Biology subjects

Mueller-Komorowska, D.

Publications and source records attributed to Mueller-Komorowska, D..

4 recordsLinked to original sources

bioRxiv2025

Compensation of Hyperexcitability with Simulation-Based Inference

The activity of healthy neuronal networks is tightly regulated, and a shift towards hyperexcitability can cause various problems, such as epilepsies, memory deficits, and motor disorders. Numerous cellular, synaptic, and intrinsic mechanisms of hyperexcitability and compensatory mechanisms to restore healthy activity have been proposed. However, quantifying multiple compensatory mechanisms and their dependence on specific pathophysiological mechanisms has proven challenging, even in computational models. We use simulation-based inference to quantify the interactions of putative compensatory mechanisms in a spiking neuronal network model. Various parameters of the model can compensate for changes in other parameters to maintain baseline activity, and we estimated their compensatory potential. Furthermore, specific causes of hyperexcitability - interneuron loss, excitatory recurrent synapses, and principal cell depolarization - have distinct compensatory mechanisms that can restore normal excitability. Our results show that spiking neuronal network simulators could generate hypotheses about the mechanisms of pathophysiological network mechanisms.

neuroscience↗

bioRxiv2024

Deciphering the astrocytic contribution to learning and relearning

Astrocytes play a key role in the regulation of synaptic strength and are thought to orchestrate synaptic plasticity and memory. Yet, how specifically astrocytes and their neuroactive transmitters control learning and memory is currently an open question. Recent experiments have uncovered an astrocyte-mediated feedback loop in CA1 pyramidal neurons which is started by the release of endocannabinoids by active neurons and closed by astrocytic regulation of the D-serine levels at the dendrites. D-serine is a co-agonist for the NMDA receptor regulating the strength and direction of synaptic plasticity. Activity-dependent D-serine release mediated by astrocytes is therefore a candidate for mediating between long-term synaptic depression (LTD) and potentiation (LTP) during learning. Here, we show that the mathematical description of this astrocytic regulation is consistent with the classic Bienenstock Cooper Munro (BCM) model for synaptic plasticity, which postulated the existence of an activity-dependent LTP/LTD threshold. We show how the resulting mathematical framework can explain the experimentally observed behavioral effects of astrocytic cannabinoid receptor knock-out on mice during a place avoidance task and give rise to new testable predictions about the learning process advancing our understanding of the functional role of neuron-glia interaction in learning.

neuroscience↗

bioRxiv2019

Unspecific expression in limited excitatory cell populations in interneuron-targeting Cre-driver lines can have large functional effects

1Transgenic Cre-recombinase expressing mouse lines are widely used to express fluorescent proteins and opto-/chemogenetic actuators, making them a cornerstone of modern neuroscience. Particularly, the investigation of interneurons has benefitted from the ability to target genetic constructs to defined cell types. However, the cell type specificity of some mouse lines has been called into questions. Here we show for the first time the functional consequences of unspecific expression in a somatostatin-Cre (SST-Cre) mouse line. We find large optogenetically evoked excitatory currents originating from unspecifically targeted CA3 pyramidal cells. We also used public Allen Brain Institute data to estimate expression specificity in other Cre lines. Another SST-Cre mouse lines shows comparable unspecificity, whereas a Parvalbumin-Cre mouse line shows much less unspecific expression. Finally, we make suggestions to ensure that the results from in-vivo use of Cre mouse lines are interpretable.

neuroscience↗

bioRxiv2019

Quantitative properties of a feedback circuit predict frequency-dependent pattern separation

Feedback inhibitory motifs are thought to be important for pattern separation across species. How feedback circuits may implement pattern separation of biologically plausible, temporally structured input in mammals is, however, poorly understood. We have quantitatively determined key properties of net feedback inhibition in the mouse dentate gyrus, a region critically involved in pattern separation. Feedback inhibition is recruited steeply with a low dynamic range (0 to 4% of active GCs), and with a non-uniform spatial profile. Additionally, net feedback inhibition shows frequency-dependent facilitation, driven by strongly facilitating mossy fiber inputs. Computational analyses show a significant contribution of the feedback circuit to pattern separation of theta modulated inputs, even within individual theta cycles. Moreover, pattern separation was selectively boosted at gamma frequencies, in particular for highly similar inputs. This effect was highly robust, suggesting that frequency dependent pattern separation is a key feature of the feedback inhibitory microcircuit.

neuroscience↗