Disentangling hand and tool processing: distal effects of neuromodulation

The neural processing within a brain region that responds to more than one object category can be separated by looking at the horizontal modulations established by that region, which suggests that local representations can be affected by connections to distal areas, in a category-specific way. Here we first wanted to test whether by applying transcranial direct current stimulation (tDCS) to a region that responds both to hands and tools (posterior middle temporal gyrus; pMTG), while participants performed either a hand- or tool-related training task, we would be able to specifically target the trained category, and thereby dissociate the overlapping neural processing. Second, we wanted to see if these effects were limited to the target area or extended to distal but functionally connected brain areas. After each combined tDCS and training session, participants therefore viewed images of tools, hands, and animals, in an fMRI scanner. Using multivoxel pattern analysis, we found that tDCS stimulation to pMTG indeed improved the classification accuracy between tools vs. animals, but only when combined with a tool training task (not a hand training task). However, surprisingly, tDCS stimulation to pMTG also improved the classification accuracy between hands vs. animals when combined with a tool training task (not a hand training task). Our findings suggest that overlapping but functionally-specific networks can be separated by using a category-specific training task together with tDCS - a strategy that can be applied more broadly to other cognitive domains using tDCS - and demonstrates the importance of horizontal modulations in object-category representations.

Neural Representations of the Committed Romantic Partner in the Nucleus Accumbens

Having an intimate romantic relationship is an important aspect of life. Dopamine-rich reward regions, including the nucleus accumbens (NAcc), have been identified as neural correlates for both emotional bonding with the partner and interest in unfamiliar attractive nonpartners. Here, we aimed to disentangle the overlapping functions of the NAcc using multivoxel pattern analysis, which can decode the cognitive processes encoded in particular neural activity. During functional MRI scanning, 46 romantically involved men performed the social-incentive-delay task, in which a successful response resulted in the presentation of a dynamic and positive facial expression from their partner and unfamiliar women. Multivoxel pattern analysis revealed that the spatial patterns of NAcc activity could successfully discriminate between romantic partners and unfamiliar women during the period in which participants anticipated the target presentation. We speculate that neural activity patterns within the NAcc represent the relationship partner, which might be a key neural mechanism for committed romantic relationships.

Resting state functional connectivity in relapsing remitting multiple sclerosis with mild disability – a data driven, whole brain multivoxel pattern analysis study

Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. The aim of the present study was to investigate RSFC differences between persons with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HCs). We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HCs. Significant group differences were noted in RSFC in 9 clusters distributed in 7 regions; right middle frontal gyrus, frontal medial cortex, left frontal pole, anterior cingulate gyrus, right middle temporal gyrus, left posterior middle temporal gyrus and right lateral occipital cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed significantly increased RSFC to the posterior brain regions (bilateral superior lateral occipital cortices, right lingual gyrus and left occipital pole) and reduced connectivity in the anterior and medial regions (right paracingulate gyrus, anterior cingulate gyrus, left amygdala and left frontal orbital cortex) in RRMS compared to HCs. The results of this study agree with the previous reports on abnormalities of RSFC in RRMS, the cognitive and clinical implications of which are discussed herein.

Vision-to-value transformations in artificial neural networks and human brain

Humans and now computers can derive subjective valuations from sensory events although such transformation process is essentially unknown. In this study, we elucidated unknown neural mechanisms by comparing convolutional neural networks (CNNs) to their corresponding representations in humans. Specifically, we optimized CNNs to predict aesthetic valuations of paintings and examined the relationship between the CNN representations and brain activity via multivoxel pattern analysis. Primary visual cortex and higher association cortex activities were similar to computations in shallow CNN layers and deeper layers, respectively. The vision-to-value transformation is hence proved to be a hierarchical process which is consistent with the principal gradient that connects unimodal to transmodal brain regions (i.e. default mode network). The activity of the frontal and parietal cortices was approximated by goal-driven CNN. Consequently, representations of the hidden layers of CNNs can be understood and visualized by their correspondence with brain activity–facilitating parallels between artificial intelligence and neuroscience.

Temporo-parietal cortex involved in modeling one’s own and others’ attention

In a traditional view, in social cognition, attention is equated with gaze and people track other people’s attention by tracking their gaze. Here, we used fMRI to test whether the brain represents attention in a richer manner. People read stories describing an agent (either oneself or someone else) directing attention to an object in one of two ways: either internally directed (endogenous) or externally induced (exogenous). We used multivoxel pattern analysis to examine how brain areas within the theory-of-mind network encoded attention type and agent type. Brain activity patterns in the left temporo-parietal junction (TPJ) showed significant decoding of information about endogenous versus exogenous attention. The left TPJ, left superior temporal sulcus (STS), precuneus, and medial prefrontal cortex (MPFC) significantly decoded agent type (self versus other). These findings show that the brain constructs a rich model of one’s own and others’ attentional state, possibly aiding theory of mind.

Characterizing the Structural Pattern of Heavy Smokers Using Multivoxel Pattern Analysis

Background: Smoking addiction is a major public health issue which causes a series of chronic diseases and mortalities worldwide. We aimed to explore the most discriminative gray matter regions between heavy smokers and healthy controls with a data-driven multivoxel pattern analysis technique, and to explore the methodological differences between multivoxel pattern analysis and voxel-based morphometry.Methods: Traditional voxel-based morphometry has continuously contributed to finding smoking addiction-related regions on structural magnetic resonance imaging. However, voxel-based morphometry has its inherent limitations. In this study, a multivoxel pattern analysis using a searchlight algorithm and support vector machine was applied on structural magnetic resonance imaging to identify the spatial pattern of gray matter volume in heavy smokers.Results: Our proposed method yielded a voxel-wise accuracy of at least 81% for classifying heavy smokers from healthy controls. The identified regions were primarily located at the temporal cortex and prefrontal cortex, occipital cortex, thalamus (bilateral), insula (left), anterior and median cingulate gyri, and precuneus (left).Conclusions: Our results suggested that several regions, which were seldomly reported in voxel-based morphometry analysis, might be latently correlated with smoking addiction. Such findings might provide insights for understanding the mechanism of chronic smoking and the creation of effective cessation treatment. Multivoxel pattern analysis can be efficient in locating brain discriminative regions which were neglected by voxel-based morphometry.

Neural Representations of Death in the Cortical Midline Structures Promote Temporal Discounting

Death is an important reminder that our lives are finite. Although some studies have shown that thinking about one’s own death increases temporal discounting (i.e., the devaluing of future rewards), the underlying neural mechanisms are still unknown. In a functional magnetic resonance imaging experiment, we compared the neural and behavioral processes of temporal discounting across four conditions involving distinct types of future thinking (death related, negative, neutral, and positive). Replicating prior research, the behavioral evidence showed that temporal discounting increased when thinking about one’s own future death. Multivoxel pattern analysis showed that death-related future thinking was decoded in default mode regions, including the inferior parietal lobule, precuneus, and medial prefrontal cortex (MPFC). When future thinking was death related (vs. negative), increased temporal discounting was associated with a higher decoding accuracy in the precuneus and MPFC. The present findings suggest that death-related neural representations are distributed across default mode regions, and neural populations in the cortical midline structures play a crucial role in the integration of one's own death into economic decision-making.