Brain Network Activity Research Articles

Prenatal environmental stressors impair postnatal microglia function and adult behavior in males.

SUMMARYGestational exposure to environmental toxins and socioeconomic stressors is epidemiologically linked to neurodevelopmental disorders with strong male bias, such as autism. We model these prenatal risk factors in mice by co-exposing pregnant dams to an environmental pollutant and limited-resource stress, which robustly activates the maternal immune system. Only male offspring display long-lasting behavioral abnormalities and alterations in the activity of brain networks encoding social interactions. Cellularly, prenatal stressors diminish microglial function within the anterior cingulate cortex, a central node of the social coding network, in males during early postnatal development. Precise inhibition of microglial phagocytosis within the anterior cingulate cortex (ACC) of wild-type (WT) mice during the same critical period mimics the impact of prenatal stressors on a male-specific behavior, indicating that environmental stressors alter neural circuit formation in males via impairing microglia function during development.

Magnetoencephalography can reveal deep brain network activities linked to memory processes.

Recording from deep neural structures such as hippocampus noninvasively and yet with high temporal resolution remains a major challenge for human neuroscience. Although it has been proposed that deep neuronal activity might be recordable during cognitive tasks using magnetoencephalography (MEG), this remains to be demonstrated as the contribution of deep structures to MEG recordings may be too small to be detected or might be eclipsed by the activity of large‐scale neocortical networks. In the present study, we disentangled mesial activity and large‐scale networks from the MEG signals thanks to blind source separation (BSS). We then validated the MEG BSS components using intracerebral EEG signals recorded simultaneously in patients during their presurgical evaluation of epilepsy. In the MEG signals obtained during a memory task involving the recognition of old and new images, we identified with BSS a putative mesial component, which was present in all patients and all control subjects. The time course of the component selectively correlated with stereo‐electroencephalography signals recorded from hippocampus and rhinal cortex, thus confirming its mesial origin. This finding complements previous studies with epileptic activity and opens new possibilities for using MEG to study deep brain structures in cognition and in brain disorders.

Diagnosis of Neural Activity among Abnormal Brain Regions in Patients with Major Depressive Disorder by Magnetic Resonance Imaging Features.

In order to explore the diagnostic value of magnetic resonance imaging (MRI) for neural activity among abnormal brain regions in patients with major depressive disorder (MDD), thirty patients with MDD (observation group) were selected for comparison with 30 healthy people without MDD (control group). The included subjects were examined by MRI to compare the MRI features and were analyzed for regional homogeneity (ReHo) and amplitude low-frequency fluctuations (ALFF). The results showed that compared with the control group, the brain regions with increased ReHo and ALFF in the observation group were medial frontal gyrus (right), middle temporal lobe (left), inferior parietal lobe (left), and posterior cerebellar lobe (right); the brain region with increased ReHo and ALFF in the observation group was the middle temporal gyrus (right). Compared with the control group, there were significant differences in ReHo and ALFF in the observation group. It was found that the brain function of patients with MDD was abnormal compared with that of the normal subjects, and the brain network activity was also abnormal. MRI features can be used to explore abnormal brain regions in patients with MDD and have positive guiding value.

Alteration of Degree Centrality in Adolescents With Early Blindness.

Congenital nystagmus in infants and young children can lead to early blindness (EB). Previous neuroimaging studies have demonstrated that EB is accompanied by alterations in brain structure and function. However, the effects of visual impairment and critical developmental periods on brain functional connectivity at rest have been unclear. Here, we used the voxel-wise degree centrality (DC) method to explore the underlying functional network brain activity in adolescents with EB. Twenty-one patients with EBs and 21 sighted controls (SCs) underwent magnetic resonance imaging. Differences between the two groups were assessed using the DC method. Moreover, the support vector machine (SVM) method was used to differentiate patients with EB patients from the SCs according to DC values. Compared with the SCs, the patients with EB had increased DC values in the bilateral cerebellum_6, cerebellum vermis_4_5, bilateral supplementary motor areas (SMA), and left fusiform gyrus; the patients with EB had decreased DC values in the bilateral rectal gyrus and left medial orbital frontal gyrus. The SVM classification of the DC values achieved an overall accuracy of 70.45% and an area under the curve of 0.86 in distinguishing between the patients with EB and the SCs. Our study may reveal the neuromechanism of neuroplasticity in EB; the findings provide an imaging basis for future development of restorative visual therapies and sensory substitution devices, and future assessments of visual rehabilitation efficacy.

