Publications by authors named "Fabio Boi"

Implantable active dense CMOS neural probes unlock the possibility of spatiotemporally resolving the activity of hundreds of single neurons in multiple brain circuits to investigate brain dynamics. Mapping neural dynamics in brain circuits with anatomical structures spanning several millimeters, however, remains challenging. Here, we demonstrate the first CMOS neural probe for mapping intracortical neural dynamics (both LFPs and spikes) in awake, behaving mice from an area >4 mm.

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Visual information processing in the retina requires the rhythmic expression of clock genes. The intrinsic retinal circadian clock is independent of the master clock located in the hypothalamic suprachiasmatic nucleus and emerges from retinal cells, including glia. Less clear is how glial oscillators influence the daily regulation of visual information processing in the mouse retina.

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Brain organoids is an exciting technology proposed to advance studies on human brain development, diseases, and possible therapies. Establishing and applying such models, however, is hindered by the lack of technologies to chronically monitor neural activity. A promising new approach comprising self-standing biosensing microdevices capable of achieving seamless tissue integration during cell aggregation and culture.

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Mechanical forces are increasingly recognized as major regulators of several physiological processes at both the molecular and cellular level; therefore, a deep understanding of the sensing of these forces and their conversion into electrical signals are essential for studying the mechanosensitive properties of soft biological tissues. To contribute to this field, we present a dual-purpose device able to mechanically stimulate retinal tissue and to record the spiking activity of retinal ganglion cells (RGCs). This new instrument relies on combining ferrule-top micro-indentation, which provides local measurements of viscoelasticity, with high-density multi-electrode array (HD-MEAs) to simultaneously record the spontaneous activity of the retina.

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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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Large-scale neural recordings with high spatial and temporal accuracy are instrumental to understand how the brain works. To this end, it is of key importance to develop probes that can be conveniently scaled up to a high number of recording channels. Despite recent achievements in complementary metal-oxide semiconductor (CMOS) multi-electrode arrays probes, in current circuit architectures an increase in the number of simultaneously recording channels would significantly increase the total chip area.

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Microelectrode array (MEA) systems with up to several thousands of recording electrodes and electrical or optical stimulation capabilities are commercially available or described in the literature. By exploiting their submillisecond and micrometric temporal and spatial resolutions to record bioelectrical signals, such emerging MEA systems are increasingly used in neuroscience to study the complex dynamics of neuronal networks and brain circuits. However, they typically lack the capability of implementing real-time feedback between the detection of neuronal spiking events and stimulation, thus restricting large-scale neural interfacing to open-loop conditions.

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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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Article Synopsis
  • Brain-machine interfaces (BMIs) create a direct communication link between the brain and the outside world, potentially improving life quality for those with disabilities, but their effectiveness is limited by how much information can be decoded from brain activity.
  • Researchers proposed using state-dependent decoding algorithms to enhance decoding performance by accounting for variability in neural responses based on the brain's current state.
  • In experiments with anesthetized rats, these algorithms achieved a 22% increase in information extraction from neural activity, improving BMI performance in controlling a dynamical system while suggesting a cost-effective way to enhance BMIs.
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This study explored the psychophysical effects of intracortical microstimulation (ICMS) coupled to auditory stimulation during a behavioral detection task in rats. ICMS directed to the sensory areas of the cortex can be instrumental in facilitating operant conditioning behavior. Moreover, multisensory stimulation promotes learning by enabling the subject to access multiple information channels.

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Motor brain-machine interfaces (BMIs) transform neural activities recorded directly from the brain into motor commands to control the movements of an external object by establishing an interface between the central nervous system (CNS) and the device. Bidirectional BMIs are closed-loop systems that add a sensory channel to provide the brain with an artificial feedback signal produced by the interaction between the device and the external world. Taking inspiration from the functioning of the spinal cord in mammalians, in our previous works we designed and developed a bidirectional BMI that uses the neural signals recorded form rats' motor cortex to control the movement of an external object.

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Article Synopsis
  • Bidirectional brain-machine interfaces (BMIs) create a direct communication link between the brain and external devices, utilizing decoders to translate neural activity into motor commands and encoders to send sensory information back to the brain.
  • This research introduces a modular BMI setup utilizing a compact neuromorphic processor, which features a network of spiking neurons capable of learning and adapting to decode neural signals effectively.
  • The study highlights successful experiments where the system allowed an anesthetized rat's brain to control the movement of an external object, suggesting that neuromorphic technology can enable low-power and compact BMIs with robust computational capabilities.
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We present a novel experimental framework that implements a bidirectional brain-machine interface inspired by the operation of the spinal cord in vertebrates that generates a control policy in the form of a force field. The proposed experimental set-up allows connecting the brain of freely moving rats to an external device. We tested this apparatus in a preliminary experiment with an alert rat that used the interface for acquiring a food reward.

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A portable 16-channels microcontroller-based wireless system for a bi-directional interaction with the central nervous system is presented in this work. The device is designed to be used with freely behaving small laboratory animals and allows recording of spontaneous and evoked neural activity wirelessly transmitted and stored on a personal computer. Biphasic current stimuli with programmable duration, frequency and amplitude may be triggered in real-time on the basis of the recorded neural activity as well as by the animal behavior within a specifically designed experimental setup.

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