Alexander Rauch

The effects of electrical microstimulation on cortical signal propagation

Electrical stimulation has been used in animals and humans to study potential causal links between neural activity and specific cognitive functions. Recently, it has found increasing use in electrotherapy and neural prostheses. However, the manner in which electrical stimulation–elicited signals propagate in brain tissues remains unclear. We used combined electrostimulation, neurophysiology, microinjection and functional magnetic resonance imaging (fMRI) to study the cortical activity patterns elicited during stimulation of cortical afferents in monkeys. We found that stimulation of a site in the lateral geniculate nucleus (LGN) increased the fMRI signal in the regions of primary visual cortex (V1) that received input from that site, but suppressed it in the retinotopically matched regions of extrastriate cortex. Consistent with previous observations, intracranial recordings indicated that a short excitatory response occurring immediately after a stimulation pulse was followed by a long-lasting inhibition. Following microinjections of GABA antagonists in V1, LGN stimulation induced positive fMRI signals in all of the cortical areas. Taken together, our findings suggest that electrical stimulation disrupts cortico-cortical signal propagation by silencing the output of any neocortical area whose afferents are electrically stimulated.

The effect of a serotonin-induced dissociation between spiking and perisynaptic activity on BOLD functional MRI

The relationship of the blood oxygen-level-dependent (BOLD) signal to its underlying neuronal activity is still poorly understood. Combined physiology and functional MRI experiments suggested that local field potential (LFP) is a better predictor of the BOLD signal than multiunit activity (MUA). To further explore this relationship, we simultaneously recorded BOLD and electrophysiological activity while inducing a dissociation of MUA from LFP activity with injections of the neuromodulator BP554 into the primary visual cortex of anesthetized monkeys. BP554 is a 5-HT1A agonist acting primarily on the membrane of efferent neurons by potassium-induced hyperpolarization. Its infusion in visual cortex reliably reduced MUA without affecting either LFP or BOLD activity. This finding suggests that the efferents of a neuronal network pose relatively little metabolic burden compared with the overall presynaptic and postsynaptic processing of incoming afferents. We discuss implications of this finding for the interpretation of BOLD activity.

A benchmark test for a quantitative assessment of simple neuron models

Several methods and algorithms have recently been proposed that allow for the systematic evaluation of simple neuron models from intracellular or extracellular recordings. Models built in this way generate good quantitative predictions of the future activity of neurons under temporally structured current injection. It is, however, difficult to compare the advantages of various models and algorithms since each model is designed for a different set of data. Here, we report about one of the first attempts to establish a benchmark test that permits a systematic comparison of methods and performances in predicting the activity of rat cortical pyramidal neurons. We present early submissions to the benchmark test and discuss implications for the design of future tests and simple neurons models.

Temporal kernel CCA and its application in multimodal neuronal data analysis

Data recorded from multiple sources sometimes exhibit non-instantaneous couplings. For simple data sets, cross-correlograms may reveal the coupling dynamics. But when dealing with high-dimensional multivariate data there is no such measure as the cross-correlogram. We propose a simple algorithm based on Kernel Canonical Correlation Analysis (kCCA) that computes a multivariate temporal filter which links one data modality to another one. The filters can be used to compute a multivariate extension of the cross-correlogram, the canonical correlogram, between data sources that have different dimensionalities and temporal resolutions. The canonical correlogram reflects the coupling dynamics between the two sources. The temporal filter reveals which features in the data give rise to these couplings and when they do so. We present results from simulations and neuroscientific experiments showing that tkCCA yields easily interpretable temporal filters and correlograms. In the experiments, we simultaneously performed electrode recordings and functional magnetic resonance imaging (fMRI) in primary visual cortex of the non-human primate. While electrode recordings reflect brain activity directly, fMRI provides only an indirect view of neural activity via the Blood Oxygen Level Dependent (BOLD) response. Thus it is crucial for our understanding and the interpretation of fMRI signals in general to relate them to direct measures of neural activity acquired with electrodes. The results computed by tkCCA confirm recent models of the hemodynamic response to neural activity and allow for a more detailed analysis of neurovascular coupling dynamics.

Predicting neuronal activity with simple models of the threshold type: Adaptive Exponential Integrate-and-Fire model with two compartments

An adaptive Exponential Integrate-and-Fire (aEIF) model was used to predict the activity of layer-V-pyramidal neurons of rat neocortex under random current injection. A new protocol has been developed to extract the parameters of the aEIF model using an optimal filtering technique combined with a black-box numerical optimization. We found that the aEIF model is able to accurately predict both subthreshold fluctuations and the exact timing of spikes, reasonably close to the limits imposed by the intrinsic reliability of pyramidal neurons.