Perinatal Supplementation of Egg Yolk Enhances Cognition and Alters Brain Network Function in Offspring

ObjectivesEgg yolks are a nutrient dense food often recommended to pregnant women, as they contain bioactive compounds that enhance brain development in offspring. We examined the effects of perinatal intake of egg yolks on cognition and brain functional network activity in offspring using a translational sow/piglet dyad model. MethodsSows were fed a control diet (n = 6) or a diet containing egg yolks (n = 5,350 mg egg yolk powder/kg BW/day, equivalent to ∼3 eggs/day for humans) from late gestation throughout lactation. At weaning, piglet offspring (n = 4/sow, total n = 44) performed object recognition testing (ORT) to assess hippocampal-dependent learning and memory outcomes. A subset of the piglets (n = 2/sow, total n = 22) underwent magnetic resonance imaging (MRI) to acquire diffusion tensor imaging (DTI) and resting-state functional MRI. Correlation analysis of outcomes from ORT and MRI was performed. ResultsPiglets from egg yolk fed sows spent more time with novel objects than familiar objects (p = 0.039), suggesting that maternal intake of egg yolk may improve hippocampal-dependent cognitive outcomes. DTI analysis showed that perinatal intake of egg yolks tended to increase fiber length in the hippocampus (p = 0.073) compared to control. Moreover, intake of egg yolk resulted in a 14.3% increase in functional connectivity in the cerebellar network (p = 0.025) and a 15.6% trending increase in the executive network (p = 0.089) compared to control. Interestingly, the visual network was positively correlated with proportional frequency (p = 0.043) and time (p = 0.078) spent with novel objects and negatively correlated with proportional frequency (p = 0.007) and time (p = 0.016) spent with familiar objects, suggesting that the activation of visual network may influence hippocampal-dependent cognitive outcomes at weaning. ConclusionsPerinatal intake of egg yolk enhanced hippocampal-dependent learning and memory, increased fiber length in the hippocampus and altered brain functional connectivity in offspring at weaning. The findings from this study support that egg yolk altered activation of specific brain networks are that associated with cognitive outcomes in weaning piglets. Funding SourcesThis work was supported by grants to H.J.P from the USDA-National Institute of Food and Agriculture and the Egg Nutrition Center.

Rest-fMRI based comparison study between autism spectrum disorder and typically control using graph frequency bands

Graph signal processing (GSP) is a subset of signal processing, allowing for the analysis of functional magnetic resonance imaging (fMRI) data in the topological domain of the brain. One of the most important and popular tools of GSP is graph Fourier transform (GFT), which can analyze the brain signals in different graph frequency bands. This paper has analyzed the resting-state fMRI (rfMRI) data of two sites using the GFT tool to discover new knowledge about autism spectrum disorder (ASD) and find features discriminating between ASD subjects and typical controls (TCs). The results were reported for both structural and functional atlases with different numbers of regions of interest (ROIs). For the ASD group, the signal energy concentrations in low and somewhat high-frequency bands declined by increasing age in most well-known brain networks. The changes of signal energy levels in different graph frequency bands were less for ASD subjects in comparison to TC ones. This result seems to reflect the difficulty in dynamic switching, which in turn leads to lower behavioral flexibility in the ASD group. In the low graph frequency band, the segregation of brain ROIs and brain networks increased with the age of ASD subjects. For TCs, growing up led to the integration of brain ROIs and segregation of brain networks in low and high-frequency bands, respectively. In the low-frequency band, the growing process was accompanied by lower activation and higher isolation of ASD brain networks. In addition, the segregation of salient-ventral attention network and dorsal attention network of ASD subjects grew with age. The structural atlas results indicated the reduced segregation of ASD subjects' default mode network in the high graph frequency band. The cross-frequency functional connectivity analysis showed that high-frequency signals of the right precentral gyrus and right precuneus posterior cingulate cortex had connections with almost all the low-frequency ROIs so that all connections were dramatically different between ASD and TC. The results of different scenarios at different graph frequency bands demonstrate that the combinatorial usage of functional and structural data through GSP can open a new avenue to investigate ASD.

