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Difficulties in social interactions characterize both autism and schizophrenia and are correlated in the neurotypical population. It is unknown whether this represents a shared etiology or superficial phenotypic overlap. Both conditions exhibit atypical neural activity in response to the perception of social stimuli and decreased neural synchronization between individuals. This study investigated if neural activity and neural synchronization associated with biological motion perception are differentially associated with autistic and schizotypal traits in the neurotypical population. Participants viewed naturalistic social interactions while hemodynamic brain activity was measured with fMRI, which was modeled against a continuous measure of the extent of biological motion. General linear model analysis revealed that biological motion perception was associated with neural activity across the action observation network. However, intersubject phase synchronization analysis revealed neural activity to be synchronized between individuals in occipital and parietal areas but desynchronized in temporal and frontal regions. Autistic traits were associated with decreased neural activity (precuneus and middle cingulate gyrus), and schizotypal traits were associated with decreased neural synchronization (middle and inferior frontal gyri). Biological motion perception elicits divergent patterns of neural activity and synchronization, which dissociate autistic and schizotypal traits in the general population, suggesting that they originate from different neural mechanisms.

Background Obesity is a pressing public health concern worldwide. Novel pharmacological means are urgently needed to combat the increase of obesity and accompanying type 2 diabetes (T2D). Although fully established obesity is associated with neuromolecular alterations and insulin resistance in the brain, potential obesity-promoting mechanisms in the central nervous system have remained elusive. In this triple-tracer positron emission tomography study, we investigated whether brain insulin signaling, μ-opioid receptors (MORs) and cannabinoid CB1 receptors (CB1Rs) are associated with risk for developing obesity. Methods Subjects were 41 young non-obese males with variable obesity risk profiles. Obesity risk was assessed by subjects’ physical exercise habits, body mass index and familial risk factors, including parental obesity and T2D. Brain glucose uptake was quantified with [18F]FDG during hyperinsulinemic euglycemic clamp, MORs were quantified with [11C]carfentanil and CB1Rs with [18F]FMPEP-d2. Results Subjects with higher obesity risk had globally increased insulin-stimulated brain glucose uptake (19 high-risk subjects versus 19 low-risk subjects), and familial obesity risk factors were associated with increased brain glucose uptake (38 subjects) but decreased availability of MORs (41 subjects) and CB1Rs (36 subjects). Conclusions These results suggest that the hereditary mechanisms promoting obesity may be partly mediated via insulin, opioid and endocannabinoid messaging systems in the brain.

Forest management inventories assisted by airborne laser scanning (ALS) can be used to predict different forest attributes. These predictions are utilized in practical forestry, but in the case of timber assortment-specific volumes, the ALS-based predictions can be inaccurate. This causes uncertainty in harvest planning. However, ALS-based predictions can be calibrated to achieve greater accuracy with local measurements. In this study, we used ALS data and accurately positioned cut-to-length harvester measurements from Norway spruce (Picea abies (L.) Karst.) dominated clear-cuts. We fitted linear mixed-effects (LME) models with exponential correlation structure for merchantable volume and sawlog volume for 225 m2 cells. Our aim was to study the effect of local harvester measurements on the accuracy of stand level merchantable and sawlog volumes. LME-based predictions were calibrated repeatedly up to 40 times as the cutting progressed. ALS data and harvester measurements were used to predict both the random effects and residual errors for each validation unit. At best, relative root mean square error (RMSE%) of initial predictions of 15.4 per cent for merchantable volume and 22.1 per cent for sawlog volume were reduced to 4.1 and 5.3 per cent, respectively, when measurements from 40 harvested cells of size 225 m2 were used. These results suggest that spatially accurate harvester data could be utilized during harvesting to increase the accuracy of volume and timber assortment predictions.

Objective To investigate whether alterations in brain glucose uptake (BGU), insulin action in the brain–liver axis and whole-body insulin sensitivity occur in young adults in pre-obese state. Methods Healthy males with either high risk (HR; n = 19) or low risk (LR; n = 22) for developing obesity were studied with [18F]fluoro-d-glucose ([18F]FDG)–positron emission tomography during hyperinsulinemic–euglycemic clamp. Obesity risk was assessed according to BMI, physical activity and parental overweight/obesity and type 2 diabetes. Brain, skeletal muscle, brown adipose tissue (BAT), visceral adipose tissue (VAT) and abdominal and femoral s.c. adipose tissue (SAT) glucose uptake (GU) rates were measured. Endogenous glucose production (EGP) was calculated by subtracting the exogenous glucose infusion rate from the rate of disappearance of [18F]FDG. BGU was analyzed using statistical parametric mapping, and peripheral tissue activity was determined using Carimas Software imaging processing platform. Results BGU was higher in the HR vs LR group and correlated inversely with whole-body insulin sensitivity (M value) in the HR group but not in the LR group. Insulin-suppressed EGP did not differ between the groups but correlated positively with BGU in the whole population, and the correlation was driven by the HR group. Skeletal muscle, BAT, VAT, abdominal and femoral SAT GU were lower in the HR group as compared to the LR group. Muscle GU correlated negatively with BGU in the HR group but not in the LR group. Conclusion Increased BGU, alterations in insulin action in the brain–liver axis and decreased whole-body insulin sensitivity occur early in pre-obese state.

