To understand the neural basis of behavior, it is necessary to record brain activity in freely moving animals. Advances in implantable multi-electrode array technology have enabled researchers to record the activity of neuronal ensembles from multiple brain regions. The full potential of this approach is currently limited by reliance on cable tethers, with bundles of wires connecting the implanted electrodes to the data acquisition system while impeding the natural behavior of the animal. To overcome these limitations, here we introduce a multi-channel wireless headstage system designed for small animals such as rats and mice. A variety of single unit and local field potential signals were recorded from the dorsal striatum and substantia nigra in mice and the ventral striatum and prefrontal cortex simultaneously in rats. This wireless system could be interfaced with commercially available data acquisition systems, and the signals obtained were comparable in quality to those acquired using cable tethers. On account of its small size, light weight, and rechargeable battery, this wireless headstage system is suitable for studying the neural basis of natural behavior, eliminating the need for wires, commutators, and other limitations associated with traditional tethered recording systems.
Mathematical models for the behavior of fractional-N phase-locked-loop frequency synthesizers (Frac-N) are presented. The models are intended for calculating rms phase error and determining spurs in the output of Frac-N. The models describe noise contributions due to the charge pump (CP), the phase frequency detector (PFD), the loop filter, the voltage control osicllator, and the delta-sigma modulator. Models are presented for the effects of static CP gain mismatch, CP dynamic mismatch and PFD reset delay mismatch. A simple analytic expression shows the level of 16 sequence noise caused by static CP current mismatch. We further show that un-equal rise time and fall time constants of the CP result in dynamic mismatch noise. Reset delay mismatch in PFD is shown to also contribute significantly to close-in phase noise. The model takes into account the reduction in CP thermal and flicker noise due to the changing duty cycle of Frac-N CP. Our model is therefore useful in characterizing the noise performance of Frac-N at the system-level, simplifying the design of fractional-N synthesizers and transmitters. Analytical and simulated results are compared and show good agreement with prior published data on Frac-N realizations.Index Terms-Charge pump (CP), delta-sigma, dynamic mismatch, dynamic mismatch corner frequency, flicker noise, flicker noise corner frequency, fractional-N frequency synthesizer (Frac-N), frequency synthesizer, gain mismatch, gain mismatch corner frequency, phase frequency detector (PFD), phase noise, reset delay mismatch, rms phase error, spurs, thermal noise, voltage-controlled oscillator (VCO).
In recent years optogenetics has rapidly become an essential technique in neuroscience. Its temporal and spatial specificity, combined with efficacy in manipulating neuronal activity, are especially useful in studying the behavior of awake behaving animals. Conventional optogenetics, however, requires the use of lasers and optic fibers, which can place considerable restrictions on behavior. Here we combined a wirelessly controlled interface and small implantable light-emitting diode (LED) that allows flexible and precise placement of light source to illuminate any brain area. We tested this wireless LED system in vivo, in transgenic mice expressing channelrhodopsin-2 in striatonigral neurons expressing D1-like dopamine receptors. In all mice tested, we were able to elicit movements reliably. The frequency of twitches induced by high power stimulation is proportional to the frequency of stimulation. At lower power, contraversive turning was observed. Moreover, the implanted LED remains effective over 50 days after surgery, demonstrating the long-term stability of the light source. Our results show that the wireless LED system can be used to manipulate neural activity chronically in behaving mice without impeding natural movements.
We have developed, manufactured, and tested two analog CMOS integrated circuit "neurochips" for recording from arrays of densely packed neural electrodes. Device A is a 16-channel buffer consisting of parallel noninverting amplifiers with a gain of 2 V/V. Device B is a 16-channel two-stage analog signal processor with differential amplification and high-pass filtering. It features selectable gains of 250 and 500 V/V as well as reference channel selection. The resulting amplifiers on Device A had a mean gain of 1.99 V/V with an equivalent input noise of 10 microV(rms). Those on Device B had mean gains of 53.4 and 47.4 dB with a high-pass filter pole at 211 Hz and an equivalent input noise of 4.4 microV(rms). Both devices were tested in vivo with electrode arrays implanted in the somatosensory cortex.
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