Normal aging in mice is associated with a global reduction in cortical spectral power and network-specific declines in functional connectivity

Normal aging is associated with a variety of neurologic changes including declines in cognition, memory, and motor activity. These declines correlate with neuronal changes in synaptic structure and function. Degradation of brain network activity and connectivity represents a likely mediator of age-related functional deterioration resulting from these neuronal changes. Human studies have demonstrated both general decreases in spontaneous cortical activity and disruption of cortical networks with aging. Current techniques used to study cerebral network activity are hampered either by limited spatial resolution (e.g. electroencephalography, EEG) or limited temporal resolution (e.g., functional magnetic resonance imaging, fMRI). Here we utilize mesoscale imaging of neuronal activity in Thy1-GCaMP6f mice to characterize neuronal network changes in aging with high spatial resolution across a wide frequency range. We show that while evoked activity is unchanged with aging, spontaneous neuronal activity decreases across a wide frequency range (0.01–4 Hz) involving all regions of the cortex. In contrast to this global reduction in cortical power, we found that aging is associated with functional connectivity (FC) deterioration of select networks including somatomotor, cingulate, and retrosplenial nodes. These changes are corroborated by reductions in homotopic FC and node degree within somatomotor and visual cortices. Finally, we found that whole-cortex delta power and delta band node degree correlate with exploratory activity in young but not aged animals. Together these data suggest that aging is associated with global declines in spontaneous cortical activity and focal deterioration of network connectivity, and that these reductions may be associated with age-related behavioral declines.

Handwriting Declines With Human Aging: A Machine Learning Study.

BackgroundHandwriting is an acquired complex cognitive and motor skill resulting from the activation of a widespread brain network. Handwriting therefore may provide biologically relevant information on health status. Also, handwriting can be collected easily in an ecological scenario, through safe, cheap, and largely available tools. Hence, objective handwriting analysis through artificial intelligence would represent an innovative strategy for telemedicine purposes in healthy subjects and people affected by neurological disorders.Materials and MethodsOne-hundred and fifty-six healthy subjects (61 males; 49.6 ± 20.4 years) were enrolled and divided according to age into three subgroups: Younger adults (YA), middle-aged adults (MA), and older adults (OA). Participants performed an ecological handwriting task that was digitalized through smartphones. Data underwent the DBNet algorithm for measuring and comparing the average stroke sizes in the three groups. A convolutional neural network (CNN) was also used to classify handwriting samples. Lastly, receiver operating characteristic (ROC) curves and sensitivity, specificity, positive, negative predictive values (PPV, NPV), accuracy and area under the curve (AUC) were calculated to report the performance of the algorithm.ResultsStroke sizes were significantly smaller in OA than in MA and YA. The CNN classifier objectively discriminated YA vs. OA (sensitivity = 82%, specificity = 80%, PPV = 78%, NPV = 79%, accuracy = 77%, and AUC = 0.84), MA vs. OA (sensitivity = 84%, specificity = 56%, PPV = 78%, NPV = 73%, accuracy = 74%, and AUC = 0.7), and YA vs. MA (sensitivity = 75%, specificity = 82%, PPV = 79%, NPV = 83%, accuracy = 79%, and AUC = 0.83).DiscussionHandwriting progressively declines with human aging. The effect of physiological aging on handwriting abilities can be detected remotely and objectively by using machine learning algorithms.

Transcranial electrical stimulation of dorsolateral prefrontal cortex in substance use disorder therapy

There is a growing interest in therapeutic applications of non-invasive brain stimulation methods. Transcranial electrical stimulation is a non-invasive brain stimulation method used to modulate central nervous system excitability. The procedure involves placing two electrodes on the patient’s head through which very low-intensity electrical current is sent. Transcranial electrical stimulation methods include transcranial direct current stimulation and transcranial alternating current stimulation. These methods are considered to be safe and relatively inexpensive, and can be used in home settings. Research conducted in recent years suggests that transcranial electrical stimulation can be applied to support substance use disorder therapy. The positive effects of stimulation include decreased craving and frequency of substance use, an improved quality of life and changes in the activity of functional brain networks. Transcranial direct current stimulation with the anode being placed over the right dorsolateral prefrontal cortex and the cathode being placed over the left dorsolateral prefrontal cortex is considered to be of a particularly high therapeutic potential. There are a limited number of studies which indicate that not only direct current stimulation, but also alternating current stimulation can be used for substance use disorder therapy.

