In vivo neural activity of electrosensory pyramidal cells: Biophysical characterization and phenomenological modeling DOI Creative Commons
Amin Akhshi, Michael G. Metzen, Maurice J. Chacron

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Июнь 3, 2025

Summary Burst firing is an important property of neuronal activity, thought to enhance sensory encoding. While previous studies show significant differences in burst between vivo and vitro conditions, how contributes neural coding it modulated by underlying biophysical mechanisms when neurons are under active synaptic bombardments remains poorly understood. Here, we combined intracellular recordings computational modeling investigate cellular can explain the activity electrosensory lateral line lobe (ELL) pyramidal cells Apteronotus leptorhynchus . We developed a biophysically detailed compartmental model incorporating voltage-gated currents, NMDA receptor-mediated Ca 2+ influx, -activated SK channels, handling, stochastic inputs reproduce activities ELL cells. Specifically, using bifurcation analysis, identified dynamical transitions quiescent, tonic, bursting regimes, governed interactions among conductance, receptor activation, applied current. Model parameters were optimized against data, accurately reproducing action potential waveforms temporal dynamics, including characteristic bimodal interspike interval distributions reflecting intra- inter-burst intervals. further modified Hindmarsh-Rose dual adaptation variables noise. This simplified phenomenological successfully captured firings comparable those observed recorded while replicating diverse patterns across population. Finally, parameter sensitivity analysis revealed slow dynamics noise intensity as key determinants spiking variability within Overall, our results demonstrate that arises from synergistic intrinsic conductances (e.g., NMDA-SK coupling), mobilization, stochasticity, offering reconciliation for discrepancies with activity. The models provide mechanistic insights into background modulates validate frameworks studying population-level dynamics.

Язык: Английский

Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function DOI Creative Commons

P. Vázquez-Guerrero,

Rohisha Tuladhar, Costas Psychalinos

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Март 9, 2024

There is an increasing need to implement neuromorphic systems that are both energetically and computationally efficient. also great interest in using electric elements with memory, memelements, can complex neuronal functions intrinsically. A feature not widely incorporated history-dependent action potential time adaptation which seen real cells. Previous theoretical work shows power-law history dependent spike adaptation, several brain areas species, be modeled fractional order differential equations. Here, we show spiking neurons implemented super-capacitors. The super-capacitors have derivative memcapacitive properties. We two circuits, a leaky integrate fire Hodgkin-Huxley. Both circuits optimal coding dynamics reproduced previously published computer simulations. However, the Hodgkin-Huxley circuit showed novel consistent criticality. compared responses of this recordings from weakly-electric fish been shown perform differentiation their sensory input. criticality was confirmed spontaneous live fish. Furthermore, predicted long-lasting stimulation corroborated experimentally. Our memcapacitors provide intrinsic memory dependence could allow implementation efficient devices. Memcapacitors static consume less energy than most studied memristors, thus allowing realization

Язык: Английский

Процитировано

5
Electrosensory midbrain neurons optimally decode ascending input during object localization DOI Creative Commons
Myriah Haggard, Maurice J. Chacron

The Journal of Physiology, Год журнала: 2025, Номер unknown

Опубликована: Май 5, 2025

Abstract Understanding how downstream brain areas decode sensory information represented by neural populations remains a central problem in neuroscience. While decoders that are optimized to extract the maximum amount of have been extensively used research, whether these physiologically realistic at best unclear. Here we show decoding scheme based on correlations between activities absence stimulation can predict responses as well optimal decoder. Simultaneous recordings were made from primary and their midbrain targets electrosensory system Apteronotus leptorhynchus . We found exhibited significant (i.e. ‘baseline’), with activity lagging short latency. then investigated combined downstream. Overall, decoder assigned weights each neuron was trained solely baseline performed stimulation. Interestingly, both greatly outperformed schemes for which every same weight or when shuffled, indicating identity is critical. Taken together, our results suggest uses strategies perform levels but qualitatively different those predicted solutions. image Key points How signals decoded give rise perception poorly understood. recorded targets. A solution responses. important qualitative differences solution. Our demonstrate do an strategy.

Язык: Английский

Процитировано

0
In vivo neural activity of electrosensory pyramidal cells: Biophysical characterization and phenomenological modeling DOI Creative Commons
Amin Akhshi, Michael G. Metzen, Maurice J. Chacron

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Июнь 3, 2025

Summary Burst firing is an important property of neuronal activity, thought to enhance sensory encoding. While previous studies show significant differences in burst between vivo and vitro conditions, how contributes neural coding it modulated by underlying biophysical mechanisms when neurons are under active synaptic bombardments remains poorly understood. Here, we combined intracellular recordings computational modeling investigate cellular can explain the activity electrosensory lateral line lobe (ELL) pyramidal cells Apteronotus leptorhynchus . We developed a biophysically detailed compartmental model incorporating voltage-gated currents, NMDA receptor-mediated Ca 2+ influx, -activated SK channels, handling, stochastic inputs reproduce activities ELL cells. Specifically, using bifurcation analysis, identified dynamical transitions quiescent, tonic, bursting regimes, governed interactions among conductance, receptor activation, applied current. Model parameters were optimized against data, accurately reproducing action potential waveforms temporal dynamics, including characteristic bimodal interspike interval distributions reflecting intra- inter-burst intervals. further modified Hindmarsh-Rose dual adaptation variables noise. This simplified phenomenological successfully captured firings comparable those observed recorded while replicating diverse patterns across population. Finally, parameter sensitivity analysis revealed slow dynamics noise intensity as key determinants spiking variability within Overall, our results demonstrate that arises from synergistic intrinsic conductances (e.g., NMDA-SK coupling), mobilization, stochasticity, offering reconciliation for discrepancies with activity. The models provide mechanistic insights into background modulates validate frameworks studying population-level dynamics.

Язык: Английский

Процитировано

0