Biology subjects

Kogo, N.

Publications and source records attributed to Kogo, N..

6 recordsLinked to original sources

bioRxiv2024

CACNA1A haploinsufficiency leads to reduced synaptic function and increased intrinsic excitability

Haploinsufficiency of the CACNA1A gene, encoding the pore-forming 1 subunit of P/Q-type voltage-gated calcium channels, is associated with a clinically variable phenotype ranging from cerebellar ataxia, to neurodevelopmental syndromes with epilepsy and intellectual disability. To understand the pathological mechanisms of CACNA1A loss-of-function variants, we characterized a human neuronal model for CACNA1A haploinsufficiency, by differentiating isogenic induced pluripotent stem cell lines into glutamatergic neurons, and investigated the effect of CACNA1A haploinsufficiency on mature neuronal networks through a combination of electrophysiology, gene expression analysis, and in silico modeling. We observed an altered network synchronization in CACNA1A+/- networks alongside synaptic deficits, notably marked by an augmented contribution of GluA2-lacking AMPA receptors. Intriguingly, these synaptic perturbations coexisted with increased non-synaptically driven activity, as characterized by inhibition of NMDA and AMPA receptors on micro-electrode arrays. Single-cell electrophysiology and gene expression analysis corroborated this increased intrinsic excitability through reduced potassium channel function and expression. Moreover, we observed partial mitigation of the CACNA1A+/- network phenotype by 4-aminopyridine, a therapeutic intervention for episodic ataxia type 2. In summary, our study pioneers the characterization of a human induced pluripotent stem cell-derived neuronal model for CACNA1A haploinsufficiency, and has unveiled novel mechanistic insights. Beyond showcasing synaptic deficits, this neuronal model exhibited increased intrinsic excitability mediated by diminished potassium channel function, underscoring its potential as a therapeutic discovery platform with predictive validity.

neuroscience↗

bioRxiv2023

Non-evoked frequencies: Retinotopic position modulation induces SSVEP signals without intrinsic neural signal processing

Periodic changes in visual input can produce rhythmic patterns in EEG signals, which appear as narrowband frequency components. These components are commonly interpreted as reflecting the activity of neurons sensitive to the modulated stimulus features. Here, we present a scenario in which frequency components arise solely from retinotopic variations in signal strength, without reflecting any specific neural mechanism sensitive to the modulated feature. Using simulated and empirical data, we show that signal fluctuations based purely on retinotopic stimulus position can produce identifiable frequency components in response to position-modulated stimuli. These components likely reflect structural rather than functional cortical factors influencing signal strength across different retinotopic areas. Our results challenge the conventional assumption that frequency components necessarily indicate intrinsic neural signal processing, instead highlighting how interactions between stimuli and cortical architecture can give rise to such components.

neuroscience↗

bioRxiv2023

SCN1A-deficient hiPSC-derived excitatory neuronal networks display mutation-specific phenotypes

Dravet syndrome is a severe epileptic encephalopathy, characterized by (febrile) seizures, behavioral problems and developmental delay. 80% of Dravet syndrome patients have a mutation in SCN1A, encoding NaV1.1. Milder clinical phenotypes, such as GEFS+ (generalized epilepsy with febrile seizures plus), can also arise from SCN1A mutations. Predicting the clinical phenotypic outcome based on the type of mutation remains challenging, even when the same mutation is inherited within one family. Both this clinical and genetic heterogeneity add to the difficulties of predicting disease progression and tailored prescription of anti-seizure medication. A better understanding of the neuropathology of different SCN1A mutations, might give insight in differentiating the expected clinical phenotype and best fit treatment choice. Initially it was recognized that loss of Na+ -current in inhibitory neurons specifically resulted in disinhibition and consequently seizure generation. However, the extent to which excitatory neurons contribute to the pathophysiology is currently debated, and might depend on the patient clinical phenotype or the specific mutation in SCN1A. To examine the genotype-phenotype correlations of SCN1A mutations in relation to excitatory neurons, we investigated a panel of patient-derived excitatory neuronal networks differentiated on multi-electrode arrays. We included patients with different clinical phenotypes, harboring different mutations in SCN1A, plus a family where the same mutation leads to both GEFS+ and Dravet syndrome. We hitherto describe a previously unidentified functional excitatory neuronal network phenotype in the context of epilepsy, which corresponded to seizurogenic network prediction patterns elicited by proconvulsive compounds. We find that excitatory neuronal networks were differently affected, dependent on the type of SCN1A mutation, but not on clinical severity. Specifically, pore domain mutations could be distinguished from voltage sensing domain mutations. Furthermore, all patients showed aggravated neuronal network responses upon febrile temperatures. While the basal neuronal network phenotypes could not be distinguished based on patient clinical severity, retrospective drug screening revealed that anti-seizure medication only affected GEFS+ patient-, but not Dravet patient-derived neuronal networks in a patient specific and clinically relevant manner. In conclusion, our results indicate a mutation-specific excitatory neuronal network phenotype, which recapitulates the foremost clinically relevant features, providing future opportunities for precision therapies. HighlightsO_LIHuman stem cell derived excitatory neurons are affected by mutations in SCN1A and display mutation-specific, but not clinical phenotype specific, neuronal network phenotypes C_LIO_LIThe neuronal network phenotype we describe corresponds to seizurogenic network prediction patterns in vitro C_LIO_LIExcitatory neuronal networks respond to Dravet syndrome clinically relevant triggers, like febrile temperatures and Dravet-contraindicated ASM Carbamazepine C_LIO_LIRetrospective drug screening revealed that GEFS+ neuronal networks, but not Dravet neuronal networks respond to ASM in a patient-specific and clinical relevant manner C_LI

