publications

2025

1. Allocentric and egocentric spatial representations coexist in rodent medial entorhinal cortex

   Xiaoyang Long, Daniel Bush, Bin Deng, and 2 more authors

   Nature Communications, 2025

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   Successful navigation relies on reciprocal transformations between spatial representations in world-centered (allocentric) and self-centered (egocentric) frames of reference. The neural basis of allocentric spatial representations has been extensively investigated with grid, border, and head-direction cells in the medial entorhinal cortex (MEC) forming key components of a ‘cognitive map’. Recently, egocentric spatial representations have also been identified in several brain regions, but evidence for the coexistence of neurons encoding spatial variables in each reference frame within MEC is so far lacking. Here, we report that allocentric and egocentric spatial representations are both present in rodent MEC, with neurons in deeper layers representing the egocentric bearing and distance towards the geometric center and / or boundaries of an environment. These results demonstrate a unity of spatial coding that can guide efficient navigation and suggest that MEC may be one locus of interactions between egocentric and allocentric spatial representations in the mammalian brain.

2. Combining video telemetry and wearable MEG for naturalistic imaging

   George C. O’Neill, Robert A. Seymour, Stephanie Mellor, and 10 more authors

   Imaging Neuroscience, 2025

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   Neuroimaging studies have typically relied on rigorously controlled experimental paradigms to probe cognition, in which movement is restricted, primitive, an afterthought or merely used to indicate a subject’s choice. Whilst powerful, these paradigms do not often resemble how we behave in everyday life, so a new generation of ecologically valid experiments are being developed. Magnetoencephalography (MEG) measures neural activity by sensing extracranial magnetic fields. It has recently been transformed from a large, static imaging modality to a wearable method where participants can move freely. This makes wearable MEG systems a prime candidate for naturalistic experiments going forward. However, these experiments will also require novel methods to capture and integrate information about behaviour executed during neuroimaging, and it is not yet clear how this could be achieved. Here, we use video recordings of multi-limb dance moves, processed with open-source machine learning methods, to automatically identify time windows of interest in concurrent, wearable MEG data. In a first step, we compare a traditional, block-designed analysis of limb movements, where the times of interest are based on stimulus presentation, to an analysis pipeline based on hidden Markov model states derived from the video telemetry. Next, we show that it is possible to identify discrete modes of neuronal activity related to specific limbs and body posture by processing the participants’ choreographed movement in a dancing paradigm. This demonstrates the potential of combining video telemetry with mobile magnetoencephalography and other legacy imaging methods for future studies of complex and naturalistic behaviours.

3. Dynamic Interplay Between Wake Slow Waves and Epileptiform Discharges in the Epileptogenic Zone

   Laurent Sheybani, Umesh Vivekananda, Nishant Sinha, and 5 more authors

   Neurology, 2025

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   Background and Objectives. Outcome of epilepsy surgery remains suboptimal, calling for the identification of new, complementary biomarkers of the epileptogenic zone (EZ). Recently, we identified local wake slow waves (LoWS) as a potential regulator of network excitability that interacts with interictal epileptiform discharges (IEDs). In this study, we tested whether this interaction is associated with surgical outcome. Methods. In this retrospective study, we analyzed intracranial recordings from patients with intractable focal epilepsy who underwent surgery at the Hospital of the University of Pennsylvania. We used surgical success as an indicator that most or all of the EZ had been resected. We used linear mixed models to test whether the incidence of IEDs and LoWS, as well as their interaction, can accurately delineate the EZ in patients with successful vs poor outcome. Results. Across 55 patients (30 women, mean age ±SD: 34 ± 10 years), we found that, although IEDs were more frequent in the seizure-onset zone, their rate in resected and nonresected areas was not associated with surgical success. Indeed, neither the rate of IEDs (F [1, 52.57] = 0.070, p = 0.793) nor that of LoWS (F [1, 48.81] = 1.1032, p = 0.299) in resected vs nonresected areas differed across surgical outcomes. Next, we examined their interaction, validating our previous findings in this larger, independent cohort, by confirming that the closer the LoWS are to an IED, the lower the network excitability during the IED. Furthermore, we found that the delay from IED to the subsequent LoWS—but not the reverse—is associated with surgical outcomes (IED to LoWS: F [1, 52.17] = 5.344, p = 0.025; LoWS to IED: F [1, 52.56] = 1.038, p = 0.313), with shorter delays observed within the EZ. We confirm this using classification analyses that yielded a significant accuracy of 63% (interquartile range: 57%–69%, p < 0.0001), underscoring its potential utility as an additional biomarker of the EZ. Discussion. The temporal proximity of LoWS to a preceding IED in the resected cortex is associated with surgical outcome. This may reflect changes in the regulation of network excitability in the EZ as a form of homeostatic regulation. It raises the possibility to use this index as an additional prognostic biomarker in epilepsy surgery.

2024

1. Firing rate adaptation affords place cell theta sweeps, phase precession, and procession

   Tianhao Chu, Zilong Ji, Junfeng Zuo, and 6 more authors

   eLife, 2024

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   Hippocampal place cells in freely moving rodents display both theta phase precession and procession, which is thought to play important roles in cognition, but the neural mechanism for producing theta phase shift remains largely unknown. Here, we show that firing rate adaptation within a continuous attractor neural network causes the neural activity bump to oscillate around the external input, resembling theta sweeps of decoded position during locomotion. These forward and backward sweeps naturally account for theta phase precession and procession of individual neurons, respectively. By tuning the adaptation strength, our model explains the difference between ‘bimodal cells’ showing interleaved phase precession and procession, and ‘unimodal cells’ in which phase precession predominates. Our model also explains the constant cycling of theta sweeps along different arms in a T-maze environment, the speed modulation of place cells’ firing frequency, and the continued phase shift after transient silencing of the hippocampus. We hope that this study will aid an understanding of the neural mechanism supporting theta phase coding in the brain.

