Biology subjects

Vivekananda, U.

Publications and source records attributed to Vivekananda, U..

8 recordsLinked to original sources

bioRxiv2026

Human Hippocampal Theta-Gamma Phase-Amplitude Coupling Signals the Distance to Remembered Goals

In mammals, flexible navigation is believed to rely on a cognitive map of known locations supported by the hippocampus and surrounding medial temporal lobe structures. Hippocampal place cells typically exhibit spatial firing fields within a given environment. Moreover, their firing is modulated by the movement-related theta rhythm such that "theta sweeps" of place cell activity encode the trajectory towards a hidden reward location during goal-directed navigation. Here, we attempted to detect signatures of theta sweeps in the human hippocampal local field potential (LFP) recorded with intracranial EEG. Specifically, we hypothesised that sequences of locations along a planned trajectory encoded by distinct cell assemblies are associated with gamma activity at successive theta phases. To test this hypothesis, we asked N=9 patients with epilepsy to perform a spatial navigation task in desktop virtual reality while we recorded LFP signals from depth electrode contacts implanted across the medial temporal lobe. Consistent with our predictions, we found an increase in hippocampal theta-gamma phase-amplitude coupling, a decrease in gamma power, and theta phase precession of gamma activity as hidden goal locations were approached and the sequence of locations remaining to be traversed became shorter. This suggests that goal-directed hippocampal theta sweeps during navigation are reflected in LFP theta-gamma phase-amplitude coupling, and that these neural mechanisms of model-based planning are conserved across species.

neuroscience↗

bioRxiv2026

Intracranial Validation of Magnetoencephalography Across Oscillatory Frequency and Depth

Non-invasive, whole-brain neuroimaging methods such as functional magnetic resonance imaging, electroencephalography (EEG), and magnetoencephalography (MEG) are essential tools for studying the basis of human cognition in health and disease. MEG offers the opportunity to study neural activity at its intrinsic timescale, by recording the magnetic fields generated by electrical currents within the brain from outside the skull. Moreover, recently developed optically pumped magnetometers (OPMs) allow these recordings to take place in new settings, for example during naturalistic behaviour and in previously inaccessible populations. These breakthroughs have led to a shift in the neuroimaging landscape, with a global increase in the adoption of MEG. Crucially, however, the extent to which MEG recordings can measure different features of neural activity remains unclear. To address this issue, we leveraged a unique and rare dataset of concurrent MEG and intracranial EEG recordings from a cohort of epileptic patients. We found that group-level inferences of spontaneous oscillatory dynamics made with source-localised MEG, i.e. estimates of power and bursts, accurately reflected the underlying neural activity. As expected, the agreement was strongest for lower-frequency activity (delta, theta, and alpha) and superficial sources, and weakest in the gamma range. Crucially, however, MEG was also sensitive to deep structures: it captured oscillatory power and burst dynamics in the hippocampus, most robustly in the theta band. These findings demonstrate that MEG is sensitive to physiologically meaningful activity in cortical and subcortical regions and establish a foundation for the interpretation of future MEG studies across a wide range of research domains.

neuroscience↗

bioRxiv2026

An Implantable Wireless Battery-Free Selective Vagus Nerve Stimulator

Objective. Vagus nerve stimulation (VNS) is an established clinical therapy for drug-resistant epilepsy and other inflammatory conditions. However, off-target stimulation can produce unwanted side effects that limit therapeutic stimulation and hinder the development of new neuromodulation therapies. Selective VNS (sVNS) offers a strategy to reduce off-target organ activation; however, this approach is not available in humans, and no implantable or portable devices exist to trial sVNS in the clinical setup. This work aimed to design, manufacture, and validate an implantable wireless, battery-free stimulator with a selectively addressable output stage for targeted current delivery to specific regions of the human vagus nerve (VN). Approach. We developed a near-field communication-controlled, wirelessly powered, battery-free, temporary implantable multichannel stimulation device, compatible with a 15-channel sVNS cuff electrode (14 selective electrode pairs and one circumferential whole-nerve channel). The device was encapsulated for short-term implantation and evaluated through benchtop characterisation, accelerated ageing, and validation in an acute porcine and a pilot human study. Main result. The sVNS device was evaluated in a porcine (n = 4) trial and a first-in-human pilot study (n = 1). Selective bradycardia of 23.28 {+/-} 12.91% was observed in pigs and 7.5% in the human participant. In the human, a clear separation of bradycardic and tachycardic effects was observed, with additional selectivity in laryngeal activity. Cardiac and laryngeal responses were separated by 231{degrees} around the circumference of the nerve. Significance. This work demonstrates the feasibility of wireless battery-free sVNS for cardiac applications using a temporary implantable device. Geometrically selective stimulation has the potential to improve therapeutic efficacy while reducing stimulation-related side effects, and may facilitate future therapies for heart failure and other autonomic disorders.

