Biology subjects

Burgess, N.

Publications and source records attributed to Burgess, N..

At least 19 recordsLinked to original sources

bioRxiv2026

Firing rate adaptation in grid cells produces macroscopic hexadirectional modulation

Hexadirectional modulation (HexMod) of macroscopic neural activity by movement direction is widely used to measure grid cell activity in human neuroimaging, but its neuronal origin is unclear. Two mechanisms have been proposed: conjunctive gridxdirection cells whose preferred directions align with the grid axes, and firing rate adaptation, which reduces firing when grid fields are visited in quick succession during movement along grid axes. Analysing almost 4,000 grid cells from foraging rats, we found that conjunctive cells' directional tuning was broad and unaligned with grid axes, whereas firing was reduced shortly after grid field visits, consistent with firing rate adaptation. Simulations of realistic grid cell populations demonstrate HexMod with the typical trajectories of human experiments, and show how it depends on grid scale, adaptation time constant, movement speed, and controlling for variation with location. We show firing rate adaptation provides a plausible mechanism for HexMod and a framework for relating human neuroimaging to neuronal activity.

neuroscience↗

bioRxiv2026

The limbic navigation system as a hierarchical RNN

Path-integration-trained recurrent neural networks (RNNs) can reproduce grid-like and head-direction-like representations, but most existing models rely on low-dimensional velocity inputs and do not capture the hierarchical organisation of the brain's self-localisation circuit. We introduce a hierarchical recurrent neural network (HRNN) that separately processes angular velocity and linear speed to perform simultaneous angular and positional path integration. Trained on these tasks, the HRNN generalises to longer timescales than seen during training and develops neural response properties resembling all the key cell types: angular velocity cells, head direction cells, speed cells, conjunctive and pure grid cells. The learned circuit also recovers key motifs of the navigation system, including attractor dynamics and asymmetric connectivity patterns. Perturbation analyses reveal functional information flow across the hierarchy, consistent with experimental observations. Finally, introducing theta-paced mutual inhibition between two learned angular-velocity subpopulations enables the HRNN to reproduce the bidirectional theta sweeps observed in empirical data. These results establish hierarchical task-driven RNNs as a biologically interpretable framework for linking neural representations, circuit motifs, and population dynamics in spatial navigation, while enabling targeted in silico perturbations and the generation of experimentally testable predictions.

neuroscience↗

bioRxiv2026

Human Hippocampal Theta-Gamma Phase-Amplitude Coupling Signals the Distance to Remembered Goals

In mammals, flexible navigation is believed to rely on a cognitive map of known locations supported by the hippocampus and surrounding medial temporal lobe structures. Hippocampal place cells typically exhibit spatial firing fields within a given environment. Moreover, their firing is modulated by the movement-related theta rhythm such that "theta sweeps" of place cell activity encode the trajectory towards a hidden reward location during goal-directed navigation. Here, we attempted to detect signatures of theta sweeps in the human hippocampal local field potential (LFP) recorded with intracranial EEG. Specifically, we hypothesised that sequences of locations along a planned trajectory encoded by distinct cell assemblies are associated with gamma activity at successive theta phases. To test this hypothesis, we asked N=9 patients with epilepsy to perform a spatial navigation task in desktop virtual reality while we recorded LFP signals from depth electrode contacts implanted across the medial temporal lobe. Consistent with our predictions, we found an increase in hippocampal theta-gamma phase-amplitude coupling, a decrease in gamma power, and theta phase precession of gamma activity as hidden goal locations were approached and the sequence of locations remaining to be traversed became shorter. This suggests that goal-directed hippocampal theta sweeps during navigation are reflected in LFP theta-gamma phase-amplitude coupling, and that these neural mechanisms of model-based planning are conserved across species.

