Attention Shifts Recruit the Monkey Default Mode Network

Mapping causal links between prefrontal cortical regions and intra-individual behavioral variability

Intra-individual behavioral variability is significantly heightened by aging or neuropsychological disorders, however it is unknown which brain regions are causally linked to such variabilities. We examine response time (RT) variability in 21 macaque monkeys performing a rule-guided decision-making task. In monkeys with selective-bilateral lesions in the anterior cingulate cortex (ACC) or in the dorsolateral prefrontal cortex, cognitive flexibility is impaired, but the RT variability is significantly diminished. Bilateral lesions within the frontopolar cortex or within the mid-dorsolateral prefrontal cortex, has no significant effect on cognitive flexibility or RT variability. In monkeys with lesions in the posterior cingulate cortex, the RT variability significantly increases without any deficit in cognitive flexibility. The effect of lesions in the orbitofrontal cortex (OFC) is unique in that it leads to deficits in cognitive flexibility and a significant increase in RT variability. Our findings indicate remarkable dissociations in contribution of frontal cortical regions to behavioral variability. They suggest that the altered variability in OFC-lesioned monkeys is related to deficits in assessing and accumulating evidence to inform a rule-guided decision, whereas in ACC-lesioned monkeys it results from a non-adaptive decrease in decision threshold and consequently immature impulsive responses.

Bayesian dynamical system analysis of the effects of methylphenidate in children with attention-deficit/hyperactivity disorder: a randomized trial

Methylphenidate is a widely used and effective treatment for attention-deficit/hyperactivity disorder (ADHD), yet the underlying neural mechanisms and their relationship to changes in behavior are not fully understood. Specifically, it remains unclear how methylphenidate affects brain and behavioral dynamics, and the interplay between these dynamics, in individuals with ADHD. To address this gap, we used a novel Bayesian dynamical system model to investigate the effects of methylphenidate on latent brain states in 27 children with ADHD and 49 typically developing children using a double-blind, placebo-controlled crossover design. Methylphenidate remediated greater behavioral variability on a continuous performance task in children with ADHD. Children with ADHD exhibited aberrant latent brain state dynamics compared to typically developing children, with a single latent state showing particularly abnormal dynamics, which was remediated by methylphenidate. Additionally, children with ADHD showed brain state-dependent hyper-connectivity in the default mode network, which was also remediated by methylphenidate. Finally, we found that methylphenidate-induced changes in latent brain state dynamics, as well as brain state-related functional connectivity between salience and default mode networks, were correlated with improvements in behavioral variability. Taken together, our findings reveal a novel latent brain state dynamical process and circuit mechanism underlying the therapeutic effects of methylphenidate in childhood ADHD. We suggest that Bayesian dynamical system models may be particularly useful for capturing complex nonlinear changes in neural activity and behavioral variability associated with ADHD. Our approach may be of value to clinicians and researchers investigating the neural mechanisms underlying pharmacological treatment of psychiatric disorders.

Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography

Cognitive flexibility encompasses the ability to efficiently shift focus and forms a critical component of goal-directed attention. The neural substrates of this process are incompletely understood in part due to difficulties in sampling the involved circuitry. We leverage stereotactic intracranial recordings to directly resolve local-field potentials from otherwise inaccessible structures to study moment-to-moment attentional activity in children with epilepsy performing a flexible attentional task. On an individual subject level, we employed deep learning to decode neural features predictive of task performance indexed by single-trial reaction time. These models were subsequently aggregated across participants to identify predictive brain regions based on AAL atlas and FIND functional network parcellations. Through this approach, we show that fluctuations in beta (12-30 Hz) and gamma (30-80 Hz) power reflective of increased top-down attentional control and local neuronal processing within relevant large-scale networks can accurately predict single-trial task performance. We next performed connectomic profiling of these highly predictive nodes to examine task-related engagement of distributed functional networks, revealing exclusive recruitment of the dorsal default mode network during shifts in attention. The identification of distinct substreams within the default mode system supports a key role for this network in cognitive flexibility and attention in children. Furthermore, convergence of our results onto consistent functional networks despite significant inter-subject variability in electrode implantations supports a broader role for deep learning applied to intracranial electrodes in the study of human attention.

