Happy people are always similar: The evidence from brain morphological and functional inter-subject correlations.

A fundamental question in the study of happiness is whether there is neural evidence to support a well-known hypothesis that happy people are always similar while unfortunate people have their own misfortunes. To investigate this, we employed several happiness-related questionnaires to identify potential components of happiness, and further investigated and confirmed their associations with personality, mood, aggressive behaviors, and amygdala reactivity to fearful faces within a substantial sample size of college students (n = 570). Additionally, we examined the functional and morphological similarities and differences among happy individuals using the inter-subject representational similarity analysis (IS-RSA). IS-RSA emphasizes the geometric properties in a high-dimensional space constructed by brain or behavioral patterns and focuses on individual subjects. Our behavioral findings unveiled two factors of happiness: individual and social, both of which mediated the effect of personality traits on individual aggression. Subsequently, mood mediated the impact of happiness on aggressive behaviors across two subgroup splits. Functional imaging data revealed that individuals with higher levels of happiness exhibited reduced amygdala reactivity to fearful faces, as evidenced by a conventional face-matching task (n = 104). Moreover, IS-RSA demonstrated that these participants manifested similar neural activation patterns when processing fearful faces within the visual pathway, but not within the emotional network (e.g., amygdala). Morphological observations (n = 425) indicated that individuals with similar high happiness levels exhibited comparable gray matter volume patterns within several networks, including the default mode network, fronto-parietal network, visual network, and attention network. Collectively, these findings offer early neural evidence supporting the proposition that happy individuals may share common neural characteristics.

The connectivity-based architecture of the human piriform cortex.

The anatomy of the human piriform cortex (PC) is poorly understood. We used a bimodal connectivity-based-parcellation approach to investigate subregions of the PC and its connectional differentiation from the amygdala. One hundred (55 % female) genetically unrelated subjects from the Human Connectome Project were included. A region of interest (ROI) was delineated bilaterally covering PC and amygdala, and functional and structural connectivity of this ROI with the whole gray matter was computed. Spectral clustering was performed to obtain bilateral parcellations at granularities of k = 2-10 clusters and combined bimodal parcellations were computed. Validity of parcellations was assessed via their mean individual-to-group similarity per adjusted rand index (ARI). Individual-to-group similarity was higher than chance in both modalities and in all clustering solutions. The amygdala was clearly distinguished from PC in structural parcellations, and olfactory amygdala was connectionally more similar to amygdala than to PC. At higher granularities, an anterior and ventrotemporal and a posterior frontal cluster emerged within PC, as well as an additional temporal cluster at their boundary. Functional parcellations also showed a frontal piriform cluster, and similar temporal clusters were observed with less consistency. Results from bimodal parcellations were similar to the structural parcellations. Consistent results were obtained in a validation cohort. Distinction of the human PC from the amygdala, including its olfactory subregions, is possible based on its structural connectivity alone. The canonical fronto-temporal boundary within PC was reproduced in both modalities and with consistency. All obtained parcellations are freely available.

The perirhinal cortex.

Anatomically, the perirhinal cortex sits at the boundary between the medial temporal lobe and the ventral visual pathway. It has prominent interconnections not only with both these systems, but also with a wide range of unimodal and polymodal association areas. Consistent with these diverse projections, neurophysiological studies reveal a multidimensional set of mnemonic signals that include stimulus familiarity, within- and between-domain associations, associative recall, and delay-based persistence. This wide range of perirhinal memory signals not only includes signals that are largely unique to the perirhinal cortex (i.e., object familiarity), consistent with dual-process theories, but also includes a range of signals (i.e., associative flexibility and recall) that are strongly associated with the hippocampus, consistent with single-process theories. These neurophysiological findings have important implications for bridging the gap between single-process and dual-process models of medial temporal lobe function.

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

The evolutionary trajectories of the individual amygdala nuclei in the common shrew, guinea pig, rabbit, fox and pig: A consequence of embryological fate and mosaic-like evolution.

