Measuring Generalization of Visuomotor Perturbations in Wrist Movements Using Mobile Phones

Recent studies in motor control have shown that visuomotor rotations for reaching have narrow generalization functions: what we learn during movements in one direction only affects subsequent movements into close directions. Here we wanted to measure the generalization functions for wrist movement. To do so we had 7 subjects performing an experiment holding a mobile phone in their dominant hand. The mobile phone's built in acceleration sensor provided a convenient way to measure wrist movements and to run the behavioral protocol. Subjects moved a cursor on the screen by tilting the phone. Movements on the screen toward the training target were rotated and we then measured how learning of the rotation in the training direction affected subsequent movements in other directions. We find that generalization is local and similar to generalization patterns of visuomotor rotation for reaching

A simulation study on the effects of neuronal ensemble properties on decoding algorithms for intracortical brain-machine interfaces

Background: Intracortical brain-machine interfaces (BMIs) harness movement information by sensing neuronal activities using chronic microelectrode implants to restore lost functions to patients with paralysis. However, neuronal signals often vary over time, even within a day, forcing one to rebuild a BMI every time they operate it. The term "rebuild" means overall procedures for operating a BMI, such as decoder selection, decoder training, and decoder testing. It gives rise to a practical issue of what decoder should be built for a given neuronal ensemble. This study aims to address it by exploring how decoders' performance varies with the neuronal properties. To extensively explore a range of neuronal properties, we conduct a simulation study. Methods: Focusing on movement direction, we examine several basic neuronal properties, including the signal-to-noise ratio of neurons, the proportion of well-tuned neurons, the uniformity of their preferred directions (PDs), and the non-stationarity of PDs. We investigate the performance of three popular BMI decoders: Kalman filter, optimal linear estimator, and population vector algorithm. Results: Our simulation results showed that decoding performance of all the decoders was affected more by the proportion of well-tuned neurons that their uniformity. Conclusions: Our study suggests a simulated scenario of how to choose a decoder for intracortical BMIs in various neuronal conditions

Decomposition of EEG Signals for Multichannel Neural Activity Analysis in Animal Experiments

International audienceWe describe in this paper some advanced protocols for the discrimination and classification of neuronal spike waveforms within multichannel electrophysiological recordings. Sparse decomposition was used to serarate the linearly independent signals underlying sensory information in cortical spike firing pat- terns. We introduce some modifications in the the IDE algorithm to take into account prior knowledge on the spike waveforms. We have investigated motor cortex responses recorded during movement in freely moving rats to provide ev- idence for the relationship between these patterns and special behavioral task

Cerebellar activation during copying geometrical shapes.

We studied functional MRI activation in the cerebellum during copying 9 geometrical shapes (equilateral triangle, isosceles triangle, square, diamond, vertical trapezoid, pentagon, hexagon, circle, and vertical lemniscate). Twenty subjects were imaged during 3 consecutive 45-s periods (rest, visual presentation, and copying). First, there was a positive relation between cerebellar activation and the peak speed of individual movements. This effect was strongest in the lateral and posterior ipsilateral cerebellum but it was also present in the paramedian zones of both cerebellar hemispheres and in the vermis. A finer grain analysis of the relations between the time course of the blood oxygenation level-dependent activation and movement parameters revealed a significant relation to hand position and speed but not to acceleration. Second, there was a significant relation between the intensity of voxel activation during visual presentation and the speed of the upcoming movement. The spatial distribution of these voxels was very similar to that of the voxels activated during copying, indicating that the cerebellum might be involved in motor rehearsal, in addition to its role during movement execution. Finally, a factor analysis of the intensity of activated voxels in the ipsilateral cerebellum during copying (adjusted for the speed effect) extracted 3 shape factors. Factor 1 reflected "roundness," factor 2 "upward pointing," and factor 3 "pointing (up or down) and elongation." These results link cerebellar activation to more global, spatial aspects of copying

Logarithmic transformation for high-field BOLD fMRI data.

Parametric statistical analyses of BOLD fMRI data often assume that the data are normally distributed, the variance is independent of the mean, and the effects are additive. We evaluated the fulfilment of these conditions on BOLD fMRI data acquired at 4 T from the whole brain while 15 subjects fixated a spot, looked at a geometrical shape, and copied it using a joystick. We performed a detailed analysis of the data to assess (a) their frequency distribution (i.e. how close it was to a normal distribution), (b) the dependence of the standard deviation (SD) on the mean, and (c) the dependence of the response on the preceding baseline. The data showed a strong departure from normality (being skewed to the right and hyperkurtotic), a strong linear dependence of the SD on the mean, and a proportional response over the baseline. These results suggest the need for a logarithmic transformation. Indeed, the log transformation reduced the skewness and kurtosis of the distribution, stabilized the variance, and made the effect additive, i.e. independent of the baseline. We conclude that high-field BOLD fMRI data need to be log-transformed before parametric statistical analyses are applied

Modular organization of directionally tuned cells in the motor cortex: Is there a short-range order?

We investigated the presence of short-range order (<600 μm) in the directional properties of neurons in the motor cortex of the monkey. For that purpose, we developed a quantitative method for the detection of functional cortical modules and used it to examine such potential modules formed by directionally tuned cells. In the functional domain, we labeled each cell by its preferred direction (PD) vector in 3D movement space; in the spatial domain, we used the position of the tip of the recording microelectrode as the cell's coordinate. The images produced by this method represented two orthogonal dimensions in the cortex; one was parallel (“horizontal”) and the other perpendicular (“vertical”) to the cortical layers. The distribution of directionally tuned cells in these dimensions was nonuniform and highly structured. Specifically, cells with similar PDs tended to segregate into vertically oriented minicolumns 50–100 μm wide and at least 500 μm high. Such minicolumns aggregated across the horizontal dimension in a secondary structure of higher order. In this structure, minicolumns with similar PDs were ≈200 μm apart and were interleaved with minicolumns representing nearly orthogonal PDs; in addition, nonoverlapping columns representing nearly opposite PDs were ≈350 μm apart