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Dive into the research topics where Caswell Barry is active.

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Featured researches published by Caswell Barry.


Nature | 2010

Evidence for grid cells in a human memory network

Christian F. Doeller; Caswell Barry; Neil Burgess

Grid cells in the entorhinal cortex of freely moving rats provide a strikingly periodic representation of self-location which is indicative of very specific computational mechanisms. However, the existence of grid cells in humans and their distribution throughout the brain are unknown. Here we show that the preferred firing directions of directionally modulated grid cells in rat entorhinal cortex are aligned with the grids, and that the spatial organization of grid-cell firing is more strongly apparent at faster than slower running speeds. Because the grids are also aligned with each other, we predicted a macroscopic signal visible to functional magnetic resonance imaging (fMRI) in humans. We then looked for this signal as participants explored a virtual reality environment, mimicking the rats’ foraging task: fMRI activation and adaptation showing a speed-modulated six-fold rotational symmetry in running direction. The signal was found in a network of entorhinal/subicular, posterior and medial parietal, lateral temporal and medial prefrontal areas. The effect was strongest in right entorhinal cortex, and the coherence of the directional signal across entorhinal cortex correlated with spatial memory performance. Our study illustrates the potential power of combining single-unit electrophysiology with fMRI in systems neuroscience. Our results provide evidence for grid-cell-like representations in humans, and implicate a specific type of neural representation in a network of regions which supports spatial cognition and also autobiographical memory.


Hippocampus | 2008

Grid Cells and Theta as Oscillatory Interference: Electrophysiological Data From Freely Moving Rats

Ali Jeewajee; Caswell Barry; John O'Keefe; Neil Burgess

The oscillatory interference model (Burgess et al. ( 2007 ) Hippocampus 17:801–812) explains the generation of spatially stable, regular firing patterns by medial entorhinal cortical (mEC) grid cells in terms of the interference between velocity‐controlled oscillators (VCOs) with different preferred directions. This model predicts specific relationships between the intrinsic firing frequency and spatial scale of grid cell firing, the EEG theta frequency, and running speed (Burgess, 2008 ). Here, we use spectral analyses of EEG and of spike autocorrelograms to estimate the intrinsic firing frequency of grid cells, and the concurrent theta frequency, in mEC Layer II in freely moving rats. The intrinsic firing frequency of grid cells increased with running speed and decreased with grid scale, according to the quantitative prediction of the model. Similarly, theta frequency increased with running speed, which was also predicted by the model. An alternative Moiré interference model (Blair et al., 2007 ) predicts a direction‐dependent variation in intrinsic firing frequency, which was not found. Our results suggest that interference between VCOs generates the spatial firing patterns of entorhinal grid cells according to the oscillatory interference model. They also provide specific constraints on this model of grid cell firing and have more general implications for viewing neuronal processing in terms of interfering oscillatory processes.


Proceedings of the National Academy of Sciences of the United States of America | 2012

Grid cell firing patterns signal environmental novelty by expansion

Caswell Barry; Ginzberg Ll; John O'Keefe; Neil Burgess

The hippocampal formation plays key roles in representing an animal’s location and in detecting environmental novelty to create or update those representations. However, the mechanisms behind this latter function are unclear. Here, we show that environmental novelty causes the spatial firing patterns of grid cells to expand in scale and reduce in regularity, reverting to their familiar scale as the environment becomes familiar. Simultaneously recorded place cell firing fields remapped and showed a smaller, temporary expansion. Grid expansion provides a potential mechanism for novelty signaling and may enhance the formation of new hippocampal representations, whereas the subsequent slow reduction in scale provides a potential familiarity signal.


Nature | 2015

Grid cell symmetry is shaped by environmental geometry

Julija Krupic; Marius Bauza; Stephen Burton; Caswell Barry; John O'Keefe

Grid cells represent an animal’s location by firing in multiple fields arranged in a striking hexagonal array. Such an impressive and constant regularity prompted suggestions that grid cells represent a universal and environmental-invariant metric for navigation. Originally the properties of grid patterns were believed to be independent of the shape of the environment and this notion has dominated almost all theoretical grid cell models. However, several studies indicate that environmental boundaries influence grid firing, though the strength, nature and longevity of this effect is unclear. Here we show that grid orientation, scale, symmetry and homogeneity are strongly and permanently affected by environmental geometry. We found that grid patterns orient to the walls of polarized enclosures such as squares, but not circles. Furthermore, the hexagonal grid symmetry is permanently broken in highly polarized environments such as trapezoids, the pattern being more elliptical and less homogeneous. Our results provide compelling evidence for the idea that environmental boundaries compete with the internal organization of the grid cell system to drive grid firing. Notably, grid cell activity is more local than previously thought and as a consequence cannot provide a universal spatial metric in all environments.


