4,672 research outputs found
On the path integration system of insects: there and back again
Navigation is an essential capability of animate organisms and robots. Among animate organisms of particular interest are insects because they are capable of a variety of navigation competencies solving challenging problems with limited resources, thereby providing inspiration for robot navigation.
Ants, bees and other insects are able to return to their nest using a navigation strategy known as path integration. During path integration, the animal maintains a running estimate of the distance and direction to its nest as it travels. This estimate, known as the `home vector', enables the animal to return to its nest.
Path integration was the technique used by sea navigators to cross the open seas in the past. To perform path integration, both sailors and insects need access to two pieces of information, their direction and their speed of motion over time. Neurons encoding the heading and speed have been found to converge on a highly conserved region of the insect brain, the central complex. It is, therefore, believed that the central complex is key to the computations pertaining to path integration.
However, several questions remain about the exact structure of the neuronal circuit that tracks the animal's heading, how it differs between insect species, and how the speed and direction are integrated into a home vector and maintained in memory. In this thesis, I have combined behavioural, anatomical, and physiological data with computational modelling and agent simulations to tackle these questions.
Analysis of the internal compass circuit of two insect species with highly divergent ecologies, the fruit fly Drosophila melanogaster and the desert locust Schistocerca gregaria, revealed that despite 400 million years of evolutionary divergence, both species share a fundamentally common internal compass circuit that keeps track of the animal's heading. However, subtle differences in the neuronal morphologies result in distinct circuit dynamics adapted to the ecology of each species, thereby providing insights into how neural circuits evolved to accommodate species-specific behaviours.
The fast-moving insects need to update their home vector memory continuously as they move, yet they can remember it for several hours. This conjunction of fast updating and long persistence of the home vector does not directly map to current short, mid, and long-term memory accounts. An extensive literature review revealed a lack of available memory models that could support the home vector memory requirements.
A comparison of existing behavioural data with the homing behaviour of simulated robot agents illustrated that the prevalent hypothesis, which posits that the neural substrate of the path integration memory is a bump attractor network, is contradicted by behavioural evidence.
An investigation of the type of memory utilised during path integration revealed that cold-induced anaesthesia disrupts the ability of ants to return to their nest, but it does not eliminate their ability to move in the correct homing direction. Using computational modelling and simulated agents, I argue that the best explanation for this phenomenon is not two separate memories differently affected by temperature but a shared memory that encodes both the direction and distance.
The results presented in this thesis shed some more light on the labyrinth that researchers of animal navigation have been exploring in their attempts to unravel a few more rounds of Ariadne's thread back to its origin. The findings provide valuable insights into the path integration system of insects and inspiration for future memory research, advancing path integration techniques in robotics, and developing novel neuromorphic solutions to computational problems
Differences in well-being:the biological and environmental causes, related phenotypes, and real-time assessment
Well-being is a complex, and multifaceted construct that includes feeling good and functioning well. There is a growing global recognition of well-being as an important research topic and public policy goal. Well-being is related to less behavioral and emotional problems, and is associated with many positive aspects of daily life, including longevity, higher educational achievement, happier marriage, and more productivity at work. People differ in their levels of well-being, i.e., some people are in general happier or more satisfied with their lives than others. These individual differences in well-being can arise from many different factors, including biological (genetic) influences and environmental influences. To enhance the development of future mental health prevention and intervention strategies to increase well-being, more knowledge about these determinants and factors underlying well-being is needed. In this dissertation, I aimed to increase the understanding of the etiology in a series of studies using different methods, including systematic reviews, meta-analyses, twin designs, and molecular genetic designs. In part I, we brought together all published studies on the neural and physiological factors underlying well-being. This overview allowed us to critically investigate the claims made about the biology involved in well-being. The number of studies on the neural and physiological factors underlying well-being is increasing and the results point towards potential correlates of well-being. However, samples are often still small, and studies focus mostly on a single biomarker. Therefore, more well-powered, data-driven, and integrative studies across biological categories are needed to better understand the neural and physiological pathways that play a role in well-being. In part II, we investigated the overlap between well-being and a range of other phenotypes to learn more about the etiology of well-being. We report a large overlap with phenotypes including optimism, resilience, and depressive symptoms. Furthermore, when removing the genetic overlap between well-being and depressive symptoms, we showed that well-being has unique genetic associations with a range of phenotypes, independently from depressive symptoms. These results can be helpful in designing more effective interventions to increase well-being, taking into account the overlap and possible causality with other phenotypes. In part III, we used the extreme environmental change during the COVID-19 pandemic to investigate individual differences in the effects of such environmental changes on well-being. On average, we found a negative effect of the pandemic on different aspects of well-being, especially further into the pandemic. Whereas most previous studies only looked at this average negative effect of the pandemic on well-being, we focused on the individual differences as well. We reported large individual differences in the effects of the pandemic on well-being in both chapters. This indicates that one-size-fits-all preventions or interventions to maintain or increase well-being during the pandemic or lockdowns will not be successful for the whole population. Further research is needed for the identification of protective factors and resilience mechanisms to prevent further inequality during extreme environmental situations. In part IV, we looked at the real-time assessment of well-being, investigating the feasibility and results of previous studies. The real-time assessment of well-being, related variables, and the environment can lead to new insights about well-being, i.e., results that we cannot capture with traditional survey research. The real-time assessment of well-being is therefore a promising area for future research to unravel the dynamic nature of well-being fluctuations and the interaction with the environment in daily life. Integrating all results in this dissertation confirmed that well-being is a complex human trait that is influenced by many interrelated and interacting factors. Future directions to understand individual differences in well-being will be a data-driven approach to investigate the complex interplay of neural, physiological, genetic, and environmental factors in well-being
