Biology subjects

Burgess, N.

Publications and source records attributed to Burgess, N..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

The influence of environment geometry on subiculum boundary vector cells in adulthood and early development

Boundaries to movement form a specific class of landmark information used for navigation: Boundary Vector Cells (BVCs) are neurons which encode an animals location as a vector displacement from boundaries. Here we report the first objective characterisation of the prevalence and spatial tuning of subiculum BVCs. Manipulations of boundary geometry reveal two novel features of BVC firing. Firstly, BVC directional tunings align with environment walls in squares, but are uniformly distributed in circles, demonstrating that environmental geometry alters BVC receptive fields. Secondly, inserted barriers uncover both excitatory and inhibitory components to BVC receptive fields, demonstrating that inhibitory inputs contribute to BVC field formation. During post-natal development, subiculum BVCs mature slowly, contrasting with the earlier maturation of boundary-responsive cells in upstream Entorhinal Cortex. However, Subiculum and Entorhinal BVC receptive fields are altered by boundary geometry as early as tested, suggesting this is an inherent feature of the hippocampal representation of space.

neuroscience↗

bioRxiv2023

Path integration selectively predicts midlife risk of Alzheimer's disease

The entorhinal cortex (EC) is the first cortical region to exhibit neurodegeneration in Alzheimers disease (AD), associated with EC grid cell dysfunction. Given the role of grid cells in path integration, we predicted that path integration impairment would represent the first behavioural change in adults at-risk of AD. Using immersive virtual reality, we found that midlife path integration impairments predicted both hereditary and physiological AD risk, with no corresponding impairment on tests of episodic memory or other spatial behaviours. Impairments related to poorer angular estimation and were associated with hexadirectional grid-like fMRI signal in the posterior-medial EC. These results indicate that altered path integration may represent the transition point from at-risk state to disease onset in AD, prior to impairment in other cognitive domains.

neuroscience↗

bioRxiv2023

Nature Forest Reserves in Tanzania and their importance for conservation

Since 1997 Tanzania has undertaken a process to identify and declare a network of Nature Forest Reserves (NFRs) with high biodiversity values, mainly from within its existing portfolio of national Forest Reserves, but with some new extensions. In recent years this expansion has accelerated, with ten NFRs declared since 2015. The current network of 19 existing NFRs covered 918,212 hectares by the end of 2020 (with an additional three reserves covering 34,862 hectares in the process of being declared). The coverage by NFRs of Tanzanian habitat types has increased to include the main forest types, wet, seasonal, and dry, and includes wetlands and grasslands. This has led to more than a doubling of the coverage of species ranges of vertebrates by the NFR network. Declared and proposed reserves now contain at least 178 of Tanzanias 242 endemic vertebrate species, of which over 50% are threatened with extinction, and 553 Tanzanian endemic plant taxa (species, subspecies, and varieties), of which 61.3% are threatened. NFRs also support 41 single site endemic vertebrate species and 76 single site endemic plant taxa. Time series data show that NFR management effectiveness is increasing, especially where donor funds are available. Tourism, diversified revenue generation and investment schemes are required to create a network of economically self-sustaining NFRs able to conserve critical biodiversity values. Improved management and investment have reduced some threats in recent years, but ongoing challenges include illegal logging, charcoal production, firewood, pole cutting, hunting, fire, wildlife trade, and the unpredictable impacts of climate change.

ecology↗

bioRxiv2023

Paradoxical consequences of early hippocampal damage: greater atrophy is associated with better recall, working memory and visuospatial perception in developmental amnesia

