Biology subjects

Laurens, J.

Publications and source records attributed to Laurens, J..

14 recordsLinked to original sources

bioRxiv2026

Directionally tuned signals in mouse visual and subicular cortex during passive rotation

Head-direction (HD) cells integrate visual and vestibular inputs and provide an internal compass which is essential for navigation, but how the directional activity in the subicular complex (SUB) and in the visual cortex (VIS) depends on the visual scene has not been compared directly. Here, we recorded simultaneously from the two regions with Neuropixels probes, while rotating head-fixed mice across all azimuthal directions, in controlled visual conditions, and in darkness. We found many directionally tuned units in both SUB and VIS. The preferred directions of SUB units were distributed uniformly and followed the rotation of a single prominent visual cue. The preferred directions of VIS units on the other hand were concentrated towards the visual cue. Heading was decoded with good accuracy from population activity from either region in cue rich visual conditions. In the presence of a single cue, decoding performance was higher in VIS. In darkness, the directional tuning was apparently lost at the single cell level, in both VIS and SUB. Importantly, even in darkness, the tuning-ordered structure of pairwise correlations was largely maintained in SUB, but not in VIS. This dissociation suggests that the SUB coherence reflects an internally organized attractor that can maintain its structure without vision or active movement, whereas VIS coherence largely reflects the external sensory structure. A wave-like distortion in decoded heading with respect to a visual cue suggests that a single salient landmark can shape the HD signal. Taken together, visual and head direction signals allow for an internal compass with continuity in the absence of landmarks, and recalibration as landmarks are reinstated.

neuroscience↗

bioRxiv2025

Dynamics of thalamic directional coding under vestibular imbalance

Head direction cells (HDCs) encode the animals orientation in space and form a core component of the brains navigation system. While their dependence on vestibular input is well established, how directional circuits respond to unilateral vestibular loss (UVL) -- the most frequent and ecologically relevant form of vestibular imbalance -- remains largely unknown. UVL offers a powerful model to investigate how spatial circuits adapt to asymmetric sensory disruption and partial deafferentation. To explore this, we examined the impact of UVL on anterior thalamic nuclei (ATN) activity and spatially tuned neurons in freely moving rats following unilateral vestibular neurectomy (UVN). UVN induced long-lasting alterations in ATN firing dynamics, including reduced theta modulation, diminished burst firing, and selective disruption across functionally defined neuronal classes: head-direction and speed-modulated cells were strongly affected, while angular head velocity and position cells remained largely preserved. Despite initial degradation, HDCs persisted and progressively regained directional tuning. Crucially, spike waveform analysis revealed two distinct HDC subtypes with markedly different vulnerabilities: one subtype showed reduced prevalence and degraded tuning, whereas the other remained resilient and supported the recovery of directional coding. These findings uncover a previously unrecognized heterogeneity within the head direction system and show that compensation following UVL is partial, cell type-specific, and functionally selective. Together, they offer new insight into sensory plasticity within thalamic navigation circuits and provide a framework to understand spatial deficits associated with vestibular imbalance.

neuroscience↗

bioRxiv2025

From Exploration to Structured Navigation: Learning Dynamics of Freely Moving Marmosets during Foraging

How do structured, memory-guided behaviors emerge in freely moving primates? We addressed this question by training common marmosets to perform a foraging task in a semi-naturalistic environment, where they retrieved food from eight dispensers over multiple sessions. Animals received no instruction or shaping and were free to visit dispensers in any order. We found that animals engaged with the task in most trials and, within engaged trials, transitioned from exploratory to efficient foraging behavior. Learning was marked by performance gains and the emergence of reproducible movement patterns between specific dispensers. Using trajectory analyses and probabilistic modeling, we found that animals formed stable route segments linking specific dispensers, reflecting the emergence of local navigation motifs. These segments became increasingly regular and predictable with experience. Yet rather than being rigidly replayed, they were flexibly recombined into variable global sequences. This indicates that animals adopted a hybrid navigation strategy, in which reusable route segments are embedded within a topological structure. These findings demonstrate how efficient, adaptive navigation can emerge through self-guided experience in complex environments. Our approach provides a naturalistic and longitudinal framework for studying the formation of structured spatial strategies in non-human primates, bridging ecological behavior with theoretical models of learning and memory.

