Optogenetic Generation of Neural Firing Patterns with Temporal Shaping of Light Pulses

Photonics, Journal Year: 2023, Volume and Issue: 10(5), P. 571 - 571

Published: May 13, 2023

The fundamental process of information processing and memory formation in the brain is associated with complex neuron firing patterns, which can occur spontaneously or be triggered by sensory inputs. Optogenetics has revolutionized neuroscience enabling precise manipulation neuronal activity patterns specified neural populations using light. However, light pulses used optogenetics have been primarily restricted to square waveforms. Here, we present a detailed theoretical analysis temporal shaping optogenetic excitation hippocampal neurons neocortical fast-spiking interneurons expressed ultrafast (Chronos), fast (ChR2), slow (ChRmine) channelrhodopsins. Optogenetic studied different shapes that include square, forward-/backward ramps, triangular, left-/right-triangular, Gaussian, left-/right-Gaussian, positive-sinusoidal, left-/right-positive sinusoidal. Different result significantly photocurrent amplitudes kinetics, spike-timing, spontaneous rate. For short duration stimulations, left-Gaussian pulse results larger ChR2 Chronos than same energy density. Time peak each opsin minimum at right-Gaussian pulse. optimal width achieve for non-square 10 ms Chronos, 50 ChRmine. evoke spike minimized on choosing Gaussian ChR2, positive-sinusoidal demonstrate waveforms generate more naturalistic spiking compared traditional pulses. These findings provide valuable insights development new strategies better simulate manipulate brain, potential improve our understanding cognitive processes treatment neurological disorders.

Language: Английский

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Multi-Scale Spatio-Temporal Fusion With Adaptive Brain Topology Learning for fMRI Based Neural Decoding

IEEE Journal of Biomedical and Health Informatics, Journal Year: 2023, Volume and Issue: 28(1), P. 262 - 272

Published: Oct. 23, 2023

Neural decoding aims to extract information from neurons' activities reveal how the brain functions. Due inherent spatial and temporal characteristics of signals, spatio-temporal computing has become a hot topic for neural decoding. However, extant methods usually use static topology, ignoring dynamic patterns interaction between regions. Further, they do not identify hierarchical organization leading only superficial insight into interactions. Therefore, here we propose novel framework, Multi-Scale Spatio-Temporal framework with Adaptive Brain Topology Learning (MSST-ABTL), It includes two new capabilities enhance decoding: i) ABTL module, which learns topology while updating specific regions, ii) MSST captures association pattern evolution, further enhances interpretability learned multi-scale perspective. We evaluated on public Human Connectome Project (HCP) dataset (resting-state task-related fMRI data). The extensive experiments show that proposed MSST-ABTL outperforms state-of-the-art four evaluation metrics, also can renew neuroscientific discoveries in brain's patterns.

Language: Английский

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Eigenvector centrality mapping reveals volatility of functional brain dynamics in anti-NMDA receptor encephalitis

Biological Psychiatry Cognitive Neuroscience and Neuroimaging, Journal Year: 2024, Volume and Issue: 9(11), P. 1222 - 1229

Published: July 27, 2024

Anti-N-methyl-D-aspartate receptor encephalitis (NMDARE) causes long-lasting cognitive deficits associated with altered functional connectivity. Eigenvector centrality (EC) mapping represents a powerful new method for data-driven voxel-wise and time-resolved estimation of network importance – beyond changes in classical 'static' To assess brain organization, we applied EC 73 patients NMDARE matched healthy controls. Areas significant group differences were further investigated using (i) spatial clustering analyses, (ii) time series correlation to synchronicity between the hippocampus cortical regions, (iii) clinical parameters. Dynamic, showed significantly higher variability 13 areas (p(FWE)<0.05) compared HC. dynamic spatially organized clusters resembling resting-state networks. Importantly, frontotemporal cluster was impaired verbal episodic memory (r=-0.25, p=0.037). medial prefrontal cortex reduced HC (p(FWE)<0.05, t(max)=3.76), (r=0.28, p=0.019). Static analyses only one region (left intracalcarine cortex). Widespread dynamics hippocampal-medial may thus represent neural correlate dysfunction NMDARE. detected substantially more alterations than traditional static approaches, highlighting potential this explain long-term

Language: Английский

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Synchronization evaluation of memristive photosensitive neurons in multi-neuronal systems

Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 187, P. 115470 - 115470

Published: Sept. 2, 2024

Language: Английский

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Neuroimaging markers of aberrant brain activity and treatment response in schizophrenia patients based on brain complexity

Translational Psychiatry, Journal Year: 2024, Volume and Issue: 14(1)

Published: Sept. 9, 2024

Language: Английский

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