No abstract

The classically conditioned eyeblink response in the rabbit is one of the best-characterized behavioral models of associative learning. It is cerebellum dependent, with many studies indicating that the hemispheral part of Larsell's cerebellar cortical lobule VI (HVI) is critical for the acquisition and performance of learned responses. However, there remain uncertainties about the distribution of the critical regions within and around HVI. In this learning, the unconditional stimulus is thought to be carried by periocular-activated climbing fibers. Here, we have used a microelectrode array to perform systematic, high-resolution, electrophysiological mapping of lobule HVI and surrounding folia in rabbits, to identify regions with periocular-evoked climbing fiber activity. Climbing fiber local field potentials and single-unit action potentials were recorded, and electrode locations were reconstructed from histological examination of brain sections. Much of the sampled cerebellar cortex, including large parts of lobule HVI, was unresponsive to periocular input. However, short-latency ipsilateral periocular-evoked climbing fiber responses were reliably found within a region in the ventral part of the medial wall of lobule HVI, extending to the base of the primary fissure. Small infusions of the AMPA/kainate receptor antagonist CNQX into this electrophysiologically defined region in awake rabbits diminished or abolished conditioned responses. The known parasagittal zonation of the cerebellum, supported by zebrin immunohistochemistry, indicates that these areas have connections consistent with an essential role in eyeblink conditioning. These small eyeblink-related areas provide cerebellar cortical targets for analysis of eyeblink conditioning at a neuronal level but need to be localized with electrophysiological identification in individual animals.

Local field potentials (LFPs) may afford insight into the mechanisms of action of deep brain stimulation (DBS) and potential feedback signals for adaptive DBS. In Parkinson's disease (PD) DBS of the subthalamic nucleus (STN) suppresses spontaneous activity in the beta band and drives evoked resonant neural activity (ERNA). Here, we investigate how STN LFP activities change over time following the onset and offset of DBS. To this end we recorded LFPs from the STN in 14 PD patients during long (mean: 181.2 s) and short (14.2 s) blocks of continuous stimulation at 130 Hz. LFP activities were evaluated in the temporal and spectral domains. During long stimulation blocks, the frequency and amplitude of the ERNA decreased before reaching a steady state after ~70 s. Maximal ERNA amplitudes diminished over repeated stimulation blocks. Upon DBS cessation, the ERNA was revealed as an under-damped oscillation, and was more marked and lasted longer after short duration stimulation blocks. In contrast, activity in the beta band suppressed within 0.5 s of continuous DBS onset and drifted less over time. Spontaneous activity was also suppressed in the low gamma band, suggesting that the effects of high frequency stimulation on spontaneous oscillations may not be selective for pathological beta activity. High frequency oscillations were present in only six STN recordings before stimulation onset and their frequency was depressed by stimulation. The different dynamics of the ERNA and beta activity with stimulation imply different DBS mechanisms and may impact how these activities may be used in adaptive feedback.

Despite our fine-grain anatomical knowledge of the cerebellar cortex, electrophysiological studies of circuit information processing over the last fifty years have been hampered by the difficulty of reliably assigning signals to identified cell types. We approached this problem by assessing the spontaneous activity signatures of identified cerebellar cortical neurones. A range of statistics describing firing frequency and irregularity were then used, individually and in combination, to build Gaussian Process Classifiers (GPC) leading to a probabilistic classification of each neurone type and the computation of equi-probable decision boundaries between cell classes. Firing frequency statistics were useful for separating Purkinje cells from granular layer units, whilst firing irregularity measures proved most useful for distinguishing cells within granular layer cell classes. Considered as single statistics, we achieved classification accuracies of 72.5% and 92.7% for granular layer and molecular layer units respectively. Combining statistics to form twin-variate GPC models substantially improved classification accuracies with the combination of mean spike frequency and log-interval entropy offering classification accuracies of 92.7% and 99.2% for our molecular and granular layer models, respectively. A cross-species comparison was performed, using data drawn from anaesthetised mice and decerebrate cats, where our models offered 80% and 100% classification accuracy. We then used our models to assess non-identified data from awake monkeys and rabbits in order to highlight subsets of neurones with the greatest degree of similarity to identified cell classes. In this way, our GPC-based approach for tentatively identifying neurones from their spontaneous activity signatures, in the absence of an established ground-truth, nonetheless affords the experimenter a statistically robust means of grouping cells with properties matching known cell classes. Our approach therefore may have broad application to a variety of future cerebellar cortical investigations, particularly in awake animals where opportunities for definitive cell identification are limited.

