Beyond faces: the contribution of the amygdala to visual processing in the macaque brain.

The amygdala is present in a diverse range of vertebrate species, such as lizards, rodents, and primates; however, its structure and connectivity differs across species. The increased connections to visual sensory areas in primate species suggests that understanding the visual selectivity of the amygdala in detail is critical to revealing the principles underlying its function in primate cognition. Therefore, we designed a high-resolution, contrast-agent enhanced, event-related fMRI experiment, and scanned 3 adult rhesus macaques, while they viewed 96 naturalistic stimuli. Half of these stimuli were social (defined by the presence of a conspecific), the other half were nonsocial. We also nested manipulations of emotional valence (positive, neutral, and negative) and visual category (faces, nonfaces, animate, and inanimate) within the stimulus set. The results reveal widespread effects of emotional valence, with the amygdala responding more on average to inanimate objects and animals than faces, bodies, or social agents in this experimental context. These findings suggest that the amygdala makes a contribution to primate vision that goes beyond an auxiliary role in face or social perception. Furthermore, the results highlight the importance of stimulus selection and experimental design when probing the function of the amygdala and other visually responsive brain regions.

Illusory faces are more likely to be perceived as male than female.

Despite our fluency in reading human faces, sometimes we mistakenly perceive illusory faces in objects, a phenomenon known as face pareidolia. Although illusory faces share some neural mechanisms with real faces, it is unknown to what degree pareidolia engages higher-level social perception beyond the detection of a face. In a series of large-scale behavioral experiments (ntotal = 3,815 adults), we found that illusory faces in inanimate objects are readily perceived to have a specific emotional expression, age, and gender. Most strikingly, we observed a strong bias to perceive illusory faces as male rather than female. This male bias could not be explained by preexisting semantic or visual gender associations with the objects, or by visual features in the images. Rather, this robust bias in the perception of gender for illusory faces reveals a cognitive bias arising from a broadly tuned face evaluation system in which minimally viable face percepts are more likely to be perceived as male.

Clutter substantially reduces selectivity for peripheral faces in the macaque brain.

According to a prominent view in neuroscience, visual stimuli are coded by discrete cortical networks that respond preferentially to specific categories, such as faces or objects. However, it remains unclear how these category-selective networks respond when viewing conditions are cluttered, i.e., when there is more than one stimulus in the visual field. Here, we asked three questions: (1) Does clutter reduce the response and selectivity for faces as a function of retinal location? (2) Is the preferential response to faces uniform across the visual field? And (3) Does the ventral visual pathway encode information about the location of cluttered faces? We used fMRI to measure the response of the face-selective network in awake, fixating macaques (2 female, 5 male). Across a series of four experiments, we manipulated the presence and absence of clutter, as well as the location of the faces relative to the fovea. We found that clutter reduces the response to peripheral faces. When presented in isolation, without clutter, the selectivity for faces is fairly uniform across the visual field, but, when clutter is present, there is a marked decrease in the selectivity for peripheral faces. We also found no evidence of a contralateral visual field bias when faces were presented in clutter. Nonetheless, multivariate analyses revealed that the location of cluttered faces could be decoded from the multivoxel response of the face-selective network. Collectively, these findings demonstrate that clutter blunts the selectivity of the face-selective network to peripheral faces, although information about their retinal location is retained.SIGNIFICANCE STATEMENTNumerous studies that have measured brain activity in macaques have found visual regions that respond preferentially to faces. Although these regions are thought to be essential for social behavior, their responses have typically been measured while faces were presented in isolation, a situation atypical of the real world. How do these regions respond when faces are presented with other stimuli? We report that, when clutter is present, the preferential response to foveated faces is spared but preferential response to peripheral faces is reduced. Our results indicate that the presence of clutter changes the response of the face-selective network.

Representation of Contralateral Visual Space in the Human Hippocampus.

