Biology subjects

Jones, M. W.

Publications and source records attributed to Jones, M. W..

14 recordsLinked to original sources

bioRxiv2024

Short- and long-term reconfiguration of rat prefrontal cortical networks following single doses of psilocybin

We quantify cellular- and circuit-resolution neural network dynamics following therapeutically relevant doses of the psychedelic psilocybin. Using chronically implanted Neuropixels probes, we recorded local field potentials (LFP) alongside action potentials from hundreds of neurons spanning infralimbic, prelimbic and cingulate subregions of the medial prefrontal cortex of freely-behaving adult rats. Psilocybin (0.3mg/kg or 1mg/kg i.p.) unmasked 100Hz high frequency oscillations that were most pronounced within the infralimbic cortex, persisted for approximately 1h post-injection and were accompanied by decreased net pyramidal cell firing rates and reduced signal complexity. These acute effects were more prominent during resting behaviour than during a sustained attention task. LFP 1-, 2- and 6-days post-psilocybin showed gradually-emerging increases in beta and low-gamma (20-60Hz) power, specific to the infralimbic cortex. These findings reveal features of psychedelic action not readily detectable in human brain imaging, implicating infralimbic network oscillations as potential biomarkers of psychedelic-induced network plasticity over multi-day timescales.

neuroscience↗

bioRxiv2024

Deep learning-based location decoding reveals that across-day representational drift is better predicted by rewarded experience than time

Neural representations of locational and spatial relations in the hippocampus and related brain areas change over timescales of days-weeks, even in familiar contexts and when behavior appears stable. It remains unclear how this representational drift is driven by combinations of the passage of time, general experience or specific features of experience. We present a novel deep-learning approach for measuring network-level representational drift, quantifying drift as the rate of change in decoder error of deep neural networks as a function of train-test lag. Using this method, we analyse a longitudinal dataset of 0.5-475 Hz broadband local field potential (LFP) data recorded from dorsal hippocampal CA1, medial prefrontal cortex and parietal cortex of six rats over [~]30 days, during learning of a spatial navigation task in an initially unfamiliar environment. All three brain regions contained clear spatial representations which evolve and drift over training sessions. We find that the rate of drift slows for later training sessions. Finally, we find that drift is statistically better explained by task-relevant experiences within the maze, rather than the passage of time or number of sessions the animal spent on the maze. While previous research has focused on drift as a measure of the changes in spiking activities of units, here we examine drift as a measure of change in oscillatory activity of local field potentials; our approach of using of deep neural networks to quantify drift in broadband neural time series unlocks new possibilities for defining the drivers and functional consequences of representational drift.

neuroscience↗

bioRxiv2023

Integration of rate and temporal codes by hippocampal cell-assemblies supports theta phase coding of episodic information

Spatial information is encoded by location-dependent hippocampal place cell firing rates and sub-second, rhythmic entrainment of spike times. These rate and temporal codes have primarily been characterized in low-dimensional environments under limited cognitive demands; but how is coding configured in complex environments when individual place cells signal several locations, individual locations contribute to multiple routes and functional demands vary? Quantifying rat CA1 population dynamics during a decision-making task, we show that the phase of individual place cells spikes relative to the local theta rhythm shifts to differentiate activity in different place fields. Theta phase coding also disambiguates repeated visits to the same location during different routes, particularly preceding spatial decisions. Using unsupervised detection of cell assemblies alongside theoretical simulation, we show that integrating rate and phase coding mechanisms dynamically recruits units to different assemblies, generating spiking sequences that disambiguate episodes of experience and multiplexing spatial information with cognitive context.

