We report on the development of high-density neural probes for distributed neuronal recording and stimulation. Our hybrid silicon-parylene probes provide high spatial resolution and incorporate a monolithically integrated flexible cable to address the challenge of stable recordings in chronic neural implants. We address a long-standing but often overlooked issue in parylene processing to realize reliable multilayer interconnects. We also discuss the design of ultracompact parylene optical waveguides for localized optogenetic stimulation of neurons. We demonstrate in-vivo electrophysiology recordings in mice.
Despite the widespread use of current-source density (CSD) analysis of extracellular potential recordings in the brain, the physical mechanisms responsible for the generation of the signal are still debated. While the extracellular potential is thought to be exclusively generated by the transmembrane currents, recent studies suggest that extracellular diffusive, advective and displacement currents-traditionally neglected-may also contribute considerably toward extracellular potential recordings. Here, we first justify the application of the electro-quasistatic approximation of Maxwell's equations to describe the electromagnetic field of physiological origin. Subsequently, we perform spatial averaging of currents in neural tissue to arrive at the notion of the CSD and derive an equation relating it to the extracellular potential. We show that, in general, the extracellular potential is determined by the CSD of membrane currents as well as the gradients of the putative extracellular diffusion current. The diffusion current can contribute significantly to the extracellular potential at frequencies less than a few Hertz; in which case it must be subtracted to obtain correct CSD estimates. We also show that the advective and displacement currents in the extracellular space are negligible for physiological frequencies while, within cellular membrane, displacement current contributes toward the CSD as a capacitive current. Taken together, these findings elucidate the relationship between electric currents and the extracellular potential in brain tissue and form the necessary foundation for the analysis of extracellular recordings.
ABSTRACT Sensory stimuli are represented by the joint activity of large populations of neurons across the mammalian cortex. Information in such responses is limited by trial-to-trial variability. Because that variability is not independent between neurons, it has the potential to improve or degrade the amount of sensory information in the population response. How visual information scales with population size remains an open empirical question. Here, we use Neuropixels to simultaneously record tens to hundreds of single neurons in primary visual cortex (V1) and lateral geniculate nucleus (LGN) of mice and estimate population information. We found a mix of synergistic and redundant coding: synergy predominated in small populations (2-12 cells) before giving way to redundancy. The shared variability of this coding regime included global shared spike count variability at longer timescales, layer specific shared spike count variability at finer timescales, and shared variability in spike timing (jitter) that linked ensembles that span layers. Such ensembles defined by their shared variability carry more information. Our results suggest fine time scale stimulus encoding may be distributed across physically overlapping but distinct ensembles in V1.
A large array of neuroscientific techniques, including in vivo electrophysiology, two-photon imaging, optogenetics, lesions, and microdialysis, require access to the brain through the skull. Ideally, the necessary craniotomies could be performed in a repeatable and automated fashion, without damaging the underlying brain tissue. Here we report that when drilling through the skull a stereotypical increase in conductance can be observed when the drill bit passes through the skull base. We present an architecture for a robotic device that can perform this algorithm, along with two implementations—one based on homebuilt hardware and one based on commercially available hardware—that can automatically detect such changes and create large numbers of precise craniotomies, even in a single skull. We also show that this technique can be adapted to automatically drill cranial windows several millimeters in diameter. Such robots will not only be useful for helping neuroscientists perform both small and large craniotomies more reliably but can also be used to create precisely aligned arrays of craniotomies with stereotaxic registration to standard brain atlases that would be difficult to drill by hand.