The initial encoding of visual information primarily from the contralateral visual field is a fundamental organizing principle of the primate visual system. Recently, the presence of such retinotopic sensitivity has been shown to extend well beyond early visual cortex to regions not historically considered retinotopically sensitive. In particular, human scene-selective regions in parahippocampal and medial parietal cortex exhibit prominent biases for the contralateral visual field. Here, we used fMRI to test the hypothesis that the human hippocampus, which is thought to be anatomically connected with these scene-selective regions, would also exhibit a biased representation of contralateral visual space. First, population receptive field (pRF) mapping with scene stimuli revealed strong biases for the contralateral visual field in bilateral hippocampus. Second, the distribution of retinotopic sensitivity suggested a more prominent representation in anterior medial portions of the hippocampus. Finally, the contralateral bias was confirmed in independent data taken from the Human Connectome Project (HCP) initiative. The presence of contralateral biases in the hippocampus, a structure considered by many as the apex of the visual hierarchy, highlights the truly pervasive influence of retinotopy. Moreover, this finding has important implications for understanding how visual information relates to the allocentric global spatial representations known to be encoded therein.SIGNIFICANCE STATEMENT Retinotopic encoding of visual information is an organizing principle of visual cortex. Recent work demonstrates this sensitivity in structures far beyond early visual cortex, including those anatomically connected to the hippocampus. Here, using population receptive field (pRF) modeling in two independent sets of data we demonstrate a consistent bias for the contralateral visual field in bilateral hippocampus. Such a bias highlights the truly pervasive influence of retinotopy, with important implications for understanding how the presence of retinotopy relates to more allocentric spatial representations.

Expert Tool Users Show Increased Differentiation between Visual Representations of Hands and Tools.

The idea that when we use a tool we incorporate it into the neural representation of our body (embodiment) has been a major inspiration for philosophy, science, and engineering. While theoretically appealing, there is little direct evidence for tool embodiment at the neural level. Using functional magnetic resonance imaging (fMRI) in male and female human subjects, we investigated whether expert tool users (London litter pickers: n = 7) represent their expert tool more like a hand (neural embodiment) or less like a hand (neural differentiation), as compared with a group of tool novices (n = 12). During fMRI scans, participants viewed first-person videos depicting grasps performed by either a hand, litter picker, or a non-expert grasping tool. Using representational similarity analysis (RSA), differences in the representational structure of hands and tools were measured within occipitotemporal cortex (OTC). Contrary to the neural embodiment theory, we find that the experts group represent their own tool less like a hand (not more) relative to novices. Using a case-study approach, we further replicated this effect, independently, in five of the seven individual expert litter pickers, as compared with the novices. An exploratory analysis in left parietal cortex, a region implicated in visuomotor representations of hands and tools, also indicated that experts do not visually represent their tool more similar to hands, compared with novices. Together, our findings suggest that extensive tool use leads to an increased neural differentiation between visual representations of hands and tools. This evidence provides an important alternative framework to the prominent tool embodiment theory.SIGNIFICANCE STATEMENT It is commonly thought that tool use leads to the assimilation of the tool into the neural representation of the body, a process referred to as embodiment. Here, we demonstrate that expert tool users (London litter pickers) neurally represent their own tool less like a hand (not more), compared with novices. Our findings advance our current understanding for how experience shapes functional organization in high-order visual cortex. Further, this evidence provides an alternative framework to the prominent tool embodiment theory, suggesting instead that experience with tools leads to more distinct, separable hand and tool representations.

Multiple adjoining word- and face-selective regions in ventral temporal cortex exhibit distinct dynamics.