The default mode network is affected in the early stage of simian immunodeficiency virus infection: a longitudinal study

Acquired immune deficiency syndrome infection can lead to cognitive dysfunction represented by changes in the default mode network. Most recent studies have been cross-sectional and thus have not revealed dynamic changes in the default mode network following acquired immune deficiency syndrome infection and antiretroviral therapy. Specifically, when brain imaging data at only one time point are analyzed, determining the duration at which the default mode network is the most effective following antiretroviral therapy after the occurrence of acquired immune deficiency syndrome. However, because infection times and other factors are often uncertain, longitudinal studies cannot be conducted directly in the clinic. Therefore, in this study, we performed a longitudinal study on the dynamic changes in the default mode network over time in a rhesus monkey model of simian immunodeficiency virus infection. We found marked changes in default mode network connectivity in 11 pairs of regions of interest at baseline and 10 days and 4 weeks after virus inoculation. Significant interactions between treatment and time were observed in the default mode network connectivity of regions of interest pairs area 31/V6.R and area 8/frontal eye field (FEF). L, area 8/FEF.L and caudal temporal parietal occipital area (TPOC).R, and area 31/V6.R and TPOC.L. ART administered 4 weeks after infection not only interrupted the progress of simian immunodeficiency virus infection but also preserved brain function to a large extent. These findings suggest that the default mode network is affected in the early stage of simian immunodeficiency virus infection and that it may serve as a potential biomarker for early changes in brain function and an objective indicator for making early clinical intervention decisions.

Noncoding transcripts are linked to brain resting-state activity in non-human primates

Brain-derived transcriptomes are known to correlate with resting-state brain activity in humans. Whether this association holds in nonhuman primates remains uncertain. Here, we search for such molecular correlates by integrating 757 transcriptomes derived from 100 macaque cortical regions with resting-state activity in separate conspecifics. We observe that 150 noncoding genes explain variations in resting-state activity at a comparable level with protein-coding genes. In-depth analysis of these noncoding genes reveals that they are connected to the function of nonneuronal cells such as oligodendrocytes. Co-expression network analysis finds that the modules of noncoding genes are linked to both autism and schizophrenia risk genes. Moreover, genes associated with resting-state noncoding genes are highly enriched in human resting-state functional genes and memory-effect genes, and their links with resting-state functional magnetic resonance imaging (fMRI) signals are altered in the brains of patients with autism. Our results highlight the potential for noncoding RNAs to explain resting-state activity in the nonhuman primate brain.

Unbalanced amygdala communication in major depressive disorder

BACKGROUND

Previous studies suggested an association between functional alteration of the amygdala and typical major depressive disorder (MDD) symptoms. Examining whether and how the interaction between the amygdala and regions/functional networks is altered in patients with MDD is important for understanding its neural basis.

METHODS

Resting-state functional magnetic resonance imaging data were recorded from 67 patients with MDD and 74 age- and sex-matched healthy controls (HCs). A framework for large-scale network analysis based on seed mappings of amygdala sub-regions, using a multi-connectivity-indicator strategy (cross-correlation, total interdependencies (TI), Granger causality (GC), and machine learning), was employed. Multiple indicators were compared between the two groups. The altered indicators were ranked in a supporting-vector machine-based procedure and associated with the Hamilton Rating Scale for Depression scores.

RESULTS

The amygdala connectivity with the default mode network and ventral attention network regions was enhanced and that with the somatomotor network, dorsal frontoparietal network, and putamen regions in patients with MDD was reduced. The machine learning analysis highlighted altered indicators that were most conducive to the classification between the two groups.

LIMITATIONS

Most patients with MDD received different pharmacological treatments. It is difficult to illustrate the medication state's effect on the alteration model because of its complex situation.

CONCLUSION

The results indicate an unbalanced interaction model between the amygdala and functional networks and regions essential for various emotional and cognitive functions. The model can help explain potential aberrancy in the neural mechanisms that underlie the functional impairments observed across various domains in patients with MDD.

