Henning Sprekeler

This study develops a phenomenological model of memory consolidation that describes it as a brain-wide process involving representational drift and provides a functional interpretation of drift as a mechanism for improved memory retention.

The paper uses information theory to analyze neural population dynamics and finds that stable neurons show higher redundancy and synergy in pairwise interactions with other neurons.

The paper demonstrates how chemoaffinity-based connectivity rules can establish innate cognitive functions and motor programs by structuring recurrent neuronal networks before experience.

This study uses a spiking neural network model with chloride dynamics to show that benzodiazepine efficacy in status epilepticus depends on GABAAR reversal potential and pyramidal cell chloride extrusion.

This paper uses evolutionary strategies to meta-learn plasticity rules in spiking networks, finding stable rules for synapse types but facing challenges with complex co-active rules.

This study shows NDNF interneurons in layer 1 modulate inhibition via GABAergic transmission, controlling information flow in pyramidal cells through competition with SOM interneurons.

This study shows that calcium-permeable AMPA receptors (CP-AMPARs) in PV interneurons reduce their feature selectivity, and removing them increases selectivity in visual cortex and hippocampus.

The paper investigates whether transcriptomic state modulation in GABAergic interneurons generalizes across species by comparing single-cell RNA sequencing data from multiple species.

This study uses a lockbox task to show that mice primarily develop motor skills before adopting a cognitive strategy for solving a complex mechanical puzzle.

This study investigates how continuous perceptual choices are encoded in human early visual cortex using motion stimuli and encoding models.

This study investigates whether the compartment-specific inhibition by PV and SST interneurons evolved due to pyramidal cell structure or other factors, finding that interneuron diversity predates this structure.

The paper identifies long-range inhibitory input to layer 1 of the auditory cortex and shows its role in facilitating memory through plasticity during threat learning.

This study shows that feedback modulation in neural networks can create context-invariant sensory representations at the population level through dynamic reorientation of neural activity.

The paper proposes a computational model of systems memory consolidation based on Hebbian plasticity in parallel synaptic pathways, showing how memories are transferred and transformed across brain regions.

The paper shows that homeostatic inhibitory plasticity in interneurons can self-organize a network state where spikes and bursts occur asynchronously and irregularly, increasing information encoded in bursts.

The paper shows that activity-dependent synaptic plasticity on PV interneurons generates excitatory-inhibitory assemblies in mouse V1, enabling stimulus-specific competition between pyramidal neurons.

The paper optimizes interneuron circuits for compartment-specific feedback inhibition onto pyramidal neurons using gradient-based optimization and biologically plausible models, revealing two interneuron classes resembling PV and SST.

The paper develops a computational model of mouse primary visual cortex to show how three interneuron types shape negative prediction-error neurons through experience-dependent inhibitory plasticity.

The paper shows presynaptic inhibition stabilizes recurrent excitation in neural networks by counteracting Hebbian plasticity-induced instabilities on sub-second timescales.

The paper proposes a computational model showing how three interneuron types interact to redistribute somato-dendritic inhibition in pyramidal cells.

The paper introduces a method to quantify local symmetry and orientation distortions in grid cell firing patterns by assigning local grid scores and orientations to individual spikes.

The paper shows that cortical neurons can communicate multiple independent signals using sparse bursts, optimizing information transmission.

The paper proposes a unifying model explaining spatial tuning patterns in neurons through excitatory and inhibitory synaptic plasticity driven by input statistics.

The paper investigates how sparse synaptic connections in balanced recurrent networks can enable memory replay through recurrent amplification and small sensory cues.