Music can induce strong subjective experience of emotions, but it is debated whether these responses engage the same neural circuits as emotions elicited by biologically significant events. We examined the functional neural basis of music-induced emotions in a large sample (n = 102) of subjects who listened to emotionally engaging (happy, sad, fearful, and tender) pieces of instrumental music while their hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI). Ratings of the four categorical emotions and liking were used to predict hemodynamic responses in general linear model (GLM) analysis of the fMRI data. Multivariate pattern analysis (MVPA) was used to reveal discrete neural signatures of the four categories of music-induced emotions. To map neural circuits governing non-musical emotions, the subjects were scanned while viewing short emotionally evocative film clips. The GLM revealed that most emotions were associated with activity in the auditory, somatosensory, and motor cortices, cingulate gyrus, insula, and precuneus. Fear and liking also engaged the amygdala. In contrast, the film clips strongly activated limbic and cortical regions implicated in emotional processing. MVPA revealed that activity in the auditory cortex and primary motor cortices reliably discriminated the emotion categories. Our results indicate that different music-induced basic emotions have distinct representations in regions supporting auditory processing, motor control, and interoception but do not strongly rely on limbic and medial prefrontal regions critical for emotions with survival value.

In many countries, airborne laser scanning (ALS) inventories are implemented to produce predictions for stand-level forest attributes. Nevertheless, mature stands are usually field-visited prior to clear-cutting, so some measurements can be conducted on these stands to calibrate the ALS-based predictions. In this paper, we developed a seemingly unrelated multivariate mixed-effects model system that includes component models for basal area, merchantable volume, and sawlog volume for 225 m2 cells. We used ALS data and accurately positioned cut-to-length harvester observations from clear-cut stands dominated by Norway spruce (Picea abies (L.) Karst.). Our aim was to study the effect of 1–10 local angle-gauge basal area measurements on the accuracy of predicted merchantable and sawlog volumes. A seemingly unrelated mixed-effect model system was fitted to estimate cross-model correlations in residuals and random effects, which were then utilized to predict all the random effects of the system for calibrated stand-level predictions. The 10 angle-gauge plots decreased the relative root mean square error (RMSE%) of the basal area and merchantable volume predictions from 16.8% to 10.5% and from 15.8% to 11.9%, respectively. Cross-model correlations of the stand effects of sawlog volume with the other responses were low; therefore, the initial RMSE% of ∼22% was decreased only marginally by the calibration.

Difficulties in social interactions are common to both autism and schizophrenia, and contribute to correlated autistic and schizotypal traits in the neurotypical population. It remains unresolved whether this represents a shared etiology or a superficial phenotypic overlap. Both conditions are associated with atypical neural activity in response to the perception of social stimuli, and also decreased neural synchronization between individuals that may prohibit establishing shared experiences. This study sought to establish if neural activity and neural synchronization associated with biological motion perception are differentially associated with autistic and schizotypal traits in the neurotypical population. Participants watched an audiovisual montage of naturalistic social interactions whilst hemodynamic brain activity was measured with fMRI. A separate sample of participants provided a continuous measure of the extent of biological motion, which was used to predict hemodynamic activity. General Linear Model analysis revealed that biological motion perception was associated with neural activity across the action-observation network. However, inter-subject phase synchronization analysis revealed that neural activity synchronized between individuals in occipital and parietal areas, but de-synchronized in temporal and frontal regions. Autistic traits were associated with a decrease in neural activity (precuneus, middle cingulate gyrus) and schizotypal traits were associated with a decrease in neural synchronization (middle and inferior frontal gyri). Biological motion perception elicits convergent and divergent patterns of neural activity and neural synchronization, and are differentially associated with shared traits related with autism and schizophrenia in the general population, suggesting that they originate from different neural mechanisms.

Major depressive disorder is associated with lowered mood, anxiety, anhedonia, sleep problems, and cognitive impairments. Many of these functions are regulated by μ-opioid receptor (MOR) system. Preclinical, in vivo, and post-mortem studies have however yielded inconclusive results regarding the role of the MOR in depression and anxiety. Moreover, it is not known whether alterations in MOR are already present in subclinical depression and anxiety. In a large-scale retrospective cross-sectional study we pooled data from 135 (113 males and 22 females) healthy subjects whose brain’s MOR availability was measured with positron emission tomography (PET) using an agonist radioligand [11C]carfentanil that has high affinity for MORs. Depressive and anxious symptomology was addressed with BDI-II and STAI-X questionnaires, respectively. Both anxiety and depression scores in the subclinical range were negatively associated with MOR availability in cortical and subcortical areas, notably in amygdala, hippocampus, ventral striatum, and orbitofrontal and cingulate cortices. We conclude that dysregulated MOR availability is involved in altered mood and pathophysiology of depression and anxiety disorders.

