Multivoxel Pattern Analysis Research Articles

Dynamic spatial coding in parietal cortex mediates tactile-motor transformation

Movements towards touch on the body require integrating tactile location and body posture information. Tactile processing and movement planning both rely on posterior parietal cortex (PPC) but their interplay is not understood. Here, human participants received tactile stimuli on their crossed and uncrossed feet, dissociating stimulus location relative to anatomy versus external space. Participants pointed to the touch or the equivalent location on the other foot, which dissociates sensory and motor locations. Multi-voxel pattern analysis of concurrently recorded fMRI signals revealed that tactile location was coded anatomically in anterior PPC but spatially in posterior PPC during sensory processing. After movement instructions were specified, PPC exclusively represented the movement goal in space, in regions associated with visuo-motor planning and with regional overlap for sensory, rule-related, and movement coding. Thus, PPC flexibly updates its spatial codes to accommodate rule-based transformation of sensory input to generate movement to environment and own body alike.

Disturbance of information in superior parietal lobe during dual-task interference in a simulated driving task

Performing a secondary task while driving causes a decline in driving performance. This phenomenon, called dual-task interference, can have lethal consequences. Previous fMRI studies have looked at the changes in the average brain activity to uncover the neural correlates of dual-task interference. From these results, it is unclear whether the overall modulations in brain activity result from general effects such as task difficulty, attentional modulations, and mental effort or whether it is caused by a change in the responses specific to each condition due to dual-task interference. To overcome this limitation, here, we used multi-voxel pattern analysis (MVPA) to interrogate the change in the information content in multiple brain regions during dual-task interference in simulated driving. Participants performed a lane-change task in a simulated driving environment, along with a tone discrimination task with either short or long onset time difference (Stimulus Onset Asynchrony, SOA) between the two tasks. Behavioral results indicated a robust dual-task effect on lane-change reaction time (RT). MVPA revealed regions that carry information about the driving lane-change direction (shift right/shift left), including the superior parietal lobe (SPL), visual, and motor regions. Comparison of decoding accuracies across SOA conditions in the SPL region revealed lower accuracy in the short compared to the long SOA condition. This change in accuracy was not observed in the visual and motor regions. These findings suggest that the dual-task interference in driving may be related to the disturbance of information processing in the SPL region.

Grasping with a twist: Dissociating action goals from motor actions in human frontoparietal circuits.

In daily life, prehension is typically not the end goal of hand-object interactions but a precursor for manipulation. Nevertheless, functional MRI (fMRI) studies investigating manual manipulation have primarily relied on prehension as the end goal of an action. Here, we used slow event-related fMRI to investigate differences in neural activation patterns between prehension in isolation and prehension for object manipulation. Sixteen (7 males and 9 females) participants were instructed either to simply grasp the handle of a rotatable dial (isolated prehension) or to grasp and turn it (prehension for object manipulation). We used representational similarity analysis to investigate whether the experimental conditions could be discriminated from each other based on differences in task-related brain activation patterns. We also used temporal multivoxel pattern analysis to examine the evolution of regional activation patterns over time. Importantly, we were able to differentiate isolated prehension and prehension for manipulation from activation patterns in the early visual cortex, the caudal intraparietal sulcus, and the superior parietal lobule. Our findings indicate that object manipulation extends beyond the putative cortical grasping network (anterior intraparietal sulcus, premotor and motor cortices) to include the superior parietal lobule and early visual cortex.Significance statement:A simple act such as turning an oven dial requires not only that the central nervous system encode the initial state (starting dial orientation) of the object but also the appropriate posture to grasp it in order to achieve the desired end state (final dial orientation) and the motor commands to achieve that state. Using advanced temporal neuroimaging analysis techniques, we reveal how such actions unfold over time and how they differ between object manipulation (turning a dial) vs. grasping alone. We find that a combination of brain areas implicated in visual processing and sensorimotor integration can distinguish between the complex and simple tasks during planning, with neural patterns that approximate those during the actual execution of the action.

Machine Learning-assisted Quantitative Mapping of Intracortical Axonal Plasticity Following a Focal Cortical Stroke in Rodents.

