Research

1. Stress, Emotion & Social Neuroscience

We investigate the neural and physiological mechanisms underlying stress, emotion, social interaction, and interpersonal behaviour using fMRI, EEG, fNIRS, HRV, and computational approaches.

Key Publications

Shadaydeh et al. (2025). Directionality of Interpersonal Neural Influence in Functional Near-Infrared Spectroscopy Hyperscanning. European Journal of Neuroscience, 62, e70252.
De Felice et al. (2025). Relational Neuroscience: Insights from hyperscanning research. Neuroscience & Biobehavioral Reviews, 169, 105979.
Fiederer et al. (2025). Resting-state functional connectivity within the reward system mediates subcortical integration during erotic stimulus processing. World Journal of Biological Psychiatry.
Zepeda et al. (2023). Trait anxiety is related to Nx4's efficacy on stress-induced changes in amygdala-centered resting-state functional connectivity. BMC Neuroscience.
Chand et al. (2022). Nx4 modulated resting-state functional connectivity between amygdala and prefrontal cortex in a placebo-controlled crossover trial. Brain Connectivity, 12, 812–822.
Chand et al. (2020). Heart Rate Variability as an Index of Differential Brain Dynamics at Rest and After Acute Stress Induction. Frontiers in Neuroscience, 14, 645.
Kochhar et al. (2026). Personalized Stress Detection Through Reinforcement Learning Based Domain Adaptation. IEEE ISBI.
Tang et al. (2025). Evaluation of the Human-Like Robotic Touch: A User Study. ICORR.

2. Clinical Neuroimaging & Computational Neuroscience

We use multimodal neuroimaging and computational approaches to investigate alterations in brain structure, functional connectivity, network dynamics, and neurochemistry associated with psychiatric and neurological conditions.

Key Publications

Bi et al. (2026). Visual cortical functional connectivity alterations and their associations with psychotic symptoms in early-onset bipolar disorder. Journal of Affective Disorders.
Bi et al. (2026). White matter alterations in the corpus callosum and visual cortical regions associated with depressive and psychotic symptoms in early-onset bipolar disorder. Psychiatry and Clinical Neurosciences.
Cao et al. (2025). White matter subgroups of bipolar II depression associate with inflammation, psychiatric symptoms, and childhood emotional maltreatment. Nature Mental Health.
Cao et al. (2025). Association between peripheral inflammation and body mass index on white matter integrity and free water in bipolar II depression. Brain, Behavior, and Immunity, 128, 208–218.
Troll et al. (2025). Altered corticostriatal connectivity in long-COVID patients is associated with cognitive impairment. Psychological Medicine, 55, e49.
Cao et al. (2025). White matter microstructural and inflammation-based subgroups in bipolar disorder II depression differentiate in depressive and psychotic symptoms. Journal of Affective Disorders, 368, 493–502.
Xiao et al. (2024). Interleukin-1β moderates relationships between middle frontal-mACC/insular connectivity and depressive symptoms in bipolar II depression. Brain, Behavior, and Immunity, 120, 44–53.
Javaheripour et al. (2023). Altered brain dynamic in major depressive disorder: State and trait features. Translational Psychiatry, 13, 261.
Guo et al. (2023). Decreased inter-hemispheric functional connectivity in the insula is associated with illness duration in recurrent depression. Journal of Affective Disorders, 329, 88–95.
Li et al. (2022). Differential association between local neurotransmitter levels and whole-brain resting-state functional connectivity in two distinct ACC subregions. Human Brain Mapping, 43, 2833–2844.
Javaheripour et al. (2021). Altered resting-state functional connectome in major depressive disorder: A mega-analysis from the PsyMRI consortium. Translational Psychiatry, 11.

3. Neuromodulation, Neurotechnology & Rehabilitation

We investigate how targeted interventions and emerging neurotechnologies modify brain function and support neurological, cognitive, and behavioural rehabilitation. Our work spans MR-guided focused ultrasound, pharmacological modulation, BCI, rehabilitation robotics, and virtual reality.

