To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Critically ill neonates are exposed to numerous painful procedures as part of lifesaving intensive care. These exposures occur during a period of brain maturation and growth. Pain pathways are still maturing and developing at the time of painful exposures. Repetitive early life exposure to painful procedures has been associated with alterations in brain maturation and growth and poorer neurodevelopmental outcomes; the impact of early life pain appears to persist until at least school age. However, commonly used analgesic medications to treat pain in neonates have also been associated with altered brain maturation and poorer neurodevelopmental outcomes. In this chapter, we review the neurobiology of pain in the developing brain, neonatal pain assessment methods, and associations of neonatal pain and analgesia exposure with brain maturation and neurodevelopmental outcomes.
Observational studies have suggested that brain imaging-derived phenotypes (IDPs) may serve as specific markers of pain-related phenotypes and severity. However, the shared genetic architecture between pain and brain IDPs and their potential causal relationships remains unclear.
Methods
We applied linkage disequilibrium score regression and Mendelian randomization (MR) analyses to uncover genetic correlations and potential causal links of brain structural (33,224 UK Biobank participants) and functional (47,276 UK Biobank participants) changes with site-specific pain phenotypes (approximately 500,000 Finngen participants). The scoping literature review was conducted to compare current findings with previous observational studies.
Results
In this study, we identified 559 significant genetic correlations between 587 structural IDPs and 13 pain-related phenotypes. Using MR analyses, we found that genetic liability to headache, migraine, joint pain, and sciatica was causally associated with alterations in 15 structural IDPs. Additionally, changes in the surface area of three brain regions were linked to a lower risk of sciatica, low back pain, and overall pain. Among the six pain-related phenotypes associated with structural IDPs, further analyses demonstrated putative causal relationships between functional IDPs and these conditions. Notably, headache exhibited both significant structural and functional changes across three key brain regions: the superior frontal gyrus, lingual gyrus, and paracentral lobule.
Conclusions
These findings provide novel insights into the genetic correlations and genetically inferred associations between pain and neurobiological abnormalities from neuroimaging perspectives, with structural alterations as the primary findings and functional changes as complementary exploratory evidence, advancing the understanding of pain-related mechanisms.
Neurological injury is common in neonates undergoing cardiac surgery with cardiopulmonary bypass, yet perioperative neuroimaging and neuromonitoring practices vary across centres. We aimed to characterise current practices and provider perceptions across Pediatric Cardiac Intensive Care Society-affiliated centres.
Methods:
We conducted an online, cross-sectional survey of Pediatric Cardiac Intensive Care Society members between August and October 2024. Part 1, completed by medical directors, assessed institutional characteristics and perioperative practices. Part 2, completed by multidisciplinary providers, evaluated perceptions of utility and sufficiency.
Results:
A total of 143 responses from 60 institutions were analysed, including 38 medical directors. Most centres had a dedicated cardiac ICU (87%) and were academically affiliated (76%). Routine neuroimaging was more common preoperatively than postoperatively (87% vs. 32%), with head ultrasound most frequently used. Near-infrared spectroscopy was the most common neuromonitoring modality, while routine electroencephalography was reported at 18% of centres preoperatively and 50% postoperatively. Physicians were more likely than advanced practice providers and nurses to report practices as sufficient. Neurocritical care teams were present at 42% of centres but were not associated with greater use of neuroimaging or monitoring.
Conclusions:
Significant variability exists in perioperative practices and provider perceptions, highlighting the need for multidisciplinary alignment and standardised guidelines.
Can we use neuroimaging to study the causes of psychiatric disorders? If so, how does neuroimaging compare to other methods in psychiatric research that allow for strong causal inferences? Neuroimaging study designs have evolved from cross-sectional, providing only correlational evidence, to longitudinal and interventional, which have strengthened the inferences we can draw from brain images. In this chapter, Heckers shows that researchers are using neuroimaging tools to pursue three very different goals. The techniques are similar, but they aim for different – at times conflicting – inferences. The three types of psychiatric neuroimaging studies pursue distinct aspects of causality, with different levels of explanation and applications for clinical practice. Much of current psychiatric neuroimaging does not study the causes of psychiatric disorders. However, the inclusion of neuroimaging methods in intervention trials has the promise to reveal causal relationships in psychiatric disorders.