Sex differences in brain activity evoked by sexual stimuli remain elusive despite robust evidence for stronger enjoyment of and interest towards sexual stimuli in men than in women. To test whether visual sexual stimuli evoke different brain activity patterns in men and women, we measured haemodynamic brain activity induced by visual sexual stimuli in two experiments in 91 subjects (46 males). In one experiment, the subjects viewed sexual and non-sexual film clips and dynamic annotations for nudity in the clips was used to predict their hemodynamic activity. In the second experiment, the subjects viewed sexual and non-sexual pictures in an event-related design. Males showed stronger activation than females in the visual and prefrontal cortices and dorsal attention network in both experiments. Furthermore, using multivariate pattern classification we could accurately predict the sex of the subject on the basis of the brain activity elicited by the sexual stimuli. The classification generalized across the experiments indicating that the sex differences were consistent. Eye tracking data obtained from an independent sample of subjects (N = 110) showed that men looked longer than women at the chest area of the nude female actors in the film clips. These results indicate that visual sexual stimuli evoke discernible brain activity patterns in men and women which may reflect stronger attentional engagement with sexual stimuli in men than women.

Funding Information: This study was supported by the Academy of Finland (grants #294897 and #332225 to L.N.), the Sigrid Jus?lius Foundation (grant to L.N.), the P?ivikki and Sakari Sohlberg Foundation (personal grant to T.M.) and the State research funding for expert responsibility area (ERVA) of the Tyks Turku University Hospital (personal grants to T.M. and L.N.), as well as Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy (personal grant EXC 2075 ? 390740016 to P.B.). We thank senior researchers Marco Bucci and Semi Helin, as well as Professor Kari Auranen for sharing their expertise on kinetic modeling, radiochemistry and Bayesian data analysis, respectively. We also thank Post-Doctoral researcher Jouni Tuisku for his consultance and help with image preprocessing and data management, as well as hospital physicists Tuula Tolvanen and Jukka Ihalainen for sharing their knowledge on the physical properties of the scanners. Authors have nothing to disclose. Background: The dopamine system contributes to a multitude of functions ranging from reward and motivation to learning and movement control, making it a key component in goal-directed behavior. Altered dopaminergic function is observed in neurological and psychiatric conditions. Numerous factors have been proposed to influence dopamine function, but due to small sample sizes and heterogeneous data analysis methods in previous studies their specific and joint contributions remain unresolved. Methods: In this cross-sectional register-based study we investigated how age, sex, body mass index (BMI), as well as cerebral hemisphere and regional volume influence striatal type 2 dopamine receptor (D2R) availability in the human brain. We analyzed a large historical dataset (n=156, 120 males and 36 females) of [11C]raclopride PET scans performed between 2004 and 2018. Results: Striatal D2R availability decreased through age for both sexes (2-5 % in striatal ROIs per 10 years) and was higher in females versus males throughout age (7-8% in putamen). BMI and striatal D2R availability were weakly associated. There was no consistent lateralization of striatal D2R. The observed effects were independent of regional volumes. These results were validated using two different spatial normalization methods, and the age and sex effects also replicated in an independent sample (n=135). Conclusions: D2R availability is dependent on age and sex, which may contribute to the vulnerability of neurological and psychiatric conditions involving altering D2R expression.

Eating behavior varies greatly between individuals, but the neurobiological basis of these trait-like differences in feeding remains poorly understood. Central μ-opioid receptors (MOR) and cannabinoid CB1 receptors (CB1R) regulate energy balance via multiple neural pathways, promoting food intake and reward. Because obesity and eating disorders have been associated with alterations in the brain’s opioid and endocannabinoid signaling, the variation in MOR and CB1R system function could potentially underlie distinct eating behavior phenotypes. In this retrospective positron emission tomography (PET) study, we analyzed [11C]carfentanil PET scans of MORs from 92 healthy subjects (70 males and 22 females), and [18F]FMPEP-d2 scans of CB1Rs from 35 subjects (all males, all also included in the [11C]carfentanil sample). Eating styles were measured with the Dutch Eating Behavior Questionnaire (DEBQ). We found that lower cerebral MOR availability was associated with increased external eating—individuals with low MORs reported being more likely to eat in response to environment’s palatable food cues. CB1R availability was associated with multiple eating behavior traits. We conclude that although MORs and CB1Rs overlap anatomically in brain regions regulating food reward, they have distinct roles in mediating individual feeding patterns. Central MOR system might provide a pharmacological target for reducing individual’s excessive cue-reactive eating behavior.