The map of category-selectivity in human ventral temporal cortex (VTC) provides organizational constraints to models of object recognition. One important principle is lateral-medial response biases to stimuli that are typically viewed in the center or periphery of the visual field. However, little is known about the relative temporal dynamics and location of regions that respond preferentially to stimulus classes that are centrally viewed, like the face- and word-processing networks. Here, word- and face-selective regions within VTC were mapped using intracranial recordings from 36 patients. Partially overlapping, but also anatomically dissociable patches of face- and word-selectivity were found in VTC. In addition to canonical word-selective regions along the left posterior occipitotemporal sulcus, selectivity was also located medial and anterior to face-selective regions on the fusiform gyrus at the group level and within individual male and female subjects. These regions were replicated using 7 Tesla fMRI in healthy subjects. Left hemisphere word-selective regions preceded right hemisphere responses by 125 ms, potentially reflecting the left hemisphere bias for language; with no hemispheric difference in face-selective response latency. Word-selective regions along the posterior fusiform responded first, then spread medially and laterally, then anteriorally. Face-selective responses were first seen in posterior fusiform regions bilaterally, then proceeded anteriorally from there. For both words and faces, the relative delay between regions was longer than would be predicted by purely feedforward models of visual processing. The distinct time-courses of responses across these regions, and between hemispheres, suggest a complex and dynamic functional circuit supports face and word perception.SIGNIFICANCE STATEMENT:Representations of visual objects in the human brain have been shown to be organized by several principles, including whether those objects tend to be viewed centrally or peripherally in the visual field. However, it remains unclear how regions that process objects that are viewed centrally, like words and faces, are organized relative to one another. Here, invasive and non-invasive neuroimaging suggests there is a mosaic of regions in ventral temporal cortex that respond selectively to either words or faces. These regions display differences in the strength and timing of their responses, both within and between brain hemispheres, suggesting they play different roles in perception. These results illuminate extended, bilateral, and dynamic brain pathways that support face perception and reading.

Scanning the horizon: towards transparent and reproducible neuroimaging research.

Functional neuroimaging techniques have transformed our ability to probe the neurobiological basis of behaviour and are increasingly being applied by the wider neuroscience community. However, concerns have recently been raised that the conclusions that are drawn from some human neuroimaging studies are either spurious or not generalizable. Problems such as low statistical power, flexibility in data analysis, software errors and a lack of direct replication apply to many fields, but perhaps particularly to functional MRI. Here, we discuss these problems, outline current and suggested best practices, and describe how we think the field should evolve to produce the most meaningful and reliable answers to neuroscientific questions.

Making sense of phantom limb pain.

Phantom limb pain (PLP) impacts the majority of individuals who undergo limb amputation. The PLP experience is highly heterogenous in its quality, intensity, frequency and severity. This heterogeneity, combined with the low prevalence of amputation in the general population, has made it difficult to accumulate reliable data on PLP. Consequently, we lack consensus on PLP mechanisms, as well as effective treatment options. However, the wealth of new PLP research, over the past decade, provides a unique opportunity to re-evaluate some of the core assumptions underlying what we know about PLP and the rationale behind PLP treatments. The goal of this review is to help generate consensus in the field on how best to research PLP, from phenomenology to treatment. We highlight conceptual and methodological challenges in studying PLP, which have hindered progress on the topic and spawned disagreement in the field, and offer potential solutions to overcome these challenges. Our hope is that a constructive evaluation of the foundational knowledge underlying PLP research practices will enable more informed decisions when testing the efficacy of existing interventions and will guide the development of the next generation of PLP treatments.

Distinct Representational Structure and Localization for Visual Encoding and Recall during Visual Imagery.

During memory recall and visual imagery, reinstatement is thought to occur as an echoing of the neural patterns during encoding. However, the precise information in these recall traces is relatively unknown, with previous work primarily investigating either broad distinctions or specific images, rarely bridging these levels of information. Using ultra-high-field (7T) functional magnetic resonance imaging with an item-based visual recall task, we conducted an in-depth comparison of encoding and recall along a spectrum of granularity, from coarse (scenes, objects) to mid (e.g., natural, manmade scenes) to fine (e.g., living room, cupcake) levels. In the scanner, participants viewed a trial-unique item, and after a distractor task, visually imagined the initial item. During encoding, we observed decodable information at all levels of granularity in category-selective visual cortex. In contrast, information during recall was primarily at the coarse level with fine-level information in some areas; there was no evidence of mid-level information. A closer look revealed segregation between voxels showing the strongest effects during encoding and those during recall, and peaks of encoding-recall similarity extended anterior to category-selective cortex. Collectively, these results suggest visual recall is not merely a reactivation of encoding patterns, displaying a different representational structure and localization from encoding, despite some overlap.

