Maxim Bazhenov

The paper uses a biophysical model to show that slow-wave and delta waves during sleep differentially control memory consolidation and forgetting through distinct synaptic mechanisms.

This study uses a computational model to show that age-related loss of recurrent excitation disrupts slow oscillations in sleep, impairing memory consolidation.

This study shows that thalamic temporal interference stimulation with a 5Hz envelope increases sleep spindle density through subthreshold resonance in thalamocortical relay neurons.

The paper uses a data-constrained RNN model to uncover two distinct circuit mechanisms for olfactory OFF responses in locust antennal lobe neurons.

This paper develops a biological brain-based gas sensor using locust olfaction to detect and classify multiple PFAS with high accuracy.

This study shows that combining cathodal tDCS with closed-loop acoustic stimulation during sleep improves memory retention compared to acoustic stimulation alone.

This paper uses a biophysically realistic network model to show how sleep replay reorganizes synaptic-weight space to support both old and new memories.

This study uses a computational model to show that ion dynamics underlie the temporal structure of resting-state functional connectivity.

This paper shows that slow-wave sleep interleaves replay of familiar and novel memory traces, enabling new memories to integrate into existing cortical memory without interference.

The paper investigates how cortical stimulation engages subcortical circuits in mice and humans, showing similar evoked potentials and thalamic contributions across species.

The paper investigates how inhibitory plasticity in the honeybee antennal lobe improves pattern separation during odor learning by suppressing shared compounds and enhancing distinct ones.

This paper develops a biophysical network model to investigate how traumatic brain injury (TBI) affects neural network dynamics, identifying mechanisms behind infra slow oscillations, delta power increases, and high frequency oscillations linked to seizures.

This paper shows that extended interval theta burst stimulation (eTBS) enhances antidepressant effects by reducing GABAergic inhibition and promoting glutamatergic plasticity.

The paper develops a biophysically realistic human brain model to study how synaptic connectivity influences the emergence of global and local slow waves during slow-wave sleep.

This study shows that cholinergic modulation dynamically switches resting-state networks by selectively suppressing the Default Mode Network in both rodent and human models.

The paper shows olfactory receptor neurons generate multiple response motifs that enhance coding dimensionality for odor classification and navigation.

This study shows that sleep prevents catastrophic forgetting in spiking neural networks by reactivating synaptic weights to maintain multiple task representations.

This study uses closed-loop acoustic stimulation in mice to explore its effects on hippocampo-thalamo-cortical activity and memory retention during sleep.

This study investigates novelty detection in honey bees by analyzing behavioral and neuronal responses to familiar and novel odors in the antennal lobes.

This study uses a hybrid model to predict how cortical stimulation can induce directional traveling waves by controlling inhibitory interneurons.

This paper introduces differential covariance analysis to estimate functional connectivity in fMRI, showing improved performance in complex network simulations.

This study examines the interaction between cortical slow oscillations and hippocampal ripples during sleep using a computational model and human recordings, finding that ripples influence cortical spatiotemporal patterns and synchronize state transitions.

This study shows that sleep replay helps protect old memories from being lost when new memories are learned, by reorganizing synaptic connections to support both memories.

This study uses computational models to show that sensory stimulation during specific phases of slow-wave sleep enhances memory consolidation by affecting slow-wave patterns and replay.

This paper develops a model to predict which cortical neurons are activated by electrical stimulation, finding selective activation across cell types, layers, and stimulation parameters.

The paper develops a computational model of olfactory processing in insects, showing that sparse KC representations optimally separate odorants in MBONs, and that synaptic plasticity preserves this separation.

The paper simulates human sleep spindle MEG and EEG by integrating ion channel dynamics and circuit-level neural activity across multiple scales.

This study shows sleep spindles and slow oscillations each play distinct roles in memory consolidation, with spindles enabling independent memory replay and slow oscillations favoring strong memories, as observed in natural sleep.

The paper develops a thalamocortical network model to explain differences in sleep spindle properties between MEG and EEG recordings and links these to cortical and thalamic connectivity.