The amygdala primarily evolved as a danger detector that regulates emotional behaviours and learning. However, it is also engaged in stress responses as well as olfactory/pheromonal and reproductive functions. All of these functions are processed by a set of nuclei which are derived from different telencephalic sources (pallial and subpallial) and have a unique cellular structure and specific connections. It is unclear how these individual anatomical and functional units evolved to fit the amygdala to the specific needs of various mammals. Thus, this study provides quantitative data regarding volumes, neuron density and neuron numbers in the main amygdala nuclei of the common shrew, guinea pig, rabbit, fox and pig - species from across the mammalian phylogeny which differ in brain complexity and ecology. The results show that the volume of the amygdala and its individual nuclei scale with negative allometry relative to brain mass (an allometric coefficient below one). However, in relation to the whole amygdala volume, volumes and volumetric percentages of the lateral (LA) and basomedial (BM) nuclei scale with positive allometry, for the medial (ME) and lateral olfactory tract (NLOT) nuclei these parameters scale with negative allometry while the values of these parameters for the basolateral (BL), central (CE) and cortical (CO) nuclei scale with isometry. Moreover, density of neurons scales with strong negative allometry relative to both brain mass and amygdala volume with values of allometric coefficient below zero across studied species. This value for BL is significantly lower than that for the whole amygdala, for ME it is significantly higher while values for NLOT, CE, CO, LA and BM are quite similar to the value for whole amygdala. Finally, neuron numbers in the whole amygdala and its individual nuclei scale with negative allometry in relation to brain mass. However, in relation to the number of neurons in the whole amygdala, neuron numbers and percentages of neurons for LA and BM scale with positive allometry, for BL and NLOT they scale with negative allometry while the values of these parameters for CE, CO and ME scale with isometry. In conclusion, all of these results indicate that each of the nuclei studied displays a different and unique pattern of evolution in relation to brain mass or the whole amygdala volume. These patterns do not match with the various classical concepts of amygdala parcellation; however, in some way, they reflect diversity revealed by the expression of homeobox genes in various embryological studies.

Parcellation of the human amygdala using recurrence quantification analysis.

Several previous attempts have been made to divide the human amygdala into smaller subregions based on the unique functional properties of the subregions. Although these attempts have provided valuable insight into the functional heterogeneity in this structure, the possibility that spatial patterns of functional characteristics can quickly change over time has rarely been considered in previous studies. In the present study, we explicitly account for the dynamic nature of amygdala activity. Our goal was not only to develop another parcellation method but also to augment existing methods with novel information about amygdala subdivisions. We performed state-specific amygdala parcellation using resting-state fMRI (rsfMRI) data and recurrence quantification analysis (RQA). RsfMRI data from 102 subjects were acquired with a 3T Trio Siemens scanner. We analyzed values of several RQA measures across all voxels in the amygdala and found two amygdala subdivisions, the ventrolateral (VL) and dorsomedial (DM) subdivisions, that differ with respect to one of the RQA measures, Shannon's entropy of diagonal lines. Compared to the DM subdivision, the VL subdivision can be characterized by a higher value of entropy. The results suggest that VL activity is determined and influenced by more brain structures than is DM activity. To assess the biological validity of the obtained subdivisions, we compared them with histological atlases and currently available parcellations based on structural connectivity patterns (Anatomy Probability Maps) and cytoarchitectonic features (SPM Anatomy toolbox). Moreover, we examined their cortical and subcortical functional connectivity. The obtained results are similar to those previously reported on parcellation performed on the basis of structural connectivity patterns. Functional connectivity analysis revealed that the VL subdivision has strong connections to several cortical areas, whereas the DM subdivision is mainly connected to subcortical regions. This finding suggests that the VL subdivision corresponds to the basolateral subdivision of the amygdala (BLA), while the DM subdivision has some characteristics typical of the centromedial amygdala (CMA). The similarity in functional connectivity patterns between the VL subdivision and BLA, as well as between the DM subdivision and CMA, confirm the utility of our parcellation method. Overall, the study shows that parcellation based on BOLD signal dynamics is a powerful tool for identifying distinct functional systems within the amygdala. This tool might be useful for future research on functional brain organization.