Key Publications

Purrer et al. (2025). Quantitative and qualitative tremor evaluation after MR-guided focused ultrasound thalamotomy. Frontiers in Neurology, 16, 1594382.
Sen et al. (2023). The effect of a single S-Ketamine infusion on resting-state functional connectivity within the modulatory pathway of the startle reflex and its affective modulation. Scientific Reports, 13, 13323.
Danyeli et al. (2023). Association of delayed changes in glutamate levels and functional connectivity with the immediate network effects of S-ketamine. Translational Psychiatry, 13, 60.
Sen et al. (2024). Ketamine-induced pleasant but not unpleasant dissociation is linked to the functional connectivity profile of the posteromedial cortex. PsyArXiv.
Chand et al. (2022). Nx4 modulated resting-state functional connectivity between amygdala and prefrontal cortex. Brain Connectivity.
Chand et al. (2021). EEG revealed improved vigilance regulation after stress exposure under Nx4. IBRO Neuroscience Reports.
Chand, Verma, Gupta, & Kalsi (2025). Assistive and Rehabilitative Brain–Computer Interfaces: Innovations in Patient Care. Springer Nature.
Kalsi, Chand, Panda, & Upadhyay (2026). Harnessing Virtual Reality for Advancing Innovations in Neurocognitive Rehabilitation. Routledge International Handbook of Neurocognitive Rehabilitation.
Tang et al. (2025). Evaluation of the Human-Like Robotic Touch: A User Study. ICORR.

4. Cognition, Memory & Brain–Body Dynamics

We investigate how memory, attention, time perception, stress, emotion, interoception, and physiological states interact to shape cognition and behaviour. Current work includes prospective memory, working-memory load, subjective time perception, stress regulation, and contemplative practices.

Current work: Time perception and interoception (Mithi Shukla); prospective memory and stress (Rachana Belal); yoga and meditation (Karan Rawat).

Key Publications

Chand et al. (2020). Heart Rate Variability as an Index of Differential Brain Dynamics at Rest and After Acute Stress Induction. Frontiers in Neuroscience, 14, 645.
Chand et al. (2021). EEG revealed improved vigilance regulation after stress exposure under Nx4. IBRO Neuroscience Reports, 11, 175–182.
Krylova et al. (2025). Comprehensive mitigation of peripheral and central stress responses by Nx4: Insights from EEG and heart rate variability in post-stress resting state. Human Psychopharmacology: Clinical and Experimental.
Palla et al. (2025). Evaluation of the Biopsychosocial Model of Health among Emerging Adults. BMC Psychology.
Das, Lindquist, Chand, & Junnarkar (2025). Analysing Eyewitness Recognition Accuracy using Event-Related Potential and Eye-tracking Analysis: An Experimental Investigation.
Khan, Kushvah, & Chand (2016). Role of inhibitory cognitive control in creative performance: An ERP Study. IOP2016.

5. Human–AI Interaction, Decision-Making & Digital Behaviour

We study how AI and emerging technologies influence human judgment, behaviour, trust, agency, learning, and social interaction. Current work examines human–AI disagreement, moral decision-making, acceptance of AI-based mental-health support, responsible AI in education, and human responses to intelligent and robotic systems.

Current work: Moral cognition and human–AI decision-making (Vidushi Choudhary); AI, education and digital divides (Divya Diksha).

Key Publications

Choudhary et al. (2026). Adaptive emotion regulation and coping strategies as correlates of AI-based mental health support acceptability among university students. Research Square.
Tang et al. (2025). Evaluation of the Human-Like Robotic Touch: A User Study. IEEE International Conference on Rehabilitation Robotics (ICORR), 1353–1360.
Chand, Weiß, & Gutzeit (2024). A Comment on identity effects in social media—Taylor et al. (2023). I4R Discussion Paper Series.
Chand, Nair, Srinivasu, & Kumar (2025). Prospects and Challenges in Decoding Consumer Behaviour using Neurotechnology. In Artificial Intelligence Applications for Brain-Computer Interfaces.
Chand, Verma, Gupta, & Kalsi (2025). Assistive and Rehabilitative Brain–Computer Interfaces: Innovations in Patient Care. Springer Nature.
Kalsi, Chand, Panda, & Upadhyay (2026). Harnessing Virtual Reality for Advancing Innovations in Neurocognitive Rehabilitation. Routledge International Handbook of Neurocognitive Rehabilitation.

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