Publications by authors named "Hayder Amin"

Individual choices shape life course trajectories of brain structure and function beyond genes and environment. We hypothesized that individual task engagement in response to a learning program results in individualized learning biographies and connectomics. Genetically identical female mice living in one large shared enclosure freely engaged in self-paced, automatically administered and monitored learning tasks.

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Large-scale multimodal neural recordings on high-density biosensing microelectrode arrays (HD-MEAs) offer unprecedented insights into the dynamic interactions and connectivity across various brain networks. However, the fidelity of these recordings is frequently compromised by pervasive noise, which obscures meaningful neural information and complicates data analysis. To address this challenge, we introduce DENOISING, a versatile data-derived computational engine engineered to adjust thresholds adaptively based on large-scale extracellular signal characteristics and noise levels.

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Large-scale neuronal networks and their complex distributed microcircuits are essential to generate perception, cognition, and behavior that emerge from patterns of spatiotemporal neuronal activity. These dynamic patterns emerging from functional groups of interconnected neuronal ensembles facilitate precise computations for processing and coding multiscale neural information, thereby driving higher brain functions. To probe the computational principles of neural dynamics underlying this complexity and investigate the multiscale impact of biological processes in health and disease, large-scale simultaneous recordings have become instrumental.

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Experiential richness creates tissue-level changes and synaptic plasticity as patterns emerge from rhythmic spatiotemporal activity of large interconnected neuronal assemblies. Despite numerous experimental and computational approaches at different scales, the precise impact of experience on network-wide computational dynamics remains inaccessible due to the lack of applicable large-scale recording methodology. We here demonstrate a large-scale multi-site biohybrid brain circuity on-CMOS-based biosensor with an unprecedented spatiotemporal resolution of 4096 microelectrodes, which allows simultaneous electrophysiological assessment across the entire hippocampal-cortical subnetworks from mice living in an enriched environment (ENR) and standard-housed (SD) conditions.

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A striking example of the brain's complexity and continued plasticity is the addition of new neuronal components to a circuit in a process called neurogenesis. Two brain regions exhibit profound circuit remodeling through this process - the olfactory bulb and hippocampus. However, how local network changes in both regions influence global circuit rewiring and dynamic network features remain largely unexplored due to the lack of spatiotemporal resolution technology and large-scale electrophysiological activity recordings.

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Large-scale multi-site biosensors are essential to probe the olfactory bulb (OB) circuitry for understanding the spatiotemporal dynamics of simultaneous discharge patterns. Current ex-vivo biosensing techniques are limited to recording a small set of neurons and cannot provide an adequate resolution, which hinders revealing the fast dynamic underlying the information coding mechanisms in the OB circuit. Here, we demonstrate a novel biohybrid OB-CMOS biosensing platform to decipher the cross-scale dynamics of the OB electrogenesis and quantify the distinct neuronal coding properties.

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Neuronal culture was used to investigate neuronal function in physiological and pathological conditions. Despite its inevitability, primary neuronal culture remained a gold standard method that requires laborious preparation, intensive training, and animal resources. To circumvent the shortfalls of primary neuronal preparations and efficiently give rise to functional neurons, we combine a neural stem cell culture method with a direct cell type-conversion approach.

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Active high-density electrode arrays realized with complementary metal-oxide-semiconductor (CMOS) technology provide electrophysiological recordings from several thousands of closely spaced microelectrodes. This has drastically advanced the spatiotemporal recording resolution of conventional multielectrode arrays (MEAs). Thus, today's electrophysiology in neuronal cultures can exploit label-free electrical readouts from a large number of single neurons within the same network.

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Electrophysiological signals in the brain are distributed over broad spatial and temporal scales. Monitoring these signals at multiple scales is fundamental in order to decipher how brain circuits operate and might dysfunction in disease. A possible strategy to enlarge the experimentally accessible spatial and temporal scales consists in combining the use of multiple probes with different resolutions and sensing areas.

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Substrate-integrated multielectrode arrays (MEAs) enable multisite, long-term, and label-free sensing and actuation of neuronal electrical signals in reduced cell culture models for network electrophysiology. Conventional, thin-film fabricated passive MEAs typically provide a few tens of electrode sites. New generations of active CMOS-based high-resolution arrays provide the capabilities of simultaneous recordings from thousands of neurons over fields of view of several square millimeters, yet allowing extracellular electrical imaging to be achieved down to the subcellular scale.

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A controlled geometry of in vitro neuronal networks allows investigation of the cellular mechanisms that underlie neuron-to-neuron and neuron-extracellular matrix interactions, which are essential to biomedical research. Herein, we report a selective guidance of primary hippocampal neurons by using arrays of three-dimensional vertical nanopillars (NPs) functionalized with a specific adhesion-promoting molecule-poly-dl-ornithine (PDLO). We show that 90% of neuronal cells are guided exclusively on the combinatorial PDLO/NP substrate.