Prior observational studies have reported conflicting results regarding whether antidepressant treatment reduces long-term dementia risk, likely due to confounding by indication and reverse causation. We aimed to investigate the association between baseline antidepressant use and incident dementia, incorporating cognitive and neuroimaging outcomes.
Methods
We conducted a prospective cohort study using UK Biobank participants free of dementia at baseline. Antidepressant use was self-reported at baseline (2006–2010). Incident dementia was identified through linked electronic health records until December 19, 2022. Cox proportional hazards models estimated hazard ratios (HRs) for all-cause dementia, Alzheimer’s disease (AD), and vascular dementia (VD), adjusting for sociodemographic, lifestyle, health-related, antidepressant indication factors, and co-medication of other anticholinergics. In subsamples, cognitive performance (n = 57,330) and structural brain imaging (n = 42,276) were examined as intermediate outcomes.
Results
Among 461,464 participants, 33,721 (7.3%) reported baseline antidepressant use. Over a mean follow-up of 13.4 years, 7,922 (1.7%) developed incident dementia. Baseline antidepressant use was associated with higher risks of all-cause dementia (adjusted HR: 1.47, 95% CI 1.36–1.60), AD (1.53, 1.36–1.73), and VD (1.44, 1.23–1.70). Users performed worse on fluid intelligence and prospective memory tasks and showed lower total and gray matter volume, regional reductions in the hippocampal gray matter and basal nucleus, and greater white matter hyperintensity volume.
Conclusions
Baseline antidepressant use was linked to a higher risk of dementia, poorer cognitive performance, and adverse brain structural changes. These findings underscore the importance of judicious prescribing, regular cognitive monitoring, and consideration of non-pharmacological approaches in clinical care.
The impact of depression on brain aging remains unclear, but both have been linked to stressful life events. Shared biological pathways may underlie structural brain changes. Clarifying these relationships could advance understanding of underlying mechanisms and inform treatment approaches.
Methods
Structural MRI scans of 190 participants (controls, n = 110, clinically diagnosed with major depressive disorder [MDD], n = 80), from the REDEEM dataset, were input into three pretrained brain age prediction models: brainageR, DeepBrainNet, and pyment. Prediction accuracy was compared in controls to identify the optimal model. DeepBrainNet demonstrated the highest accuracy and was selected for subsequent analysis. Brain-predicted age difference (brain-PAD) was calculated as predicted age minus chronological age. Linear regression examined the effects of MDD diagnosis, childhood maltreatment, and cortisol awakening response on brain-PAD.
Results
Depressed participants reported greater childhood maltreatment but a similar cortisol awakening response. An Age × Group interaction (β = 0.34, 95% CI: 0.15–0.53, p < 0.001) indicated older adults with MDD exhibited greater positive deviations from normative brain age predictions, suggesting nonuniform brain aging across the lifespan. Cortisol awakening response showed a negative association with brain-PAD (β = −0.01, 95% CI: −0.01 to −0.00, p = 0.041), indicating higher HPA-axis reactivity was linked to younger-appearing brains. Females showed lower brain-PAD than males, reflecting younger-appearing brains.
Conclusions
MDD was associated with age-dependent differences in brain-PAD. The protective association between cortisol awakening response and brain age highlights the importance of integrating stress biomarkers to better understand neural aging mechanisms in depression.
Few studies have examined how differing diagnostic criteria for mild cognitive impairment (MCI) relate to neuroimaging markers of cerebrovascular disease and neurodegeneration in Veterans. We compared three MCI diagnostic schemes on their associations with white matter hyperintensity (WMH) burden, hippocampal volume, and cortical thickness in nondemented Vietnam-era Veterans.
Methods:
228 Veterans (mean age = 69.65) were classified using: (1) Alzheimer’s Disease Neuroimaging Initiative (ADNI) criteria (subjective memory concerns, impaired Logical Memory, global Clinical Dementia Rating = 0.5); (2) neuropsychological criteria (>1 standard deviation [SD] below norms on two tests within a domain or one test across three domains); and (3) typical criteria (subjective memory concerns and >1.5 SD below norms on one test). Regression models predicting WMH burden adjusted for age and intracranial volume and included MCI status and hippocampal volume; ADNI-based models also included posttraumatic stress disorder symptom severity.
Results:
Neuropsychological criteria were associated with greater WMH burden (β = 0.45, p = .024), whereas typical and ADNI criteria were not. Sensitivity analyses found that meeting neuropsychological criteria for amnestic MCI interacted with lower hippocampal volume to predict greater WMH burden (β = −0.001, p = .028). No criteria were associated with cortical thickness.
Conclusions:
Neuropsychological criteria more sensitively identified Veterans with greater WMH burden and demonstrated a small, hippocampal volume-dependent effect in amnestic MCI. These findings support the clinical utility of multi-test neuropsychological approaches for detecting complex brain changes in high-comorbidity populations, with implications for risk stratification and targeted intervention in aging Veterans.
Anxiety disorders are distressing and impairing and may be becoming more prevalent. There remains much uncertainty about key factors in the development and maintenance of anxiety disorders, which may underpin some of the limitations of existing psychological, pharmacological and other treatments.
Selective serotonin reuptake inhibitors (SSRIs) are limited by inadequate response in a significant proportion of patients, slow onset, minimal cognitive benefit and side-effects. Preclinical studies suggest selective serotonin 4 receptor (5-HT4R) agonists may produce faster antidepressant effects via distinct mechanisms; however, there has been no experimental research in clinical populations to date.
Aims
To test whether the novel 5-HT4R partial agonist PF-04995274 produces early behavioural and neural changes in emotional cognition similar to SSRIs in patients with unmedicated major depressive disorder (MDD).
Method
In a double-blind, placebo-controlled trial, 90 participants with MDD were randomised to 7 days of PF-04995274 (15 mg), citalopram (20 mg) or placebo. Emotional processing was assessed using a behavioural facial expression recognition task and functional magnetic resonance imaging (fMRI) of implicit emotional face processing (days 6–9). Observer- and self-reported symptoms of depression were also measured at baseline and study end.
Results
As anticipated, citalopram reduced relative accuracy and increased relative reaction time to identify negative faces, with corresponding changes in neural activity (reduced left amygdala activation to emotional faces and valence-specific shifts in cortical regions). In contrast, PF-04995274 produced no change in behavioural negative bias or amygdala activity but increased medial-frontal cortex activation across valences. While this was not a clinical trial, both active treatments demonstrated an early treatment response with reduced observer-rated depression severity relative to placebo; PF-04995274 also reduced self-reported depression, state anxiety and negative affect.
Conclusions
PF-04995274 did not show the typical antidepressant profile of negative bias reductions observed with citalopram. Instead, it was associated with distinct increased medial-frontal activation during an emotional faces task, coupled with preliminary evidence of early clinical improvement, suggesting a potential alternative pathway for antidepressant effects. Findings support further clinical trials of 5-HT4R agonists and investigation of pro-cognitive and mood effects.
Individual responses to stress are highly heterogeneous, resulting in diverse psychopathological outcomes. This variability poses challenges for traditional diagnostic frameworks and underscores the need for a transdiagnostic approach to guide interventions. This study aimed to identify distinct phenotypes within a stress-exposed population and to characterize their biological profiles using a multimodal machine learning framework.
Methods
A total of 809 stress-exposed adults (mean age 40.5 ± 8.74 years; 53.7% female) underwent clinical, laboratory, and structural MRI assessments. Data-driven clustering of clinical variables identified phenotypes, followed by machine learning classifiers trained on neuroimaging and laboratory data to predict phenotype membership. SHapley Additive exPlanations (SHAP) analysis was used to identify key biological features distinguishing each phenotype.