Nature Neuroscience | 2013

Specific evidence of low-dimensional continuous attractor dynamics in grid cells

KiJung Yoon; Michael A Buice; Caswell Barry; Robin Hayman; Neil Burgess; Ila Fiete

We examined simultaneously recorded spikes from multiple rat grid cells, to explain mechanisms underlying their activity. Among grid cells with similar spatial periods, the population activity was confined to lie close to a two-dimensional (2D) manifold: grid cells differed only along two dimensions of their responses and otherwise were nearly identical. Relationships between cell pairs were conserved despite extensive deformations of single-neuron responses. Results from novel environments suggest such structure is not inherited from hippocampal or external sensory inputs. Across conditions, cell-cell relationships are better conserved than responses of single cells. Finally, the system is continually subject to perturbations that, were the 2D manifold not attractive, would drive the system to inhabit a different region of state space than observed. These findings have strong implications for theories of grid-cell activity and substantiate the general hypothesis that the brain computes using low-dimensional continuous attractors.


Trends in Neurosciences | 2014

What do grid cells contribute to place cell firing

Daniel Bush; Caswell Barry; Neil Burgess

Highlights • It is commonly assumed that grid cell inputs generate hippocampal place fields, but recent empirical evidence brings this assumption into doubt.• We suggest that place fields are primarily determined by environmental sensory inputs.• Grid cells provide a complementary path integration input and large-scale spatial metric.• Place and grid cell representations interact to support accurate coding of large-scale space.


eLife | 2015

Hippocampal place cells construct reward related sequences through unexplored space.

H. Freyja Ólafsdóttir; Caswell Barry; Aman B Saleem; Demis Hassabis; Hugo J. Spiers

Dominant theories of hippocampal function propose that place cell representations are formed during an animals first encounter with a novel environment and are subsequently replayed during off-line states to support consolidation and future behaviour. Here we report that viewing the delivery of food to an unvisited portion of an environment leads to off-line pre-activation of place cells sequences corresponding to that space. Such ‘preplay’ was not observed for an unrewarded but otherwise similar portion of the environment. These results suggest that a hippocampal representation of a visible, yet unexplored environment can be formed if the environment is of motivational relevance to the animal. We hypothesise such goal-biased preplay may support preparation for future experiences in novel environments. DOI: http://dx.doi.org/10.7554/eLife.06063.001


Current opinion in behavioral sciences | 2015

Neural systems supporting navigation

Hugo J. Spiers; Caswell Barry

Much is known about how neural systems determine current spatial position and orientation in the environment. By contrast little is understood about how the brain represents future goal locations or computes the distance and direction to such goals. Recent electrophysiology, computational modelling and neuroimaging research have shed new light on how the spatial relationship to a goal may be determined and represented during navigation. This research suggests that the hippocampus may code the path to the goal while the entorhinal cortex represents the vector to the goal. It also reveals that the engagement of the hippocampus and entorhinal cortex varies across the different operational stages of navigation, such as during travel, route planning, and decision-making at waypoints.


Neuron | 2015

Using Grid Cells for Navigation

Daniel Bush; Caswell Barry; Daniel Manson; Neil Burgess

Summary Mammals are able to navigate to hidden goal locations by direct routes that may traverse previously unvisited terrain. Empirical evidence suggests that this “vector navigation” relies on an internal representation of space provided by the hippocampal formation. The periodic spatial firing patterns of grid cells in the hippocampal formation offer a compact combinatorial code for location within large-scale space. Here, we consider the computational problem of how to determine the vector between start and goal locations encoded by the firing of grid cells when this vector may be much longer than the largest grid scale. First, we present an algorithmic solution to the problem, inspired by the Fourier shift theorem. Second, we describe several potential neural network implementations of this solution that combine efficiency of search and biological plausibility. Finally, we discuss the empirical predictions of these implementations and their relationship to the anatomy and electrophysiology of the hippocampal formation.


Current Biology | 2015

Grid Cells Form a Global Representation of Connected Environments.

Francis Carpenter; Daniel Manson; Kate Jeffery; Neil Burgess; Caswell Barry

Summary The firing patterns of grid cells in medial entorhinal cortex (mEC) and associated brain areas form triangular arrays that tessellate the environment [1, 2] and maintain constant spatial offsets to each other between environments [3, 4]. These cells are thought to provide an efficient metric for navigation in large-scale space [5–8]. However, an accurate and universal metric requires grid cell firing patterns to uniformly cover the space to be navigated, in contrast to recent demonstrations that environmental features such as boundaries can distort [9–11] and fragment [12] grid patterns. To establish whether grid firing is determined by local environmental cues, or provides a coherent global representation, we recorded mEC grid cells in rats foraging in an environment containing two perceptually identical compartments connected via a corridor. During initial exposures to the multicompartment environment, grid firing patterns were dominated by local environmental cues, replicating between the two compartments. However, with prolonged experience, grid cell firing patterns formed a single, continuous representation that spanned both compartments. Thus, we provide the first evidence that in a complex environment, grid cell firing can form the coherent global pattern necessary for them to act as a metric capable of supporting large-scale spatial navigation.

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Neil Burgess

University College London

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Christian F. Doeller

Norwegian University of Science and Technology

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Daniel Bush

University College London

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John O'Keefe

University College London

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Kate Jeffery

University College London

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Robin Hayman

University College London

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Daniel Manson

University College London

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Ali Jeewajee

University College London

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