pwc-archive/papers-with-abstracts huggingface dataset:
A Polyunsaturated Fatty Acid (PUFA) Theory of Schizophrenia
Authors: Ari Rappoport
Date: 2024-08-13 00:00:00

I present a theory of schizophrenia (SZ) that mechanistically explains its etiology, symptoms, pathophysiology, and treatment. SZ involves the chronic release of membrane polyunsaturated fatty acids (PUFAs) and their utilization for the synthesis of stress-induced plasticity agents such as endocannabinoids (ECBs). The causal event in SZ is prolonged stress during a sensitive period, which can induce prolonged and heritable changes. The physiological effect of the released PUFAs and their products is to disconnect neurons from their inputs and promote intrinsic excitability. I show that these effects can explain the positive, negative, cognitive, and mood symptoms of SZ, as well as the mechanisms of many known triggers of psychosis. The theory is supported by overwhelming evidence addressing lipids, immunity, ECBs, neuromodulators, hormones, neurotransmitters, and cortical parameters in SZ. It explains why antipsychotic drugs are effective against positive symptoms, and why they do not affect the other symptoms. Finally, I present promising treatment directions implied by the theory, including some that are immediately available.
A Sympathetic Nervous System Theory of Migraine
Authors: Ari Rappoport
Date: 2024-08-13 00:00:00
Tasks: Sensitivity

Migraine (MGR) ranks first among diseases in terms of years of lost healthy life in young adult and adult women. Currently, there is no theory of MGR. This paper presents a complete theory of migraine that explains its etiology, symptoms, pathology, and treatment. Migraine involves partially saturated (usually chronically high) sympathetic nervous system (SNS) activity, mainly due to higher sensitivity of the metabolic sensors that recruit it. MGR headache occurs when SNS activity is desensitized or excessive, resulting in hyperexcitability of baroreceptors, oxidative stress, and activation of pain pathways via TRPV1 channels and CGRP. The theory is supported by overwhelming evidence, and explains the properties of current MGR treatments.
A Dynorphin Theory of Depression and Bipolar Disorder
Authors: Ari Rappoport
Date: 2024-08-13 00:00:00

Major depressive disorder (MDD) is a debilitating health condition affecting a substantial part of the world's population. At present, there is no biological theory of MDD, and treatment is partial at best. Here I present a theory of MDD that explains its etiology, symptoms, pathophysiology, and treatment. MDD involves stressful life events that the person does not manage to resolve. In this situation animals normally execute a 'disengage' survival response. In MDD, this response is chronically executed, leading to depressed mood and the somatic MDD symptoms. To explain the biological mechanisms involved, I present a novel theory of opioids, where each opioid mediates one of the basic survival responses. The opioid mediating 'disengage' is dynorphin. The paper presents strong evidence for chronic dynorphin signaling in MDD and for its causal role in the disorder. The theory also explains bipolar disorder, and the mechanisms behind the treatment of both disorders.
A CRH Theory of Autism Spectrum Disorder
Authors: Ari Rappoport
Date: 2024-08-13 00:00:00

This paper presents a complete theory of autism spectrum disorder (ASD), explaining its etiology, symptoms, and pathology. The core cause of ASD is excessive stress-induced postnatal release of corticotropin-releasing hormone (CRH). CRH competes with urocortins for binding to the CRH2 receptor, impairing their essential function in the utilization of glucose for growth. This results in impaired development of all brain areas depending on CRH2, including areas that are central in social development and eye gaze learning, and low-level sensory areas. Excessive CRH also induces excessive release of adrenal androgens (mainly DHEA), which impairs the long-term plasticity function of gonadal steroids. I show that these two effects can explain all of the known symptoms and properties of ASD. The theory is supported by strong diverse evidence, and points to very early detection biomarkers and preventive pharmaceutical treatments, one of which seems to be very promising.
Mechanical problem solving in Goffin's cockatoos -- Towards modeling complex behavior
Authors: Manuel Baum, Theresa Roessler, Antonio J. Osuna-Mascaró, Alice Auersperg, Oliver Brock
Date: 2024-08-12 00:00:00