Results
Three phenotypes were identified: a multi-risk group (n = 321) characterized by prominent depression, anxiety, and sleep disturbances; an alcohol-related risk group (n = 226) with high alcohol misuse and minimal comorbidity; and a resilient low-risk group (n = 262). Machine learning models accurately classified these phenotypes, indicating distinct biological profiles. SHAP analysis revealed phenotype-specific signatures: the multi-risk phenotype was associated with frontal-subcortical structural alterations and dysregulated cortisol, whereas the alcohol-related risk phenotype was characterized by frontal-insular structural alterations and metabolic abnormalities.
Conclusions
This study demonstrates the stratification of stress-exposed individuals into clinically and biologically distinct phenotypes. By integrating multimodal data with machine learning, we identified phenotype-specific neurobiological and metabolic profiles that extend beyond conventional diagnostic frameworks. These findings support a transdiagnostic, data-driven approach to improve risk stratification and inform personalized interventions in stress-exposed populations.
Prior neuroimaging studies and meta-analyses investigating brain correlates of placebo analgesia (PA) have yielded neuroanatomically heterogeneous findings, which may be reconciled from a connectomics perspective. The objective of this study was to examine network localization of brain functional alterations related to PA.
Methods
We initially identified PA-induced brain activation alterations (hyper-activation and hypo-activation separately) during experimental pain from 29 published studies with 674 individuals. By combining these implicated dysfunctional brain regions with large-scale discovery (N = 1113) and validation (N = 1093) resting-state functional magnetic resonance imaging datasets, we then employed a novel functional connectivity network mapping approach to construct PA hyper-activation and hypo-activation networks, respectively.
Results
The PA hyper-activation network manifested as a pattern of circumscribed brain regions mainly involving the limbic, default, and frontoparietal networks. By contrast, the PA hypo-activation network comprised a broadly distributed set of brain regions primarily implicating the ventral attention, somatomotor, and subcortical networks.
Conclusions
Our findings regarding the brain network representations of PA may contribute to a deeper understanding of its action mechanisms and provide a neural framework that may inform future clinical translation.
Emotion regulation relies on the interplay between prefrontal and limbic brain regions, with prefrontal regions implicated in the top-down modulation of the amygdala. In social anxiety disorder, disruptions in these networks have been reported, but most studies used undirected functional connectivity.
Aims
Dynamic causal modelling (DCM) was used to assess effective (i.e. directed) connectivity differences during emotion processing and regulation in individuals with social anxiety disorder compared with healthy controls.
Method
A total of 102 participants (61 with social anxiety disorder, 41 healthy controls) performed a functional magnetic resonance imaging emotion regulation task under two conditions: viewing neutral/negative faces, and downregulating emotions using a self-chosen strategy. DCM was applied to model effective connectivity among the amygdala and key prefrontal regions. Connectivity patterns were characterised in healthy controls, and group comparisons tested how social anxiety disorder differed from this baseline model using parametric empirical Bayes. Leave-one-out cross-validation (LOOCV) evaluated whether connectivity differences predicted diagnostic group, symptom severity and emotion regulation difficulties.
Results
In healthy controls, observation of negative faces was characterised by reciprocal influences between the amygdala and prefrontal cortex (PFC), including increased amygdala-to-ventromedial PFC (vmPFC) connectivity and inhibitory vmPFC-to-amygdala connectivity. During emotion regulation, healthy controls showed negative modulation from the amygdala to all prefrontal regions. Patients with social anxiety disorder did not differ from controls in amygdala–prefrontal connectivity; their alterations were confined to prefrontal circuits, with inhibitory connectivity from the pre-supplementary motor area (preSMA) to dorsolateral PFC during observation and bidirectional excitatory connectivity between the preSMA and vmPFC during regulation. LOOCV indicated that connectivity differences predicted diagnostic group.