High-resolution mapping and digital atlas of subcortical regions in the macaque monkey based on matched MAP-MRI and histology.

Subcortical nuclei and other deep brain structures are known to play an important role in the regulation of the central and peripheral nervous systems. It can be difficult to identify and delineate many of these nuclei and their finer subdivisions in conventional MRI due to their small size, buried location, and often subtle contrast compared to neighboring tissue. To address this problem, we applied a multi-modal approach in ex vivo non-human primate (NHP) brain that includes high-resolution mean apparent propagator (MAP)-MRI and five different histological stains imaged with high-resolution microscopy in the brain of the same subject. By registering these high-dimensional MRI data to high-resolution histology data, we can map the location, boundaries, subdivisions, and micro-architectural features of subcortical gray matter regions in the macaque monkey brain. At high spatial resolution, diffusion MRI in general, and MAP-MRI in particular, can distinguish a large number of deep brain structures, including the larger and smaller white matter fiber tracts as well as architectonic features within various nuclei. Correlation with histology from the same brain enables a thorough validation of the structures identified with MAP-MRI. Moreover, anatomical details that are evident in images of MAP-MRI parameters are not visible in conventional T1-weighted images. We also derived subcortical template "SC21" from segmented MRI slices in three-dimensions and registered this volume to a previously published anatomical template with cortical parcellation (Reveley et al., 2017; Saleem and Logothetis, 2012), thereby integrating the 3D segmentation of both cortical and subcortical regions into the same volume. This newly updated three-dimensional D99 digital brain atlas (V2.0) is intended for use as a reference standard for macaque neuroanatomical, functional, and connectional imaging studies, involving both cortical and subcortical targets. The SC21 and D99 digital templates are available as volumes and surfaces in standard NIFTI and GIFTI formats.

Sexual dimorphism, estrous cycle and laterality determine the intrinsic and synaptic properties of medial amygdala neurons in rat.

The posterodorsal medial amygdala (MePD) is a sex steroid-sensitive area that modulates different social behavior by relaying chemosensorial information to hypothalamic nuclei. However, little is known about MePD cell type diversity and functional connectivity. Here, we have characterized neurons and synaptic inputs in the right and left MePD of adult male and cycling female (in diestrus, proestrus or estrus) rats. Based on their electrophysiological properties and morphology, we found two coexisting subpopulations of spiny neurons that are sexually dimorphic. They were classified as Class I (predominantly bitufted-shaped neurons showing irregular spikes with frequency adaptation) or Class II (predominantly stellate-shaped neurons showing full spike frequency adaptation). Furthermore, excitatory and inhibitory inputs onto MePD cells were modulated by sex, estrous cycle and hemispheric lateralization. In the left MePD, there was an overall increase in the excitatory input to neurons of males compared to cycling females. However, in proestrus, the MePD neurons received mainly inhibitory inputs. Our findings indicate the existence of hemispheric lateralization, estrous cycle and sexual dimorphism influences at cellular and synaptic levels in the adult rat MePD.

Genetic scores for adult subcortical volumes associate with subcortical volumes during infancy and childhood.

Individual differences in subcortical brain volumes are highly heritable. Previous studies have identified genetic variants that underlie variation in subcortical volumes in adults. We tested whether those previously identified variants also affect subcortical regions during infancy and early childhood. The study was performed within the Generation R study, a prospective birth cohort. We calculated polygenic scores based on reported GWAS for volumes of the accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus. Participants underwent cranial ultrasound around 7 weeks of age (range: 3-20), and we obtained metrics for the gangliothalamic ovoid, a predecessor of the basal ganglia. Furthermore, the children participated in a magnetic resonance imaging (MRI) study around the age of 10 years (range: 9-12). A total of 340 children had complete data at both examinations. Polygenic scores primarily associated with their corresponding volumes at 10 years of age. The scores also moderately related to the diameter of the gangliothalamic ovoid on cranial ultrasound. Mediation analysis showed that the genetic influence on subcortical volumes at 10 years was only mediated for 16.5-17.6% of the total effect through the gangliothalamic ovoid diameter at 7 weeks of age. Combined, these findings suggest that previously identified genetic variants in adults are relevant for subcortical volumes during early life, and that they affect both prenatal and postnatal development of the subcortical regions.