Research continues to accumulate evidence that Goffin's cockatoos (Cacatua goffiniana) can solve wide sets of mechanical problems, such as tool use, tool manufacture, and solving mechanical puzzles. However, the proximate mechanisms underlying this adaptive behavior are largely unknown. In this study, we analyze how three Goffin's cockatoos learn to solve a specific mechanical puzzle, a lockbox. The observed behavior results from the interaction between a complex environment (the lockbox) and different processes that jointly govern the animals' behavior. We thus jointly analyze the parrots' (1) engagement, (2) sensorimotor skill learning, and (3) action selection. We find that neither of these aspects could solely explain the animals' behavioral adaptation and that a plausible model of proximate mechanisms (including adaptation) should thus also jointly address these aspects. We accompany this analysis with a discussion of methods that may be used to identify such mechanisms. A major point we want to make is, that it is implausible to reliably identify a detailed model from the limited data of one or a few studies. Instead, we advocate for a more coarse approach that first establishes constraints on proximate mechanisms before specific, detailed models are formulated. We exercise this idea on the data we present in this study.
Status epilepticus and thinning of the entorhinal cortex
Authors: Jonathan Horsley, Yujiang Wang, Callum Simpson, Vyte Janiukstyte, Karoline Leiberg, Beth Little, Jane de Tisi, John Duncan, Peter N. Taylor
Date: 2024-08-11 00:00:00

Status epilepticus (SE) carries risks of morbidity and mortality. Experimental studies have implicated the entorhinal cortex in prolonged seizures; however, studies in large human cohorts are limited. We hypothesised that individuals with temporal lobe epilepsy (TLE) and a history of SE would have more severe entorhinal atrophy compared to others with TLE and no history of SE. 357 individuals with drug resistant temporal lobe epilepsy (TLE) and 100 healthy controls were scanned on a 3T MRI. For all subjects the cortex was segmented, parcellated, and the thickness calculated from the T1-weighted anatomical scan. Subcortical volumes were derived similarly. Cohen's d and Wilcoxon rank-sum tests respectively were used to capture effect sizes and significance. Individuals with TLE and SE had reduced entorhinal thickness compared to those with TLE and no history of SE. The entorhinal cortex was more atrophic ipsilaterally (d=0.51, p<0.001) than contralaterally (d=0.37, p=0.01). Reductions in ipsilateral entorhinal thickness were present in both left TLE (n=22:176, d=0.78, p<0.001), and right TLE (n=19:140, d=0.31, p=0.04), albeit with a smaller effect size in right TLE. Several other regions exhibited atrophy in individuals with TLE, but these did not relate to a history of SE. These findings suggest potential involvement or susceptibility of the entorhinal cortex in prolonged seizures.
Geometrical determinant of nonlinear synaptic integration in human cortical pyramidal neurons
Authors: Jaeyoung Yoon
Date: 2024-08-10 00:00:00

Neurons integrate synaptic inputs and convert them to action potential output at electrically distant locations. The computational power of a neuron is hence enhanced by subcellular compartmentalization and nonlinear synaptic integration, but the biophysical determinants of these features in human neurons are not completely understood. By examining the synaptic input-output function of human neocortical pyramidal neurons, we found that the nonlinearity threshold at the soma was linearly determined by the shortest path distance from the synapse to the apical trunk, and the slope of this relationship was consistent throughout the dendritic arbor. Analogous rules were found from both supragranular and infragranular layers of the rodent cortex, suggesting that these represent a fundamental property of pyramidal neurons. Additionally, we found that neurons associated with tumor or epilepsy had distinct membrane properties, but the nonlinearity threshold was shifted in amplitude such that the slope of its relationship with synaptic distance remained consistent.
Recurrence Resonance -- Noise-Enhanced Dynamics in Recurrent Neural Networks
Authors: Claus Metzner, Achim Schilling, Andreas Maier, Patrick Krauss
Date: 2024-08-10 00:00:00