Stroke destroys neurons and their connections leading to focal neurological deficits. Although limited, many patients exhibit a certain degree of spontaneous functional recovery. Structural remodeling of the intracortical axonal connections is implicated in the reorganization of cortical motor representation maps, which is considered to be an underlying mechanism of the improvement in motor function. Therefore, an accurate assessment of intracortical axonal plasticity would be necessary to develop strategies to facilitate functional recovery following a stroke. The present study developed a machine learning-assisted image analysis tool based on multi-voxel pattern analysis in fMRI imaging. Intracortical axons originating from the rostral forelimb area (RFA) were anterogradely traced using biotinylated dextran amine (BDA) following a photothrombotic stroke in the mouse motor cortex. BDA-traced axons were visualized in tangentially sectioned cortical tissues, digitally marked, and converted to pixelated axon density maps. Application of the machine learning algorithm enabled sensitive comparison of the quantitative differences and the precise spatial mapping of the post-stroke axonal reorganization even in the regions with dense axonal projections. Using this method, we observed a substantial extent of the axonal sprouting from the RFA to the premotor cortex and the peri-infarct region caudal to the RFA. Therefore, the machine learningassisted quantitative axonal mapping developed in this study can be utilized to discover intracortical axonal plasticity that may mediate functional restoration following stroke.

Pattern classification based on the amygdala does not predict an individual's response to emotional stimuli.

Functional magnetic resonance imaging (fMRI) studies have often recorded robust univariate group effects in the amygdala of subjects exposed to emotional stimuli. Yet it is unclear to what extent this effect also holds true when multi-voxel pattern analysis (MVPA) is applied at the level of the individual participant. Here we sought to answer this question. To this end, we combined fMRI data from two prior studies (N = 112). For each participant, a linear support vector machine was trained to decode the valence of emotional pictures (negative, neutral, positive) based on brain activity patterns in either the amygdala (primary region-of-interest analysis) or the whole-brain (secondary exploratory analysis). The accuracy score of the amygdala-based pattern classifications was statistically significant for only a handful of participants (4.5%) with a mean and standard deviation of 37% ± 5% across all subjects (range: 28-58%; chance-level: 33%). In contrast, the accuracy score of the whole-brain pattern classifications was statistically significant in roughly half of the participants (50.9%), and had an across-subjects mean and standard deviation of 49% ± 6% (range: 33-62%). The current results suggest that the information conveyed by the emotional pictures was encoded by spatially distributed parts of the brain, rather than by the amygdala alone, and may be of particular relevance to studies that seek to target the amygdala in the treatment of emotion regulation problems, for example via real-time fMRI neurofeedback training.

Multivariate prediction of long COVID headache in adolescents using gray matter structural MRI features.

Headache is among the most frequent symptoms after coronavirus disease 2019 (COVID-19), so-called long COVID syndrome. Although distinct brain changes have been reported in patients with long COVID, such reported brain changes have not been used for predictions and interpretations in a multivariate manner. In this study, we applied machine learning to assess whether individual adolescents with long COVID can be accurately distinguished from those with primary headaches. Twenty-three adolescents with long COVID headaches with the persistence of headache for at least 3 months and 23 age- and sex-matched adolescents with primary headaches (migraine, new daily persistent headache, and tension-type headache) were enrolled. Multivoxel pattern analysis (MVPA) was applied for disorder-specific predictions of headache etiology based on individual brain structural MRI. In addition, connectome-based predictive modeling (CPM) was also performed using a structural covariance network. MVPA correctly classified long COVID patients from primary headache patients, with an area under the curve of 0.73 (accuracy = 63.4%; permutation p = 0.001). The discriminating GM patterns exhibited lower classification weights for long COVID in the orbitofrontal and medial temporal lobes. The CPM using the structural covariance network achieved an area under the curve of 0.81 (accuracy = 69.5%; permutation p = 0.005). The edges that classified long COVID patients from primary headache were mainly comprising thalamic connections. The results suggest the potential value of structural MRI-based features for classifying long COVID headaches from primary headaches. The identified features suggest that the distinct gray matter changes in the orbitofrontal and medial temporal lobes occurring after COVID, as well as altered thalamic connectivity, are predictive of headache etiology.