Despite bilateral hippocampal damage dating to perinatal or early-childhood period, and severely-impaired episodic memory that unfolds in later childhood, patients with developmental amnesia continue to exhibit well-developed semantic memory across the developmental trajectory. Detailed information on the extent and focality of brain damage in these patients is needed to hypothesize about the neural substrate that supports their remarkable capacity for encoding and retrieval of semantic memory. In particular, we need to assess whether the residual hippocampal tissue is involved in this preservation, or whether the surrounding cortical areas reorganise to rescue aspects of these critical cognitive memory processes after early injury. We used voxel-based morphometry (VBM) analysis, automatic (FreeSurfer) and manual segmentation to characterize structural changes in the brain of an exceptionally large cohort of 23 patients with developmental amnesia in comparison with 32 control subjects. Both the VBM and the FreeSurfer analyses revealed severe structural alterations in the hippocampus and thalamus of patients with developmental amnesia. Milder damage was found in the amygdala, caudate and parahippocampal gyrus. Manual segmentation demonstrated differences in the degree of atrophy of the hippocampal subregions in patients. The level of atrophy in CA-DG subregions and subicular complex was more than 40% while the atrophy of the uncus was moderate (-23%). Anatomo-functional correlations were observed between the volumes of residual hippocampal subregions in patients and selective aspects of their cognitive performance viz, intelligence, working memory, and verbal and visuospatial recall. Our findings suggest that in patients with developmental amnesia, cognitive processing is compromised as a function of the extent of atrophy in hippocampal subregions, such that the greater the damage, the more likely it is that surrounding cortical areas will be recruited to rescue the putative functions of the damaged subregions. Our findings document for the first time not only the extent, but also the limits of circuit reorganization occurring in the young brain after early bilateral hippocampal damage.

neuroscience↗

bioRxiv2023

A Generative Model of Memory Construction and Consolidation

Episodic memories are (re)constructed, combining unique features with familiar schemas, share neural substrates with imagination, and show schema-based distortions that increase with consolidation. Here we present a computational model in which hippocampal replay (from an autoassociative network) trains generative models (variational autoencoders) in neo-cortex to (re)create sensory experiences via latent variable representations in entorhinal, medial prefrontal, and anterolateral temporal cortices. Simulations show effects of memory age and hippocampal lesions in agreement with previous models, but also provide mechanisms for se-mantic memory, imagination, episodic future thinking, relational inference, and schema-based distortions including boundary extension. The model explains how unique sensory and predict-able conceptual or schematic elements of memories are stored and reconstructed by efficiently combining both hippocampal and neocortical systems, optimising the use of limited hippocam-pal storage for new and unusual information. Overall, we believe hippocampal replay training neocortical generative models provides a comprehensive account of memory construction, ima-gination and consolidation.

neuroscience↗

bioRxiv2022

Firing rate adaptation in continuous attractor neural networks accounts for theta phase shift of hippocampal place cells

Hippocampal place cells in freely moving rodents display both theta phase precession and procession, which is thought to play important roles in cognition, but the neural mechanism for producing theta phase shift remains largely unknown. Here we show that firing rate adaptation within a continuous attractor neural network causes the neural activity bump to oscillate around the external input, resembling theta sweeps of decoded position during locomotion. These forward and backward sweeps naturally account for theta phase precession and procession of individual neurons, respectively. By tuning the adaptation strength, our model explains the difference between "bimodal cells" showing interleaved phase precession and procession, and "unimodal cells" in which phase precession predominates. Our model also explains the constant cycling of theta sweeps along different arms in a T-maze environment, the speed modulation of place cells firing frequency, and the continued phase shift after transient silencing of the hippocampus. We hope that this study will aid an understanding of the neural mechanism supporting theta phase coding in the brain.

neuroscience↗

bioRxiv2022

A probabilistic successor representation for context-dependent prediction

The different strategies that animals use for predicting reward are often classified as model-based or model-free reinforcement learning (RL) algorithms. Model-based RL involves explicit simulation the future to make decisions while model-free strategies rely on learning associations between stimuli and predicted reward by trial and error. An alternative, intermediate strategy for RL is based on the "successor representation" (SR), an encoding of environmental states in terms of predicted future states. A recent theoretical proposal suggests that the hippocampus encodes the SR in order to facilitate prediction of future reward. However, this proposal does not take into account how learning should adapt under uncertainty and switches of context. Here, we introduce a theory of learning SRs using prediction errors which includes optimally balancing uncertainty in new observations versus existing knowledge. We then generalise that approach to a multi-context setting, allowing the model to learn and maintain multiple task-specific SRs and infer which one to use at any moment based on the accuracy of its predictions. Thus, the context used for predictions can be determined by both the contents of the states themselves and the distribution of transitions between them. This probabilistic SR model captures animal behaviour in tasks which require contextual memory and generalisation, and unifies previous SR theory with hippocampal-dependent contextual decision making.