In specific motifs of three recurrently connected neurons with probabilistic response, the spontaneous information flux, defined as the mutual information between subsequent states, has been shown to increase by adding ongoing white noise of some optimal strength to each of the neurons \cite{krauss2019recurrence}. However, the precise conditions for and mechanisms of this phenomenon called 'recurrence resonance' (RR) remain largely unexplored. Using Boltzmann machines of different sizes and with various types of weight matrices, we show that RR can generally occur when a system has multiple dynamical attractors, but is trapped in one or a few of them. In probabilistic networks, the phenomenon is bound to a suitable observation time scale, as the system could autonomously access its entire attractor landscape even without the help of external noise, given enough time. Yet, even in large systems, where time scales for observing RR in the full network become too long, the resonance can still be detected in small subsets of neurons. Finally, we show that short noise pulses can be used to transfer recurrent neural networks, both probabilistic and deterministic, between their dynamical attractors. Our results are relevant to the fields of reservoir computing and neuroscience, where controlled noise may turn out a key factor for efficient information processing leading to more robust and adaptable systems.
Testing the Brain Wave Hypothesis
Authors: Robert Worden
Date: 2024-07-25 00:00:00

It has been proposed that there is a wave excitation in animal brains, whose function is to represent three-dimensional space around the animal as a working spatial memory. After surveying the evidence supporting the hypothesis, I discuss ways in which it can be tested. There are many ways to investigate it, theoretically and experimentally. They include connectome studies, computational modelling, experimental neuroscience, genomics and proteomics, studies of animal behaviour, and biophysics. If the wave exists, there is a compelling case to identify it as the source of consciousness. This would advance our understanding of one of the greatest scientific challenges of all time, while changing our view of the human mind.
Assessing the Brain Wave Hypothesis: Call for Commentary
Authors: Robert Worden
Date: 2024-07-25 00:00:00

It has been proposed that there is a wave excitation in animal brains, whose role is to represent three dimensional local space in a working memory. Evidence for the wave comes from the mammalian thalamus, the central body of the insect brain, and from computational models of spatial cognition. This is described in related papers. I assess the Bayesian probability that the wave exists, from this evidence. The probability of the wave in the brain is robustly greater than 0.4. If there is such a wave, we may need to re-think our whole understanding of the brain, in a break from classical neuroscience. I ask other researchers to comment on the wave hypothesis and on this assessment. In a companion paper, I outline possible ways to test it.
Signal selective amplification for below-the-threshold stimulus in Fitzhugh-Nagumo neuronal model
Authors: Mariia Sorokina
Date: 2024-07-22 00:00:00

Brain operates at remarkably low signal power. It has been noted that noise may play a constructive role in neural networks and facilitate the subthreshold signaling. The process of spiking pattern excitation at the characteristic neuronal spiking frequency from the random noisy stimulus remains unexplained. Furthermore, recent research indicates that neuronal processing enables signal selective amplification. Also, there is a growing number of studies indicating the role of coloured noise for spike generation, while noise shaping effect have been recently observed in neuronal networks as well as in single neurons. We demonstrate for the first time that noise shaping enables efficient signal amplification and spike excitation for below-the-threshold stimulus. On the example of the seminal FitzHugh-Nagumo (FHN) model we reveal that the complex interplay between the fast and slow FHN variables leads to noise accumulation at the FHN characteristic spiking frequencies, while tails follow a power-law frequency scaling. We demonstrate that the discovered effect allows selective amplification of signal waveforms presenting a novel type of amplification process.
Harmonic fractal transformation, 4R-regeneration and noise shaping for ultra wide-band reception in FitzHugh-Nagumo neuronal model
Authors: Mariia Sorokina
Date: 2024-07-22 00:00:00
Tasks: Functional Connectivity

Human hearing range significantly surpasses the typical neuronal spiking frequency. Yet, neurons with their modest frequency range not only efficiently receive and process multiple orders higher frequency signals, but also demonstrate remarkable stability and adaptability to frequency variations in brain functional connectivity. Ability to process signals beyond the limitations of the receiver temporal or frequency (bandwidth) resolution is highly desirable yet requires complex design architectures. Using the FitzHugh-Nagumo model we reveal the harmonic fractal transformation of frequency and bandwidth, which enables the Nyquist rate integer (for low frequencies) and sub-integer (for high frequencies) multiplication. We also demonstrate for the first time that noise shaping can be achieved in a simple RLC-circuit without a requirement of a delay line. The discovered effect presents a novel regeneration type - 4R: re-amplifying, re-shaping, re-timing, and re-modulating and due to the fractal nature of transformation offers a remarkable regenerative efficiency. The effect is a generalization of phase locking to non-periodic encoded signals. The discovered physical mechanism explains how using neuronal functionality one can receive and process signals over an ultra-wide band (below or higher the spiking neuronal range by multiple orders) and below the noise floor.
White matter tract crossing and bottleneck regions in the fetal brain
Authors: Camilo Calixto, Matheus D. Soldatelli, Bo Li, Lana Pierotich, Ali Gholipour, Simon K. Warfield, Davood Karimi
Date: 2024-07-20 00:00:00
Tasks: Diffusion  MRI