A BS TRACT: Background: High-frequency thalamic stimulation is an effective therapy for essential tremor, which mainly affects voluntary movements and/or sustained postures. However, continuous stimulation may deliver unnecessary current to the brain due to the intermittent nature of the tremor. Objective: We proposed to close the loop of thalamic stimulation by detecting tremor-provoking movement states using local field potentials recorded from the same electrodes implanted for stimulation, so that the stimulation is only delivered when necessary. Methods: Eight patients with essential tremor participated in this study. Patient-specific support vector machine classifiers were first trained using data recorded while the patient performed tremor-provoking movements. Then, the trained models were applied in real-time to detect these movements and triggered the delivery of stimulation. Results: Using the proposed method, stimulation was switched on for 80.37 ± 7.06% of the time when tremorevoking movements were present. In comparison, the stimulation was switched on for 12.71 ± 7.06% of the time when the patients were at rest and tremor-free. Compared with continuous stimulation, a similar amount of tremor suppression was achieved while only delivering 36.62 ± 13.49% of the energy used in continuous stimulation. Conclusions: The results suggest that responsive thalamic stimulation for essential tremor based on tremorprovoking movement detection can be achieved without any requirement for external sensors or additional electrocorticography strips. Further research is required to investigate whether the decoding model is stable across time and generalizable to the variety of activities patients may engage with in everyday life.

Bursts of beta frequency band activity in the basal ganglia of patients with Parkinson's disease (PD) are associated with impaired motor performance. Here we test in human adults whether small variations in the timing of movement relative to beta bursts have a critical effect on movement velocity and whether the cumulative effects of multiple beta bursts, both locally and across networks, matter. We recorded local field potentials from the subthalamic nucleus (STN) in 15 PD patients of both genders OFF-medication, during temporary lead externalization after deep brain stimulation surgery. Beta bursts were defined as periods exceeding the 75th percentile amplitude threshold. Subjects performed a visual cued joystick reaching task, with the visual cue being triggered in real time with different temporal relationships to bursts of STN beta activity. The velocity of actions made in response to cues prospectively triggered by STN beta bursts was slower than when responses were not time-locked to recent beta bursts. Importantly, slow movements were those that followed multiple bursts close to each other within a trial. In contrast, small differences in the delay between the last burst and movement onset had no significant impact on velocity. Moreover, when the overlap of bursts between the two STN was high, slowing was more pronounced. Our findings suggest that the cumulative, but recent, history of beta bursting, both locally and across basal ganglia networks, may impact on motor performance.

We recently showed that the activity of cerebellar Golgi cells can be powerfully modulated by stimulation of peripheral afferents, in a pattern different to local Purkinje cells. Here we have examined the pathways underlying these responses. Graded electrical stimulation of muscle and cutaneous nerves revealed that long-lasting depressions and short-lasting excitations of Golgi cells were evoked by stimulation of cutaneous nerves at stimulus intensities that activated large mechanoreceptive afferents, and grew as additional afferents were recruited. In contrast, none of the neurones responded to stimulation of muscle nerves at intensities that activated group I afferents, although about half responded with long-lasting depressions, but not excitations, to stimuli that recruited group II and III afferents. Selective lesions of the spinal dorsal columns did not affect either of these types of response. After lesions of one lateral funiculus in the lumbar cord the responses evoked by stimulation of the hindlimb contralateral to the lesion were reduced or abolished, leaving responses evoked by ipsilateral hindlimb afferents unaltered. Since both ipsi-and contralateral afferents generate responses in Golgi cells, the convergence from the two sides must occur supraspinally. It is difficult to reconcile these properties with any of the direct spinocerebellar pathways or spinoreticulocerebellar pathways that have been described. Instead, it is likely that the responses are evoked via the multimodal 'wide dynamic range' neurones of the anterolateral system. Golgi cell activity may thus be powerfully enhanced or depressed during arousal via the anterolateral system.

Finely-tuned gamma (FTG) oscillations can be recorded from cortex or the subthalamic nucleus (STN) in patients with Parkinson’s disease (PD) on dopaminergic medication, and have been associated with dyskinesias. When recorded during deep brain stimulation (DBS) on medication the FTG is entrained to half the stimulation frequency. We investigated whether these characteristics are shared off medication by recording local field potentials (LFP) from the STN from externalised DBS leads in 14 PD patients after overnight withdrawal of medication. FTG was induced de-novo by DBS in the absence of dyskinesias in a third of our cohort. The FTG could outlast stimulation or arise only after DBS ceased. FTG frequencies decreased during and across consec-utive DBS blocks, but did not shift with changing stimulation frequency off medication. Together with the sustained after-effects this argues against simple entrainment by DBS in the off medication state. We also found significant coherence between STN-LFP and electroencephalogram (EEG) signals at FTG frequencies. We conclude that FTG is a network phenomenon that behaves differently in the off medication state, when it is neither associated with dyskinesias nor susceptible to entrainment.