| 1. |
- Belmeguenai, Amor, et al.
(author)
-
Intrinsic Plasticity Complements Long-Term Potentiation in Parallel Fiber Input Gain Control in Cerebellar Purkinje Cells
- 2010
-
In: The Journal of Neuroscience. - 1529-2401. ; 30:41, s. 13630-13643
-
Journal article (peer-reviewed)abstract
- Synaptic gain control and information storage in neural networks are mediated by alterations in synaptic transmission, such as in long-term potentiation (LTP). Here, we show using both in vitro and in vivo recordings from the rat cerebellum that tetanization protocols for the induction of LTP at parallel fiber (PF)-to-Purkinje cell synapses can also evoke increases in intrinsic excitability. This form of intrinsic plasticity shares with LTP a requirement for the activation of protein phosphatases 1, 2A, and 2B for induction. Purkinje cell intrinsic plasticity resembles CA1 hippocampal pyramidal cell intrinsic plasticity in that it requires activity of protein kinaseA (PKA) and case in kinase 2 (CK2) and is mediated by a downregulation of SK-type calcium-sensitive K conductances. In addition, Purkinje cell intrinsic plasticity similarly results in enhanced spine calcium signaling. However, there are fundamental differences: first, while in the hippocampus increases in excitability result in a higher probability for LTP induction, intrinsic plasticity in Purkinje cells lowers the probability for subsequent LTP induction. Second, intrinsic plasticity raises the spontaneous spike frequency of Purkinje cells. The latter effect does not impair tonic spike firing in the target neurons of inhibitory Purkinje cell projections in the deep cerebellar nuclei, but lowers the Purkinje cell signal-to-noise ratio, thus reducing the PF readout. These observations suggest that intrinsic plasticity accompanies LTP of active PF synapses, while it reduces at weaker, nonpotentiated synapses the probability for subsequent potentiation and lowers the impact on the Purkinje cell output.
|
|
| 2. |
- Jörntell, Henrik, et al.
(author)
-
Cerebellar molecular layer interneurons - computational properties and roles in learning.
- 2010
-
In: Trends in Neurosciences. - : Elsevier BV. - 1878-108X .- 0166-2236. ; 33, s. 524-532
-
Journal article (peer-reviewed)abstract
- In recent years there has been an increased interest in the function of inhibitory interneurons. In the cerebellum this interest has been paired with successes in obtaining recordings from these neurons in vivo and genetic manipulations to probe their function during behavioral tasks such as motor learning. This review focuses on a synthesis of recent findings on the computational properties that these neurons confer to the cerebellar circuitry and on their recently discovered capacity for plasticity and learning in vivo. Since the circuitry of the cerebellar cortex is relatively well-defined, the specificity with which the potential roles of these interneurons can be described will help to guide new avenues of research on the functions of interneurons in general.
|
|
| 3. |
- Lang, Eric J., et al.
(author)
-
The Roles of the Olivocerebellar Pathway in Motor Learning and Motor Control. A Consensus Paper
- 2017
-
In: Cerebellum. - : Springer Science and Business Media LLC. - 1473-4222. ; 16:1, s. 230-252
-
Journal article (peer-reviewed)abstract
- For many decades, the predominant view in the cerebellar field has been that the olivocerebellar system’s primary function is to induce plasticity in the cerebellar cortex, specifically, at the parallel fiber-Purkinje cell synapse. However, it has also long been proposed that the olivocerebellar system participates directly in motor control by helping to shape ongoing motor commands being issued by the cerebellum. Evidence consistent with both hypotheses exists; however, they are often investigated as mutually exclusive alternatives. In contrast, here, we take the perspective that the olivocerebellar system can contribute to both the motor learning and motor control functions of the cerebellum and might also play a role in development. We then consider the potential problems and benefits of it having multiple functions. Moreover, we discuss how its distinctive characteristics (e.g., low firing rates, synchronization, and variable complex spike waveforms) make it more or less suitable for one or the other of these functions, and why having multiple functions makes sense from an evolutionary perspective. We did not attempt to reach a consensus on the specific role(s) the olivocerebellar system plays in different types of movements, as that will ultimately be determined experimentally; however, collectively, the various contributions highlight the flexibility of the olivocerebellar system, and thereby suggest that it has the potential to act in both the motor learning and motor control functions of the cerebellum.
|
|
| 4. |
|
|
| 5. |
- Seepers, R.M., et al.
