8,998 research outputs found
Prefrontal control over motor cortex cycles at beta-frequency during movement inhibition
A fully adapted behavior requires maximum efficiency to inhibit processes in the motor domain [ 1 ]. Although a number of cortical and subcortical brain regions have been implicated, converging evidence suggests that activation of right inferior frontal gyrus (r-IFG) and right presupplementary motor area (r-preSMA) is crucial for successful response inhibition [ 2, 3 ]. However, it is still unknown how these prefrontal areas convey the necessary signal to the primary motor cortex (M1), the cortical site where the final motor plan eventually has to be inhibited or executed. On the basis of the widely accepted view that brain oscillations are fundamental for communication between neuronal network elements [ 4–6 ], one would predict that the transmission of these inhibitory signals within the prefrontal-central networks (i.e., r-IFG/M1 and/or r-preSMA/M1) is realized in rapid, periodic bursts coinciding with oscillatory brain activity at a distinct frequency. However, the dynamics of corticocortical effective connectivity has never been directly tested on such timescales. By using double-coil transcranial magnetic stimulation (TMS) and electroencephalography (EEG) [ 7, 8 ], we assessed instantaneous prefrontal-to-motor cortex connectivity in a Go/NoGo paradigm as a function of delay from (Go/NoGo) cue onset. In NoGo trials only, the effects of a conditioning prefrontal TMS pulse on motor cortex excitability cycled at beta frequency, coinciding with a frontocentral beta signature in EEG. This establishes, for the first time, a tight link between effective cortical connectivity and related cortical oscillatory activity, leading to the conclusion that endogenous (top-down) inhibitory motor signals are transmitted in beta bursts in large-scale cortical networks for inhibitory motor control
Linear stability in networks of pulse-coupled neurons
In a first step towards the comprehension of neural activity, one should
focus on the stability of the various dynamical states. Even the
characterization of idealized regimes, such as a perfectly periodic spiking
activity, reveals unexpected difficulties. In this paper we discuss a general
approach to linear stability of pulse-coupled neural networks for generic
phase-response curves and post-synaptic response functions. In particular, we
present: (i) a mean-field approach developed under the hypothesis of an
infinite network and small synaptic conductances; (ii) a "microscopic" approach
which applies to finite but large networks. As a result, we find that no matter
how large is a neural network, its response to most of the perturbations
depends on the system size. There exists, however, also a second class of
perturbations, whose evolution typically covers an increasingly wide range of
time scales. The analysis of perfectly regular, asynchronous, states reveals
that their stability depends crucially on the smoothness of both the
phase-response curve and the transmitted post-synaptic pulse. The general
validity of this scenarion is confirmed by numerical simulations of systems
that are not amenable to a perturbative approach.Comment: 13 pages, 7 figures, submitted to Frontiers in Computational
Neuroscienc
Phase Dependency of the Human Primary Motor Cortex and Cholinergic Inhibition Cancelation during Beta tACS
The human motor cortex has a tendency to resonant activity at about 20 Hz so stimulation should more readily entrain neuronal populations at this frequency. We investigated whether and how different interneuronal circuits contribute to such resonance by using transcranial magnetic stimulation (TMS) during transcranial alternating current stimulation (tACS) at motor (20 Hz) and a nonmotor resonance frequency (7 Hz). We tested different TMS interneuronal protocols and triggered TMS pulses at different tACS phases. The effect of cholinergic short-latency afferent inhibition (SAI) was abolished by 20 Hz tACS, linking cortical beta activity to sensorimotor integration. However, this effect occurred regardless of the tACS phase. In contrast, 20 Hz tACS selectively modulated MEP size according to the phase of tACS during single pulse, GABAAergic short-interval intracortical inhibition (SICI) and glutamatergic intracortical facilitation (ICF). For SICI this phase effect was more marked during 20 Hz stimulation. Phase modulation of SICI also depended on whether or not spontaneous beta activity occurred at ~20 Hz, supporting an interaction effect between tACS and underlying circuit resonances. The present study provides in vivo evidence linking cortical beta activity to sensorimotor integration, and for beta oscillations in motor cortex being promoted by resonance in GABAAergic interneuronal circuits
Encoding and processing of sensory information in neuronal spike trains
Recently, a statistical signal-processing technique has allowed the information carried by single spike trains of sensory neurons on time-varying stimuli to be characterized quantitatively in a variety of preparations. In weakly electric fish, its application to first-order sensory neurons encoding electric field amplitude (P-receptor afferents) showed that they convey accurate information on temporal modulations in a behaviorally relevant frequency range (<80 Hz). At the next stage of the electrosensory pathway (the electrosensory lateral line lobe, ELL), the information sampled by first-order neurons is used to extract upstrokes and downstrokes in the amplitude modulation waveform. By using signal-detection techniques, we determined that these temporal features are explicitly represented by short spike bursts of second-order neurons (ELL pyramidal cells). Our results suggest that the biophysical mechanism underlying this computation is of dendritic origin. We also investigated the accuracy with which upstrokes and downstrokes are encoded across two of the three somatotopic body maps of the ELL (centromedial and lateral). Pyramidal cells of the centromedial map, in particular I-cells, encode up- and downstrokes more reliably than those of the lateral map. This result correlates well with the significance of these temporal features for a particular behavior (the jamming avoidance response) as assessed by lesion experiments of the centromedial map