Highly similar and competing visual scenes lead to diminished object but not spatial detail in memory drawings.

Drawings of scenes made from memory can be highly detailed and spatially accurate, with little information not found in the observed stimuli. While prior work has focused on studying memory for distinct scenes, less is known about the specific detail recalled when episodes are highly similar and competing. Here, participants (N = 30) were asked to study and recall eight complex scene images using a drawing task. Importantly, four of these images were exemplars of different scene categories, while the other four images were from the same scene category. The resulting 213 drawings were judged by 1764 online scorers for a comprehensive set of measures, including scene and object diagnosticity, spatial information, and fixation and pen movement behaviour. We observed that competition in memory resulted in diminished object detail, with drawings and objects that were less diagnostic of their original image. However, repeated exemplars of a category did not result in differences in spatial memory accuracy, and there were no differences in fixations during study or pen movements during recall. These results reveal that while drawings for distinct categories of scenes can be highly detailed and accurate, drawings for scenes from repeated categories, creating competition in memory, show reduced object detail.

Theta-burst TMS of lateral occipital cortex reduces BOLD responses across category-selective areas in ventral temporal cortex.

Human visual cortex contains three scene-selective regions in the lateral, medial and ventral cortex, termed the occipital place area (OPA), medial place area (MPA) and parahippocampal place area (PPA). Using functional magnetic resonance imaging (fMRI), all three regions respond more strongly when viewing visual scenes compared with isolated objects or faces. To determine how these regions are functionally and causally connected, we applied transcranial magnetic stimulation to OPA and measured fMRI responses before and after stimulation, using a theta-burst paradigm (TBS). To test for stimulus category-selectivity, we presented a range of visual categories (scenes, buildings, objects, faces). To test for specificity of any effects to TBS of OPA we employed two control conditions: Sham, with no TBS stimulation, and an active TBS-control with TBS to a proximal face-selective cortical region (occipital face area, or OFA). We predicted that TBS to OPA (but not OFA) would lead to decreased responses to scenes and buildings (but not other categories) in other scene-selective cortical regions. Across both ROI and whole-volume analyses, we observed decreased responses to scenes in PPA as a result of TBS. However, these effects were neither category specific, with decreased responses to all stimulus categories, nor limited to scene-selective regions, with decreases also observed in face-selective fusiform face area (FFA). Furthermore, similar effects were observed with TBS to OFA, thus effects were not specific to the stimulation site in the lateral occipital cortex. Whilst these data are suggestive of a causal, but non-specific relationship between lateral occipital and ventral temporal cortex, we discuss several factors that could have underpinned this result, such as the differences between TBS and online TMS, the role of anatomical distance between stimulated regions and how TMS effects are operationalised. Furthermore, our findings highlight the importance of active control conditions in brain stimulation experiments to accurately assess functional and causal connectivity between specific brain regions.

Disrupted object-scene semantics boost scene recall but diminish object recall in drawings from memory.

Humans are highly sensitive to the statistical relationships between features and objects within visual scenes. Inconsistent objects within scenes (e.g., a mailbox in a bedroom) instantly jump out to us and are known to catch our attention. However, it is debated whether such semantic inconsistencies result in boosted memory for the scene, impaired memory, or have no influence on memory. Here, we examined the relationship of scene-object consistencies on memory representations measured through drawings made during recall. Participants (N = 30) were eye-tracked while studying 12 real-world scene images with an added object that was either semantically consistent or inconsistent. After a 6-minute distractor task, they drew the scenes from memory while pen movements were tracked electronically. Online scorers (N = 1,725) rated each drawing for diagnosticity, object detail, spatial detail, and memory errors. Inconsistent scenes were recalled more frequently, but contained less object detail. Further, inconsistent objects elicited more errors reflecting looser memory binding (e.g., migration across images). These results point to a dual effect in memory of boosted global (scene) but diminished local (object) information. Finally, we observed that participants fixate longest on inconsistent objects, but these fixations during study were not correlated with recall performance, time, or drawing order. In sum, these results show a nuanced effect of scene inconsistencies on memory detail during recall.

