Dopamine-induced dissociation of BOLD and neural activity in macaque visual cortex

Neuromodulators determine how neural circuits process information during cognitive states such as wakefulness, attention, learning, and memory [1]. fMRI can provide insight into their function and dynamics, but their exact effect on BOLD responses remains unclear [2, 3 and 4], limiting our ability to interpret the effects of changes in behavioral state using fMRI. Here, we investigated the effects of dopamine (DA) injections on neural responses and haemodynamic signals in macaque primary visual cortex (V1) using fMRI (7T) and intracortical electrophysiology. Aside from DA’s involvement in diseases such as Parkinson’s and schizophrenia, it also plays a role in visual perception [5, 6, 7 and 8]. We mimicked DAergic neuromodulation by systemic injection of L-DOPA and Carbidopa (LDC) or by local application of DA in V1 and found that systemic application of LDC increased the signal-to-noise ratio (SNR) and amplitude of the visually evoked neural responses in V1. However, visually induced BOLD responses decreased, whereas cerebral blood flow (CBF) responses increased. This dissociation of BOLD and CBF suggests that dopamine increases energy metabolism by a disproportionate amount relative to the CBF response, causing the reduced BOLD response. Local application of DA in V1 had no effect on neural activity, suggesting that the dopaminergic effects are mediated by long-range interactions. The combination of BOLD-based and CBF-based fMRI can provide a signature of dopaminergic neuromodulation, indicating that the application of multimodal methods can improve our ability to distinguish sensory processing from neuromodulatory effects

Predicting spike timing of neocortical pyramidal neurons by simple threshold models

Neurons generate spikes reliably with millisecond precision if driven by a fluctuating current—is it then possible to predict the spike timing knowing the input? We determined parameters of an adapting threshold model using data recorded in vitro from 24 layer 5 pyramidal neurons from rat somatosensory cortex, stimulated intracellularly by a fluctuating current simulating synaptic bombardment in vivo. The model generates output spikes whenever the membrane voltage (a filtered version of the input current) reaches a dynamic threshold. We find that for input currents with large fluctuation amplitude, up to 75% of the spike times can be predicted with a precision of ±2ms. Some of the intrinsic neuronal unreliability can be accounted for by a noisy threshold mechanism. Our results suggest that, under random current injection into the soma, (i) neuronal behavior in the subthreshold regime can be well approximated by a simple linear filter; and (ii) most of the nonlinearities are captured by a simple threshold proces

Two distinct profiles of fMRI and neurophysiological activity elicited by acetylcholine in visual cortex

Cholinergic neuromodulation is involved in all aspects of sensory processing and is crucial for processes such as attention, learning and memory, etc. However, despite the known roles of acetylcholine (ACh), we still do not how to disentangle ACh contributions from sensory or task-evoked changes in functional magnetic resonance imaging (fMRI). Here, we investigated the effects of local injection of ACh on fMRI and neural signals in the primary visual cortex (V1) of anesthetized macaques by combining pharmaco-based MRI (phMRI) with electrophysiological recordings, using single electrodes and electrode arrays. We found that local injection of ACh elicited two distinct profiles of fMRI and neurophysiological activity, depending on the distance from the injector. Near the injection site, we observed an increase in the baseline blood oxygen-level-dependent (BOLD) and cerebral blood flow (CBF) responses, while their visual modulation decreased. In contrast, further from the injection site, we observed an increase in the visually induced BOLD and CBF modulation without changes in baseline. Neurophysiological recordings suggest that the spatial correspondence between fMRI responses and neural activity does not change in the gamma, high-gamma, and multiunit activity (MUA) bands. The results near the injection site suggest increased inhibitory drive and decreased metabolism, contrasting to the far region. These changes are thought to reflect the kinetics of ACh and its metabolism to choline

The gravitational wave background from star-massive black hole fly-bys

Stars on eccentric orbits around a massive black hole (MBH) emit bursts of gravitational waves (GWs) at periapse. Such events may be directly resolvable in the Galactic centre. However, if the star does not spiral in, the emitted GWs are not resolvable for extra-galactic MBHs, but constitute a source of background noise. We estimate the power spectrum of this extreme mass ratio burst background (EMBB) and compare it to the anticipated instrumental noise of the Laser Interferometer Space Antenna (LISA). To this end, we model the regions close to a MBH, accounting for mass-segregation, and for processes that limit the presence of stars close to the MBH, such as GW inspiral and hydrodynamical collisions between stars. We find that the EMBB is dominated by GW bursts from stellar mass black holes, and the magnitude of the noise spectrum (f S_GW)^{1/2} is at least a factor ~10 smaller than the instrumental noise. As an additional result of our analysis, we show that LISA is unlikely to detect relativistic bursts in the Galactic centre.Comment: Accepted for publication by MNRAS; New appendix on population of phase space in presence of gravitational wave inspira

A general property for time aggregation

We classify all functions of multivariate stochastic processes having time-series estimates that are independent of data frequency. Such an estimator applied to high-frequency data may be used to infer properties of estimates relating to low-frequency data. Our property encompasses two previously-proposed time-aggregation properties (with limited solutions) as different special cases. Our general time-aggregating functions satisfy a pair of coupled second-order partial differential equations. We derive analytic solutions for arbitrary-dimensional martingales and log-martingales. The time-aggregation property of a time-series model is similar – indeed time-aggregating functions always correspond to point estimators based on expected values – but we do not propose a specific new forecasting model. However, we do derive time-aggregating unbiased and efficient estimators for nth-order moments of log returns, applying these results to problems facing portfolio managers who re-optimise portfolios or hedge their risks at lower frequencies than the frequency at which their risk premia are monitored

Directed energy deposition-arc (DED-Arc) and numerical welding simulation as a method to determine the homogeneity

This research presents a hybrid approach to for the prediction of the homogeneity of mechanical properties in 3D metal parts manufactured using directed energy deposition-arc (DED-Arc). DED-Arc is an additive manufacturing process which can offer a cost-effective way to manufacture 3D metal parts, due to high deposition rate of up to 8 kg/h. Regression equations developed in a previous study were used to predict the mechanical properties of a wall structure using only the cooling time t8/5 calculated in a numerical welding simulation. The new approach in this research paper contains the prediction of the homogeneity of the mechanical properties, especially hardness, in 3D metal parts, which can vary due to localized changes in t8/5 cooling time provoked by specific geometrical features or general changes in dimensions. In this study a method for the calculation of the hardness distribution on additively manufactured parts was developed and shown