Farhad Farkhondeh Tale Navi

Farhad Farkhondeh Tale Navi is an Assistant Professor in the Department of Cognitive Neuroscience at the University of Tabriz, Iran. With a Ph.D. in Cognitive Neuroscience and an engineering background, his research focuses on decision-making, memory systems, brain oscillations, and cognition in both animals and humans. He employs innovative methodologies such as closed-loop systems, machine learning, neuromodulation techniques, and computational neuroscience to advance understanding in brain and cognition research.

Key Research Interests:

1. Closed-loop Neuromodulation: Investigating how real-time feedback can be used to modulate brain activity for therapeutic or cognitive enhancement purposes.

2. Numerical Cognition: Exploring how the brain processes numerical information and the underlying neural mechanisms.

3. Decision Making: Studying the neural and cognitive processes involved in making decisions, particularly in high-stakes or emotionally charged contexts.

4. Computational Neuroscience: Applying mathematical models and computational techniques to understand brain function and behavior.

Notable Publications:

• Closed-loop modulation of the self-regulating brain: A comprehensive review on approaches and experimental designs in neuromodulation (Neuroscience, 2022).

• Time distortions induced by emotional faces: An event-related potential study examining how high-arousing emotional faces affect time perception (Psychological Research, 2023).

• Number-hand congruency effect: Behavioral and electrophysiological evidence supporting the interaction between numerical processing and motor responses (Acta Psychologica, 2023).

• Machine learning-based classification of risk-takers: Using resting-state EEG data to distinguish between risk-prone and risk-averse individuals (Brain and Behavior, 2023).

• Emotions and mental number line: Investigating how emotions influence accuracy and bias in numerical cognition (Cognition and Emotion, 2024).

Recent Projects:

• Adaptive closed-loop modulation of cortical theta oscillations: Insights into navigational decision-making (Brain Stimulation, 2024).

• Social dominance and neural dynamics: Exploring behavioral and neural correlates of social hierarchy and inhibitory control (Behavioural Brain Research, 2024).

• Training the brain to time: Neurofeedback of SMR–Beta1 rhythm and its impact on time perception (Experimental Brain Research, 2022).

Metrics:

• Citations: 43

• h-index: 4

Farhad Farkhondeh Tale Navi's work bridges the gap between engineering and cognitive neuroscience, leveraging advanced technologies to unravel the complexities of the human brain and behavior. His contributions to closed-loop neuromodulation and numerical cognition are particularly noteworthy, offering new insights into how we can harness brain activity for cognitive enhancement and therapeutic interventions.