neuroscience↗

bioRxiv2026

Dorsoventral gradient of theta sweeps in medial entorhinal cortex

During random foraging, the positional signal decoded from entorhinal grid cells exhibits left-right theta sweeps, alternating from one side of the heading direction to the other across successive theta cycles. Here, we report that theta sweeps are topographically organised along the dorsoventral axis of the medial entorhinal cortex, with the angular deviation from heading direction increasing gradually from dorsal (smaller scale) to ventral (larger scale) modules. This gradient coexists with a corresponding dorsoventral increase in angular deviation decoded from theta-modulated directional cells, which drive grid-cell theta sweeps. These phenomena parallel a broadening of head direction tuning and increasing occurrence of theta cycle skipping in single cell firing along the dorsoventral axis. Computational modelling demonstrates that these patterns are consistent with continuous attractor dynamics and a dorsoventral gradient in firing rate adaptation. These results highlight how theta sweeps can simultaneously represent multiple potential future locations and reveal a clear neural mechanism underlying this process.

neuroscience↗

bioRxiv2026

Fast-ripples are emergent properties of neuronal networks

Fast-ripples (250-500 Hz) have been proposed as a promising biomarker in epilepsy, but their specificity remains unclear. In particular, it is uncertain whether they reflect chance coincident neural activity or distinctly generated pathological entities. We combined in silico simulations, neuronal cultures, the intra-hippocampal kainate rat model of hippocampal epilepsy, and human microwire recordings to investigate whether fast-ripples occur more frequently than expected by the chance aggregation of action potentials. Our simulations showed that chance aggregation can generate fast-ripples and that their incidence changes depending on brain state, an observation that we confirmed in our rodent data. The likelihood of exceeding chance depended on biological system complexity and vigilance state: fast-ripples in neuronal cultures did not surpass chance levels, whereas those in awake - but not sleeping - rodents did. Similarly, the incidence of fast-ripples in awake human recordings was ~30% greater than expected by chance. As such, our findings suggest that most fast-ripples reflect stochastic network activity rather than distinctly generated pathological entities. This work does not rule out FRs as potential indicators of epileptogenic tissue, but it does challenge prevailing assumptions about their generation and specificity. Their higher prevalence in epileptogenic tissue is likely primarily due to increased excitation and/or neural synchronization, rather than peculiar abnormalities in network behavior.

neuroscience↗

bioRxiv2025

Unfolding the Black Box of Recurrent Neural Networks for Path Integration

Path integration is essential for spatial navigation. Experimental studies have identified neural correlates for path integration, but exactly how the neural system accomplishes this computation remains unresolved. Here, we adopt recurrent neural networks (RNNs) trained to perform a path integration task to explore this issue. After training, we borrow neuroscience prior knowledge and methods to unfold the black box of the trained model, including: clarifying neuron types based on their receptive fields, dissecting information flows between neuron groups by pruning their connections, and analyzing internal dynamics of neuron groups using the attractor framework. Intriguingly, we uncover a hierarchical information processing pathway embedded in the RNN model, along which velocity information of an agent is first forwarded to band cells, band and grid cells then coordinate to carry out path integration, and finally grid cells output the agent location. Inspired by the RNN-based study, we construct a neural circuit model, in which band cells form one-dimensional (1D) continuous attractor neural networks (CANNs) and serve as upstream neurons to support downstream grid cells to carry out path integration in the 2D space. Our study challenges the conventional view of considering grid cells as the principal velocity integrator, and supports a neural circuit model with the hierarchy of band and grid cells.

neuroscience↗

bioRxiv2025

Head direction cells use a head-referenced dual-axis updating rule in 3D space

Head direction (HD) cells, comprising a compass signal for the brains spatial map, may update their firing during 3D movement by using a dual axis (DA) rule that summates head rotation around a local axis and local-axis rotation around the gravity axis. To test for operation of this rule we recorded HD cell activity from rats exploring a hemispherical surface. We assessed HD cell tuning curves in either the standard horizontal reference frame or in two reference frames governed by a DA rule, with the local axis referenced to the head (DAH) or local surface (DAS). Tuning curves were best when plotted in the DAH reference frame. This confirms that the cells use a head-referenced DA rule and indicates that the relationship of the head pose to gravity in two planes, one egocentric (head-plane) and one allocentric (earth-horizontal plane), forms a component of the inputs to the HD system.

neuroscience↗

bioRxiv2025

Localized Space Coding and Phase Coding Complement Each Other to Achieve Robust and Efficient Spatial Representation

