International Conference on Mathematical Neuroscience (ICMNS)
CONTRIBUTED TALKS & POSTERS
talks
Noise-induced pattern formation in networks of spatially-dependent neural networks | Daniele Avitabile
Three-factor cortico-striatal plasticity shifts activity of cortico-basal ganglia-thalamic subnetworks towards optimal performance in decision-making tasks | Jyotika Bahuguna
Modeling cyclic-sequential brain activity via biologically plausible dynamics | Virginia Bolelli
An analysis of the temporal component of motor preparation and execution in High Frequency Local Field Potentials: A Theoretical Approach | Marc Burillo Garcia
A mesoscopic theory for coupled stochastic oscillators | Victor Buendía Ruiz-Azuaga
Classification of Neural Mass Models based on codimension-2 bifurcations | Gabriele Casagrande
Balanced inhibition allows for robust learning of input-output associations in feedforward networks with Hebbian plasticity | Gloria Cecchini
Dynamic Mean Field Theories for Correlated Strong Noise in Nonlinear Gain | Shoshana Chipman
A Neural Mass Model with Neuromodulation for Whole-Brain Modeling in Parkinson's Disease | Damien Depannemaecker
Uncertainty in stimulus dynamics drives asymmetries in evidence integration | Tahra Eissa
Interspike Interval dynamics in neuronal populations | Luca Falorsi
Glial ensheathment of inhibitory synapses drives hyperactivity and increases correlations | Gregory Handy
Neural fields with auto-associative memories: collective activity, pattern formation, and memory dynamics | Akke Mats Houben
Koopman analysis of stochastic oscillator networks | Pierre Houzelstein
A Spiking Neural Network Model for Categorization Tasks | Sophie Jaffard
Towards translation of whole-brain neural mass models to clinical practice: finding the right level of model complexity | Xenia Kobeleva
Fluctuations in strongly coupled soft-threshold integrate-and-fire networks | Gabriel Koch Ocker
Altered slow inactivation of sodium channels carrying an epilepsy mutation promotes depolarization block | Louisiane Lemaire
Parkinsonian patients have a broader range of time-scales of EEG motor cortex activity than healthy subjects | Cheng Ly
The Hydrodynamic Limit of Neural Networks with Balanced Excitation and Inhibition | James Maclaurin
Fine-tuning of attractors on a ring underlies the learning of robust working memory in mice | Alexandre Mahrach
Transitions in cartwheel cell electrical activity: bifurcations of super-slow equilibria explain effects of ion current blockers | Matteo Martin
Optimal control over damped Oscillations via response curves | Kevin Martínez Anhom
A stochastic hierarchical model for low grade glioma evolution | Amira Meddah
tDCS montage optimization for the treatment of epilepsy using Neurotwins | Borja Mercadal
Beyond Synchrony: The Role of Electrical Synapses in Neural Pattern Formation | Bastian Pietras
Optimal signal transmission and timescale diversity in a model of human brain operating near criticality | Yang Qi
Metric Framework of Synchronous States Identification in Spiking Neural Networks | Daniil Radushev
Interaction of segregated resonant mechanisms along the dendritic axis in CA1 pyramidal cells: Interplay of cellular biophysics and spatial structure | Horacio G. Rotstein
Ulises Chialva¹ and Horacio G. Rotstein²
¹ Department of Mathematics, Universidad Nacional del Sur, Bahía Blanca, Argentina
² Federated Department of Biological Sciences, New Jersey Institute of Technology & Rutgers University, Newark, NJ, USA
Neuronal frequency filters play a crucial role in cognition, motor behavior, and the dynamics of information processing in neural networks in both health and disease. The filtering properties of neurons are shaped by several factors, including the intrinsic properties of neurons, their dendritic geometry, and the heterogeneous distribution of ionic currents [1]. Experimental results show the existence of two distinct theta (∼ 4 – 10 Hz) resonant mechanisms in CA1 pyramidal neurons: (i) a perisomatic resonance mediated by an M-type potassium current (IM ) and amplified by a persistent sodium current (INap), and (ii) a dendritic resonance mediated by a hyperpolarization-activated current (Ih) [2].
