Biology subjects

Stewart, T. C.

Publications and source records attributed to Stewart, T. C..

7 recordsLinked to original sources

bioRxiv2026

Novel model combining intrinsic and learned behaviours captures divergent effects of dopaminergic drugs on different types of motivation

Motivation-based symptoms occur in an array of neurological and neurodegenerative disorders, including Schizophrenia and Parkinsons Disease. Unfortunately, there is, as yet, no agreed treatment approach. To establish a better understanding of motivation, and so highlight potential avenues for treatment, motivation is often investigated using operant behavioural paradigms such as the Effort for Reward (EfR) task. Performance on these tasks is thought to be influenced by reinforcement learning (RL) mechanisms, such that disorders of motivation can be described in terms of altered interactions with RL processes. Recently, foraging behaviour has been increasingly adopted as an ethologically valid approach to investigating cognitive mechanisms, including motivation. One example of this is the recently developed Effort Based Foraging task (EBF). Foraging behaviour, unlike the strictly controlled and contrived operant behavioural paradigms, involves a series of complex behavioural processes, each potentially driven by different cognitive processes. It is therefore important to identify which portion of the foraging behavioural sequence is driven by the same RL mechanisms as classical operant behavioural paradigms, and therefore can be used to investigate motivation. In this work we set out to establish whether the same RL mechanisms could be used to account for behaviours observed in both EfR and EBF tasks. We identified where, within the EBF task, RL mechanisms were no long sufficient and developed a novel hybrid model of the behaviour. This model successfully accounted for external influences on motivation, including previously unpredicted effects of clinically used dopaminergic drugs. This work reveals that motivation in complex, naturalistic tasks cannot be fully explained by learning-based models alone. Incorporating intrinsic behavioural drives may be needed as neuroscience moves toward more ethological behavioural assays.

neuroscience↗

bioRxiv2025

Rare bioactive tau oligomers from Alzheimer brain support both templated misfolding and fibril formation

In Alzheimers disease, both classical neurofibrillary tangles, and diffusible, aqueous soluble (High Molecular Weight, or HMW) species are able to support templated misfolding. How these tau proteoforms relate is uncertain. Using sequential size exclusion and anion exchange chromatography, we fractionated the HMW tau population and found both seed competent, and seed not competent proteoforms. Super resolution, atomic force, and immunogold electron microscopy confirmed that the size and conformation of both bioactive and non-bioactive tau proteoforms are similar, with dimers, trimers, and tetramers predominating. The presence of surface phosphorylation correlates with seeding capacity. Bioactive tau at fMol concentrations can induce seeding in a reporter cell. The soluble bioactive species support aggregation of a truncated repeat domain tau construct into thioflavin T positive fibrils and retain seeding activity over serial amplification in vitro and in cellulo, whereas non-bioactive oligomeric species do not. Together, these findings indicate that oligomeric assembly is required but not sufficient for seeding; instead, specific biochemical attributes of a rare oligomeric tau subset confer self-propagating, prion-like templated misfolding.

neuroscience↗

bioRxiv2025

Neurons accumulate disease-specific somatic genomic changes across taupathologic states in Alzheimer's disease

Tau deposition within neurons marks Alzheimers disease (AD) neuropathology, suggesting that tau may contribute to cellular dysfunction and death. In AD, somatic mutations accumulate in neurons, with features that suggest deleterious effects on cellular function. To examine the relationship between tau and somatic mutation, we isolated neurons according to tau pathology and performed single-cell whole-genome sequencing on tau+, tau-, and tau-agnostic neurons from 13 individuals with AD, as well as neurons from 15 control individuals. We found that AD neurons, regardless of tau status, exhibited an increased burden of somatic single-nucleotide variants (sSNVs) and insertions and deletions (sIndels). Mutational signature analyses revealed disease-specific patterns, including sIndels characterized by two-basepair (2bp) deletions, indicating shared mutagenic mechanisms in AD neurons across tau pathologic cell states. Somatic mutations are associated with tissue-wide tau pathology, suggesting that tangles do not confer cell-autonomous genotoxicity to neurons and that non-tangle components drive somatic mutation in AD.

genomics↗

bioRxiv2024

Molecular Polymorphism of tau aggregates in Pick's disease

Tau protein plays a central role in many neuropathies. The trajectory by which tau spreads through neural networks is disease-specific but the events driving progression are unknown. This is due in part to the challenge of characterizing tau aggregates in situ. We address that challenge using in situ micro-x-ray diffraction ({micro}XRD) and micro-X-ray fluorescence (XRF) to examine tau lesions in the brain of a 79-year-old male with dementia. Neuropathological examination revealed classical forms of tau in the hippocampal formation: extensive Pick bodies in the granular layer; modest numbers of neurofibrillary tangles and dystrophic neurites in the CA4 and hilus. {micro}XRD indicated that Pick bodies are low in fibril content, whereas neurofibrillary lesions within adjacent tissue exhibit far greater density of fibrillar tau. XRF demonstrated elevated levels of zinc, calcium and phosphorous in all tau-containing lesions whereas sulfur deposition was greatest in lesions exhibiting high fibrillar content. Correlation of lesion morphology with anatomical localization, tau fibrillation and differential elemental accumulation suggests tau fibrils generate biochemically distinct microenvironments that influence lesion morphology, tau seed formation and spreading.

