Prefrontal cortex activation reflects efficient exploitation of higher-order statistical structure

Since everyday actions are statistically structured, knowing which action a person has just completed allows predicting the most likely next action step. Taking even more than the preceding action into account improves this predictability, but also causes higher processing costs. Using fMRI, we investigated whether observers exploit 2nd-order statistical regularities preferentially if information on possible upcoming actions provided by 1st-order regularities is insufficient. We hypothesized that anterior prefrontal cortex balances whether or not 2nd order information should be exploited. Participants watched videos of actions that were structured by 1st- and 2nd-order conditional probabilities. Information provided by the 1st and by the 2nd order was manipulated independently. BOLD activity in the action observation network was more attenuated the more information on upcoming actions was provided by 1st- order structure, reflecting expectation suppression for more predictable actions. Activation in posterior parietal sites decreased further with 2nd-order information, but increased in temporal areas. As expected, 2nd-order information was integrated more when less 1st-order information was provided, and this interaction was mediated by anterior prefrontal cortex (BA 10). Observers spontaneously used both the present and the preceding action to predict the upcoming action, and integration of the preceding action was enhanced when the present action was uninformative.This research was supported by the University of Münster, Germany, and the Max-Planck-Society

Direct entropy determination and application to artificial spin ice

From thermodynamic origins, the concept of entropy has expanded to a range of statistical measures of uncertainty, which may still be thermodynamically significant. However, laboratory measurements of entropy continue to rely on direct measurements of heat. New technologies that can map out myriads of microscopic degrees of freedom suggest direct determination of configurational entropy by counting in systems where it is thermodynamically inaccessible, such as granular and colloidal materials, proteins and lithographically fabricated nanometre-scale arrays. Here, we demonstrate a conditional-probability technique to calculate entropy densities of translation-invariant states on lattices using limited configuration data on small clusters, and apply it to arrays of interacting nanometre-scale magnetic islands (artificial spin ice). Models for statistically disordered systems can be assessed by applying the method to relative entropy densities. For artificial spin ice, this analysis shows that nearest-neighbour correlations drive longer-range ones.Comment: 10 page

Ferromagnetic Semiconductors: Moving Beyond (Ga,Mn)As

The recent development of MBE techniques for growth of III-V ferromagnetic semiconductors has created materials with exceptional promise in spintronics, i.e. electronics that exploit carrier spin polarization. Among the most carefully studied of these materials is (Ga,Mn)As, in which meticulous optimization of growth techniques has led to reproducible materials properties and ferromagnetic transition temperatures well above 150 K. We review progress in the understanding of this particular material and efforts to address ferromagnetic semiconductors as a class. We then discuss proposals for how these materials might find applications in spintronics. Finally, we propose criteria that can be used to judge the potential utility of newly discovered ferromagnetic semiconductors, and we suggest guidelines that may be helpful in shaping the search for the ideal material.Comment: 37 pages, 4 figure

RNAseq Analyses Identify Tumor Necrosis Factor-Mediated Inflammation as a Major Abnormality in ALS Spinal Cord

ALS is a rapidly progressive, devastating neurodegenerative illness of adults that produces disabling weakness and spasticity arising from death of lower and upper motor neurons. No meaningful therapies exist to slow ALS progression, and molecular insights into pathogenesis and progression are sorely needed. In that context, we used high-depth, next generation RNA sequencing (RNAseq, Illumina) to define gene network abnormalities in RNA samples depleted of rRNA and isolated from cervical spinal cord sections of 7 ALS and 8 CTL samples. We aligned \u3e50 million 2X150 bp paired-end sequences/sample to the hg19 human genome and applied three different algorithms (Cuffdiff2, DEseq2, EdgeR) for identification of differentially expressed genes (DEG’s). Ingenuity Pathways Analysis (IPA) and Weighted Gene Co-expression Network Analysis (WGCNA) identified inflammatory processes as significantly elevated in our ALS samples, with tumor necrosis factor (TNF) found to be a major pathway regulator (IPA) and TNFα-induced protein 2 (TNFAIP2) as a major network “hub” gene (WGCNA). Using the oPOSSUM algorithm, we analyzed transcription factors (TF) controlling expression of the nine DEG/hub genes in the ALS samples and identified TF’s involved in inflammation (NFkB, REL, NFkB1) and macrophage function (NR1H2::RXRA heterodimer). Transient expression in human iPSC-derived motor neurons of TNFAIP2 (also a DEG identified by all three algorithms) reduced cell viability and induced caspase 3/7 activation. Using high-density RNAseq, multiple algorithms for DEG identification, and an unsupervised gene co-expression network approach, we identified significant elevation of inflammatory processes in ALS spinal cord with TNF as a major regulatory molecule. Overexpression of the DEG TNFAIP2 in human motor neurons, the population most vulnerable to die in ALS, increased cell death and caspase 3/7 activation. We propose that therapies targeted to reduce inflammatory TNFα signaling may be helpful in ALS patients

Prefrontal and anterior cingulate cortex abnormalities in Tourette Syndrome: evidence from voxel-based morphometry and magnetization transfer imaging