animal behavior and cognition↗

bioRxiv2022

The statistical power of three monkeys

Neuroscience studies in non-human primates (NHP) often follow the rule of thumb that results observed in one animal must be replicated in at least one other. However, we lack a statistical justification for this rule of thumb, or an analysis of whether including three or more animals is better than including two. Yet, a formal statistical framework for experiments with few subjects would be crucial for experimental design, ethical justification, and data analysis. Also, including three or four animals in a study creates the possibility that the results observed in one animal will differ from those observed in the others: we need a statistically justified rule to resolve such situations. Here, I present a statistical framework to address these issues. This framework assumes that conducting an experiment will produce a similar result for a large proportion of the population (termed representative), but will produce spurious results for a substantial proportion of animals (termed outliers); the fractions of representative and outliers animals being defined by a prior distribution. I propose a procedure in which experimenters collect results from M animals and accept results that are observed in at least N of them ( N-out-of-M procedure). I show how to compute the risks (of reaching an incorrect conclusion) and {beta} (of failing to reach a conclusion) for any prior distribution, and as a function of N and M. Strikingly, I find that the N-out-of-M model leads to a similar conclusion across a wide range of prior distributions: recordings from two animals lowers the risk and therefore ensures reliable result, but leaves a large risk {beta}; and recordings from three animals and accepting results observed in two of them strikes an efficient balance between acceptable risks and {beta}. This framework gives a formal justification for the rule of thumb of using at least two animals in NHP studies, suggests that recording from three animals when possible markedly improves statistical power, provides a statistical solution for situations where results are not consistent between all animals, and may apply to other types of studies involving few animals.

neuroscience↗

bioRxiv2021

Two functionally distinct Purkinje cell populations implement an internal model within a single olivo-cerebellar loop

Olivo-cerebellar loops, where anatomical patches of the cerebellar cortex and inferior olive project one onto the other, form an anatomical unit of cerebellar computation. Here, we investigated how successive computational steps map onto olivo-cerebellar loops. Lobules IX-X of the cerebellar vermis, i.e. the nodulus and uvula, implement an internal model of the inner ears graviceptor, the otolith organs. We have previously identified two populations of Purkinje cells that participate in this computation: Tilt-selective cells transform egocentric rotation signals into allocentric tilt velocity signals, to track head motion relative to gravity, and translation-selective cells encode otolith prediction error. Here we show that, despite very distinct simple spike response properties, both types of Purkinje cells emit complex spikes that are proportional to sensory prediction error. This indicates that both cell populations comprise a single olivo-cerebellar loop, in which only translation-selective cells project to the inferior olive. We propose a neural network model where sensory prediction errors computed by translation-selective cells are used as a teaching signal for both populations, and demonstrate that this network can learn to implement an internal model of the otoliths.

neuroscience↗

bioRxiv2020

Spatial representations in macaque hippocampal formation

The hippocampal formation is linked to spatial navigation, but there is little corroboration from freely-moving primates with concurrent monitoring of three-dimensional head and gaze stances. We recorded neurons and local field potentials across hippocampal regions in rhesus macaques during free foraging in an open environment while tracking their head and eye. Theta band activity was intermittently present at movement onset and modulated by saccades. Many cells were phase-locked to theta, with few showing theta phase precession. Most hippocampal neurons encoded a mixture of spatial variables beyond place fields and a negligible number showed prominent grid tuning. Spatial representations were dominated by facing location and allocentric direction, mostly in head, rather than gaze, coordinates. Importantly, eye movements strongly modulated neural activity in all regions. These findings reveal that the macaque hippocampal formation represents three-dimensional space using a multiplexed code, with head orientation and eye movement properties dominating over simple place and grid coding during free exploration.

