Biology subjects

Burgess, N.

Publications and source records attributed to Burgess, N..

5 recordsLinked to original sources

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↗

bioRxiv2018

Spatial cell firing during virtual navigation of open arenas by head-restrained mice

We present a mouse virtual reality (VR) system which restrains head-movements to horizontal rotations, potentially compatible with multi-photon imaging. We show that this system allows expression of the spatial navigational behaviour and neuronal firing patterns characteristic of real open arenas (R). Place and grid, but not head-direction, cell firing had broader spatial tuning in VR than R. Theta frequency increased less with running speed in VR than in R, while firing rates increased similarly in both. Place, but not grid, cell firing was more directional in VR than R. These results suggest that the scale of grid and place cell firing patterns, and the frequency of theta, reflect translational motion inferred from both virtual (visual and proprioceptive) cues and uncontrolled static (vestibular translation and extra-maze) cues, while firing rates predominantly reflect visual and proprioceptive motion. They also suggest that omni-directional place cell firing in R reflects local-cues unavailable in VR.

neuroscience↗

bioRxiv2017

To be a Grid Cell: Shuffling procedures for determining “Gridness”

Grid cells in freely behaving mammals are defined by the strikingly regular periodic spatial distribution of their firing. The standard method of identification calculates the \"Gridness\" of the spatial firing pattern, with significance being defined relative to the 95th percentile of a null distribution of the Gridness values found after randomly permuting spike times relative to behaviour. We determined the false-positive rate by applying the method to simulated firing with irregular spatially inhomogeneity (i.e. randomly distributed Gaussian patches). We found surprisingly high false positive rates (potentially approaching 20%), which were strongly dependent on the type of Gridness measure used and the number of spatial fields in the synthetic data. This likely reflects the spatial homogeneity of the distributions of spikes after shuffling compared to the inhomogeneous synthetic data. However, false positive rates were reduced (generally below 8%), and less dependent on other factors, when an alternative spatial field shuffling method was used to generate the null Gridness distribution. For comparison, we analysed single unit recordings made using tetrodes implanted into rat medial entorhinal cortex for the purpose of finding grid cells. We found 24% of active neurons were classified as grid cells via spike shuffling and 22% via field shuffling. These results, and the potentially high false-positive rate when classifying cells with patchy but irregular firing as grid cells, indicate that the proportion of cells with regular grid-like firing patterns can be over-estimated by standard methods.

neuroscience↗

bioRxiv2017

Optimal decision making using grid cells under spatial uncertainty

Minimizing spatial uncertainty is essential for navigation, but the neural mechanisms remain elusive. Here we combine predictions of a simulated grid cell system with behavioural and fMRI measures in humans during virtual navigation. First, we showed that polarising cues produce anisotropy in motion parallax. Secondly, we simulated entorhinal grid cells in an environment with anisotropic information and found that self-location is decoded best when grid-patterns are aligned with the axis of greatest information. Thirdly, when exposing human participants to polarised virtual reality environments, we found that navigation performance is anisotropic, in line with the use of parallax. Eye movements showed that participants preferentially viewed polarising cues, which correlated with navigation performance. Finally, using fMRI we found that the orientation of grid-cell-like representations in entorhinal cortex anchored to the environmental axis of greatest parallax information, orthogonal to the polarisation axis. In sum, we demonstrate a crucial role of the entorhinal grid system in reducing uncertainty in representations of self-location and find evidence for adaptive spatial computations underlying entorhinal representations in service of optimal navigation.

neuroscience↗