There is a growing interest in using diffusion MRI to study the white matter tracts and structural connectivity of the fetal brain. Recent progress in data acquisition and processing suggests that this imaging modality has a unique role in elucidating the normal and abnormal patterns of neurodevelopment in utero. However, there have been no efforts to quantify the prevalence of crossing tracts and bottleneck regions, important issues that have been extensively researched for adult brains. In this work, we determined the brain regions with crossing tracts and bottlenecks between 23 and 36 gestational weeks. We performed probabilistic tractography on 59 fetal brain scans and extracted a set of 51 distinct white tracts, which we grouped into 10 major tract bundle groups. We analyzed the results to determine the patterns of tract crossings and bottlenecks. Our results showed that 20-25% of the white matter voxels included two or three crossing tracts. Bottlenecks were more prevalent. Between 75-80% of the voxels were characterized as bottlenecks, with more than 40% of the voxels involving four or more tracts. The results of this study highlight the challenge of fetal brain tractography and structural connectivity assessment and call for innovative image acquisition and analysis methods to mitigate these problems.
TGL-Lambda: An implementation of TrapGrid to estimate trap attractiveness from heterogeneous field data
Authors: Ben Scalero, Nicholas C. Manoukis
Date: 2024-08-10 00:00:00

This paper describes a recently developed software called ``TGL-Lambda'' enables quantifying lure attractiveness under a variety of field capture scenarios including mixed lure/trap combinations. TGL-Lambda delivers a flexible approach to simultaneously estimating the {\lambda} value for multiple trap types, accommodating a common situation in ``Mark-release-recapture'' (MRR) experiments in the field. Specifically, where researchers release a known number of marked insects in a field and count how many are recaptured in two to five trap and lure types, and the trap and release locations are known, TGL-Lambda can be used to estimate the attractiveness ({\lambda}) of each of the trap types.
Within-host infection dynamics with master equations and the method of moments: A case study of human papillomavirus in the epithelium
Authors: Mariah C. Boudreau, Jamie A. Cohen, Laurent Hébert-Dufresne
Date: 2024-08-09 00:00:00

Master equations provide researchers with the ability to track the distribution over possible states of a system. From these equations, we can summarize the temporal dynamics through a method of moments. These distributions and their moments capture the stochastic nature of a system, which is essential to study infectious diseases. In this paper, we define the states of the system to be the number of infected cells of a given type in the epithelium, the hollow organ tissue in the human body. Epithelium found in the cervix provides a location for viral infections to live and persist, such as human papillomavirus (HPV). HPV is a highly transmissible disease which most commonly affects biological females and has the potential to progress into cervical cancer. By defining a master equation model which tracks the infected cell layer dynamics, information on disease extinction, progression, and viral output can be derived from the method of moments. From this methodology and the outcomes we glean from it, we aim to inform differing states of HPV infected cells, and assess the effects of structural information for each outcome.
The 2023 Dengue Outbreak in Lombardy, Italy: A One-Health Perspective
Authors: Francesca Rovida, Marino Faccini, Carla Molina Grané, Irene Cassaniti, Sabrina Senatore, Eva Rossetti, Giuditta Scardina, Manuela Piazza, Giulia Campanini, Daniele Lilleri, Stefania Paolucci, Guglielmo Ferrari, Antonio Piralla, Francesco Defilippo, Davide Lelli, Ana Moreno, Luigi Vezzosi, Federica Attanasi, Soresini Marzia, Barozzi Manuela, Lorenzo Cerutti, Stefano Paglia, Angelo Regazzetti, Maurilia Marcacci, Guido Di Donato, Marco Farioli, Mattia Manica, Piero Poletti, Antonio Lavazza, Maira Bonini, Stefano Merler, Fausto Baldanti, Danilo Cereda, Lombardy Dengue network
Date: 2024-08-08 00:00:00
Tasks: Diagnostic