Localized space coding and phase coding are two distinct strategies responsible, respectively, for representing abstract structure and sensory observations in neural cognitive maps. In spatial representation, localized space coding is implemented by place cells in the hippocampus (HPC), while phase coding is implemented by grid cells in the medial entorhinal cortex (MEC). Both strategies have their own advantages and disadvantages, and neither of them meets the requirement of representing space robustly and efficiently in the brain. Here, we show that through reciprocal connections between HPC and MEC, place and grid cells can complement each other to overcome their respective shortcomings. Specifically, we build a coupled network model, in which a continuous attractor neural network (CANN) with position coordinate models place cells, while multiple CANNs with phase coordinates model grid cell modules with varying spacings. The reciprocal connections between place and grid cells encode the correlation prior between the sensory cues processed by HPC and MEC, respectively. Using this model, we show that: 1) place and grid cells interact to integrate sensory cues in a Bayesian manner; 2) place cells complement grid cells in coding accuracy by eliminating non-local errors of the latter; 3) grid cells complement place cells in coding efficiency by enlarging the number of environmental maps stored stably by the latter. We demonstrate that the coupled network model explains the seemingly contradictory experimental findings about the remapping phenomena of place cells when grid cells are either inactivated or depolarized. This study gives us insight into understanding how the brain employs collaborative localized and phase coding to realize both robust and efficient information representation.

neuroscience↗

bioRxiv2025

Hippocampal theta sweeps indicate goal direction

Successful spatial navigation requires rapid evaluation of potential future trajectories. Hippocampal "theta sweeps", sequential activation of place cells within individual theta cycles, exhibit predictive dynamics within the ideal timeframe to fulfill this role. However, whether these sequences simply reflect movement-related variables or afford more cognitive goal-directed planning remains unresolved. Using data from a navigation task on the "Honeycomb" maze that allows dissociation of head-, movement- and goal-direction correlates, we found that hippocampal theta sweeps exhibit robust goal-oriented directional biases, independent of movement- or head-direction. An existing model of theta sweeps, with an additional goal-oriented directional input, reproduces these findings and predicts goal-oriented theta phase precession, which we confirm empirically. Replay events during immobility-related sharp wave/ripples are also goal-directed, and therefore more aligned with theta sweeps than experience. Our findings indicate that hippocampal theta sweeps provide a neural substrate for online goal-directed spatial planning.

neuroscience↗

bioRxiv2025

Bidirectional Crosstalk Between Sleep and Pulmonary Arterial Hypertension

BackgroundPulmonary Arterial Hypertension (PAH) is a devastating cardiopulmonary disease characterized by pulmonary vascular remodeling due to vascular cells dysfunction. Among other clinical signs, emerging data suggest poor sleep quality in patients with PAH; however, how poor sleep impacts hemodynamic burden, symptom severity, and pulmonary vascular remodeling during PAH progression remains unknown. MethodsWe used two models of sleep disturbances (sleep fragmentation and chronic jet lag) and different mouse models of PAH to determine the effects of poor sleep on PAH. We carried out timepoint quantitative RT-PCR analyses to define the clock gene oscillations in human pulmonary artery smooth muscle cells (PASMCs) isolated from non-PAH and PAH patients. Bulk RNA-sequencing analysis, immunostaining, and proliferation assays were used to explore the mechanisms by which poor sleep impacts PAH. Electroencephalogram and Electromyogram recordings (EEG/EMG) were used to determine whether PAH affects sleep in mice. ResultsPoor sleep exacerbated right ventricular dysfunction, pulmonary vascular remodeling, and PAH. RNA-seq and immunostaining analyses showed that poor sleep induces lung inflammation. Inflammation affected the pulmonary vascular molecular clock to drive PASMC hyperproliferation and increased migration. SMC-specific deletion of Bmal1 protected mice from RV dysfunction, pulmonary vascular remodeling, and PAH. EEG/EMG measurements demonstrated that PAH causes poor sleep quality in mice. Lastly, we showed that improving sleep via melatonin delivery and blunting inflammation with clodronate inhibited pulmonary vascular remodeling and PAH. ConclusionsOur study demonstrates that PAH causes poor sleep which in turn induces inflammation, increases PASMC proliferation, and exacerbates PAH. This suggests that the relationship between PAH and poor sleep is a self-amplifying cycle, and that a combination of hypnotic and anti-inflammatory drugs may give PAH patients better clinical outcomes. Clinical PerspectiveO_ST_ABSWhat is New?C_ST_ABSO_LIPAH causes poor sleep quality which in turn induces lung inflammation, PASMC proliferation, and exacerbated PAH. C_LIO_LIBmal1 rhythmicity is disrupted, and its expression is increased in lungs of patients with PAH. C_LIO_LISMC-specific deletion of Bmal1 protects from PAH. C_LIO_LIImproving sleep quality and blunting inflammation attenuates PAH. C_LI What Are the Clinical Implications?O_LIBmal1 represents a promising disease-modifying agent with potential for clinical translation in the treatment of PAH. C_LIO_LIA combination of hypnotic and anti-inflammatory drugs has therapeutic potential to treat PAH. C_LI

