Single-dose serotonergic stimulation shows widespread effects on functional brain connectivity

Modulation of functional networks related to the serotonin neurotransmitter system by citalopram: Evidence from a multimodal neuroimaging study

BACKGROUND

Selective serotonin reuptake inhibitors (SSRIs) potentiate serotonergic neurotransmission by blocking the serotonin transporter (5-HTT), but the functional brain response to SSRIs involves neural circuits beyond regions with high 5-HTT expression. Currently, it is unclear whether and how changes in 5-HTT availability after SSRI administration modulate brain function of key serotoninergic circuits, including those characterized by high availability of the serotonin 1A receptor (5-HT1AR).

AIM

We investigated the association between 5-HTT availability and 5-HTT- and 5-HT1AR-enriched functional connectivity (FC) after an acute citalopram challenge.

METHODS

We analyzed multimodal data from a dose-response, placebo-controlled, double-blind study, in which 45 healthy women were randomized into three groups receiving placebo, a low (4 mg), or high (16 mg) oral dose of citalopram. Receptor-Enhanced Analysis of functional Connectivity by Targets was used to estimate 5-HTT- and 5-HT1AR-enriched FC from resting-state and task-based fMRI. 5-HTT availability was determined using [123I]FP-CIT single-photon emission computerized tomography.

RESULTS

5-HTT availability was negatively correlated with resting-state 5-HTT-enriched FC, and with task-dependent 5-HT1AR-enriched FC. Our exploratory analyses revealed lower 5-HT1AR-enriched FC in the low-dose group compared to the high-dose group at rest and the placebo group during the emotional face-matching task.

CONCLUSIONS

Taken together, our findings provide evidence for differential links between 5-HTT availability and brain function within 5-HTT and 5-HT1AR pathways and in context- and dose-dependent manner. As such, they support a potential pivotal role of the 5-HT1AR in the effects of citalopram on the brain and add to its potential as a therapeutic avenue for mood and anxiety disturbances.

Modulation of resting-state functional connectivity in default mode network is associated with the long-term treatment outcome in major depressive disorder

BACKGROUND

Treatment non-response and recurrence are the main sources of disease burden in major depressive disorder (MDD). However, little is known about its neurobiological mechanism concerning the brain network changes accompanying pharmacotherapy. The present study investigated the changes in the intrinsic brain networks during 6-month antidepressant treatment phase associated with the treatment response and recurrence in MDD.

METHODS

Resting-state functional magnetic resonance imaging was acquired from untreated patients with MDD and healthy controls at baseline. The patients' depressive symptoms were monitored by using the Hamilton Rating Scale for Depression (HAMD). After 6 months of antidepressant treatment, patients were re-scanned and followed up every 6 months over 2 years. Traditional statistical analysis as well as machine learning approaches were conducted to investigate the longitudinal changes in macro-scale resting-state functional network connectivity (rsFNC) strength and micro-scale resting-state functional connectivity (rsFC) associated with long-term treatment outcome in MDD.

RESULTS

Repeated measures of the general linear model demonstrated a significant difference in the default mode network (DMN) rsFNC change before and after the 6-month antidepressant treatment between remitters and non-remitters. The difference in the rsFNC change over the 6-month antidepressant treatment between recurring and stable MDD was also specific to DMN. Machine learning analysis results revealed that only the DMN rsFC change successfully distinguished non-remitters from the remitters at 6 months and recurring from stable MDD during the 2-year follow-up.

CONCLUSION

Our findings demonstrated that the intrinsic DMN connectivity could be a unique and important target for treatment and recurrence prevention in MDD.

Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine

Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.

Default Mode Network Modulation by Psychedelics: A Systematic Review

Psychedelics are a unique class of drug that commonly produce vivid hallucinations as well as profound psychological and mystical experiences. A grouping of interconnected brain regions characterized by increased temporal coherence at rest have been termed the Default Mode Network (DMN). The DMN has been the focus of numerous studies assessing its role in self-referencing, mind wandering, and autobiographical memories. Altered connectivity in the DMN has been associated with a range of neuropsychiatric conditions such as depression, anxiety, post-traumatic stress disorder, attention deficit hyperactive disorder, schizophrenia, and obsessive-compulsive disorder. To date, several studies have investigated how psychedelics modulate this network, but no comprehensive review, to our knowledge, has critically evaluated how major classical psychedelic agents-lysergic acid diethylamide, psilocybin, and ayahuasca-modulate the DMN. Here we present a systematic review of the knowledge base. Across psychedelics there is consistent acute disruption in resting state connectivity within the DMN and increased functional connectivity between canonical resting-state networks. Various models have been proposed to explain the cognitive mechanisms of psychedelics, and in one model DMN modulation is a central axiom. Although the DMN is consistently implicated in psychedelic studies, it is unclear how central the DMN is to the therapeutic potential of classical psychedelic agents. This article aims to provide the field with a comprehensive overview that can propel future research in such a way as to elucidate the neurocognitive mechanisms of psychedelics.

A complex systems perspective on psychedelic brain action

Recent findings suggesting the potential transdiagnostic efficacy of psychedelic-assisted therapy have fostered the need to deepen our understanding of psychedelic brain action. Functional neuroimaging investigations have found that psychedelics reduce the functional segregation of large-scale brain networks. However, beyond this general trend, findings have been largely inconsistent. We argue here that a perspective based on complexity science that foregrounds the distributed, interactional, and dynamic nature of brain function may render these inconsistencies intelligible. We propose that psychedelics induce a mode of brain function that is more dynamically flexible, diverse, integrated, and tuned for information sharing, consistent with greater criticality. This 'meta' perspective has the potential to unify past findings and guide intuitions toward compelling mechanistic models.

Neural Mechanisms and Psychology of Psychedelic Ego Dissolution

Neuroimaging studies of psychedelics have advanced our understanding of hierarchical brain organization and the mechanisms underlying their subjective and therapeutic effects. The primary mechanism of action of classic psychedelics is binding to serotonergic 5-HT2A receptors. Agonist activity at these receptors leads to neuromodulatory changes in synaptic efficacy that can have a profound effect on hierarchical message-passing in the brain. Here, we review the cognitive and neuroimaging evidence for the effects of psychedelics: in particular, their influence on selfhood and subject-object boundaries-known as ego dissolution-surmised to underwrite their subjective and therapeutic effects. Agonism of 5-HT2A receptors, located at the apex of the cortical hierarchy, may have a particularly powerful effect on sentience and consciousness. These effects can endure well after the pharmacological half-life, suggesting that psychedelics may have effects on neural plasticity that may play a role in their therapeutic efficacy. Psychologically, this may be accompanied by a disarming of ego resistance that increases the repertoire of perceptual hypotheses and affords alternate pathways for thought and behavior, including those that undergird selfhood. We consider the interaction between serotonergic neuromodulation and sentience through the lens of hierarchical predictive coding, which speaks to the value of psychedelics in understanding how we make sense of the world and specific predictions about effective connectivity in cortical hierarchies that can be tested using functional neuroimaging. SIGNIFICANCE STATEMENT: Classic psychedelics bind to serotonergic 5-HT2A receptors. Their agonist activity at these receptors leads to neuromodulatory changes in synaptic efficacy, resulting in a profound effect on information processing in the brain. Here, we synthesize an abundance of brain imaging research with pharmacological and psychological interpretations informed by the framework of predictive coding. Moreover, predictive coding is suggested to offer more sophisticated interpretations of neuroimaging findings by bridging the role between the 5-HT2A receptors and large-scale brain networks.

Postpartum depression: A role for psychedelics?

BACKGROUND

Postpartum depression (PPD) is a major public health concern and has, at its core, a sense of maternal 'disconnection' - from the self, the infant, and the support system. While PPD bears similarities with MDD, there is increasing evidence for its distinct nature, especially with the unique aspect of the mother-infant relationship. Current treatment modalities for PPD, largely based on those used in major depressive disorder (MDD), have low remission rates with emerging evidence for treatment resistance. It is, therefore, necessary to explore alternative avenues of treatment for PPD.

OBJECTIVE

In this narrative review, we outline the potential therapeutic rationale for serotonergic psychedelics in the treatment of PPD, and highlight safety and pragmatic considerations for the use of psychedelics in the postpartum period.

