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Hasselmo, M.

Publications and source records attributed to Hasselmo, M..

6 recordsLinked to original sources

Medial septum glutamatergic neurons support speed coding and grid cell spatial stability in the medial entorhinal cortex

Successful navigation requires the integration of self-motion signals with spatial representations, yet the circuits that provide velocity information necessary for stable grid cell firing remain incompletely understood. Here, we identify medial septal (MS) glutamatergic neurons as a critical component of this pathway. Using cell-type-specific optogenetic silencing combined with in vivo electrophysiology in freely moving mice, we show that MS glutamatergic neurons support the fidelity of firing rate-based speed coding in the medial entorhinal cortex (MEC). Silencing this population reduced grid cell spatial periodicity and stability and produced distortions of grid firing fields. Silencing also reduced theta phase-locking strength in strongly theta-modulated MEC neurons. Model simulations of a hybrid oscillatory interference-continuous attractor network with reductions in speed-signal fidelity disrupted grid periodicity and reproduced features of the spatial distortions observed in vivo. Together, these findings identify a septo-entorhinal circuit that coordinates self-motion information with the spatial and temporal organization of MEC activity to maintain a stable neural representation of space.

neuroscience↗

Single and complex spikes relay distinct frequency-dependent circuit information in the hippocampus

Hippocampal neurons generate either single spikes or stereotyped bursts of spikes known as complex spikes. Although single and complex spikes co-occur in the same neuron, their contribution to information processing remains unclear. We analyzed hippocampal CA1 neurons in awake mice and in behaving rats, combining cellular membrane voltage imaging with optogenetics and extracellular recordings. We found that network-driven subthreshold membrane rhythms in the theta versus gamma frequencies preferably entrained complex versus single spikes in individual neurons. Optogenetic membrane perturbation revealed a causal link between subthreshold theta and gamma power and the initiation of complex versus single spikes. Further, single and complex spikes exhibited different place field properties and frequency-dependent coding during spatial navigation. Thus, individual hippocampal neurons do not integrate theta and gamma rhythms into a combined spike timing code, but instead, transmit frequency-specific information as distinct output modes of single versus complex spikes during spatial cognition.

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Internally Generated Time in the Rodent Hippocampus is Logarithmically Compressed

The Weber-Fechner law proposes that our perceived sensory input increases with physical input on a logarithmic scale. Hippocampal "time cells" carry a record of recent experience by firing sequentially during a circumscribed period of time after a triggering stimulus. Different cells have "time fields" at different delays up to at least tens of seconds. Past studies suggest that time cells represent a compressed timeline by demonstrating that fewer time cells fire late in the delay and their time fields are wider. This paper asks whether the compression of time cells obeys the Weber-Fechner Law. Time cells were studied with a hierarchical Bayesian model that simultaneously accounts for the firing pattern at the trial level, cell level, and population level. This procedure allows separate estimates of the within-trial receptive field width and the across-trial variability. After isolating across-trial variability, time field width increased linearly with delay. Further, the time cell population was distributed evenly along a logarithmic time axis. These findings provide strong quantitative evidence that the neural temporal representation in rodent hippocampus is logarithmically compressed and obeys a neural Weber-Fechner Law.

neuroscience↗

Consistent population activity on the scale of minutes in the mouse hippocampus

Neurons in the hippocampus fire in consistent sequence over the timescale of seconds during the delay period of some memory experiments. For longer timescales, firing of hippocampal neurons also changes slowly over minutes within experimental sessions. It was thought that these slow dynamics are caused by stochastic drift or a continuous change in the representation of the episode, rather than consistent sequences unfolding over minutes. This paper studies the consistency of contextual drift in three chronic calcium imaging recordings from the hippocampus CA1 region in mice. Computational measures of consistency show reliable sequences within experimental trials at the scale of seconds as one would expect from time cells or place cells during the trial, as well as across experimental trials on the scale of minutes within a recording session. Consistent sequences in the hippocampus are observed over a wide range of time scales, from seconds to minutes. Hippocampal activity could reflect a scale-invariant spatiotemporal context as suggested by theories of memory from cognitive psychology.

neuroscience↗

Egocentric boundary vector tuning of the retrosplenial cortex

The retrosplenial cortex is reciprocally connected with a majority of structures implicated in spatial cognition and damage to the region itself produces numerous spatial impairments. However, in many ways the retrosplenial cortex remains understudied. Here, we sought to characterize spatial correlates of neurons within the region during free exploration in two-dimensional environments. We report that a large percentage of retrosplenial cortex neurons have spatial receptive fields that are active when environmental boundaries are positioned at a specific orientation and distance relative to the animal itself. We demonstrate that this vector-based location signal is encoded in egocentric coordinates, localized to the dysgranular retrosplenial sub-region, independent of self-motion, and context invariant. Further, we identify a sub-population of neurons with this response property that are synchronized with the hippocampal theta oscillation. Accordingly, the current work identifies a robust egocentric spatial code in retrosplenial cortex that can facilitate spatial coordinate system transformations and support the anchoring, generation, and utilization of allocentric representations.

neuroscience↗

A Neural Microcircuit Model for a Scalable Scale-invariant Representation of Time

Scale-invariant timing has been observed in a wide range of behavioral experiments. The firing properties of recently described time cells provide a possible neural substrate for scale-invariant behavior. Earlier neural circuit models do not produce scale-invariant neural sequences. In this paper we present a biologically detailed network model based on an earlier mathematical algorithm. The simulations incorporate exponentially decaying persistent firing maintained by the calcium-activated nonspecific (CAN) cationic current and a network structure given by the inverse Laplace transform to generate time cells with scale-invariant firing rates. This model provides the first biologically detailed neural circuit for generating scale-invariant time cells. The circuit that implements the inverse Laplace transform merely consists of off-center/on-surround receptive fields. Critically, rescaling temporal sequences can be accomplished simply via cortical gain control (changing the slope of the f-I curve).

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