neuroscience↗

bioRxiv2020

Influence of sensory modality and control dynamics on human path integration

Path integration is a sensorimotor computation that can be used to infer latent dynamical states by integrating self-motion cues. We studied the influence of sensory observation (visual/vestibular) and latent control dynamics (velocity/acceleration) on human path integration using a novel motion-cueing algorithm. Sensory modality and control dynamics were both varied randomly across trials, as participants controlled a joystick to steer to a memorized target location in virtual reality. Visual and vestibular steering cues allowed comparable accuracies only when participants controlled their acceleration, suggesting that vestibular signals, on their own, fail to support accurate path integration in the absence of sustained acceleration. Nevertheless, performance in all conditions reflected a failure to fully adapt to changes in the underlying control dynamics, a result that was well explained by a bias in the dynamics estimation. This work demonstrates how an incorrect internal model of control dynamics affects navigation in volatile environments in spite of continuous sensory feedback.

neuroscience↗

bioRxiv2019

Multiplexed code of navigation variables in the anterior limbic system

The brains navigation system integrates multimodal cues to create a sense of position and orientation. Here we used a multimodal model to systematically assess how neurons in the anterior thalamic nuclei, retrosplenial cortex and anterior hippocampus of mice, as well as in the cingulum fiber bundle and the white matter regions surrounding the hippocampus, encode an array of navigational variables when animals forage in a circular arena. In addition to coding head direction, we found that some thalamic cells encode the animals allocentric position, similar to place cells. We also found that a large fraction of retrosplenial neurons, as well as some hippocampal neurons, encode the egocentric position of the arenas boundary. We compared the multimodal model to traditional methods of head direction tuning and place field analysis, and found that the latter were inapplicable to multimodal regions such as the anterior thalamus and retrosplenial cortex. Our results draw a new picture of the signals carried and outputted by the anterior thalamus and retrosplenial cortex, offer new insights on navigational variables represented in the hippocampus and its vicinity, and emphasize the importance of using multimodal models to investigate neural coding throughout the navigation system.

neuroscience↗

bioRxiv2019

Simple spike dynamics of Purkinje cells in the macaque vestibulo-cerebellum reflect sensory prediction error

Theories of cerebellar functions posit that the cerebellum implements forward models for online correction of motor actions and sensory estimation. As an example of such computations, a forward model compensates for a sensory ambiguity where the peripheral otolith organs in the inner ear sense both head tilts and translations. Here we exploit the response dynamics of two functionally-coupled Purkinje cell types in the caudal vermis to understand their role in this computation. We find that one population encodes tilt velocity, whereas the other, translation-selective, population encodes linear acceleration. Using a dynamical model, we further show that these signals likely represent sensory prediction error for the on-line updating of tilt and translation estimates. These properties also reveal the need for temporal integration between the tilt-selective velocity and translation-selective acceleration population signals. We show that a simple model incorporating a biologically plausible short time constant can mediate the required temporal integration.

neuroscience↗

bioRxiv2019

A gravity-based three-dimensional compass in the mouse brain

Head direction cells in the mammalian limbic system are thought to function as an allocentric neuronal compass. Although traditional views hold that the compass of ground-dwelling species is planar, we show that head-direction cells in the rodent thalamus, retrosplenial cortex and cingulum fiber bundle are tuned to conjunctive combinations of azimuth, pitch or roll, similarly to presubicular cells in flying bats. Pitch and roll orientation tuning is ubiquitous, anchored to gravity, and independent of visual landmarks. When head tilts, azimuth tuning is affixed to the head-horizontal plane, but also uses gravity to remain anchored to the terrestrial allocentric world. These findings suggest that gravity defines all three degrees of freedom of the allocentric orientation compass, and only the azimuth component can flexibly remap to local cues in different environments. Collectively, these results demonstrate that a three-dimensional, gravity-based, neural compass is likely a ubiquitous property of mammalian species, including ground-dwelling animals.

neuroscience↗

bioRxiv2019

A re-interpretation of the experimental data of Shinder and Taube \"Three-dimensional Tuning of Head Direction Cells in Rats\", Journal of Neurophysiology 121(1), 2019.

In a recent study, Shinder and Taube (2019) concluded that head direction cells in the anterior thalamus of rats are tuned to one-dimensional (1D, yaw-only) motion exclusively, in contrast to recent findings in bats (Finkelstein et al. 2015), mice (Angelaki et al. 2016; Cham et al. 2017; Laurens et al. 2017), and rats (Page et al. 2017). Here we re-interpret the authors experimental results using model comparison and demonstrate that, contrary to their conclusions, their data actually supports the dual-axis rule (Page et al. 2017) and tilted azimuth model (Laurens and Angelaki 2018), where head direction cells use gravity to integrate 3D rotation signals about all cardinal axes of the head. We further show that this study is inconclusive regarding the presence of vertical orientation tuning; i.e. whether head direction cells encode 3D orientation in the horizontal and vertical planes conjunctively. Using model simulations, we demonstrate that, even if 3D tuning existed, the experimental protocol and data analyses used by Shinder and Taube (2019) would not have revealed it. We conclude that the actual experimental data of Shinder and Taube (2019) are compatible with the 3D properties of head direction cells discovered by other groups, yet incorrect conclusions were reached because of incomplete and qualitative analyses.

neuroscience↗

bioRxiv2018

Neuronal thresholds and correlations in the peripheral vestibular system during rotation discrimination

Neuronal and behavioral thresholds were measured simultaneously as trained male macaques performed a yaw rotation discrimination task in darkness. When corrected to account for variations in neuronal direction preferences, neurons in the vestibular nuclei and semicircular canal afferents had discrimination thresholds that were only two-fold smaller than behavioral thresholds. There was no significant trial-by-trial correlation between neuronal activity and perceptual decisions, despite the presence of significant pair-wise noise correlations. The lack of choice-related activity during rotation discrimination contrasts with the robust correlations observed previously between brainstem neurons and choices during translation perception. These results suggest task-dependent differences in subcortical processing of vestibular signals, as well as how signals related to perceptual decisions may propagate back to early stages of sensory processing.\n\nSIGNIFICANCE STATEMENTThis is the first ever simultaneous recordings of neural and behavioral thresholds during rotation discrimination. Its importance lies on the fact that the vestibular system provides an excellent model to probe origins of perception because directional selectivity signals are similar at many levels of processing, from afferents to cortex. The findings of similar neuronal and behavioral discrimination thresholds, significant inter-neuronal correlations, but lack of correlations between behavior and neuronal activity of both afferents and central brainstem neurons are intriguing and suggest task-dependent organization of early sensory areas.

neuroscience↗

bioRxiv2017

The brain compass: a perspective on how self-motion updates the head direction cell attractor

Head Direction cells form an internal compass that signals head azimuth orientation even in the absence of visual landmarks. It is well accepted that head direction properties are generated through a ring attractor that is updated using rotation self-motion cues. The properties and origin of this self-motion velocity drive remain, however, unknown. We propose a unified, quantitative framework whereby the attractor velocity input represents a multisensory self-motion estimate computed through an internal model that uses sensory prediction error based on vestibular, visual, and somatosensory cues to improve on-line motor drive. We show how context-dependent strength of recurrent connections within the attractor itself, rather than the self-motion input, explain differences in head direction cell firing between free foraging and restrained movements. We also summarize recent findings on how head tilt relative to gravity influences the azimuth coding of head direction cells, and explain why and how these effects reflect an updating self-motion velocity drive that is not purely egocentric. Finally, we highlight recent findings that the internal compass may be three-dimensional and hypothesize that the additional vertical degrees of freedom are defined based on global allocentric gravity cues.

neuroscience↗

bioRxiv2017

A unified internal model theory to resolve the paradox of active versus passive self-motion sensation

Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally-generated ( passive) movements. However, these neurons show reduced responses during self-generated ( active) movements, indicating that the brain computes the predicted sensory consequences of motor commands in order to cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations established during passive movements remain unknown. Here we construct a Kalman filter that incorporates motor commands into a previously-established model of optimal passive self-motion estimation. We find that the simulated sensory error and feedback signals match experimentally measured neuronal response during active and passive head and trunk rotations and translations. We conclude that a single internal model of head motion can process motor commands and sensory afferent signals optimally, and we describe how previously identified neural responses in the brainstem and cerebellum may represent distinct nodes in these computations.

neuroscience↗