Effects of Neural Synchrony on Surface EEG

It has long been assumed that the surface electroencephalography (EEG) signal depends on both the amplitude and spatial synchronization of underlying neural activity, though isolating their respective contribution remains elusive. To address this, we made simultaneous surface EEG measurements along with intracortical recordings of local field potentials (LFPs) in the primary visual cortex of behaving nonhuman primates. We found that trial-by-trial fluctuations in EEG power could be explained by a linear combination of LFP power and interelectrode temporal synchrony. This effect was observed in both stimulus and stimulus-free conditions and was particularly strong in the gamma range (30-100 Hz). Subsequently, we used pharmacological manipulations to show that neural synchrony can produce a positively modulated EEG signal even when the LFP signal is negatively modulated. Taken together, our results demonstrate that neural synchrony can modulate EEG signals independently of amplitude changes in neural activity. This finding has strong implications for the interpretation of EEG in basic and clinical research, and helps reconcile EEG response discrepancies observed in different modalities (e.g., EEG vs. functional magnetic resonance imaging) and different spatial scales (e.g., EEG vs. intracranial EEG).

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. fMRI can provide insight into their function and dynamics, but their exact effect on BOLD responses remains unclear, 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 DAs involvement in diseases such as Parkinsons and schizophrenia, it also plays a role in visual perception. 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.

Unravelling cerebellar pathways with high temporal precision targeting motor and extensive sensory and parietal networks

Increasing evidence has implicated the cerebellum in providing forward models of motor plants predicting the sensory consequences of actions. Assuming that cerebellar input to the cerebral cortex contributes to the cerebro-cortical processing by adding forward model signals, we would expect to find projections emphasising motor and sensory cortical areas. However, this expectation is only partially met by studies of cerebello-cerebral connections. Here we show that by electrically stimulating the cerebellar output and imaging responses with functional magnetic resonance imaging, evoked blood oxygen level-dependant activity is observed not only in the classical cerebellar projection target, the primary motor cortex, but also in a number of additional areas in insular, parietal and occipital cortex, including sensory cortical representations. Further probing of the responses reveals a projection system that has been optimized to mediate fast and temporarily precise information. In conclusion, both the topography of the stimulation effects and its emphasis on temporal precision are in full accordance with the concept of cerebellar forward model information modulating cerebro-cortical processing.

Pharmacological MRI combined with electrophysiology in non-human primates: effects of Lidocaine on primary visual cortex.

Pharmacological magnetic resonance imaging (phMRI) is a current direction in biomedical imaging, whose goal is the non-invasive monitoring of pharmacological manipulations on brain processes. We have developed techniques combining phMRI with simultaneous monitoring of electrophysiological activity during local injections of pharmacological agents into defined brain regions. We have studied effects of the local anesthetic Lidocaine on BOLD activity in primary visual cortex (V1) of non-human primates. Using independent component analysis (ICA), we describe and quantify the pharmacodynamics and spatial distribution of Lidocaine effects on visually evoked V1 BOLD signal in a dose-dependent manner. We relate these findings to effects of Lidocaine on neural activity as estimated by multi unit activity (MUA) and the local field potential (LFP). Our results open the way for specific fMRI-based investigations regarding the impact of pharmacological agents on the BOLD signal and its coupling to the underlying neuronal activity.

Mass spectrometry-based neurochemical analysis: perspectives for primate research

The analysis of neurochemicals from the brain represents a challenge for current analytical techniques due to a variety of factors, such as compositional complexity, limited amounts of sample and endogenous inferences. Advances in mass spectrometry (MS) provide great opportunities for the sensitive measurement of neurochemicals, offering benefits including simple sample preparation, broad capability for analysis of diverse compounds and rich structural information of analytes. Until recently, however, limited numbers of studies have reported on the analysis of small molecular neurochemicals, such as classical neurotransmitters, in part due to the difficulties in separation of polar molecules by using current chromatography techniques with MS-compatible conditions. By contrast, MS has become an indispensable tool for neuropeptide analysis , offering tremendous potential in the discovery of novel signaling peptides and biomarkers. This review covers recent advances in MS-based neurochemical analysis , including a comparison with related detection techniques, chromatographic separation and neuropeptide discovery. Issues relating to in vivo sample collection and sample preparation are discussed. To provide a wider view of the capability of MS in basic neuroscience and clinical research, we discuss MS-based neurochemical analysis conducted in different animal models and humans. We specifically highlight perspectives for the use of MS for brain functional studies and drug discovery in nonhuman primates.