Space, time and item coding in the lateral entorhinal cortex and the hippocampus

Episodic memory formation involves encoding information about space, items and time of an experience. In humans and animals, episodic memory formation depends on the interaction of associative areas with the hippocampus (HC) and its surrounding parahippocampal areas, in particular the entorhinal cortex (EC). The EC medial and lateral subdivisions (MEC and LEC), harbour a plethora of spatially and item modulated cell types, respectively. Thus, MEC and LEC were long considered specialised spatial and item coding centres, respectively, that conveyed this information to the HC, where it was integrated into one episodic memory. In agreement with this hypothesis, the firing of neurons in the HC is spatially modulated but is also modified by changes in contextual and item components of an environment. However, recent studies suggest that both the MEC and LEC carry out spatial and item coding, albeit the way these elements are encoded may differ. In addition, temporal coding in the hippocampus requires an intact MEC, however, the specific functional MEC cell types involved in this process are unknown. Thus, it is currently unclear how space, items and time are encoded in each of the entorhinal-hippocampal areas, and how the different entorhinal-hippocampal circuits contribute to the transmission and association of episodic memory components. In this thesis, I explored this question from three different angles: firstly, I characterized mechanisms of spatial and item coding in the LEC and in the CA1 hippocampal area; secondly, I studied the contribution of a specific MEC-to-LEC pathway to spatial and item coding in the LEC; thirdly, I evaluated whether the temporal coding process of phase precession in hippocampal neurons is dependent on a specific MEC functional cell type, namely grid cells. For this purpose, I performed and analysed in vivo electrophysiological recordings in freely moving mice subjected to a variety of experimental settings, and combined this with optogenetic tagging of neurons for circuit characterisation. The findings reported in this thesis fundamentally advance our understanding of the processes underlying episodic memory encoding in several ways. First, I found that spatial selectivity in the LEC decreases along the anteroposterior axis, and that spatially modulated neurons remap when the spatial framework changes. In addition, I describe distinct functional cell types in the LEC encoding for different object features. Importantly, spatial and object coding neurons appear to be distinct non-overlapping neuronal populations, arguing for a separate processing of items and space in the LEC. Interestingly, object coding neurons are selectively avoided by long-range GABAergic projections from MEC to LEC. In the HC, in turn, a subset of spatially modulated neurons also encode object-related information, suggesting that these two components of episodic memory are integrated, at least to some extent, in this region. These findings give experimental evidence to the episodic memory encoding process proposed by the cognitive map theory. Finally, in respect to temporal coding, I demonstrated that phase precession is intact in the HC when grid cell firing is disrupted in the MEC, indicating that this mechanism may be dependent on other MEC neurons and/or pathways. Together, these findings uncover new mechanisms of encoding and transmission of the three episodic memory components in the entorhinal-hippocampal circuits

Stimulus-invariant processing and spectrotemporal reverse correlation in primary auditory cortex

The spectrotemporal receptive field (STRF) provides a versatile and integrated, spectral and temporal, functional characterization of single cells in primary auditory cortex (AI). In this paper, we explore the origin of, and relationship between, different ways of measuring and analyzing an STRF. We demonstrate that STRFs measured using a spectrotemporally diverse array of broadband stimuli -- such as dynamic ripples, spectrotemporally white noise, and temporally orthogonal ripple combinations (TORCs) -- are very similar, confirming earlier findings that the STRF is a robust linear descriptor of the cell. We also present a new deterministic analysis framework that employs the Fourier series to describe the spectrotemporal modulations contained in the stimuli and responses. Additional insights into the STRF measurements, including the nature and interpretation of measurement errors, is presented using the Fourier transform, coupled to singular-value decomposition (SVD), and variability analyses including bootstrap. The results promote the utility of the STRF as a core functional descriptor of neurons in AI.Comment: 42 pages, 8 Figures; to appear in Journal of Computational Neuroscienc

CA1-projecting subiculum neurons facilitate object-place learning.

Recent anatomical evidence suggests a functionally significant back-projection pathway from the subiculum to the CA1. Here we show that the afferent circuitry of CA1-projecting subicular neurons is biased by inputs from CA1 inhibitory neurons and the visual cortex, but lacks input from the entorhinal cortex. Efferents of the CA1-projecting subiculum neurons also target the perirhinal cortex, an area strongly implicated in object-place learning. We identify a critical role for CA1-projecting subicular neurons in object-location learning and memory, and show that this projection modulates place-specific activity of CA1 neurons and their responses to displaced objects. Together, these experiments reveal a novel pathway by which cortical inputs, particularly those from the visual cortex, reach the hippocampal output region CA1. Our findings also implicate this circuitry in the formation of complex spatial representations and learning of object-place associations

Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands

Cortical mechanisms for tinnitus in humans /

PhD ThesisThis work sought to characterise neurochemical and neurophysiological processes underlying tinnitus in humans. The first study involved invasive brain recordings from a neurosurgical patient, along with experimental manipulation of his tinnitus, to map the cortical system underlying his tinnitus. Widespread tinnitus-linked changes in low- and high-frequency oscillations were observed, along with inter-regional and cross-frequency patterns of communication. The second and third studies compared tinnitus patients to controls matched for age, sex and hearing loss, measuring auditory cortex spontaneous oscillations (with magnetoencephalography) and neurochemical concentrations (with magnetic resonance spectroscopy) respectively. Unlike in previous studies not controlled for hearing loss, there were no group differences in oscillatory activity attributable to tinnitus. However, there was a significant correlation between gamma oscillations (>30Hz) and hearing loss in the tinnitus group, and between delta oscillations (1-4Hz) and perceived tinnitus loudness. In the neurochemical study, tinnitus patients had significantly reduced GABA concentrations compared to matched controls, and within this group there was a positive correlation between choline concentration (potentially linked to acetylcholine and/or neuronal plasticity) and both hearing loss, and subjective tinnitus intensity and distress. In light of present and previous findings, tinnitus may be best explained by a predictive coding model of perception, which was tested in the final experiment. This directly controlled the three main quantities comprising predictive coding models, and found that delta/theta/alpha oscillations (1-12Hz) encoded the precision of predictions, beta oscillations (12-30Hz) encoded changes to predictions, and gamma oscillations represented surprise (unexpectedness of stimuli based on predictions). The work concludes with a predictive coding model of tinnitus that builds upon the present findings and settles unresolved paradoxes in the literature. In this, precursor processes (in varying combinations) synergise to increase the precision associated with spontaneous activity in the auditory pathway to the point where it overrides higher predictions of ‘silence’.Medical Research Council Wellcome Trust and the National Institutes of Healt