P284. Spectral-Temporal Electrophysiological Features Predict Short-Term Plasticity in Humans Following Repetitive Stimulation

Stimulating specific parts of the brain allows us to better understand the activity of brain networks. Hebbian theory suggests: repetitive stimulation of regions that are functionally connected (‘fire together’) undergo eventual neural plasticity(‘wire together’). However, it's unclear how Hebbian theory manifests when evaluating the local field potential temporal-spectral changes after repetitive stimulation. Our previous research demonstrated a relationship between post-stimulation changes in the evoked potential and pre-stimulation evoked potentials.

Neural excursions from manifold structure explain patterns of learning during human sensorimotor adaptation.

Humans vary greatly in their motor learning abilities, yet little is known about the neural mechanisms that underlie this variability. Recent neuroimaging and electrophysiological studies demonstrate that large-scale neural dynamics inhabit a low-dimensional subspace or manifold, and that learning is constrained by this intrinsic manifold architecture. Here, we asked, using functional MRI, whether subject-level differences in neural excursion from manifold structure can explain differences in learning across participants. We had subjects perform a sensorimotor adaptation task in the MRI scanner on 2 consecutive days, allowing us to assess their learning performance across days, as well as continuously measure brain activity. We find that the overall neural excursion from manifold activity in both cognitive and sensorimotor brain networks is associated with differences in subjects' patterns of learning and relearning across days. These findings suggest that off-manifold activity provides an index of the relative engagement of different neural systems during learning, and that subject differences in patterns of learning and relearning are related to reconfiguration processes occurring in cognitive and sensorimotor networks.

Multi-dynamic modelling reveals strongly time-varying resting fMRI correlations.

The activity of functional brain networks is responsible for the emergence of time-varying cognition and behaviour. Accordingly, time-varying correlations (Functional Connectivity) in resting fMRI have been shown to be predictive of behavioural traits, and psychiatric and neurological conditions. Typically, methods that measure time varying Functional Connectivity (FC), such as sliding windows approaches, do not separately model when changes occur in the mean activity levels from when changes occur in the FC, therefore conflating these two distinct types of modulation. We show that this can bias the estimation of time-varying FC to appear more stable over time than it actually is. Here, we propose an alternative approach that models changes in the mean brain activity and in the FC as being able to occur at different times to each other. We refer to this method as the Multi-dynamic Adversarial Generator Encoder (MAGE) model, which includes a model of the network dynamics that captures long-range time dependencies, and is estimated on fMRI data using principles of Generative Adversarial Networks. We evaluated the approach across several simulation studies and resting fMRI data from the Human Connectome Project (1003 subjects), as well as from UK Biobank (13301 subjects). Importantly, we find that separating fluctuations in the mean activity levels from those in the FC reveals much stronger changes in FC over time, and is a better predictor of individual behavioural variability.

It is all about our impulsiveness – How consumer impulsiveness modulates neural evaluation of hedonic and utilitarian banners

The increasing number of active Internet users has encouraged companies to compete to design the most efficient online ads for their target audience. While some companies build their ads based on the functional and instrumental benefits of their advertised products (i.e., utilitarian banners), others emphasize the experiential, personal, and emotional advantages of purchasing their product (i.e., hedonic banners). This is the first study to use neuroimaging to address the debate in the literature regarding the processing and effectiveness of these types of messages. By means of functional Magnetic Resonance Imaging (fMRI), we explored the neural mechanisms by which an individual consumer trait, namely consumer impulsiveness, influences the evaluation of hedonic and utilitarian banners. The neural results revealed that more impulsive consumers exhibit a higher level of activation in brain regions linked to reward, trust, emotion, as well as a reduction of activity in self-control brain networks, when viewing hedonic banners. Consumers reporting lower levels of impulsiveness (i.e., prudent users), in turn, exhibited stronger activation in brain regions associated with self-control and cognition when evaluating utilitarian banners. Consequently, on the basis of an objective and neuropsychological approach, these results can be used to inform companies about the type of online advertising they should use based on the characteristics of their target audience.

