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Researchers generally agree that when upregulating and downregulating emotion, control regions in the prefrontal cortex turn up or down activity in affect-generating brain areas. However, the affective dial hypothesis that turning up and down emotions produces opposite effects in the same affect-generating regions is untested. We tested this hypothesis by examining the overlap between the regions activated during upregulation and those deactivated during downregulation in 54 male and 51 female humans. We found that upregulation and downregulation both recruit regulatory regions, such as the inferior frontal gyrus and dorsal anterior cingulate gyrus, but act on distinct affect-generating regions. Upregulation increased activity in regions associated with emotional experience, such as the amygdala, anterior insula, striatum, and anterior cingulate gyrus as well as in regions associated with sympathetic vascular activity, such as periventricular white matter, while downregulation decreased activity in regions receiving interoceptive input, such as the posterior insula and postcentral gyrus. Nevertheless, participants subjective sense of emotional intensity was associated with activity in overlapping brain regions (dorsal anterior cingulate, insula, thalamus, and frontal pole) across upregulation and downregulation. These findings indicate that upregulation and downregulation rely on overlapping brain regions to control and assess emotions but target different affect-generating brain regions.SIGNIFICANCE STATEMENT Many contexts require modulating ones own emotions. Identifying the brain areas implementing these regulatory processes should advance understanding emotional disorders and designing potential interventions. The emotion regulation field has an implicit assumption we call the affective dial hypothesis: both emotion upregulation and downregulation modulate the same emotion-generating brain areas. Countering the hypothesis, our findings indicate that up- and down-modulating emotions target different brain areas. Thus, the mechanisms underlying emotion regulation might differ more than previously appreciated for upregulation versus downregulation. In addition to their theoretical importance, these findings are critical for researchers attempting to target activity in particular brain regions during an emotion regulation intervention.

Pepper (Capsicum annuum) is an important vegetable crop that has been subjected to intensive breeding, resulting in limited genetic diversity, especially for sweet peppers. Previous studies have reported pepper draft genome assemblies using short read sequencing, but their capture of the extent of large structural variants (SVs), such as presence-absence variants (PAVs), inversions, and copy-number variants (CNVs) in the complex pepper genome falls short. In this study, we sequenced the genomes of representative sweet and hot pepper accessions by long-read and/or linked-read methods and advanced scaffolding technologies. First, we developed a high-quality reference genome for the sweet pepper cultivar Dempsey and then used the reference genome to identify SVs in 11 other pepper accessions and constructed a graph-based pan-genome for pepper. We annotated an average of 42 972 gene families in each pepper accession, defining a set of 19 662 core and 23 115 non-core gene families. The new pepper pan-genome includes informative variants, 222 159 PAVs, 12 322 CNVs, and 16 032 inversions. Pan-genome analysis revealed PAVs associated with important agricultural traits, including potyvirus resistance, fruit color, pungency, and pepper fruit orientation. Comparatively, a large number of genes are affected by PAVs, which is positively correlated with the high frequency of transposable elements (TEs), indicating TEs play a key role in shaping the genomic landscape of peppers. The datasets presented herein provide a powerful new genomic resource for genetic analysis and genome-assisted breeding for pepper improvement.

Previous research has shown associations between brain structure and resting state high-frequency heart rate variability (HF HRV). Age affects both brain structure and HF HRV. Therefore, we sought to examine the relationship between brain structure and HF HRV as a function of age. Data from two independent studies were used for the present analysis. Study 1 included 19 older adults (10 males, age range 62-78 years) and 19 younger adults (12 males, age range 19-37). Study 2 included 23 older adults (12 males; age range 55-75) and 27 younger adults (17 males; age range 18-34). The root-mean-square of successive R-R-interval differences (RMSSD) from ECG recordings was used as time-domain measure of HF HRV. MRI scans were performed on a 3.0-T Siemens Magnetom Trio scanner. Cortical reconstruction and volumetric segmentation were performed with the Freesurfer image analysis suite, including 12 regions as regions of interests (ROI). Zero-order and partial correlations were used to assess the correlation of RMSSD with cortical thickness in selected ROIs. Lateral orbitofrontal cortex (OFC) cortical thickness was significantly associated with RMSSD. Further, both studies, in line with previous research, showed correlations between RMSSD and anterior cingulate cortex (ACC) cortical thickness. Meta-analysis on adjusted correlation coefficients from individual studies confirmed an association of RMSSD with the left rostral ACC and the left lateral OFC. Future longitudinal studies are necessary to trace individual trajectories in the association of HRV and brain structure across aging.