animal behavior and cognition↗

bioRxiv2021

Ripple Band Phase Precession of Place Cell Firing during Replay

Phase coding offers several theoretical advantages for information transmission compared to an equivalent rate code. Phase coding is shown by place cells in the rodent hippocampal formation, which fire at progressively earlier phases of the movement related 6-12Hz theta rhythm as their spatial receptive fields are traversed. Importantly, however, phase coding is independent of carrier frequency, and so we asked whether it might also be exhibited by place cells during 150-250Hz ripple band activity, when they are thought to replay information to neocortex. We demonstrate that place cells which fire multiple spikes during candidate replay events do so at progressively earlier ripple phases, and that spikes fired across all replay events exhibit a negative relationship between decoded location within the firing field and ripple phase. These results provide insights into the mechanisms underlying phase coding and place cell replay, as well as the neural code propagated to downstream neurons.

neuroscience↗

bioRxiv2020

Replay as structural inference in the hippocampal-entorhinal system

Model-based decision making relies on the construction of an accurate representation of the underlying state-space, and localization of ones current state within it. One way to localize is to recognize the state with which incoming sensory observations have been previously associated. Another is to update a previous state estimate given a known transition. In practice, both strategies are subject to uncertainty and must be balanced with respect to their relative confidences; robust learning requires aligning the predictions of both models over historic observations. Here, we propose a dual-systems account of the hippocampal-entorhinal system, where sensory prediction errors between these models during online exploration of state space initiate offline probabilistic inference. Offline inference computes a metric embedding on grid cells of an associative place graph encoded in the recurrent connections between place cells, achieved by message passing between cells representing non-local states. We provide testable explanations for coordinated place and grid cell replay as efficient message passing, and for distortions, partial rescaling and direction-dependent offsets in grid patterns as the confidence weighted balancing of model priors, and distortions to grid patterns as reflecting inhomogeneous sensory inputs across states. Author SummaryO_LIMinimising prediction errors between transition and sensory input (observation) models predicts partial rescaling and direction-dependent offsets in grid cell firing patterns. C_LIO_LIInhomogeneous sensory inputs predict distortions of grid firing patterns during online localisation, and local changes of grid scale during offline inference. C_LIO_LIPrincipled information propagation during offline inference predicts coordinated place and grid cell replay, where sequences propagate between structurally related features. C_LI

animal behavior and cognition↗

bioRxiv2019

The importance of Indigenous Peoples lands for the conservation of terrestrial vertebrates

Indigenous Peoples lands cover over one-quarter of the Earths surface, a significant proportion of which is still free from industrial-level human impacts. As a result, Indigenous Peoples lands are crucial for the long-term persistence of Earths biodiversity and ecosystem services. Yet, information on species composition within Indigenous Peoples lands globally remains unknown. Here, we provide the first comprehensive analysis of terrestrial vertebrate composition across mapped Indigenous lands by using distribution range data for 20,328 IUCN-assessed mammal, bird and amphibian species. We estimate that 12,521 species (62%) have [≥]10% of their ranges in Indigenous Peoples lands, and 3,314 species (16%) have >half of their ranges within these lands. For threatened species assessed, 1,878 (41.5% of all threatened of all threatened mammals, birds and amphibians) occur in Indigenous Peoples lands. We also find that 3,989 species (of which 418 are threatened) have [≥]10% of their range in Indigenous Peoples lands that have low human pressure. Our results are conservative because not all known Indigenous lands are mapped, and this analysis shows how important Indigenous Peoples lands are for the successful implementation of international conservation and sustainable development agendas.

ecology↗

bioRxiv2019

The Tolman-Eichenbaum Machine: Unifying space and relational memory through generalisation in the hippocampal formation

The hippocampal-entorhinal system is important for spatial and relational memory tasks. We formally link these domains; provide a mechanistic understanding of the hippocampal role in generalisation; and offer unifying principles underlying many entorhinal and hippocampal cell-types. We propose medial entorhinal cells form a basis describing structural knowledge, and hippocampal cells link this basis with sensory representations. Adopting these principles, we introduce the Tolman-Eichenbaum machine (TEM). After learning, TEM entorhinal cells include grid, band, border and object-vector cells. Hippocampal cells include place and landmark cells, remapping between environments. Crucially, TEM also predicts empirically recorded representations in complex non-spatial tasks. TEM predicts hippocampal remapping is not random as previously believed. Rather structural knowledge is preserved across environments. We confirm this in simultaneously recorded place and grid cells.\n\nOne Sentence SummarySimple principles of representation and generalisation unify spatial and non-spatial accounts of hippocampus and explain many cell representations.