METHODS

We examined the available evidence for the treatment of PPD and the evidence for psychedelics in the treatment of MDD. We explored safety considerations in the use of psychedelics in the postpartum period.

RESULTS

There is increasing evidence for safety, and encouraging signals for efficacy, of psilocybin in the treatment of MDD. Psilocybin has been shown to catalyse a sense of 'reconnection' in participants with MDD. This effect in PPD, by fostering a sense of 'reconnection' for the mother, may allow for improved mood and maternal sensitivity towards the infant, which can positively impact maternal role gratification and the mother-infant relationship.

CONCLUSION

Psychedelic assisted therapy in PPD may have a positive effect on the mother-infant dyad and warrants further examination.

Influences of social uncertainty and serotonin on gambling decisions

In many instances in life, our decisions’ outcomes hinge on someone else’s choices (i.e., under social uncertainty). Behavioral and pharmacological work has previously focused on different types of uncertainty, such as risk and ambiguity, but not so much on risk behaviors under social uncertainty. Here, in two different studies using a double-blind, placebo-controlled, within-subject design, we administrated citalopram (a selective-serotonin-reuptake inhibitor) to male participants and investigated decisions in a gambling task under social and nonsocial uncertainty. In the social condition, gamble outcomes were determined by another participant. In the nonsocial condition, gamble outcomes were determined by a coin toss. We observed increased gamble acceptance under social uncertainty, especially for gambles with lower gains and higher losses, which might be indicative of a positivity bias in social expectations in conditions of high uncertainty about others’ behaviors. A similar effect was found for citalopram, which increased overall acceptance behavior for gambles irrespective of the source of uncertainty (social/nonsocial). These results provide insights into the cognitive and neurochemical processes underlying decisions under social uncertainty, with implications for research in risk-taking behaviors in healthy and clinical populations.

Differential contributions of serotonergic and dopaminergic functional connectivity to the phenomenology of LSD

RATIONALE

LSD is the prototypical psychedelic. Despite a clear central role of the 5HT2a receptor in its mechanism of action, the contributions of additional receptors for which it shows affinity and agonist activity remain unclear.

OBJECTIVES

We employed receptor-enriched analysis of functional connectivity by targets (REACT) to explore differences in functional connectivity (FC) associated with the distributions of the primary targets of LSD-the 5HT1a, 5HT1b, 5HT2a, D1 and D2 receptors.

METHODS

We performed secondary analyses of an openly available dataset (N = 15) to estimate the LSD-induced alterations in receptor-enriched FC maps associated with these systems. Principal component analysis (PCA) was employed as a dimension reduction strategy for subjective experiences associated with LSD captured by the Altered States of Consciousness (ASC) questionnaire. Correlations between these principal components as well as VAS ratings of subjective effects with receptor-enriched FC were explored.

RESULTS

Compared to placebo, LSD produced differences in FC when the analysis was enriched with each of the primary serotonergic and dopaminergic receptors. Altered receptor-enriched FC showed relationships with the subjective effects of LSD on conscious experience, with serotonergic and dopaminergic systems being predominantly associated with perceptual effects and perceived selfhood as well as cognition respectively. These relationships were dissociable, with different receptors showing the same relationships within, but not between, the serotonergic and dopaminergic systems.

CONCLUSIONS

These exploratory findings provide new insights into the pharmacology of LSD and highlight the need for additional investigation of non-5HT2a-mediated mechanisms.

The psychological processes of classic psychedelics in the treatment of depression: a systematic review protocol

BACKGROUND

There is currently renewed interest in the use of psychedelic therapy in the treatment of psychiatric disorders, including depression. The proposed systematic review will aim to identify, evaluate and summarise the psychological processes of change underlying psychedelic therapy for depression in the current literature and consider the implications these processes may have on the psychotherapy component of treatment.

METHODS

Scopus, PsycINFO, PubMed and Web of Science databases will be searched using relevant terms. Studies will be included if they discuss the use of a classic psychedelic to treat depression symptomology in an adult population and report or propose psychological processes responsible for depression symptom change. Two authors will independently screen articles, complete quality assessment tools and conduct data extraction. Empirical and non-empirical research will be extracted and synthesised separately. A narrative synthesis approach will be used to report psychological processes identified in the literature.

DISCUSSION

This systematic review will be the first to collate available evidence on the psychological processes associated with psychedelic therapy for depression. The preliminary nature of this research field is expected to result in the review having several limitations, namely heterogeneity between studies and the inclusion of limited empirical research. We intend for this review to present the current state of the literature, identify gaps and generate candidate variables that warrant further investigation.

SYSTEMATIC REVIEW

PROSPERO CRD42020197202.

Classic Psychedelic Drugs: Update on Biological Mechanisms

Renewed interest in the effects of psychedelics in the treatment of psychiatric disorders warrants a better understanding of the neurobiological mechanisms underlying the effects of these substances. During the past two decades, state-of-the-art studies of animals and humans have yielded new important insights into the molecular, cellular, and systems-level actions of psychedelic drugs. These efforts have revealed that psychedelics affect primarily serotonergic receptor subtypes located in cortico-thalamic and cortico-cortical feedback circuits of information processing. Psychedelic drugs modulate excitatory-inhibitory balance in these circuits and can participate in neuroplasticity within brain structures critical for the integration of information relevant to sensation, cognition, emotions, and the narrative of self. Neuroimaging studies showed that characteristic dimensions of the psychedelic experience obtained through subjective questionnaires as well as alterations in self-referential processing and emotion regulation obtained through neuropsychological tasks are associated with distinct changes in brain activity and connectivity patterns at multiple-system levels. These recent results suggest that changes in self-experience, emotional processing, and social cognition may contribute to the potential therapeutic effects of psychedelics.

Escitalopram modulates learning content-specific neuroplasticity of functional brain networks

Learning-induced neuroplastic changes, further modulated by content and setting, are mirrored in brain functional connectivity (FC). In animal models, selective serotonin reuptake inhibitors (SSRIs) have been shown to facilitate neuroplasticity. This is especially prominent during emotional relearning, such as fear extinction, which may translate to clinical improvements in patients. To investigate a comparable modulation of neuroplasticity in humans, 99 healthy subjects underwent three weeks of emotional (matching faces) or non-emotional learning (matching Chinese characters to unrelated German nouns). Shuffled pairings of the original content were subsequently relearned for the same time. During relearning, subjects received either a daily dose of the SSRI escitalopram or placebo. Resting-state functional magnetic resonance imaging was performed before and after the (re-)learning phases. FC changes in a network comprising Broca's area, the medial prefrontal cortex, the right inferior temporal and left lingual gyrus were modulated by escitalopram intake. More specifically, it increased the bidirectional connectivity between medial prefrontal cortex and lingual gyrus for non-emotional and the connectivity from medial prefrontal cortex to Broca's area for emotional relearning. The context dependence of these effects together with behavioral correlations supports the assumption that SSRIs in clinical practice improve neuroplasticity rather than psychiatric symptoms per se. Beyond expanding the complexities of learning, these findings emphasize the influence of external factors on human neuroplasticity.

Effects of escitalopram therapy on resting-state functional connectivity of subsystems of the default mode network in unmedicated patients with major depressive disorder

Antidepressants are often the first-line medications prescribed for patients with major depressive disorder (MDD). Given the critical role of the default mode network (DMN) in the physiopathology of MDD, the current study aimed to investigate the effects of antidepressants on the resting-state functional connectivity (rsFC) within and between the DMN subsystems. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data from 36 unmedicated MDD patients at baseline and after escitalopram treatment for 12 weeks. The rs-fMRI data were also collected from 61 matched healthy controls at the time point with the same interval. Then, we decomposed the DMN into three subsystems based on a template from previous studies and computed the rsFC within and between the three subsystems. Finally, repeated measures analysis of covariance was conducted to identify the main effect of group and time and their interaction effect. We found that the significantly reduced within-subsystem rsFC in the DMN core subsystem in patients with MDD at baseline was increased after escitalopram treatment and became comparable with that in the healthy controls, whereas the reduced within-subsystem rsFC persisted in the DMN dorsal medial prefrontal cortex (dMPFC) and medial temporal subsystems in patients with MDD following escitalopram treatment. In addition, the reduced between-subsystem rsFC between the core and dMPFC subsystem showed a similar trend of change after treatment in patients with MDD. Moreover, our main results were confirmed using the DMN regions from another brain atlas. In the current study, we found different effects of escitalopram on the rsFC of the DMN subsystems. These findings deepened our understanding of the neuronal basis of antidepressants' effect on brain function in patients with MDD. The trial name: appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement. URL: http://www.chictr.org.cn/showproj.aspx?proj=21377 . Registration number: ChiCTR-OOC-17012566.