2. Neuronal oscillations in cognition: Down syndrome as a model of mouse to human translation

   Pishan Chang, Marta Pérez-González, Jessica Constable, and 5 more authors

   The Neuroscientist, 2024

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   Down syndrome (DS), a prevalent cognitive disorder resulting from trisomy of human chromosome 21 (Hsa21), poses a significant global health concern. Affecting approximately 1 in 800 live births worldwide, DS is the leading genetic cause of intellectual disability and a major predisposing factor for early-onset Alzheimer’s dementia. The estimated global population of individuals with DS is 6 million, with increasing prevalence due to advances in DS health care. Global efforts are dedicated to unraveling the mechanisms behind the varied clinical outcomes in DS. Recent studies on DS mouse models reveal disrupted neuronal circuits, providing insights into DS pathologies. Yet, translating these findings to humans faces challenges due to limited systematic electrophysiological analyses directly comparing human and mouse. Additionally, disparities in experimental procedures between the two species pose hurdles to successful translation. This review provides a concise overview of neuronal oscillations in human and rodent cognition. Focusing on recent DS mouse model studies, we highlight disruptions in associated brain function. We discuss various electrophysiological paradigms and suggest avenues for exploring molecular dysfunctions contributing to DS-related cognitive impairments. Deciphering neuronal oscillation intricacies holds promise for targeted therapies to alleviate cognitive disabilities in DS individuals.

2023

1. Reduced grid-like theta modulation in schizophrenia

   Laura Convertino, Daniel Bush, Fanfan Zheng, and 2 more authors

   Brain, 2023

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   The hippocampal formation has been implicated in the pathophysiology of schizophrenia, with patients showing impairments in spatial and relational cognition, structural changes in entorhinal cortex and reduced theta coherence with medial prefrontal cortex. Both the entorhinal cortex and medial prefrontal cortex exhibit a 6-fold (or ‘hexadirectional’) modulation of neural activity during virtual navigation that is indicative of grid cell populations and associated with accurate spatial navigation. Here, we examined whether these grid-like patterns are disrupted in schizophrenia. We asked 17 participants with diagnoses of schizophrenia and 23 controls (matched for age, sex and IQ) to perform a virtual reality spatial navigation task during magnetoencephalography. The control group showed stronger 4–10 Hz theta power during movement onset, as well as hexadirectional modulation of theta band oscillatory activity in the right entorhinal cortex whose directional stability across trials correlated with navigational accuracy. This hexadirectional modulation was absent in schizophrenia patients, with a significant difference between groups. These results suggest that impairments in spatial and relational cognition associated with schizophrenia may arise from disrupted grid firing patterns in entorhinal cortex.

2. Cognitive impairments in a Down syndrome model with abnormal hippocampal and prefrontal dynamics and cytoarchitecture

   Phillip M Muza, Daniel Bush, Marta Pérez-González, and 8 more authors

   iScience, 2023

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   The Dp(10)2Yey mouse carries a ∼2.3-Mb intra-chromosomal duplication of mouse chromosome 10 (Mmu10) that has homology to human chromosome 21, making it an essential model for aspects of Down syndrome (DS, trisomy 21). In this study, we investigated neuronal dysfunction in the Dp(10)2Yey mouse and report spatial memory impairment and anxiety-like behavior alongside altered neural activity in the medial prefrontal cortex (mPFC) and hippocampus (HPC). Specifically, Dp(10)2Yey mice showed impaired spatial alternation associated with increased sharp-wave ripple activity in mPFC during a period of memory consolidation, and reduced mobility in a novel environment accompanied by reduced theta-gamma phase-amplitude coupling in HPC. Finally, we found alterations in the number of interneuron subtypes in mPFC and HPC that may contribute to the observed phenotypes and highlight potential approaches to ameliorate the effects of human trisomy 21.

3. Hippocampal theta activity during encoding promotes subsequent associative memory in humans

   Bárður H Joensen, Daniel Bush, Umesh Vivekananda, and 7 more authors

   Cerebral Cortex, 2023

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   Hippocampal theta oscillations have been implicated in associative memory in humans. However, findings from electrophysiological studies using scalp electroencephalography or magnetoencephalography, and those using intracranial electroencephalography are mixed. Here we asked 10 pre-surgical epilepsy patients undergoing intracranial electroencephalography recording, along with 21 participants undergoing magnetoencephalography recordings, to perform an associative memory task, and examined whether hippocampal theta activity during encoding was predictive of subsequent associative memory performance. Across the intracranial electroencephalography and magnetoencephalography studies, we observed that theta power in the hippocampus increased during encoding, and that this increase differed as a function of subsequent memory, with greater theta activity for pairs that were successfully retrieved in their entirety compared with those that were not remembered. This helps to clarify the role of theta oscillations in associative memory formation in humans, and further, demonstrates that findings in epilepsy patients undergoing intracranial electroencephalography recordings can be extended to healthy participants undergoing magnetoencephalography recordings.

4. Wake slow waves in focal human epilepsy impact network activity and cognition

   Laurent Sheybani, Umesh Vivekananda, Roman Rodionov, and 8 more authors

   Nature Communications, 2023

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   Slow waves of neuronal activity are a fundamental component of sleep that are proposed to have homeostatic and restorative functions. Despite this, their interaction with pathology is unclear and there is only indirect evidence of their presence during wakefulness. Using intracortical recordings from the temporal lobe of 25 patients with epilepsy, we demonstrate the existence of local wake slow waves (LoWS) with key features of sleep slow waves, including a down-state of neuronal firing. Consistent with a reduction in neuronal activity, LoWS were associated with slowed cognitive processing. However, we also found that LoWS showed signatures of a homeostatic relationship with interictal epileptiform discharges (IEDs): exhibiting progressive adaptation during the build-up of network excitability before an IED and reducing the impact of subsequent IEDs on network excitability. We therefore propose an “epilepsy homeostasis hypothesis”: that slow waves in epilepsy reduce aberrant activity at the price of transient cognitive impairment.

2022

1. Ripple band phase precession of place cell firing during replay

   Daniel Bush, H Freyja Olafsdottir, Caswell Barry, and 1 more author

   Current Biology, 2022

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   Neuronal “replay,” in which place cell firing during rest recapitulates recently experienced trajectories, is thought to mediate the transmission of information from hippocampus to neocortex, but the mechanism for this transmission is unknown. Here, we show that replay uses a phase code to represent spatial trajectories by the phase of firing relative to the 150- to 250-Hz “ripple” oscillations that accompany replay events. This phase code is analogous to the theta phase precession of place cell firing during navigation, in which place cells fire at progressively earlier phases of the 6- to 12-Hz theta oscillation as their place field is traversed, providing information about self-location that is additional to the rate code and a necessary precursor of replay. Thus, during replay, each ripple cycle contains a “forward sweep” of decoded locations along the recapitulated trajectory. Our results indicate a novel encoding of trajectory information during replay and implicates phase coding as a general mechanism by which the hippocampus transmits experienced and replayed sequential information to downstream targets.

