Hippocampal theta sequences: from phenomenology to circuit mechanisms

The hippocampus is a brain structure involved in episodic memory and spatial cognition. Neuronal activity within the hippocampus exhibits intricate temporal patterning, including oscillatory and sequential dynamics, which are believed to underlie these cognitive processes. In individual cells, a temporal activity pattern called phase precession occurs which leads to the organisation of neuronal populations into sequences. These sequences are hypothesised to form a substrate for episodic memory and the representation of spatial trajectories during navigation. In this thesis, I present a novel theory of the phenomenological properties of these neuronal activity sequences. In particular, I propose that the sequential organisation of population activity is governed by the independent phase precession of each cell. By comparison of models in which cells are independent and models in which cells exhibit coordinated activity against experimental data, I provide empirical evidence to support this hypothesis. Further, I show how independent coding affords a vast capacity for the generation of sequential activity patterns across distinct environments, allowing the representation of episodes and spatial experiences across a large number of contexts. This theory is then extended to account for grid cells, whose activity patterns form a hexagonal lattice over external space. By analysing simple forms of phase coding in populations of grid cells, I show how previously undocumented constraints on phase coding in two dimensional environments are imposed by the symmetries of grid cell firing fields. To overcome these constraints, I propose a more complex phenomenological model which can account for phase precession in both place cells and grid cells in two dimensional environments. Using insights from this theory, I then propose a biophysical circuit mechanism for hippocampal sequences. I show that this biophysical circuit model can account for the proposed phenomenological coding properties and provide experimentally testable predictions which can distinguish this model from existing models of phase precession. Finally, I outline a scheme by which this biophysical mechanism can implement supervised learning using spike time dependent plasticity in order to learn associations between events occurring on behavioural timescales. The models presented in this thesis challenge previous theories of hippocampal circuit function and suggest a much higher degree of flexibility and capacity for the generation of sequences than previously believed. This flexibility may underlie our ability to represent spatial experiences and store episodic memories across a seemingly unlimited number of distinct contexts

Low Tensor Rank Learning of Neural Dynamics

Learning relies on coordinated synaptic changes in recurrently connected populations of neurons. Therefore, understanding the collective evolution of synaptic connectivity over learning is a key challenge in neuroscience and machine learning. In particular, recent work has shown that the weight matrices of task-trained RNNs are typically low rank, but how this low rank structure unfolds over learning is unknown. To address this, we investigate the rank of the 3-tensor formed by the weight matrices throughout learning. By fitting RNNs of varying rank to large-scale neural recordings during a motor learning task, we find that the inferred weights are low-tensor-rank and therefore evolve over a fixed low-dimensional subspace throughout the entire course of learning. We next validate the observation of low-tensor-rank learning on an RNN trained to solve the same task by performing a low-tensor-rank decomposition directly on the ground truth weights, and by showing that the method we applied to the data faithfully recovers this low rank structure. Finally, we present a set of mathematical results bounding the matrix and tensor ranks of gradient descent learning dynamics which show that low-tensor-rank weights emerge naturally in RNNs trained to solve low-dimensional tasks. Taken together, our findings provide novel constraints on the evolution of population connectivity over learning in both biological and artificial neural networks, and enable reverse engineering of learning-induced changes in recurrent network dynamics from large-scale neural recordings.Comment: The last two authors contributed equall

Independent theta phase coding accounts for CA1 population sequences and enables flexible remapping

Hippocampal place cells encode an animal's past, current, and future location through sequences of action potentials generated within each cycle of the network theta rhythm. These sequential representations have been suggested to result from temporally coordinated synaptic interactions within and between cell assemblies. Instead, we find through simulations and analysis of experimental data that rate and phase coding in independent neurons is sufficient to explain the organization of CA1 population activity during theta states. We show that CA1 population activity can be described as an evolving traveling wave that exhibits phase coding, rate coding, spike sequences and that generates an emergent population theta rhythm. We identify measures of global remapping and intracellular theta dynamics as critical for distinguishing mechanisms for pacemaking and coordination of sequential population activity. Our analysis suggests that, unlike synaptically coupled assemblies, independent neurons flexibly generate sequential population activity within the duration of a single theta cycle

Learning shapes cortical dynamics to enhance integration of relevant sensory input

Adaptive sensory behavior is thought to depend on processing in recurrent cortical circuits, but how dynamics in these circuits shapes the integration and transmission of sensory information is not well understood. Here, we study neural coding in recurrently connected networks of neurons driven by sensory input. We show analytically how information available in the network output varies with the alignment between feedforward input and the integrating modes of the circuit dynamics. In light of this theory, we analyzed neural population activity in the visual cortex of mice that learned to discriminate visual features. We found that over learning, slow patterns of network dynamics realigned to better integrate input relevant to the discrimination task. This realignment of network dynamics could be explained by changes in excitatory-inhibitory connectivity among neurons tuned to relevant features. These results suggest that learning tunes the temporal dynamics of cortical circuits to optimally integrate relevant sensory input