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Excitation-inhibition imbalance in migraine: from neurotransmitters to brain oscillations
Migraine is among the most common and debilitating neurological disorders typically affecting people of working age. It is characterised by a unilateral, pulsating headache often associated with severe pain. Despite the intensive research, there is still little understanding of the pathophysiology of migraine. At the electrophysiological level, altered oscillatory parameters have been reported within the alpha and gamma bands. At the molecular level, altered glutamate and GABA concentrations have been reported. However, there has been little cross-talk between these lines of research. Thus, the relationship between oscillatory activity and neurotransmitter concentrations remains to be empirically traced. Importantly, how these indices link back to altered sensory processing has to be clearly established as yet. Accordingly, pharmacologic treatments have been mostly symptom-based, and yet sometimes proving ineffective in resolving pain or related issues. This review provides an integrative theoretical framework of excitation-inhibition imbalance for the understanding of current evidence and to address outstanding questions concerning the pathophysiology of migraine. We propose the use of computational modelling for the rigorous formulation of testable hypotheses on mechanisms of homeostatic imbalance and for the development of mechanism-based pharmacological treatments and neurostimulation interventions
Space, time and item coding in the lateral entorhinal cortex and the hippocampus
Episodic memory formation involves encoding information about space, items and time of an experience. In
humans and animals, episodic memory formation depends on the interaction of associative areas with the
hippocampus (HC) and its surrounding parahippocampal areas, in particular the entorhinal cortex (EC). The EC
medial and lateral subdivisions (MEC and LEC), harbour a plethora of spatially and item modulated cell types,
respectively. Thus, MEC and LEC were long considered specialised spatial and item coding centres, respectively,
that conveyed this information to the HC, where it was integrated into one episodic memory. In agreement
with this hypothesis, the firing of neurons in the HC is spatially modulated but is also modified by changes in
contextual and item components of an environment. However, recent studies suggest that both the MEC and
LEC carry out spatial and item coding, albeit the way these elements are encoded may differ. In addition,
temporal coding in the hippocampus requires an intact MEC, however, the specific functional MEC cell types
involved in this process are unknown. Thus, it is currently unclear how space, items and time are encoded in
each of the entorhinal-hippocampal areas, and how the different entorhinal-hippocampal circuits contribute to
the transmission and association of episodic memory components. In this thesis, I explored this question from
three different angles: firstly, I characterized mechanisms of spatial and item coding in the LEC and in the CA1
hippocampal area; secondly, I studied the contribution of a specific MEC-to-LEC pathway to spatial and item
coding in the LEC; thirdly, I evaluated whether the temporal coding process of phase precession in hippocampal
neurons is dependent on a specific MEC functional cell type, namely grid cells. For this purpose, I performed
and analysed in vivo electrophysiological recordings in freely moving mice subjected to a variety of experimental
settings, and combined this with optogenetic tagging of neurons for circuit characterisation. The findings
reported in this thesis fundamentally advance our understanding of the processes underlying episodic memory
encoding in several ways. First, I found that spatial selectivity in the LEC decreases along the anteroposterior
axis, and that spatially modulated neurons remap when the spatial framework changes. In addition, I describe
distinct functional cell types in the LEC encoding for different object features. Importantly, spatial and object
coding neurons appear to be distinct non-overlapping neuronal populations, arguing for a separate processing
of items and space in the LEC. Interestingly, object coding neurons are selectively avoided by long-range
GABAergic projections from MEC to LEC. In the HC, in turn, a subset of spatially modulated neurons also encode
object-related information, suggesting that these two components of episodic memory are integrated, at least
to some extent, in this region. These findings give experimental evidence to the episodic memory encoding
process proposed by the cognitive map theory. Finally, in respect to temporal coding, I demonstrated that phase
precession is intact in the HC when grid cell firing is disrupted in the MEC, indicating that this mechanism may
be dependent on other MEC neurons and/or pathways. Together, these findings uncover new mechanisms of
encoding and transmission of the three episodic memory components in the entorhinal-hippocampal circuits
NeuroGame: neural mechanisms underlying cognitive improvement in video gamers
The video game market represents an influential and profitable industry. But concerns have been raised how video games impact on the human mind. There are reservations that video gaming may be addictive and foster aggressive behaviour. In contrast, a convincing body of research indicates that playing video games may improve cognitive processing. The exact mechanism thereof is not entirely understood. Most research suggests that video games train individuals in learning how to employ attentional control to focus on processing relevant information, while being able to suppress irrelevant information. Thus, video game players acquire the ability of being able to develop strategies to process information more efficiently. However, no algorithmic solution therefore has been provided yet. Thus, it is not clear which and how attentional control functions contribute to these effects. Moreover, neural mechanisms thereof are not well understood. We hypothesized that alterations in alpha power, i.e., modulations in brain oscillatory activity around 10 Hz, represent a promising neural substrate of video gaming effects. This was because, alpha activity represents an established neural correlate of attention processing given that its amplitude modulation corresponds to alterations in information processing. We investigated this by relating differential cognitive processing in video game players to changes in alpha power modulation. Moreover, we tried to imitate this effect using non-invasive brain stimulation. We were successful in achieving the former but not the latter. We provide a reasonable explanation for this. Thus, our results mostly support our hypothesis according to which altered alpha power may account for gaming effects
Analytical validation of innovative magneto-inertial outcomes: a controlled environment study.