Introduction. Here we reported the virological, entomological and epidemiological characteristics of the large autochthonous outbreak of dengue (DENV) occurred in a small village of the Lombardy region (Northern Italy) during summer 2023. Methods. After the diagnosis of the first autochthonous case on 18 August 2023, public health measures, including epidemiological investigation and vector control measures, were carried out. A serological screening for DENV antibodies detection was offered to the population. In the case of positive DENV IgM, a second sample was collected to detect DENV RNA and verify seroconversion. Entomological and epidemiological investigations were also performed. A modeling analysis was conducted to estimate the dengue generation time, transmission potential, distance of transmission, and assess diagnostic delays. Results. Overall, 416 subjects participated to the screening program and 20 were identified as DENV-1 cases (15 confirmed and 5 probable). In addition, DENV-1 infection was diagnosed in 24 symptomatic subjects referred to the local Emergency Room Department for suggestive symptoms and 1 case was identified through blood donation screening. The average generation time was estimated to be 18.3 days (95% CI: 13.1-23.5 days). R0 was estimated at 1.31 (95% CI: 0.76-1.98); 90% of transmission occurred within 500m. Entomological investigations performed in 46 pools of mosquitoes revealed the presence of only one positive pool for DENV-1. Discussion. This report highlights the importance of synergic surveillance, including virological, entomological and public health measures to control the spread of arboviral infections.
All the single cells: single-cell transcriptomics/epigenomics experimental design and analysis considerations for glial biologists
Authors: Katherine E. Prater, Kevin Z. Lin
Date: 2024-08-12 00:00:00
Tasks: All, Experimental Design

Single-cell transcriptomics, epigenomics, and other 'omics applied at single-cell resolution can significantly advance hypotheses and understanding of glial biology. Omics technologies are revealing a large and growing number of new glial cell subtypes, defined by their gene expression profile. These subtypes have significant implications for understanding glial cell function, cell-cell communications, and glia-specific changes between homeostasis and conditions such as neurological disease. For many, the training in how to analyze, interpret, and understand these large datasets has been through reading and understanding literature from other fields like biostatistics. Here, we provide a primer for glial biologists on experimental design and analysis of single-cell RNA-seq datasets. Our goal is to further the understanding of why decisions might be made about datasets and to enhance biologists' ability to interpret and critique their work and the work of others. We review the steps involved in single-cell analysis with a focus on decision points and particular notes for glia. The goal of this primer is to ensure that single-cell 'omics experiments continue to advance glial biology in a rigorous and replicable way.
Facilitating bootstrapped and rarefaction-based microbiome diversity analysis with q2-boots
Authors: Isaiah Raspet, Elizabeth Gehret, Chloe Herman, Jeff Meilander, Andrew Manley, Anthony Simard, Evan Bolyen, J. Gregory Caporaso
Date: 2024-08-10 00:00:00
Tasks: Diversity

Background: We present q2-boots, a QIIME 2 plugin that facilitates bootstrapped and rarefaction-based microbiome diversity analysis. This plugin provides eight new actions that allow users to apply any of thirty different alpha diversity metrics and twenty-two beta diversity metrics to bootstrapped or rarefied feature tables, using a single QIIME 2 Pipeline command, or more granular QIIME 2 Action commands. Results: Given a feature table, an even sampling depth, and the number of iterations to perform (n), the command qiime boots core-metrics will resample the feature table n times and compute alpha and beta diversity metrics on each resampled table. The results will be integrated in summary data artifacts that are identical in structure and type to results that would be generated by applying diversity metrics to a single table. This enables all of the same downstream analytic tools to be applied to these tables, and ensures that all collected data is considered when computing microbiome diversity metrics. Conclusions: A challenge of this work was deciding how to integrate distance matrices that were computed on n resampled feature tables, as a simple average of pairwise distances (median or mean) does not account for the structure of distance matrices. q2-boots provides three options, and we show here that the results of these approaches are highly correlated. q2-boots is free and open source. Source code, installation instructions, and a tutorial can be found at https://github.com/caporaso-lab/q2-boots.