While the propagation of (amplitude) resonances along dendritic trees has been investigated before [3], a number of biologically and mathematically relevant questions remain open. It is unclear how the two experimentally observed biophysically different and spatially segregated types of resonance interact in the presence of a heterogeneous distribution of ionic currents and membrane potential variations. It is also unknown what are the interaction and propagation properties of the associated phasonances (phase-resonances). In this study, we address these issues using CA1 pyramidal neurons as a case study.
We use a multicompartmental model based on the Hodgkin-Huxley formalism. The model includes IM , INap and Ih, spatially and heterogeneously distributed along the dendrites. We also use a linearized version of this model that allows for mathematical tractability. The model is minimal in the sense that it includes enough compartments to capture the filtering properties of CA1 pyramidal cells, but this number is small enough to allow for the conceptual understanding of the underlying mechanisms. In practice we use 20 compartments, which we found to be appropriate to preserve the experimentally observed segregation of the two resonant mechanisms, while allowing for their interaction without creating unrealistic interferences. We apply sinusoidal inputs at proximal, distal, and intermediate dendritic locations, we compute the amplitude and phase profiles across all compartments, and describe them for a number of realistic scenarios.
Our results reveal that voltage variations along the dendritic cable differentially activate ionic channels, creating a diverse range of resonant and phasonant responses. The spatial structure of the dendrites provides the neuron with remarkable flexibility to process these inputs and support a variety of scenarios of resonance interaction. Our findings highlight the complex relationship between dendritic structure, ionic mechanisms, and neuronal filtering properties. These flexible filtering capabilities not only enable individual neurons to adapt to spatially and frequency-specific inputs, but also significantly contribute to the generation of network rhythms and the regulation of neural activity at the network level.
References
[1] G. Buzsáki. Rhythms of the brain. Oxford University Press, 2006.
[2] H. Hu, K. Vervaeke, L. J. Graham, and J. F. Storm. Complementary theta resonance filtering by two spatially segregated mechanisms in CA1 hippocampal pyramidal neurons. The Journal of physiology, 29:14472–14483, 2009.
[3] J. Laudansky, B. Torben-Nielsen, I. Segev, and S. Shama. Spatially distributed dendritic resonance selectively filters synaptic input. PLoS Computational Biology, 8:e1003775, 2014.
Distinct dopaminergic spike-timing-dependent plasticity rules are suited to different functional roles | Jonathan Rubin
One-shot normative modelling of whole-brain functional connectivity | Janus Rønn Lind Kobbersmed
Paths to depolarization block: modeling neuron dynamics during spreading depolarization events | Marisa Saggio
Neuronal field model analysis from a mathematical point of view | Lena Schadow
A Biologically Plausible Associative Memory Network | Mohadeseh Shafiei Kafraj
Understanding neuronal responses to transient inputs: a dynamical systems approach | Justyna Signerska-Rynkowska
Rate-like dynamics of memory-dependent spiking neural networks | Kasper Smeets
Activity-Dependent Homeostatic Plasticity Maintains Circuit-Level Dynamic Properties with Local Activity Information | Lindsay Stolting
Dynamics of synaptic weights under spike-timing-dependent plasticity | Jakob Stubenrauch
gPC-based robustness analysis of neural systems through probabilistic recurrence metrics | Uros Sutulovic
Neural Signal Prediction and Demixing via Multi-Time Delay Reservoir Computing | Kamyar Tavakoli
Homeostatic gain modulation drives changes in heterogeneity expressed by neural populations | Daniel Trotter
Human brain dynamics are shaped by rare long-range connections over and above cortical geometry | Jakub Vohryzek
Minimizing information loss reduces spiking neuronal networks to differential equations | Zhuo-Cheng Xiao