BACKGROUNDThe dopamine system contributes to a multitude of functions ranging from reward and motivation to learning and movement control, making it a key component in goal-directed behavior. Altered dopaminergic function is observed in neurological and psychiatric conditions. Numerous factors have been proposed to influence dopamine function, but due to small sample sizes and heterogeneous data analysis methods in previous studies their specific and joint contributions remain unresolved.METHODSIn this cross-sectional register-based study we investigated how age, sex, body mass index (BMI), as well as cerebral hemisphere and regional volume influence striatal type 2 dopamine receptor (D2R) availability in the human brain. We analyzed a large historical dataset (n=156, 120 males and 36 females) of [11C]raclopride PET scans performed between 2004 and 2018.RESULTSStriatal D2R availability decreased through age for both sexes and was higher in females versus males throughout age. BMI and striatal D2R availability were weakly associated. There was no consistent lateralization of striatal D2R. The observed effects were independent of regional volumes. These results were validated using two different spatial normalization methods, and the age and sex effects also replicated in an independent sample (n=135).CONCLUSIONSD2R density is dependent on age and sex, which may contribute to the vulnerability of neurological and psychiatric conditions involving altering D2R expression.

In this paper, we examine the transferability of airborne laser scanning (ALS) based models for individual-tree detection (ITD) from one ALS inventory area (A1) to two other areas (A2 and A3). All areas were located in eastern Finland less than 100 km from each other and were scanned using different ALS devices and parameters. The tree attributes of interest were diameter at breast height (Dbh), height (H), crown base height (Cbh), stem volume (V), and theoretical sawlog volume (Vlog) of Scots pine (Pinus sylvestris L.) with Dbh ≥ 16 cm. All trees were first segmented from the canopy height models, and various ALS metrics were derived for each segment. Then only the segments covering correctly detected pines were chosen for further inspection. The tree attributes were predicted using the k-nearest neighbor (k-NN) imputation. The results showed that the relative root mean square error (RMSE%) values increased for each attribute after the transfers. The RMSE% values were, for A1, A2, and A3, respectively: Dbh, 13.5%, 14.8%, and 18.1%; H, 3.2%, 5.9%, and 6.2%; Cbh, 13.3%, 15.3%, and 18.3%; V, 29.3%, 35.4%, and 39.1%; and Vlog, 38.2%, 54.4% and 51.8%. The observed values indicate that it may be possible to employ ALS-based tree-level k-NN models over different inventory areas without excessive reduction in accuracy, assuming that the tree species are known to be similar.

Background Neurotransmitter substance P (SP) and its preferred neurokinin-1 receptor (NK1R) have been implicated in the treatment of affective and addiction disorders. Despite promising preclinical data on antidepressant action, the clinical trials of NK1R antagonists in major depression have been disappointing. There are no direct in vivo imaging studies on NK1R characteristics in patients with a major depressive disorder (MDD). Methods In this cross-sectional case-control study, we recruited nine never-medicated patients with moderate to severe MDD and nine matched healthy controls. NK1R availability (NK1R binding potential, BPND) was measured with in vivo 3-D positron emission tomography and a specific NK1 receptor tracer [18F]SPA-RQ. Clinical symptoms were assessed with the 17-item Hamilton Rating Scale for Depression (HAM-D17). Results NK1R-BPND did not differ statistically significantly between patients with MDD and healthy controls. HAM-D17 total scores (range 21–32) correlated positively with NK1R-BPND in cortical and limbic areas. HAM-D17 subscale score for anxiety symptoms correlated positively with NK1R-BPND in specific brain areas implicated in fear and anxiety. Limitations Small sample size. Low variability in the clinical HAM-D subscale ratings may affect the observed correlations. Conclusions Our preliminary results do not support a different baseline expression of NK1Rs in a representative sample of never-medicated patients with MDD during a current moderate/severe depressive episode. The modulatory effect of NK1Rs on affective symptoms is in line with early positive results on antidepressant action of NK1 antagonists. However, the effect is likely to be too weak for treatment of MDD with NK1R antagonists alone in clinical practice.

Psychopathy is characterized by persistent antisocial behavior, impaired empathy, and egotistical traits. These traits vary also in normally functioning individuals. Here, we tested whether such antisocial personalities are associated with similar structural and neural alterations as those observed in criminal psychopathy. Subjects were 100 non-convicted well-functioning individuals, 19 violent male offenders, and 19 matched controls. Subjects underwent T1-weighted magnetic resonance imaging and viewed movie clips with varying violent content during functional magnetic resonance imaging. Psychopathic traits were evaluated with Levenson Self-Report Psychopathy Scale (controls) and Psychopathy Checklist-Revised (offenders). Psychopathic offenders had lower gray matter density (GMD) in orbitofrontal cortex and anterior insula. In the community sample, affective psychopathy traits were associated with lower GMD in the same areas. Viewing violence increased brain activity in periaqueductal grey matter, thalamus, somatosensory, premotor, and temporal cortices. Psychopathic offenders had increased responses to violence in thalamus and orbitofrontal, insular, and cingulate cortices. In the community sample, impulsivity-related psychopathy traits were positively associated with violence-elicited responses in similar areas. We conclude that brain characteristics underlying psychopathic spectrum in violent psychopathy are related to those observed in well-functioning individuals with asocial personality features.