High resolution automated labeling of the hippocampus and amygdala using a 3D convolutional neural network trained on whole brain 700 µm isotropic 7T MP2RAGE MRI.

Image labeling using convolutional neural networks (CNNs) are a template-free alternative to traditional morphometric techniques. We trained a 3D deep CNN to label the hippocampus and amygdala on whole brain 700 µm isotropic 3D MP2RAGE MRI acquired at 7T. Manual labels of the hippocampus and amygdala were used to (i) train the predictive model and (ii) evaluate performance of the model when applied to new scans. Healthy controls and individuals with epilepsy were included in our analyses. Twenty-one healthy controls and sixteen individuals with epilepsy were included in the study. We utilized the recently developed DeepMedic software to train a CNN to label the hippocampus and amygdala based on manual labels. Performance was evaluated by measuring the dice similarity coefficient (DSC) between CNN-based and manual labels. A leave-one-out cross validation scheme was used. CNN-based and manual volume estimates were compared for the left and right hippocampus and amygdala in healthy controls and epilepsy cases. The CNN-based technique successfully labeled the hippocampus and amygdala in all cases. Mean DSC = 0.88 ± 0.03 for the hippocampus and 0.8 ± 0.06 for the amygdala. CNN-based labeling was independent of epilepsy diagnosis in our sample (p = .91). CNN-based volume estimates were highly correlated with manual volume estimates in epilepsy cases and controls. CNNs can label the hippocampus and amygdala on native sub-mm resolution MP2RAGE 7T MRI. Our findings suggest deep learning techniques can advance development of morphometric analysis techniques for high field strength, high spatial resolution brain MRI.

Redundancy circuits of the commissural pathways in human and rhesus macaque brains.

It has been hypothesized that the human brain has less redundancy than animals, but the structural evidence has not been identified to confirm this claim. Here, we report three redundancy circuits of the commissural pathways in primate brains, namely the orbitofrontal, temporal, and occipital redundancy circuits of the anterior commissure and corpus callosum. Each redundancy circuit has two distinctly separated routes connecting a common pair of cortical regions. We mapped their trajectories in human and rhesus macaque brains using individual and population-averaged tractography. The dissection results confirmed the existence of these redundancy circuits connecting the orbitofrontal lobe, amygdala, and visual cortex. The volume analysis showed a significant reduction in the orbitofrontal and occipital redundancy circuits of the human brain, whereas the temporal redundancy circuit had a substantial organizational difference between the human and rhesus macaque. Our results support the hypothesis that the human brain has less redundancy in the commissural pathways than that of the rhesus macaque brain. Further studies are needed to explore its neuropathological implications.

Differential spatial patterns of structural connectivity of amygdala nuclei with orbitofrontal cortex.

