Biology subjects

Nierula, B.

Publications and source records attributed to Nierula, B..

8 recordsLinked to original sources

bioRxiv2026

Expectation Shapes Neural Preparation for AI-generated and Real Image Processing: Evidence from EEG

AbstractAI-generated images, videos, and news have become an inseparable part of daily life, leading to increasing skepticism toward online information. Understanding how expectations about the presence of AI-generated content influence perception is crucial for elucidating the underlying neural mechanisms and facilitating the generation of naturalistic avatars. In this study, we analyzed an existing EEG dataset (N = 29) in which participants viewed emotional facial photographs of only real individuals while being informed that upcoming faces were either real ("REAL") or AI-generated ("FAKE"). We examined pre-stimulus oscillatory activities in the one-second EEG interval before stimulus onset and found significantly lower alpha power when participants expected "FAKE" compared to "REAL" faces. This effect was region-specific, particularly in right occipito-parietal and temporo-parietal regions, as identified by both sensor- and source- level analyses. In addition, the modulation effect between pre-stimulus alpha activity and post-stimulus event-related potentials (ERPs) was measured. A significant correlation between changes in late positive potential (LPP) amplitudes and pre-stimulus alpha power was observed exclusively for "FAKE" smiling faces, consistent with our previous findings. These results suggest that AI-related expectations modulate neural preparatory states, with lower alpha activity presumably reflecting increased attentional demands for stimuli believed to be artificially generated. This study demonstrates that top-down beliefs systematically shape both pre- and post-stimulus neural dynamics, providing new insights into how cognitive expectations bias perceptual processing, with implications for understanding human-AI interaction and improving the design and evaluation of AI- generated content in real-world contexts.

neuroscience↗

bioRxiv2026

Decoding peripheral stimulation from cortical and spinal recordings reveals complementary sensorimotor information

The somatosensory system encodes peripheral inputs through a sequence of ascending neural relays spanning spinal, subcortical and cortical levels. While multivariate decoding of electroencephalography (EEG) signals has demonstrated that cortical activity contains fine-grained information about somatosensory stimuli, the extent to which earlier processing stages contribute additional, non-redundant information remains unclear. To address this gap, we investigated a dataset comprising peripheral sensory stimulation and mixed stimulation (i.e., stimulation engaging both sensory and motor fibers). We assessed whether stimulation characteristics can be decoded from spinal recordings using high-density electrospinography (ESG), and whether combining ESG with EEG enhances decoding performance. Decoding accuracy varied systematically with both stimulation type and signal modality. ESG was the most informative signal for mixed and mixed vs sensory discrimination, reaching an average accuracy of [~]98%, while EEG provided a relative advantage for purely sensory tasks, though absolute accuracy remained more modest for both modalities. Critically, combining the two modalities together consistently matched or outperformed either one, used alone, across all conditions, with gains most pronounced for mixed vs sensory discrimination. Multi-subject generalization improved progressively with training-set size, rising to [~]88% with 15 training subjects for mixed classification, suggesting that subject-independent decoding of motor intent may be achievable when models are trained on a larger number of subjects. Taken together, these results establish that spinal ESG signals carry decodable information about peripheral stimulation that is complementary to and not redundant with cortical EEG. This finding supports a multilevel framework for decoding sensorimotor processing in humans and motivates the development of dual-modality brain-machine interfaces that leverage both cortical and spinal signals to improve the control of neurostimulation and assistive devices.

bioengineering↗

bioRxiv2025

Expectation effects on repetition suppression in nociception

Repetition suppression, the reduced neural response upon repeated presentation of a stimulus, can be explained by models focussing on bottom-up (i.e. adaptation) or top-down (i.e. expectation) mechanisms. Predictive coding models fall into the latter category and propose that repetitions are expected and therefore elicit smaller prediction error responses. While studies in the visual and auditory domain provide some support for such models, in nociception evidence remains inconclusive, despite the substantial influence expectations exert on pain perception. To assess expectation effects on repetition suppression in nociception, we developed a paradigm in which healthy volunteers received brief CO2 laser stimuli, while we acquired electroencephalographic (EEG) and peripheral physiological data. Importantly, laser stimuli could be either repeated after one second or not be repeated, with the probability of repetitions manipulated in a block-wise fashion, such that repetitions were either expected or unexpected. We observed repetition suppression in laser-evoked potentials as well as laser-induced gamma band oscillations, but not in laser-induced desynchronisations in the alpha and beta band. Critically, neither these EEG responses, nor the peripheral physiological data showed significant differences between the expectation conditions, with Bayesian analyses mostly providing evidence for an absence of effects. This indicates that repetition suppression to brief nociceptive laser stimuli is not driven by top-down factors, but rather mediated by other adaptation processes. While this does not preclude an influence of predictive coding models in nociception, it suggests that when the nervous system receives highly precise input, its responses are less susceptible to influence from expectations.

neuroscience↗

bioRxiv2024

Somatosensory high frequency oscillations across the human central nervous system

Information transmission in the central nervous system (CNS) relies on the propagation of action potentials (neuronal spikes), traditionally thought to be inaccessible with electroencephalography (EEG). Converging evidence from human and animal recordings however demonstrates that high frequency oscillations (HFOs) in EEG recordings represent neuronal population spiking, complementing standard low-frequency EEG recordings in cortex. Here, we developed an approach to simultaneously record HFOs to somatosensory stimulation across the entire human CNS noninvasively: from spinal over subcortical to cortical stages. Our approach provides a detailed temporal and spectral characterization of HFOs at each CNS level, delineating how they evolve across the somatosensory processing hierarchy. Critically, we show that low and high frequency electrophysiological responses represent at least partly independent processing channels across the CNS. We thus demonstrate the feasibility of studying the full spectrum of neuronal information processing across the CNS, offering a multi-level window into human neurophysiology in health and disease.