Eating behavior varies greatly between healthy individuals, but the neurobiological basis of these trait-like differences in feeding remains unknown. Central µ-opioid receptors (MOR) and cannabinoid CB1-receptors (CB1R) regulate energy balance via multiple neural pathways, promoting food intake and reward. Because obesity and eating disorders have been associated with alterations in the brain’s opioid and endocannabinoid signaling, the variation in MOR and CB1R system function could potentially underlie distinct eating behavior phenotypes. In this retrospective positron emission tomography (PET) study, we analyzed [11C]carfentanil PET scans of MORs from 92 healthy subjects (70 males and 22 females), and [18F]FMPEP-d2 scans of CB1Rs from 35 subjects (all males, all also included in the [11C]carfentanil sample). Eating styles were measured with the Dutch Eating Behavior Questionnaire (DEBQ). We found that lower cerebral MOR availability was associated with increased external eating – individuals with low MORs reported being more likely to eat in response to environment’s palatable food cues. CB1R availability was associated with multiple eating behavior traits. We conclude that although MORs and CB1Rs overlap anatomically and functionally in the brain, they have distinct roles in mediating individual feeding patterns.

Publisher Copyright: © 2021 The Authors We studied the association between episodic memory and cortical fibrillar β-amyloid pathology within twin pairs. Using telephone-administered cognitive screening of 1415 twin pairs in a population-based older Finnish Twin Cohort study, we identified 45 (mean [SD] age 72.9 [4.0] years, 40% women) cognitively discordant same-sex twin pairs (24 dizygotic and 21 monozygotic) without neurological or psychiatric disorders other than AD or mild cognitive impairment. In-person neuropsychological testing was conducted. Cortical amyloid was measured with carbon 11-labelled Pittsburgh compound B ([11C]PiB) positron emission tomography imaging and quantified as the average standardized uptake value ratio in cortical regions affected in AD. Larger within-twin pair differences in verbal immediate (r = -0.42) and delayed free recall (r = -0.41), and visual delayed free recall (r = -0.46) were associated with larger within-twin pair differences in [11C]PiB uptake (p's < 0.01). Correlations were not significantly different in dizygotic and monozygotic pairs suggesting that the episodic memory-cortical amyloid relationship is not confounded by genetic effects. However, larger samples are needed to draw more definitive conclusions.

Music can induce strong subjective experience of emotions, but it is debated whether these responses engage the same neural circuits as emotions elicited by biologically significant events. We examined the functional neural basis of music-induced emotions in a large sample (n=102) of subjects who listened to emotionally engaging (happy, sad, fearful, and tender) pieces of instrumental music while their haemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI). Ratings of the four categorical emotions and liking were used to predict haemodynamic responses in general linear model (GLM) analysis of the fMRI data. Multivariate pattern analysis (MVPA) was used to reveal discrete neural signatures of the four categories of music-induced emotions. To map neural circuits governing non-musical emotions, the subjects were scanned while viewing short emotionally evocative film clips. The GLM revealed that most emotions were associated with activity in the auditory, somatosensory and motor cortices, cingulate gyrus, insula, and precuneus. Fear and liking also engaged the amygdala. In contrast, the film clips strongly activated limbic and cortical regions implicated in emotional processing. MVPA revealed that activity in the auditory cortex in particular as well as in the primary motor cortices reliably discriminated the emotion categories. Our results indicate that different music-induced basic emotions have distinct representations in regions supporting auditory processing, motor control, somatosensation and interoception but do not strongly rely on limbic and medial prefrontal regions critical for emotions with survival value.

Seasonal rhythms influence mood and sociability. The brain μ-opioid receptor (MOR) system modulates a multitude of seasonally varying socioemotional functions, but its seasonal variation remains elusive with no previously reported in vivo evidence. Here, we studied the seasonal effects on brain MOR availability via analysing a dataset (n=204) of [11C]carfentanil positron emission tomography (PET) scans of healthy volunteers. We found that seasonally varying daylength had an inverted U-shaped functional relationship with brain MOR availability. Brain regions sensitive to daylength spanned the socio-emotional brain circuits, where MOR availability formed a spring-like peak. Causal effect of daylength on brain MOR availability was further verified by a post hoc experiment with repeated PET imaging of rats (n=9) under seasonal photoperiodic simulation. Therefore, the in vivo brain MOR availability in normal humans shows significant seasonal variation, which aligns with expected seasonal variation in mood and suicidality.