Modeling disorders of consciousness at the patient level reveals the network's influence on the diagnosis vs the local node parameters role in prognosis | Lou Zonca
posters
1 - Learning and connectivity in heterogeneous recurrent neural networks | Martina Acevedo
2 - Predicting individual traits from models of brain dynamics using the Fisher kernel | Christine Ahrends (Presented by Diego Vidaurre)
3 - Generation, Stability, and Robustness of Rhythmic Locomotion Patterns | Zahra Aminzare
4 - Analysis of bursting in a next-generation neural mass model with spike-frequency adaptation using nonstandard geometrical singular perturbation theory | Daniele Andrean
5 - Impact of age-related perturbations on a bump attractor model of working memory | Alexandra Antoniadou
6 - Spatiotemporal integration properties in MT neurons affect motion discrimination | Lucia Arancibia
7 - Fluid dynamics as a driver of retronasal olfaction | Andrea Barreiro
8 - Hodgkin-Huxley framework-based associative memory for neural adaptation in the human temporal lobe | Diletta Bartolini
9 - Neuronal rhythmic activity induced by the electrogenic Na+/K+-ATPase | Mahraz Behbood
10 - Frequency-dependent communication of information in networks of neurons in response to oscillatory inputs | Andrea Bel (Presented by Horacio Rotstein)
11 - A battle of timing vs amplitude: signal competition in the olfactory networks | Alla Borisyuk
12 - Estimating neural connection strengths from firing intervals | Maren Bråthen Kristoffersen
13 - An Event-Based Approach for the Statistical Analysis of Complex Intermittency in Brain Data | Marco Cafiso
14 - A Rosetta Stone for Neural Oscillators: Unifying Computational Models of Brain Dynamics | Francesca Castaldo
15 - Secondary Bifurcations in a Next Generation Neural Field Model | Oliver Cattell
16 - The effect of systemic ketamine on working memory history dependencies | Konstantinos Chatzimichail
17 - Kuramoto model for populations of quadratic integrate-and-fire neurons with chemical and electrical coupling | Pau Clusella
18 - The geometry of primary visual cortex representations is dynamically adapted to task performance | Julien Corbo
19 - Stochastic Optimal Control and Estimation with Multiplicative and Internal Noise | Francesco Damiani
20 - Delving into UP and DOWN States in Cortical Networks: Mechanisms Underlying Synaptic Plasticity | Rosa Maria Delicado Moll
21 - Pyramidal Interneuron Next-Generation Neural Mass Model: Synaptic Properties and Stimulation Response | Raul de Palma Aristides
22 - Brain rhythms based inference for energy-efficient speech processing | Olesia Dogonasheva
23 - Neural Field Equations with Slowly Evolving Parameters | Dirk Doorakkers
24 - Collective Behaviour of Chaotic Hénon Particles with Short-range Spatial Interaction | Congcong Du
25 - Discrete synaptic transmission impacts the onset of rhythmic network dynamics | Rainer Engelken
26 - Driven chimera states for analyzing focal and non-focal signals in epilepsy | Jacopo Epifanio
27 - Synaptic Plasticity and Spatial Patterning in the Next-Generation Neural Field Model | Niamh Fennelly
28 - Spatiotemporal Dynamics in Networks of Stochastic Integrate-and-Fire Neurons | Lauren Forbes
29 - Dendritic excitability controls overdispersion | Zachary Friedenberger
30 - Bistable perception emerges from loopy inference in strongly coupled probabilistic graphs | Alexandre Garcia-Duran Castilla
31 - Hydra’s Neural Symphony : Tuning into the Rhythms and Connections of cnidarians | Sarah Gaubi
32 - Low-Frequency Electrical Stimulation in Epilepsy: a Biophysical and Mathematical Representation | Guillaume Girier
33 - Experimental and Modeling Insights into Neural Dynamics Under Alternating Current Stimulation (tACS) | Camille Godin
34 - Stochastic cubic models of EEG dynamics during sleep-onset | Zhenxing Hu
35 - Exploring Neural Communication via Phase-Amplitude Dynamics: Efficient numerical methods | Gemma Huguet
36 - Stochastic random network dynamics describes endogenous fluctuations and Event-related Synchronisation and Desynchronisation | Axel Hutt
37 - The dynamical modes framework: towards a biophysical interpretation of neural data | Jorge Jaramillo
38 - Phase Oscillator Networks with Distance-Dependent Delays: How Does Conduction Speed Affect Large-Scale Brain Dynamics? | Grace Jolly