A Posterior-Anterior Distinction between Scene Perception and Scene Construction in Human Medial Parietal Cortex.

Human retrosplenial complex (RSC), located in medial parietal cortex, has been implicated in numerous cognitive functions, including scene perception, spatial navigation, and autobiographical memory retrieval. Recently, a posterior-anterior distinction within RSC was proposed, such that posterior aspects process scene-related visual information (constituting a medial place area [MPA]), whereas anterior aspects process information that is vividly retrieved from memory, thereby supporting remembering and potentially navigation. Here, we tested this proposed distinction in a single group of participants (both male and female) using fMRI with both perceptual and mnemonic tasks. After completing a resting-state scan, participants performed a task that required constructing scenes from memory and completed a scene selectivity localizer task. We tested directly perceptual and mnemonic responses in MPA and an anterior, connectivity-defined region (CON), which showed strong functional connectivity with anterior parahippocampal place area. A double dissociation was observed, such that CON was more strongly activated during scene construction than was MPA, whereas MPA was more perceptually responsive than CON. Further, peak responses from the scene construction task were anterior to perceptual peaks in all but 1 participant and hemisphere. Finally, through analyses of the posterior-anterior response profiles, we identify the fundus of the parieto-occipital sulcus as a potential location for the crossover from perceptual to mnemonic representations and highlight a potential left-hemisphere advantage for mnemonic representations. Collectively, our results support a distinction between posterior and anterior aspects of the RSC, suggesting that more specific functional-anatomic terms should be used in its place in future work.SIGNIFICANCE STATEMENT The retrosplenial complex (RSC) has been implicated in vision, spatial cognition, and memory. We previously speculated on a potential posterior-anterior distinction within RSC for scene perception and memory-based scene construction/navigation. Here, we tested this distinction through a combination of resting-state, perceptual, and mnemonic task data. Consistent with our predictions, we demonstrate that perceptual responses peak consistently posterior of those elicited by memory-based scene construction within the broader RSC. Further, we highlight (1) the fundus of the parieto-occipital sulcus as a landmark for the transition between these representations, (2) the anterior bank of parieto-occipital sulcus as the point of maximal separation between these representations, and (3) identify a potential hemispheric asymmetry in mnemonic representations. These data support functional dissociations within RSC.

Differential Representations of Perceived and Retrieved Visual Information in Hippocampus and Cortex.

Memory retrieval is thought to depend on interactions between hippocampus and cortex, but the nature of representation in these regions and their relationship remains unclear. Here, we performed an ultra-high field fMRI (7T) experiment, comprising perception, learning and retrieval sessions. We observed a fundamental difference between representations in hippocampus and high-level visual cortex during perception and retrieval. First, while object-selective posterior fusiform cortex showed consistent responses that allowed us to decode object identity across both perception and retrieval one day after learning, object decoding in hippocampus was much stronger during retrieval than perception. Second, in visual cortex but not hippocampus, there was consistency in response patterns between perception and retrieval, suggesting that substantial neural populations are shared for both perception and retrieval. Finally, the decoding in hippocampus during retrieval was not observed when retrieval was tested on the same day as learning suggesting that the retrieval process itself is not sufficient to elicit decodable object representations. Collectively, these findings suggest that while cortical representations are stable between perception and retrieval, hippocampal representations are much stronger during retrieval, implying some form of reorganization of the representations between perception and retrieval.