Positron emission tomography (PET) can be used for in vivo measurement of specific neuroreceptors and transporters using radioligands, while voxel-based morphometric analysis of magnetic resonance images allows automated estimation of local grey matter densities. However, it is not known how regional neuroreceptor or transporter densities are reflected in grey matter densities. Here, we analyzed brain scans retrospectively from 325 subjects and compared grey matter density estimates with three different neuroreceptors and transporter availabilities. µ-opioid receptors (MORs) were measured with [11C]carfentanil (162 scans), dopamine D2 receptors with [11C]raclopride (91 scans) and serotonin transporters (SERT) with [11C]MADAM (72 scans). The PET data were modelled with simplified reference tissue model. Voxel-wise correlations between binding potential and grey matter density images were computed. Regional binding of all the used radiotracers was associated with grey matter density in region and ligand-specific manner independently of subjects’ age or sex. These data show that grey matter density and MOR and D2R neuroreceptor / SERT availability are correlated, with effect sizes (r2) ranging from 0.04 to 0.69. This suggests that future studies comparing PET outcome measure different groups (such as patients and controls) should take grey matter density differences between the groups into account.

Processing of positron emission tomography (PET) data typically involves manual work, causing inter-operator variance. Here we introduce the Magia toolbox that enables processing of brain PET data with minimal user intervention. We investigated the accuracy of Magia with four tracers: [11C]carfentanil, [11C]raclopride, [11C]MADAM, and [11C]PiB. We used data from 30 control subjects for each tracer. Five operators manually delineated reference regions for each subject. The data were processed using Magia using the manually and automatically generated reference regions. We first assessed inter-operator variance resulting from the manual delineation of reference regions. We then compared the differences between the manually and automatically produced reference regions and the subsequently obtained binding potentials and standardized-uptake-value-ratios. The results show that manually produced reference regions can be remarkably different from each other, leading to substantial differences also in outcome measures. While the Magia-derived reference regions were anatomically different from the manual ones, Magia produced outcome measures highly consistent with the average of the manually obtained estimates. For [11C]carfentanil and [11C]PiB there was no bias, while for [11C]raclopride and [11C]MADAM Magia produced 3–5% higher binding potentials. Based on these results and considering the high inter-operator variance of the manual method, we conclude that Magia can be reliably used to process brain PET data.

The brain’s µ-opioid receptors (MORs) are involved in analgesia, reward and mood regulation. Several neuropsychiatric diseases have been associated with dysfunctional MOR system, and there is also considerable variation in receptor density among healthy individuals. Sex, age, body mass and smoking have been proposed to influence the MOR system, but due to small sample sizes the magnitude of their influence remains inconclusive. Here we quantifiedin vivoMOR availability in the brains of 204 individuals with no neurologic or psychiatric disorders using positron emission tomography (PET) with tracer [11C]carfentanil. We then used Bayesian hierarchical modeling to estimate the effects of sex, age, body mass index (BMI) and smoking on [11C]carfentanil binding potential. We also examined hemispheric lateralization of MOR availability. Age had regionally specific effects on MOR availability, with age-dependent increase in frontotemporal areas but decrease in amygdala, thalamus, and nucleus accumbens. The age-dependent increase was stronger in males. MOR availability was globally lowered in smokers but independent of BMI. Finally, MOR availability was higher in the right versus the left hemisphere. The presently observed variation in MOR availability may explain why some individuals are prone to develop MOR-linked pathological states, such as chronic pain or psychiatric disorders.

Fear protects organisms by increasing vigilance and preparedness, and by coordinating survival responses during life-threatening encounters. The fear circuit must thus operate on multiple timescales ranging from preparatory sustained alertness to acute fight-or-flight responses. Here we studied the brain basis of sustained and acute fear using naturalistic functional magnetic resonance imaging (fMRI) enabling analysis of different time-scales of fear responses. Subjects (N ​= ​37) watched feature-length horror movies while their hemodynamic brain activity was measured with fMRI. Time-variable intersubject correlation (ISC) was used to quantify the reliability of brain activity across participants, and seed-based phase synchronization was used for characterizing dynamic connectivity. Subjective ratings of fear were used to assess how synchronization and functional connectivity varied with emotional intensity. These data suggest that acute and sustained fear are supported by distinct neural pathways, with sustained fear amplifying mainly sensory responses, and acute fear increasing activity in brainstem, thalamus, amygdala and cingulate cortices. Sustained fear increased ISC in regions associated with acute fear, and also amplified functional connectivity within this network. The results were replicated in an independent experiment with a different subject sample and stimulus movie. The functional interplay between cortical networks involved in sustained anticipation of, and acute response to, threat involves a complex and dynamic interaction that depends on the proximity of threat, and the need to employ threat appraisals and vigilance for decision making and response selection.

