Mohammadreza Saghafi

Mohammadreza Saghafi

Ph.D Candidate at Virginia Tech |


email: saghafim [at] vt.edu

Posts by Collection

other-publications

The critical modulatory role of spiny stellate cells in seizure onset based on dynamic analysis of a neural mass model

Published:

This study challenges the traditional view that seizures are solely caused by excessive excitation or reduced inhibition in the brain. Instead, it highlights the paradoxical role of both glutamatergic (excitatory) and GABAergic (inhibitory) neurotransmitters in seizure generation. By extending an existing thalamocortical model to include spiny stellate (excitatory interneuron) cells, the research demonstrates how these neurons are crucial for generating preictal activity—the transitional state before seizures. Through bifurcation analysis and simulations, the model replicates a wide range of brain dynamics, including normal activity, preictal spikes, absence seizures, clonic seizures, and tonic seizures. The findings reveal that the cooperation between excitatory and inhibitory mechanisms, particularly the role of spiny stellate cells and thalamic inputs, governs the transition from normal brain states to seizures. This extended mathematical model provides deeper insights into seizure prediction and may help develop more effective therapeutic strategies.

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Perceptual Ratings Predict Speech Inversion Articulatory Kinematics in Childhood Speech Sound Disorders

Published:

This study provides empirical support for using inferred articulatory kinematic data to characterize perceptually rated speech sound errors in children with SSD. Articulatory kinematics were inferred using speech inversion neural networks. Findings demonstrate that inferred articulatory kinematic data were sensitive to both the phonetic category and magnitude of articulatory difference label using the PERCEPT Rating Scale, particularly for productions of /ɹ/. These results support the validation of speech inversion and the PERCEPT Rating Scale for speech science and clinical investigations of childhood SSD.

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portfolio

publications

All-Electric NASA N3-X Aircraft Electric Power Systems

Published in IEEE Transactions on Transportation Electrification, 2022

This article introduces a fully electric version of NASA’s N3-X aircraft powered by four electrochemical energy units. It proposes and analyzes three medium-voltage DC and AC power system architectures using modified power flow solvers, evaluates cable conductors based on aircraft dimensions, and confirms the systems meet planning criteria under normal and contingency conditions.

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Predictive Time-Series Analysis of Single-Qubit Quantum Circuit Outcomes for a Superconducting Quantum Computer: Forecasting Error Patterns

Published in IEEE ACCESS, 2025

In this work, we analyze and predict the output patterns of a single qubit quantum circuit by treating the results of repeated executions as a time series. Specifically, we collect measurement data from multiple runs of a quantum circuit and construct a time series from these observations. By training a predictive model, we aim to forecast future outcomes, providing insights into the error behavior of the quantum circuit. Additionally, we analyze time series data from two different circuits executed on the same qubit to investigate potential relationships and assess whether one dataset can be used to predict the other. Our findings reveal key characteristics of quantum circuit outputs, including stationarity, autocorrelation, seasonality, trends, linearity, and causality. The analysis highlights intriguing behaviors within the dataset. Furthermore, we evaluate multiple time series prediction methods and determine that XGBoost (Extreme Gradient Boosting) outperforms other approaches, demonstrating its effectiveness in accurately predicting quantum computing outputs in subsequent runs.”

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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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