Impaired Auditory Temporal Selectivity in the Inferior Colliculus of Aged Mongolian Gerbils
Aged humans show severe difficulties in temporal auditory processing tasks (e.g., speech recognition in noise, low-frequency sound localization, gap detection). A degradation of auditory function with age is also evident in experimental animals. To investigate age-related changes in temporal processing, we compared extracellular responses to temporally variable pulse trains and human speech in the inferior colliculus of young adult (3 month) and aged (3 years) Mongolian gerbils. We observed a significant decrease of selectivity to the pulse trains in neuronal responses from aged animals. This decrease in selectivity led, on the population level, to an increase in signal correlations and therefore a decrease in heterogeneity of temporal receptive fields and a decreased efficiency in encoding of speech signals. A decrease in selectivity to temporal modulations is consistent with a downregulation of the inhibitory transmitter system in aged animals. These alterations in temporal processing could underlie declines in the aging auditory system, which are unrelated to peripheral hearing loss. These declines cannot be compensated by traditional hearing aids (that rely on amplification of sound) but may rather require pharmacological treatment
Variability in the Firing of Nerve Impulses in Eccentric Cells of the Limulus Eye
Thesis is concerned with the source and characteristics of variability in the discharge of impulses by neurons. The neuron in which variability was studied is the eccentric cell in the compound eye of the horseshoe crab, Limulus polyphemus. In Part I a theory is presented which accounts for the variability in the response of an eccentric cell to light. The main idea of this theory is that the source of randomness in the impulse rate is noise in the generator potential. Another essential aspect of the theory is the view that the process which codes the generator potential into the impulse rate may be treated as a linear filter. These ideas lead directly to Fourier analysis of the fluctuations of the generator potential and fluctuations of the impulse rate. Experimental verification of theoretical predictions was obtained by measurement of the fluctuations and calculation of their variance spectrum. The variance spectrum (or power spectrum) of the impulse rate is shown to be the filtered variance spectrum of the generator potential. Another verification of the theory is the finding that in many cells the signal-to-noise ratio is constant for responses to sinusoidally modulated light, at all modulation frequencies. Inhibition from neighboring eccentric cells will have an effect on the variability of firing of a given eccentric cell. The effects of inhibition are discussed in Part II. The reduction in the average impulse rate which is caused by inhibition decreases the variance of the impulse rate. However, this reduction of the average impulse rate increases the coefficient of variation of the impulse rate. Inhibitory synaptic noise adds to the low frequency portion of the variance spectrum of the impulse rate. This occurs because of the Ill slow time course of the inhibitory synaptic potentials. As a consequence, inhibition decreases the signal-to-noise ratio for low frequency modulated stimuli. The net effect of inhibition is to increase the coefficient of variation of the impulse rate. This effect is predicted by the linear model of the eccentric cell. The same qualitative effect is predicted by other theories of neuronal variability, although its importance is stressed here for the first time
Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience
This essay is presented with two principal objectives in mind: first, to
document the prevalence of fractals at all levels of the nervous system, giving
credence to the notion of their functional relevance; and second, to draw
attention to the as yet still unresolved issues of the detailed relationships
among power law scaling, self-similarity, and self-organized criticality. As
regards criticality, I will document that it has become a pivotal reference
point in Neurodynamics. Furthermore, I will emphasize the not yet fully
appreciated significance of allometric control processes. For dynamic fractals,
I will assemble reasons for attributing to them the capacity to adapt task
execution to contextual changes across a range of scales. The final Section
consists of general reflections on the implications of the reviewed data, and
identifies what appear to be issues of fundamental importance for future
research in the rapidly evolving topic of this review
Time-resolved magnetic sensing with electronic spins in diamond
Quantum probes can measure time-varying fields with high sensitivity and
spatial resolution, enabling the study of biological, material, and physical
phenomena at the nanometer scale. In particular, nitrogen-vacancy centers in
diamond have recently emerged as promising sensors of magnetic and electric
fields. Although coherent control techniques have measured the amplitude of
constant or oscillating fields, these techniques are not suitable for measuring
time-varying fields with unknown dynamics. Here we introduce a coherent
acquisition method to accurately reconstruct the temporal profile of
time-varying fields using Walsh sequences. These decoupling sequences act as
digital filters that efficiently extract spectral coefficients while
suppressing decoherence, thus providing improved sensitivity over existing
strategies. We experimentally reconstruct the magnetic field radiated by a
physical model of a neuron using a single electronic spin in diamond and
discuss practical applications. These results will be useful to implement
time-resolved magnetic sensing with quantum probes at the nanometer scale.Comment: 8+12 page
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