neuroscience↗

bioRxiv2023

Wolbachia is a nutritional symbiont

The intracellular bacterium Wolbachia is a common symbiont of many arthropods and nematodes, well studied for its impacts on host reproductive biology. However, its broad success as a vertically transmitted infection cannot be attributed to manipulations of host reproduction alone. Using the Drosophila melanogaster model and their natively associated Wolbachia strain "wMel", we show that Wolbachia infection supports fly development and buffers against nutritional stress. Wolbachia infection across several fly genotypes and a range of nutrient conditions resulted in reduced pupal mortality, increased adult emergence, and larger size. We determined that the exogenous supplementation of pyrimidines partially rescued developmental phenotypes in the Wolbachia-free flies, and that Wolbachia titers were responsive to reduced gene expression of the flys de novo pyrimidine synthesis pathway. In parallel, transcriptomic and metabolomic analyses indicated that Wolbachia impacts larval biology far beyond pyrimidine metabolism. Wolbachia-infected larvae had strong signatures of shifts in glutathione and mitochondrial metabolism, plus significant changes in the expression of key developmental regulators including Notch, the insulin receptor (lnR), and the juvenile hormone receptor Methoprene-tolerant (Met). We propose that Wolbachia acts as a beneficial symbiont to support fly development and enhance host fitness, especially during periods of nutrient stress. SIGNIFICANCEWolbachia is a bacterial symbiont of arthropods and nematodes, well described for its manipulations of arthropod reproduction. However, many have theorized there must be more to this symbiosis, even in well-studied Wolbachia-host relationships such as with Drosophila. Reproductive impacts alone cannot explain the success and ubiquity of this bacterium. Here, we use Drosophila melanogaster and their native Wolbachia infections to show that Wolbachia supports fly development and significantly buffers flies against nutritional stress. These developmental advantages might help explain the ubiquity of Wolbachia infections.

developmental biology↗

bioRxiv2022

Infection dynamics of co-transmitted reproductive symbionts are mediated by sex, tissue, and development

One of the most prevalent intracellular infections on earth is with Wolbachia: a bacterium in the Rickettsiales that infects a range of insects, crustaceans, chelicerates, and nematodes. Wolbachia is maternally transmitted to offspring and has profound effects on the reproduction and physiology of its hosts, which can result in reproductive isolation, altered vectorial capacity, mitochondrial sweeps, and even host speciation. Some populations stably harbor multiple Wolbachia strains, which can further contribute to reproductive isolation and altered host physiology. However, almost nothing is known about the requirements for multiple intracellular microbes to be stably maintained across generations while they likely compete for space and resources. Here we use a coinfection of two Wolbachia strains ("wHa" and "wNo") in Drosophila simulans to define the infection and transmission dynamics of an evolutionarily stable double infection. We find that a combination of sex, tissue, and host development contribute to the infection dynamics of the two microbes and that these infections exhibit a degree of niche partitioning across host tissues. wHa is present at a significantly higher titer than wNo in most tissues and developmental stages, but wNo is uniquely dominant in ovaries. Unexpectedly, the ratio of wHa to wNo in embryos does not reflect those observed in the ovaries, indicative of strain-specific transmission dynamics. Understanding how Wolbachia strains interact to establish and maintain stable infections has important implications for the development and effective implementation of Wolbachia-based vector biocontrol strategies, as well as more broadly defining how cooperation and conflict shape intracellular communities. IMPORTANCEWolbachia are maternally transmitted intracellular bacteria that manipulate the reproduction and physiology of arthropods, resulting in drastic effects on the fitness, evolution, and even speciation of their hosts. Some hosts naturally harbor multiple strains of Wolbachia that are stably transmitted across generations, but almost nothing is known about the factors that limit or promote these co-infections which can have profound effects on the hosts biology and evolution, and are under consideration as an insect-management tool. Here we define the infection dynamics of a known stably transmitted double infection in Drosophila simulans with an eye towards understanding the patterns of infection that might facilitate compatibility between the two microbes. We find that a combination of sex, tissue, and development all contribute how the coinfection establishes.

microbiology↗

bioRxiv2021

Prefrontal cortical contributions to working memory loading, maintenance and recall are parsed by hippocampal-prefrontal oscillatory assembly dynamics

Working memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both prefrontal cortex and hippocampus, where neurons encode task cues, rules and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC populations lead in maintaining sample information across delays of an operant nonmatch to sample task, despite individual neurons firing only transiently. During sample encoding, distinct mPFC subpopulations joined distributed CA1-mPFC cell assemblies hallmarked by 4-5Hz rhythmic modulation; CA1-mPFC assemblies re-emerged during choice episodes, but were not 4-5Hz modulated. Delay-dependent errors arose when attenuated rhythmic assembly activity heralded collapse of sustained mPFC encoding; pharmacological disruption of CA1-mPFC assembly rhythmicity impaired task performance. Our results map component processes of memory-guided decisions onto heterogeneous CA1-mPFC subpopulations and the dynamics of physiologically distinct, distributed cell assemblies.