The orbitofrontal cortex (OFC)-amygdala circuit is critical to goal-directed behavior, learning, and valuation. However, our understanding of the OFC-amygdala connections that support these emergent processes is hampered by our reliance on the primate literature and insufficient knowledge regarding the connectivity patterns between regions of OFC and amygdala nuclei, each of which is differentially involved in these processes in humans. Thus, we examined structural connectivity between different OFC regions and four amygdala nuclei in healthy adults (n = 1,053) using diffusion-based anatomical networks and probabilistic tractography in four conceptually distinct ways. First, we identified the OFC regions that connect with each nucleus. Second, we identified the OFC regions that were more likely to connect with a given nucleus than the others. Finally, we developed probabilistic and rank-order maps of OFC (one for each nucleus) based upon the likelihood of each OFC voxel exhibiting preferential connectivity with each nucleus and the relative density of connectivity between each OFC voxel and each nucleus, respectively. The first analyses revealed that the connections of each nucleus spanned all of OFC, reflecting widespread overall amygdala linkage with OFC. Analysis of preferential connectivity and probabilistic and rank-order maps of OFC converged to reveal differential patterns of connectivity between OFC and each nucleus. Present findings illustrate the importance of accounting for spatial specificity when examining links between OFC and amygdala. This fine-grained examination of OFC-amygdala connectivity can be applied to understand how such connectivity patterns support a range of emergent functions including affective and motivational processes.

Reproducibility of volume and asymmetry measurements of hippocampus, amygdala, and entorhinal cortex on traveling volunteers: a multisite MP2RAGE prospective study.

BACKGROUND: Multisite studies can considerably increase the pool of normally aging individuals with neurodegenerative disorders and thereby expedite the associated research. Understanding the reproducibility of the parameters of related brain structures-including the hippocampus, amygdala, and entorhinal cortex-in multisite studies is crucial in determining the impact of healthy aging or neurodegenerative diseases. PURPOSE: To estimate the reproducibility of the fascinating structures by automatic (FreeSurfer) and manual segmentation methods in a well-controlled multisite dataset. MATERIAL AND METHODS: Three traveling individuals were scanned at 10 sites, which were equipped with the same equipment (3T Prisma Siemens). They used the same scan protocol (two inversion-contrast magnetization-prepared rapid gradient echo sequences) and operators. Validity coefficients (intraclass correlations coefficient [ICC]) and spatial overlap measures (Dice Similarity Coefficient [DSC]) were used to estimate the reproducibility of multisite data. RESULTS: ICC and DSC values varied substantially among structures and segmentation methods, and values of manual tracing were relatively higher than the automated method. ICC and DSC values of structural parameters were greater than 0.80 and 0.60 across sites, as determined by manual tracing. Low reproducibility was observed in the amygdala parameters by automatic segmentation method (ICC = 0.349-0.529, DSC = 0.380-0.873). However, ICC and DSC scores of the hippocampus were higher than 0.60 and 0.65 by two segmentation methods. CONCLUSION: This study suggests that a well-controlled multisite study could provide a reliable MRI dataset. Manual tracing of volume assessments is recommended for low reproducibility structures that require high levels of precision in multisite studies.

Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors.

BACKGROUND: The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults. METHODS: Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session. RESULTS: Significant MRI site and vendor effects (p â€‹< â€‹.05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p â€‹< â€‹1.39E-36). In particular, volumes larger than 200 â€‹mm3 (for amygdalar nuclei) and 300 â€‹mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε â€‹< â€‹5% and DICE â€‹> â€‹0.80). CONCLUSION: Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.

Sex-biased trajectories of amygdalo-hippocampal morphology change over human development.

The amygdala and hippocampus are two adjacent allocortical structures implicated in sex-biased and developmentally-emergent psychopathology. However, the spatiotemporal dynamics of amygdalo-hippocampal development remain poorly understood in healthy humans. The current study defined trajectories of volume and shape change for the amygdala and hippocampus by applying a multi-atlas segmentation pipeline (MAGeT-Brain) and semi-parametric mixed-effects spline modeling to 1,529 longitudinally-acquired structural MRI brain scans from a large, single-center cohort of 792 youth (403 males, 389 females) between the ages of 5 and 25 years old. We found that amygdala and hippocampus volumes both follow curvilinear and sexually dimorphic growth trajectories. These sex-biases were particularly striking in the amygdala: males showed a significantly later and slower adolescent deceleration in volume expansion (at age 20 years) than females (age 13 years). Shape analysis localized significant hot-spots of sex-biased anatomical development in sub-regional territories overlying rostral and caudal extremes of the CA1/2 in the hippocampus, and the centromedial nuclear group of the amygdala. In both sexes, principal components analysis revealed close integration of amygdala and hippocampus shape change along two main topographically-organized axes - low vs. high areal expansion, and early vs. late growth deceleration. These results (i) bring greater resolution to our spatiotemporal understanding of amygdalo-hippocampal development in healthy males and females, and (ii) uncover focal sex-differences in the structural maturation of the brain components that may contribute to differences in behavior and psychopathology that emerge during adolescence.