Pupillary response is associated with the reset and switching of functional brain networks during salience processing

The interface between processing internal goals and salient events in the environment involves various top-down processes. Previous studies have identified multiple brain areas for salience processing, including the salience network (SN), dorsal attention network, and the locus coeruleus-norepinephrine (LC-NE) system. However, interactions among these systems in salience processing remain unclear. Here, we simultaneously recorded pupillometry, EEG, and fMRI during an auditory oddball paradigm. The analyses of EEG and fMRI data uncovered spatiotemporally organized target-associated neural correlates. By modeling the target-modulated effective connectivity, we found that the target-evoked pupillary response is associated with the network directional couplings from late to early subsystems in the trial, as well as the network switching initiated by the SN. These findings indicate that the SN might cooperate with the pupil-indexed LC-NE system in the reset and switching of cortical networks, and shed light on their implications in various cognitive processes and neurological diseases.

Optogenetic stimulation of anterior insular cortex neurons in male rats reveals causal mechanisms underlying suppression of the default mode network by the salience network

The salience network (SN) and default mode network (DMN) play a crucial role in cognitive function. The SN, anchored in the anterior insular cortex (AI), has been hypothesized to modulate DMN activity during stimulus-driven cognition. However, the causal neural mechanisms underlying changes in DMN activity and its functional connectivity with the SN are poorly understood. Here we combine feedforward optogenetic stimulation with fMRI and computational modeling to dissect the causal role of AI neurons in dynamic functional interactions between SN and DMN nodes in the male rat brain. Optogenetic stimulation of Chronos-expressing AI neurons suppressed DMN activity, and decreased AI-DMN and intra-DMN functional connectivity. Our findings demonstrate that feedforward optogenetic stimulation of AI neurons induces dynamic suppression and decoupling of the DMN and elucidates previously unknown features of rodent brain network organization. Our study advances foundational knowledge of causal mechanisms underlying dynamic cross-network interactions and brain network switching.

A role for the claustrum in cognitive control

Early hypotheses of claustrum function were fueled by neuroanatomical data and yielded suggestions that the claustrum is involved in processes ranging from salience detection to multisensory integration for perceptual binding. While these hypotheses spurred useful investigations, incompatibilities inherent in these views must be reconciled to further conceptualize claustrum function amid a wealth of new data. Here, we review the varied models of claustrum function and synthesize them with developments in the field to produce a novel functional model: network instantiation in cognitive control (NICC). This model proposes that frontal cortices direct the claustrum to flexibly instantiate cortical networks to subserve cognitive control. We present literature support for this model and provide testable predictions arising from this conceptual framework.

Moxibustion for primary dysmenorrhea: A resting-state functional magnetic resonance imaging study exploring the alteration of functional connectivity strength and functional connectivity

Introduction

Primary dysmenorrhea (PDM) is a common gynecological disease and chronic pain disorder. Moxibustion, a form of traditional Chinese medicine therapy, has proven to be effective for PDM. However, the central mechanisms of PDM and moxibustion for PDM are still unclear. This study aims to explore the potential central mechanism of PDM and clarify the possible mechanism of moxibustion for relieving pain.

Materials and methods

A total of 23 PDM patients and 23 matched healthy controls (HCs) were enrolled. For PDM patients, resting-state functional magnetic resonance imaging (rs-fMRI) data were collected pre- and post-moxibustion treatment of 3 consecutive menstrual cycles, respectively. For HCs, rs-fMRI data were collected in the baseline. The resting-state functional connectivity strength (rs-FCS) analysis and the resting-state functional connectivity (rs-FC) analysis based on the region of interest (ROI) were combined to be conducted.

Results

Compared to HCs, PDM patients showed weaker rs-FCS in the left inferior frontal gyrus (IFG). After the moxibustion treatment, rs-FCS in the left IFG was increased with clinical improvement. Then, the left IFG was chosen as ROI, and the rs-FC analysis was conducted. It showed that the left IFG rs-FC in the bilateral anterior cingulate cortex (ACC)/middle cingulate cortex (MCC), the left posterior cingulate cortex (PCC)/precuneus (PCU), and the left parahippocampal gyrus (PHG) decreased after moxibustion treatment, most of which belong to the default mode network (DMN).