neuroscience↗

bioRxiv2020

Heterozygous deletion of SYNGAP enzymatic domains in rats causes selective learning, social and seizure phenotypes

Pathogenic variants in SYNGAP1 are one of the most common genetic causes of nonsyndromic intellectual disability (ID) and are considered a risk for autism spectrum disorder (ASD). SYNGAP1 encodes a synaptic GTPase activating protein that modulates the intrinsic GTPase activity of several small G-proteins and is implicated in regulating the composition of the postsynaptic density. By targeting the deletion of exons encoding the calcium/lipid binding (C2) and GTPase activating protein (GAP) domains, we generated a novel rat model to study SYNGAP related pathophysiology. We find that rats heterozygous for the C2/GAP domain deletion (Syngap+/{Delta}-GAP) exhibit reduced exploration and fear extinction, altered social behaviour, and spontaneous seizures, while homozygous mutants die within days after birth. This new rat model reveals that the enzymatic domains of SYNGAP are essential for normal brain function and provide an important new model system in the study of both ID/ASD and epilepsy.

neuroscience↗

bioRxiv2020

Neurotrophin receptor activation rescues cognitive and synaptic abnormalities caused by mutation of the psychiatric risk gene Cacna1c

Genetic variation in CACNA1C, which encodes the alpha-1 subunit of CaV1.2 L-type voltage-gated calcium channels, is strongly linked to risk for psychiatric disorders including schizophrenia and bipolar disorder. To translate genetics to neurobiological mechanisms and rational therapeutic targets, we investigated the impact of altered Cacna1c dosage on rat cognitive, synaptic and circuit phenotypes implicated by patient studies. We show that rats hemizygous for Cacna1c harbor marked impairments in learning to disregard non-salient stimuli, a behavioral change previously associated with psychosis. This behavioral deficit is accompanied by dys-coordinated network oscillations during learning, pathway-selective disruption of hippocampal synaptic plasticity, attenuated Ca2+ signaling in dendritic spines and decreased signaling through the Extracellular-signal Regulated Kinase (ERK) pathway. Activation of the ERK pathway by a small molecule agonist of TrkB/TrkC neurotrophin receptors rescued both behavioral and synaptic plasticity deficits in Cacna1c+/- rats. These results map a route through which genetic variation in CACNA1C can disrupt experience-dependent synaptic signaling and circuit activity, culminating in cognitive alterations associated with psychiatric disorders. Our findings highlight targeted activation of neurotrophin signaling pathways with BDNF mimetic drugs as a novel, genetically informed therapeutic approach for rescuing behavioral abnormalities in psychiatric disorder. One Sentence SummaryNeurotrophin receptor activation reveals that BDNF mimetic drugs have therapeutic potential to ameliorate genetic risk for psychiatric disorders.

neuroscience↗

bioRxiv2020

Dopamine-gated memory selection during slow wave sleep

The human brain selectively stores knowledge of the world to optimise future behaviour, automatically rehearsing, contextualising or discarding information to create a robust record of experiences. Storage or forgetting evolves over time, particularly during sleep. We have previously shown that dopamine given in the form of L-DOPA tablets improves long-term memory in Parkinsons disease, but only when given overnight. L-DOPA is already prescribed widely with a good safety profile and could potentially be rapidly repurposed to improve cognitive performance and improve quality of life in, for example, early Alzheimers Disease, if we understood the best time of day to prescribe. Therefore, we sought to test how dopamine shaped long-term memory formation before and during sleep in a double-blind randomised placebo-controlled cross-over trial of healthy older adults (n = 35). We administered L-DOPA after word-list learning to be active during repeat exposure to a proportion of the words and during subsequent nocturnal sleep. Nocturnal dopamine accelerated forgetting for words presented once but it did not affect memory for words presented twice. During slow wave sleep, L-DOPA also increased spindle amplitude around slow oscillation peaks. Larger dopamine-induced difference in word memory was associated with a larger increase in spindle amplitude. Dopamine-dependent memory processing may therefore modulate spindles dependent on slow-oscillation phase. Further, overnight dopamine increased total slow wave sleep duration by approximately 11%. This pharmaceutical modification of slow wave sleep may have potential health-enhancing benefits in old age that could include cognitive enhancement and Alzheimers prevention. One Sentence SummaryDopamine before sleep promotes forgetting of weak memory traces associated with increased spindle amplitude around the peak of a slow oscillations.

