Biology subjects

Zabeh, E.

Publications and source records attributed to Zabeh, E..

8 recordsLinked to original sources

bioRxiv2026

NeuralFieldManifold: Uncovering the Manifold Geometry of Local Field Potentials

Manifold geometry has become a powerful framework for understanding how the brain organizes high-dimensional neural activity into compact, interpretable structure. To date, however, most theoretical and methodological advances in neural manifold analysis have focused on spiking activity, leaving unresolved a fundamental question: What are the geometric principles governing the dynamics of local field potentials (LFPs); population level signals reflecting integrated subthreshold and suprathreshold neural activity that are broadly integral to clinical and brain-computer interface settings. Here, we establish, analytically and empirically, that the lag-embedded dynamics of LFP signals lie on a low-dimensional K-torus, where K directly relates to sustained oscillatory modes present in the signal. Modeling LFPs as bounded autoregressive processes, we show that each oscillatory component contributes an independent circular degree of freedom, while aperiodic 1/f structure and noise contribute only geometric thickness around the manifold without altering its topology. To apply this theory to real nonstationary recordings, we introduce DeepLagField, a physics-informed network that jointly estimates time-varying AR structure and effective model order, with formal guarantees that local toroidal geometry is preserved despite non-stationary nature of neuronal processes. Persistent homology analysis on real recordings reveals topological signatures consistent with the predicted toroidal Betti numbers in primate V1 LFP, rodent hippocampal LFP, and mouse cortical EEG, with varying degrees of agreement across recordings and temporal windows. Crucially, decoding analyses across three distinct neural datasets demonstrate that these geometric structures are not merely descriptive but capture behaviorally relevant information rivaling conventional spectral features. Together, these findings establish a theoretically grounded and empirically validated geometric framework for neural field analysis, extending the manifold perspective beyond spiking activity and offering a complementary language to spectral analysis for understanding and translating population dynamics across neural modalities.

neuroscience↗

bioRxiv2025

Hidden Spirals Reveal Neurocomputational Mechanisms of Traveling Waves in Human Memory

While traveling waves are often described as planar propagations across cortex, recent theoretical work predicts that more complex spatial patterns, including spiral dynamics, could organize large-scale neural computations but remain difficult to detect in the human brain. To investigate this, we analyzed direct brain recordings from humans performing a working memory task. To characterize traveling wave patterns, we used independent component analysis, and showed that traveling waves propagated along the cortex in complex spatial patterns that correlated with behaviors such as memory encoding, maintenance, and retrieval. We then developed a novel computational framework based on coupled phase oscillators to model these distinct wave patterns. This computational approach revealed hidden spirals that were not visible in the original recordings. The center of these hidden spirals shifted across the cortex to distinguish separate behavioral states, such as memory encoding and retrieval. Together, these findings reveal that cortical traveling waves are governed by latent spiral attractor dynamics and suggest that rotating wave architectures provide a fundamental neurocomputational mechanism for flexible human memory processing.

neuroscience↗

bioRxiv2025

Cholinergic blockade reveals role for human hippocampal theta in encoding but not retrieval

Cholinergic dysfunction is a hallmark of Alzheimers disease and other memory disorders. Yet, the neurophysiological mechanisms linking cholinergic signaling to memory remain poorly understood. In this study, we administered scopolamine, a muscarinic cholinergic antagonist, to neurosurgical patients with intracranial electrodes as they performed an associative recognition memory task. When scopolamine was present at encoding, we observed disruptions to hippocampal slow theta oscillations (2-4 Hz), with selective impairments to recollection-based memory. However, when scopolamine was present during retrieval alone, we observed disruptions to slow theta without impaired memory performance. These disruptions included dose-dependent reductions in theta power, theta phase reset, and encoding-retrieval pattern reinstatement. Together, our results challenge the notion that theta oscillations are necessary for memory retrieval, and instead suggest that theta universally reflects an encoding-related neural state. These findings motivate updates to current models of acetylcholines role in memory and may inform future therapies targeting rhythmic biomarkers of memory dysfunction.

neuroscience↗

bioRxiv2024

Recurrent Connectivity Shapes Spatial Coding in Hippocampal CA3 Subregions

Stable and flexible neural representations of space in the hippocampus are crucial for navigating complex environments. However, how these distinct representations emerge from the underlying local circuit architecture remains unknown. Using two-photon imaging of CA3 subareas during active behavior, we reveal opposing coding strategies within specific CA3 subregions, with proximal neurons demonstrating stable and generalized representations and distal neurons showing dynamic and context-specific activity. To test the causal role of excitatory connectivity in neural computation, we employed a genetic manipulation approach in which local disruption of glutamatergic synaptic transmission impaired context-specific spatial coding in distal CA3. Aligned with these experimental results, we show in artificial neural network models that varying the recurrence level causes these differences in coding properties to emerge. We confirmed the contribution of recurrent connectivity to functional heterogeneity by characterizing the representational geometry of neural recordings and comparing it with theoretical predictions of neural manifold dimensionality. Our results indicate that local circuit organization, particularly recurrent connectivity among excitatory neurons, plays a key role in shaping complementary spatial representations within the hippocampus. HighlightsO_LIProximodistal CA3 subregions implement complementary coding strategies in relation to time and context C_LIO_LIDisrupting excitatory recurrence in distal CA3 impairs context-discriminative neural coding C_LIO_LISparse and dense neural networks capture the functional heterogeneity of CA3 subcircuits C_LIO_LIRecurrence level tunes the geometry of neural manifolds both in vivo and in silico C_LI

neuroscience↗

bioRxiv2024

Planar, Spiral, and Concentric Traveling Waves Distinguish Cognitive States in Human Memory