Subcortical structural variations associated with low socioeconomic status in adolescents.

Low socioeconomic status (SES) is associated with a higher probability of multiple exposures (e.g., neighborhood violence, poor nutrition, housing instability, air pollution, and insensitive caregiving) known to affect structural development of subcortical brain regions that subserve threat and reward processing, however, few studies have examined the relationship between SES and such subcortical structures in adolescents. We examined SES variations in volume and surface morphometry of subcortical regions. The sample comprised 256 youth in eighth grade (mean age = 13.9 years), in whom high dimensional deformation mapping of structural 3T magnetic resonance imaging scans was performed. Vertex-wise linear regression analyses examined associations between income to poverty ratio and surfaces of the hippocampus, amygdala, thalamus, caudate, putamen, nucleus accumbens and pallidum, with the covariates age, pubertal status, and intracranial volume. Given sex differences in pubertal development and subcortical maturation at this age, the analyses were stratified by sex. Among males, who at this age average an earlier pubertal stage than females, the relationship between SES and local shape variation in subcortical regions was almost entirely positive. For females, the relationship between SES and local shape variation was negative. Racial identity was associated with SES in our sample, however supplementary analyses indicated that most of the associations between SES and subcortical structure were independent of it. Although these cross-sectional results are not definitive, they are consistent with a scenario where low SES delays structural maturation of subcortical regions involved with threat and reward processing. Future longitudinal studies are needed to test this hypothesis.

Birth weight is associated with adolescent brain development: A multimodal imaging study in monozygotic twins.

Previous research has shown that the prenatal environment, commonly indexed by birth weight (BW), is a predictor of morphological brain development. We previously showed in monozygotic (MZ) twins associations between BW and brain morphology that were independent of genetics. In the present study, we employed a longitudinal MZ twin design to investigate whether variations in prenatal environment (as indexed by discordance in BW) are associated with resting-state functional connectivity (rs-FC) and with structural connectivity. We focused on the limbic and default mode networks (DMNs), which are key regions for emotion regulation and internally generated thoughts, respectively. One hundred and six healthy adolescent MZ twins (53 pairs; 42% male pairs) followed longitudinally from birth underwent a magnetic resonance imaging session at age 15. Graph theoretical analysis was applied to rs-FC measures. TrackVis was used to determine track count as an indicator of structural connectivity strength. Lower BW twins had less efficient limbic network connectivity as compared to their higher BW co-twin, driven by differences in the efficiency of the right hippocampus and right amygdala. Lower BW male twins had fewer tracks connecting the right hippocampus and right amygdala as compared to their higher BW male co-twin. There were no associations between BW and the DMN. These findings highlight the possible role of unique prenatal environmental influences in the later development of efficient spontaneous limbic network connections within healthy individuals, irrespective of DNA sequence or shared environment.

Functional differentiation in the human ventromedial frontal lobe: A data-driven parcellation.

