Ronen Sosnik

Transformation from temporal to rate coding in a somatosensory thalamocortical pathway.

The anatomical connections from the whiskers to the rodent somatosensory (barrel) cortex form two parallel (lemniscal and paralemniscal) pathways. It is unclear whether the paralemniscal pathway is directly involved in tactile processing, because paralemniscal neuronal responses show poor spatial resolution, labile latencies and strong dependence on cortical feedback. Here we show that the paralemniscal system can transform temporally encoded vibrissal information into a rate code. We recorded the representations of the frequency of whisker movement along the two pathways in anaesthetized rats. In response to varying stimulus frequencies, the lemniscal neurons exhibited amplitude modulations and constant latencies. In contrast, paralemniscal neurons in both thalamus and cortex coded the input frequency as changes in latency. Because the onset latencies increased and the offset latencies remained constant, the latency increments were translated into a rate code: increasing onset latencies led to lower spike counts. A thalamocortical loop that includes cortical oscillations and thalamic gating can account for these results. Thus, variable latencies and effective cortical feedback in the paralemniscal system can serve the processing of temporal sensory cues, such as those that encode object location during whisking. In contrast, fixed time locking in the lemniscal system is crucial for reliable spatial processing.

A neuronal analogue of state-dependent learning

State-dependent learning is a phenomenon in which the retrieval of newly acquired information is possible only if the subject is in the same sensory context and physiological state as during the encoding phase. In spite of extensive behavioural and pharmacological characterization, no cellular counterpart of this phenomenon has been reported. Here we describe a neuronal analogue of state-dependent learning in which cortical neurons show an acetylcholine-dependent expression of an acetylcholine-induced functional plasticity. This was demonstrated on neurons of rat somatosensory ‘barrel’ cortex, whose tunings to the temporal frequency of whisker deflections were modified by cellular conditioning. Pairing whisker stimulation with acetylcholine applied iontophoretically yielded selective lasting modification of responses, the expression of which depended on the presence of exogenous acetylcholine. Administration of acetylcholine during testing revealed frequency-specific changes in response that were not expressed when tested without acetylcholine or when the muscarinic antagonist, atropine, was applied concomitantly. Our results suggest that both acquisition and recall can be controlled by the cortical release of acetylcholine.

When practice leads to co-articulation: the evolution of geometrically defined movement primitives.

The skilled generation of motor sequences involves the appropriate choice, ordering and timing of a sequence of simple, stereotyped movement elements. Nevertheless, a given movement element within a well-rehearsed sequence can be modified through interaction with its neighboring elements (co-articulation). We show that extensive training on a sequence of planar hand trajectories passing through several targets resulted in the co-articulation of movement components, and in the formation of new movement elements (primitives). Reduction in movement duration was accompanied by the gradual replacement of straight trajectories by longer curved ones, the latter affording the maximization of movement smoothness. Surprisingly, the curved trajectories were generated even when new target configurations were introduced, i.e., when target distances were scaled, movement direction reversed or when different start and end positions were used, indicating the acquisition of geometrically defined movement elements. However, the new trajectories were not shared by the untrained hand. Altogether, our results suggest that novel movement elements can be acquired through extensive training in adults.

Simultaneous multi-site recordings and iontophoretic drug and dye applications along the trigeminal system of anesthetized rats.

A multi-electrode system that permits simultaneous recordings from multiple neurons and iontophoretic applications at two or three different brain sites during acute experiments is described. This system consists of two or three microdrive terminals, each of which includes four electrodes that can be moved independently and used for both extracellular recordings and microiontophoretic drug administration. Drug applications were performed during standard extracellular recordings of multiple single-units via specialized combined electrodes (CEs), which enable ejection of neuroactive substances and recording of neuronal activity from the same electrode. With this system, we were able to successfully record simultaneously from different levels (brainstem, thalamus, and cortex) of the vibrissal ascending pathway of the anesthetized rat. Herein, examples of simultaneous recordings from the brainstem and thalamus and from the thalamus and cortex are presented. An effect of iontophoretic applications of agonists and antagonists of metabotropic glutamate receptors (mGluRs) in the thalamus is demonstrated, and the extent of drug diffusion in the barrel cortex is demonstrated with biocytin. This new multi-electrode system will facilitate the study of transformations of sensory information acquired by the whiskers into cortical representations.