pathology↗

bioRxiv2024

Human Hippocampal Theta Oscillations Organise Distance to Goal Coding

The rodent hippocampal local field potential is dominated by 6-12 Hz theta oscillations during active behaviour that are strongly implicated in spatial coding and memory function across species. Invasive electrophysiology in both rodents and humans has shown increases in hippocampal theta power immediately before the onset of translational movement that persists throughout subsequent motion, and the magnitude of this increase correlates with the distance subsequently travelled. Using non-invasive magnetoencephalography (MEG) and an abstract navigation task, we observed increased theta power during both spatial planning and subsequent navigation. Importantly, theta power in the right hippocampus covaried with subsequent path distance during planning, only when participants were aware of the distance to their goal. During subsequent navigation, hippocampal theta power decreased dynamically as participants approached the goal, only when they were aware of how far they still needed to travel. In addition, theta phase during navigation modulated 70-140 Hz fast gamma amplitude in the entorhinal cortex while traversing novel paths; and 30-70 Hz slow gamma amplitude in the right hippocampus while traversing previously experienced paths. In both cases, theta-gamma phase-amplitude coupling increased with proximity to the goal during navigation, consistent with the hypothesis that sequences of upcoming locations were represented by gamma bursts occurring at successive theta phases. In sum, these findings are consistent with the proposed role of hippocampal theta oscillation in flexible planning and goal-directed spatial navigation across mammalian species.

neuroscience↗

bioRxiv2024

Consolidation of sequential experience into a deep generative network explains human memory, prediction and planning

Many aspects of learning, memory, and problem solving involve interplay between episodic (hippocampal) and semantic (neocortical) systems, but the neural mechanisms supporting this are unclear. We present a computational model in which sequential experiences are encoded in hippocampus in compressed form and replayed to train a neocortical generative network. This network captures the gist of specific episodes and extracts statistical patterns that generalise to new situations, enabling efficient reconstruction of the past and prediction of the future. The two systems interact during encoding, recall and problem solving, with the hippocampus retrieving relevant episodic information into working memory as a basis for generation using the general knowledge of the neocortical network. We simulate this interaction as retrieval-augmented generation, with the addition of mechanisms to compress episodic memories into hippocampus and to consolidate them into neocortex. The model explains changes to memories over time, including schema-based distortions, and shows how episodic and semantic memory contribute to problem solving.

neuroscience↗

bioRxiv2024

Consolidation of Sequential Planning

Thriving in changing environments requires the capacity to evaluate novel courses of action1. This ability is hypothesized to depend on sequential planning via step-by-step simulations of the future 2-4, using cognitive maps or schemas of task contingencies5,6. However, it is still unclear if, how and where in the brain such flexible planning is enacted. In parallel, it is thought that consolidation transforms memory representations over time to promote adaptive behaviour7. Here, we hypothesize that consolidation strengthens cognitive maps of task contingencies used for simulation during sequential planning. To test this, we developed a novel behavioural task and a new multivariate method for analysis of magnetoencephalography (MEG) data. Using choice and reaction time data we dissociated flexible sequential planning from alternative non-sequential strategies, and identified this behaviour with robust neural markers of step-by-step simulation, localized to the anterior medial temporal lobe. Retesting a week later we showed that consolidation enhanced sequential planning and strengthened markers of sequential simulation in the prefrontal cortex, consistent with systems consolidation theory8-15. By revealing that consolidation improves future simulations for flexible planning we open up a new frontier for the investigation of the functional interactions between memory and decision-making.