neuroscience↗

bioRxiv2020

Schizophrenia-associated variation at ZNF804A correlates with altered experience-dependent dynamics of sleep slow-waves and spindles in healthy young adults

BackgroundThe rs1344706 polymorphism in ZNF804A is robustly associated with schizophrenia (SZ), yet brain and behavioral phenotypes related to this variant have not been extensively characterized. In turn, SZ is associated with abnormal non-rapid eye movement (NREM) sleep neurophysiology. To examine whether rs1344706 is associated with intermediate neurophysiological traits in the absence of disease, we assessed the relationship between genotype, sleep neurophysiology, and sleep-dependent memory consolidation in healthy participants. MethodsWe recruited healthy adult males, with no history of psychiatric disorder, from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. Participants were homozygous for either the SZ-associated A allele (N=25) or the alternative C allele (N=22) at rs1344706. Actigraphy, polysomnography (PSG) and a motor sequencing task (MST) were used to characterize daily activity patterns, sleep neurophysiology and sleep-dependent memory consolidation. ResultsAverage MST learning and sleep-dependent performance improvements were similar across genotype groups, but with increased variability in the AA group. CC participants showed increased slow-wave and spindle amplitudes, plus augmented coupling of slow-wave activity across recording electrodes after learning. Slow-waves and spindles in those with the AA genotype were insensitive to learning, whilst slow-wave coherence decreased following MST training. ConclusionWe describe evidence that rs1344706 polymorphism in ZNF804A is associated with changes in experience- and sleep-dependent, local and distributed neural network activity that supports offline information processing during sleep in a healthy population. These findings highlight the utility of sleep neurophysiology in mapping the impacts of SZ-associated variants on neural circuit oscillations and function.

neuroscience↗

bioRxiv2019

Behavioural and computational evidence for memory consolidation biased by reward-prediction errors

Neural activity encoding recent experiences is replayed during sleep and rest to promote consolidation of memories. However, precisely which features of experience influence replay prioritisation to optimise adaptive behaviour remains unclear. Here, we trained adult male rats on a novel maze-based reinforcement learning task designed to dissociate reward outcomes from reward-prediction errors. Four variations of a reinforcement learning model were fitted to the rats behaviour over multiple days. Behaviour was best predicted by a model incorporating replay biased by reward-prediction error, compared to the same model with no replay, random replay or reward-biased replay. Neural population recordings from the hippocampus and ventral striatum of rats trained in the task evidenced preferential reactivation of reward-prediction and reward-prediction error signals during post-task rest. These insights disentangle the influences of salience on replay, suggesting that reinforcement learning is tuned by post-learning replay biased by reward-prediction error, not by reward per se. This work therefore provides a behavioural and theoretical toolkit with which to measure and interpret the neural mechanisms linking replay and reinforcement learning.

neuroscience↗

bioRxiv2019

Neurophysiological predictors of memory impairment in schizophrenia: decoupled slow-wave dynamics during non-REM sleep

The slow-waves (SW) of non-rapid eye movement sleep (NREM) reflect neocortical components of network activity during sleep-dependent information processing; their disruption may therefore contribute to impaired memory consolidation. Here, we quantify SW dynamics relative to motor sequence memory in patients suffering schizophrenia and healthy volunteers.\n\nPatients showed normal intrinsic SW properties but impaired SW coherence, which failed to exhibit the learning-dependent increases evident in healthy volunteers. SW-spindle phase amplitude coupling across distributed EEG electrodes was also dissociated from experience in patients, with long-range fronto-parietal and -occipital networks most severely affected. Partial least squares regression modelling confirmed distributed SW coherence and SW-spindle coordination as predictors of overnight memory consolidation in healthy controls, but not in patients.\n\nQuantifying the full repertoire of NREM EEG oscillations and their long-range covariance therefore presents learning-dependent changes in distributed SW and spindle coordination as fingerprints of impaired cognition in schizophrenia.

neuroscience↗

bioRxiv2018

Locus Coeruleus tracking of prediction errors optimises cognitive flexibility: an Active Inference model.