Talking with hands and feet: Selective somatosensory attention and fMRI enable robust and convenient brain-based communication

In brain-based communication, voluntarily modulated brain signals (instead of motor output) are utilized to interact with the outside world. The possibility to circumvent the motor system constitutes an important alternative option for severely paralyzed. Most communication brain-computer interface (BCI) paradigms require intact visual capabilities and impose a high cognitive load, but for some patients, these requirements are not given. In these situations, a better-suited, less cognitively demanding information-encoding approach may exploit auditorily-cued selective somatosensory attention to vibrotactile stimulation. Here, we propose, validate and optimize a novel communication-BCI paradigm using differential fMRI activation patterns evoked by selective somatosensory attention to tactile stimulation of the right hand or left foot. Using cytoarchitectonic probability maps and multi-voxel pattern analysis (MVPA), we show that the locus of selective somatosensory attention can be decoded from fMRI-signal patterns in (especially primary) somatosensory cortex with high accuracy and reliability, with the highest classification accuracy (85.93%) achieved when using Brodmann area 2 (SI-BA2) at a probability level of 0.2. Based on this outcome, we developed and validated a novel somatosensory attention-based yes/no communication procedure and demonstrated its high effectiveness even when using only a limited amount of (MVPA) training data. For the BCI user, the paradigm is straightforward, eye-independent, and requires only limited cognitive functioning. In addition, it is BCI-operator friendly given its objective and expertise-independent procedure. For these reasons, our novel communication paradigm has high potential for clinical applications.

The involvement of the semantic neural network in rule identification of mathematical processing

The role of the visuospatial network in mathematical processing has been established, but the involvement of the semantic network in mathematical processing is still poorly understood. The current study utilized a number series completion paradigm with the event-related potential (ERP) technique to examine whether the semantic network supports mathematical processing and to find the corresponding spatiotemporal neural marker. In total, 32 right-handed undergraduate students were recruited and asked to complete the number series completion as well as the arithmetical computation task in which numbers were presented in sequence. The event-related potential and multi-voxel pattern analysis showed that the rule identification process involves more semantic processing when compared with the arithmetical computation processes, and it elicited higher amplitudes for the late negative component (LNC) in left frontal and temporal lobes. These results demonstrated that the semantic network supports the rule identification in mathematical processing, with the LNC acting as the neural marker.

Deciphering Functional Connectivity Differences Between Motor Imagery and Execution of Target-Oriented Grasping.

This study aimed to delineate overlapping and distinctive functional connectivity in visual motor imagery, kinesthetic motor imagery, and motor execution of target-oriented grasping action of the right hand. Functional magnetic resonance imaging data were obtained from 18 right-handed healthy individuals during each condition. Seed-based connectivity and multi-voxel pattern analyses were employed after selecting seed regions with the left primary motor cortex and supplementary motor area. There was equivalent seed-based connectivity during the three conditions in the bilateral frontoparietal and temporal areas. When the seed region was the left primary motor cortex, increased connectivity was observed in the left cuneus and superior frontal area during visual and kinesthetic motor imageries, respectively, compared with that during motor execution. Multi-voxel pattern analyses revealed that each condition was differentiated by spatially distributed connectivity patterns of the left primary motor cortex within the right cerebellum VI, cerebellum crus II, and left lingual area. When the seed region was the left supplementary motor area, the connectivity patterns within the right putamen, thalamus, cerebellar areas IV-V, and left superior parietal lobule were significantly classified above chance level across the three conditions. The present findings improve our understanding of the spatial representation of functional connectivity and its specific patterns among motor imagery and motor execution. The strength and fine-grained connectivity patterns of the brain areas can discriminate between motor imagery and motor execution.

Neither Enhanced Nor Lost: The Unique Role of Attention in Children's Neural Representations.

A defining feature of children's cognition is the especially slow development of their attention. Despite a rich behavioral literature characterizing the development of attention, little is known about how developing attentional abilities modulate neural representations in children. This information is critical to understanding how attentional development shapes the way children process information. One possibility is that attention might be less likely to shape neural representations in children as compared with adults. In particular, representations of attended items may be less likely to be enhanced relative to unattended items. To investigate this possibility, we measured brain activity using fMRI while children (seven to nine years; male and female) and adults (21-31 years; male and female) performed a one-back task in which they were directed to attend to either motion direction or an object in a display where both were present. We used multivoxel pattern analysis to compare decoding accuracy of attended and unattended information. Consistent with attentional enhancement, we found higher decoding accuracy for task-relevant information (i.e., objects in the object-attended condition) than for task-irrelevant information (i.e., motion in the object-attended condition) in adults' visual cortices. However, in children's visual cortices, both task-relevant and task-irrelevant information were decoded equally well. What is more, whole-brain analysis showed that the children represented task-irrelevant information more than adults in multiple regions across the brain, including the prefrontal cortex. These findings show that (1) attention does not modulate neural representations in the child visual cortex, and (2) developing brains can, and do, represent more information than mature brains.SIGNIFICANCE STATEMENT Children have been shown to struggle with maintaining their attention to specific information, and at the same time, can show better learning of "distractors." While these are critical properties of childhood, their underlying neural mechanisms are unknown. To fill in this critical knowledge gap, we explored how attention shapes what is represented in children's and adults' brains using fMRI while both were asked to focus on just one of two things (objects and motion). We found that unlike adults, who prioritize the information they were asked to focus on, children represent both what they were asked to prioritize and what they were asked to ignore. This shows that attention has a fundamentally different impact on children's neural representations.