Conclusion

Our results highlight the role of the left IFG and the DMN in PDM. Specifically, the central mechanism of moxibustion for analgesia may be related to modulating the disorders of the reappraisal and processing of pain stimuli through influencing the cognition of pain.

An evolutionary gap in primate default mode network organization

The human default mode network (DMN) is engaged at rest and in cognitive states such as self-directed thoughts. Interconnected homologous cortical areas in primates constitute a network considered as the equivalent. Here, based on a cross-species comparison of the DMN between humans and non-hominoid primates (macaques, marmosets, and mouse lemurs), we report major dissimilarities in connectivity profiles. Most importantly, the medial prefrontal cortex (mPFC) of non-hominoid primates is poorly engaged with the posterior cingulate cortex (PCC), though strong correlated activity between the human PCC and the mPFC is a key feature of the human DMN. Instead, a fronto-temporal resting-state network involving the mPFC was detected consistently across non-hominoid primate species. These common functional features shared between non-hominoid primates but not with humans suggest a substantial gap in the organization of the primate’s DMN and its associated cognitive functions.

By comparing resting-state networks in humans, macaques, marmosets, and mouse lemurs, Garin et al. identify two networks in non-hominoid primates that include homolog areas of the human default mode network. The mPFC and PCC are tightly connected in the human DMN but poorly connected to each other across non-hominoid primates.

Population receptive fields in non-human primates from whole-brain fMRI and large-scale neurophysiology in visual cortex

Population receptive field (pRF) modeling is a popular fMRI method to map the retinotopic organization of the human brain. While fMRI-based pRF maps are qualitatively similar to invasively recorded single-cell receptive fields in animals, it remains unclear what neuronal signal they represent. We addressed this question in awake nonhuman primates comparing whole-brain fMRI and large-scale neurophysiological recordings in areas V1 and V4 of the visual cortex. We examined the fits of several pRF models based on the fMRI blood-oxygen-level-dependent (BOLD) signal, multi-unit spiking activity (MUA), and local field potential (LFP) power in different frequency bands. We found that pRFs derived from BOLD-fMRI were most similar to MUA-pRFs in V1 and V4, while pRFs based on LFP gamma power also gave a good approximation. fMRI-based pRFs thus reliably reflect neuronal receptive field properties in the primate brain. In addition to our results in V1 and V4, the whole-brain fMRI measurements revealed retinotopic tuning in many other cortical and subcortical areas with a consistent increase in pRF size with increasing eccentricity, as well as a retinotopically specific deactivation of default mode network nodes similar to previous observations in humans.

Modelling behaviors relevant to brain disorders in the nonhuman primate: Are we there yet?

Recent years have seen a profound resurgence of activity with nonhuman primates (NHPs) to model human brain disorders. From marmosets to macaques, the study of NHP species offers a unique window into the function of primate-specific neural circuits that are impossible to examine in other models. Examining how these circuits manifest into the complex behaviors of primates, such as advanced cognitive and social functions, has provided enormous insights to date into the mechanisms underlying symptoms of numerous neurological and neuropsychiatric illnesses. With the recent optimization of modern techniques to manipulate and measure neural activity in vivo, such as optogenetics and calcium imaging, NHP research is more well-equipped than ever to probe the neural mechanisms underlying pathological behavior. However, methods for behavioral experimentation and analysis in NHPs have noticeably failed to keep pace with these advances. As behavior ultimately lies at the junction between preclinical findings and its translation to clinical outcomes for brain disorders, approaches to improve the integrity, reproducibility, and translatability of behavioral experiments in NHPs requires critical evaluation. In this review, we provide a unifying account of existing brain disorder models using NHPs, and provide insights into the present and emerging contributions of behavioral studies to the field.