neuroscience↗

bioRxiv2024

A systems model of alternating theta sweeps via firing rate adaptation

Place and grid cells provide a neural system for self-location and tend to fire in sequences within each cycle of the hippocampal theta rhythm when rodents run on a linear track. These sequences correspond to the decoded location of the animal sweeping forward from its current location ("theta sweeps"). However recent findings in open-field environments show alternating left-right theta sweeps, and propose a circuit for their generation. Here, we present a computational model of this circuit, comprising head direction cells, conjunctive grid x direction cells, and pure grid cells, based on continuous attractor dynamics, firing rate adaptation, and modulated by the medial-septal theta rhythm. Due to firing rate adaptation, the head-direction ring attractor exhibits left-right sweeps coding for internal direction, providing an input to the grid cell attractor network shifted along the internal direction, via an intermediate layer of conjunctive grid x direction cells, producing left-right sweeps of position by grid cells. Our model explains the empirical findings, including the alignment of internal position and direction sweeps and the dependence of sweep length on grid spacing. It makes predictions for thetamodulated head-direction cells, including specific relationships between theta phase precession during turning, theta skipping, anticipatory firing and directional tuning width. These predictions are verified in experimental data from anteroventral thalamus. The model also makes several predictions for the relationships between position and direction sweeps, running speed and dorsal-ventral location within the entorhinal cortex. Overall, a simple intrinsic mechanism explains the complex theta dynamics of the spatial circuit, with testable predictions.

neuroscience↗

bioRxiv2024

Dynamical Modulation of Hippocampal Replay Sequences through Firing Rate Adaptation

During periods of immobility and sleep, the hippocampus generates diverse self-sustaining sequences of "replay" activity, exhibiting stationary, diffusive, and super-diffusive dynamical patterns. However, the neural mechanisms underlying this diversity in hippocampal sequential dynamics remain largely unknown. Here, we propose such a mechanism demonstrating that modulation of firing rate adaptation in a continuous attractor model of place cells causes the emergence of different types of replay. Our model makes several key predictions. First, more diffusive replay sequences positively correlate with longer theta sequences across animals (both reflecting stronger adaptation). Second, replay diffusivity varies within an animal across behavioural states that affect adaptation (such as wake and sleep). Third, increases in neural excitability, incorporated with firing rate adaptation, reduce the step size of decoded movements within individual replay sequences. We provide new experimental evidence for all three predictions. These insights suggested that the diverse replay dynamics observed in the hippocampus can be reconciled through a simple yet effective neural mechanism, shedding light on its role in hippocampal-dependent cognitive functions and its relationship to other aspects of hippocampal electrophysiology.

neuroscience↗

bioRxiv2024

Repix: reliable, reusable, versatile chronic Neuropixels implants using minimal components

Neuropixels probes represent the state-of-the-art for high-yield electrophysiology in neuroscience: the simultaneous recording of hundreds of neurons is now routinely carried out in head-restrained animals. In contrast, neural recording in unrestrained animals, as well as recording and tracking neurons over days, remains challenging, though it is possible using chronic implants. A major challenge is the availability of simple methods that can be implemented with limited or no prior experience with Neuropixels probes, while achieving reliable, reusable, versatile high-density electrophysiology. Here we developed, deployed, and evaluated the real-world performance of Repix, a chronic implantation system that permits the repeated re-use of Neuropixels probes. The lightweight system allows implanted animals to express a full range of natural behaviors, including social behaviors. We show that Repix allows the recording of hundreds of neurons across many months, up to a year, with implants across cortical and subcortical brain regions. Probes can be reused repeatedly with stable yield. Repix has been used by 16 researchers in 10 laboratories to date, and we evaluated the real-world performance of Repix in a variety of chronic recording paradigms in both mice and rats with a combined 209 implantations. We found that the key advantage of Repix is robustness and simplicity. Adopters of Repix became proficient at five procedures on average, regardless of prior experience with in vivo electrophysiology. With the companion protocol alongside this article, the performance and user-friendliness of Repix should facilitate a wide uptake of chronic Neuropixels recordings.

