Performance- and Stimulus-Dependent Oscillations in Monkey Prefrontal Cortex During Short-Term Memory

Short-term memory requires the coordination of sub-processes like encoding, retention, retrieval and comparison of stored material to subsequent input. Neuronal oscillations have an inherent time structure, can effectively coordinate synaptic integration of large neuron populations and could therefore organize and integrate distributed sub-processes in time and space. We observed field potential oscillations (14–95 Hz) in ventral prefrontal cortex of monkeys performing a visual memory task. Stimulus-selective and performance-dependent oscillations occurred simultaneously at 65–95 Hz and 14–50 Hz, the latter being phase-locked throughout memory maintenance. We propose that prefrontal oscillatory activity may be instrumental for the dynamical integration of local and global neuronal processes underlying short-term memory

Fluctuations in Evolutionary Integration Allow for Big Brains and Disparate Faces

In theory, evolutionary modularity allows anatomical structures to respond differently to selective regimes, thus promoting morphological diversification. These differences can then influence the rate and direction of phenotypic evolution among structures. Here we use geometric morphometrics and phenotypic matrix statistics to compare rates of craniofacial evolution and estimate evolvability in the face and braincase modules of a clade of teleost fishes (Gymnotiformes) and a clade of mammals (Carnivora), both of which exhibit substantial craniofacial diversity. We find that the face and braincase regions of both clades display different degrees of integration. We find that the face and braincase evolve at similar rates in Gymnotiformes and the reverse in Carnivora with the braincase evolving twice as fast as the face. Estimates of evolvability and constraints in these modules suggest differential responses to selection arising from fluctuations in phylogenetic integration, thus influencing differential rates of skull-shape evolution in these two clades

Design, construction, and characterization of a compact DD neutron generator designed for 40Ar/39Ar geochronology

A next-generation, high-flux DD neutron generator has been designed, commissioned, and characterized, and is now operational in a new facility at the University of California Berkeley. The generator, originally designed for 40Ar/39Ar dating of geological materials, has since served numerous additional applications, including medical isotope production studies, with others planned for the near future. In this work, we present an overview of the High Flux Neutron Generator (HFNG) which includes a variety of simulations, analytical models, and experimental validation of results. Extensive analysis was performed in order to characterize the neutron yield, flux, and energy distribution at specific locations where samples may be loaded for irradiation. A notable design feature of the HFNG is the possibility for sample irradiation internal to the cathode, just 8 mm away from the neutron production site, thus maximizing the neutron flux (n/cm2/s). The generator's maximum neutron flux at this irradiation position is 2.58e7 n/cm2/s +/- 5% (approximately 3e8 n/s total yield) as measured via activation of small natural indium foils. However, future development is aimed at achieving an order of magnitude increase in flux. Additionally, the deuterium ion beam optics were optimized by simulations for various extraction configurations in order to achieve a uniform neutron flux distribution and an acceptable heat load. Finally, experiments were performed in order to benchmark the modeling and characterization of the HFNG.Comment: 31 pages, 20 figure

Reduction of Pavlovian bias in schizophrenia: Enhanced effects in clozapine-administered patients

The negative symptoms of schizophrenia (SZ) are associated with a pattern of reinforcement learning (RL) deficits likely related to degraded representations of reward values. However, the RL tasks used to date have required active responses to both reward and punishing stimuli. Pavlovian biases have been shown to affect performance on these tasks through invigoration of action to reward and inhibition of action to punishment, and may be partially responsible for the effects found in patients. Forty-five patients with schizophrenia and 30 demographically-matched controls completed a four-stimulus reinforcement learning task that crossed action ("Go" or "NoGo") and the valence of the optimal outcome (reward or punishment-avoidance), such that all combinations of action and outcome valence were tested. Behaviour was modelled using a six-parameter RL model and EEG was simultaneously recorded. Patients demonstrated a reduction in Pavlovian performance bias that was evident in a reduced Go bias across the full group. In a subset of patients administered clozapine, the reduction in Pavlovian bias was enhanced. The reduction in Pavlovian bias in SZ patients was accompanied by feedback processing differences at the time of the P3a component. The reduced Pavlovian bias in patients is suggested to be due to reduced fidelity in the communication between striatal regions and frontal cortex. It may also partially account for previous findings of poorer "Go-learning" in schizophrenia where "Go" responses or Pavlovian consistent responses are required for optimal performance. An attenuated P3a component dynamic in patients is consistent with a view that deficits in operant learning are due to impairments in adaptively using feedback to update representations of stimulus value

Abnormal Frontostriatal Activity During Unexpected Reward Receipt in Depression and Schizophrenia: Relationship to Anhedonia.

Alterations in reward processes may underlie motivational and anhedonic symptoms in depression and schizophrenia. However it remains unclear whether these alterations are disorder-specific or shared, and whether they clearly relate to symptom generation or not. We studied brain responses to unexpected rewards during a simulated slot-machine game in 24 patients with depression, 21 patients with schizophrenia, and 21 healthy controls using functional magnetic resonance imaging. We investigated relationships between brain activation, task-related motivation, and questionnaire rated anhedonia. There was reduced activation in the orbitofrontal cortex, ventral striatum, inferior temporal gyrus, and occipital cortex in both depression and schizophrenia in comparison with healthy participants during receipt of unexpected reward. In the medial prefrontal cortex both patient groups showed reduced activation, with activation significantly more abnormal in schizophrenia than depression. Anterior cingulate and medial frontal cortical activation predicted task-related motivation, which in turn predicted anhedonia severity in schizophrenia. Our findings provide evidence for overlapping hypofunction in ventral striatal and orbitofrontal regions in depression and schizophrenia during unexpected reward receipt, and for a relationship between unexpected reward processing in the medial prefrontal cortex and the generation of motivational states.Supported by a MRC Clinician Scientist award (G0701911), a Brain and Behaviour Research Foundation Young Investigator, and an Isaac Newton Trust award to Dr Murray; an award to Dr Segarra from the Secretary for Universities and Research of the Ministry of Economy and Knowledge of the Government of Catalonia and the European Union; by the University of Cambridge Behavioural and Clinical Neuroscience Institute, funded by a joint award from the Medical Research Council and Wellcome Trust (G1000183 and 093875/Z/10Z respectively); by awards from the Wellcome Trust (095692) and the Bernard Wolfe Health Neuroscience Fund to Professor Fletcher, and by awards from the Wellcome Trust Institutional Strategic Support Fund (097814/Z/11) and Cambridge NIHR Biomedical Research Centre. The authors are grateful for the help of clinical staff in CAMEO, in the Cambridge Rehabilitation and Recovery service and Pathways, and in the Cambridge IAPT service, for help with participant recruitment.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/npp.2015.37

Theories of American Imperialism: A Critical Evaluation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68828/2/10.1177_048661347400600303.pd

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.</p