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Neuronal responses to external stimuli vary from trial to trial partly because they depend on continuous spontaneous variations of the state of neural circuits, reflected in variations of ongoing activity prior to stimulus presentation. Understanding how post-stimulus responses relate to the pre-stimulus spontaneous activity is thus important to understand how state dependence affects information processing and neural coding, and how state variations can be discounted to better decode single-trial neural responses. Here we exploited high-resolution CMOS electrode arrays to record simultaneously from thousands of electrodes in in-vitro cultures stimulated at specific sites.

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Individuals with 22q11.2 microdeletion syndrome (22q11.2 DS) show cognitive and behavioral dysfunctions, developmental delays in childhood and risk of developing schizophrenia and autism.

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Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures.

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Neurotoxicity and the accumulation of extracellular amyloid-beta (Aβ) peptides are associated with the development of Alzheimer's disease (AD) and correlate with neuronal activity and network dysfunctions, ultimately leading to cellular death. However, research on neurodegenerative diseases is hampered by the paucity of reliable readouts and experimental models to study such functional decline from an early onset and to test rescue strategies within networks at cellular resolution. To overcome this important obstacle, we demonstrate a simple yet powerful in vitro AD model based on a rat hippocampal cell culture system that exploits large-scale neuronal recordings from 4096-electrodes on CMOS-chips for electrophysiological quantifications.

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Three-dimensional vertical micro- and nanostructures can enhance the signal quality of multielectrode arrays and promise to become the prime methodology for the investigation of large networks of electrogenic cells. So far, access to the intracellular environment has been obtained via spontaneous poration, electroporation, or by surface functionalization of the micro/nanostructures; however, these methods still suffer from some limitations due to their intrinsic characteristics that limit their widespread use. Here, we demonstrate the ability to continuously record both extracellular and intracellular-like action potentials at each electrode site in spontaneously active mammalian neurons and HL-1 cardiac-derived cells via the combination of vertical nanoelectrodes with plasmonic optoporation.

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Recent evidence indicates that the miRNA biogenesis factors DROSHA, DGCR8, and DICER exert non-overlapping functions, and have also roles in miRNA-independent regulatory mechanisms. However, it is currently unknown whether miRNA-independent functions of DGCR8 play any role in the maintenance of neuronal progenitors and during corticogenesis. Here, by phenotypic comparison of cortices from conditional and knockout mice, we show that deletion, in contrast to depletion, leads to premature differentiation of neural progenitor cells and overproduction of TBR1-positive neurons.

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The recent availability of human induced pluripotent stem cells (hiPSCs) holds great promise as a novel source of human-derived neurons for cell and tissue therapies as well as for in vitro drug screenings that might replace the use of animal models. However, there is still a considerable lack of knowledge on the functional properties of hiPSC-derived neuronal networks, thus limiting their application. Here, upon optimization of cell culture protocols, we demonstrate that both spontaneous and evoked electrical spiking activities of these networks can be characterized on-chip by taking advantage of the resolution provided by CMOS multielectrode arrays (CMOS-MEAs).

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High density multielectrode arrays (MEAs) based on CMOS technology (CMOS-MEAs) can simultaneously record extracellular spiking activity in neuronal cultures from 4096 closely spaced microelectrodes. This allows for a finer investigation of neuronal network activity compared to conventional MEAs with a few tens of electrodes. However, the sensing properties of these devices differ.

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High density multielectrode array recordings with CMOS-MEAs allow to monitor cell culture activity with unprecedent details respect to previous recording techniques. This is clarifying how network activity develops and is motivating the development of novel data analysis tools. Here, in order to advance in the exploitation of the richness of these large-scale array recordings, we introduce a principal component analysis approach that aims at improving on existing methodologies to describe neural activity events within large networks.

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An emerging generation of high-density microelectrode arrays (MEAs) is now capable of recording spiking activity simultaneously from thousands of neurons with closely spaced electrodes. Reliable spike detection and analysis in such recordings is challenging due to the large amount of raw data and the dense sampling of spikes with closely spaced electrodes. Here, we present a highly efficient, online capable spike detection algorithm, and an offline method with improved detection rates, which enables estimation of spatial event locations at a resolution higher than that provided by the array by combining information from multiple electrodes.

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Deciphering neural network function in health and disease requires recording from many active neurons simultaneously. Developing approaches to increase their numbers is a major neurotechnological challenge. Parallel to recent advances in optical Ca(2+) imaging, an emerging approach consists in adopting complementary-metal-oxide-semiconductor (CMOS) technology to realize MultiElectrode Array (MEA) devices.

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Various plasticity mechanisms, including experience-dependent, spontaneous, as well as homeostatic ones, continuously remodel neural circuits. Yet, despite fluctuations in the properties of single neurons and synapses, the behavior and function of neuronal assemblies are generally found to be very stable over time. This raises the important question of how plasticity is coordinated across the network.

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Neuronal signaling in brain circuits occurs at multiple scales ranging from molecules and cells to large neuronal assemblies. However, current sensing neurotechnologies are not designed for parallel access of signals at multiple scales. With the aim of combining nanoscale molecular sensing with electrical neural activity recordings within large neuronal assemblies, in this work three-dimensional (3D) plasmonic nanoantennas are integrated with multielectrode arrays (MEA).

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