Latent brain state dynamics distinguish behavioral variability, impaired decision-making, and inattention

Children with Attention Deficit Hyperactivity Disorder (ADHD) have prominent deficits in sustained attention that manifest as elevated intra-individual response variability and poor decision-making. Influential neurocognitive models have linked attentional fluctuations to aberrant brain dynamics, but these models have not been tested with computationally rigorous procedures. Here we use a Research Domain Criteria approach, drift-diffusion modeling of behavior, and a novel Bayesian Switching Dynamic System unsupervised learning algorithm, with ultrafast temporal resolution (490 ms) whole-brain task-fMRI data, to investigate latent brain state dynamics of salience, frontoparietal, and default mode networks and their relation to response variability, latent decision-making processes, and inattention. Our analyses revealed that occurrence of a task-optimal latent brain state predicted decreased intra-individual response variability and increased evidence accumulation related to decision-making. In contrast, occurrence and dwell time of a non-optimal latent brain state predicted inattention symptoms and furthermore, in a categorical analysis, distinguished children with ADHD from controls. Importantly, functional connectivity between salience and frontoparietal networks predicted rate of evidence accumulation to a decision threshold, whereas functional connectivity between salience and default mode networks predicted inattention. Taken together, our computational modeling reveals dissociable latent brain state features underlying response variability, impaired decision-making, and inattentional symptoms common to ADHD. Our findings provide novel insights into the neurobiology of attention deficits in children.

Posterior Intraparietal Sulcus Mediates Detection of Salient Stimuli Outside the Endogenous Focus of Attention

Visual consciousness is shaped by the interplay between endogenous selection and exogenous capture. If stimulus saliency is aligned with a subject’s attentional priorities, endogenous selection will be facilitated. In case of a misalignment, endogenous selection may be compromised as attentional capture is a strong and automatic process. We manipulated task-congruent versus -incongruent saliency in a functional magnetic resonance imaging change-detection task and analyzed brain activity patterns in the cortex surrounding the intraparietal sulcus (IPS) within the Julich-Brain probabilistic cytoarchitectonic mapping reference frame. We predicted that exogenous effects would be seen mainly in the posterior regions of the IPS (hIP4–hIP7–hIP8), whereas a conflict between endogenous and exogenous orienting would elicit activity from more anterior cytoarchitectonic areas (hIP1–hIP2–hIP3). Contrary to our hypothesis, a conflict between endogenous and exogenous orienting had an effect early in the IPS (mainly in hIP7 and hIP8). This is strong evidence for an endogenous component in hIP7/8 responses to salient stimuli beyond effects of attentional bottom-up sweep. Our results suggest that hIP7 and hIP8 are implicated in the individuation of attended locations based on saliency as well as endogenous instructions.

Common functional localizers to enhance NHP & cross-species neuroscience imaging research

Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform.

The modulation of brain network integration and arousal during exploration

There is growing interest in how neuromodulators shape brain networks. Recent neuroimaging studies provide evidence that brainstem arousal systems, such as the locus coeruleus-norepinephrine system (LC-NE), influence functional connectivity and brain network topology, suggesting they have a role in flexibly reconfiguring brain networks in order to adapt behavior and cognition to environmental demands. To date, however, the relationship between brainstem arousal systems and functional connectivity has not been assessed within the context of a task with an established relationship between arousal and behavior, with most prior studies relying on incidental variations in arousal or pharmacological manipulation and static brain networks constructed over long periods of time. These factors have likely contributed to a heterogeneity of effects across studies. To address these issues, we took advantage of the association between LC-NE-linked arousal and exploration to probe the relationships between exploratory choice, arousal—as measured indirectly via pupil diameter—and brain network dynamics. Exploration in a bandit task was associated with a shift toward fewer, more weakly connected modules that were more segregated in terms of connectivity and topology but more integrated with respect to the diversity of cognitive systems represented in each module. Functional connectivity strength decreased, and changes in connectivity were correlated with changes in pupil diameter, in line with the hypothesis that brainstem arousal systems influence the dynamic reorganization of brain networks. More broadly, we argue that carefully aligning dynamic network analyses with task designs can increase the temporal resolution at which behaviorally- and cognitively-relevant modulations can be identified, and offer these results as a proof of concept of this approach.