Conclusions
The results support the idea that emotion processing and regulation influence connectivity between prefrontal areas and the amygdala in a complex, feedback-driven manner. Our findings suggest that aberrant emotion regulation in social anxiety disorder appears to be more closely linked to differences in intra-prefrontal circuits than deficits in amygdala–prefrontal connectivity.
We tested the hypothesis that resuming dietary control in early-treated phenylketonuria (PKU) is associated with improvements in white matter integrity, using data from the ReDAPT study, which previously demonstrated cognitive and psychiatric improvements with reduced phenylalanine (Phe) levels.
Methods:
We re-initiated dietary control for early-treated patients with PKU and assessed the T1w/T2w ratio from standard T1-and T2-weighted magnetic resonance images, a marker of myelination and microstructural integrity. General linear mixed-effects model (GLMM) analyses were performed to assess change in the T1w/T2w ratio from baseline over twelve months after resumption of dietary control.
Results:
Seven participants (mean age 31 years; five female) with neuroimaging were included, with a mean of 16 years off diet and baseline Phe levels of 1157 µmol/L. GLMM analyses showed significant increases in T1w/T2w ratio over time for the whole brain (β = 0.47 [95%CI = 0.28, 0.66]), left hemisphere (β = 0.36 [95%CI = 0.19, 0.54]) and right hemisphere regions of interest (β = 0.52 [95%CI = 0.30, 0.72]). Longer time off diet was also positively associated with greater T1w/T2w changes. There was no evidence for the effects of gender or age at baseline.
Conclusions:
This study demonstrated significant increases in the T1w/T2w ratio in PKU patients as they resumed dietary control over a 12-month period. Raw Phe levels were not strongly associated with neuroimaging measures. These findings support the importance of lifelong treatment for PKU and also demonstrate the potential reversibility of white matter changes in the disease.
We need to identify novel, tractable therapeutic targets for anxiety disorders. Converging evidence suggests the endogenous opioid system plays a role in modulating affective processing, but its contribution to regulation of threat processing in humans remains unclear.
Aims
We investigated the neural correlates of non-specific opioid antagonism on explicit and implicit regulation of threatening stimuli in healthy volunteers, using functional magnetic resonance imaging (fMRI).
Method
In a randomised, double-blind, placebo-controlled, crossover design, 38 healthy participants received the opioid antagonist naltrexone (50 mg) or placebo before completing two tasks during fMRI: (a) a cognitive emotional reappraisal task probing explicit regulation and (b) a face-viewing task probing implicit processing.
Results
Contrary to our hypothesis, we found naltrexone reduced distress ratings during the reappraisal task (p = 0.044) without impairing regulation success. Explicit regulation in the reappraisal task engaged lateral prefrontal regions similarly across drug conditions. However, naltrexone attenuated ventromedial prefrontal cortex, thalamus and caudate activation when viewing negative images. Naltrexone additionally altered ventromedial prefrontal cortex activity and in task-positive regions including right premotor area and frontal pole compared with placebo when viewing emotional faces. In particular, naltrexone increased left middle frontal gyrus activity when viewing fearful faces.
Conclusions
Our results support a role for opioid signalling in automatic emotional regulation, but not in explicit regulation. Furthermore, naltrexone appeared to diminish activity in task-positive regions in response to emotional faces. These findings are consistent with a model where endogenous opioids ‘fine-tune’ affective responses to both negative and positive stimuli. Future research should explore dose–response effects, kappa-opioid contributions and whether similar results are seen in clinical populations.
This clinical reflection explores the evolving landscape of teaching and training in old age psychiatry, highlighting recent reforms such as the 2022 UK curriculum revision, which emphasises person-centred, interdisciplinary and digitally enhanced care. It examines national and international initiatives addressing health inequalities, integration of artificial intelligence, and co-produced education. The article underscores the need for adaptable, inclusive and forward-thinking training to meet the complex mental health needs of an ageing global population.