39 - Impact of meningioma and glioma on whole-brain dynamics | Albert Juncà Sabrià
40 - Model selection methods for estimating learning behavior in cuttlefish and octopuses | Louis Köhler
41 - Dynamical analysis of the Chialvo model under a locally active memristor as electromagnetic radiation | Ajay Kumar
Ajay kumar, V.V.M.S. Chandramouli
Affiliations Indian Institute of Technology Jodhpur, INDIA
Abstract: The study of neuron models under the influence of electromagnetic radiation is essential for understanding brain functions and developing treatments for neurological disorders. In this talk, we discuss the design of the discrete locally active memristor (DLAM) model and thoroughly analyze its characteristics. Further, this DLAM is utilize to introduce electromagnetic radiation into the reduced Chailvo neuron model (called the M-rChialvo model). We analyze the equilibrium points of the M-rChialvo model and discuss the dynamical characteristics, including phase portraits, stability analysis, forward and backward bifurcation, chaotic attractor, and multistability. This study reveals rich dynamical behaviors and diverse neuron firing patterns.
Additionally, we explore the behavior of a network of neurons governed by the proposed model within the ring-star network structure. Simulations highlight the emergence of various dynamical states, such as multi-chimera patterns, synchronization, and imperfect synchronization, under varying coupling strengths.”
42 - Combining Genetic Algorithms and Bifurcation Analysis to Link Bifurcation Structure and Evolutionary Objectives | Ece Kuru
43 - Effects of local gain modulation on probabilistic selection of actions | Elif Köksal-Ersöz
44 - Nonlinear plasticity models increase noise robustness and pattern retrieval capacity | Eddy Kwessi
45 - A Laminar Whole-brain Model of Serotonergic Psychedelics: Restoring Oscillatory Dynamics in Alzheimer’s Disease | Edmundo Lopez
46 - Structured Dynamics in The Algorithmic Agent | Giulio Ruffini
47 - Laminar Neural Mass Model for Representing Alzheimer's Disease Electrophysiological Biomarkers | Roser Sanchez Todo
48 - Breaking the flow: How a temporal gap restructures decision-making mechanisms | Encarni Marcos
Alejandro Sospedra, Santiago Canals, Encarni Marcos*
Decision making involves assessing potential options and their expected outcomes. In laboratory studies, this process is often examined through perceptual discrimination tasks, where sensory streams are presented sequentially. Temporal gaps, or pauses, within such sensory inputs can significantly alter the decision-making process, yet the precise impact of such gaps remains underexplored. In this study, we designed a task based on the original tokens task [2]. In brief, fifteen tokens were presented on a central circle, each sequentially jumping to one of two peripheral circles (targets). Participants were required to report which target they believed would have the majority of tokens by the trial’s end. Our task introduced two key modifications: tokens disappeared after they jumped [1] and half of the trials included a temporal gap, during which no information was presented. This design allowed us to explore how a temporal gap within sequences of perceptual stimuli influences the information weighting and subsequent choices. We show that, although decisions are made with less information following a temporal gap, accuracy remains comparable to conditions without gaps when stimulus dynamics enhance the salience of the post-gap token. Critically, the token presented immediately after the gap exerts a disproportionately strong influence on decision making, a phenomenon that persists even when the post-gap token lacks inherent saliency. These findings suggest that the influence of post-gap evidence is not dependent on its saliency. Traditional decision-making models, including the urgency gating model, fail to account for this behavior, highlighting the need to extend current models to capture the uneven weighting of information, particularly in the presence of temporal disruptions. By highlighting the distinctive role of post-gap evidence, our results offer new insights into how temporal gaps and the sequence of sensory input shape the decision-making process under complex conditions.