Psychiatric Neural Networks and Precision Therapeutics by Machine Learning

Learning and environmental adaptation increase the likelihood of survival and improve the quality of life. However, it is often difficult to judge optimal behaviors in real life due to highly complex social dynamics and environment. Consequentially, many different brain regions and neuronal circuits are involved in decision-making. Many neurobiological studies on decision-making show that behaviors are chosen through coordination among multiple neural network systems, each implementing a distinct set of computational algorithms. Although these processes are commonly abnormal in neurological and psychiatric disorders, the underlying causes remain incompletely elucidated. Machine learning approaches with multidimensional data sets have the potential to not only pathologically redefine mental illnesses but also better improve therapeutic outcomes than DSM/ICD diagnoses. Furthermore, measurable endophenotypes could allow for early disease detection, prognosis, and optimal treatment regime for individuals. In this review, decision-making in real life and psychiatric disorders and the applications of machine learning in brain imaging studies on psychiatric disorders are summarized, and considerations for the future clinical translation are outlined. This review also aims to introduce clinicians, scientists, and engineers to the opportunities and challenges in bringing artificial intelligence into psychiatric practice.

Eight-week antidepressant treatment reduces functional connectivity in first-episode drug-naïve patients with major depressive disorder

Previous neuroimaging studies have revealed abnormal functional connectivity of brain networks in patients with major depressive disorder (MDD), but findings have been inconsistent. A recent big‐data study found abnormal intrinsic functional connectivity within the default mode network in patients with recurrent MDD but not in first‐episode drug‐naïve patients with MDD. This study also provided evidence for reduced default mode network functional connectivity in medicated MDD patients, raising the question of whether previously observed abnormalities may be attributable to antidepressant effects. The present study (ClinicalTrials.gov identifier: NCT03294525) aimed to disentangle the effects of antidepressant treatment from the pathophysiology of MDD and test the medication normalization hypothesis. Forty‐one first‐episode drug‐naïve MDD patients were administrated antidepressant medication (escitalopram or duloxetine) for 8 weeks, with resting‐state functional connectivity compared between posttreatment and baseline. To assess the replicability of the big‐data finding, we also conducted a cross‐sectional comparison of resting‐state functional connectivity between the MDD patients and 92 matched healthy controls. Both Network‐Based Statistic analyses and large‐scale network analyses revealed intrinsic functional connectivity decreases in extensive brain networks after treatment, indicating considerable antidepressant effects. Neither Network‐Based Statistic analyses nor large‐scale network analyses detected significant functional connectivity differences between treatment‐naïve patients and healthy controls. In short, antidepressant effects are widespread across most brain networks and need to be accounted for when considering functional connectivity abnormalities in MDD.

MDMA-induced changes in within-network connectivity contradict the specificity of these alterations for the effects of serotonergic hallucinogens

It has been reported that serotonergic hallucinogens like lysergic acid diethylamide (LSD) induce decreases in functional connectivity within various resting-state networks. These alterations were seen as reflecting specific neuronal effects of hallucinogens and it was speculated that these shifts in connectivity underlie the characteristic subjective drug effects. In this study, we test the hypothesis that these alterations are not specific for hallucinogens but that they can be induced by monoaminergic stimulation using the non-hallucinogenic serotonin-norepinephrine-dopamine releasing agent 3,4-methylenedioxymethamphetamine (MDMA). In a randomized, placebo-controlled, double-blind, crossover design, 45 healthy participants underwent functional magnetic resonance imaging (fMRI) following oral administration of 125 mg MDMA. The networks under question were identified using independent component analysis (ICA) and were tested with regard to within-network connectivity. Results revealed decreased connectivity within two visual networks, the default mode network (DMN), and the sensorimotor network. These findings were almost identical to the results previously reported for hallucinogenic drugs. Therefore, our results suggest that monoaminergic substances can induce widespread changes in within-network connectivity in the absence of marked subjective drug effects. This contradicts the notion that these alterations can be regarded as specific for serotonergic hallucinogens. However, changes within the DMN might explain antidepressants effects of some of these substances.

Deactivation of anterior cingulate cortex during virtual social interaction in obsessive-compulsive disorder

Studies about social functioning in obsessive-compulsive disorder (OCD) are lacking, even though neuroimaging studies and metacognition evaluation results suggest abnormal neural responses during social interactions. This study examined neural responses of OCD patients during handshakes with a virtual avatar. Because of the nature of the handshaking task, we expected that OCD patients with predominantly contamination/washing symptoms (CON) would show different neural responses compared to healthy controls (HCs) and to disease-controlled (NCON) patients. Thirteen CON, 13 NCON, and 18 HC participants performed handshake tasks with clean or dirty virtual avatars while undergoing functional magnetic resonance imaging. During handshakes with a clean avatar, deactivation in the left anterior cingulate cortex was found in CON patients compared to NCON and HC subjects. This cortical deactivation also occurred with dirty-avatar handshakes, but the difference was significant only between the two OCD groups and HC patients. Deactivation in the left anterior cingulate cortex was correlated with both OCD symptom severity and social anxiety traits. This cortical deactivation in OCD, especially in CON patients, suggests that social dysfunction in OCD may be due to interactions between OCD symptoms and impairment in social cognition, including emotional processing.

Evaluation of Inhibitory Effects of Caffeine on Human Carcinoma Cells

One of the world's most consumed medications is caffeine which is available in the vast majority of beverages. Previously, some effects of caffeine have been evaluated including its inhibitory effect on cancer cells. But, the influence of caffeine on esophagus carcinoma squamous cells (CSC) and head and neck carcinoma cells still has not well understood. Herein, the relation between different amounts of caffeine with the proliferation rate of human esophagus carcinoma squamous cell line KYSE-30 as well as human head and neck carcinoma cell line HN5 was evaluated. Furthermore, concentrations of caffeine were adjusted and their effect on cells were studied. The inhibitory effects of caffeine on cells were measured using the conventional colorimetric MTT assay after 3 and 7 day of incubation. Our findings are suggested that caffeine has a significant inhibitory effect on both cell lines at the concentrations of 20, 50, and 70 milli-mol (mmol). The result shows that caffeine can prevent the proliferation of carcinoma cells and it is a perfect candidate for therapeutic applications.

Psychedelic drugs: neurobiology and potential for treatment of psychiatric disorders

Renewed interest in the use of psychedelics in the treatment of psychiatric disorders warrants a better understanding of the neurobiological mechanisms underlying the effects of these substances. After a hiatus of about 50 years, state-of-the art studies have recently begun to close important knowledge gaps by elucidating the mechanisms of action of psychedelics with regard to their effects on receptor subsystems, systems-level brain activity and connectivity, and cognitive and emotional processing. In addition, functional studies have shown that changes in self-experience, emotional processing and social cognition may contribute to the potential therapeutic effects of psychedelics. These discoveries provide a scientific road map for the investigation and application of psychedelic substances in psychiatry.

Effects of different smoothing on global and regional resting functional connectivity

PURPOSE

Spatial smoothing is an essential pre-processing step in the process of analysing functional magnetic resonance imaging (fMRI) data, both during an experimental task or during resting-state fMRI (rsfMRI). The main benefit of this spatial smoothing step is to artificially increase the signal-to-noise ratio of the fMRI signal. Previous fMRI studies have investigated the impact of spatial smoothing on task fMRI data, while rsfMRI studies usually apply the same analytical process used for the task data. However, this study investigates changes in different rsfMRI analyses, such as ROI-to-ROI, seed-to-voxels and ICA analyses.