The acquisition and implementation of the smoothness maximization motion strategy is dependent on spatial accuracy demands

We recently showed that extensive training on a sequence of planar hand trajectories passing through several targets resulted in the co-articulation of movement components and in the formation of new movement elements (primitives) (Sosnik et al. in Exp Brain Res 156(4):422–438, 2004). Reduction in movement duration was accompanied by the gradual replacing of a piecewise combination of rectilinear trajectories with a single, longer curved one, the latter affording the maximization of movement smoothness (“global motion planning”). The results from transfer experiments, conducted by the end of the last training session, have suggested that the participants have acquired movement elements whose attributes were solely dictated by the figural (i.e., geometrical) form of the path, rather than by both path geometry and its time derivatives. Here we show that the acquired movement generation strategy (“global motion planning”) was not specific to the trained configuration or total movement duration. Performance gain (i.e., movement smoothness, defined by the fit of the data to the behavior, predicted by the “global planning” model) transferred to non-trained configurations in which the targets were spatially co-aligned or when participants were instructed to perform the task in a definite amount of time. Surprisingly, stringent accuracy demands, in transfer conditions, resulted not only in an increased movement duration but also in reverting to the straight trajectories (loss of co-articulation), implying that the performance gain was dependent on accuracy constraints. Only 28.5% of the participants (two out of seven) who were trained in the absence of visual feedback from the hand (dark condition) co-articulated by the end of the last training session compared to 75% (six out of eight) who were trained in the light, and none of them has acquired a geometrical motion primitive. Furthermore, six naïve participants who trained in dark condition on large size targets have all co-articulated by the end of the last training session, still, none of them has acquired a geometrical motion primitive. Taken together, our results indicate that the acquisition of a geometrical motion primitive is dependent on the existence of visual feedback from the hand and that the implementation of the smoothness-maximization motion strategy is dependent on spatial accuracy demands. These findings imply that the specific features of the training experience (i.e., temporal or spatial task demands) determine the attributes of an acquired motion planning strategy and primitive.

A new method to record and control for 2D-movement kinematics during functional magnetic resonance imaging (fMRI).

The recording of movement kinematics during functional magnetic resonance imaging (fMRI) experiments is complicated due to technical constraints of the imaging environment. Nevertheless, to study the functions of brain areas related to motor control, reliable and accurate records of movement trajectories and speed profiles are needed. We present a method designed to record and characterize the kinematic properties of drawing- and handwriting-like forearm movements during fMRI studies by recording pen stroke trajectories. The recording system consists of a translucent plastic board, a plastic pen containing fiber optics and a halogen light power source, a CCD camera, a video monitor and a PC with a video grabber card. Control experiments using a commercially available digitizer tablet have demonstrated the reliability of the data recorded during fMRI. Since the movement tracking signal is purely optical, there is no interaction with the MR (echoplanar) images. Thus, the method allows to obtain movement records with high spatial and temporal resolution which are suitable for the kinematic analysis of hand movements in fMRI studies.

The point of no return in planar hand movements: an indication of the existence of high level motion primitives.

