Are Adolescents More Optimal Decision-Makers in Novel Environments? Examining the Benefits of Heightened Exploration in a Patch Foraging Paradigm

Adolescence is a period of heightened exploration relative to adulthood and childhood. This predisposition has been linked with negative behaviours related to risk-taking, including dangerous driving, substance misuse and risky sexual practices. However, recent models have argued that adolescents’ heightened exploration serves a functional purpose within the lifespan, allowing adolescents to develop experiential knowledge of their surroundings. Yet, there is limited evidence that heightened exploration in adolescence is associated with positive outcomes. To address this, the present pre-registered study utilised a foraging paradigm with a sample of adolescents aged 16–17 (N = 68) and of adults aged 21 and above (N = 69). Participants completed a patch foraging task, which required them to choose between exploiting a known resource which gradually yields fewer rewards, and exploring a novel, unknown resource with a fresh distribution of rewards. Findings demonstrated that adolescents explored more than adults, which – in the context of the current task—represented more optimal patch foraging behaviour. These findings indicate that adolescents’ heightened exploration can be beneficial, as they were able to effectively navigate unknown environments and accrue rewards more successfully than adults. This provides evidence that heightened exploration in adolescence, relative to adulthood, can lead to positive outcomes and contributes to our understanding of the role increased novelty-seeking plays at this point in the lifespan

Structural Basis of Large-Scale Functional Connectivity in the Mouse

Translational neuroimaging requires approaches and techniques that can bridge between multiple different species and disease states. One candidate method that offers insights into the brain's functional connectivity (FC) is resting-state fMRI (rs-fMRI). In both humans and nonhuman primates, patterns of FC (often referred to as the functional connectome) have been related to the underlying structural connectivity (SC; also called the structural connectome). Given the recent rise in preclinical neuroimaging of mouse models, it is an important question whether the mouse functional connectome conforms to the underlying SC. Here, we compared FC derived from rs-fMRI in female mice with the underlying monosynaptic structural connectome as provided by the Allen Brain Connectivity Atlas. We show that FC between interhemispheric homotopic cortical and hippocampal areas, as well as in cortico-striatal pathways, emerges primarily via monosynaptic structural connections. In particular, we demonstrate that the striatum (STR) can be segregated according to differential rs-fMRI connectivity patterns that mirror monosynaptic connectivity with isocortex. In contrast, for certain subcortical networks, FC emerges along polysynaptic pathways as shown for left and right STR, which do not share direct anatomical connections, but high FC is putatively driven by a top-down cortical control. Finally, we show that FC involving cortico-thalamic pathways is limited, possibly confounded by the effect of anesthesia, small regional size, and tracer injection volume. These findings provide a critical foundation for using rs-fMRI connectivity as a translational tool to study complex brain circuitry interactions and their pathology due to neurological or psychiatric diseases across species.A comprehensive understanding of how the anatomical architecture of the brain, often referred to as the "connectome," corresponds to its function is arguably one of the biggest challenges for understanding the brain and its pathologies. Here, we use the mouse as a model for comparing functional connectivity (FC) derived from resting-state fMRI with gold standard structural connectivity measures based on tracer injections. In particular, we demonstrate high correspondence between FC measurements of cortico-cortical and cortico-striatal regions and their anatomical underpinnings. This work provides a critical foundation for studying the pathology of these circuits across mouse models and human patients

Personality Modulates the Effects of Emotional Arousal and Valence on Brain Activation

The influence of personality on the neural correlates of emotional processing is still not well characterized. We investigated the relationship between extraversion and neuroticism and emotional perception using functional magnetic resonance imaging (fMRI) in a group of 23 young, healthy women. Using a parametric modulation approach, we examined how the blood oxygenation level dependent (BOLD) signal varied with the participants’ ratings of arousal and valence, and whether levels of extraversion and neuroticism were related to these modulations. In particular, we wished to test Eysenck\u27s biological theory of personality, which links high extraversion to lower levels of reticulothalamic–cortical arousal, and neuroticism to increased reactivity of the limbic system and stronger reactions to emotional arousal. Individuals high in neuroticism demonstrated reduced sustained activation in the orbitofrontal cortex (OFC) and attenuated valence processing in the right temporal lobe while viewing emotional images, but an increased BOLD response to emotional arousal in the right medial prefrontal cortex (mPFC). These results support Eysenck\u27s theory, as well as our hypothesis that high levels of neuroticism are associated with attenuated reward processing. Extraversion was inversely related to arousal processing in the right cerebellum, but positively associated with arousal processing in the right insula, indicating that the relationship between extraversion and arousal is not as simple as that proposed by Eysenck

Cerebellar atrophy in Parkinson's disease and its implication for network connectivity.

Pathophysiological and atrophic changes in the cerebellum are documented in Parkinson's disease. Without compensatory activity, such abnormalities could potentially have more widespread effects on both motor and non-motor symptoms. We examined how atrophic change in the cerebellum impacts functional connectivity patterns within the cerebellum and between cerebellar-cortical networks in 42 patients with Parkinson's disease and 29 control subjects. Voxel-based morphometry confirmed grey matter loss across the motor and cognitive cerebellar territories in the patient cohort. The extent of cerebellar atrophy correlated with decreased resting-state connectivity between the cerebellum and large-scale cortical networks, including the sensorimotor, dorsal attention and default networks, but with increased connectivity between the cerebellum and frontoparietal networks. The severity of patients' motor impairment was predicted by a combination of cerebellar atrophy and decreased cerebellar-sensorimotor connectivity. These findings demonstrate that cerebellar atrophy is related to both increases and decreases in cerebellar-cortical connectivity in Parkinson's disease, identifying potential cerebellar driven functional changes associated with sensorimotor deficits. A post hoc analysis exploring the effect of atrophy in the subthalamic nucleus, a cerebellar input source, confirmed that a significant negative relationship between grey matter volume and intrinsic cerebellar connectivity seen in controls was absent in the patients. This suggests that the modulatory relationship of the subthalamic nucleus on intracerebellar connectivity is lost in Parkinson's disease, which may contribute to pathological activation within the cerebellum. The results confirm significant changes in cerebellar network activity in Parkinson's disease and reveal that such changes occur in association with atrophy of the cerebellum