In acute ischemic stroke (AIS), timely detection and reliable segmentation of AIS lesions on magnetic resonance images (MRIs) are essential for patient selection for treatment. Our purpose was to develop and validate an innovative knowledge-based automated technique that utilizes diffusion weighted images (DWIs) and apparent diffusion coefficient (ADC) images for detection and segmentation of AIS lesions. We developed and evaluated our method on a large dataset (n=156) images including 106 stroke and 50 healthy controls. The proposed method compares DWI and ADC images of the subjects – after MNI space normalization and Gaussian kernel smoothing with full width at half maximum (FWHM) of range 2 to 5 mm – with a group of 50 healthy images in voxel-level by means of the Crawford-Howell ttest. T-maps created by the t-test are then screened for extreme values. Areas with hypersignal on DWI and hyposignal on ADC are identified as lesion. We divided our data to train set and validation set and measured Dice Similarity Index (DSI) between automated and manually segmented lesions. The mean DSI for FWHM range from 2 to 5 was 0.47, 0.49, 0.48, and 0.42 on the train set respectively. The method was optimized for thresholds with images smoothed by FWHM of 3, which demonstrated the best DSI. The mean DSI for the optimized parameters on the unseen validation set was 0.50 (SD = 0.19). In conclusion, this fully automated approach showed good agreement with the manually drawn lesions. The approach does not require high computational power, which allows the technique to be implemented on an ordinary computer to be integrated into the routine clinical diagnostic pipeline.

Background Successful delineation of lesions in acute ischemic strokes (AIS) is crucial for increasing the likelihood of good clinical outcome for the patient. New methods We developed a fully automated method to localize and segment AIS lesions in variable locations for 192 multimodal 3D-magnetic resonance images (MRI) including 106 stroke and 86 healthy cases. The method works based on the Crawford-Howell t-test and comparison of stroke images to healthy controls. We then developed a classifier to discriminate the images into stroke or non-stroke categories following the lesion segmentation. Results The mean Dice similarity coefficient (DSC) for the test set was 0.50 ± 0.21 (min-max: 0.07–0.83) and mean net overlap was 0.66 ± 0.18 (min-max: 0.22–1). The experimental results for the classification of strokes from non-strokes showed mean accuracy, precision, sensitivity, and specificity of 73 %, 0.77 %, 84 %, and 69 %, respectively. Comparison with existing method The performance of our methods is comparable with previously published approaches based on machine learning and/or deep learning lesion segmentation techniques. However, most of the previously published methods have yielded low sensitivity, are computationally heavy, and difficult to interpret. The present approach is a significant improvement because it does not require high computation power and memory and can be implemented on a desktop workstation and integrated into the routine clinical diagnostic pipeline. Conclusions The current method is straightforward, fast, and shows good agreement with the lesions identified by human experts.

Fear protects organisms by increasing vigilance and preparedness, and by coordinating survival responses during life-threatening encounters. The fear circuit must thus operate on multiple timescales ranging from preparatory sustained alertness to acute fight-or-flight responses. Here we studied the brain basis of sustained (“looming”) and acute fear using naturalistic functional magnetic resonance imaging (fMRI) enabling analysis of different time-scales of fear responses. Subjects (N = 51) watched feature-length horror movies while their hemodynamic brain activity was measured with fMRI. Time-variable intersubject correlation (ISC) was used to quantify the reliability of brain activity across participants, and seed-based phase synchronization was used for characterizing dynamic connectivity. Subjective ratings of fear were obtained from a separate sample, and were used to assess how synchronization and functional connectivity varied with emotional intensity. These data suggest that acute and sustained fear are supported by distinct neural pathways, with sustained fear amplifying mainly sensory responses, and acute fear increasing activity in brainstem, thalamus, amygdala and cingulate cortices. Sustained fear increased ISC in regions associated with acute fear, and also amplified functional connectivity within this network. The results were replicated in two independent experiments with different subject samples. The functional interplay between cortical networks involved in sustained anticipation of, and acute response to, threat involves a complex and dynamic interaction that depends on the proximity of threat, and the need to employ threat appraisals and vigilance for decision making and response selection.