Previous psychophysical studies have sought to determine whether the processes of movement engagement and termination are dissociable, whether stopping an action is a generic process, and whether there is a point in time in which the generation of a planned action is inevitable (“point of no return”). It is not clear yet, however, whether the action of stopping is merely a manifestation of low level, dynamic constraints, or whether it is also subject to a high level, kinematic plan. In the present study, stopping performance was studied while nine subjects, who generated free scribbling movements looking for the location of an invisible circular target, were requested unexpectedly to impede movement. Temporal analysis of the data shows that in 87% of the movements subsequent to the ‘stop’ cue, the tangential motion velocity profile was not a decelerating function of the time but rather exhibited a complex pattern comprised of one or more velocity peaks, implying an unstoppable motion element. Furthermore, geometrical analysis shows that the figural properties of the path generated after the ‘stop’ cue were part of a repetitive geometrical pattern and that the probability of completing a pattern after the ‘stop’ cue was correlated with the relative advance in the geometrical plan rather than the amount of time that had elapsed from the pattern initiation. Altogether, these findings suggest that the “point of no return” phenomenon in humans may also reflect a high level kinematic plan and could serve as a new operative definition of motion primitives.

E3D hand movement velocity reconstruction using power spectral density of EEG signals and neural network

Three dimensional (3D) limb motion trajectory is predictable with a non-invasive brain-computer interface (BCI). To date, most non-invasive motion trajectory prediction BCIs use potential values of electroencephalographic (EEG) signals as the input to a multiple linear regression (mLR) based kinetic data estimator. We investigated the possible improvement in accuracy of 3D hand movement prediction (i.e., the correlation of registered and reconstructed hand velocities) by replacing raw EEG potentials with spectrum power values of specific EEG bands. We also investigated if a non-linear neural network based estimator outperformed the mLR approach. The spectrum power model provided significantly higher accuracy (R~0.60) compared to the similar EEG potentials based approach (R~0.45). Additionally, when replacing the mLR based kinetic data estimation module with a feed-forward neural network (NN) we found the NN based spectrum power model provided higher accuracy (R~0.70) compared to the similar mLR based approach (R~0.60).

Latency Coding in POm: Importance of Parametric Regimes

to the editor: In a recent Epub issue of the Journal of Neurophysiology , a paper ([Masri et al. 2008][1]) appeared in which the authors claim to replicate experiments, but not results, previously obtained in our laboratory ([Ahissar et al. 2000][2]; [Sosnik et al. 2001][3]). We maintain that Masri

3D hand motion trajectory prediction from EEG mu and beta bandpower.

A motion trajectory prediction (MTP) - based brain-computer interface (BCI) aims to reconstruct the three-dimensional (3D) trajectory of upper limb movement using electroencephalography (EEG). The most common MTP BCI employs a time series of bandpass-filtered EEG potentials (referred to here as the potential time-series, PTS, model) for reconstructing the trajectory of a 3D limb movement using multiple linear regression. These studies report the best accuracy when a 0.5-2Hz bandpass filter is applied to the EEG. In the present study, we show that spatiotemporal power distribution of theta (4-8Hz), mu (8-12Hz), and beta (12-28Hz) bands are more robust for movement trajectory decoding when the standard PTS approach is replaced with time-varying bandpower values of a specified EEG band, ie, with a bandpower time-series (BTS) model. A comprehensive analysis comprising of three subjects performing pointing movements with the dominant right arm toward six targets is presented. Our results show that the BTS model produces significantly higher MTP accuracy (R~0.45) compared to the standard PTS model (R~0.2). In the case of the BTS model, the highest accuracy was achieved across the three subjects typically in the mu (8-12Hz) and low-beta (12-18Hz) bands. Additionally, we highlight a limitation of the commonly used PTS model and illustrate how this model may be suboptimal for decoding motion trajectory relevant information. Although our results, showing that the mu and beta bands are prominent for MTP, are not in line with other MTP studies, they are consistent with the extensive literature on classical multiclass sensorimotor rhythm-based BCI studies (classification of limbs as opposed to motion trajectory prediction), which report the best accuracy of imagined limb movement classification using power values of mu and beta frequency bands. The methods proposed here provide a positive step toward noninvasive decoding of imagined 3D hand movements for movement-free BCIs.