peer reviewe
Study of neural circuits using multielectrode arrays in movement disorders
Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2022-2023. Tutor/Director: RodrÃguez Allué, Manuel JoséNeurodegenerative movement-related disorders are characterized by a progressive degeneration and loss of neurons, which lead to motor control impairment. Although the precise mechanisms underlying these conditions are still unknown, an increasing number of studies point towards the analysis of neural networks and functional connectivity to unravel novel insights. The main objective of this work is to understand cellular mechanisms related to dysregulated motor control symptoms in movement disorders, such as Chorea-Acanthocytosis (ChAc), by employing multielectrode arrays to analyze the electrical activity of neuronal networks in mouse models. We found no notable differences in cell viability between neurons with and without VPS13A knockdown, that is the only gene known to be implicated in the disease, suggesting that the absence of VPS13A in neurons may be partially compensated by other proteins. The MEA setup used to capture the electrical activity from neuron primary cultures is described in detail, pointing out its specific characteristics. At last, we present the alternative backup approach implemented to overcome the challenges faced during the research process and to explore the advanced algorithms for signal processing and analysis.
In this report, we present a thorough account of the conception and implementation of our research, outlining the multiple limitations that have been encountered all along the course of the project. We provide a detailed analysis on the project’s economical and technical feasibility, as well as a comprehensive overview of the ethical and legal aspects considered during the execution
Scale-free avalanches in arrays of FitzHugh-Nagumo oscillators
The activity in the brain cortex remarkably shows a simultaneous presence of
robust collective oscillations and neuronal avalanches, where intermittent
bursts of pseudo-synchronous spiking are interspersed with long periods of
quiescence. The mechanisms allowing for such a coexistence are still a matter
of an intensive debate. Here, we demonstrate that avalanche activity patterns
can emerge in a rather simple model of an array of diffusively coupled neural
oscillators with multiple timescale local dynamics in vicinity of a canard
transition. The avalanches coexist with the fully synchronous state where the
units perform relaxation oscillations. We show that the mechanism behind the
avalanches is based on an inhibitory effect of interactions, which may quench
the spiking of units due to an interplay with the maximal canard. The avalanche
activity bears certain heralds of criticality, including scale-invariant
distributions of event sizes. Furthermore, the system shows an increased
sensitivity to perturbations, manifested as critical slowing down and a reduced
resilience.Comment: 9 figure
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The Monogenic Architecture of Retinal and Neurological Diseases
Monogenic diseases, or single-gene disorders, are clinical manifestations that can be traced to genetic variation in a single gene that alters the biologically intended (wildtype) function of its protein (or mRNA) product. Although the causal gene and its function are well-understood in many monogenic diseases, this knowledge alone often does not fully encapsulate the extensive clinical spectrum of phenotypes seen in patients. This is due in part to the numerous types of pathogenic variants that can arise in a single gene, all of which can have distinct effects on disease expression. Understanding the relationship between the vast number of possible genotypes and corresponding disease phenotypes defines a gene’s monogenic disease architecture—an important but poorly understood concept that can yield informative mechanistic and clinical insight.
This doctoral dissertation integrates traditional sequencing approaches with in-depth characterization of patient phenotypes to elucidate the monogenic disease architecture of three etiologically distinct disorders: retinal degeneration caused by autosomal recessive variation in ABCA4 and neurodevelopmental disease entities caused by autosomal dominant variants in CERT1 and PUM1. Genetic modifiers are identified as a significant factor in the penetrance of the major disease-causing allele of ABCA4 and several other genetic inconsistencies are resolved to create a coherent genotype-phenotype model for the disease. Insight from this model is then applied to demonstrate the effect of allele differences in disease progression and evaluation of treatment efficacy in patients. A large cohort of affected individuals with CERT1 variation is assembled to (1) validate the causal role of CERT1 in disease, (2) delineate the precise mechanism of CERT protein dysfunction in sphingolipid metabolism and (3) demonstrate therapeutic efficacy of an inhibitor compound for a newly described syndrome.
Finally, the mutational spectrum of PUM1 is expanded to previously unattributed variant classes with unexpected pathophysiological consequences to patients. Not only do the findings in this dissertation advance the prospects of delivering personalized, precision medicine to patients, the overall impact underscores the importance of this integrated approach in reconciling knowledge gaps between observations at the molecular and organismal level
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