Differential Sampling of Visual Space in Ventral and Dorsal Early Visual Cortex.

A fundamental feature of cortical visual processing is the separation of visual processing for the upper and lower visual fields. In early visual cortex (EVC), the upper visual field is processed ventrally, with the lower visual field processed dorsally. This distinction persists into several category-selective regions of occipitotemporal cortex, with ventral and lateral scene-, face-, and object-selective regions biased for the upper and lower visual fields, respectively. Here, using an elliptical population receptive field (pRF) model, we systematically tested the sampling of visual space within ventral and dorsal divisions of human EVC in both male and female participants. We found that (1) pRFs tend to be elliptical and oriented toward the fovea with distinct angular distributions for ventral and dorsal divisions of EVC, potentially reflecting a radial bias; and (2) pRFs in ventral areas were larger (∼1.5×) and more elliptical (∼1.2×) than those in dorsal areas. These differences potentially reflect a tendency for receptive fields in ventral temporal cortex to overlap the fovea with less emphasis on precise localization and isotropic representation of space compared with dorsal areas. Collectively, these findings suggest that ventral and dorsal divisions of EVC sample visual space differently, likely contributing to and/or stemming from the functional differentiation of visual processing observed in higher-level regions of the ventral and dorsal cortical visual pathways.SIGNIFICANCE STATEMENT The processing of visual information from the upper and lower visual fields is separated in visual cortex. Although ventral and dorsal divisions of early visual cortex (EVC) are commonly assumed to sample visual space equivalently, we demonstrate systematic differences using an elliptical population receptive field (pRF) model. Specifically, we demonstrate that (1) ventral and dorsal divisions of EVC exhibit diverging distributions of pRF angle, which are biased toward the fovea; and (2) ventral pRFs exhibit higher aspect ratios and cover larger areas than dorsal pRFs. These results suggest that ventral and dorsal divisions of EVC sample visual space differently and that such differential sampling likely contributes to different functional roles attributed to the ventral and dorsal pathways, such as object recognition and visually guided attention, respectively.

Differential impact of reward and punishment on functional connectivity after skill learning.

Reward and punishment shape behavior, but the mechanisms underlying their effect on skill learning are not well understood. Here, we tested whether the functional connectivity of premotor cortex (PMC), a region known to be critical for learning of sequencing skills, is altered after training when reward or punishment is given during training. Resting-state fMRI was collected in two experiments before and after participants trained on either a serial reaction time task (SRTT; n = 36) or force-tracking task (FTT; n = 36) with reward, punishment, or control feedback. In each experiment, training-related change in PMC functional connectivity was compared across feedback groups. In both tasks, we found that reward and punishment differentially affected PMC functional connectivity. On the SRTT, participants trained with reward showed an increase in functional connectivity between PMC and cerebellum as well as PMC and striatum, while participants trained with punishment showed an increase in functional connectivity between PMC and medial temporal lobe connectivity. After training on the FTT, subjects trained with control and reward showed increases in PMC connectivity with parietal and temporal cortices after training, while subjects trained with punishment showed increased PMC connectivity with ventral striatum. While the results from the two experiments overlapped in some areas, including ventral pallidum, temporal lobe, and cerebellum, these regions showed diverging patterns of results across the two tasks for the different feedback conditions. These findings suggest that reward and punishment strongly influence spontaneous brain activity after training, and that the regions implicated depend on the task learned.

Finding the baby in the bath water - evidence for task-specific changes in resting state functional connectivity evoked by training.

