Biology subjects

Bicanski, A.

Publications and source records attributed to Bicanski, A..

5 recordsLinked to original sources

bioRxiv2026

A Vector Navigation and Inference Architecture can Construct Universal Cognitive Maps for Abstract Reasoning

The idea of cognitive maps in the hippocampal formation has its origins in decades of spatial cognition research. However, increasing evidence points to cognitive maps also supporting non-spatial tasks. It appears that the hippocampal-entorhinal system can map any combination of systematically varying stimulus dimensions onto the same neural manifolds that support spatial representations - grid cells. Here I propose a model that shows how spatial navigation architectures can iteratively construct universal cognitive maps. The model is neurally plausible and exhibits noise-tolerance that implies specific behavioral predictions. The mapping process accommodates discontinuous stimulus spaces and the model can be used to support several types of abstract reasoning, including analogy making, subspace construction, and perspective taking. Importantly, these capabilities are supported by the same neural processes that are used to build a map. Thus, the combination of mechanisms at play suggests how spatial navigation architectures can function as domain-general substrates of cognition.

neuroscience↗

bioRxiv2025

How human aging disrupts the head direction network: evidence from VR experiments and mechanistic models

Navigational deficits during aging can severely limit mobility and reduce quality of life. While research on the underlying neural mechanisms has primarily focused on medial temporal lobe dysfunction, the head-direction (HD) system--a core component of the mammalian navigation circuit--remains largely unexplored in the context of aging. We established an immersive virtual reality paradigm that provides direct behavioral read-outs of HD signals. In addition, we developed a biologically inspired HD model, which accommodates noise sources that simulate age-related neural changes. Compared to younger adults, older participants exhibited larger angular errors, and a brief delay increased their heading uncertainty. In addition, our novel ring-attractor architecture shows that synaptic noise and small-scale neuronal loss replicate the magnitude and dynamics of the age-related deficits observed behaviorally. Together, these behavioral and computational findings provide the first evidence that aging compromises the fidelity and stability of the HD system. By pinpointing noise accumulation and neuron attrition as mechanistic contributors, our study significantly advances the understanding of spatial navigation deficits in old age, and it highlights novel targets for interventions aimed at preserving navigational abilities and quality of life.

neuroscience↗

bioRxiv2025

Dynamic updating of cognitive maps via traces of experience in the subiculum

In the classical view of hippocampal function, the subiculum is assigned the role as the output layer. In spatial paradigms, some subiculum neurons manifest as so-called boundary vector cells (BVCs), firing in response to boundaries at specific allocentric directions and distances. More recently it has been shown that some subiculum BVCs can be classified as vector trace cells (VTCs), which exhibit traces of activity after a boundary/object has been removed. Here we propose a model of processing within subiculum that accounts for VTCs, taking into account proximodistal differences in subiculum (pSub vs dSub) and CA1. dSub neurons receive feedforward input, either in the form of perceptual information (from BVCs in pSub) or mnemonic information (from place cells in CA1). Mismatch between these two inputs updates associative memory encoded in the synapses between CA1 and dSub. With a range of learning rates, the model captures the majority of experimental findings, including the distribution of VTCs along the proximodistal axis, the percentage of VTCs across different cue types, and the hours-long persistence of the vector trace. Incorporating experimentally reported effects of inserted objects/rewards on place cells (place field shift), we also explain why VTCs have longer tuning distances after cue removal. This adds predictive character to subiculum traces and suggests the online use of mnemonic content during navigation. Our model suggests that mismatch detection for updating spatial memory content provides a mechanistic explanation for findings in the CA1-subiculum pathway. This work constitutes the first dedicated circuit-level model of computation within the subiculum, consistent with known effects in CA1, and provides a potential framework to extend the canonical model of hippocampal function with a subiculum component.

neuroscience↗

bioRxiv2025

Re-enacting steps supports human path integration consistent with motor-corrected grid cell drift

