Poster 2022#2 – Yuri DABAGHIAN – Grid Cell Percolation

Grid cells are famous for the lattice-like layouts of their firing fields—a property has led many researchers to assume that these neurons readily convey spatial scales and metrics to downstream networks and thus contribute to spatial cognition and memory. In reality, this is not the case: grid cells commonly exhibit irregular spiking, reflecting how the … Continue reading Poster 2022#2 – Yuri DABAGHIAN – Grid Cell Percolation

Poster 2022#3 – Takahisa DATE – Effects of spatial constraints of inhibitory connectivity on the dynamical development of criticality in spiking networks

Many experimental studies have reported that in-vitro neuronal networks develop into a critical state. Potential mechanisms for such development have been suggested by modeling studies, such as short-term and long-term synaptic plasticity, the balance between excitatory and inhibitory neurons, or the network topology. However, it remains unclear how these mechanisms are orchestrated in physical space … Continue reading Poster 2022#3 – Takahisa DATE – Effects of spatial constraints of inhibitory connectivity on the dynamical development of criticality in spiking networks

Poster 2022#4 – Anja RABUS – Different paths of information routing preserve scale-free neuronal and behavioral dynamics [VIDEO]

Different paths of information routing preserve scale-free neuronal and behavioural dynamics. Psychedelics promote altered mental states and under certain conditions, mental health. Recent investigation into the mechanism of psychedelics has focused on whole-brain models. We study the relationship between functional connectivity (FC) and neuronal and behavioral dynamics on the microscale in the retro-splenial cortex (RSC) … Continue reading Poster 2022#4 – Anja RABUS – Different paths of information routing preserve scale-free neuronal and behavioral dynamics [VIDEO]

Poster 2022#5 – Anna-Thekla JÄGER – Self-Similar Properties of the rs-fMRI Signal Reflect Functional Changes in Neuroplasticity Following Motor Sequence Learning

Recent research in functional magnetic resonance imaging (fMRI) shows that scale-free properties of brain signals can meaningfully reflect human brain activity in health and disease. Here, we sought to examine whether changes in scale-free temporal dynamics within resting-state fMRI (rsfMRI) data are reflective of functional neuroplasticity following sequence-specific motor sequence learning (MSL). Using the Hurst … Continue reading Poster 2022#5 – Anna-Thekla JÄGER – Self-Similar Properties of the rs-fMRI Signal Reflect Functional Changes in Neuroplasticity Following Motor Sequence Learning

Poster 2022#6 – Eunjin HWANG – Characterization of Phase Transition in Brain during Anesthesia-Induced Loss of Consciousness

The thalamocortical system plays a key role in the breakdown or emergence of consciousness, providing bottom-up information delivery from sensory afferents and integrating top-down intracortical and thalamocortical reciprocal signaling. A fundamental and so far unanswered question for cognitive neuroscience remains whether the thalamocortical switch for consciousness works in a discontinuous manner or not. To unveil … Continue reading Poster 2022#6 – Eunjin HWANG – Characterization of Phase Transition in Brain during Anesthesia-Induced Loss of Consciousness

Poster 2022#7 – Benedetta MARIANI – Collective oscillations in the rat barrel-thalamus network

Task-dependent neuronal oscillations are often found in mammalian cortical networks, and investigating their origin and function is an open area of research[1]. In this work we analyze LFPs and MUAs data from the barrel cortex of urethane anesthetized rats, and we find long-lasting collective oscillations in the 6-10 Hz band after stimulation of the rat … Continue reading Poster 2022#7 – Benedetta MARIANI – Collective oscillations in the rat barrel-thalamus network

Poster 2022#8 – Geza ODOR – Comparison of the synchronization transition of the Kuramoto model on fruit-fly versus a large human connectome

Previous simulation studies on human connectomes suggested that critical dynamics emerge subcritically in the so-called Griffiths phases. Now we investigate this on the largest available brain network, the 21662 node fruit-fly connectome, using the Kuramoto synchronization model. As this graph is less heterogeneous, lacking modular structure and exhibiting high topological dimension, we expect a difference … Continue reading Poster 2022#8 – Geza ODOR – Comparison of the synchronization transition of the Kuramoto model on fruit-fly versus a large human connectome

Poster 2022#9 – Wesley Charles SMITH – In vivo Quantification of Neural Criticality and Complexity in Mouse Cortex and Striatum in a Model of Cocaine Abstinence

Self-organized criticality is a hallmark of complex dynamic systems at phase transitions. Systems that operate at or near criticality have large-scale fluctuations or “avalanches”, the frequency and duration power of which are best fit with a power law revealing them to be scale-free and fractal, and such power laws are ubiquitous. It is an attractive … Continue reading Poster 2022#9 – Wesley Charles SMITH – In vivo Quantification of Neural Criticality and Complexity in Mouse Cortex and Striatum in a Model of Cocaine Abstinence

Poster 2022#10 – Gabriel MARGHOTI – Intermittent chimera-like and bi-stable synchronization states in network of distinct Izhikevich neurons [VIDEO]

Phase synchronization phenomena of neuronal networks are one of many features depicted by real networks that can be studied using computational models. Here, we proceed with numerical simulations of a globally connected network composed of non-identical (distinct) Izhikevich neuron model to study clustered phase synchronization. We investigate the case in which, once coupled, there exist … Continue reading Poster 2022#10 – Gabriel MARGHOTI – Intermittent chimera-like and bi-stable synchronization states in network of distinct Izhikevich neurons [VIDEO]

Poster 2022#11 – Jungyoung KIM – Synaptic I/E ratio affects neural network synchronization and computational capabilities

We introduce a neural network model to study the effect of synchronization on the encoding capacity and spreading spikes in more realistic situation. In this model the neural network is composed of excitatory and inhibitory neurons and long-lasting synaptic current operated by heterogeneous Poisson synaptic input. Based on numerical integration, we find three different regimes … Continue reading Poster 2022#11 – Jungyoung KIM – Synaptic I/E ratio affects neural network synchronization and computational capabilities