Cross-Frequency Brain Network Dynamics Support Pitch Change Detection.

Processing auditory sequences involves multiple brain networks and is crucial to complex perception associated with music appreciation and speech comprehension. We used time-resolved cortical imaging in a pitch change detection task to detail the underlying nature of human brain network activity, at the rapid time scales of neurophysiology. In response to tone sequence presentation to the participants, we observed slow inter-regional signaling at the pace of tone presentations (2-4 Hz) that was directed from auditory cortex toward both inferior frontal and motor cortices. Symmetrically, motor cortex manifested directed influence onto auditory and inferior frontal cortices via bursts of faster (15-35 Hz) activity. These bursts occurred precisely at the expected latencies of each tone in a sequence. This expression of interdependency between slow/fast neurophysiological activity yielded a form of local cross-frequency phase-amplitude coupling in auditory cortex, which strength varied dynamically and peaked when pitch changes were anticipated. We clarified the mechanistic relevance of these observations in relation to behavior by including a group of individuals afflicted by congenital amusia, as a model of altered function in processing sound sequences. In amusia, we found a depression of inter-regional slow signaling toward motor and inferior frontal cortices, and a chronic overexpression of slow/fast phase-amplitude coupling in auditory cortex. These observations are compatible with a misalignment between the respective neurophysiological mechanisms of stimulus encoding and internal predictive signaling, which was absent in controls. In summary, our study provides a functional and mechanistic account of neurophysiological activity for predictive, sequential timing of auditory inputs.SIGNIFICANCE STATEMENT Auditory sequences are processed by extensive brain networks, involving multiple systems. In particular, fronto-temporal brain connections participate in the encoding of sequential auditory events, but so far, their study was limited to static depictions. This study details the nature of oscillatory brain activity involved in these inter-regional interactions in human participants. It demonstrates how directed, polyrhythmic oscillatory interactions between auditory and motor cortical regions provide a functional account for predictive timing of incoming items in an auditory sequence. In addition, we show the functional relevance of these observations in relation to behavior, with data from both normal hearing participants and a rare cohort of individuals afflicted by congenital amusia, which we considered here as a model of altered function in processing sound sequences.

Large-scale brain network activation during emotional inhibitory control: Associations with alcohol misuse in college freshmen.

The transition to college is associated with increased risk of alcohol misuse and a consequent increase in negative, alcohol-related social and health impacts. Traits associated with ongoing brain maturation during this period, including impulsivity in emotional contexts, could contribute to risky alcohol use. This functional magnetic resonance imaging (fMRI) study examined brain network activation strength during an emotional inhibitory control task (Go-NoGo), which required participants to ignore background images with negative or neutral emotional valence during performance. Participants were 60 college freshmen (aged 18-20years, 33 women). Survey measures, completed at baseline and one-year follow-up (follow-up n=52, 29 women), assessed alcohol misuse alcohol use disorders identification test (AUDIT), alcohol/substance use counseling center assessment of psychological symptoms (C-CAPS), and negative consequences of alcohol use young adult alcohol consequences questionnaire (YAACQ). Measures were examined relative to network activation strength, on the Negative NoGo>Neutral NoGo contrast, of four large-scale brain networks implicated in top-down regulation of cognition and attention: right and left lateral frontoparietal networks (rL-FPN; lL-FPN), dorsal attention network (DAN), and salience network (SN). Activation strength of DAN was negatively associated with scores on the AUDIT (p=0.013) and YAACQ (p=0.004) at baseline, and with C-CAPS score at baseline and follow-up (p=0.002; p=0.005), and positively associated with accuracy on NoGo trials with negative backgrounds (p=0.014). Activation strength of rL-FPN was positively associated with C-CAPS score at follow-up (p=0.003). SN activation strength was negatively associated with accuracy on NoGo trials with negative (p<0.001) and neutral (p=0.002) backgrounds and with the accuracy difference between negative versus neutral NoGo trials (p=0.003). These findings suggest that less engagement of large-scale brain circuitry that supports top-down attentional control, specifically during negative emotions, is associated with more problematic drinking in emerging adults who attend college. This pattern of network activation may serve as a risk marker for ongoing self-regulation deficits during negative emotion that could increase risk of problematic alcohol use and negative impacts of drinking.