bioengineering↗

bioRxiv2026

Fast-ripples are emergent properties of neuronal networks

Fast-ripples (250-500 Hz) have been proposed as a promising biomarker in epilepsy, but their specificity remains unclear. In particular, it is uncertain whether they reflect chance coincident neural activity or distinctly generated pathological entities. We combined in silico simulations, neuronal cultures, the intra-hippocampal kainate rat model of hippocampal epilepsy, and human microwire recordings to investigate whether fast-ripples occur more frequently than expected by the chance aggregation of action potentials. Our simulations showed that chance aggregation can generate fast-ripples and that their incidence changes depending on brain state, an observation that we confirmed in our rodent data. The likelihood of exceeding chance depended on biological system complexity and vigilance state: fast-ripples in neuronal cultures did not surpass chance levels, whereas those in awake - but not sleeping - rodents did. Similarly, the incidence of fast-ripples in awake human recordings was ~30% greater than expected by chance. As such, our findings suggest that most fast-ripples reflect stochastic network activity rather than distinctly generated pathological entities. This work does not rule out FRs as potential indicators of epileptogenic tissue, but it does challenge prevailing assumptions about their generation and specificity. Their higher prevalence in epileptogenic tissue is likely primarily due to increased excitation and/or neural synchronization, rather than peculiar abnormalities in network behavior.

neuroscience↗

bioRxiv2026

The Extremely Brilliant Brain: An Isotropic Microscale Human Brain Dataset

We present an isotropic 7.72 {micro}m/voxel post-mortem human brain dataset acquired using Hierarchical Phase-Contrast Tomography (HiP-CT) at the ESRF Extremely Brilliant Source, beamline BM18. This fills a critical gap between whole-brain MRI at 100 {micro}m resolution and serial-section histological reconstructions at 20 {micro}m or finer. HiP-CT contrast, derived from X-ray phase shifts, enables rich 3D visualisation of complex neuroanatomy including white-matter bundles, microvasculature, and sub-nuclei. We provide open-source workflows for online data exploration, subvolume download, segmentation, and reintegration of analyses into the full dataset. We demonstrate the potential of this resource by tracing vasculature over long distances, segmenting nuclei, and extracting whitematter orientations with 3D structure-tensor analysis. High-resolution human brain datasets are transformative for quantitative neuroanatomy, circuit mapping, and validation of clinical imaging; this openly available resource is a critical step for global access to next-generation multiscale brain imaging.

neuroscience↗

bioRxiv2026

Electrophysiological Correlates of Reinforcement Learning in the Human Ventral Tegmental Area

The ventral tegmental area (VTA) is the principal source of dopaminergic input to the human prefrontal cortex and is hypothesised to play a central role in reward-based learning. However, direct electrophysiological evidence in humans has been lacking. Here, using intracranial recordings obtained during an instrumental learning task in patients undergoing deep brain stimulation surgery for chronic cluster headache (n=13), we show that VTA local field potentials selectively encode rewarding outcomes compared with losses or neutral outcomes independently of whether behavioural learning occurred. In a subset of participants (n= 8) who learned to prefer a high-reward option, VTA responses to unexpected rewards were larger than to expected rewards. In two participants who sufficiently explored both options, VTA activity reflected the expected value of the chosen option during decision-making. These findings provide direct electrophysiological evidence that the human VTA encodes reward-related signals consistent with reinforcement learning mechanisms described in animal models.

neuroscience↗

bioRxiv2026

Impaired Associative Memory, Inference, and Theta Dynamics in Postictal Psychosis of Epilepsy

Postictal psychosis (PIP) is a severe complication occurring in 2% of people with epilepsy (PWE) whose underlying pathophysiology remains poorly understood. Although historically considered separate from other forms of psychosis, newer evidence demonstrates a shared genetic susceptibility. People with schizophrenia are typically impaired at both associative learning and inferring connections between overlapping associations. Successful associative encoding, retrieval, and inference can each be predicted by changes in frontotemporal theta band activity, which is impaired in rodent models and people with schizophrenia. Here, we recorded high-density scalp EEG from PWE with history of PIP and well-matched control participants while they undertook a memory inference task. We found that associative memory and inference were both impaired in the PIP group, despite no difference in item recognition. Moreover, we found disrupted theta activity during memory encoding and the retrieval of inferred associations in PWE with PIP that likely originated from the medial temporal and frontal lobes. These results suggest a pattern of behavioural deficits and altered neural dynamics common to both PIP and schizophrenia. Interpreted in conjunction with previous genetic studies, they may reflect shared neural mechanisms contributing to psychopathology in both conditions and argue that PIP is a model of more general psychoses.

neuroscience↗

bioRxiv2019

Theta power and theta-gamma coupling support spatial memory retrieval

Hippocampal theta oscillations have been implicated in spatial memory function in both rodents and humans. What is less clear is how hippocampal theta interacts with higher frequency oscillations during spatial memory function, and how this relates to subsequent behaviour. Here we asked ten human epilepsy patients undergoing intracranial EEG recording to perform a desk-top virtual reality spatial memory task, and found that increased theta power in two discrete bands ( low 2-5Hz and high 6-9Hz) during cued retrieval was associated with improved task performance. Similarly, increased coupling between low theta phase and gamma amplitude during the same period was associated with improved task performance. These results support a role of theta oscillations and theta-gamma phase-amplitude coupling in human spatial memory function.

neuroscience↗