IntroductionModelling of the radioactivity images produced by PET scanners into biologically meaningful quantities, such as binding potential, is a complex multi-stage process involving data retrieval, preprocessing, drawing reference regions, kinetic modelling, and post-processing of parametric images. The process is challenging to automatize mainly because of manual work related to input generation, thus prohibiting large-scale standardized analysis of brain PET data. To resolve this problem, we introduce the Magia pipeline that enables processing of brain PET data with minimal user intervention. We investigated the accuracy of Magia in the automatic brain-PET data processing with four tracers binding to different binding sites: [11C]raclopride, [11C]carfentanil, [11C]MADAM, and [11C]PiB.Materials and methodsFor each tracer, we processed 30 historical control subjects’ data with manual and automated methods. Five persons manually delineated the reference regions (cerebellar or occipital cortex depending on tracer) for each subject according to written and visual instructions. The automatic reference-region extraction was based on FreeSurfer parcellations. We first assessed inter-operator variance resulting from manual delineation of reference regions. Then we compared the differences between the manually and automatically produced reference regions and the subsequently obtained metrics.ResultsThe manually delineated reference regions were remarkably different from each other. The differences translated into differences in outcome measures (binding potential or SUV-ratio), and the intra-class correlation coefficients were between 47 % and 96 % for the tracers. While the Magia-derived reference regions were topographically very different from the manually defined reference regions, Magia produced outcome measures highly consistent with average of the manually obtained estimates. For [11C]carfentanil and [11C]PiB there was no bias, while for [11C]raclopride and [11C]MADAM Magia produced 3-5 % higher binding potentials as a result of slightly lower time-integrals of reference region time-activity curves.ConclusionEven if Magia produces reference regions that are anatomically different from manually drawn reference regions, the resulting outcome measures are highly similar. Based on these results and considering the high inter-operator variance of the manual method, the high level of standardization and strong scalability of Magia, we conclude that Magia can be reliably used to process brain PET data.

The reinforcement-sensitivity theory proposes that behavioural activation and inhibition systems (BAS and BIS, respectively) guide approach and avoidance behaviour in potentially rewarding and punishing situations. Their baseline activity presumably explains individual differences in behavioural dispositions when a person encounters signals of reward and harm. Yet, neurochemical bases of BAS and BIS have remained poorly understood. Here we used in vivo positron emission tomography with a μ-opioid receptor (MOR) specific ligand [11C]carfentanil to test whether individual differences in MOR availability would be associated with BAS or BIS. We scanned 49 healthy subjects and measured their BAS and BIS sensitivities using the BIS/BAS scales. BAS but not BIS sensitivity was positively associated with MOR availability in frontal cortex, amygdala, ventral striatum, brainstem, cingulate cortex and insula. Strongest associations were observed for the BAS subscale ‘Fun Seeking’. Our results suggest that endogenous opioid system underlies BAS, and that differences in MOR availability could explain inter-individual differences in reward seeking behaviour.

Emotions can be characterized by dimensions of arousal and valence (pleasantness). While the functional brain bases of emotional arousal and valence have been actively investigated, the neuromolecular underpinnings remain poorly understood. We tested whether the opioid and dopamine systems involved in reward and motivational processes would be associated with emotional arousal and valence. We used in vivo positron emission tomography to quantify μ-opioid receptor and type 2 dopamine receptor (MOR and D2R, respectively) availability in brains of 35 healthy adult females. During subsequent functional magnetic resonance imaging carried out to monitor hemodynamic activity, the subjects viewed movie scenes of varying emotional content. Arousal and valence were associated with hemodynamic activity in brain regions involved in emotional processing, including amygdala, thalamus, and superior temporal sulcus. Cerebral MOR availability correlated negatively with the hemodynamic responses to arousing scenes in amygdala, hippocampus, thalamus, and hypothalamus, whereas no positive correlations were observed in any brain region. D2R availability—here reliably quantified only in striatum—was not associated with either arousal or valence. These results suggest that emotional arousal is regulated by the MOR system, and that cerebral MOR availability influences brain activity elicited by arousing stimuli.

This study examines the alternatives to include crown base height (CBH) predictions in operational forest inventories based on airborne laser scanning (ALS) data. We studied 265 field sample plots in a strongly pine-dominated area in northeastern Finland. The CBH prediction alternatives used area-based metrics of sparse ALS data to produce this attribute by means of: 1) Tree-level imputation based on the -nearest neighbor (-nn) method and full field-measured tree lists including CBH observations as reference data; 2) Tree-level mixed-effects model (LME) prediction based on tree diameter (DBH) and height and ALS metrics as predictors of the models; 3) Plot-level prediction based on analyzing the computational geometry and topology of the ALS point clouds; and 4) Plot-level regression analysis using average CBH observations of the plots for model fitting. The results showed that all of the methods predicted CBH with an accuracy of 1â1.5 m. The plot-level regression model was the most accurate alternative, although alternatives producing tree-level information may be more interesting for inventories aiming at forest management planning. For this purpose, -nn approach is promising and it only requires that field measurements of CBH is added to the tree lists used as reference data. Alternatively, the LME-approach produced good results especially in the case of dominant trees.kkk

Seloste artikkelista: Maltamo M., Karjalainen T., Repola J., Vauhkonen J. (2018). Incorporating tree- and stand-level information on crown base height into multivariate forest management inventories based on airborne laser scanning. Silva Fennica vol. 52 no. 3 article id 10006. https://doi.org/10.14214/sf.10006