Dynamic functional brain network connectivity during pseudoword processing relates to children's reading skill

Learning to read requires children to link print (orthography) with its corresponding speech sounds (phonology). Yet, most EEG studies of reading development focus on emerging functional specialization (e.g., developing increasingly refined orthographic representations), rather than directly measuring the functional connectivity that links orthography and phonology in real time. In this proof-of-concept study we relate children's reading skill to both orthographic specialization for print (via the N170, also called the N1, event related potential, ERP) and orthographic-phonological integration (via dynamic/event-related EEG phase synchronization – an index of functional brain network connectivity). Typically developing English speaking children (n = 24; 4–14 years) and control adults (n = 20; 18–35 years) viewed pseudowords, consonants and unfamiliar false fonts during a 1-back memory task while 64-channel EEG was recorded. Orthographic specialization (larger N170 for pseudowords vs. false fonts) became more left-lateralized with age, but not with reading skill. Conversely, children's reading skill correlated with functional brain network connectivity during pseudoword processing that requires orthography-phonology linking. This was seen during two periods of simultaneous low frequency synchronization/high frequency desynchronization of posterior-occipital brain network activity. Specifically, in stronger readers, left posterior-occipital activity showed more delta (1–3Hz) synchronization around 300–500 ms (simultaneous with gamma 30–80 Hz desynchronization) and more gamma desynchronization around 600–1000 ms (simultaneous with theta 3–7Hz synchronization) during pseudoword vs. false font processing. These effects were significant even when controlling for age (moderate – large effect sizes). Dynamic functional brain network connectivity measures the brain's real-time sound-print linking. It may offer an under-explored, yet sensitive, index of the neural plasticity associated with reading development.

Complex functional brain network properties in anorexia nervosa

BackgroundAnorexia nervosa (AN) is a disorder characterized by an incapacitating fear of weight gain and by a disturbance in the way the body is experienced, facets that motivate dangerous weight loss behaviors. Multimodal neuroimaging studies highlight atypical neural activity in brain networks involved in interoceptive awareness and reward processing.MethodsThe current study used resting-state neuroimaging to model the architecture of large-scale functional brain networks and characterize network properties of individual brain regions to clinical measures. Resting-state neuroimaging was conducted in 62 adolescents, 22 (21 female) with a history of AN and 40 (39 female) healthy controls (HCs). Sensorimotor and basal ganglia regions, as part of a 165-region whole-brain network, were investigated. Subject-specific functional brain networks were computed to index centrality. A contrast analysis within the general linear model covarying for age was performed. Correlations between network properties and behavioral measures were conducted (significance q < .05).ResultsCompared to HCs, AN had lower connectivity from sensorimotor regions, and greater connectivity from the left caudate nucleus to the right postcentral gyrus. AN demonstrated lower sensorimotor centrality, but higher basal ganglia centrality. Sensorimotor connectivity dyads and centrality exhibited negative correlations with body dissatisfaction and drive for thinness, two essential features of AN.ConclusionsThese findings suggest that AN is associated with greater communication from the basal ganglia, and lower information propagation in sensorimotor cortices. This is consistent with the clinical presentation of AN, where individuals exhibit patterns of rigid habitual behavior that is not responsive to bodily needs, and seem “disconnected” from their bodies.

High-definition transcranial direct current stimulation enhances network segregation during spatial navigation in mild cognitive impairment.

Spatial navigation is essential for everyday life and relies on complex network-level interactions. Recent evidence suggests that transcranial direct current stimulation (tDCS) can influence the activity of large-scale functional brain networks. We characterized brain-wide changes in functional network segregation (i.e. the balance of within vs. between-network connectivity strength) induced by high-definition (HD) tDCS in older adults with mild cognitive impairment (MCI) during virtual spatial navigation. Twenty patients with MCI and 22 cognitively intact older adults (healthy controls-HC) underwent functional magnetic resonance imaging following two counterbalanced HD-tDCS sessions (one active, one sham) that targeted the right parietal cortex (center anode at P2) and delivered 2mA for 20min. Compared to HC, MCI patients showed lower brain-wide network segregation following sham HD-tDCS. However, following active HD-tDCS, MCI patients' network segregation increased to levels similar to those in HC, suggesting functional normalization. Follow-up analyses indicated that the increase in network segregation for MCI patients was driven by HD-tDCS effects on the "high-level"/association brain networks, in particular the dorsal-attention and default-mode networks. HD-tDCS over the right parietal cortex may normalize the segregation/integration balance of association networks during spatial navigation in MCI patients, highlighting its potential to restore brain activity in Alzheimer's disease.