2021

1. Theta power and theta-gamma coupling support long-term spatial memory retrieval

   Umesh Vivekananda, Daniel Bush, James A Bisby, and 8 more authors

   Hippocampus, 2021

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   Hippocampal theta oscillations have been implicated in spatial memory function in both rodents and humans. What is less clear is how hippocampal theta interacts with higher frequency oscillations to support long-term memory. Here we asked 10 presurgical epilepsy patients undergoing intracranial EEG recording to perform a long-term spatial memory task in desktop virtual reality and found that increased theta power in two discrete bands (“low” 2-5 Hz and “high” 6-11 Hz) during cued retrieval was associated with improved task performance. Similarly, increased coupling between “low” theta phase and gamma amplitude during the same period was associated with improved task performance. Finally, low and high gamma amplitude appeared to peak at different phases of the theta cycle; providing a novel connection between human hippocampal function and rodent data. These results help to elucidate the role of theta oscillations and theta-gamma phase-amplitude coupling in human long-term memory.

2. Model of theta frequency perturbations and contextual fear memory

   Giuseppe Castegnetti, Daniel Bush, and Dominik R Bach

   Hippocampus, 2021

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   Theta oscillations in the hippocampal local field potential (LFP) appear during translational movement and arousal, modulate the activity of principal cells, and are associated with spatial cognition and episodic memory function. All known anxiolytics slightly but consistently reduce hippocampal theta frequency. However, whether this electrophysiological effect is mechanistically related to the decreased behavioral expression of anxiety is currently unclear. Here, we propose that a reduction in theta frequency affects synaptic plasticity and mnemonic function and that this can explain the reduction in anxiety behavior. We test this hypothesis in a biophysical model of contextual fear conditioning. First, we confirm that our model reproduces previous empirical results regarding the dependence of synaptic plasticity on presynaptic firing rate. Next, we investigate how theta frequency during contextual conditioning impacts learning. These simulations demonstrate that learned associations between threat and context are attenuated when learning takes place under reduced theta frequency. Additionally, our simulations demonstrate that learned associations result in increased theta activity in the amygdala, consistent with empirical data. In summary, we propose a mechanism that can account for the behavioral effect of anxiolytics by impairing the integration of threat attributes of an environment into the cognitive map due to reduced synaptic potentiation.

3. Comparison of resting-state EEG between adults with Down syndrome and typically developing controls

   Sarah Hamburg, Daniel Bush, Andre Strydom, and 1 more author

   Journal of Neurodevelopmental Disorders, 2021

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   Background: Down syndrome (DS) is the most common genetic cause of intellectual disability (ID) worldwide. Understanding electrophysiological characteristics associated with DS provides potential mechanistic insights into ID, helping inform biomarkers and targets for intervention. Currently, electrophysiological characteristics associated with DS remain unclear due to methodological differences between studies and inadequate controls for cognitive decline as a potential cofounder. Methods: Eyes-closed resting-state EEG measures (specifically delta, theta, alpha, and beta absolute and relative powers, and alpha peak amplitude, frequency and frequency variance) in occipital and frontal regions were compared between adults with DS (with no diagnosis of dementia or evidence of cognitive decline) and typically developing (TD) matched controls (n = 25 per group). Results: We report an overall ‘slower’ EEG spectrum, characterised by higher delta and theta power, and lower alpha and beta power, for both regions in people with DS. Alpha activity in particular showed strong group differences, including lower power, lower peak amplitude and greater peak frequency variance in people with DS. Conclusions: Such EEG ‘slowing’ has previously been associated with cognitive decline in both DS and TD populations. These findings indicate the potential existence of a universal EEG signature of cognitive impairment, regardless of origin (neurodevelopmental or neurodegenerative), warranting further exploration.

2020

1. Human hippocampal theta oscillations reflect sequential dependencies during spatial planning

   Raphael Kaplan, Adria Tauste Campo, Daniel Bush, and 6 more authors

   Cognitive Neuroscience, 2020

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   Movement-related theta oscillations in rodent hippocampus coordinate ‘forward sweeps’ of location-specific neural activity that could be used to evaluate spatial trajectories online. This raises the possibility that increases in human hippocampal theta power accompany the evaluation of upcoming spatial choices. To test this hypothesis, we measured neural oscillations during a spatial planning task that closely resembles a perceptual decision-making paradigm. In this task, participants searched visually for the shortest path between a start and goal location in novel mazes that contained multiple choice points, and were subsequently asked to make a spatial decision at one of those choice points. We observed  4–8 Hz hippocampal/medial temporal lobe theta power increases specific to sequential planning that were negatively correlated with subsequent decision speed, where decision speed was inversely correlated with choice accuracy. These results implicate the hippocampal theta rhythm in decision tree search during planning in novel environments.

2. Altered hippocampal-prefrontal neural dynamics in mouse models of Down syndrome

   Pishan Chang, Daniel Bush, Stephanie Schorge, and 8 more authors

   Cell Reports, 2020

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   Altered neural dynamics in the medial prefrontal cortex (mPFC) and hippocampus may contribute to cognitive impairments in the complex chromosomal disorder Down syndrome (DS). Here, we demonstrate non-overlapping behavioral differences associated with distinct abnormalities in hippocampal and mPFC electrophysiology during a canonical spatial working memory task in three partially trisomic mouse models of DS (Dp1Tyb, Dp10Yey, and Dp17Yey) that together cover all regions of homology with human chromosome 21 (Hsa21). Dp1Tyb mice show slower decision-making (unrelated to the gene dose of DYRK1A, which has been implicated in DS cognitive dysfunction) and altered theta dynamics (reduced frequency, increased hippocampal-mPFC coherence, and increased modulation of hippocampal high gamma); Dp10Yey mice show impaired alternation performance and reduced theta modulation of hippocampal low gamma; and Dp17Yey mice are not significantly different from the wild type. These results link specific hippocampal and mPFC circuit dysfunctions to cognitive deficits in DS models and, importantly, map them to discrete regions of Hsa21.