What multiplexing means for the interpretation of functional MRI data.

Despite technology advances that have enabled routine acquisition of functional MRI data with sub-millimeter resolution, the inferences that cognitive neuroscientists must make to link fMRI data to behavior are complicated. Thus, a single dataset subjected to different analyses can be interpreted in different ways. This article presents two optical analogies that can be useful for framing fMRI analyses in a way that allows for multiple interpretations of fMRI data to be valid simultaneously without undermining each other. The first is reflection: when an object is reflected in a mirrored surface, it appears as if the reflected object is sharing space with the mirrored object, but of course it is not. This analogy can be a good guide for interpreting the fMRI signal, since even at sub-millimeter resolutions the signal is determined by a mixture of local and long-range neural computations. The second is refraction. If we view an object through a multi-faceted prism or gemstone, our view will change-sometimes dramatically-depending on our viewing angle. In the same way, interpretation of fMRI data (inference of underlying neuronal activity) can and should be different depending on the analysis approach. Rather than representing a weakness of the methodology, or the superiority of one approach over the other (for example, simple regression analysis versus multi-voxel pattern analysis), this is an expected consequence of how information is multiplexed in the neural networks of the brain: multiple streams of information are simultaneously present in each location. The fact that any one analysis typically shows only one view of the data also puts some parentheses around fMRI practitioners' constant search for ground truth against which to compare their data. By holding our interpretations lightly and understanding that many interpretations of the data can all be true at the same time, we do a better job of preparing ourselves to appreciate, and eventually understand, the complexity of the brain and the behavior it produces.

A sculpting effect of reading on later representational quality of phonology revealed by multi-voxel pattern analysis in young children

Using univariate analysis, a previous study by Wang et al. (2020) found a scaffolding effect of earlier phonological representation in superior temporal gyrus (STG) on later reading skill but failed to observe a sculpting effect of earlier reading on later phonological representation. The current study applied multi-voxel pattern analysis (MVPA) to examine if both scaffolding and sculpting effects were present in young children. We found that better initial reading skill predicted higher decoding coefficient of brain activity patterns for phonological representations in STG. This sculpting effect was present only for decoding small grain sizes (phonemes) and in younger children (6- to 7.5-year-olds), as we did not find any effects for large grain sizes (rhymes) or older children (7.5- to 9.5-year-olds). Although a scaffolding effect was not observed, the current study provides the first neural evidence of how earlier reading sculpts later phonological awareness in beginning readers.

MULTI-VOXEL PATTERN ANALYSIS OF fMRI DATA DURING SELF- AND OTHER-REFERENTIAL PROCESSING

The study of brain activity in the processing of self-referential information, as compared to the processing of information related to other people, is based on the application of mass-univariate analysis, based on the assumption that activity in one region is independent of activity in other regions. Recently, there has been a growing interest in neuroimaging to investigate spatially distributed information using multivariate approaches such as multivoxel pattern analysis (MVPA). In this paper, we used MVPA to analyze fMRI data recorded during self-evaluation and evaluation of other people of varying proximity. In all pairwise classifications tested, the number of correct identifications was significantly higher than the level of random matches. Predictively significant structures were widely distributed over different brain regions and included areas of the visual, lateral prefrontal, and many other cortical areas in addition to the cortical midline structures that contributed the most. In the self-other classification, ventral areas of the medial prefrontal and cingulate cortex were the most informative for the self condition, whereas parietal and occipital medial areas were the most informative for the other condition. The combination of brain structures, which included the anterior cingulate cortex and both amygdalae, revealed by principal component analysis, correlated positively with the psychometric scale of sensitivity to reward, and negatively with neuroticism scales. Overall, the results show the fruitfulness of using machine learning methods to analyze data from such kinds of experiments.