The locus coeruleus (LC) in the pons is the major source of noradrenaline (NA) in the brain. Two modes of LC firing have been associated with distinct cognitive states: changes in tonic rates of firing are correlated with global levels of arousal and behavioural flexibility, whilst phasic LC responses are evoked by salient stimuli. Here, we unify these two modes of firing by modelling the response of the LC as a correlate of a prediction error when inferring states for action planning under Active Inference (AI).\n\nWe simulate a classic Go/No-go reward learning task and a three-arm foraging task and show that, if LC activity is considered to reflect the magnitude of high level state-action prediction errors, then both tonic and phasic modes of firing are emergent features of belief updating. We also demonstrate that when contingencies change, AI agents can update their internal models more quickly by feeding back this state-action prediction error - reflected in LC firing and noradrenaline release - to optimise learning rate, enabling large adjustments over short timescales. We propose that such prediction errors are mediated by cortico-LC connections, whilst ascending input from LC to cortex modulates belief updating in anterior cingulate cortex (ACC).\n\nIn short, we characterise the LC/ NA system within a general theory of brain function. In doing so, we show that contrasting, behaviour-dependent firing patterns are an emergent property of the LCs crucial role in translating prediction errors into an optimal mediation between plasticity and stability.\n\nAuthor SummaryThe brain uses sensory information to build internal models and make predictions about the world. When errors of prediction occur, models must be updated to ensure desired outcomes are still achieved. Neuromodulator chemicals provide a possible pathway for triggering such changes in brain state. One such neuromodulator, noradrenaline, originates predominantly from a cluster of neurons in the brainstem - the locus coeruleus (LC) - and plays a key role in behaviour, for instance, in determining the balance between exploiting or exploring the environment.\n\nHere we use Active Inference (AI), a mathematical model of perception and action, to formally describe LC function. We propose that LC activity is triggered by errors in prediction and that the subsequent release of noradrenaline alters the rate of learning about the environment. Biologically, this describes an LC-cortex feedback loop promoting behavioural flexibility in times of uncertainty. We model LC output as a simulated animal performs two tasks known to elicit archetypal responses. We find that experimentally observed phasic and tonic patterns of LC activity emerge naturally, and that modulation of learning rates improves task performance. This provides a simple, unified computational account of noradrenergic computational function within a general model of behaviour.

neuroscience↗

bioRxiv2017

Defining the synaptic mechanisms that tune CA3-CA1 reactivation during sharp-wave ripples.

During non-REM sleep, memory consolidation is driven by a dialogue between hippocampus and cortex involving the reactivation of specific neural activity sequences ( replay). In the hippocampus, replay occurs during sharp-wave ripples (SWRs), short bouts of excitatory activity in area CA3 which induce high frequency oscillations in the inhibitory interneurons of area CA1. Despite growing evidence for the functional importance of replay, its neural mechanisms remain poorly understood. Here, we develop a novel theoretical model of hippocampal spiking during SWRs. In our model, noise-induced activation of CA3 pyramidal cells triggered an excitatory cascade capable of inducing local ripple events in CA1. Ripples occurred stochastically, with Schaffer Collaterals driving their coordination, so that localized sharp waves in CA3 produced consistently localized CA1 ripples. In agreement with experimental data, the majority of pyramidal cells in the model showed low reactivation probabilities across SWRs. We found, however, that a subpopulation of pyramidal cells had high reactivation probabilities, which derived from fine-tuning of the network connectivity. In particular, the excitatory inputs along synaptic pathway(s) converging onto cells and cell pairs controlled emergent single cell and cell pair reactivation, with inhibitory inputs and intrinsic cell excitability playing differential roles in CA3 vs. CA1. Our model predicts (1) that the hippocampal network structure driving the emergence of SWR is also able to generate and modulate reactivation, (2) inhibition plays a particularly prominent role in CA3 reactivation and (3) CA1 sequence reactivation is reliant on CA3-CA1 interactions rather than an intrinsic CA1 process.

neuroscience↗