Dissociations between glucose metabolism and blood oxygenation in the human default mode network revealed by simultaneous PET-fMRI

A consistent finding from functional MRI (fMRI) of externally focused cognitive control is negative signal change in the brain’s default mode network (DMN), but it is unknown whether this reflects an increase of synaptic activity during rest periods or active suppression during task. Using hybrid PET-MRI, we show that task-positive fMRI responses align with increasing glucose metabolism during cognitive control, but task-negative fMRI responses in DMN are not accompanied by corresponding decreases in metabolism. The results are incompatible with an interpretation of task-negative fMRI signal in DMN as a relative metabolic increase during a resting baseline condition. The present results open up avenues for understanding abnormal fMRI activity patterns in DMN in aging and psychiatric disease.

The finding of reduced functional MRI (fMRI) activity in the default mode network (DMN) during externally focused cognitive control has been highly influential to our understanding of human brain function. However, these negative fMRI responses, measured as relative decreases in the blood-oxygenation-level–dependent (BOLD) response between rest and task, have also prompted major questions of interpretation. Using hybrid functional positron emission tomography (PET)-MRI, this study shows that task-positive and -negative BOLD responses do not reflect antagonistic patterns of synaptic metabolism. Task-positive BOLD responses in attention and control networks were accompanied by concomitant increases in glucose metabolism during cognitive control, but metabolism in widespread DMN remained high during rest and task despite negative BOLD responses. Dissociations between glucose metabolism and the BOLD response specific to the DMN reveal functional heterogeneity in this network and demonstrate that negative BOLD responses during cognitive control should not be interpreted to reflect relative increases in metabolic activity during rest. Rather, neurovascular coupling underlying BOLD response patterns during rest and task in DMN appears fundamentally different from BOLD responses in other association networks during cognitive control.

Dynamic causal brain circuits during working memory and their functional controllability

Control processes associated with working memory play a central role in human cognition, but their underlying dynamic brain circuit mechanisms are poorly understood. Here we use system identification, network science, stability analysis, and control theory to probe functional circuit dynamics during working memory task performance. Our results show that dynamic signaling between distributed brain areas encompassing the salience (SN), fronto-parietal (FPN), and default mode networks can distinguish between working memory load and predict performance. Network analysis of directed causal influences suggests the anterior insula node of the SN and dorsolateral prefrontal cortex node of the FPN are causal outflow and inflow hubs, respectively. Network controllability decreases with working memory load and SN nodes show the highest functional controllability. Our findings reveal dissociable roles of the SN and FPN in systems control and provide novel insights into dynamic circuit mechanisms by which cognitive control circuits operate asymmetrically during cognition.

Retrosplenial Cortical Connectivity with Frontal Basal Ganglia Networks

Previous studies of the retrosplenial cortex (RSC) have focused on its role in navigation and memory, consistent with its well-established medial temporal connections, but recent evidence also suggests a role for this region in reward and decision making. Because function is determined largely by anatomical connections, and to better understand the anatomy of RSC, we used tract-tracing methods to examine the anatomical connectivity between the rat RSC and frontostriatal networks (canonical reward and decision-making circuits). We find that, among frontal cortical regions, RSC bidirectionally connects most strongly with the anterior cingulate cortex, but also with an area of the central-medial orbito-frontal cortex. RSC projects to the dorsomedial striatum, and its terminal fields are virtually encompassed by the frontal-striatal projection zone, suggestive of functional convergence through the basal ganglia. This overlap is driven by anterior cingulate cortex, prelimbic cortex, and orbito-frontal cortex, all of which contribute to goal-directed decision making, suggesting that the RSC is involved in similar processes.

Measuring executive function in sheep (Ovis aries) using visual stimuli in a semi-automated operant system

BACKGROUND

Cognitive impairment is a distinguishing feature of many neurodegenerative diseases. The intra-dimensional (ID) extra-dimensional (ED) attentional set shift task is part of a clinical battery of tests used to evaluate executive function in Huntington's and Alzheimer's disease patients. The IDED task, however, has not translated well to pre-clinical rodent models of neurological disease.

NEW METHOD

The ability to perform executive tasks coupled with a long lifespan makes sheep (Ovis aries) an ideal species for modelling cognitive decline in progressive neurodegenerative conditions. We describe the methodology for testing the performance of sheep in the IDED task using a semi-automated system in which visual stimuli are presented as coloured letters on computer screens.