The default mode network is associated with changes in internalizing and externalizing problems differently in adolescent boys and girls.

Internalizing and externalizing problems that emerge during adolescence differentially increase boys' and girls' risk for developing psychiatric disorders. It is not clear, however, whether there are sex differences in the intrinsic functional architecture of the brain that underlie changes in the severity of internalizing and externalizing problems in adolescents. Using resting-state fMRI data and self-reports of behavioral problems obtained from 128 adolescents (73 females; 9-14 years old) at two timepoints, we conducted multivoxel pattern analysis to identify resting-state functional connectivity markers at baseline that predict changes in the severity of internalizing and externalizing problems in boys and girls 2 years later. We found sex-differentiated involvement of the default mode network in changes in internalizing and externalizing problems. Whereas changes in internalizing problems were associated with the dorsal medial subsystem in boys and with the medial temporal subsystem in girls, changes in externalizing problems were predicted by hyperconnectivity between core nodes of the DMN and frontoparietal network in boys and hypoconnectivity between the DMN and affective networks in girls. Our results suggest that different neural mechanisms predict changes in internalizing and externalizing problems in adolescent boys and girls and offer insights concerning mechanisms that underlie sex differences in the expression of psychopathology in adolescence.

High and low worriers do not differ in unstimulated resting-state brain connectivity

Chronic, excessive and uncontrollable worry presents an anxiety rising and distressing mental activity relevant in a range of psychological disorders. Task based studies investigating its underlying neural mechanisms reveal fairly heterogenous results. The current study aimed to investigate pathological worry related effects on the functional neural network architecture in the resting unstimulated brain. Using resting-state functional magnetic resonance imaging (rsfMRI) we compared functional connectivity (FC) patterns between 21 high worriers and 21 low worriers. We, on the one hand, conducted a seed-to-voxel analysis based on recent meta-analytic findings and, on the other hand, implemented a data-driven multi voxel pattern analysis (MVPA) approach to yield brain clusters showing connectivity differences between the two groups. Additionally, the seed regions and MVPA were used to investigate whether whole brain connectivity is associated with momentary state worry across groups. The data did not reveal differences in resting-state FC related to pathological worry, neither by the seed-to-voxel or MVPA approach testing for differences linked to trait worry nor by using the MVPA to test for state worry related aberrations. We discuss whether the null findings in our analyses are related to spontaneous fluctuations in momentary worry and the associated presence of multiple fluctuating brain states that could cause mutually cancelling effects. For future studies investigating the neural correlates of excessive worry, we propose a direct worry induction for better control of the situation.

Fear in the mind's eye: the neural correlates of differential fear acquisition to imagined conditioned stimuli.

Mental imagery is involved in both the expression and treatment of fear-related disorders such as anxiety and post-traumatic stress disorder. However, the neural correlates associated with the acquisition and generalization of differential fear conditioning to imagined conditioned stimuli are relatively unknown. In this study, healthy human participants (n = 27) acquired differential fear conditioning to imagined conditioned stimuli paired with a physical unconditioned stimulus (i.e.mild shock), as measured via self-reported fear, the skin conductance response and significant right anterior insula (aIn) activation. Multivoxel pattern analysis cross-classification also demonstrated that the pattern of activity in the right aIn during imagery acquisition was quantifiably similar to the pattern produced by standard visual acquisition. Additionally, mental imagery was associated with significant differential fear generalization. Fear conditioning acquired to imagined stimuli generalized to viewing those same stimuli as measured with self-reported fear and right aIn activity, and likewise fear conditioning to visual stimuli was associated with significant generalized differential self-reported fear and right aIn activity when imagining those stimuli. Together, the study provides a novel understanding of the neural mechanisms associated with the acquisition of differential fear conditioning to imagined stimuli and that of the relationship between imagery and emotion more generally.