A fundamental challenge in neuroscience is explaining how widespread brain regions flexibly interact to support behaviors. We hypothesize that traveling waves of oscillations are a key mechanism of neural coordination, such that they propagate across the cortex in distinctive patterns that control how different regions interact. To test this hypothesis, we used direct brain recordings from humans performing multiple memory experiments and an analytical framework that flexibly measures the propagation patterns of traveling waves. We found that traveling waves propagated along the cortex in not only plane waves, but also spirals, sources and sinks, and more complex patterns. The propagation patterns of traveling waves correlated with novel aspects of behavior, with specific wave shapes reflecting particular cognitive processes and even individual remembered items. Our findings suggest that large-scale cortical patterns of traveling waves reveal the spatial organization of cognitive processes in the brain and may be relevant for neural decoding.

neuroscience↗

bioRxiv2022

Traveling waves in the monkey frontoparietal network predict recent reward memory

Brain function depends on neural communication, but the mechanisms of this communication are not well understood. Recent studies suggest that one form of neural communication is through traveling waves (TWs)--patterns of neural oscillations that propagate within and between areas. We show that TWs appear robustly in microarray recordings in monkey frontal and parietal cortex and encode memory for recent rewards. While making saccades to obtain probabilistic rewards, monkeys were sensitive to the (statistically irrelevant) prior reward, which is consistent with behavioral biases produced by reward history. TWs in frontal and parietal areas were stronger in trials following a prior reward versus a lack of reward and, in the frontal lobe, correlated with the monkeys sensitivity to the prior reward. The findings suggest that neural communication across fronto-parietal areas, reflected by TWs, maintains default reward memories, while communication within the frontal lobe mediates the read out of the memories for prospective expectations.

neuroscience↗

bioRxiv2022

V1 receptive field structure contributes to neuronal response latency

The timing of neuronal responses is considered to be important for information transferring and communication across individual neurons. However, the sources of variabilities in the timing of neuronal responses are not well understood and sometimes over-interpreted. A systematic variability in the response latencies of the primary visual cortex has been reported in presence of drifting grating stimulus. Whereas the response latencies are systematically dependent on stimulus orientation. To understand the underlying mechanism of these systematic latencies, we recorded the neuronal response of the cat visual cortex, area 17, and simulated the response latency of V1 neurons, with two geometric models. We showed that outputs of these two models significantly predict the response latencies of the electrophysiology recording during orientation tasks. The periodic patterns created in the raster plots were dependent on the relative position of the stimulus rotation center and the receptive-field sub-regions. We argue the position of stimulus is contributing to systematic response latencies, dependent on drifting orientation. Therefore, we provide a toolbox based on our geometrical model for determining the exact location of RF sub-regions. Our result indicates that a major source of neuronal variability is the lack of fine-tuning in the task parameters. Considering the simplicity of the orientation selectivity task, we argue fine-tuning of stimulus properties is crucial for deduction of neural variability in higher-order cortical areas and understanding their neural dynamics.

neuroscience↗

bioRxiv2021

Neural Oscillatory Characteristics of Feedback Associated Activity in Globus Pallidus Interna

Neural oscillatory activities in basal ganglia have prominent roles in cognitive processes on local and global scales. However, the characteristics of high frequency oscillatory activities during cognitive tasks have not been extensively explored in human Globus Pallidus internus (GPi). This study aimed to investigate amplitude and interhemispheric coupling of bilateral GPi high gamma bursts in dystonia and Parkinsons Disease (PD) patients, in on and off medication states, after feedback during the Intra-Extra-Dimension shift (IED) task. Bilateral GPi Local Field Potentials (LFP) activity was recorded via externalized DBS electrodes during the IED task. Inter hemisphere phase synchrony was assessed using Inter-Site Phase Clustering (ISPC). Transient high gamma activity ([~]100-150Hz) was observed immediately after feedback in the dystonia patient. Moreover, these bursts were phase synchronous between left and right GPis with an antiphase clustering of phase differences. In contrast, no synchronous high gamma activity was detected in the PD patient with or without dopamine administration. The off-med PD patient displayed enhanced low frequency clusters ameliorated by medication in the on-med state. Furthermore, an increased low frequency activity was observed after feedback of incorrect trials in both disease states. The current study provides a rare report of antiphase homotopic synchrony in human GPi, potentially related to incorporating and processing feedback information. The absence of these activities in off and on-med PD indicates the potential presence of impaired medication independent circuits related to feedback processing. Together, these findings are helpful in pointing to the potential role of GPis synchronized high frequency activity in cognitive tasks and feedback information processing.

neuroscience↗