RESULTS

During each stage of IDED testing, all sheep (n = 12) learned successfully to discriminate between different colours and letters. Sheep were quick to learn the rules of acquisition at each stage. They required significantly more trials to reach criterion (p < 0.05) and made more errors (p < 0.05) following stimulus reversal, with the exception of the ED shift (p > 0.05).

COMPARISON WITH EXISTING METHOD(S)

Previous research shows that sheep can perform IDED set shifting in a walk-through maze using solid objects with two changeable dimensions (colour and shape) as the stimuli. Presenting the stimuli on computer screens provides better validity, greater task flexibility and higher throughput than the walk-through maze.

CONCLUSION

All sheep completed each stage of the task, with a range of abilities expected in an outbred population. The IDED task described is ideally suited as a quantifiable and clinically translatable measure of executive function in sheep.

Task-induced functional brain connectivity mediates the relationship between striatal D2/3 receptors and working memory

Working memory performance is thought to depend on both striatal dopamine 2/3 receptors (D2/3Rs) and task-induced functional organisation in key cortical brain networks. Here, we combine functional magnetic resonance imaging and D2/3R positron emission tomography in 51 healthy volunteers, to investigate the relationship between working memory performance, task-induced default mode network (DMN) functional connectivity changes, and striatal D2/3R availability. Increasing working memory load was associated with reduced DMN functional connectivity, which was itself associated with poorer task performance. Crucially, the magnitude of the DMN connectivity reduction correlated with striatal D2/3R availability, particularly in the caudate, and this relationship mediated the relationship between striatal D2/3R availability and task performance. These results inform our understanding of natural variation in working memory performance, and have implications for understanding age-related cognitive decline and cognitive impairments in neuropsychiatric disorders where dopamine signalling is altered.

Brain regions modulated during covert visual attention in the macaque

Neurophysiological studies of covert visual attention in monkeys have emphasized the modulation of sensory neural responses in the visual cortex. At the same time, electrophysiological correlates of attention have been reported in other cortical and subcortical structures, and recent fMRI studies have identified regions across the brain modulated by attention. Here we used fMRI in two monkeys performing covert attention tasks to reproduce and extend these findings in order to help establish a more complete list of brain structures involved in the control of attention. As expected from previous studies, we found attention-related modulation in frontal, parietal and visual cortical areas as well as the superior colliculus and pulvinar. We also found significant attention-related modulation in cortical regions not traditionally linked to attention - mid-STS areas (anterior FST and parts of IPa, PGa, TPO), as well as the caudate nucleus. A control experiment using a second-order orientation stimulus showed that the observed modulation in a subset of these mid-STS areas did not depend on visual motion. These results identify the mid-STS areas (anterior FST and parts of IPa, PGa, TPO) and caudate nucleus as potentially important brain regions in the control of covert visual attention in monkeys.

Cerebellar Structural Abnormalities Associated With Cognitive Function in Patients With First-Episode Psychosis

Introduction: The fundamental role of the cerebellum in higher cognitive processing has recently been highlighted. However, inconsistent findings exist in schizophrenia with respect to the exact nature of cerebellar structural abnormalities and their associations with cognitive and clinical features. Materials and Methods: We undertook a detailed investigation of cerebellar lobular volumes in 40 patients with first-episode psychosis (FEP) and 40 healthy controls (HCs) using the spatially unbiased atlas template of the cerebellum (SUIT). We examined the functional significance of cerebellar structural abnormalities in relation to cognitive and clinical outcomes in patients. Results: We found that left cerebellar lobules VI and X volumes were lower in FEP patients, compared to HCs. Smaller left lobules VI and X volumes were associated with fewer number of categories completed on the Wisconsin Card Sorting Test (WCST) in patients. In addition, smaller left lobule X volume was related to performance delay on the Trail Making Test (TMT) Part B in patients. Conclusion: Our results demonstrate that cerebellar structural abnormalities are present at the early stage of schizophrenia. We suggest functional associations of cerebellar structural changes with non-verbal executive dysfunctions in FEP.