Oscillator-interference models of path integration do not require theta oscillations

Biologically-Based Computation: How Neural Details and Dynamics Are Suited for Implementing a Variety of Algorithms

The Neural Engineering Framework (Eliasmith & Anderson, 2003) is a long-standing method for implementing high-level algorithms constrained by low-level neurobiological details. In recent years, this method has been expanded to incorporate more biological details and applied to new tasks. This paper brings together these ongoing research strands, presenting them in a common framework. We expand on the NEF's core principles of (a) specifying the desired tuning curves of neurons in different parts of the model, (b) defining the computational relationships between the values represented by the neurons in different parts of the model, and (c) finding the synaptic connection weights that will cause those computations and tuning curves. In particular, we show how to extend this to include complex spatiotemporal tuning curves, and then apply this approach to produce functional computational models of grid cells, time cells, path integration, sparse representations, probabilistic representations, and symbolic representations in the brain.

Advantages and detection of phase coding in the absence of rhythmicity

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.

Overview of computational models of hippocampus and related structures: Introduction to the special issue

Extensive computational modeling has focused on the hippocampal formation and associated cortical structures. This overview describes some of the factors that have motivated the strong focus on these structures, including major experimental findings and their impact on computational models. This overview provides a framework for describing the topics addressed by individual articles in this special issue of the journal Hippocampus.

Nonoscillatory Phase Coding and Synchronization in the Bat Hippocampal Formation

Hippocampal theta oscillations were proposed to be important for multiple functions, including memory and temporal coding of position. However, previous findings from bats have questioned these proposals by reporting absence of theta rhythmicity in bat hippocampal formation. Does this mean that temporal coding is unique to rodent hippocampus and does not generalize to other species? Here, we report that, surprisingly, bat hippocampal neurons do exhibit temporal coding similar to rodents, albeit without any continuous oscillations at the 1-20 Hz range. Bat neurons exhibited very strong locking to the non-rhythmic fluctuations of the field potential, such that neurons were synchronized together despite the absence of oscillations. Further, some neurons exhibited "phase precession" and phase coding of the bat's position-with spike phases shifting earlier as the animal moved through the place field. This demonstrates an unexpected type of neural coding in the mammalian brain-nonoscillatory phase coding-and highlights the importance of synchrony and temporal coding for hippocampal function across species.

Modulating medial septal cholinergic activity reduces medial entorhinal theta frequency without affecting speed or grid coding

Medial septal inputs to the hippocampal system are crucial for aspects of temporal and spatial processing, such as theta oscillations and grid cell firing. However, the precise contributions of the medial septum’s cholinergic neurones to these functions remain unknown. Here, we recorded neuronal firing and local field potentials from the medial entorhinal cortex of freely foraging mice, while modulating the excitability of medial septal cholinergic neurones. Alteration of cholinergic activity produced a reduction in the frequency of theta oscillations, without affecting the slope of the non-linear theta frequency vs running speed relationship observed. Modifying septal cholinergic tone in this way also led mice to exhibit behaviours associated with novelty or anxiety. However, grid cell firing patterns were unaffected, concordant with an absence of change in the slopes of the theta frequency and firing rate speed signals thought to be used by grid cells.

Human hippocampal theta power indicates movement onset and distance travelled

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.