Tatjana Tchumatchenko

The paper investigates how input geometry affects neural adaptation dynamics in a spiking neural network model of relatedness priming.

The paper shows that CA3 axons maintain a stable spatial coding manifold that encodes aversive information without disrupting spatial representation.

The paper develops a computational model to show that MID1 binding increases mutant huntingtin RNA stability, validated experimentally.

The paper introduces a data-driven framework to predict collective synaptic plasticity outcomes by considering protein allocation and spatial competition among synapses.

This study identifies molecular signatures of aging in the mouse brain through proteo-transcriptomic analysis, revealing changes in protein aggregation, mRNA relocalization, and translation efficiency linked to neurodegeneration.

The paper shows that dendrites have nanoscale constrictions that create electrical compartments, altering synaptic integration in neurons.

The paper develops a computational model to explain how local translation of CNIH-2 affects the trafficking and kinetics of different AMPAR subtypes during long-term potentiation.

SpyDen automates molecular and structural analysis in neural compartments by providing an open-source, customizable platform for image annotation and analysis.

The paper shows that astrocyte-mediated regulation of D-serine aligns with the BCM model of synaptic plasticity, explaining behavioral effects in mice and predicting new learning mechanisms.

The paper investigates how local synaptic plasticity influences population-level synaptic size distribution through spontaneous and stimulated spine dynamics.

This paper introduces an unbiased clustering algorithm for single-molecule localization microscopy that reduces false positives and negatives compared to existing methods.

The paper develops DELTA, a method to measure brain-wide synaptic protein turnover at single-synapse resolution, revealing localized plasticity in hippocampal CA1 during learning.

This study investigates how neurons allocate resources for synaptic plasticity across homosynaptic and heterosynaptic sites, revealing collaboration and competition among spines and the impact of spatial-temporal distance on spine dynamics.

This paper identifies spiking network connectivity patterns underlying nonlinear computations and shows how to target dynamic firing rate trajectories in biologically realistic networks.

This study examines how dopamine and serotonin interact to influence spatial learning and cognitive flexibility using a reward-modulated spike time-dependent plasticity model.

The paper quantifies the spatial scale of synaptic protein allocation during homeostatic plasticity and finds that proteins are distributed at the level of synaptic neighborhoods.

This study shows how synaptic plasticity affects network contrast invariance in balanced networks using mean-field models and simulations.

The paper introduces a computational model that simulates repair-or-dispose decisions by glia and their long-term implications in neurodegenerative disease progression.

This study shows that synaptic short-term plasticity and noise can create active and transient working memory representations, and how dysregulation of a synaptic signaling mechanism affects memory duration.