3. Advantages and detection of phase coding in the absence of rhythmicity

   Daniel Bush, and Neil Burgess

   Hippocampus, 2020

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   The encoding of information in spike phase relative to local field potential (LFP) oscillations offers several theoretical advantages over equivalent firing rate codes. One notable example is provided by place and grid cells in the rodent hippocampal formation, which exhibit phase precession—firing at progressively earlier phases of the 6–12 Hz movement-related theta rhythm as their spatial firing fields are traversed. It is often assumed that such phase coding relies on a high amplitude baseline oscillation with relatively constant frequency. However, sustained oscillations with fixed frequency are generally absent in LFP and spike train recordings from the human brain. Hence, we examine phase coding relative to LFP signals with broadband low-frequency (2–20 Hz) power but without regular rhythmicity. We simulate a population of grid cells that exhibit phase precession against a baseline oscillation recorded from depth electrodes in human hippocampus. We show that this allows grid cell firing patterns to multiplex information about location, running speed and movement direction, alongside an arbitrary fourth variable encoded in LFP frequency. This is of particular importance given recent demonstrations that movement direction, which is essential for path integration, cannot be recovered from head direction cell firing rates. In addition, we investigate how firing phase might reduce errors in decoded location, including those arising from differences in firing rate across grid fields. Finally, we describe analytical methods that can identify phase coding in the absence of high amplitude LFP oscillations with approximately constant frequency, as in single unit recordings from the human brain and consistent with recent data from the flying bat. We note that these methods could also be used to detect phase coding outside of the spatial domain, and that multi-unit activity can substitute for the LFP signal. In summary, we demonstrate that the computational advantages offered by phase coding are not contingent on, and can be detected without, regular rhythmicity in neural activity.

4. Impaired theta phase coupling underlies frontotemporal dysconnectivity in schizophrenia

   Rick A Adams, Daniel Bush, Fanfan Zheng, and 6 more authors

   Brain, 2020

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   Frontotemporal dysconnectivity is a key pathology in schizophrenia. The specific nature of this dysconnectivity is unknown, but animal models imply dysfunctional theta phase coupling between hippocampus and medial prefrontal cortex (mPFC). We tested this hypothesis by examining neural dynamics in 18 participants with a schizophrenia diagnosis, both medicated and unmedicated; and 26 age, sex and IQ matched control subjects. All participants completed two tasks known to elicit hippocampal-prefrontal theta coupling: a spatial memory task (during magnetoencephalography) and a memory integration task. In addition, an overlapping group of 33 schizophrenia and 29 control subjects underwent PET to measure the availability of GABAARs expressing the α5 subunit (concentrated on hippocampal somatostatin interneurons). We demonstrate—in the spatial memory task, during memory recall—that theta power increases in left medial temporal lobe (mTL) are impaired in schizophrenia, as is theta phase coupling between mPFC and mTL. Importantly, the latter cannot be explained by theta power changes, head movement, antipsychotics, cannabis use, or IQ, and is not found in other frequency bands. Moreover, mPFC-mTL theta coupling correlated strongly with performance in controls, but not in subjects with schizophrenia, who were mildly impaired at the spatial memory task and no better than chance on the memory integration task. Finally, mTL regions showing reduced phase coupling in schizophrenia magnetoencephalography participants overlapped substantially with areas of diminished α5-GABAAR availability in the wider schizophrenia PET sample. These results indicate that mPFC-mTL dysconnectivity in schizophrenia is due to a loss of theta phase coupling, and imply α5-GABAARs (and the cells that express them) have a role in this process.

5. EPS mid-career prize 2018: Inference within episodic memory reflects pattern completion

   Siti Nurnadhirah Binte Mohd Ikhsan, James A Bisby, Daniel Bush, and 2 more authors

   Quarterly Journal of Experimental Psychology, 2020

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   Recollection of episodic memories is a process of reconstruction where coherent events are inferred from subsets of remembered associations. Here, we investigated the formation of multielement events from sequential presentation of overlapping pairs of elements (people, places, and objects/animals), interleaved with pairs from other events. Retrievals of paired associations from a fully observed event (e.g., AB, BC, AC) were statistically dependent, indicating a process of pattern completion, but retrievals from a partially observed event (e.g., AB, BC, CD) were not. However, inference for unseen “indirect” associations (i.e., AC, BD or AD) from a partially observed event showed strong dependency with each other and with linking direct associations from that event. In addition, inference of indirect associations correlated with the product of performance on the linking direct associations across events (e.g., AC with ABxBC) but not on the non-linking association (e.g., AC with CD). These results were seen across three experiments, with greater differences in dependency between indirect and direct associations when they were separately tested, but similar results following single and repeated presentations of the direct associations. The results could be accounted for by a simple auto-associative network model of hippocampal memory function. Our findings suggest that pattern completion supports recollection of fully observed multielement events and the inference of indirect associations in partly observed multielement events, mediated via the directly observed linking associations (although the direct associations themselves were retrieved independently). Together with previous work, our results suggest that associative inference plays a key role in reconstructive episodic memory and does so through hippocampal pattern completion.

2019

1. A mechanistic account of bodily resonance and implicit bias

   Rachel L Bedder, Daniel Bush, Domna Banakou, and 3 more authors

   Cognition, 2019

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   Implicit social biases play a critical role in shaping our attitudes towards other people. Such biases are thought to arise, in part, from a comparison between features of one’s own self-image and those of another agent, a process known as ‘bodily resonance’. Recent data have demonstrated that implicit bias can be remarkably plastic, being modulated by brief immersive virtual reality experiences that place participants in a virtual body with features of an out-group member. Here, we provide a mechanistic account of bodily resonance and implicit bias in terms of a putative self-image network that encodes associations between different features of an agent. When subsequently perceiving another agent, the output of this self-image network is proportional to the overlap between their respective features, providing an index of bodily resonance. By combining the self-image network with a drift diffusion model of decision making, we simulate performance on the implicit association test (IAT) and show that the model captures the ubiquitous implicit bias towards in-group members. We subsequently demonstrate that this implicit bias can be modulated by a simulated illusory body ownership experience, consistent with empirical data; and that the magnitude and plasticity of implicit bias correlates with self-esteem. Hence, we provide a simple mechanistic account of bodily resonance and implicit bias which could contribute to the development of interventions for reducing the negative evaluation of social out-groups.

2. Neural oscillations: phase coding in the absence of rhythmicity

   Daniel Bush, and Neil Burgess

   Current Biology, 2019

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   In the brain, coding information in the phase of neural firing relative to some baseline oscillation offers numerous theoretical advantages. New research suggests this may occur even when the baseline frequency is highly irregular, as seen in bats and humans.

3. MATLAB for Brain and Cognitive Scientists by Mike X. Cohen

   Daniel Bush

   The Quarterly Review of Biology, 2019

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4. Neural competitive queuing of ordinal structure underlies skilled sequential action

   Katja Kornysheva, Daniel Bush, Sofie S Meyer, and 3 more authors

   Neuron, 2019

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   Fluent retrieval and execution of movement sequences is essential for daily activities, but the neural mechanisms underlying sequence planning remain elusive. Here participants learned finger press sequences with different orders and timings and reproduced them in a magneto-encephalography (MEG) scanner. We classified the MEG patterns for each press in the sequence and examined pattern dynamics during preparation and production. Our results demonstrate the “competitive queuing” (CQ) of upcoming action representations, extending previous computational and non-human primate recording studies to non-invasive measures in humans. In addition, we show that CQ reflects an ordinal template that generalizes across specific motor actions at each position. Finally, we demonstrate that CQ predicts participants’ production accuracy and originates from parahippocampal and cerebellar sources. These results suggest that the brain learns and controls multiple sequences by flexibly combining representations of specific actions and interval timing with high-level, parallel representations of sequence position.

