The spiking of neuronal populations in motor cortex provides accurate information about movement parameters. Here we show that hand movement target and velocity can be inferred from multiple local field potentials (LFPs) in single trials approximately as efficiently as from multiple single-unit activity (SUA) recorded from the same electrodes. Our results indicate that LFPs can be used as an additional signal for decoding brain activity, particularly for new neuroprosthetic applications.

Recent studies showed that the low-frequency component of local field potentials (LFPs) in monkey motor cortex carries information about parameters of voluntary arm movements. Here, we studied how different signal components of the LFP in the time and frequency domains are modulated during center-out arm movements. Analysis of LFPs in the time domain showed that the amplitude of a slow complex waveform beginning shortly before the onset of arm movement is modulated with the direction of the movement. Examining LFPs in the frequency domain, we found that direction-dependent modulations occur in three frequency ranges, which typically increased their amplitudes before and during movement execution: Յ4, 6 -13, and 63-200 Hz. Cosine-like tuning was prominent in all signal components analyzed. In contrast, activity in a frequency band Ϸ30 Hz was not modulated with the direction of movement and typically decreased its amplitude during the task. This suggests that high-frequency oscillations have to be divided into at least two functionally different regimes: one Ϸ30 Hz and one Ͼ60 Hz. Furthermore, using multiple LFPs, we could show that LFP amplitude spectra can be used to decode movement direction, with the best performance achieved by the combination of different frequency ranges. These results suggest that using the different frequency components in the LFP is useful in improving inference of movement parameters from local field potentials.

When we perform a skilled movement such as reaching for an object, we can make use of prior information, for example about the location of the object in space. This helps us to prepare the movement, and we gain improved accuracy and speed during movement execution. Here, we investigate how prior information affects the motor cortical representation of movements during preparation and execution. We trained two monkeys in a delayed reaching task and provided a varying degree of prior information about the final target location. We decoded movement direction from multiple single-unit activity recorded from M1 (primary motor cortex) in one monkey and from PMd (dorsal premotor cortex) in a second monkey. Our results demonstrate that motor cortical cells in both areas exhibit individual encoding characteristics that change dynamically in time and dependent on prior information. On the population level, the information about movement direction is at any point in time accurately represented in a neuronal ensemble of time-varying composition. We conclude that movement representation in the motor cortex is not a static one, but one in which neurons dynamically allocate their computational resources to meet the demands defined by the movement task and the context of the movement. Consequently, we find that the decoding accuracy decreases if the precise task time, or the previous information that was available to the monkey, were disregarded in the decoding process. An optimal strategy for the readout of movement parameters from motor cortex should therefore take into account time and contextual parameters.

A novel computer aided manufacturing (CAM) method for electrocorticography (ECoG) microelectrodes was developed to be able to manufacture small, high density microelectrode arrays based on laser-structuring medical grade silicone rubber and high purity platinum. With this manufacturing process, we plan to target clinical applications, such as presurgical epilepsy monitoring, functional imaging during cerebral tumor resections and brain-computer interface control in paralysed patients, in the near future. This paper describes the manufacturing, implantation and long-term behaviour of such an electrode array. In detail, we implanted 8-channel electrode arrays subdurally over rat cerebral cortex over a period of up to 25 weeks. Our primary objective was to ascertain the electrode's stability over time, and to analyse the host response in vivo. For this purpose, impedance measurements were carried out at regular intervals over the first 18 weeks of the implantation period. The impedances changed between day 4 and day 7 after implantation, and then remained stable until the end of the implantation period, in accordance with typical behaviour of chronically implanted microelectrodes. A post-mortem histological examination was made to assess the tissue reaction due to the implantation. A mild, chronically granulated inflammation was found in the area of the implant, which was essentially restricted to the leptomeninges. Overall, these findings suggest that the concept of the presented ECoG-electrodes is promising for use in long-term implantations.