neuroscience↗

bioRxiv2024

Pathologic α-Synuclein-NOD2 Interaction and RIPK2 Activation Drives Microglia-Induced Neuroinflammation in Parkinson's Disease

Pathological aggregation of -Synuclein (-Syn) and neuroinflammation are closely linked to Parkinsons disease (PD). However, the specific regulators of the neuroinflammation caused by pathological -syn remain obscure. In this study, we show that NOD2/RIPK2 signaling is a crucial regulator of neuroinflammation in PD. Pathological -syn binds to NOD2, causing self-oligomerization and complex formation with RIPK2, leading to RIPK2 ubiquitination and activation of MAPK and NF-kB. Notably, this NOD2/RIPK2 signaling is particularly active in microglia of human PD brains and the -Syn preformed fibril (-Syn PFF) mouse model. Depleting NOD2 or RIPK2 reduces neuroinflammation and protects against dopamine neuron degeneration in a pathologic -Syn mouse model by blocking the formation of neurotoxic reactive astrocytes caused by microglia activation. The discovery of NOD2/RIPK2 signaling as a key regulator of neuroinflammation in PD provides a new understanding of -Syn-driven neuroinflammation and neurodegeneration in PD and a potential new therapeutic strategy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/580982v2_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@10c010aorg.highwire.dtl.DTLVardef@1183b23org.highwire.dtl.DTLVardef@1d289dborg.highwire.dtl.DTLVardef@158b6ef_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefPathological -Synuclein (-Syn) binds to the microglial NOD2 protein, which in turn triggers NOD2/RIPK2 complex and RIPK2 phosphorylation/ubiquitination. This process activates the NF-kB/MAPK pathways, ultimately leading to neurotoxic reactive astrocyte-induced dopaminergic neurodegeneration. Depletion of RIPK2 (RIPK2 KO) or NOD2 (NOD2) protects dopamine neurons in a mouse model of Parkinsons disease (PD). These findings provide insights into -Syn-driven neuroinflammation and offer potential therapeutic strategies for PD. HighlightsNOD2/RIPK2 signaling is identified as a crucial regulator of neuroinflammation in PD. NOD2/RIPK2 signaling is highly active in microglia in human PD brains and -Syn PFF mouse models. Pathological -Syn binds to NOD2, triggering self-oligomerization and RIPK2 complex formation, leading to MAPK and NF-kB activation Genetic depletion of NOD2 or RIPK2 reduces neuroinflammation and protects dopamine neurons by blocking the formation of neurotoxic reactive astrocytes.

neuroscience↗

bioRxiv2023

Visual boundary cues, alone, can anchor place and grid cells in virtual reality

The hippocampal formation contains neurons responsive to an animals current location and orientation, which together provide the organism with a neural map of space1-3. Spatially tuned neurons rely on external landmark cues and internally generated movement information to estimate position4,5. An important class of landmark cue are the boundaries delimiting an environment, which can define place cell field position6,7 and stabilise grid cell firing8. However, the precise nature of the sensory information used by the hippocampus to detect boundaries remains unknown. Here we use 2-dimensional virtual reality (VR)9 to show that purely visual cues from the surrounding walls are both sufficient and necessary to stabilise place and grid cell responses. Unstable grid cells retain internally coherent, hexagonally arranged firing fields, but these fields drift with respect to the virtual environment over periods >5 sec. Optic flow from a virtual floor does not slow drift dynamics, emphasising the importance of boundary-related visual information. Surprisingly, place fields are more stable close to boundaries even when these are invisible. Invisible boundary locations can only be inferred from the relative movements of the animal and a reward beacon, specifically, from the mismatch between observed beacon movement and that predicted from motor output. This shows that boundary information can be detected through sensorimotor feedback. We find that subsets of place cells show allocentric directional tuning towards the beacon, with strength of tuning correlating with place field stability when boundaries are removed.

neuroscience↗