5. Altered neural odometry in the vertical dimension

   Giulio Casali, Daniel Bush, and Kate Jeffery

   Proceedings of the National Academy of Sciences, 2019

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   Entorhinal grid cells integrate sensory and self-motion inputs to provide a spatial metric of a characteristic scale. One function of this metric may be to help localize the firing fields of hippocampal place cells during formation and use of the hippocampal spatial representation (“cognitive map”). Of theoretical importance is the question of how this metric, and the resulting map, is configured in 3D space. We find here that when the body plane is vertical as rats climb a wall, grid cells produce stable, almost-circular grid-cell firing fields. This contrasts with previous findings when the body was aligned horizontally during vertical exploration, suggesting a role for the body plane in orienting the plane of the grid cell map. However, in the present experiment, the fields on the wall were fewer and larger, suggesting an altered or absent odometric (distance-measuring) process. Several physiological indices of running speed in the entorhinal cortex showed reduced gain, which may explain the enlarged grid pattern. Hippocampal place fields were found to be sparser but unchanged in size/shape. Together, these observations suggest that the orientation and scale of the grid cell map, at least on a surface, are determined by an interaction between egocentric information (the body plane) and allocentric information (the gravity axis). This may be mediated by the different sensory or locomotor information available on a vertical surface and means that the resulting map has different properties on a vertical plane than a horizontal plane (i.e., is anisotropic).

6. Spatial and episodic memory tasks promote temporal lobe interictal spikes

   Umesh Vivekananda, Daniel Bush, James A Bisby, and 6 more authors

   Annals of Neurology, 2019

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   Reflex epilepsies have been demonstrated to exploit specific networks that subserve normal physiological function. It is unclear whether more common forms of epilepsy share this particular feature. By measuring interictal spikes in patients with a range of epilepsies, we show that 2 tasks known to specifically engage the hippocampus and temporal neocortex promoted increased interictal spiking within these regions, whereas a nonhippocampal dependent task did not. This indicates that interictal spike frequency may reflect the processing demands being placed on specific functional–anatomical networks in epilepsy.

7. Spectral fingerprints or spectral tilt? Evidence for distinct oscillatory signatures of memory formation

   Marie-Christin Fellner, Stephanie Gollwitzer, Stefan Rampp, and 6 more authors

   PLoS Biology, 2019

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   Decreases in low-frequency power (2–30 Hz) alongside high-frequency power increases (>40 Hz) have been demonstrated to predict successful memory formation. Parsimoniously, this change in the frequency spectrum can be explained by one factor, a change in the tilt of the power spectrum (from steep to flat) indicating engaged brain regions. A competing view is that the change in the power spectrum contains several distinct brain oscillatory fingerprints, each serving different computations. Here, we contrast these two theories in a parallel magnetoencephalography (MEG)–intracranial electroencephalography (iEEG) study in which healthy participants and epilepsy patients, respectively, studied either familiar verbal material or unfamiliar faces. We investigated whether modulations in specific frequency bands can be dissociated in time and space and by experimental manipulation. Both MEG and iEEG data show that decreases in alpha/beta power specifically predicted the encoding of words but not faces, whereas increases in gamma power and decreases in theta power predicted memory formation irrespective of material. Critically, these different oscillatory signatures of memory encoding were evident in different brain regions. Moreover, high-frequency gamma power increases occurred significantly earlier compared to low-frequency theta power decreases. These results show that simple “spectral tilt” cannot explain common oscillatory changes and demonstrate that brain oscillations in different frequency bands serve different functions for memory encoding.

2018

1. The role of hippocampal replay in memory and planning

   H Freyja Ólafsdóttir, Daniel Bush, and Caswell Barry

   Current Biology, 2018

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   The mammalian hippocampus is important for normal memory function, particularly memory for places and events. Place cells, neurons within the hippocampus that have spatial receptive fields, represent information about an animal’s position. During periods of rest, but also during active task engagement, place cells spontaneously recapitulate past trajectories. Such ‘replay’ has been proposed as a mechanism necessary for a range of neurobiological functions, including systems memory consolidation, recall and spatial working memory, navigational planning, and reinforcement learning. Focusing mainly, but not exclusively, on work conducted in rodents, we describe the methodologies used to analyse replay and review evidence for its putative roles. We identify outstanding questions as well as apparent inconsistencies in existing data, making suggestions as to how these might be resolved. In particular, we find support for the involvement of replay in disparate processes, including the maintenance of hippocampal memories and decision making. We propose that the function of replay changes dynamically according to task demands placed on an organism and its current level of arousal.

2. Negative emotional content disrupts the coherence of episodic memories.

   James A Bisby, Aidan J Horner, Daniel Bush, and 1 more author

   Journal of Experimental Psychology: General, 2018

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   Events are thought to be stored in episodic memory as coherent representations, in which the constituent elements are bound together so that a cue can trigger reexperience of all elements via pattern completion. Negative emotional content can strongly influence memory, but opposing theories predict strengthening or weakening of memory coherence. Across a series of experiments, participants imagined a number of person-location-object events with half of the events including a negative element (e.g., an injured person), and memory was tested across all within event associations. We show that the presence of a negative element reduces memory for associations between event elements, including between neutral elements encoded after a negative element. The presence of a negative element reduces the coherence with which a multimodal event is remembered. Our results, supported by a computational model, suggest that coherent retrieval from neutral events is supported by pattern completion, but that negative content weakens associative encoding which impairs this process. Our findings have important implications for understanding the way traumatic events are encoded and support therapeutic strategies aimed at restoring associations between negative content and its surrounding context.

3. Computational models of grid cell firing

   Daniel Bush, and Christoph Schmidt-Hieber

   Hippocampal Microcircuits: A Computational Modeler’s Resource Book, 2018

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   Grid cells in the medial entorhinal cortex (mEC) fire whenever the animal enters a regular triangular array of locations that cover its environment. Since their discovery, several models that can account for these remarkably regular spatial firing patterns have been proposed. These generally fall into one of three classes, generating grid cell firing patterns either by oscillatory interference, through continuous attractor dynamics, or as a result of spatially modulated input from a place cell population. Neural network simulations have been used to explore the implications and predictions made by each class of model, while subsequent experimental data have allowed their architecture to be refined. Here, we describe implementations of two classes of grid cell model – oscillatory interference and continuous attractor dynamics – alongside a hybrid model that incorporates the principal features of each. These models are intended to be both parsimonious and make testable predictions. We discuss the strengths and weaknesses of each model and the predictions they make for future experimental manipulations of the grid cell network in vivo.