neuroscience↗

bioRxiv2024

Computational Models of Age-Associated Cognitive Slowing

BackgroundCognitive slowing accompanies normal aging, yet understanding of the mechanisms of slowing is limited at the network and neuronal level. Relating the pathophysiological factors responsible for cognitive slowing, and interpreting its relationship to working memory, requires multiscale computer modeling. ObjectiveThe aim of this research is to explore multiple mechanisms of cognitive slowing using computational modeling of the cortex to link neuronal activity with cognitive content. MethodWe developed multiscale computer models of a simple cognitive task - Condition 1 of the Stroop recognition task - using the Nengo system, a cognitive simulation environment with a semantic pointer architecture developed to model cognitive tasks using spiking neural networks. We explored how changes associated with aging such as increased input noise, axonal loss, neuronal loss, and feedback would affect the function of the models. ResultsAxonal loss and increased input noise produced profound slowing. High levels of neuronal loss severely impaired memory and paradoxically decreased slowing via the ability to respond more quickly by "releasing" a prior memory. Increased feedback improved memory at the cost of increased slowing. ConclusionOur simulations suggest that significant slowing could be caused by white matter loss (axonal loss) or input signal degradation (which could be caused by visual or other afferent system worsening). As neuronal loss markedly decreased the duration of working memory, we propose that physiological feedback is increased to preserve working memory at the cost of further cognitive slowing.

neuroscience↗

bioRxiv2020

A neural model for insect steering applied to olfaction and path integration

Many animal behaviours require orientation and steering with respect to the environment. For insects, a key brain area involved in spatial orientation and navigation is the central complex. Activity in this neural circuit has been shown to track the insects current heading relative to its environment, and has also been proposed to be the substrate of path integration. However, it remains unclear how the output of the central complex is integrated into motor commands. Central complex output neurons project to the lateral accessory lobes (LAL), from which descending neurons project to thoracic motor centres. Here, we present a computational model of a simple neural network that has been described anatomically and physiologically in the LALs of male silkworm moths, in the context of odour-mediated steering. We present and analyze two versions of this network, both implemented in the Nengo framework, one rate-based and one based on spiking neurons. The modelled network consists of an inhibitory local interneuron and a bistable descending neuron ( flip-flop), which both receive input in the LAL. The flip-flop neuron projects onto neck motor neurons to induce steering. We show that this simple computational model not only replicates the basic parameters of male silkworm moth behaviour in a simulated odour plume, but can also take input from a computational model of path integration in the central complex and use it to steer back to a point of origin. Furthermore, we find that increasing the level of detail within the model improves the realism of the models behaviour. Our results suggest that descending neurons originating in the lateral accessory lobes, such as flip-flop neurons, are sufficient to mediate multiple steering behaviours. This study is therefore a first step to close the gap between orientation circuits in the central complex and downstream motor centres. Author summaryTargeted movements and steering within an environment are essential for many behaviours. In insects, the brains center for spatial orientation and navigation is the central complex, which processes information about the configuration of the local environment as well as global orientation cues such as the Sun position. Neural networks in the central complex also compute the insects heading direction, and are thought to be involved in generating steering commands. However, it is unclear how these steering commands are transmitted to downstream motor centers. Output neurons from the central complex project to the lateral accessory lobes, a neuropil which also gives rise to descending pre-motor neurons that are involved in steering in the silkworm moth Bombyx mori. In this study, we provide a computational model of a pre-motor neural network in the lateral accessory lobes. We show that this network can steer an agent towards the source of a simulated odor plume, but that it can also steer efficiently when getting input from an anatomically constrained network model of the central complex. This model is therefore a first step to close the gap between the central complex and thoracic motor circuits.

neuroscience↗

bioRxiv2019

A functional spiking-neuron model of activity-silent working memory in humans based on calcium-mediated short-term synaptic plasticity

In this paper, we present a functional spiking-neuron model of human working memory (WM). This model combines neural firing for encoding of information with activity-silent maintenance. While it used to be widely assumed that information in WM is maintained through persistent recurrent activity, recent studies have shown that information can be maintained without persistent firing; instead, information can be stored in activity-silent states. A candidate mechanism underlying this type of storage is short-term synaptic plasticity (STSP), by which the strength of connections between neurons rapidly changes to encode new information. To demonstrate that STSP can lead to functional behavior, we integrated STSP by means of calcium-mediated synaptic facilitation in a large-scale spiking-neuron model and added a decision mechanism. The model was used to simulate a recent study that measured behavior and EEG activity of participants in three delayed-response tasks. In these tasks, one or two visual gratings had to be maintained in WM, and compared to subsequent probes. The original study demonstrated that WM contents and its priority status could be decoded from neural activity elicited by a task-irrelevant stimulus displayed during the activity-silent maintenance period. In support of our model, we show that it can perform these tasks, and that both its behavior as well as its neural representations are in agreement with the human data. We conclude that information in WM can be effectively maintained in activity-silent states by means of calcium-mediated STSP. Author SummaryMentally maintaining information for short periods of time in working memory is crucial for human adaptive behavior. It was recently shown that the human brain does not only store information through neural firing - as was widely believed - but also maintains information in activity-silent states. Here, we present a detailed neural model of how this could happen in our brain through short-term synaptic plasticity: rapidly adapting the connection strengths between neurons in response to incoming information. By reactivating the adapted network, the stored information can be read out later. We show that our model can perform three working memory tasks as accurately as human participants can, while using similar mental representations. We conclude that our model is a plausible and effective neural implementation of human working memory.

neuroscience↗