Efficient navigation, especially in the absence of vision, requires path integration -- the continuous updating of spatial position from self-motion cues. However, path integration is prone to cumulative error, which can be amplified when body-derived information is inconsistent between encoding and retrieval paths. Drawing on evidence from sensorimotor reactivation during memory retrieval, we hypothesized that re-enacting encoding-related movement patterns could serve as a body-derived mechanism to counteract such errors. In a novel virtual reality task with motion tracking, participants learned unique, irregular step sequences linked to specific target distances during an encoding phase. They later reproduced these distances in complete darkness under three conditions: self-paced free retrieval, retrieval with encoding-congruent movements, and retrieval with encoding-incongruent, regular gait. During free retrieval, participants naturally re-enacted encoding-related movements associated with improved distance reproduction. As predicted, distance estimation was significantly more accurate during congruent retrieval than during incongruent retrieval. These behavioral findings are consistent with a neural network model in which retrieved encoding-related motor patterns correct path integration errors in grid cells. Together, these results provide converging behavioral and computational evidence that body-derived, encoding-related motor patterns can enhance distance estimation, possibly by filtering grid cell error accumulation, offering new insights into embodied mechanisms of path integration.

neuroscience↗

bioRxiv2024

Sensory and central contributions to motor pattern generation in a spiking, neuro-mechanical model of the salamander spinal cord

This study introduces a novel neuromechanical model employing a detailed spiking neural network to explore the role of axial proprioceptive sensory feedback, namely stretch feedback, in salamander locomotion. Unlike previous studies that often oversimplified the dynamics of the locomotor networks, our model includes detailed simulations of the classes of neurons that are considered responsible for generating movement patterns. The locomotor circuits, modeled as a spiking neural network of adaptive leaky integrate-and-fire neurons, are coupled to a three-dimensional mechanical model of a salamander with realistic physical parameters and simulated muscles. In open-loop simulations (i.e., without sensory feedback), the model replicates locomotor patterns observed in-vitro and in-vivo for swimming and trotting gaits. Additionally, a modular descending reticulospinal drive to the central pattern generation network allows to accurately control the activation, frequency and phase relationship of the different sections of the limb and axial circuits. In closed-loop swimming simulations (i.e. including axial stretch feedback), systematic evaluations reveal that intermediate values of feedback strength increase the tail beat frequency and reduce the intersegmental phase lag, contributing to a more coordinated, faster and energy-efficient locomotion. Interestingly, the result is conserved across different feedback topologies (ascending or descending, excitatory or inhibitory), suggesting that it may be an inherent property of axial proprioception. Moreover, intermediate feedback strengths expand the stability region of the network, enhancing its tolerance to a wider range of descending drives, internal parameters modifications and noise levels. Conversely, high values of feedback strength lead to a loss of controllability of the network and a degradation of its locomotor performance. Overall, this study highlights the beneficial role of proprioception in generating, modulating and stabilizing locomotion patterns, provided that it does not excessively override centrally-generated locomotor rhythms. This work also underscores the critical role of detailed, biologically-realistic neural networks to improve our understanding of vertebrate locomotion. Author summaryIn this paper, we developed a computational model to investigate how salamanders move, both while swimming and walking. Unlike previous studies that often oversimplified the dynamics of these complex neural networks, our model includes detailed simulations of the classes of neurons that are considered responsible for generating movement patterns. The locomotor circuits, modeled as a spiking neural network, are coupled to a three-dimensional mechanical model of a salamander with realistic physical parameters and simulated muscles. The neural model integrates axial proprioceptive sensory feedback from the bodys movements to modulate the locomotor gaits. Our simulations suggest that this sensory feedback plays a major role in controlling the rhythm and coordination of movements. This has implications for understanding not only how salamanders move but also provides insights into the evolution of locomotion in vertebrates. By investigating how central and sensory mechanisms interact to produce efficient and adaptable movement, our work contributes to the broader field of neuroscience and robotics, offering potential strategies for designing more effective biomimetic robots.

neuroscience↗