2017

1. Medial prefrontal–medial temporal theta phase coupling in dynamic spatial imagery

   Raphael Kaplan, Daniel Bush, James A Bisby, and 3 more authors

   Journal of Cognitive Neuroscience, 2017

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   Hippocampal–medial prefrontal interactions are thought to play a crucial role in mental simulation. Notably, the frontal midline/medial pFC (mPFC) theta rhythm in humans has been linked to introspective thought and working memory. In parallel, theta rhythms have been proposed to coordinate processing in the medial temporal cortex, retrosplenial cortex (RSc), and parietal cortex during the movement of viewpoint in imagery, extending their association with physical movement in rodent models. Here, we used noninvasive whole-head MEG to investigate theta oscillatory power and phase-locking during the 18-sec postencoding delay period of a spatial working memory task, in which participants imagined previously learned object sequences either on a blank background (object maintenance), from a first-person viewpoint in a scene (static imagery), or moving along a path past the objects (dynamic imagery). We found increases in 4- to 7-Hz theta power in mPFC when comparing the delay period with a preencoding baseline. We then examined whether the mPFC theta rhythm was phase-coupled with ongoing theta oscillations elsewhere in the brain. The same mPFC region showed significantly higher theta phase coupling with the posterior medial temporal lobe/RSc for dynamic imagery versus either object maintenance or static imagery. mPFC theta phase coupling was not observed with any other brain region. These results implicate oscillatory coupling between mPFC and medial temporal lobe/RSc theta rhythms in the dynamic mental exploration of imagined scenes.

2. Human hippocampal theta power indicates movement onset and distance travelled

   Daniel Bush, James A Bisby, Chris M Bird, and 6 more authors

   Proceedings of the National Academy of Sciences, 2017

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   Theta frequency oscillations in the 6- to 10-Hz range dominate the rodent hippocampal local field potential during translational movement, suggesting that theta encodes self-motion. Increases in theta power have also been identified in the human hippocampus during both real and virtual movement but appear as transient bursts in distinct high- and low-frequency bands, and it is not yet clear how these bursts relate to the sustained oscillation observed in rodents. Here, we examine depth electrode recordings from the temporal lobe of 13 presurgical epilepsy patients performing a self-paced spatial memory task in a virtual environment. In contrast to previous studies, we focus on movement-onset periods that incorporate both initial acceleration and an immediately preceding stationary interval associated with prominent theta oscillations in the rodent hippocampal formation. We demonstrate that movement-onset periods are associated with a significant increase in both low (2–5 Hz)- and high (6–9 Hz)-frequency theta power in the human hippocampus. Similar increases in low- and high-frequency theta power are seen across lateral temporal lobe recording sites and persist throughout the remainder of movement in both regions. In addition, we show that movement-related theta power is greater both before and during longer paths, directly implicating human hippocampal theta in the encoding of translational movement. These findings strengthen the connection between studies of theta-band activity in rodents and humans and offer additional insight into the neural mechanisms of spatial navigation.

2016

1. Grid-like processing of imagined navigation

   Aidan J Horner, James A Bisby, Ewa Zotow, and 2 more authors

   Current Biology, 2016

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   Grid cells in the entorhinal cortex (EC) of rodents and humans fire in a hexagonally distributed spatially periodic manner. In concert with other spatial cells in the medial temporal lobe (MTL), they provide a representation of our location within an environment and are specifically thought to allow the represented location to be updated by self-motion. Grid-like signals have been seen throughout the autobiographical memory system, suggesting a much more general role in memory. Grid cells may allow us to move our viewpoint in imagination, a useful function for goal-directed navigation and planning, and episodic future thinking more generally. We used fMRI to provide evidence for similar grid-like signals in human entorhinal cortex during both virtual navigation and imagined navigation of the same paths. We show that this signal is present in periods of active navigation and imagination, with a similar orientation in both and with the specifically 6-fold rotational symmetry characteristic of grid cell firing. We therefore provide the first evidence suggesting that grid cells are utilized during movement of viewpoint within imagery, potentially underpinning our more general ability to mentally traverse possible routes in the service of planning and episodic future thinking.

2. How environment and self-motion combine in neural representations of space

   Talfan Evans, Andrej Bicanski, Daniel Bush, and 1 more author

   The Journal of Physiology, 2016

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   Estimates of location or orientation can be constructed solely from sensory information representing environmental cues. In unfamiliar or sensory-poor environments, these estimates can also be maintained and updated by integrating self-motion information. However, the accumulation of error dictates that updated representations of heading direction and location become progressively less reliable over time, and must be corrected by environmental sensory inputs when available. Anatomical, electrophysiological and behavioural evidence indicates that angular and translational path integration contributes to the firing of head direction cells and grid cells. We discuss how sensory inputs may be combined with self-motion information in the firing patterns of these cells. For head direction cells, direct projections from egocentric sensory representations of distal cues can help to correct cumulative errors. Grid cells may benefit from sensory inputs via boundary vector cells and place cells. However, the allocentric code of boundary vector cells and place cells requires consistent head-direction information in order to translate the sensory signal of egocentric boundary distance into allocentric boundary vector cell firing, suggesting that the different spatial representations found in and around the hippocampal formation are interdependent. We conclude that, rather than representing pure path integration, the firing of head-direction cells and grid cells reflects the interface between self-motion and environmental sensory information. Together with place cells and boundary vector cells they can support a coherent unitary representation of space based on both environmental sensory inputs and path integration signals.

2015

1. Evidence for holistic episodic recollection via hippocampal pattern completion

   Aidan J Horner, James A Bisby, Daniel Bush, and 2 more authors

   Nature Communications, 2015

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   Recollection is thought to be the hallmark of episodic memory. Here we provide evidence that the hippocampus binds together the diverse elements forming an event, allowing holistic recollection via pattern completion of all elements. Participants learn complex ‘events’ from multiple overlapping pairs of elements, and are tested on all pairwise associations. At encoding, element ‘types’ (locations, people and objects/animals) produce activation in distinct neocortical regions, while hippocampal activity predicts memory performance for all within-event pairs. When retrieving a pairwise association, neocortical activity corresponding to all event elements is reinstated, including those incidental to the task. Participant’s degree of incidental reinstatement correlates with their hippocampal activity. Our results suggest that event elements, represented in distinct neocortical regions, are bound into coherent ‘event engrams’ in the hippocampus that enable episodic recollection—the re-experiencing or holistic retrieval of all aspects of an event—via a process of hippocampal pattern completion and neocortical reinstatement.

