Neural prostheses have already a long history and yet the cochlear implant remains the only success story about a longterm sensory function restoration. On the other hand, neural implants for deep brain stimulation are gaining acceptance for variety of disorders including Parkinson’s disease and obsessive-compulsive disorder. It is anticipated that the progress in the field has been hampered by a combination of technological and biological factors, such as the limited understanding of the longterm behaviour of implants, unreliability of devices, biocompatibility of the implants among others. While the field's understanding of the cell biology of interactions at the biotic-abiotic interface has improved, relatively little attention has been paid on the mechanical factors (stress, strain), and hence on the geometry that can modulate it. This focused review summarizes the recent progress in the understanding of the mechanisms of mechanical interaction between the implants and the brain. The review will give an overview of the factors by which the implants interact acutely and chronically with the tissue: blood-brain barrier breach, vascular damage, micromotions, diffusion etc. We propose some design constraints to be considered in future studies. Aspects of the chronic cell-implant interaction will be discussed in view of the chronic local inflammation and the ways of modulating it.

The establishment of neuronal connectivity depends on the correct initial polarization of the young neurons. In vivo , developing neurons sense a multitude of inputs and a great number of molecules are described that affect their outgrowth. In vitro, many studies have shown the possibility to influence neuronal morphology and growth by biophysical, i.e. topographic, signaling. In this work we have taken this approach one step further and investigated the impact of substrate topography in the very early differentiation stages of developing neurons, i.e. when the cell is still at the round stage and when the first neurite is forming. For this purpose we fabricated micron sized pillar structures with highly reproducible feature sizes, and analyzed neurons on the interface of flat and topographic surfaces. We found that topographic signaling was able to attract the polarization markers of mouse embryonic neurons -N-cadherin, Golgi-centrosome complex and the first bud were oriented towards topographic stimuli. Consecutively, the axon was also preferentially extending along the pillars. These events seemed to occur regardless of pillar dimensions in the range we examined. However, we found differences in neurite length that depended on pillar dimensions. This study is one of the first to describe in detail the very early response of hippocampal neurons to topographic stimuli.

Deep Brain Stimulation (DBS) has evolved into a well-accepted add-on treatment for patients with severe Parkinsons disease as well as for other chronic neurological conditions. The focal action of electrical stimulation can yield better responses and it exposes the patient to fewer side effects compared to pharmaceuticals distributed throughout the body toward the brain. On the other hand, the current practice of DBS is hampered by the relatively coarse level of neuromodulation achieved. Optogenetics, in contrast, offers the perspective of much more selective actions on the various physiological structures, provided that the stimulated cells are rendered sensitive to the action of light. Optogenetics has experienced tremendous progress since its first in vivo applications about 10 years ago. Recent advancements of viral vector technology for gene transfer substantially reduce vector-associated cytotoxicity and immune responses. This brings about the possibility to transfer this technology into the clinic as a possible alternative to DBS and neuromodulation. New paths could be opened toward a rich panel of clinical applications. Some technical issues still limit the long term use in humans but realistic perspectives quickly emerge. Despite a rapid accumulation of observations about patho-physiological mechanisms, it is still mostly serendipity and empiric adjustments that dictate clinical practice while more efficient logically designed interventions remain rather exceptional. Interestingly, it is also very much the neuro technology developed around optogenetics that offers the most promising tools to fill in the existing knowledge gaps about brain function in health and disease. The present review examines Parkinson's disease and refractory epilepsy as use cases for possible optogenetic stimulation therapies.

We assemble a compact lens-free in-line holographic microscope, employ it to image blood cells flowing in a microfluidic chip and perform a three-part leukocyte differential based on the acquired images.

Since a few decades, micro-fabricated neural probes are being used, together with microelectronic interfaces, to get more insight in the activity of neuronal networks. The need for higher temporal and spatial recording resolutions imposes new challenges on the design of integrated neural interfaces with respect to power consumption, data handling and versatility. In this paper, we present an integrated acquisition system for in vitro and in vivo recording of neural activity. The ASIC consists of 16 low-noise, fully-differential input channels with independent programmability of its amplification (from 100 to 6000 V/V) and filtering (1-6000 Hz range) capabilities. Each channel is AC-coupled and implements a fourth-order band-pass filter in order to steeply attenuate out-of-band noise and DC input offsets. The system achieves an input-referred noise density of 37 nV/√Hz, a NEF of 5.1, a CMRR >; 60 dB, a THD <; 1% and a sampling rate of 30 kS/s per channel, while consuming a maximum of 70 μA per channel from a single 3.3 V. The ASIC was implemented in a 0.35 μm CMOS technology and has a total area of 5.6 × 4.5 mm². The recording system was successfully validated in in vitro and in vivo experiments, achieving simultaneous multichannel recordings of cell activity with satisfactory signal-to-noise ratios.