neuroscience↗

bioRxiv2024

Evaluating noise correction approaches for non-invasive electrophysiology of the human spinal cord

The spinal cord is a vital component of the central nervous system for the processing of sensorimotor information transmitted between the body and the brain. Electrospinography (ESG) is the most accessible non-invasive technique for recording spinal signals in humans, but the vast and detrimental impact of physiological noise (mostly of cardiac nature) has prevented widespread adoption. Here, we aim to address this issue by examining various denoising algorithms for cardiac artefact reduction - including principal component analysis-based techniques (PCA), independent component analysis-based approaches (ICA) and signal space projection (SSP). We observed that in situations where large numbers of spinal electrodes are used, SSP offers the best results in terms of balancing the removal of harmful noise and preserving neural information of interest. In cases where only a small number of electrodes are available, an approach based on PCA is deemed helpful. Approaches based on ICA were found to be unsuitable for cardiac artefact removal in ESG, due to a suboptimal balance of artefact removal and signal preservation. Finally, we also approached this issue from a signal-enhancement perspective and observed that in cases where extensive electrode arrays are used in the context of task-based designs, a spatial filtering technique based on canonical correlation analysis (CCA) reveals clear evoked spinal potentials even with single-trial resolution. Taken together, there are several appropriate algorithms for physiological noise removal in ESG, rendering this an accessible and easy-to-use technique for non-invasive assessments of human spinal cord function.

neuroscience↗

bioRxiv2022

Non-invasive multi-channel electrophysiology of the human spinal cord - assessing somatosensory processing from periphery to cortex

The spinal cord is of fundamental importance for integrative processing in brain-body communication, yet routine non-invasive recordings in humans are hindered by vast methodological challenges. Here we overcome these challenges by developing an easy-to-use electrophysiological approach based on high-density multi-channel spinal recordings combined with multivariate spatial-filtering analyses. These advances enable a spatiotemporal characterization of spinal cord responses and demonstrate a sensitivity that permits assessing even single-trial responses. To furthermore enable the study of integrative processing along the neural processing hierarchy in somatosensation, we expand this approach by simultaneous peripheral, spinal and cortical recordings and provide direct evidence that bottom-up integrative processing occurs already within the spinal cord and thus after the first synaptic relay in the central nervous system. Finally, we demonstrate the versatility of this approach by providing non-invasive recordings of nociceptive spinal cord responses during heat-pain stimulation. Beyond establishing a new window on human spinal cord function at millisecond timescale, this work provides the foundation to study brain-body communication in its entirety in health and disease.

neuroscience↗

bioRxiv2022

Cortical response variability is driven by local excitability changes with somatotopic organization

Identical sensory stimuli can lead to different neural responses depending on the instantaneous brain state. Specifically, neural excitability in sensory areas may shape the brains response already from earliest cortical processing onwards. However, whether these dynamics affect a given sensory domain globally or occur on a spatially local level is largely unknown. We studied this in the somatosensory domain of 38 human participants with EEG, presenting stimuli to the median and tibial nerves alternatingly, and testing the co-variation of initial cortical responses in hand and foot areas, as well as their relation to pre-stimulus oscillatory states. We found that amplitude fluctuations of initial cortical responses to hand and foot stimulation - the N20 and P40 components of the somatosensory evoked potential (SEP), respectively - were not related, indicating local excitability changes in primary sensory regions. In addition, effects of pre-stimulus alpha (8-13 Hz) and beta (18-23 Hz) band amplitude on hand-related responses showed a robust somatotopic organization, thus further strengthening the notion of local excitability fluctuations. However, for foot-related responses, the spatial specificity of pre-stimulus effects was less consistent across frequency bands, with beta appearing to be more foot-specific than alpha. Connectivity analyses in source space suggested this to be due to a somatosensory alpha rhythm that is primarily driven by activity in hand regions while beta frequencies may operate in a more hand-region-independent manner. Altogether, our findings suggest spatially distinct excitability dynamics within the primary somatosensory cortex, yet with the caveat that frequency-specific processes in one sub-region may not readily generalize to other sub-regions.

neuroscience↗

bioRxiv2019

Agency and responsibility over virtual movements controlled through different paradigms of brain-computer interface

Agency is the attribution of an action to the self and is a prerequisite for experiencing responsibility over its consequences. Here we investigated agency and responsibility by studying the control of movements of an embodied avatar, via brain computer interface (BCI) technology, in immersive virtual reality. After induction of virtual body ownership by visuomotor correlations, healthy participants performed a motor task with their virtual body. We compared the passive observation of the subjects own virtual arm performing the task with (1) the control of the movement through activation of sensorimotor areas (motor imagery) and (2) the control of the movement through activation of visual areas (steady-state visually evoked potentials). The latter two conditions were carried out using a brain-computer interface (BCI) and both shared the intention and the resulting action. We found that BCI-control of movements engenders the sense of agency, which is strongest for sensorimotor areas activation. Furthermore, increased activity of sensorimotor areas, as measured using EEG, correlates with levels of agency and responsibility. We discuss the implications of these results for the neural bases of agency, but also in the context of novel therapies involving BCI and the ethics of neurotechnology.\n\nKey points summaryO_LIWe induced embodiment of a virtual body and its movements were controlled by two different BCI paradigms - one based on signals from sensorimotor versus one from visual cortical areas.\nC_LIO_LIBCI-control of movements engenders agency, but not equally for all paradigms.\nC_LIO_LICortical sensorimotor activation correlates with agency and responsibility.\nC_LIO_LIThis has significant implications for neurological rehabilitation and neuroethics.\nC_LI

neuroscience↗