2. Using grid cells for navigation

   Daniel Bush, Caswell Barry, Daniel Manson, and 1 more author

   Neuron, 2015

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   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.

2014

1. Optimal configurations of spatial scale for grid cell firing under noise and uncertainty

   Benjamin W Towse, Caswell Barry, Daniel Bush, and 1 more author

   Philosophical Transactions of the Royal Society B: Biological Sciences, 2014

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   We examined the accuracy with which the location of an agent moving within an environment could be decoded from the simulated firing of systems of grid cells. Grid cells were modelled with Poisson spiking dynamics and organized into multiple ‘modules’ of cells, with firing patterns of similar spatial scale within modules and a wide range of spatial scales across modules. The number of grid cells per module, the spatial scaling factor between modules and the size of the environment were varied. Errors in decoded location can take two forms: small errors of precision and larger errors resulting from ambiguity in decoding periodic firing patterns. With enough cells per module (e.g. eight modules of 100 cells each) grid systems are highly robust to ambiguity errors, even over ranges much larger than the largest grid scale (e.g. over a 500 m range when the maximum grid scale is 264 cm). Results did not depend strongly on the precise organization of scales across modules (geometric, co-prime or random). However, independent spatial noise across modules, which would occur if modules receive independent spatial inputs and might increase with spatial uncertainty, dramatically degrades the performance of the grid system. This effect of spatial uncertainty can be mitigated by uniform expansion of grid scales. Thus, in the realistic regimes simulated here, the optimal overall scale for a grid system represents a trade-off between minimizing spatial uncertainty (requiring large scales) and maximizing precision (requiring small scales). Within this view, the temporary expansion of grid scales observed in novel environments may be an optimal response to increased spatial uncertainty induced by the unfamiliarity of the available spatial cues.

2. What do grid cells contribute to place cell firing?

   Daniel Bush, Caswell Barry, and Neil Burgess

   Trends in Neurosciences, 2014

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   The unitary firing fields of hippocampal place cells are commonly assumed to be generated by input from entorhinal grid cell modules with differing spatial scales. Here, we review recent research that brings this assumption into doubt. Instead, we propose that place cell spatial firing patterns are determined by environmental sensory inputs, including those representing the distance and direction to environmental boundaries, while grid cells provide a complementary self-motion related input that contributes to maintaining place cell firing. In this view, grid and place cell firing patterns are not successive stages of a processing hierarchy, but complementary and interacting representations that work in combination to support the reliable coding of large-scale space.

3. Medial prefrontal theta phase coupling during spatial memory retrieval

   Raphael Kaplan, Daniel Bush, Mathilde Bonnefond, and 4 more authors

   Hippocampus, 2014

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   Memory retrieval is believed to involve a disparate network of areas, including medial prefrontal and medial temporal cortices, but the mechanisms underlying their coordination remain elusive. One suggestion is that oscillatory coherence mediates inter-regional communication, implicating theta phase and theta-gamma phase-amplitude coupling in mnemonic function across species. To examine this hypothesis, we used non-invasive whole-head magnetoencephalography (MEG) as participants retrieved the location of objects encountered within a virtual environment. We demonstrate that, when participants are cued with the image of an object whose location they must subsequently navigate to, there is a significant increase in 4–8 Hz theta power in medial prefrontal cortex (mPFC), and the phase of this oscillation is coupled both with ongoing theta phase in the medial temporal lobe (MTL) and perceptually induced 65–85 Hz gamma amplitude in medial parietal cortex. These results suggest that theta phase coupling between mPFC and MTL and theta-gamma phase-amplitude coupling between mPFC and neocortical regions may play a role in human spatial memory retrieval.

4. A hybrid oscillatory interference/continuous attractor network model of grid cell firing

   Daniel Bush, and Neil Burgess

   Journal of Neuroscience, 2014

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   Grid cells in the rodent medial entorhinal cortex exhibit remarkably regular spatial firing patterns that tessellate all environments visited by the animal. Two theoretical mechanisms that could generate this spatially periodic activity pattern have been proposed: oscillatory interference and continuous attractor dynamics. Although a variety of evidence has been cited in support of each, some aspects of the two mechanisms are complementary, suggesting that a combined model may best account for experimental data. The oscillatory interference model proposes that the grid pattern is formed from linear interference patterns or “periodic bands” in which velocity-controlled oscillators integrate self-motion to code displacement along preferred directions. However, it also allows the use of symmetric recurrent connectivity between grid cells to provide relative stability and continuous attractor dynamics. Here, we present simulations of this type of hybrid model, demonstrate that it generates intracellular membrane potential profiles that closely match those observed in vivo, addresses several criticisms aimed at pure oscillatory interference and continuous attractor models, and provides testable predictions for future empirical studies.

2012

1. Models of grid cells and theta oscillations

   Caswell Barry, Daniel Bush, John O’Keefe, and 1 more author

   Nature, 2012

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   Grid cells recorded in the medial entorhinal cortex (MEC) of freely moving rodents show a markedly regular spatial firing pattern whose underlying mechanism has been the subject of intense interest. Yartsev et al. report that the firing of grid cells in crawling bats does not show theta rhythmicity “causally disproving a major class of computational models” of grid cell firing that rely on oscillatory interference. However, their data may be consistent with these models, with the apparent lack of theta rhythmicity reflecting slow movement speeds and low firing rates. Thus, the conclusion of Yartsev et al. is not supported by their data.

2. Recruitment of resting vesicles into recycling pools supports NMDA receptor-dependent synaptic potentiation in cultured hippocampal neurons

   Arjuna Ratnayaka, Vincenzo Marra, Daniel Bush, and 3 more authors

   The Journal of Physiology, 2012

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   Most presynaptic terminals in the central nervous system are characterized by two functionally distinct vesicle populations: a recycling pool, which supports action potential-driven neurotransmitter release via vesicle exocytosis, and a resting pool. The relative proportions of these two pools are highly variable between individual synapses, prompting speculation on their specific relationship, and on the possible functions of the resting pool. Using fluorescence imaging of FM-styryl dyes and synaptophysinI-pHluorin (sypHy) as well as correlative electron microscopy approaches, we show here that Hebbian plasticity-dependent changes in synaptic strength in rat hippocampal neurons can increase the recycling pool fraction at the expense of the resting pool in individual synaptic terminals. This recruitment process depends on NMDA-receptor activation, nitric oxide signalling and calcineurin and is accompanied by an increase in the probability of neurotransmitter release at individual terminals. Blockade of actin-mediated intersynaptic vesicle exchange does not prevent recycling pool expansion demonstrating that vesicle recruitment is intrasynaptic. We propose that the conversion of resting pool vesicles to the functionally recycling pool provides a rapid mechanism to implement long-lasting changes in presynaptic efficacy.