METHODS

Nineteen healthy volunteers were scanned using rsfMRI with three applied smoothing kernels: 0 mm, 4 mm and 8 mm. Appropriate statistical comparisons were made.

RESULTS

The findings showed that spatial smoothing has a greater effect on rsfMRI data when analysed using seed-to-voxel-based analysis. The effect was less pronounced when analysing data using ROI-ROI or ICA analyses. The results demonstrated that even when analysing the data without the application of spatial smoothing, the results were significant compared with data analysed using a typical smoothing kernel. However, data analysed with lower-smoothing kernels produced greater negative correlations, particularly with the ICA analysis.

CONCLUSION

The results suggest that a medium smoothing kernel (around 4 mm) may be preferable, as it is comparable with the 8 mm kernel in all of the analyses performed. It is also recommended that the researchers consider analysing the data using two different smoothing kernels, as this will help to confirm the significance of the results and avoid overestimating the findings.

White matter connectivity differences between treatment responders and non-responders in patients with panic disorder

BACKGROUND

Panic disorder (PD) is a prevalent and highly disabling mental condition. However, less is known about relationships between biomarkers that may together predict a better response to pharmacological treatment. The objective of the present study was to compare the brain white matter (WM) connectivity between treatment-responsive patients with panic disorder (RPD) and non-responsive patients with panic disorder (NRPD) after 12 weeks of pharmacotherapy.

METHODS

Sixty-four patients with PD were enrolled in this study (RPD, n = 37; NRPD, n = 27). All patients were examined by using magnetic resonance imaging at 3 Tesla. The Panic Disorder Severity Scale (PDSS), Albany Panic and Phobia Questionnaire (APPQ), Anxiety Sensitivity Inventory-Revised (ASI-R), Beck Anxiety Inventory (BAI), and Beck Depression Inventory (BDI) were administered at baseline of the study. Fractional anisotropy (FA) data were compared using tract-based spatial statistics (TBSS).

RESULTS

TBSS results showed that the FA values of the patients with NRPD were significantly higher than of those with RPD in the WM regions such as the precentral gyrus, parahippocampal gyrus, posterior corona radiata, posterior thalamic radiation, posterior parts of the corpus callosum, and precuneus. Symptom severity scales, such as ASI-R scores, showed significant positive correlations of the FA values with the fronto-temporal WM regions in NRPD.

CONCLUSIONS

These results suggest that structural changes to areas such as the fronto-limbic regions and the posterior part of default mode network, could influence medication response in PD. Further studies with a larger number of patients should be performed to confirm our findings.

Functional consequences of acute tryptophan depletion on raphe nuclei connectivity and network organization in healthy women

Previous research on central nervous serotonin (5-HT) function provided evidence for a substantial involvement of 5-HT in the regulation of brain circuitries associated with cognitive and affective processing. The underlying neural networks comprise core subcortical/cortical regions such as amygdala and medial prefrontal cortex, which are assumed to be modulated amongst others by 5-HT. Beside the use of antidepressants, acute tryptophan depletion (ATD) is a widely accepted technique to manipulate of 5-HT synthesis and its respective metabolites in humans by means of a dietary and non-pharmacological tool. We used a double-blind, randomized, cross-over design with two experimental challenge conditions, i.e. ATD and tryptophan (TRP) supplementation (TRYP+) serving as a control. The aim was to perturb 5-HT synthesis and to detect its impact on brain functional connectivity (FC) of the upper serotonergic raphe nuclei, the amygdala and the ventromedial prefrontal cortex as well as on network organization using resting state fMRI. 30 healthy adult female participants (age: M ​= ​24.5 ​± ​4.4 ​yrs) were included in the final analysis. ATD resulted in a 90% decrease of TRP in the serum relative to baseline. Compared to TRYP ​+ ​for the ATD condition a significantly lower FC of the raphe nucleus to the frontopolar cortex was detected, as well as greater functional coupling between the right amygdala and the ventromedial prefrontal cortex. FC of the raphe nucleus correlated significantly with the magnitude of TRP changes for both challenge conditions (ATD & TRYP+). Network-based statistical analysis using time series from 260 independent anatomical ROIs revealed significantly greater FC after ATD compared to TRYP+ in several brain regions being part of the default-mode (DMN) and the executive-control networks (ECN), but also of salience or visual networks. Finally, we observed an impact of ATD on the rich-club organization in terms of decreased rich-club coefficients compared to TRYP+. In summary we could confirm previous findings that the putative decrease in brain 5-HT synthesis via ATD significantly alters FC of the raphe nuclei as well as of specific subcortical/cortical regions involved in affective, but also in cognitive processes. Moreover, an ATD-effect on the so-called rich-club organization of some nodes with the high degree was demonstrated. This may indicate effects of brain 5-HT on the integration of information flow from several brain networks.

Brainstem Modulation of Large-Scale Intrinsic Cortical Activity Correlations

Brain activity fluctuates continuously, even in the absence of changes in sensory input or motor output. These intrinsic activity fluctuations are correlated across brain regions and are spatially organized in macroscale networks. Variations in the strength, topography, and topology of correlated activity occur over time, and unfold upon a backbone of long-range anatomical connections. Subcortical neuromodulatory systems send widespread ascending projections to the cortex, and are thus ideally situated to shape the temporal and spatial structure of intrinsic correlations. These systems are also the targets of the pharmacological treatment of major neurological and psychiatric disorders, such as Parkinson's disease, depression, and schizophrenia. Here, we review recent work that has investigated how neuromodulatory systems shape correlations of intrinsic fluctuations of large-scale cortical activity. We discuss studies in the human, monkey, and rodent brain, with a focus on non-invasive recordings of human brain activity. We provide a structured but selective overview of this work and distil a number of emerging principles. Future efforts to chart the effect of specific neuromodulators and, in particular, specific receptors, on intrinsic correlations may help identify shared or antagonistic principles between different neuromodulatory systems. Such principles can inform models of healthy brain function and may provide an important reference for understanding altered cortical dynamics that are evident in neurological and psychiatric disorders, potentially paving the way for mechanistically inspired biomarkers and individualized treatments of these disorders.

Spatiotemporal brain activation pattern following acute citalopram challenge is dose dependent and associated with neuroticism: A human phMRI study

BACKGROUND

The initial effects of selective serotonin reuptake inhibitors (SSRIs) in the human living brain are poorly understood. We carried out a 3T resting state fMRI study with pharmacological challenge to determine the brain activation changes over time following different dosages of citalopram.

METHODS

During the study, 7.5 mg i.v. citalopram was administered to 32 healthy subjects. In addition, 11.25 mg citalopram was administered to a subset of 9 subjects to investigate the dose-response. Associations with neuroticism (assessed by the NEO PI-R) of the emerging brain activation to citalopram was also investigated.

RESULTS

Citalopram challenge evoked significant activation in brain regions that are part of the default mode network, the visual network and the sensorimotor network, extending to the thalamus, and midbrain. Most effects appeared to be dose-dependent and this was statistically significant in the middle cingulate gyrus. Individual citalopram-induced brain responses were positively correlated with neuroticism scores and its subscales in specific brain areas; anxiety subscale scores in thalamus and midbrain and self-consciousness scores in middle cingulate gyrus. There were no sex differences.

LIMITATIONS

We investigated only healthy subjects and we used a relatively low sample size in the 11.25 mg citalopram analysis.

DISCUSSION

Our results suggest that SSRIs acutely induce an increased arousal-like state of distributed cortical and subcortical systems that is mediated by enhanced serotonin neurotransmission according to levels of neuroticism and underpins trait sensitivity to environmental stimuli and stressors. Studies in depression are needed to determine how therapeutic effects eventually emerge. This article is part of the special issue entitled 'Serotonin Research: Crossing Scales and Boundaries'.

Resting-state dynamics as a neuromarker of dopamine administration in healthy female adults

BACKGROUND

Different neuromarkers of people's emotions, personality traits and behavioural performance have recently been identified. However, not much attention has been devoted to neuromarkers of neural responsiveness to drug administration.

AIMS

We investigated the predictive neuromarkers of acute dopamine (DA) administration.