Neurobiological Correlates of Fatherhood During the Postpartum Period: A Scoping Review.

During the postpartum period, the paternal brain suffers extensive and complex neurobiological alterations, through the experience of father–infant interactions. Although the impact of such experience in the mother has been increasingly studied over the past years, less is known about the neurobiological correlates of fatherhood—that is, the alterations in the brain and other physiological systems associated with the experience of fatherhood. With the present study, we aimed to perform a scoping review of the available literature on the genetic, neuroendocrine, and brain correlates of fatherhood and identify the main gaps in the current knowledge. PubMed, Scopus, and Web of Science electronic databases were searched for eligible studies on paternal neuroplasticity during the postpartum period, over the past 15 years. Reference lists of relevant key studies and reviews were also hand-searched. The research team independently screened the identified studies based on the established inclusion criteria. Extracted data were analyzed using tables and descriptive synthesis. Among the 29 studies that met our inclusion criteria, the vast majority pertained to neuroendocrine correlates of fatherhood (n = 19), followed by brain activity or connectivity (n = 7), association studies of candidate genes (n = 2), and brain structure correlates (n = 1). Collectively, studies published during the past 15 years suggest the existence of significant endocrine (testosterone, oxytocin, prolactin, and cortisol levels) and neurofunctional alterations (changed activity in several brain networks related to empathy and approach motivation, emotional processing and mentalizing, emotion regulation, dorsal attention, and default mode networks) as a result of fatherhood, as well as preliminary evidence of genetic variability accounting for individual differences during the postpartum period in fathers. No studies were so far published evaluating epigenetic mechanisms associated with the paternal brain, something that was also the focus of the current review. We highlight the need for further research that examines neuroplasticity during the experience of fatherhood and that considers both the interplay between hormones and simultaneous assessment of the different biomarkers (e.g., associations between hormones and neural activity); data collection protocols and assessment times should also be refined.

Differentiating Melancholic and Non-melancholic Major Depressive Disorder Using Fractional Amplitude of Low-Frequency Fluctuations.

BackgroundMelancholic major depressive disorder (MDD) is a network-based brain disorder. However, whether or not network-based changes can be applied to differentiate melancholic (MEL) from non-melancholic (NMEL) MDD remains unclear.MethodsThirty-one MEL patients, 28 NMEL patients, and 32 matched healthy controls (HCs) were scanned using resting-state functional magnetic resonance imaging. Patients were assessed by the Chinese version of Snaith–Hamilton Pleasure Scale (SHAPS-C) and Temporal Experience of Pleasure Scale (TEPS). Fractional amplitude of low-frequency fluctuations (fALFF) and correlation analysis were used to analyze the data.ResultsCompared with HCs, the MEL group had significantly higher fALFF values in the bilateral inferior frontal gyrus and right supplementary motor area (SMA) and significantly lower fALFF values in the right inferior occipital gyrus (IOG), right middle temporal gyrus (MTG)/left IOG, and bilateral superior occipital gyrus (SOG)/MTG. On the other hand, the NMEL group showed significantly higher fALFF values in the bilateral SMA and significantly lower fALFF values in the bilateral posterior cingulate cortex/precuneus relative to HCs. Compared with the NMEL group, the MEL group showed significantly lower fALFF values in the left anterior cingulate cortex (ACC). A correlation was found between the fALFF values of the right SMA and the SHAPS-C in the MEL group. In addition, correlations were observed between the fALFF values of the left ACC and the TEPS contextual consummatory and total scores in all patients.ConclusionOur study uncovered that MDD exhibited altered brain activity in extensive brain networks, including the default-mode network, frontal-striatal network, reward system, and frontal-limbic network. Decreased fALFF in the left ACC might be applied to differentiate the two subtypes of MDD.