Older adults are relatively more susceptible to impulsive social influence than young adults

People differ in their levels of impulsivity and patience, and these preferences are heavily influenced by others. Previous research suggests that susceptibility to social influence may vary with age, but the mechanisms and whether people are more influenced by patience or impulsivity remain unknown. Here, using a delegated inter-temporal choice task and Bayesian computational models, we tested susceptibility to social influence in young (aged 18–36, N = 76) and older (aged 60–80, N = 78) adults. Participants completed a temporal discounting task and then learnt the preferences of two other people (one more impulsive and one more patient) before making their choices again. We used the signed Kullback-Leibler divergence to quantify the magnitude and direction of social influence. We found that, compared to young adults, older adults were relatively more susceptible to impulsive social influence. Factor analyses showed that older adults with higher self-reported levels of affective empathy and emotional motivation were particularly susceptible to impulsive influence. Importantly, older and young adults showed similar learning accuracy about others’ preferences, and their baseline impulsivity did not differ. Together, these findings suggest highly affectively empathetic and emotionally motivated older adults may be at higher risk for impulsive decisions, due to their susceptibility to social influence

The Dynamics of Functional Brain Networks:Integrated Network States during Cognitive Task Performance

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions, however it is unclear how this mechanism manifests over time. In this study, we use time-resolved network analysis of functional magnetic resonance imaging data to demonstrate that the human brain traverses between two functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. The integrated state enables faster and more accurate performance on a cognitive task, and is associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Our data confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.Comment: 38 pages, 4 figure

Enhancing studies of the connectome in autism using the autism brain imaging data exchange II

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity

Resisting Sleep Pressure:Impact on Resting State Functional Network Connectivity

In today's 24/7 society, sleep restriction is a common phenomenon which leads to increased levels of sleep pressure in daily life. However, the magnitude and extent of impairment of brain functioning due to increased sleep pressure is still not completely understood. Resting state network (RSN) analyses have become increasingly popular because they allow us to investigate brain activity patterns in the absence of a specific task and to identify changes under different levels of vigilance (e.g. due to increased sleep pressure). RSNs are commonly derived from BOLD fMRI signals but studies progressively also employ cerebral blood flow (CBF) signals. To investigate the impact of sleep pressure on RSNs, we examined RSNs of participants under high (19 h awake) and normal (10 h awake) sleep pressure with three imaging modalities (arterial spin labeling, BOLD, pseudo BOLD) while providing confirmation of vigilance states in most conditions. We demonstrated that CBF and pseudo BOLD signals (measured with arterial spin labeling) are suited to derive independent component analysis based RSNs. The spatial map differences of these RSNs were rather small, suggesting a strong biological substrate underlying these networks. Interestingly, increased sleep pressure, namely longer time awake, specifically changed the functional network connectivity (FNC) between RSNs. In summary, all FNCs of the default mode network with any other network or component showed increasing effects as a function of increased 'time awake'. All other FNCs became more anti-correlated with increased 'time awake'. The sensorimotor networks were the only ones who showed a within network change of FNC, namely decreased connectivity as function of 'time awake'. These specific changes of FNC could reflect both compensatory mechanisms aiming to fight sleep as well as a first reduction of consciousness while becoming drowsy. We think that the specific changes observed in functional network connectivity could imply an impairment of information transfer between the affected RSNs

Donepezil Impairs Memory in Healthy Older Subjects: Behavioural, EEG and Simultaneous EEG/fMRI Biomarkers

Rising life expectancies coupled with an increasing awareness of age-related cognitive decline have led to the unwarranted use of psychopharmaceuticals, including acetylcholinesterase inhibitors (AChEIs), by significant numbers of healthy older individuals. This trend has developed despite very limited data regarding the effectiveness of such drugs on non-clinical groups and recent work indicates that AChEIs can have negative cognitive effects in healthy populations. For the first time, we use a combination of EEG and simultaneous EEG/fMRI to examine the effects of a commonly prescribed AChEI (donepezil) on cognition in healthy older participants. The short- and long-term impact of donepezil was assessed using two double-blind, placebo-controlled trials. In both cases, we utilised cognitive (paired associates learning (CPAL)) and electrophysiological measures (resting EEG power) that have demonstrated high-sensitivity to age-related cognitive decline. Experiment 1 tested the effects of 5 mg/per day dosage on cognitive and EEG markers at 6-hour, 2-week and 4-week follow-ups. In experiment 2, the same markers were further scrutinised using simultaneous EEG/fMRI after a single 5 mg dose. Experiment 1 found significant negative effects of donepezil on CPAL and resting Alpha and Beta band power. Experiment 2 replicated these results and found additional drug-related increases in the Delta band. EEG/fMRI analyses revealed that these oscillatory differences were associated with activity differences in the left hippocampus (Delta), right frontal-parietal network (Alpha), and default-mode network (Beta). We demonstrate the utility of simple cognitive and EEG measures in evaluating drug responses after acute and chronic donepezil administration. The presentation of previously established markers of age-related cognitive decline indicates that AChEIs can impair cognitive function in healthy older individuals. To our knowledge this is the first study to identify the precise neuroanatomical origins of EEG drug markers using simultaneous EEG/fMRI. The results of this study may be useful for evaluating novel drugs for cognitive enhancement