Distinct neural representations of hand movement direction between motor imagery and execution in the presupplementary motor area

Motor simulation theory proposes a functional equivalence between motor execution (ME) and its simulation, suggesting that motor imagery (MI) is the self-intentioned simulation of one’s actions. This study used functional magnetic resonance imaging (fMRI) with multivoxel pattern analysis to test whether the direction of hand movement is represented with a similar neural code between ME and MI. In our study, participants used their right hand to move an on-screen cursor in the left–right direction with a joystick or imagined the same movement without execution. The results indicated that the left–right direction as well as their modality (ME or MI) could be decoded significantly above the chance level in the presupplementary motor area (pre-SMA) and primary visual cortex (V1). Next, we used activation patterns of ME as inputs to the decoder to predict hand move directions in MI sessions and found a significantly higher-than-chance accuracy only in V1, not in pre-SMA. Moreover, the representational similarity analysis showed similar activation patterns for the same directions between ME and MI in V1 but not in pre-SMA. This study’s finding indicates distinct spatial activation patterns for movement directions between ME and MI in pre-SMA.

Cortical areas involved in grasping and reaching actions with and without visual information: An ALE meta-analysis of neuroimaging studies.

The functional specialization of the ventral stream in Perception and the dorsal stream in Action is the cornerstone of the leading model proposed by Goodale and Milner in 1992. This model is based on neuropsychological evidence and has been a matter of debate for almost three decades, during which the dual-visual stream hypothesis has received much attention, including support and criticism. The advent of functional magnetic resonance imaging (fMRI) has allowed investigating the brain areas involved in Perception and Action, and provided useful data on the functional specialization of the two streams. Research on this topic has been quite prolific, yet no meta-analysis so far has explored the spatial convergence in the involvement of the two streams in Action. The present meta-analysis (N=53 fMRI and PET studies) was designed to reveal the specific neural activations associated with Action (i.e., grasping and reaching movements), and the extent to which visual information affects the involvement of the two streams during motor control. Our results provide a comprehensive view of the consistent and spatially convergent neural correlates of Action based on neuroimaging studies conducted over the past two decades. In particular, occipital-temporal areas showed higher activation likelihood in the Vision compared to the No vision condition, but no difference between reach and grasp actions. Frontal-parietal areas were consistently involved in both reach and grasp actions regardless of visual availability. We discuss our results in light of the well-established dual-visual stream model and frame these findings in the context of recent discoveries obtained with advanced fMRI methods, such as multivoxel pattern analysis.

Altered engagement of the speech motor network is associated with reduced phonological working memory in autism

Nonword repetition, a common clinical measure of phonological working memory, involves component processes of speech perception, working memory, and speech production. Autistic children often show behavioral challenges in nonword repetition, as do many individuals with communication disorders. It is unknown which subprocesses of phonological working memory are vulnerable in autistic individuals, and whether the same brain processes underlie the transdiagnostic difficulty with nonword repetition. We used functional magnetic resonance imaging (fMRI) to investigate the brain bases for nonword repetition challenges in autism. We compared activation during nonword repetition in functional brain networks subserving speech perception, working memory, and speech production between neurotypical and autistic children. Autistic children performed worse than neurotypical children on nonword repetition and had reduced activation in response to increasing phonological working memory load in the supplementary motor area. Multivoxel pattern analysis within the speech production network classified shorter vs longer nonword-repetition trials less accurately for autistic than neurotypical children. These speech production motor-specific differences were not observed in a group of children with reading disability who had similarly reduced nonword repetition behavior. These findings suggest that atypical function in speech production brain regions may contribute to nonword repetition difficulties in autism.

Investigation of Involvement between Specific Brain Regions and Evaluation Criteria Elements in a Two-Selections Task.

It is essential to understand the neural mechanisms underlying human decision-making. Several studies using traditional analysis have attempted to explain the neural mechanisms associated with decision-making based on abstract rewards. However, brain-decoding research that utilizes the multivoxel pattern analysis (MVPA) method, especially research focusing on decision-making, remains limited. In brain analysis, decoding strategies for multivoxels are required for various decision-making evaluation criteria. This is because in daily life, the human decision-making process makes use of many evaluation criteria. In the present study, we investigated the representation of evaluation criterion categories in a decision-making process using functional magnetic resonance imaging and MVPA. Participants performed a decision-making task that involved choosing a smartphone by referring to four types of evaluation criteria. The regions of interest (ROIs) were the ventromedial prefrontal cortex (vmPFC), nucleus accumbens (NAcc), and insula. Each combination of the four evaluation criteria was analyzed based on a binary classification using MVPA. From the binary classification accuracy obtained from MVPA, the regions that reflected differences in the evaluation criteria among the ROIs were evaluated. The results of the binary classification in the vmPFC and NAcc indicated that these regions can express evaluation criteria in decision-making processes.