neuroscience↗

bioRxiv2019

Evaluating the relationships between the legal and illegal international wildlife trades

The international legal trade in wildlife can provide economic and other benefits, but when unsustainable can be a driver of population declines. This impact is enhanced by the additional burden of illegal trade. We combined law-enforcement time-series of seizures of wildlife goods imported into the United States (US) and the European Union (EU) with data on reported legal trade to evaluate the evidence for any relationships. Our analysis examined 28 (US) and 20 (EU) taxon-products with high volume and frequency of reported trade and seizures. On average, seizures added 28% and 9% to US and EU reported legal trade levels respectively, and in several cases exceeded legal imports. We detected a significant but weak overall positive relationship between seizure volumes and reported trade imported to the US over time, but none in the EU. Our findings suggest a complex and nuanced temporal association between the illegal and legal wildlife trades.

ecology↗

bioRxiv2019

Theta power and theta-gamma coupling support spatial memory retrieval

Hippocampal theta oscillations have been implicated in spatial memory function in both rodents and humans. What is less clear is how hippocampal theta interacts with higher frequency oscillations during spatial memory function, and how this relates to subsequent behaviour. Here we asked ten human epilepsy patients undergoing intracranial EEG recording to perform a desk-top virtual reality spatial memory task, and found that increased theta power in two discrete bands ( low 2-5Hz and high 6-9Hz) during cued retrieval was associated with improved task performance. Similarly, increased coupling between low theta phase and gamma amplitude during the same period was associated with improved task performance. These results support a role of theta oscillations and theta-gamma phase-amplitude coupling in human spatial memory function.

neuroscience↗

bioRxiv2019

Altered Hippocampal-Prefrontal Neural Dynamics in Mouse Models of Down Syndrome

Altered neural dynamics in medial prefrontal cortex (mPFC) and hippocampus may contribute to cognitive impairments in the complex chromosomal disorder, Down Syndrome (DS). Here, we demonstrate non-overlapping behavioural differences associated with distinct abnormalities in hippocampal and mPFC electrophysiology during a canonical spatial memory task in three partially trisomic mouse models of DS (Dp1Tyb, Dp10Yey, Dp17Yey) that together cover all regions of homology with human chromosome 21 (Hsa21). Dp1Tyb mice showed slower decision-making (unrelated to the gene dose of DYRK1A, which has been implicated in DS cognitive dysfunction) and altered theta dynamics (reduced frequency, increased hippocampal-mPFC coherence, increased modulation of hippocampal high gamma); Dp10Yey mice showed impaired alternation performance and reduced theta modulation of hippocampal low gamma; while Dp17Yey mice were no different from wildtype mice. These results link specific hippocampal and mPFC circuit dysfunctions to cognitive deficits in DS models and, importantly, map them to discrete regions of Hsa21.

neuroscience↗

bioRxiv2019

Neural dynamics indicate parallel integration of environmental and self-motion information by place and grid cells.

Place cells and grid cells in the hippocampal formation are thought to integrate sensory and self-motion information into a representation of estimated spatial location, but the precise mechanism is unknown. We simulated a parallel attractor system in which place cells form an attractor network driven by environmental inputs and grid cells form an attractor network performing path integration driven by self-motion, with inter-connections between them allowing both types of input to influence firing in both ensembles. We show that such a system is needed to explain the spatial patterns and temporal dynamics of place cell firing when rats run on a linear track in which the familiar correspondence between environmental and self-motion inputs is changed (Gothard et al., 1996b; Redish et al., 2000). In contrast, the alternative architecture of a single recurrent network of place cells (performing path integration and receiving environmental inputs) cannot reproduce the place cell firing dynamics. These results support the hypothesis that grid and place cells provide two different but complementary attractor representations (based on self-motion and environmental sensory inputs respectively). Our results also indicate the specific neural mechanism and main predictors of hippocampal map realignment and make predictions for future studies.