Resting-state functional connectivity (rsFC) between brain regions has been used for studying training-related changes in brain function during the offline period of skill learning. However, it is difficult to infer whether the observed training-related changes in rsFC measured between two scans occur as a consequence of task performance, whether they are specific to a given task, or whether they reflect confounding factors such as diurnal fluctuations in brain physiology that impact the MRI signal. Here, we sought to elucidate whether task-specific changes in rsFC are dissociable from time-of-day related changes by evaluating rsFC changes after participants were provided training in either a visuospatial task or a motor sequence task compared to a non-training condition. Given the nature of the tasks, we focused on changes in rsFC of the hippocampal and sensorimotor cortices after short-term training, while controlling for the effect of time-of-day. We also related the change in rsFC of task-relevant brain regions to performance improvement in each task. Our results demonstrate that, even in the absence of any experimental manipulation, significant changes in rsFC can be detected between two resting state functional MRI scans performed just a few hours apart, suggesting time-of-day has a significant impact on rsFC. However, by estimating the magnitude of the time-of-day effect, our findings also suggest that task-specific changes in rsFC can be dissociated from the changes attributed to time-of-day. Taken together, our results show that rsFC can provide insights about training-related changes in brain function during the offline period of skill learning. However, demonstrating the specificity of the changes in rsFC to a given task requires a rigorous experimental design that includes multiple active and passive control conditions, and robust behavioral measures.

Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic images.

Numerous factors have been reported to underlie the representation of complex images in high-level human visual cortex, including categories (e.g. faces, objects, scenes), animacy, and real-world size, but the extent to which this organization reflects behavioral judgments of real-world stimuli is unclear. Here, we compared representations derived from explicit behavioral similarity judgments and ultra-high field (7T) fMRI of human visual cortex for multiple exemplars of a diverse set of naturalistic images from 48 object and scene categories. While there was a significant correlation between similarity judgments and fMRI responses, there were striking differences between the two representational spaces. Behavioral judgements primarily revealed a coarse division between man-made (including humans) and natural (including animals) images, with clear groupings of conceptually-related categories (e.g. transportation, animals), while these conceptual groupings were largely absent in the fMRI representations. Instead, fMRI responses primarily seemed to reflect a separation of both human and non-human faces/bodies from all other categories. Further, comparison of the behavioral and fMRI representational spaces with those derived from the layers of a deep neural network (DNN) showed a strong correspondence with behavior in the top-most layer and with fMRI in the mid-level layers. These results suggest a complex relationship between localized responses in high-level visual cortex and behavioral similarity judgments - each domain reflects different properties of the images, and responses in high-level visual cortex may correspond to intermediate stages of processing between basic visual features and the conceptual categories that dominate the behavioral response.

Deconstructing multivariate decoding for the study of brain function.

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function.

Impact of time-of-day on diffusivity measures of brain tissue derived from diffusion tensor imaging.

Diurnal fluctuations in MRI measures of structural and functional properties of the brain have been reported recently. These fluctuations may have a physiological origin, since they have been detected using different MRI modalities, and cannot be explained by factors that are typically known to confound MRI measures. While preliminary evidence suggests that measures of structural properties of the brain based on diffusion tensor imaging (DTI) fluctuate as a function of time-of-day (TOD), the underlying mechanism has not been investigated. Here, we used a longitudinal within-subjects design to investigate the impact of time-of-day on DTI measures. In addition to using the conventional monoexponential tensor model to assess TOD-related fluctuations, we used a dual compartment tensor model that allowed us to directly assess if any change in DTI measures is due to an increase in CSF/free-water volume fraction or due to an increase in water diffusivity within the parenchyma. Our results show that Trace or mean diffusivity, as measured using the conventional monoexponential tensor model tends to increase systematically from morning to afternoon scans at the interface of grey matter/CSF, most prominently in the major fissures and the sulci of the brain. Interestingly, in a recent study of the glymphatic system, these same regions were found to show late enhancement after intrathecal injection of a CSF contrast agent. The increase in Trace also impacts DTI measures of diffusivity such as radial and axial diffusivity, but does not affect fractional anisotropy. The dual compartment analysis revealed that the increase in diffusivity measures from PM to AM was driven by an increase in the volume fraction of CSF-like free-water. Taken together, our findings provide important insight into the likely physiological origins of diurnal fluctuations in MRI measurements of structural properties of the brain.