neuroscience↗

bioRxiv2021

Emergence of border-ownership by large-scale consistency and long-range interactions: Neuro-computational model to reflect global configurations

The visual system performs remarkably well to perceive depth order of surfaces without stereo disparity, indicating the importance of figure-ground organization based on pictorial cues. To understand how figure-ground organization emerges, it is essential to investigate how the global configuration of an image is reflected. In the past, many neuro- computational models developed to reproduce figure-ground organization implemented algorithms to give a bias to convex areas. However, in certain conditions, a convex area can be perceived as a hole and a non-convex area as figural. This occurs when the surface properties of the convex area are consistent with the background and, hence, are grouped together in our perception. We argue that large-scale consistency of surface properties is reflected in the border-ownership computation. We developed a model, called DISC2, that first analyzes relationships between two border-ownership signals of all possible combinations in the image. It then enhances signals if they satisfy the following conditions: 1. the two signals fit to a convex configuration, and 2. the surface properties at the locations of the two signals are consistent. The strength of the enhancement decays with distance between the signals. The model gives extremely robust responses to various images with complexities both in shape and depth order. Furthermore, we developed an advanced version of the model ("augmented model") where the global computation above interacts with local computation of curvilinearity, which further enhanced the robust nature of the model. The results suggest the involvement of similar computational processes in the brain for figure-ground organization.

animal behavior and cognition↗

bioRxiv2021

Loss-of-function variants in the schizophrenia risk gene SETD1A alter neuronal network activity in human neurons through cAMP/PKA pathway

Heterozygous loss-of-function (LoF) mutations in SETD1A, which encodes a subunit of histone H3 lysine 4 methyltransferase, were shown to cause a novel neurodevelopmental syndrome and increase the risk for schizophrenia. We generated excitatory/inhibitory neuronal networks from human induced pluripotent stem cells with a SETD1A heterozygous LoF mutation (SETD1A+/-) using CRISPR/Cas9. Our data show that SETD1A haploinsufficiency resulted in morphologically increased dendritic complexity and functionally increased bursting activity. This network phenotype was primarily driven by SETD1A haploinsufficiency in glutamatergic neurons. In accordance with the functional changes, transcriptomic profiling revealed perturbations in gene sets associated with glutamatergic synaptic function. At the molecular level, we identified specific changes in the cAMP/PKA pathway pointing toward a hyperactive cAMP pathway in SETD1A+/- neurons. Finally, by pharmacologically targeting the cAMP pathway we were able to rescue the network deficits in SETD1A+/- cultures. Our results demonstrate a link between SETD1A and the cAMP-dependent pathway in human neurons.

neuroscience↗

bioRxiv2020

Dynamics of mutual inhibition between two visual cortical neurons compared to human perceptual competition

Neural competition plays an essential role in active selection processes of noisy and ambiguous input signals and it is assumed to underlie emergent properties of brain functioning such as perceptual organization and decision making. Despite ample theoretical research on neural competition, experimental tools to allow neurophysiological investigation of competing neurons have not been available. We developed a "hybrid" system where real-life neurons and a computer-simulated neural circuit interacted. It enabled us to construct a mutual inhibition circuit between two real life pyramidal neurons. We then asked what dynamics this minimal unit of neural competition exhibits and compared them to the known behavioral-level dynamics of neural competition. We found that the pair of neurons shows bi-stability when activated simultaneously by current injections. The addition of modelled noise and changes in the activation strength showed that the dynamics of the circuit are strikingly similar to the known properties of bi-stable visual perception.

neuroscience↗