Biology subjects

Huszar, R.

Publications and source records attributed to Huszar, R..

7 recordsLinked to original sources

bioRxiv2025

From labels to latents: revealing state-dependent hippocampal computations with Jump Latent Variable Model

Neural activity is usually interpreted by imposing external labels (e.g., stimuli or position during locomotion) and decoding within that space (e.g. replay). While powerful, such supervision can mask structure in the data that do not correspond to the label. Unsupervised methods, in turn, often assume smooth latent dynamics and miss genuine discontinuities. We introduce a conceptually simple, computationally efficient latent variable model that infers both (i) the latent variables organizing population activity and (ii) whether their dynamics are continuous or fragmented in time. Fitting reduces to an expectation-maximization (EM) procedure that alternates two operations familiar to systems neuroscience--tuning-curve estimation and label decoding--without requiring external labels. Applied to rodent hippocampal spike recordings, the model reveals distinct population patterns at the same physical position that supervised spatial decoding fails to detect. While learned latents exhibit place-field-like tuning, their reactivation patterns are better distinguished by behavioral states. The model further identifies a continuity-fragmentation axis that characterizes population activities across sleep-wake brain states that is modulated by cholinergic inputs. By not relying on externally imposed spatial labels, our approach exposes structure that supervised approaches obscure and provides a powerful tool for datasets lacking behavioral tracking.

neuroscience↗

bioRxiv2024

Perpetual step-like restructuring of hippocampal circuit dynamics

Representation of the environment by hippocampal populations is known to drift even within a familiar environment, which could reflect gradual changes in single cell activity or result from averaging across discrete switches of single neurons. Disambiguating these possibilities is crucial, as they each imply distinct mechanisms. Leveraging change point detection and model comparison, we found that CA1 population vectors decorrelated gradually within a session. In contrast, individual neurons exhibited predominantly step-like emergence and disappearance of place fields or sustained change in within-field firing. The changes were not restricted to particular parts of the maze or trials and did not require apparent behavioral changes. The same place fields emerged, disappeared, and reappeared across days, suggesting that the hippocampus reuses pre-existing assemblies, rather than forming new fields de novo. Our results suggest an internally-driven perpetual step-like reorganization of the neuronal assemblies.

neuroscience↗

bioRxiv2023

Selection of experience for memory by hippocampal sharp wave ripples

A general wisdom is that experiences need to be tagged during learning for further consolidation. However, brain mechanisms that select experiences for lasting memory are not known. Combining large-scale neural recordings with a novel application of dimensionality reduction techniques, we observed that successive traversals in the maze were tracked by continuously drifting populations of neurons, providing neuronal signatures of both places visited and events encountered (trial number). When the brain state changed during reward consumption, sharp wave ripples (SPW-Rs) occurred on some trials and their unique spike content most often decoded the trial in which they occurred. In turn, during post-experience sleep, SPW-Rs continued to replay those trials that were reactivated most frequently during awake SPW-Rs. These findings suggest that replay content of awake SPW-Rs provides a tagging mechanism to select aspects of experience that are preserved and consolidated for future use.

neuroscience↗

bioRxiv2023

ThermoMaze: A behavioral paradigm for readout of immobility-related brain events

Brain states fluctuate between exploratory and consummatory phases of behavior. These state changes affect both internal computation and the organisms responses to sensory inputs. Understanding neuronal mechanisms supporting exploratory and consummatory states and their switching requires experimental control of behavioral shifts and collecting sufficient amounts of brain data. To achieve this goal, we developed the ThermoMaze, which exploits the animals natural warmth-seeking homeostatic behavior. By decreasing the floor temperature and selectively heating unmarked areas, mice avoid the aversive state by exploring the maze and finding the warm spot. In its design, the ThermoMaze is analogous to the widely used water maze but without the inconvenience of a wet environment and, therefore, allows the collection of physiological data in many trials. We combined the ThermoMaze with electrophysiology recording, and report that spiking activity of hippocampal CA1 neurons during sharp-wave ripple events encode the position of the animal. Thus, place-specific firing is not confined to locomotion and associated theta oscillations but persist during waking immobility and sleep at the same location. The ThermoMaze will allow for detailed studies of brain correlates of immobility, preparatory-consummatory transitions and open new options for studying behavior-mediated temperature homeostasis.