METHODS

In a double-blind, within-subject study, we administrated a DA agonist (pramipexole) or placebo to 27 healthy female subjects. Using multivariate classification and prediction analyses, we examined whether dopaminergic modulations of task-free resting-state brain dynamics predict individual differences in pramipexole's modulation of facial attractiveness evaluations.

RESULTS

Our results demonstrate that pramipexole's effects on brain dynamics could be successfully discriminated from resting-state functional connectivity (accuracy: 78.9%; p < 0.0001). On the behavioural level, pramipexole increased facial attractiveness evaluations (t₍₃₉₎ = 4.44; p < 0.0001). In particular, pramipexole administration enhanced connectivity strength of the cinguloopercular network (t₍₂₃₎ = 3.29; p = 0.003) and increased brain signal variability in subcortical and prefrontal brain areas (t₍₁₃₎ = 3.05, p = 0.009). Importantly, multivariate predictive models reveal that pramipexole-dependent modulation of resting-state dynamics predicted the increase of facial attractiveness evaluations after pramipexole (connectivity strength: standardized mean squared error, smse = 0.65; p = 0.0007; brain signal variability: smse = 0.94, p = 0.015).

CONCLUSION

These results demonstrate that modulations of resting-state brain dynamics induced by a DA agonist predict drug-related effects on evaluation processes, providing a neuromarker of the neural responsiveness of specific brain networks to DA administration.

Selective serotonin reuptake inhibitors for functional recovery after stroke: similarities with the critical period and the role of experience-dependent plasticity

There has been a growing interest in the potential for plasticity-inducing pharmacological interventions to enhance post-stroke recovery. One group of drugs that continues to garner a great deal of attention in this regard is a class of antidepressants called the selective serotonin reuptake inhibitors. Here we propose a model for the mechanism by which these drugs may enhance plasticity after ischemic brain injury. First, we review the research in animal models demonstrating how selective serotonin reuptake inhibitors reopen the critical period for ocular dominance plasticity in adulthood. We then compare this period of heightened plasticity to the cellular and biochemical milieu of perilesional tissue after an ischemic event in the adult brain. We argue that selective serotonin reuptake inhibitors administered acutely after an ischemic stroke alter excitatory-inhibitory balance in perilesional tissue and reinstate a type of plasticity reminiscent of the critical period in development. Finally, we discuss opportunities for future research in this area in both the preclinical and clinical realms.

Antidepressant treatment, not depression, leads to reductions in behavioral and neural responses to pain empathy

Major depressive disorder (MDD) has been hypothesized to lead to impairments in empathy. Previous cross-sectional studies did not disentangle effects of MDD itself and antidepressant treatment. In this first longitudinal neuroimaging study on empathy in depression, 29 patients with MDD participated in two functional magnetic resonance imaging (fMRI) sessions before and after 3 months of antidepressant therapy. We compared their responses to an empathy for pain task to a group of healthy controls (N = 35). All participants provided self-report ratings targeting cognitive (perspective taking) and affective (unpleasant affect) aspects of empathy. To control for general effects on processing of negative affective states, participants additionally underwent an electrical pain task. Before treatment, we found no differences in empathic responses between controls and patients with MDD. After treatment, patients showed significant decreases in both affective empathy and activity of three a priori selected brain regions associated with empathy for pain. Decreases in affective empathy were moreover correlated with symptom improvement. Moreover, functional connectivity during the empathy task between areas associated with affective (anterior insula) and cognitive (precuneus) empathy decreased between sessions in the MDD group. Neither cognitive empathy nor responses to painful electrical shocks were changed after treatment. These findings contradict previous cross-sectional reports of empathy deficits in acute MDD. Rather, they suggest that antidepressant treatment reduces the aversive responses triggered by exposure to the suffering of others. Importantly, this cannot be explained by a general blunting of negative affect, as treatment did not change self-experienced pain.

Modeling the acute pharmacological response to selective serotonin reuptake inhibitors in human brain using simultaneous PET/MR imaging

Pharmacological imaging of the effects of selective serotonin reuptake inhibitors (SSRI) may aid the clarification of their mechanism of action and influence treatment of highly prevalent neuropsychiatric conditions if the detected effects could be related to patient outcomes. In a randomized double-blind design, 38 healthy participants received a constant infusion of 8 mg citalopram or saline during either their first or second of two PET/MR scans. Resting-state functional MRI (fMRI) was acquired simultaneously with PET data on the binding of serotonin transporters (5-HTT) using [¹¹C]DASB. Three different approaches for modeling of pharmacological fMRI response were tested separately. These relied on the use of regressors corresponding to (1) the drug infusion paradigm, (2) time courses of citalopram plasma concentrations and (3) changes in 5-HTT binding measured in each individual, respectively. Furthermore, the replication of results of a widely used model-free analysis method was attempted which assesses the deviation of signal in discrete time bins of fMRI data acquired after start of drug infusion. Following drug challenge, average 5-HTT occupancy was 69±7% and peak citalopram plasma levels were 111.8 ± 21.1 ng/ml. None of the applied methods could detect significant differences in the pharmacological response between SSRI and placebo scans. The failed replication of SSRI effects reported in the literature despite a threefold larger sample size highlights the importance of appropriate correction for family-wise error in order to avoid spurious results in pharmacological imaging. This calls for the development of analysis methods which take regional specialization and the dynamics of brain activity into account.

Cholinergic and serotonergic modulation of resting state functional brain connectivity in Alzheimer's disease

Disruption of cholinergic and serotonergic neurotransmitter systems is associated with cognitive, emotional and behavioural symptoms of Alzheimer's disease (AD). To investigate the responsiveness of these systems in AD we measured the effects of a single-dose of the selective serotonin reuptake inhibitor citalopram and acetylcholinesterase inhibitor galantamine in 12 patients with AD and 12 age-matched controls on functional brain connectivity with resting state functional magnetic resonance imaging. In this randomized, double blind, placebo-controlled crossover study, functional magnetic resonance images were repeatedly obtained before and after dosing, resulting in a dataset of 432 scans. Connectivity maps of ten functional networks were extracted using a dual regression method and drug vs. placebo effects were compared between groups with a multivariate analysis with signals coming from cerebrospinal fluid and white matter as covariates at the subject level, and baseline and heart rate measurements as confound regressors in the higher-level analysis (at p < 0.05, corrected). A galantamine induced difference between groups was observed for the cerebellar network. Connectivity within the cerebellar network and between this network and the thalamus decreased after galantamine vs. placebo in AD patients, but not in controls. For citalopram, voxelwise network connectivity did not show significant group × treatment interaction effects. However, we found default mode network connectivity with the precuneus and posterior cingulate cortex to be increased in AD patients, which could not be detected within the control group. Further, in contrast to the AD patients, control subjects showed a consistent reduction in mean connectivity with all networks after administration of citalopram. Since AD has previously been characterized by reduced connectivity between the default mode network and the precuneus and posterior cingulate cortex, the effects of citalopram on the default mode network suggest a restoring potential of selective serotonin reuptake inhibitors in AD. The results of this study also confirm a change in cerebellar connections in AD, which is possibly related to cholinergic decline.

Regional default mode network connectivity in major depressive disorder: modulation by acute intravenous citalopram

The relationship between altered default mode network (DMN) connectivity and abnormal serotonin function in major depressive disorder (MDD) has not been investigated. Using intravenous citalopram and resting-state fMRI, we investigated DMN intra-network connectivity and serotonin function in 77 healthy controls and patients with MDD. There were no significant main effects of MDD or citalopram on DMN intra-network connectivity; however, significant interactions indicated that group differences under saline were modified by citalopram. In MDD patients during saline infusion, in contrast with controls, the DMN (i) did not include the precuneus that was instead part of an anti-correlated network but (ii) did include amygdala that was part of the anti-correlated network in controls. Citalopram infusion in MDD patients restored the pattern seen in controls under saline. In healthy controls, citalopram infusion disengaged the precuneus from the DMN and engaged the amygdala, partially reproducing the abnormalities seen under saline in MDD. In exploratory analyses within the MDD group, greater rumination self-ratings were associated with greater intra-network connectivity of the anterior cingulate cortex with the DMN. We hypothesise that, in MDD, disengagement of the precuneus from the DMN relates to overgeneral memory bias in rumination. The opposite effect, with greater engagement of the amygdala in the DMN, reflects the negative valence of rumination. Reversal of these abnormalities by citalopram suggests that they may be related to impaired serotonin function. That citalopram engaged the amygdala in the DMN in controls may relate to the paradoxical effects on aversive processing seen with acute SSRIs in healthy subjects.