[1] Ferrucci, Genovesio & Marcos (2021) PLoS Comp Biol
[2] Cisek, Puskas, El-Murr (2009) J Neurosci”
49 - ToMATo clustering algorithm for spike sorting | Louise Martineau
50 - The Role of Synaptic Dynamics in the Dynamical Behavior of Mean-Field Models of Neural Populations | Ana Mayora-Cebollero
51 - Deep Learning for Dynamical Behavior Analysis of Excitable Cells | Carmen Mayora-Cebollero
52 - Analysis of a group of Hindmarsh-Rose neurons with directional connections | Noah Marko Mesić
53 - Correlated Excitatory & Inhibitory Noise Mitigates Hebbian Synaptic Drift | Michelle Miller
54 - Movement and reward are encoded in the cerebellar signals to the substantia nigra dopamine neurons | Farzan Nadim (presented by Horacio Rotstein)
55 - Learning synaptic properties from neural activity in a recurrent neural network model of insect olfaction | Maria Gabriela Navas Zuloaga
56 - Modelling dopamine dynamics: encoding predicted reward in the striatum enables adaptive decision-making within a spiking CBGT network | Alex O'Hare
57 - A preprocessing method of time series signals for the transfer entropy using the classical multi-dimensional scaling | Mayu Ohira
58 - Off-Equilibrium Fluctuation-Dissipation Theorem Paves the Way in Alzheimer’s Disease Research | Gustavo Patow
59 - Generalized dynamical phase reduction for stochastic oscillators | Alberto Pérez Cervera
60 - A dynamical system perspective on the mean-field limit of spatially structured recurrent neural networks | Louis Pezon
61 - Mittag-Leffler fractional integrals in stochastic models for neuronal dynamics | Enrica Pirozzi
62 - The path the brain takes – a closer look at the temporal evolution of functional states in a network control theoretical framework | Alina Podschun
63 - Sparse synchronization in networks of Excitatory and Inhibitory oscillators | Pau Pomés
64 - Thalamo-cortical Modelling to Advance Treatments of Tourette Syndrome | Angelica Pozzi
65 - Brain-wide calcium imaging in zebrafish and generative network modelling reveal cell-level functional network properties of seizure susceptibility | Wei Qin
66 - Resting-state EEG spatiotemporal changes observed in patients with depression: a theoretical insight | Ian Ramsey
67 - Multi-bump attractors in a neural field model with two firing thresholds | Helmut Schmidt
68 - A biophysical model of AMPA receptor dynamics | Brian Skelly
69 - Differences in spatial dynamics: effects of adaptation versus h-currents in a Wilson-Cowan field | Ronja Strömsdörfer
70 - Weighted sparsity regularization for solving the inverse EEG problem | Niranjana Sudheer
71 - Phase-Locking Induced by Transcranial Alternating Current Stimulation in a Balanced Network of Adaptive Exponential Integrate-and-Fire Neurons | Saeed Taghavi
72 - Global solutions with infinitely many blowups in a mean-field neural network | Thibaud Taillefumier
73 - Hawkes AutoRegressive processes, a new model for functional connectivity estimation: theoretical analysis | Leblanc Théo
74 - Balance between local and global connections enhance spatiotemporal complexity in a cortial network model | Lluc Tresseras
75 - Short-Term Plasticity modulates UP and DOWN cortical dynamics | Catalina Vich
76 - Generalized Tripod Gaits: A Topological Perspective on Neuron Networks | Rubén Vigara
77 - Noise induced phase transition in cortical neural field: the role of finite-size fluctuations | Gianni Valerio Vinci
78 - Characterization of a bio-realistic cortical column during the generation of alpha rhythm | Pablo Vizcaíno García
79 - Diversity-induced decoherence in a slow-fast neuron model | Marius Yamakou
80 - Coherent states in the interacting populations oh interneurons and pyramidal cells with ring nonlocal connections | Denis Zakharov
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