Biology subjects

Bowler, J. C.

Publications and source records attributed to Bowler, J. C..

6 recordsLinked to original sources

bioRxiv2026

Spatial and temporal representations are organized along a stable coding gradient in the medial entorhinal cortex

The medial entorhinal cortex (MEC) has classically been viewed as a spatial coding region, but growing evidence indicates that it also contains temporal representations. However, how spatial and temporal codes are organized within the MEC remains unclear. Here we recorded MEC neurons with high-density silicon probes while mice performed a MEC-dependent timing task and a virtual reality spatial navigation task in a similar head-fixed setup. We found that spatial and temporal representations were partially overlapping but systematically biased across the MEC population. Grid cells and non-grid cells with strong spatial tuning were less likely to show reliable time-locked activity during the timing task. In contrast, neurons with weaker spatial tuning more flexibly shifted their coding scheme to temporal coding during timing task. Moreover, spatial tuning strength and its negative relationship with temporal tuning were preserved in a distinct open field environment, indicating that the coding preferences of individual neurons are constrained by a stable network-level organization. Together, these findings suggest MEC is organized along a coding gradient, ranging from dedicated stable spatial coding neurons to more flexible spatial or temporal coding neurons which represent information according to cognitive demands.

neuroscience↗

bioRxiv2025

Hippocampal time cell dynamics evolve with learning to reflect cognitive demands

The hippocampus creates cognitive maps, or internal representations that reflect knowledge of the external world. Hippocampal time cells are thought to represent the temporal structure of experiences, or temporal context. However, it remains unknown whether hippocampal time cells display learning dynamics that reflect increased knowledge of the temporal relationships that define a context. To address this gap, we utilized a behavioral paradigm with a shaping curriculum that allows animals to systematically acquire knowledge of temporal structure, ultimately enabling them to perform a temporal Delayed Non-Match to Sample (tDNMS) task. We conducted two-photon calcium imaging on large populations of CA1 neurons as mice progressed through the curriculum--from their initial exposure to the task structure to their successful discrimination of context at the end of training. Time cells were present from the outset, yet their activity evolved with experience, both at the single-cell level and across the population. Notably, at key moments in the curriculum, time cell dynamics adapted to reflect whether mice generalized across contexts or discriminated between them. Our findings suggest that CA1 time cells not only represent temporal context but may also reflect the processes by which temporal relationships are utilized. Hippocampal time cells therefore serve as a cognitive map, representing temporal relationships in a manner that reflects cognitive demands.

neuroscience↗

bioRxiv2025

Structured experience shapes strategy learning and neural dynamics in the medial entorhinal cortex

Animals can solve new, complex tasks by reusing and adapting what theyve learned before. This kind of flexibility depends not just on having prior experience, but on how that experience was structured in the first place. The design of early training curriculum is especially important: poorly structured experiences can hinder abstraction and limit generalization, while carefully structured training promotes more flexible and adaptive behavior. Yet, the neural mechanisms supporting this process remain unclear. To investigate how early training shapes learning we first trained recurrent neural networks (RNNs) on variants of an odor-timing task previously used to study complex timing behavior in mice. We then tested the RNN predictions on how previous experience affects generalization using behavioral and electrophysiological recordings in mice trained on the same task using staged training sequences. RNNs and mice trained without well-structured early experience developed rigid strategies and made repeated errors. In contrast, those given more balanced early training were better able to generalize and showed similar neural activity patterns that reflected the tasks underlying temporal structure. Using dynamical systems approaches, we reveal a mechanism for this effect: networks trained with appropriately structured curricula developed distinct dynamical motifs that support the correct abstractions when complexity was increased. Networks that lacked early training or received remedial curricula developed single fixed-point solutions that failed to generalize beyond the training stimuli. Together, these findings demonstrate that it is not just the presence of prior experience, but its structure, that governs how flexible and generalizable knowledge emerges in both biological systems and computational models.

neuroscience↗

bioRxiv2023

behaviorMate: An Intranet of Things Approach for Adaptable Control of Behavioral and Navigation-Based Experiments

1Investigators conducting behavioral experiments often need precise control over the timing of the delivery of stimuli to subjects and to collect the precise times of the subsequent behavioral responses. Furthermore, investigators want fine-tuned control over how various multi-modal cues are presented. behaviorMate takes an "Intranet of Things" approach, using a networked system of hardware and software components for achieving these goals. The system outputs a file with integrated timestamp-event pairs that investigators can then format and process using their own analysis pipelines. We present an overview of the electronic components and GUI application that make up behaviorMate as well as mechanical designs for compatible experimental rigs to provide the reader with the ability to set up their own system. A wide variety of paradigms are supported, including goal-oriented learning, random foraging, and context switching. We demonstrate behaviorMates utility and reliability with a range of use cases from several published studies and benchmark tests. Finally, we present experimental validation demonstrating different modalities of hippocampal place field studies. Both treadmill with burlap belt and virtual reality with running wheel paradigms were performed to confirm the efficacy and flexibility of the approach. Previous solutions rely on proprietary systems that may have large upfront costs or present frameworks that require customized software to be developed. behaviorMate uses open-source software and a flexible configuration system to mitigate both concerns. behaviorMate has a proven record for head-fixed imaging experiments and could be easily adopted for task control in a variety of experimental situations.

neuroscience↗

bioRxiv2022

Direct Cortical Inputs to Hippocampal Area CA1 Transmit Complementary Signals for Goal-directed Navigation

The entorhinal cortex (EC) is central to the brains navigation system. Its subregions are conventionally thought to compute dichotomous representations for spatial processing: medial entorhinal cortex (MEC) provides a global spatial map, while lateral entorhinal cortex (LEC) encodes specific sensory details of experience. While local recordings of EC circuits have amassed a vast catalogue of specialized cell types that could support navigation computations in the brain, we have little direct evidence for how these signals are actually transmitted outside of the EC to its primary downstream reader, the hippocampus, which itself is critical for the formation of spatial and episodic memories. Here we exploit in vivo sub-cellular imaging to directly record from EC axon terminals as they locally innervate hippocampal area CA1, while mice performed navigational and spatial learning tasks in virtual reality. We find both distinct and overlapping representations of task, location, and context in both MEC and LEC axons. While MEC transmitted a highly location- and context-specific code, LEC inputs were strongly biased by ongoing navigational goals and reward. Surprisingly, the position of the animal could be accurately decoded from either entorhinal subregion. Our results challenge prevailing dogma on the routing of spatial and non-spatial information from the cortex to the hippocampus, indicating that cortical interactions upstream of the hippocampus are critical for combining these processing streams to support navigation and memory.

neuroscience↗

bioRxiv2021

Signatures of rapid synaptic learning in the hippocampus during novel experiences

Neurons in the hippocampus exhibit striking selectivity for specific combinations of sensory features, forming representations which are thought to subserve episodic memory. Even during a completely novel experience, ensembles of hippocampal "place cells" are rapidly configured such that the population sparsely encodes visited locations, stabilizing within minutes of the first exposure to a new environment. What cellular mechanisms enable this fast encoding of experience? Here we leverage virtual reality and large scale neural recordings to dissect the effects of novelty and experience on the dynamics of place field formation. We show that the place fields of many CA1 neurons transiently shift locations and modulate the amplitude of their activity immediately after place field formation, consistent with rapid plasticity mechanisms driven by plateau potentials and somatic burst spiking. These motifs were particularly enriched during initial exploration of a novel context and decayed with experience. Our data suggest that novelty modulates the effective learning rate in CA1, favoring burst-driven field formation to support fast synaptic updating during new experience.

neuroscience↗