Acute tryptophan loading decreases functional connectivity between the default mode network and emotion-related brain regions

It has been shown that the functional architecture of the default mode network (DMN) can be affected by serotonergic challenges and these effects may provide insights on the neurobiological bases of depressive symptomatology. To deepen our understanding of this possible interplay, we used a double-blind, randomized, cross-over design, with a control condition and two interventions to decrease (tryptophan depletion) and increase (tryptophan loading) brain serotonin synthesis. Resting-state fMRI from 85 healthy subjects was acquired for all conditions 3 hr after the ingestion of an amino acid mixture containing different amounts of tryptophan, the dietary precursor of serotonin. The DMN was derived for each participant and session. Permutation testing was performed to detect connectivity changes within the DMN as well as between the DMN and other brain regions elicited by the interventions. We found that tryptophan loading increased tryptophan plasma levels and decreased DMN connectivity with visual cortices and several brain regions involved in emotion and affect regulation (i.e., putamen, subcallosal cortex, thalamus, and frontal cortex). Tryptophan depletion significantly reduced tryptophan levels but did not affect brain connectivity. Subjective ratings of mood, anxiety, sleepiness, and impulsive choice were not strongly affected by any intervention. Our data indicate that connectivity between the DMN and emotion-related brain regions might be modulated by changes in the serotonergic system. These results suggest that functional changes in the brain associated with different brain serotonin levels may be relevant to understand the neural bases of depressive symptoms.

Trajectories in Cerebral Blood Flow Following Antidepressant Treatment in Late-Life Depression: Support for the Vascular Depression Hypothesis

OBJECTIVE

Studies have identified longitudinally that there exists an association between depression, cerebral blood flow (CBF), and white matter hyperintensities that are thought to be due to vascular pathologies in the brain. However, the changes in CBF, a measure that reflects cerebrovascular integrity, following pharmacotherapy are not well understood. In this study, we investigated the dynamic CBF changes over the course of antidepressant treatment and the association of these changes with depressive symptoms.

METHODS

We used pseudocontinuous arterial spin labeling to investigate CBF changes in a sample of older patients (≥ 50 years of age; N = 46; 29 female) with a DSM-IV diagnosis of major depressive disorder. Participants had 5 magnetic resonance imaging scans (at baseline, the day after receiving a placebo, the day after receiving a first dose of venlafaxine, a week after starting venlafaxine treatment, and at the end of trial [12 weeks]). Montgomery-Asberg Depression Rating Scale (MADRS) was used to evaluate depression severity and treatment outcome. We investigated the association between changes in depression severity with changes in voxel-wise CBF while adjusting for potential confounding factors.

RESULTS

Increased CBF in the middle and posterior cingulate between baseline and end of treatment was significantly associated with percent decrease in MADRS score, independent of sex and Mini-Mental State Examination score (5,000 permutations, cluster forming threshold P < .005, family-wise error P < .05). No significant effects were detected between baseline and other scans (ie, placebo, acute [single dose], or subacute [after a week]).

CONCLUSIONS

Regional CBF increases were associated with decreases in depressive symptoms. This observation is consistent with the vascular depression hypothesis in late-life depression.

TRIAL REGISTRATION

ClinicalTrials.gov identifiers: NCT00892047 and NCT01124188.

Serotonin transporter occupancy by the SSRI citalopram predicts default-mode network connectivity

The default mode network (DMN) is an important connectivity hub, and alterations may play a role in the pathophysiology of several neuropsychiatric disorders. Despite the growing body of research on DMN (dys)function, the underlying neurochemical substrate remains to be elucidated. The serotonergic neurotransmitter system has been suggested to play a substantial role in modulating the DMN. Therefore, we investigated the association between serotonin transporter (SERT) occupancy by the selective serotonin reuptake inhibitor citalopram and DMN functional connectivity. Forty-five healthy female volunteers (mean age = 21.6y) participated in a double-dose study. The subjects were randomized to pre-treatment with placebo, a low (4 mg; 'low group') or clinically standard (16 mg; 'high group') oral citalopram dose (corresponding to 0%, ∼40% and ∼80% SERT occupancy, respectively). They underwent [¹²³I]FP-CIT single-photon emission computed tomography (SPECT) imaging to assess SERT occupancy. In addition, resting-state functional magnetic resonance imaging was used to measure DMN connectivity. With non-parametric permutation testing we assessed the association between SERT occupancy and DMN connectivity. We found that SERT occupancy by citalopram was negatively associated with DMN connectivity with a number of cortical regions, including the anterior cingulate cortex (ACC), paracingulate gyrus, postcentral gyrus, superior parietal gyrus and temporal pole. These findings provide further neurochemical evidence that the serotonin system dose-dependently modulates DMN function.

Advances and challenges in neuroimaging studies on the effects of serotonergic hallucinogens: Contributions of the resting brain

The effects of hallucinogenic drugs on the human brain have been studied since the earliest days of neuroimaging in the 1990s. However, approaches are often hard to compare and results are heterogeneous. In this chapter, we summarize studies investigating the effects of hallucinogens on the resting brain, with a special emphasis on replicability and limitations. In previous studies, similarities were observed between psilocybin, LSD, and ayahuasca, with respect to decreases in cerebral blood flow and increases in global functional connectivity in the precuneus and thalamus. Additionally, LSD consistently decreased functional connectivity within distinct resting state networks. Little convergence was observed for connectivity between networks and for blood flow in other brain regions. Although these studies are limited by small sample sizes and might be biased by unspecific drug effects on physiological parameters and the vascular system, current results indicate that neuroimaging could be a useful tool to elucidate the neuronal correlates of hallucinogenic effects.

The effects of serotonin modulation on medial prefrontal connectivity strength and stability: A pharmacological fMRI study with citalopram

BACKGROUND

Static and dynamic functional connectivity are being increasingly used to measure the effects of disease and a range of different interventions on brain networks. While preliminary evidence suggests that static connectivity can be modulated by chronic antidepressants administration in healthy individuals and in major depression, much less is known about the acute effects of antidepressants especially on dynamic functional connectivity changes. Here we examine acute effects of antidepressants on dynamic functional connectivity within the default mode network. The default mode network is a well described network with many functions in which the role of serotonin is not clear.

METHODS

In this work we measured acute pharmacological effects of an infusion of the selective serotonin reuptake inhibitor (SSRI) citalopram (10 mg) in a sample of thirteen healthy volunteers randomised to receive on two occasions the active compound or placebo in a cross over dosing.

RESULTS

Acute citalopram administration relative to placebo increased static connectivity between the medial prefrontal cortex and right dorsolateral prefrontal cortex and posterior cingulate cortex. The SSRI also induced a reduction in variability of connectivity with the medial prefrontal cortex in the precuneus and posterior cingulate cortex.

DISCUSSION

The measured changes are compatible with modified serotonin cortical availability.

The effect of a single dose of escitalopram on sensorimotor networks

INTRODUCTION

Serving as a pilot study of poststroke pharmacotherapy, the present investigation was intended to establish the effect of a single dose of escitalopram on motor task performance in normal volunteers.

METHODS

Ten healthy volunteers of median age 63 years including four females performed a well-studied tactile manipulation task in two fMRI sessions using a double-blind cross-over design. The sessions began approximately three hours after ingestion of 20 mg escitalopram or placebo presented in pseudorandom order. The fMRI image sequences were submitted to principal component analysis (PCA).

RESULTS

Based on volume correlations of task-related principal components with the mean component images derived in our previous study, we established the reproducibility of two networks of sensorimotor activity proposed there. The network reflecting motor control (cerebral pattern I) appeared invariably in placebo and verum conditions. In contrast, the other network, attributed to diminished motor control due to distracting mental processing (cerebral pattern II), emerged less regularly and exhibited more variability. Second-level PCAs of both conditions confirmed the findings of the initial analysis. Specifically, it validated the dominant and invariable expression of cerebral pattern I after application of a single dose of escitalopram. Dynamic causal modeling confirmed enhanced motor output as a result of a significantly increased connectivity between primary motor cortex and dorsal premotor cortex.

