Interest has increased recently in correlations across brain regions in the resting-state fMRI blood oxygen level-dependent (BOLD) response, but little is known about the functional significance of these correlations. Here we directly test the behavioral relevance of the resting-state correlation between two face-selective regions in human brain, the occipital face area (OFA) and the fusiform face area (FFA). We found that the magnitude of the resting-state correlation, henceforth called functional connectivity (FC), between OFA and FFA correlates with an individual's performance on a number of face-processing tasks, not non-face tasks. Further, we found that the behavioral significance of the OFA/FFA FC is independent of the functional activation and the anatomical size of either the OFA or FFA, suggesting that face processing depends not only on the functionality of individual face-selective regions, but also on the synchronized spontaneous neural activity between them. Together, these findings provide strong evidence that the functional correlations in the BOLD response observed at rest reveal functionally significant properties of cortical processing. IntroductionRecently a number of functional magnetic resonance imaging (fMRI) studies have investigated neural activity in the human brain during periods of rest (when no stimuli are presented and no tasks are performed), and found that the spontaneous blood oxygenation level-dependent (BOLD) fluctuations are not random, but correlated across cortical regions with similar functional properties [for review, see Fox and Raichle (2007) and Greicius (2008)]. Further, these functional correlations are thought to reflect functional relationships mediated by anatomical connections (e.g., Vincent et al., 2007;Greicius et al., 2009;Honey et al., 2009). However, despite the abundance of work finding such correlations across cortical regions, little is known about the functional significance of these correlations: is synchronized spontaneous neural activity across cortical regions relevant for behavior, or is it merely epiphenomenal? Here we addressed this question by directly testing the behavioral significance of the resting-state correlations between two face-selective regions in the occipitotemporal cortex that are primarily involved in recognition of individual identity (Haxby et al., 2000;Calder and Young, 2005;Ishai, 2008)-the occipital face area (OFA) (Gauthier et al., 2000) and the fusiform face area (FFA) (Kanwisher et al., 1997)-found to be functionally correlated using resting-state fMRI (Nir et al., 2006;Zhang et al., 2009).First, we calculated the correlation in spontaneous BOLD fluctuations between OFA and FFA during the resting state in participants, and then behaviorally tested the same participants outside the scanner on a number of face and non-face tasks. If the correlation in spontaneous BOLD fluctuations between OFA and FFA, henceforth referred to as functional connectivity (FC), is behaviorally relevant, then we predict that the magnitude of the OF...

Most of human daily social interactions rely on the ability to successfully recognize faces. Yet ϳ2% of the human population suffers from face blindness without any acquired brain damage [this is also known as developmental prosopagnosia (DP) or congenital prosopagnosia]). Despite the presence of severe behavioral face recognition deficits, surprisingly, a majority of DP individuals exhibit normal face selectivity in the right fusiform face area (FFA), a key brain region involved in face configural processing. This finding, together with evidence showing impairments downstream from the right FFA in DP individuals, has led some to argue that perhaps the right FFA is largely intact in DP individuals. Using fMRI multivoxel pattern analysis, here we report the discovery of a neural impairment in the right FFA of DP individuals that may play a critical role in mediating their face-processing deficits. In seven individuals with DP, we discovered that, despite the right FFA's preference for faces and it showing decoding for the different face parts, it exhibited impaired face configural decoding and did not contain distinct neural response patterns for the intact and the scrambled face configurations. This abnormality was not present throughout the ventral visual cortex, as normal neural decoding was found in an adjacent object-processing region. To our knowledge, this is the first direct neural evidence showing impaired face configural processing in the right FFA in individuals with DP. The discovery of this neural impairment provides a new clue to our understanding of the neural basis of DP.

Numerous studies with functional magnetic resonance imaging have shown that the fusiform face area (FFA) in the human brain plays a key role in face perception. Recent studies have found that both the featural information of faces (e.g., eyes, nose, and mouth) and the configural information of faces (i.e., spatial relation among features) are encoded in the FFA. However, little is known about whether the featural information is encoded independent of or combined with the configural information in the FFA. Here we used multi-voxel pattern analysis to examine holistic representation of faces in the FFA by correlating spatial patterns of activation with behavioral performance in discriminating face parts with face configurations either present or absent. Behaviorally, the absence of face configurations (versus presence) impaired discrimination of face parts, suggesting a holistic representation in the brain. Neurally, spatial patterns of activation in the FFA were more similar among correct than incorrect trials only when face parts were presented in a veridical face configuration. In contrast, spatial patterns of activation in the occipital face area, as well as the object-selective lateral occipital complex, were more similar among correct than incorrect trials regardless of the presence of veridical face configurations. This finding suggests that in the FFA faces are represented not on the basis of individual parts but in terms of the whole that emerges from the parts.

Thermoelectric cells (TEC) directly convert heat into electricity via the Seebeck effect. Known as one TEC, thermogalvanic hydrogels are promising for harvesting low-grade thermal energy for sustainable energy production. In recent years, research on thermogalvanic hydrogels has increased dramatically due to their capacity to continuously convert heat into electricity with or without consuming the material. Until recently, the commercial viability of thermogalvanic hydrogels was limited by their low power output and the difficulty of packaging. In this review, we summarize the advances in electrode materials, redox pairs, polymer network integration approaches, and applications of thermogalvanic hydrogels. Then, we highlight the key challenges, that is, low-cost preparation, high thermoelectric power, long-time stable operation of thermogalvanic hydrogels, and broader applications in heat harvesting and thermoelectric sensing.