Early neuroimaging studies using Cyberball suggested that social rejection activated the pain matrix, as identified in studies of physical pain. However, these early studies were characterized by small sample sizes. Our statistical multi-level kernel density analysis (MKDA) of Cyberball neuroimaging studies with 244 participants fails to support the claim that social rejection operates on the same pain matrix as nociceptive stimuli, questioning whether social pain is more figurative or literal. We also performed an MKDA of the neuroimaging studies of reliving a romantic rejection to test whether the pain matrix was activated if the rejection were more meaningful. Results again failed to support the notion that rejection activates the neural matrix identified in studies of physical pain. Reliving an unwanted rejection by a romantic partner was significantly characterized by activation within and beyond the “Cyberball” brain network, suggesting that the neural correlates of social pain are more complex than previously thought.
The ability to detect and rapidly process harmonic sounds, which in nature are typical of animal vocalizations and speech, can be critical for communication among conspecifics and for survival. Single-unit studies have reported neurons in auditory cortex sensitive to specific combinations of frequencies (e.g., harmonics), theorized to rapidly abstract or filter for specific structures of incoming sounds, where large ensembles of such neurons may constitute spectral templates. We studied the contribution of harmonic structure to activation of putative spectral templates in human auditory cortex by using a wide variety of animal vocalizations, as well as artificially constructed iterated rippled noises (IRNs). Both the IRNs and vocalization sounds were quantitatively characterized by calculating a global harmonics-to-noise ratio (HNR). Using functional MRI, we identified HNR-sensitive regions when presenting either artificial IRNs and/or recordings of natural animal vocalizations. This activation included regions situated between functionally defined primary auditory cortices and regions preferential for processing human nonverbal vocalizations or speech sounds. These results demonstrate that the HNR of sound reflects an important second-order acoustic signal attribute that parametrically activates distinct pathways of human auditory cortex. Thus, these results provide novel support for the presence of spectral templates, which may subserve a major role in the hierarchical processing of vocalizations as a distinct category of behaviorally relevant sound.
With regard to hearing perception, it remains unclear as to whether, or the extent to which, different conceptual categories of real-world sounds and related categorical knowledge are differentially represented in the brain. Semantic knowledge representations are reported to include the major divisions of living versus non-living things, plus more specific categories including animals, tools, biological motion, faces, and places-categories typically defined by their characteristic visual features. Here, we used functional magnetic resonance imaging (fMRI) to identify brain regions showing preferential activity to four categories of action sounds, which included non-vocal human and animal actions (living), plus mechanical and environmental sound-producing actions (nonliving). The results showed a striking antero-posterior division in cortical representations for sounds produced by living versus non-living sources. Additionally, there were several significant differences by category, depending on whether the task was category-specific (e.g. human or not) versus nonspecific (detect end-of-sound). In general, (1) human-produced sounds yielded robust activation in the bilateral posterior superior temporal sulci independent of task. Task demands modulated activation of left-lateralized fronto-parietal regions, bilateral insular cortices, and subcortical regions previously implicated in observation-execution matching, consistent with "embodied" and mirrorneuron network representations subserving recognition. (2) Animal action sounds preferentially activated the bilateral posterior insulae. (3) Mechanical sounds activated the anterior superior temporal gyri and parahippocampal cortices. (4) Environmental sounds preferentially activated dorsal occipital and medial parietal cortices. Overall, this multi-level dissociation of networks for preferentially representing distinct sound-source categories provides novel support for grounded cognition models that may underlie organizational principles for hearing perception.
Introduction. Brain imaging is becoming a powerful tool in the study of human cerebral functions related to close personal relationships. Outside of subcortical structures traditionally thought to be involved in reward-related systems, a wide range of neuroimaging studies in relationship science indicate a prominent role for different cortical networks and cognitive factors. Thus, the field needs a better anatomical/network/whole-brain model to help translate scientific knowledge from lab bench to clinical models and ultimately to the patients suffering from disorders associated with love and couple relationships. Aim. The aim of the present review is to provide a review across wide range of functional magnetic resonance imaging (fMRI) studies to critically identify the cortical networks associated with passionate love, and to compare and contrast it with other types of love (such as maternal love and unconditional love for persons with intellectual disabilities). Methods. Retrospective review of pertinent neuroimaging literature. Main Outcome Measures. Review of published literature on fMRI studies of love illustrating brain regions associated with different forms of love. Results. Although all fMRI studies of love point to the subcortical dopaminergic reward-related brain systems (involving dopamine and oxytocin receptors) for motivating individuals in pair-bonding, the present meta-analysis newly demonstrated that different types of love involve distinct cerebral networks, including those for higher cognitive functions such as social cognition and bodily self-representation. Conclusions. These metaresults provide the first stages of a global neuroanatomical model of cortical networks involved in emotions related to different aspects of love. Developing this model in future studies should be helpful for advancing clinical approaches helpful in sexual medicine and couple therapy. Ortigue S, Bianchi-Demicheli F, Patel N, Frum C, and Lewis JW. Neuroimaging of love: fMRI meta-analysis evidence toward new perspectives in sexual medicine.
Introduction.One of the most difficult dilemmas in relationship science and couple therapy concerns the interaction between sexual desire and love. As two mental states of intense longing for union with others, sexual desire and love are, in fact, often difficult to disentangle from one another. Aim. The present review aims to help understand the differences and similarities between these two mental states using a comprehensive statistical meta-analyses of all functional magnetic resonance imaging (fMRI) studies on sexual desire and love. Methods. Systematic retrospective review of pertinent neuroimaging literature. Main Outcome Measures. Review of published literature on fMRI studies illustrating brain regions associated with love and sexual desire to date. Results. Sexual desire and love not only show differences but also recruit a striking common set of brain areas that mediate somatosensory integration, reward expectation, and social cognition. More precisely, a significant posteriorto-anterior insular pattern appears to track sexual desire and love progressively. Conclusions. This specific pattern of activation suggests that love builds upon a neural circuit for emotions and pleasure, adding regions associated with reward expectancy, habit formation, and feature detection. In particular, the shared activation within the insula, with a posterior-to-anterior pattern, from desire to love, suggests that love grows out of and is a more abstract representation of the pleasant sensorimotor experiences that characterize desire. From these results, one may consider desire and love on a spectrum that evolves from integrative representations of affective visceral sensations to an ultimate representation of feelings incorporating mechanisms of reward expectancy and habit learning. Cacioppo S, Bianchi-Demicheli F, Frum C, Pfaus JG, and Lewis JW. The common neural bases between sexual desire and love: A multilevel kernel density fMRI analysis. J Sex Med 2012;9:1048-1054.
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