CONCLUSION

This pilot study suggests the promise of stimulation by a specific serotonin reuptake inhibitor in regard to recovery and preservation of motor control after stroke.

Altered network hub connectivity after acute LSD administration

LSD is an ambiguous substance, said to mimic psychosis and to improve mental health in people suffering from anxiety and depression. Little is known about the neuronal correlates of altered states of consciousness induced by this substance. Limited previous studies indicated profound changes in functional connectivity of resting state networks after the administration of LSD. The current investigation attempts to replicate and extend those findings in an independent sample. In a double-blind, randomized, cross-over study, 100 μg LSD and placebo were orally administered to 20 healthy participants. Resting state brain activity was assessed by functional magnetic resonance imaging. Within-network and between-network connectivity measures of ten established resting state networks were compared between drug conditions. Complementary analysis were conducted using resting state networks as sources in seed-to-voxel analyses. Acute LSD administration significantly decreased functional connectivity within visual, sensorimotor and auditory networks and the default mode network. While between-network connectivity was widely increased and all investigated networks were affected to some extent, seed-to-voxel analyses consistently indicated increased connectivity between networks and subcortical (thalamus, striatum) and cortical (precuneus, anterior cingulate cortex) hub structures. These latter observations are consistent with findings on the importance of hubs in psychopathological states, especially in psychosis, and could underlay therapeutic effects of hallucinogens as proposed by a recent model.

Serotonergic and cholinergic modulation of functional brain connectivity: A comparison between young and older adults

Aging is accompanied by changes in neurotransmission. To advance our understanding of how aging modifies specific neural circuitries, we examined serotonergic and cholinergic stimulation with resting state functional magnetic resonance imaging (RS-fMRI) in young and older adults. The instant response to the selective serotonin reuptake inhibitor citalopram (30 mg) and the acetylcholinesterase inhibitor galantamine (8 mg) was measured in 12 young and 17 older volunteers during a randomized, double blind, placebo-controlled, crossover study. A powerful dataset consisting of 522 RS-fMRI scans was obtained by acquiring multiple scans per subject before and after drug administration. Group × treatment interaction effects on voxelwise connectivity with ten functional networks were investigated (p < .05, FWE-corrected) using a non-parametric multivariate analysis technique with cerebrospinal fluid, white matter, heart rate and baseline measurements as covariates. Both groups showed a decrease in sensorimotor network connectivity after citalopram administration. The comparable findings after citalopram intake are possibly due to relatively similar serotonergic systems in the young and older subjects. Galantamine altered connectivity between the occipital visual network and regions that are implicated in learning and memory in the young subjects. The lack of a cholinergic response in the elderly might relate to the well-known association between cognitive and cholinergic deterioration at older age.

Psychotropic medication use in autism spectrum disorders may affect functional brain connectivity

BACKGROUND

Prescription of psychotropic medications is common in autism spectrum disorders (ASDs), either off-label or to treat comorbid conditions such as ADHD or depression. Psychotropic medications are intended to alter brain function. Yet, studies investigating the functional brain organization in ASDs rarely take medication usage into account. This could explain some of the inconsistent findings of atypical brain network connectivity reported in the autism literature.

METHODS

The current study tested whether functional connectivity patterns, as assessed with functional magnetic resonance imaging (fMRI), differed in a cohort of 49 children and adolescents with ASDs based on psychotropic medication status, and in comparison with 50 matched typically developing (TD) participants. Twenty-five participants in the ASD group (51%) reported current psychotropic medication usage, including stimulants, antidepressants, antipsychotics, and anxiolytics. Age, IQ, head motion, and ASD symptom severity did not differ between groups. Whole-brain functional connectivity between 132 regions of interest was assessed.

RESULTS

Different functional connectivity patterns were identified in the ASD group taking psychotropic medications (ASD-on), as compared to the TD group and the ASD subgroup not using psychotropic medications (ASD-none). The ASD-on group showed distinct underconnectivity between the cerebellum and basal ganglia but cortico-cortical overconnectivity compared to the TD group. Cortical underconnectivity relative to the TD pattern, on the other hand, was pronounced in the ASD-none group.

CONCLUSIONS

These results suggest that psychotropic medications may affect functional connectivity, and that medication status should be taken into consideration when studying brain function in autism.

Bupropion Administration Increases Resting-State Functional Connectivity in Dorso-Medial Prefrontal Cortex

Background

Patients on the selective serotonergic reuptake inhibitors like citalopram report emotional blunting. We showed previously that citalopram reduces resting-state functional connectivity in healthy volunteers in a number of brain regions, including the dorso-medial prefrontal cortex, which may be related to its clinical effects. Bupropion is a dopaminergic and noradrenergic reuptake inhibitor and is not reported to cause emotional blunting. However, how bupropion affects resting-state functional connectivity in healthy controls remains unknown.

Methods

Using a within-subjects, repeated-measures, double-blind, crossover design, we examined 17 healthy volunteers (9 female, 8 male). Volunteers received 7 days of bupropion (150 mg/d) and 7 days of placebo treatment and underwent resting-state functional Magnetic Resonance Imaging. We selected seed regions in the salience network (amygdala and pregenual anterior cingulate cortex) and the central executive network (dorsal medial prefrontal cortex). Mood and anhedonia measures were also recorded and examined in relation to resting-state functional connectivity.

Results

Relative to placebo, bupropion increased resting-state functional connectivity in healthy volunteers between the dorsal medial prefrontal cortex seed region and the posterior cingulate cortex and the precuneus cortex, key parts of the default mode network.

Conclusions

These results are opposite to that which we found with 7 days treatment of citalopram in healthy volunteers. These results reflect a different mechanism of action of bupropion compared with selective serotonergic reuptake inhibitors. These results help explain the apparent lack of emotional blunting caused by bupropion in depressed patients.

Diminished Posterior Precuneus Connectivity with the Default Mode Network Differentiates Normal Aging from Alzheimer's Disease

Both normal aging and Alzheimer's disease (AD) have been associated with a reduction in functional brain connectivity. It is unknown how connectivity patterns due to aging and AD compare. Here, we investigate functional brain connectivity in 12 young adults (mean age 22.8 ± 2.8), 12 older adults (mean age 73.1 ± 5.2) and 12 AD patients (mean age 74.0 ± 5.2; mean MMSE 22.3 ± 2.5). Participants were scanned during 6 different sessions with resting state functional magnetic resonance imaging (RS-fMRI), resulting in 72 scans per group. Voxelwise connectivity with 10 functional networks was compared between groups (p < 0.05, corrected). Normal aging was characterized by widespread decreases in connectivity with multiple brain networks, whereas AD only affected connectivity between the default mode network (DMN) and precuneus. The preponderance of effects was associated with regional gray matter volume. Our findings indicate that aging has a major effect on functional brain interactions throughout the entire brain, whereas AD is distinguished by additional diminished posterior DMN-precuneus coherence.

Computational neuroscience approach to biomarkers and treatments for mental disorders

Psychiatry research has long experienced a stagnation stemming from a lack of understanding of the neurobiological underpinnings of phenomenologically defined mental disorders. Recently, the application of computational neuroscience to psychiatry research has shown great promise in establishing a link between phenomenological and pathophysiological aspects of mental disorders, thereby recasting current nosology in more biologically meaningful dimensions. In this review, we highlight recent investigations into computational neuroscience that have undertaken either theory- or data-driven approaches to quantitatively delineate the mechanisms of mental disorders. The theory-driven approach, including reinforcement learning models, plays an integrative role in this process by enabling correspondence between behavior and disorder-specific alterations at multiple levels of brain organization, ranging from molecules to cells to circuits. Previous studies have explicated a plethora of defining symptoms of mental disorders, including anhedonia, inattention, and poor executive function. The data-driven approach, on the other hand, is an emerging field in computational neuroscience seeking to identify disorder-specific features among high-dimensional big data. Remarkably, various machine-learning techniques have been applied to neuroimaging data, and the extracted disorder-specific features have been used for automatic case-control classification. For many disorders, the reported accuracies have reached 90% or more. However, we note that rigorous tests on independent cohorts are critically required to translate this research into clinical applications. Finally, we discuss the utility of the disorder-specific features found by the data-driven approach to psychiatric therapies, including neurofeedback. Such developments will allow simultaneous diagnosis and treatment of mental disorders using neuroimaging, thereby establishing 'theranostics' for the first time in clinical psychiatry.

Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry

A decade of research and development in resting-state functional MRI (RSfMRI) has opened new translational and clinical research frontiers. This review aims to bridge between technical and clinical researchers who seek reliable neuroimaging biomarkers for studying drug interactions with the brain. About 85 pharma-RSfMRI studies using BOLD signal (75% of all) or arterial spin labeling (ASL) were surveyed to investigate the acute effects of psychoactive drugs. Experimental designs and objectives include drug fingerprinting dose-response evaluation, biomarker validation and calibration, and translational studies. Common biomarkers in these studies include functional connectivity, graph metrics, cerebral blood flow and the amplitude and spectrum of BOLD fluctuations. Overall, RSfMRI-derived biomarkers seem to be sensitive to spatiotemporal dynamics of drug interactions with the brain. However, drugs cause both central and peripheral effects, thus exacerbate difficulties related to biological confounds, structured noise from motion and physiological confounds, as well as modeling and inference testing. Currently, these issues are not well explored, and heterogeneities in experimental design, data acquisition and preprocessing make comparative or meta-analysis of existing reports impossible. A unifying collaborative framework for data-sharing and data-mining is thus necessary for investigating the commonalities and differences in biomarker sensitivity and specificity, and establishing guidelines. Multimodal datasets including sham-placebo or active control sessions and repeated measurements of various psychometric, physiological, metabolic and neuroimaging phenotypes are essential for pharmacokinetic/pharmacodynamic modeling and interpretation of the findings. We provide a list of basic minimum and advanced options that can be considered in design and analyses of future pharma-RSfMRI studies. Hum Brain Mapp 38:2276-2325, 2017. © 2017 Wiley Periodicals, Inc.

Default mode network deactivation during emotion processing predicts early antidepressant response

Several previous functional magnetic resonance imaging (fMRI) studies have demonstrated the predictive value of brain activity during emotion processing for antidepressant response, with a focus on clinical outcome after 6-8 weeks. However, longitudinal studies emphasize the paramount importance of early symptom improvement for the course of disease in major depressive disorder (MDD). We therefore aimed to assess whether neural activity during the emotion discrimination task (EDT) predicts early antidepressant effects, and how these predictive measures relate to more sustained response. Twenty-three MDD patients were investigated once with ultrahigh-field 7T fMRI and the EDT. Following fMRI, patients received Escitalopram in a flexible dose schema and were assessed with the Hamilton Depression Rating Scale (HAMD) before, and after 2 and 4 weeks of treatment. Deactivation of the precuneus and posterior cingulate cortex (PCC) during the EDT predicted change in HAMD scores after 2 weeks of treatment. Baseline EDT activity was not predictive of HAMD change after 4 weeks of treatment. The precuneus and PCC are integral components of the default mode network (DMN). We show that patients who exhibit stronger DMN suppression during emotion processing are more likely to show antidepressant response after 2 weeks. This is, to our knowledge, the first study to show that DMN activity predicts early antidepressant effects. However, DMN deactivation did not predict response at 4 weeks, suggesting that our finding is representative of early, likely treatment-related, yet unspecific symptom improvement. Regardless, early effects may be harnessed for optimization of treatment regimens and patient care.

Effects of Anodal Transcranial Direct Current Stimulation and Serotonergic Enhancement on Memory Performance in Young and Older Adults

In the absence of effective therapies for dementia and its precursors, enhancing neuroplasticity by means of non-invasive brain stimulation such as anodal transcranial direct current stimulation (atDCS) might be a promising approach to counteract or delay the onset of cognitive decline, but effect sizes have been moderate so far. Previous reports indicate that increasing serotonin levels may enhance atDCS-induced neuroplasticity. However, evidence for serotonergic modulation of atDCS effects on memory is still lacking. Here, we conducted a double-blind, randomized, sham-/placebo-controlled trial to investigate the impact of a selective serotonin reuptake inhibitor (SSRI; single dose of 20 mg citalopram) and atDCS over the right temporoparietal cortex (1 mA, 20 min) on memory formation. Twenty young and 20 older subjects completed an object-location learning task in each of the four conditions: sham+placebo, sham+SSRI, atDCS+placebo, and atDCS+SSRI. Outcome measures were performance in immediate (primary outcome) and delayed cued recall. While we found an SSRI effect, but no statistically significant effect of atDCS on immediate recall scores, young and older adults benefited most from the combined application (comparisons: atDCS+SSRI>atDCS+placebo and atDCS+SSRI>sham+placebo). Thus, our data provide evidence that atDCS improves memory formation if serotonergic neurotransmission is enhanced simultaneously. Further studies are needed to assess whether these findings extend to clinical populations with memory impairment and translate into clinically relevant improvements after long-term serotonergic enhancement and repeated stimulation.

Serotonergic agents act on 5-HT3 receptors in the brain to block seizure-induced respiratory arrest in the DBA/1 mouse model of SUDEP

Drugs that enhance the action of serotonin (5-hydroxytrypamine, 5-HT), including several selective serotonin reuptake inhibitors (SSRIs), reduce susceptibility to seizure-induced respiratory arrest (S-IRA) that leads to death in the DBA/1 mouse model of sudden unexpected death in epilepsy (SUDEP). However, it is not clear if specific 5-HT receptors are important in the action of these drugs and whether the brain is the major site of action of these agents in this SUDEP model. The current study examined the actions of agents that affect the 5-HT3 receptor subtype on S-IRA and whether intracerebroventricular (ICV) microinjection of an SSRI would reduce S-IRA susceptibility in DBA/1 mice. The data indicate that systemic administration of SR 57227, a 5-HT3 agonist, was effective in blocking S-IRA in doses that did not block seizures, and the S-IRA blocking effect of the SSRI, fluoxetine, was abolished by coadministration of a 5-HT3 antagonist, ondansetron. Intracerebroventricular administration of fluoxetine in the present study was also able to block S-IRA without blocking seizures. These findings suggest that 5-HT3 receptors play an important role in the block of S-IRA by serotonergic agents, such as SSRIs, which is consistent with the abnormal expression of 5-HT3 receptors in the brainstem of DBA mice observed previously. Taken together, these data indicate that systemically administered serotonergic agents act, at least, in part, in the brain, to reduce S-IRA susceptibility in DBA/1 mice and that 5-HT3 receptors may be important to this effect.

Decreased functional connectivity to posterior cingulate cortex in major depressive disorder

The default mode network (DMN) and its interaction with other key networks such as the salience network and executive network are keys to understand psychiatric and neurological disorders including major depressive disorder (MDD). In this study, we combined independent component analysis and seed based connectivity analysis to study the posterior default mode network between 20 patients with MDD and 25 normal controls, as well as pre-treatment and post-treatment conditions of the patients. Both correlated and anti-correlated networks centered at the posterior cingulate cortex (PCC) were examined (PCC+ and PCC-). Our results showed aberrant functional connectivity of the PCC+ and PCC- networks between patients and normal controls. Specifically, normal controls exhibited significantly higher connectivity between the PCC and frontal/temporal regions for the PCC+ network and stronger connectivity strength between the PCC and the insula/middle frontal cortex for the PCC- network. The overall connectivity strength of the PCC+ and PCC- networks was also significantly lower in MDD. Because the PCC is a hub in the DMN that interacts with other networks, our result suggested a stronger interaction between the DMN and the salience network but a weak interaction between the DMN and the executive network in MDD. The treatment using sertraline did increase the functional connectivity strength, especially in the PCC+ network. Despite a large inter-subject variability in the overall connectivity strengths and change of the PCC network in response to the treatment, a high correlation between change of connectivity strength and the Hamilton depression score was observed for both the PCC+ and PCC- network.