neuroscience↗

bioRxiv2018

Differentiation of mild cognitive impairment using an entorhinal cortex-based test of VR navigation

The entorhinal cortex is one of the first regions to exhibit neurodegeneration in Alzheimers disease, and as such identification of entorhinal cortex dysfunction may aid detection of the disease in its earliest stages. Extensive evidence demonstrates that the entorhinal cortex is critically implicated in navigation underpinned by the firing of spatially modulated neurons. This study tested the hypothesis that entorhinal-dependent navigation is impaired in pre-dementia Alzheimers disease.\n\nForty-five patients with mild cognitive impairment (26 with CSF Alzheimers disease biomarker data: 12 biomarker-positive and 14 biomarker-negative) and 41 healthy control participants undertook an immersive virtual reality path integration test, as a measure of entorhinal-dependent navigation. Behavioural performance was correlated with MRI measures of entorhinal cortex volume, and the classification accuracy of the path integration task was compared with a battery of cognitive tests considered sensitive and specific for early Alzheimers Disease.\n\nBiomarker-positive patients exhibited larger errors in the navigation task than biomarker-negative patients, whose performance did not significantly differ from controls participants. Path-integration errors were negatively correlated with the volumes of the total entorhinal cortex and of its posteromedial subdivision. The path integration task demonstrated higher diagnostic sensitivity and specificity for differentiating biomarker positive versus negative patients (area under the curve = 0.90) than was achieved by the best of the cognitive tests (area under the curve = 0.57).\n\nThis study demonstrates that an entorhinal cortex-based virtual reality navigation task can differentiate patients with mild cognitive impairment at low and high risk of developing dementia, with classification accuracy superior to reference cognitive tests considered to be highly sensitive to early Alzheimers disease. This study provides evidence that navigation tasks may aid early diagnosis of Alzheimers disease, and the basis of this in animal cellular and behavioural studies provides the opportunity to answer the unmet need for translatable outcome measures for comparing treatment effect across preclinical and clinical trial phases of future anti-Alzheimers drugs.

neuroscience↗

bioRxiv2018

Neural competitive queuing of ordinal structure underlies skilled sequential action

The fluent retrieval and production of movement sequences is essential for a variety of daily activities such as speech, tool-use, musical and athletic performance, but the neural mechanisms underlying sequence planning remain elusive. Here, participants learned sequences of finger presses with different timings and different finger orders, and reproduced them in a magneto-encephalography (MEG) scanner. We classified the MEG patterns immediately preceding each press in the sequence, and examined their dynamics over the production of the whole sequence. Our results confirm a role for the competitive queuing of upcoming action representations in the production of learned motor sequences, extending previous computational and non-human primate recording studies to non-invasive measures in humans. In addition, we show that competitive queuing does not simply reflect specific motor actions, but representations of higher-level sequential order that generalise across different motor sequences. Finally, we show that the quality of competitive queuing predicts participants production accuracy, and originates from parahippocampal and cerebellar sources. These results suggest that the brain learns and produces multiple behavioural sequences by flexibly combining representations of specific actions with more abstract, parallel representations of sequential structure.

neuroscience↗

bioRxiv2018

Two Sides of the Same Coin: The Hippocampus as a Common Neural Substrate for Model-Based Planning and Spatial Memory

Little is known about the neural mechanisms that allow humans and animals to plan actions using knowledge of task contingencies. Emerging theories hypothesize that it involves the same hippocampal mechanisms that support self-localization and memory for locations. Yet, there is limited direct evidence for the link between model-based planning and the hippocampal place map. We addressed this by investigating model-based planning and place memory in healthy controls and epilepsy patients treated using unilateral anterior temporal lobectomy with hippocampal resection. We found that both functions were impaired in the patient group. Specifically, the planning impairment was related to right hippocampal lesion size, controlling for overall lesion size. Furthermore, planning and place memory covaried with one another, but only in neurologically intact controls, consistent with both functions relying on the same structure in the healthy brain. These findings clarify the scope of hippocampal contributions to behavior and the neural mechanism of model-based planning.

neuroscience↗