(author)
-
Enhancing heart-beat-based security for mHealth applications
- 2017
-
In: IEEE Journal of Biomedical and Health Informatics. - 2168-2194 .- 2168-2208. ; 21:1, s. 254-262
-
Journal article (peer-reviewed)abstract
- In heart-beat-based security, a security key is derived from the time difference between two consecutive heart beats (the Inter-Pulse-Interval, IPI) which may, subsequently, be used to enable secure communication. While heart-beatbased security holds promise in mobile health (mHealth) applications, there currently exists no work that provides a detailed characterization of the delivered security in a real system. In this paper, we evaluate the strength of IPI-based security keys in the context of entity authentication. We investigate several aspects which should be considered in practice, including subjects with reduced heart-rate variability, different sensor-sampling frequencies, inter-sensor variability (i.e., how accurate each entity may measure heart beats) as well as average and worst-caseauthentication time. Contrary to the current state of the art, our evaluation demonstrates that authentication using multiple, lessentropic keys may actually increase the key strength by reducing the effects of inter-sensor variability. Moreover, we find that the maximal key strength of a 60-bit key varies between 29.2 bits and only 5.7 bits, depending on the subject's heart-rate variability. To improve security, we introduce the Inter-multi-Pulse Interval (ImPI), a novel method of extracting entropy from the heart by considering the time difference between two non-consecutive heart beats. Given the same authentication time, using the ImPI for key generation increases key strength by up to 3.4x (+19.2 bits) for subjects with limited heart-rate variability, at the cost of an extended key-generation time of 4.8x (+45 sec).
|
|
| 6. |
- Smaragdos, G., et al.
(author)
-
BrainFrame: a node-level heterogeneous accelerator platform for neuron simulations
- 2017
-
In: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 14:6
-
Journal article (peer-reviewed)abstract
- Objective: The advent of High-Performance Computing (HPC) in recent years has led to its increasing use in brain study through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a homogeneous acceleration platform to effectively address the complete array of modeling requirements. Approach: In this paper we propose and build BrainFrame, a heterogeneous acceleration platform that incorporates three distinct acceleration technologies, an Intel Xeon-Phi CPU, a NVidia GP-GPU and a Maxeler Dataflow Engine. The PyNN software framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different experiment instances of a state-of-the-art neuron model, representing the Inferior-Olivary Nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal-network dimensions but also different network-connectivity densities, which can drastically affect the workload's performance characteristics. Main results: The combined use of different HPC fabrics demonstrated that BrainFrame is better able to cope with the modeling diversity encountered in realistic experiments. Our performance analysis shows clearly that the model directly affects performance and all three technologies are required to cope with all the model use cases. Significance: The BrainFrame framework is designed to transparently configure and select the appropriate back-end accelerator technology for use per simulation run. The PyNN integration provides a familiar bridge to the vast number of models already available. Additionally, it gives a clear roadmap for extending the platform support beyond the proof of concept, with improved usability and directly useful features to the computational-neuroscience community, paving the way for wider adoption.
|
|
| 7. |
- Özcan, Orcun Orkan, et al.
(author)
-
Differential Coding Strategies in Glutamatergic and GABAergic Neurons in the Medial Cerebellar Nucleus
- 2020
-
In: Journal of Neuroscience. - : NLM (Medline). - 0270-6474 .- 1529-2401. ; 40:1, s. 159-170
-
Journal article (peer-reviewed)abstract
- The cerebellum drives motor coordination and sequencing of actions at the millisecond timescale through adaptive control of cerebellar nuclear output. Cerebellar nuclei integrate high-frequency information from both the cerebellar cortex and the two main excitatory inputs of the cerebellum: the mossy fibers and the climbing fiber collaterals. However, how nuclear cells process rate and timing of inputs carried by these inputs is still debated. Here, we investigate the influence of the cerebellar cortical output, the Purkinje cells, on identified cerebellar nuclei neurons in vivo in male mice. Using transgenic mice expressing Channelrhodopsin2 specifically in Purkinje cells and tetrode recordings in the medial nucleus, we identified two main groups of neurons based on the waveform of their action potentials. These two groups of neurons coincide with glutamatergic and GABAergic neurons identified by optotagging after Chrimson expression in VGLUT2-cre and GAD-cre mice, respectively. The glutamatergic-like neurons fire at high rate and respond to both rate and timing of Purkinje cell population inputs, whereas GABAergic-like neurons only respond to the mean population firing rate of Purkinje cells at high frequencies. Moreover, synchronous activation of Purkinje cells can entrain the glutamatergic-like, but not the GABAergic-like, cells over a wide range of frequencies. Our results suggest that the downstream effect of synchronous and rhythmic Purkinje cell discharges depends on the type of cerebellar nuclei neurons targeted.
|
|
