information. The connectivity-guided decoding approach shown here provides a novel demonstration of the crucial relationship between wider brain connectivity and complex local-level functional responses at different levels of the visual processing streams. Further, this approach generates testable new hypotheses about the relationships between connectivity and local selectivity.

Multi-modal Representation of the Size of Space in the Human Brain.

To estimate the size of an indoor space, we must analyze the visual boundaries that limit the spatial extent and acoustic cues from reflected interior surfaces. We used fMRI to examine how the brain processes the geometric size of indoor scenes when various types of sensory cues are presented individually or together. Specifically, we asked whether the size of space is represented in a modality-specific way or in an integrative way that combines multimodal cues. In a block-design study, images or sounds that depict small- and large-sized indoor spaces were presented. Visual stimuli were real-world pictures of empty spaces that were small or large. Auditory stimuli were sounds convolved with different reverberations. By using a multivoxel pattern classifier, we asked whether the two sizes of space can be classified in visual, auditory, and visual-auditory combined conditions. We identified both sensory-specific and multimodal representations of the size of space. To further investigate the nature of the multimodal region, we specifically examined whether it contained multimodal information in a coexistent or integrated form. We found that angular gyrus and the right medial frontal gyrus had modality-integrated representation, displaying sensitivity to the match in the spatial size information conveyed through image and sound. Background functional connectivity analysis further demonstrated that the connection between sensory-specific regions and modality-integrated regions increases in the multimodal condition compared with single modality conditions. Our results suggest that spatial size perception relies on both sensory-specific and multimodal representations, as well as their interplay during multimodal perception.

Working Memory Maintenance of Visual and Auditory Spatial Information Relies on Supramodal Neural Codes in the Dorsal Frontoparietal Cortex.

The frontoparietal attention network plays a pivotal role during working memory (WM) maintenance, especially under high-load conditions. Nevertheless, there is ongoing debate regarding whether this network relies on supramodal or modality-specific neural signatures. In this study, we used multi-voxel pattern analysis (MVPA) to evaluate the neural representation of visual versus auditory information during WM maintenance. During fMRI scanning, participants maintained small or large spatial configurations (low- or high-load trials) of either colour shades or sound pitches in WM for later retrieval. Participants were less accurate in retrieving high- vs. low-load trials, demonstrating an effective manipulation of WM load, irrespective of the sensory modality. The frontoparietal regions involved in maintaining high- vs. low-load spatial maps in either sensory modality were highlighted using a conjunction analysis. Widespread activity was found across the dorsal frontoparietal network, peaking on the frontal eye fields and the superior parietal lobule, bilaterally. Within these regions, MVPAs were performed to quantify the pattern of distinctness of visual vs. auditory neural codes during WM maintenance. These analyses failed to reveal distinguishable patterns in the dorsal frontoparietal regions, thus providing support for a common, supramodal neural code associated with the retention of either visual or auditory spatial configurations.

Familiarity Processing through Faces and Names: Insights from Multivoxel Pattern Analysis.

The way our brain processes personal familiarity is still debatable. We used searchlight multivoxel pattern analysis (MVPA) to identify areas where local fMRI patterns could contribute to familiarity detection for both faces and name categories. Significantly, we identified cortical areas in frontal, temporal, cingulate, and insular areas, where it is possible to accurately cross-classify familiar stimuli from one category using a classifier trained with the stimulus from the other (i.e., abstract familiarity) based on local fMRI patterns. We also discovered several areas in the fusiform gyrus, frontal, and temporal regions-primarily lateralized to the right hemisphere-supporting the classification of familiar faces but failing to do so for names. Also, responses to familiar names (compared to unfamiliar names) consistently showed less activation strength than responses to familiar faces (compared to unfamiliar faces). The results evinced a set of abstract familiarity areas (independent of the stimulus type) and regions specifically related only to face familiarity, contributing to recognizing familiar individuals.

Scene-selectivity in CA1/subicular complex: Multivoxel pattern analysis at 7T

Prior univariate functional magnetic resonance imaging (fMRI) studies in humans suggest that the anteromedial subicular complex of the hippocampus is a hub for scene-based cognition. However, it is possible that univariate approaches were not sufficiently sensitive to detect scene-related activity in other subfields that have been implicated in spatial processing (e.g., CA1). Further, as connectivity-based functional gradients in the hippocampus do not respect classical subfield boundary definitions, category selectivity may be distributed across anatomical subfields. Region-of-interest approaches, therefore, may limit our ability to observe category selectivity across discrete subfield boundaries. To address these issues, we applied searchlight multivariate pattern analysis to 7T fMRI data of healthy adults who undertook a simultaneous visual odd-one-out discrimination task for scene and non-scene (including face) visual stimuli, hypothesising that scene classification would be possible in multiple hippocampal regions within, but not constrained to, anteromedial subicular complex and CA1. Indeed, we found that the scene-selective searchlight map overlapped not only with anteromedial subicular complex (distal subiculum, pre/para subiculum), but also inferior CA1, alongside posteromedial (including retrosplenial) and parahippocampal cortices. Probabilistic overlap maps revealed gradients of scene category selectivity, with the strongest overlap located in the medial hippocampus, converging with searchlight findings. This was contrasted with gradients of face category selectivity, which had stronger overlap in more lateral hippocampus, supporting ideas of parallel processing streams for these two categories. Our work helps to map the scene, in contrast to, face processing networks within, and connected to, the human hippocampus.

Brain connectomics improve prediction of 1-year decreased quality of life in breast cancer: A multi-voxel pattern analysis

PurposeWhether brain connectomics can predict 1-year decreased Quality of Life (QoL) in patients with breast cancer are unclear. A longitudinal study was utilized to explore their prediction abilities with a multi-center sample. Methods232 breast cancer patients were consecutively enrolled and 214 completed the 1-year QoL assessment (92.2%). Resting state functional magnetic resonance imaging was collected before the treatment and a multivoxel pattern analysis (MVPA) was performed to differentiate whole-brain resting-state connectivity patterns. Net Reclassification Improvement (NRI) as well as Integrated Discrimination Improvement (IDI) were calculated to estimate the incremental value of brain connectomics over conventional risk factors. ResultsParacingulate Gyrus, Superior Frontal Gyrus and Frontal Pole were three significant brain areas. Brain connectomics yielded 7.8–17.2% of AUC improvement in predicting 1-year decreased QoL. The NRI and IDI ranged from 20.27 to 54.05%, 13.21–33.34% respectively. ConclusionBrain connectomics contribute to a more accurate prediction of 1-year decreased QoL in breast cancer. Significant brain areas in the prefrontal lobe could be used as potential intervention targets (i.e., Cognitive Behavioral Group Therapy) to improve long-term QoL outcomes in breast cancer.