neuroscience↗

bioRxiv2022

Preconfigured dynamics in the hippocampus are guided by embryonic birthdate and rate of neurogenesis

The incorporation of novel information into the hippocampal network is likely be constrained by its innate architecture and internally generated activity patterns. However, the origin, organization, and consequences of such patterns remain poorly understood. Here, we show that hippocampal network dynamics are affected by sequential neurogenesis. We birthdated CA1 pyramidal neurons with in-utero electroporation over 4 embryonic days encompassing the peak of hippocampal neurogenesis, and compared their functional features in freely moving, adult mice. Neurons of the same birthdate displayed distinct connectivity, coactivity across brain states, and assembly dynamics. Same birthdate hippocampal neurons were topographically organized, in that anatomically clustered (<500{micro}m) neurons exhibited overlapping spatial representations. Overall, the wiring and functional features of CA1 pyramidal neurons reflected a combination of birthdate and the rate of neurogenesis. These observations demonstrate that sequential neurogenesis in embryonic development shapes the preconfigured forms of adult network dynamics.

neuroscience↗

bioRxiv2021

Distinct ground state and activated state modes of spiking in forebrain neurons

Neuronal firing patterns have significant spatiotemporal variability with no agreed upon theoretical framework. Using a combined experimental and modeling approach, we found that spike interval statistics can be described by discrete modes of activity. Of these, a "ground state" (GS) mode of low-rate spiking is universal among forebrain excitatory neurons and characterized by irregular spiking at neuron-specific rates. In contrast, "activated state" (AS) modes consist of spiking at characteristic timescales and regularity that are specific to neuron populations in a given region and brain state. The majority of spiking is contributed by GS mode, while neurons can transiently switch to AS spiking in response to stimuli or in coordination with population activity patterns. We hypothesize that GS spiking serves to maintain a persistent backbone of neuronal activity while AS modes support communication functions.

neuroscience↗

bioRxiv2019

Preexisting hippocampal network dynamics constrain optogenetically induced place fields

Neuronal circuits face a fundamental tension between maintaining existing structure and changing to accommodate new information. Memory models often emphasize the need to encode novel patterns of neural activity imposed by \"bottom-up\" sensory drive. In such models, learning is achieved through synaptic alterations, a process which potentially interferes with previously stored knowledge 1-3. Alternatively, neuronal circuits generate and maintain a preconfigured stable dynamic, sometimes referred to as an attractor, manifold, or schema 4-7, with a large reservoir of patterns available for matching with novel experiences 8-13. Here, we show that incorporation of arbitrary signals is constrained by pre-existing circuit dynamics. We optogenetically stimulated small groups of hippocampal neurons as mice traversed a chosen segment of a linear track, mimicking the emergence of place fields 1,14,15, while simultaneously recording the activity of stimulated and non-stimulated neighboring cells. Stimulation of principal neurons in CA1, but less so CA3 or the dentate gyrus, induced persistent place field remapping. Novel place fields emerged in both stimulated and non-stimulated neurons, which could be predicted from sporadic firing in the new place field location and the temporal relationship to peer neurons prior to the optogenetic perturbation. Circuit modification was reflected by altered spike transmission between connected pyramidal cell - inhibitory interneuron pairs, which persisted during post-experience sleep. We hypothesize that optogenetic perturbation unmasked sub-threshold, pre-existing place fields16,17. Plasticity in recurrent/lateral inhibition may drive learning through rapid exploration of existing states.

neuroscience↗