Ventromedial regions of the frontal lobe (vmFL) are thought to play a key role in decision-making and emotional regulation. However, aspects of this area's functional organization, including the presence of a multiple subregions, their functional and anatomical connectivity, and the cross-species homologies of these subregions with those of other species, remain poorly understood. To address this uncertainty, we employed a two-stage parcellation of the region to identify six distinct structures within the region on the basis of data-driven classification of functional connectivity patterns obtained using the meta-analytic connectivity modeling (MACM) approach. From anterior to posterior, the derived subregions included two lateralized posterior regions, an intermediate posterior region, a dorsal and ventral central region, and a single anterior region. The regions were characterized further by functional connectivity derived using resting-state fMRI and functional decoding using the Brain Map database. In general, the regions could be differentiated on the basis of different patterns of functional connectivity with canonical "default mode network" regions and/or subcortical regions such as the striatum. Together, the findings suggest the presence of functionally distinct neural structures within vmFL, consistent with data from experimental animals as well prior demonstrations of anatomical differences within the region. Detailed correspondence with the anterior cingulate, medial orbitofrontal cortex, and rostroventral prefrontal cortex, as well as specific animal homologs are discussed. The findings may suggest future directions for resolving potential functional and structural correspondence of subregions within the frontal lobe across behavioral contexts, and across mammalian species.

The amygdala of the common shrew, guinea pig, rabbit, fox and pig: five flavours of the mammalian amygdala as a consequence of clade-specific mosaic-like evolution.

The amygdala is a part of neural networks that contribute to the regulation of emotional behaviours and emotional learning, stress response, and olfactory, pheromonal and reproductive functions. All these various functions are processed by the three main functional systems, frontotemporal, autonomic and olfactory, which are derived from different telencephalic sources (claustrum, striatum and olfactory cortex) and are represented, respectively, by the basolateral complex (BLC), the central complex (CC) and corticomedial complex (CMC) of the amygdala. The question arises of how these three functional systems evolved during mammalian phylogeny to fit the amygdala to specific needs of various animals. In the present study, we provide quantitative information regarding the individual volumes and neuron numbers in the BLC, CC and CMC of the common shrew, guinea pig, rabbit, fox and pig, a series of animals arranged according to increasing size and complexity of the brain. The results show that, in this series of animals, the BLC underwent a gradual size increase in volume and number of neurons, whereas the CMC was gradually reduced with regard to both these measures. The CC was more or less conserved across studied species. For example, the volume of the amygdala in pigs is ~250 times larger than that in shrews and it also has almost 26 times as many neurons as the amygdala of shrews. However, the volumes of the BLC, CC and CMC were ~380, 208 and 148 times larger, respectively, in pigs than in shrews. The number of neurons in these three regions was ~38, 23 and 20 times greater, respectively, in pigs than in shrews. The results also show striking morphometric similarities of the amygdala in the guinea pig and rabbit as well as fox and pig. For example, the percentages of neurons in the fox and pig are 42.23% and 42.78%, respectively, for the BLC, 16.64% and 16.58%, respectively, for the CC, and 41.12% and 40.64%, respectively, for the CMC. In conclusion, our results indicate that the amygdala does not evolve as a single unit but, instead, the three main functional systems evolved independently, which suggests that brain structures with major functional links evolve together independently of evolutionary changes in other unrelated structures. The size progression of the BLC parallels the size progression of the neocortex with which it is strongly functionally linked, whereas the CMC is strongly connected to olfactory regions, and all these structures follow the same regression course. Remarkable morphometric similarity of the amygdala in the guinea pig and rabbit as well as in the fox and pig, however, suggest that there must also be another mechanism shaping the morphology of the amygdala and the brain during evolution. The gradual nature of size changes in the BLC and CMC support this hypothesis as well.

A higher-order theory of emotional consciousness.

Emotional states of consciousness, or what are typically called emotional feelings, are traditionally viewed as being innately programmed in subcortical areas of the brain, and are often treated as different from cognitive states of consciousness, such as those related to the perception of external stimuli. We argue that conscious experiences, regardless of their content, arise from one system in the brain. In this view, what differs in emotional and nonemotional states are the kinds of inputs that are processed by a general cortical network of cognition, a network essential for conscious experiences. Although subcortical circuits are not directly responsible for conscious feelings, they provide nonconscious inputs that coalesce with other kinds of neural signals in the cognitive assembly of conscious emotional experiences. In building the case for this proposal, we defend a modified version of what is known as the higher-order theory of consciousness.