Tort law has traditionally prioritized physical over emotional injury claims, due in part to insufficient methods of quantifying the latter. But advances in neuroimaging now make it possible to measure the distinct (and often chronic) neurological damage caused by PTSD, suggesting that it should be treated as both a physical and emotional harm. I argue that this recategorization may help PTSD victims win just restitution, especially for those from marginalized groups whose suffering has traditionally been overlooked and underappreciated by the legal system. Lingering probative and prejudicial flaws will likely limit current judicial applications of PTSD neuroimaging to citations of aggregate research. Until the technology improves in accuracy and sensitivity, individual PTSD neuroimaging on tort plaintiffs will fail to meet most state and federal evidentiary standards. When it does achieve sufficient reliability, neuroimaging precedent for traumatic brain injury may offer guidance on how to incorporate the technology without creating a “CSI effect” that harms plaintiffs unable to access or afford brain scans. PTSD neuroimaging may ultimately foster a greater appreciation for the physical toll of psychological illnesses, catalyzing the movement to dismantle the mind-body divide in tort jurisprudence.
In the current chapter, we review the research on close relationships done via the methodologies of neuroscience – in short relationship neuroscience (RN). Much of the research we review focuses on attachment (child–parent or romantic) and sexuality. Nevertheless, we aim to cover RN broadly defined. We start by framing our topic and providing a few working definitions. We then cover the various relational (attachment, interdependence) and neuroscience (social baseline theory, and the Functional Neuroanatomical Model of Human Attachment) theories, methodologies (MRI, ERPs, and genetics), and types of relationships (familial relations, romantic, friendships, sexual relations, etc.) used or covered in this subfield. We explore both positive and negative aspects of close relationships. Finally, we reflect on the bidirectional link and contributions between relationship science and neuroscience and suggest potential implications for mental and physical health and policymaking. We also outline some remaining issues and future directions for RN.
Obsessive-compulsive disorder (OCD) is a complex psychiatric disorder. While existing studies have revealed abnormalities in brain structure and function associated with OCD, there is a paucity of research integrating these two aspects, and the transcriptional patterns underlying these abnormalities remain unclear. This study is a multiscale, exploratory investigation designed to generate hypotheses rather than to test causal mechanisms. We aimed to investigate aberrations in brain structure–function coupling (SFC) in OCD patients and, by integrating gene expression profiles and neurotransmitter maps, to explore the potential molecular and genetic bases of these changes. We recruited 100 medication-free OCD patients and 90 healthy controls, and employed multimodal imaging techniques to systematically analyze abnormalities in static SFC in OCD patients. Subsequently, we conducted transcriptomic analysis to identify genes associated with SFC abnormalities and performed spatial correlation analysis with neurotransmitter atlases to investigate potential links between SFC dysregulation and transcriptional patterns. Our findings demonstrated that OCD patients exhibit significant SFC abnormalities in the right temporoparietal junction (rTPJ). These SFC abnormalities are significantly associated with 2,421 gene expression profiles and the serotonin neurotransmitter system. Gene enrichment analysis revealed that these aberrant genes are primarily involved in key biological processes, such as brain development, synaptic signaling, cell projection development, and regulation of neuronal processes. By integrating multimodal imaging, transcriptomic, and neurotransmitter data, this study provides multiscale evidence for the potential molecular basis of SFC abnormalities in the rTPJ of OCD patients, offering preliminary insights into a possible pathological pathway of OCD.
This chapter provides a comprehensive overview of the neurotechnologies used to record and stimulate brain activity, from invasive techniques like optogenetics and intracranial electrodes to noninvasive methods such as electroencephalography and functional magnetic resonance imaging. It explains how these technologies are evaluated based on criteria like spatial resolution, temporal resolution, safety, and portability. With this framework, each technology is evaluated in terms of its power and constraints. This chapter highlights the trade-off between technological power and practical constraints, emphasizing the need for safer, more adaptable devices for both clinical and research purposes.