<p>Abstract</p> <p>Background</p> <p>Pathophysiological evidence suggests an involvement of fronto-striatal circuits in Tourette syndrome (TS). To identify TS related abnormalities in gray and white matter we used optimized voxel-based morphometry (VBM) and magnetization transfer imaging (MTI) which are more sensitive to tissue alterations than conventional MRI and provide a quantitative measure of macrostructural integrity.</p> <p>Methods</p> <p>Volumetric high-resolution anatomical T1-weighted MRI and MTI were acquired in 19 adult, unmedicated male TS patients without co-morbidities and 20 age- and sex-matched controls on a 1.5 Tesla neuro-optimized GE scanner. Images were pre-processed and analyzed using an optimized version of VBM in SPM2.</p> <p>Results</p> <p>Using VBM, TS patients showed significant decreases in gray matter volumes in prefrontal areas, the anterior cingulate gyrus, sensorimotor areas, left caudate nucleus and left postcentral gyrus. Decreases in white matter volumes were detected in the right inferior frontal gyrus, the left superior frontal gyrus and the anterior corpus callosum. Increases were found in the left middle frontal gyrus and left sensorimotor areas. In MTI, white matter reductions were seen in the right medial frontal gyrus, the inferior frontal gyrus bilaterally and the right cingulate gyrus. Tic severity was negatively correlated with orbitofrontal structures, the right cingulate gyrus and parts of the parietal-temporal-occipital association cortex bilaterally.</p> <p>Conclusion</p> <p>Our MRI <it>in vivo </it>neuropathological findings using two sensitive and unbiased techniques support the hypothesis that alterations in frontostriatal circuitries underlie TS pathology. We suggest that anomalous frontal lobe association and projection fiber bundles cause disinhibition of the cingulate gyrus and abnormal basal ganglia function.</p

Surprised at All the Entropy: Hippocampal, Caudate and Midbrain Contributions to Learning from Prediction Errors

Influential concepts in neuroscientific research cast the brain a predictive machine that revises its predictions when they are violated by sensory input. This relates to the predictive coding account of perception, but also to learning. Learning from prediction errors has been suggested for take place in the hippocampal memory system as well as in the basal ganglia. The present fMRI study used an action-observation paradigm to investigate the contributions of the hippocampus, caudate nucleus and midbrain dopaminergic system to different types of learning: learning in the absence of prediction errors, learning from prediction errors, and responding to the accumulation of prediction errors in unpredictable stimulus configurations. We conducted analyses of the regions of interests' BOLD response towards these different types of learning, implementing a bootstrapping procedure to correct for false positives. We found both, caudate nucleus and the hippocampus to be activated by perceptual prediction errors. The hippocampal responses seemed to relate to the associative mismatch between a stored representation and current sensory input. Moreover, its response was significantly influenced by the average information, or Shannon entropy of the stimulus material. In accordance with earlier results, the habenula was activated by perceptual prediction errors. Lastly, we found that the substantia nigra was activated by the novelty of sensory input. In sum, we established that the midbrain dopaminergic system, the hippocampus, and the caudate nucleus were to different degrees significantly involved in the three different types of learning: acquisition of new information, learning from prediction errors and responding to unpredictable stimulus developments. We relate learning from perceptual prediction errors to the concept of predictive coding and related information theoretic accounts

Pathoadaptive mutations of Escherichia coli K1 in experimental neonatal systemic infection

Although Escherichia coli K1 strains are benign commensals in adults, their acquisition at birth by the newborn may result in life-threatening systemic infections, most commonly sepsis and meningitis. Key features of these infections, including stable gastrointestinal (GI) colonization and age-dependent invasion of the bloodstream, can be replicated in the neonatal rat. We previously increased the capacity of a septicemia isolate of E. coli K1 to elicit systemic infection following colonization of the small intestine by serial passage through two-day-old (P2) rat pups. The passaged strain, A192PP (belonging to sequence type 95), induces lethal infection in all pups fed 2–6 x 106 CFU. Here we use whole-genome sequencing to identify mutations responsible for the threefold increase in lethality between the initial clinical isolate and the passaged derivative. Only four single nucleotide polymorphisms (SNPs), in genes (gloB, yjgV, tdcE) or promoters (thrA) involved in metabolic functions, were found: no changes were detected in genes encoding virulence determinants associated with the invasive potential of E. coli K1. The passaged strain differed in carbon source utilization in comparison to the clinical isolate, most notably its inability to metabolize glucose for growth. Deletion of each of the four genes from the E. coli A192PP chromosome altered the proteome, reduced the number of colonizing bacteria in the small intestine and increased the number of P2 survivors. This work indicates that changes in metabolic potential lead to increased colonization of the neonatal GI tract, increasing the potential for translocation across the GI epithelium into the systemic circulation

Regulation of Kainate Receptor Subunit mRNA by Stress and Corticosteroids in the Rat Hippocampus

Kainate receptors are a class of ionotropic glutamate receptors that have a role in the modulation of glutamate release and synaptic plasticity in the hippocampal formation. Previous studies have implicated corticosteroids in the regulation of these receptors and recent clinical work has shown that polymorphisms in kainate receptor subunit genes are associated with susceptibility to major depression and response to anti-depressant treatment. In the present study we sought to examine the effects of chronic stress and corticosteroid treatments upon the expression of the mRNA of kainate receptor subunits GluR5-7 and KA1-2. Our results show that, after 7 days, adrenalectomy results in increased expression of hippocampal KA1, GluR6 and GluR7 mRNAs, an effect which is reversed by treatment with corticosterone in the case of KA1 and GluR7 and by aldosterone treatment in the case of GluR6. 21 days of chronic restraint stress (CRS) elevated the expression of the KA1 subunit, but had no effect on the expression of the other subunits. Similarly, 21 days of treatment with a moderate dose of corticosterone also increased KA1 mRNA in the dentate gyrus, whereas a high corticosterone dose has no effect. Our results suggest an interaction between hippocampal kainate receptor composition and the hypothalamic-pituitary-adrenal (HPA) axis and show a selective chronic stress induced modulation of the KA1 subunit in the dentate gyrus and CA3 that has implications for stress-induced adaptive structural plasticity