Applications of Information Theory to Analysis of Neural Data

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying information flow in the nervous system. It has a number of useful properties: it is a general measure sensitive to any relationship, not only linear effects; it has meaningful units which in many cases allow direct comparison between different experiments; and it can be used to study how much information can be gained by observing neural responses in single trials, rather than in averages over multiple trials. A variety of information theoretic quantities are commonly used in neuroscience - (see entry "Definitions of Information-Theoretic Quantities"). In this entry we review some applications of information theory in neuroscience to study encoding of information in both single neurons and neuronal populations.Comment: 8 pages, 2 figure

Total Luminal Volume Predicts Risk after Endovascular Aneurysm Repair

Objective: Large aneurysm diameter represents a well known predictor of late complications after endovascular aneurysm repair (EVAR). However, the role of the thrombus free lumen inside the abdominal aortic aneurysm (AAA) sac is not clear. It was hypothesised that greater luminal volume represents a relevant risk factor for late complications after EVAR. Methods: A retrospective cohort analysis was performed including all patients undergoing EVAR from 2005 to 2016 at a tertiary referral institution. Pre-operative AAA lumen volume was measured in centre lumen line reconstructions and patients were stratified into quartiles according to luminal volume. The primary endpoint was freedom from AAA related complications. Secondary endpoints were freedom from neck events (type 1A endoleak, migration >5 mm or any pre-emptive neck related intervention), iliac related events (type 1B endoleak or pre-emptive iliac related intervention), and overall survival. Results: Four hundred and four patients were included: 101 in the first quartile (Q1; <61 cm3). Patients with higher luminal volumes had wider, shorter, and more angulated proximal necks. There were more ruptured AAAs, more aorto-uni-iliac implanted devices and patients outside neck instructions for use in the 4th quartile. Five year freedom from AAA related complications was 79%, 66%, 58% and 56%, respectively (p = .007). At five years, freedom from neck related events was 86%, 84%, 73%, and 71%, respectively, for the four groups (p = .009), and freedom from iliac related events was 96%, 91%, 88%, and 88%, respectively (p = .335). On multivariable analysis, luminal volume was an independent predictor of late complications (Q4 vs. Q1 - hazard ratio: 1.91, 95% confidence interval 1.01-3.6, p = .046). Overall survival at five years was not affected by lumen volume (p = .75). Conclusion: AAA luminal volume represents an important risk factor for AAA related complications. This information may be considered when deciding tailoring surveillance protocols after EVAR. However, larger studies are needed to validate this hypothesis.info:eu-repo/semantics/publishedVersio

Sparse, decorrelated odor coding in the mushroom body enhances learned odor discrimination

Sparse coding may be a general strategy of neural systems for augmenting memory capacity. In Drosophila melanogaster, sparse odor coding by the Kenyon cells of the mushroom body is thought to generate a large number of precisely addressable locations for the storage of odor-specific memories. However, it remains untested how sparse coding relates to behavioral performance. Here we demonstrate that sparseness is controlled by a negative feedback circuit between Kenyon cells and the GABAergic anterior paired lateral (APL) neuron. Systematic activation and blockade of each leg of this feedback circuit showed that Kenyon cells activated APL and APL inhibited Kenyon cells. Disrupting the Kenyon cell–APL feedback loop decreased the sparseness of Kenyon cell odor responses, increased inter-odor correlations and prevented flies from learning to discriminate similar, but not dissimilar, odors. These results suggest that feedback inhibition suppresses Kenyon cell activity to maintain sparse, decorrelated odor coding and thus the odor specificity of memories

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons