Biology subjects

Verschure, P. F. M. J.

Publications and source records attributed to Verschure, P. F. M. J..

5 recordsLinked to original sources

bioRxiv2025

Motivational Cognitive Maps for Self-Regulated Autonomous Navigation

The mammalian hippocampal formation plays a critical role in efficient and flexible navigation. Hippocampal place cells exhibit spatial tuning, characterized by increased firing rates when an animal occupies specific locations in its environment. However, the mechanisms underlying the encoding of spatial information by hippocampal place cells remain not fully understood. Evidence suggests that spatial preferences are shaped by multimodal sensory inputs. Yet, existing hippocampal models typically rely on a single sensory modality, overlooking the role of interoceptive information in the formation of cognitive maps. In this paper, we introduce the Motivational Hippocampal Autoencoder (MoHA), a biologically inspired model that integrates interoceptive (motivational) and exteroceptive (visual) information to generate motivationally modulated cognitive maps. MoHA captures key hippocampal firing properties across different motivational states and, when embedded in a reinforcement learning agent, generates adaptive internal representations that drive goal-directed foraging behavior. Grounded in the principle of biological autonomy, MoHA enables the agent to dynamically adjust its navigation strategies based on internal drives, ensuring that behavior remains flexible and context-dependent. Our results show the benefits of integrating motivational cognitive maps into artificial agents with a varying set of goals, laying the foundation for self-regulated multi-objective reinforcement learning.

neuroscience↗

bioRxiv2022

Theta oscillations optimize information rate in the hippocampus

Low-frequency oscillations shape how neurons sample their synaptic inputs, regulating information exchange across networks. In the hippocampus, theta-band oscillations (3-8 Hz) reorganize cortical input signals temporally, resulting in a phase code. However, the reason hippocampal oscillations are limited to low frequencies like the theta band remains unclear. Here, we derive a theoretical framework for neuronal phase coding to show that realistic noise levels create a trade-off between sampling speed (controlled by oscillation frequency) and encoding precision in hippocampal neurons. This speed-precision trade-off produces a maximum in information rate within the theta band of ~1-2 bits/s. Additionally, we demonstrate that our framework explains other key hippocampal properties, such as the preservation of theta along the dorsoventral axis despite various physiological gradients, and the modulation of theta frequency and amplitude by the animals running speed. Extending our analysis to extra-hippocampal areas, we propose that theta oscillations may also support efficient encoding of stimuli in visual cortex and olfactory bulb. More broadly, we lay the groundwork for rigorously studying how system constraints determine optimal sampling frequency regimes for phase coding neurons in biological and artificial brains. Author SummaryThe rodent hippocampus exhibits prominent oscillations in the theta band (3-8 Hz) during exploration, enabling individual neurons to rhythmically sample and represent sensory signals from the cortex. However, the reason behind the specific frequency of this hippocampal rhythm has remained unclear. In this study, we developed a biologically-based theoretical framework to demonstrate that neurons using oscillations to efficiently sample noisy signals encounter a trade-off between their sampling speed (i.e., oscillation frequency) and their coding precision (i.e., reliability of encoding). Notably, our findings reveal that this trade-off is optimized precisely within the theta band, while also providing insights into other fundamental features. In conclusion, we offer an explanation grounded in efficient coding for why hippocampal oscillations are confined to the theta band and establish a foundation for exploring how the properties of individual neurons determine optimal sampling frequencies in specific neural circuits.

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bioRxiv2021

Theta phase mediates deliberate action switching in human Supplementary Motor Areas

The ability to deliberately overwrite ongoing automatic actions is a necessary feature of adaptive behavior. It has been proposed that the supplementary motor areas (SMAs) operate as a controller that orchestrates the switching between automatic and deliberate processes by inhibiting ongoing behaviors and so facilitating the execution of alternative ones. In addition, previous studies support the involvement of SMAs theta waves (4-9 Hz) in cognitive control. However, the exact role of such oscillatory dynamics and their contribution to the control of action are not fully understood. To investigate the mechanisms by which the SMAs support direct control of deliberate behavior, we recorded intracranial electroencephalography (iEEG) activity in humans performing a motor sequence task. Subjects had to perform a "change of plans" motor task requiring habitual movements to be overwritten at unpredictable moments. We found that SMAs were exclusively active during trials that demand action reprogramming in response to the unexpected cue but were silent during automatic action execution. Importantly, SMAs activity was characterized by a distinct temporal pattern, expressed in a stereotypical phase alignment of theta oscillations. More specifically, single trial motor performance was correlated with the trial contribution to the global inter-trial phase coherence, with higher coherence associated with faster trials. In addition, theta phase modulated the amplitude of gamma oscillations, with higher cross-frequency coupling in faster trials. Our results suggest that within frontal cortical networks, theta oscillations could encode a control signal that promotes the execution of deliberate actions.

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bioRxiv2018

Revealing an extended critical window of recovery post-stroke

The impact of rehabilitation on post-stroke motor recovery and its dependency on the patients chronicity remain unclear. The existence and regularity of a, so called, proportional recovery rule across a range of functional deficits and therapies supports the notion that functional interventions have little or no impact beyond spontaneous recovery rates in a critical window of recovery which lasts from 3 to 6 months post-stroke. In this meta-analysis, we apply a bootstrap analysis method to assess the overall impact of a specific VR-based rehabilitation protocol for the upper extremities on a homogeneous sample of 219 individuals with hemiparesis at various stages post stroke. Our analysis uncovers a precise gradient of sensitivity to treatment that expands more than one year beyond the limits of the so-called critical window of recovery. These findings redefine the limits of the so-called critical window of recovery and suggest that stroke-derived plasticity mechanisms do facilitate functional recovery even at the chronic and late chronic stage.

neuroscience↗

bioRxiv2017

The Perceptual Shaping of Anticipatory Actions

Humans display anticipatory motor responses to minimize the adverse effects of predictable perturbations. A widely accepted explanation for this behavior relies on the notion of an inverse model that, learning from motor errors, anticipates corrective responses. Here, we propose and validate the alternative hypothesis that anticipatory control can be realized through a cascade of purely sensory predictions that drive the motor system, reflecting the causal sequence of the perceptual events preceding the error. We compare both hypotheses in a simulated anticipatory postural adjustment task. We observe that adaptation in the sensory domain, but not in the motor one, supports the robust and generalizable anticipatory control characteristic of biological systems. Our proposal unites the neurobiology of the cerebellum with the theory of active inference and provides a concrete implementation of its core tenets with great relevance both to our understanding of biological control systems and, possibly, to their emulation in complex artefacts.

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