3. From A to Z: a potential role for grid cells in spatial navigation

   Caswell Barry, and Daniel Bush

   Neural Systems & Circuits, 2012

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   Since their discovery, the strikingly regular and spatially stable firing of entorhinal grid cells has attracted the attention of experimentalists and theoreticians alike. The bulk of this work has focused either on the assumption that the principal role of grid cells is to support path integration or the extent to which their multiple firing locations can drive the sparse activity of hippocampal place cells. Here, we propose that grid cells are best understood as part of a network that combines self-motion and environmental cues to accurately track an animal’s location in space. Furthermore, that grid cells - more so than place cells - efficiently encode self-location in allocentric coordinates. Finally, that the regular structure of grid firing fields represents information about the relative structure of space and, as such, may be used to guide goal directed navigation.

4. Calcium control of triphasic hippocampal STDP

   Daniel Bush, and Yaochu Jin

   Journal of Computational Neuroscience, 2012

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   Synaptic plasticity is believed to represent the neural correlate of mammalian learning and memory function. It has been demonstrated that changes in synaptic conductance can be induced by approximately synchronous pairings of pre- and post- synaptic action potentials delivered at low frequencies. It has also been established that NMDAr-dependent calcium influx into dendritic spines represents a critical signal for plasticity induction, and can account for this spike-timing dependent plasticity (STDP) as well as experimental data obtained using other stimulation protocols. However, subsequent empirical studies have delineated a more complex relationship between spike-timing, firing rate, stimulus duration and post-synaptic bursting in dictating changes in the conductance of hippocampal excitatory synapses. Here, we present a detailed biophysical model of single dendritic spines on a CA1 pyramidal neuron, describe the NMDAr-dependent calcium influx generated by different stimulation protocols, and construct a parsimonious model of calcium driven kinase and phosphatase dynamics that dictate the probability of stochastic transitions between binary synaptic weight states in a Markov model. We subsequently demonstrate that this approach can account for a range of empirical observations regarding the dynamics of synaptic plasticity induced by different stimulation protocols, under regimes of pharmacological blockade and metaplasticity. Finally, we highlight the strengths and weaknesses of this parsimonious, unified computational synaptic plasticity model, discuss differences between the properties of cortical and hippocampal plasticity highlighted by the experimental literature, and the manner in which further empirical and theoretical research might elucidate the cellular basis of mammalian learning and memory function.

2010

1. Reconciling the STDP and BCM models of synaptic plasticity in a spiking recurrent neural network

   Daniel Bush, Andrew Philippides, Phil Husbands, and 1 more author

   Neural Computation, 2010

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   Rate-coded Hebbian learning, as characterized by the BCM formulation, is an established computational model of synaptic plasticity. Recently it has been demonstrated that changes in the strength of synapses in vivo can also depend explicitly on the relative timing of pre- and postsynaptic firing. Computational modeling of this spike-timing-dependent plasticity (STDP) has demonstrated that it can provide inherent stability or competition based on local synaptic variables. However, it has also been demonstrated that these properties rely on synaptic weights being either depressed or unchanged by an increase in mean stochastic firing rates, which directly contradicts empirical data. Several analytical studies have addressed this apparent dichotomy and identified conditions under which distinct and disparate STDP rules can be reconciled with rate-coded Hebbian learning. The aim of this research is to verify, unify, and expand on these previous findings by manipulating each element of a standard computational STDP model in turn. This allows us to identify the conditions under which this plasticity rule can replicate experimental data obtained using both rate and temporal stimulation protocols in a spiking recurrent neural network. Our results describe how the relative scale of mean synaptic weights and their dependence on stochastic pre- or postsynaptic firing rates can be manipulated by adjusting the exact profile of the asymmetric learning window and temporal restrictions on spike pair interactions respectively. These findings imply that previously disparate models of rate-coded autoassociative learning and temporally coded heteroassociative learning, mediated by symmetric and asymmetric connections respectively, can be implemented in a single network using a single plasticity rule. However, we also demonstrate that forms of STDP that can be reconciled with rate-coded Hebbian learning do not generate inherent synaptic competition, and thus some additional mechanism is required to guarantee long-term input-output selectivity.

2. Dual coding with STDP in a spiking recurrent neural network model of the hippocampus

   Daniel Bush, Andrew Philippides, Phil Husbands, and 1 more author

   PLoS Computational Biology, 2010

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   The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal’s spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain.

3. Spike-timing dependent plasticity and the cognitive map

   Daniel Bush, Andrew Philippides, Phil Husbands, and 1 more author

   Frontiers in Computational Neuroscience, 2010

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   Since the discovery of place cells – single pyramidal neurons that encode spatial location – it has been hypothesized that the hippocampus may act as a cognitive map of known environments. This putative function has been extensively modeled using auto-associative networks, which utilize rate-coded synaptic plasticity rules in order to generate strong bi-directional connections between concurrently active place cells that encode for neighboring place fields. However, empirical studies using hippocampal cultures have demonstrated that the magnitude and direction of changes in synaptic strength can also be dictated by the relative timing of pre- and post-synaptic firing according to a spike-timing dependent plasticity (STDP) rule. Furthermore, electrophysiology studies have identified persistent “theta-coded” temporal correlations in place cell activity in vivo, characterized by phase precession of firing as the corresponding place field is traversed. It is not yet clear if STDP and theta-coded neural dynamics are compatible with cognitive map theory and previous rate-coded models of spatial learning in the hippocampus. Here, we demonstrate that an STDP rule based on empirical data obtained from the hippocampus can mediate rate-coded Hebbian learning when pre- and post-synaptic activity is stochastic and has no persistent sequence bias. We subsequently demonstrate that a spiking recurrent neural network that utilizes this STDP rule, alongside theta-coded neural activity, allows the rapid development of a cognitive map during directed or random exploration of an environment of overlapping place fields. Hence, we establish that STDP and phase precession are compatible with rate-coded models of cognitive map development.