arXiv subjects

Mojtaba Madadi Asl

Publications and source records attributed to Mojtaba Madadi Asl.

4 recordsLinked to original sources

arXiv2026

Information, entropy and the paradox of choice: A model for understanding human choice behavior

Choice overload occurs when individuals feel overwhelmed by excessive alternatives during decision making. Although larger choice sets are often assumed to be more satisfying, behavioral evidence reveals an inverted U-shaped relationship between satisfaction and choice set size. However, quantitative frameworks linking information processing to choice satisfaction remain underdeveloped. Here, we develop a simple framework based on relative entropy and effective information to explain this behavior. We propose that satisfaction depends on the probability of finding an ideal option within a choice set and is determined by the informational structure of preferential choice probabilities relative to a baseline state of indifference. Small to moderately sized sets allow efficient comparison and identification of preferred options, thereby maximizing both effective information and satisfaction. As the number of alternatives increases, cognitive limitations increase uncertainty, leading to reduced effective information and satisfaction. This mechanism naturally produces the experimentally observed inverted U-shaped dependence of satisfaction on choice set size. Behavioral experiments across varying choice set sizes closely matched model predictions, suggesting that effective information provides a robust metric for choice satisfaction. These findings offer a principled theoretical account of the paradox of choice and carry broader implications for consumer psychology and human choice behavior.

physics.soc-ph↗

arXiv2026

Synaptic delays modulate population phase and amplitude responses in oscillatory excitatory-inhibitory networks

Synaptic delays are fundamental determinants of neuronal communication and can profoundly influence the emergence and stability of cortical oscillations. Although their role in shaping network synchronization is well established, how synaptic delays regulate the collective response of neuronal populations to transient perturbations remains poorly understood. Here, we investigate the effects of synaptic delays on the phase and amplitude responses of oscillatory activity in a conductance-based excitatory-inhibitory spiking network operating in the pyramidal-interneuron gamma (PING) regime. By systematically varying the synaptic delay and applying brief external perturbations to the excitatory population, inhibitory population, or the entire network, we computed network phase response curves (nPRCs) and network amplitude response curves (nARCs) to quantify changes in oscillation timing and population coherence. Increasing synaptic delay slowed network oscillations while enhancing population synchrony, demonstrating a trade-off between oscillation frequency and coherence. Excitatory perturbations produced relatively robust phase responses across delays but exhibited a pronounced delay-dependent reduction in amplitude enhancement. In contrast, inhibitory perturbations generated substantially stronger delay-dependent modulation of both phase resetting and amplitude suppression, whereas whole-network stimulation combined features of both excitatory and inhibitory responses. Taken toghether, these findings identify synaptic delay as a key parameter governing the balance between phase resetting and amplitude modulation and provide a computational framework for understanding delay-dependent control of oscillatory brain networks.

q-bio.NC↗

arXiv2026

Phase- and amplitude-dependent control of synchronization in excitatory-inhibitory networks via pulsed stimulation

Oscillatory neuronal networks exhibit complex collective responses to external perturbations that depend on both the intrinsic network dynamics and the timing of stimulation. Although phase response curves (PRCs) have become a standard tool for characterizing these responses, phase resetting alone provides an incomplete description of how transient perturbations reshape collective activity. Here, we investigate the dynamics of a balanced excitatory-inhibitory network of exponential integrate-and-fire (EIF) neurons subjected to phase-targeted current pulses. By jointly analyzing the network phase response curve (nPRC), network amplitude response curve (nARC), and changes in the population synchrony, we establish a framework for characterizing collective network responses in terms of phase, amplitude, and synchronization. We show that identical stimulation pulses can either enhance, suppress, or leave network synchronization unchanged depending solely on their phase within the oscillation cycle, revealing distinct synchronizing and desynchronizing windows. The nARC further identifies robust phase intervals that maximize suppression of oscillatory activity and provide optimal targets for repeated stimulation. Successive perturbations progressively desynchronize the network activity while continuously reshaping the phase, amplitude, and synchrony response landscapes, driving the network toward a modified dynamical state without altering the optimal stimulation phase. These cumulative effects remain robust across stimulation intensities, inhibitory synaptic time constants, and independent network realizations. Our results demonstrate that phase, amplitude, and synchronization represent complementary dynamical dimensions of oscillatory neuronal networks and provide general principles for the state-dependent control of collective dynamics through phase-targeted perturbations.

q-bio.NC↗

arXiv2025

A theoretical framework to explain non-Nash equilibrium strategic behavior in experimental games

Conventional game theory assumes that players are perfectly rational. In a realistic situation, however, players are rarely perfectly rational. This bounded rationality is one of the main reasons why the predictions of Nash equilibrium in normative game theory often diverge from human behavior in real experiments. Motivated by the Boltzmann weight formalism, here we present a theoretical framework to predict the non-Nash equilibrium probabilities of possible outcomes in strategic games by focusing on the differences in expected payoffs of players rather than traditional utility metrics. In this model, bounded rationality is parameterized by assigning a temperature to each player, reflecting their level of rationality by interpolating between two decision-making regimes, i.e., utility maximization and equiprobable choices. Our framework predicts all possible joint strategies and is able to determine the relative probabilities for multiple pure or mixed strategy equilibria. To validate model predictions, by analyzing experimental data we demonstrated that our model can successfully explain non-Nash equilibrium strategic behavior in experimental games. Our approach reinterprets the concept of temperature in game theory, leveraging the development of theoretical frameworks to bridge the gap between the predictions of normative game theory and the results of behavioral experiments.

physics.soc-ph↗