Strengthening impact assessment: a call for integration and focus

We suggest that the impact assessment community has lost its way based on our observation that impact assessment is under attack because of a perceived lack of efficiency. Specifically, we contend that the proliferation of different impact assessment types creates separate silos of expertise and feeds arguments for not only a lack of efficiency but also a lack of effectiveness of the process through excessive specialisation and a lack of interdisciplinary practice. We propose that the solution is a return to the basics of impact assessment with a call for increased integration around the goal of sustainable development and focus through better scoping. We rehearse and rebut counter arguments covering silo-based expertise, advocacy, democracy, sustainability understanding and communication. We call on the impact assessment community to rise to the challenge of increasing integration and focus, and to engage in the debate about the means of strengthening impact assessment

'Sifting the significance from the data' - the impact of high-throughput genomic technologies on human genetics and health care.

This report is of a round-table discussion held in Cardiff in September 2009 for Cesagen, a research centre within the Genomics Network of the UK's Economic and Social Research Council. The meeting was arranged to explore ideas as to the likely future course of human genomics. The achievements of genomics research were reviewed, and the likely constraints on the pace of future progress were explored. New knowledge is transforming biology and our understanding of evolution and human disease. The difficulties we face now concern the interpretation rather than the generation of new sequence data. Our understanding of gene-environment interaction is held back by our current primitive tools for measuring environmental factors, and in addition, there may be fundamental constraints on what can be known about these complex interactions.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

CO2-brine flow-through on an Utsira Sand core sample: Experimental and modelling. Implications for the Sleipner storage field

Sleipner (North Sea) is the world’s first commercial-scale carbon capture and storage (CCS) project, active since 1996, with ∼17 million tonnes of CO2 stored. The main reservoir, Utsira Sand, constitutes an ideal host formation of exceptionally high porosity-permeability and large lateral extent. However, the extensive seismic time-lapse, gravity and electromagnetic monitoring surveys deployed at Sleipner have not been well-supported by laboratory measurements. Here, we investigate the geophysical and geomechanical response of an Utsira core sample for the first time, using controlled inflation/depletion cycles at variable CO2-to-brine fractional flow rates. Ultrasonic P-wave velocities and attenuations are measured together with electrical resistivity (converted into CO2-saturation), along with continuous axial and radial strain monitoring. Ultrasonic velocity and attenuation data were simultaneously inverted and results extrapolated to field-scale seismic-frequencies using a new rock physics theory, which combines patchy fluid distribution and squirt flow effects. It provides a velocity-saturation relationship of practical importance to CO2 plume monitoring. Furthermore, by combining ultrasonic and deformation data, we report empirical relations between pore pressure changes and geomechanical effects in the reservoir, for different saturation ranges. Our dataset complements and constrains existing geophysical monitoring surveys at Sleipner and, more generally, improves the understanding of shallow weakly-cemented sand reservoirs

UK national clinical audit: Management of pregnancies in women with HIV

BACKGROUND: The potential for HIV transmission between a pregnant woman and her unborn child was first recognized in 1982. Since then a complex package of measures to reduce risk has been developed. This project aims to review UK management of HIV in pregnancy as part of the British HIV Association (BHIVA) audit programme. METHODS: The National Study of HIV in Pregnancy and Childhood (NSHPC), a population-based surveillance study, provided data for pregnancies with an expected delivery date from 1/1/13 - 30/6/14. Services also completed a survey on local management policies. Data were audited against the 2012 BHIVA pregnancy guidelines. RESULTS: During the audit period 1483 pregnancies were reported and 112 services completed the survey. Use of dedicated multidisciplinary teams was reported by 99% although 26% included neither a specialist midwife nor nurse. 17% of services reported delays >1 week for HIV specialist review of women diagnosed antenatally. Problematic urgent HIV testing had been experienced by 9% of services although in a further 49% the need for urgent testing had not arisen. Delays of >2 h in obtaining urgent results were common. Antiretroviral therapy (ART) was started during pregnancy in 37% women with >94% regimens in accordance with guidelines. Late ART initiation was common, particularly in those with a low CD4 count or high viral load. Eleven percent of services reported local policy contrary to guidelines regarding delivery mode for women with a VL <50 copies/mL at ≥36 weeks. According to NSHPC reports 27% of women virologically eligible for vaginal delivery planned to deliver by CS. CONCLUSIONS: Pregnant women in the UK are managed largely in accordance with BHIVA guidelines. Improvements are needed to ensure timely referral and ART initiation to ensure the best possible outcomes