George C. Nascimento

fMRI in the awake marmoset: somatosensory-evoked responses, functional connectivity, and comparison with propofol anesthesia

Functional neuroimaging in animal models is essential for understanding the principles of neurovascular coupling and the physiological basis of fMRI signals that are widely used to study sensory and cognitive processing in the human brain. While hemodynamic responses to sensory stimuli have been characterized in humans, animal studies are able to combine very high resolution imaging with invasive measurements and pharmacological manipulation. To date, most high-resolution studies of neurovascular coupling in small animals have been carried out in anesthetized rodents. Here we report fMRI experiments in conscious, awake common marmosets (Callithrix jacchus), and compare responses to animals anesthetized with propofol. In conscious marmosets, robust BOLD fMRI responses to somatosensory stimulation of the forearm were found in contralateral and ipsilateral regions of the thalamus, primary (SI) and secondary (SII) somatosensory cortex, and the caudate nucleus. These responses were markedly stronger than those in anesthetized marmosets and showed a monotonic increase in the amplitude of the BOLD response with stimulus frequency. On the other hand, anesthesia significantly attenuated responses in thalamus, SI and SII, and abolished responses in caudate and ipsilateral SI. Moreover, anesthesia influenced several other aspects of the fMRI responses, including the shape of the hemodynamic response function and the interareal (SI-SII) spontaneous functional connectivity. Together, these findings demonstrate the value of the conscious, awake marmoset model for studying physiological responses in the somatosensory pathway, in the absence of anesthesia, so that the data can be compared most directly to fMRI in conscious humans.

Magnetic resonance imaging quantification of regional cerebral blood flow and cerebrovascular reactivity to carbon dioxide in normotensive and hypertensive rats

Hypertension afflicts 25% of the general population and over 50% of the elderly. In the present work, arterial spin labeling MRI was used to non-invasively quantify regional cerebral blood flow (CBF), cerebrovascular resistance and CO(2) reactivity in spontaneously hypertensive rats (SHR) and in normotensive Wistar Kyoto rats (WKY), at two different ages (3 months and 10 months) and under the effects of two anesthetics, α-chloralose and 2% isoflurane (1.5 MAC). Repeated CBF measurements were highly consistent, differing by less than 10% and 18% within and across animals, respectively. Under α-chloralose, whole brain CBF at normocapnia did not differ between groups (young WKY: 61 ± 3ml/100g/min; adult WKY: 62 ± 4ml/100g/min; young SHR: 70 ± 9ml/100g/min; adult SHR: 69 ± 8ml/100g/min), indicating normal cerebral autoregulation in SHR. At hypercapnia, CBF values increased significantly, and a linear relationship between CBF and PaCO(2) levels was observed. In contrast, 2% isoflurane impaired cerebral autoregulation. Whole brain CBF in SHR was significantly higher than in WKY rats at normocapnia (young SHR: 139 ± 25ml/100g/min; adult SHR: 104 ± 23ml/100g/min; young WKY: 55± 9ml/100g/min; adult WKY: 71 ± 19ml/100g/min). CBF values increased significantly with increasing CO(2); however, there was a clear saturation of CBF at PaCO(2) levels greater than 70mmHg in both young and adult rats, regardless of absolute CBF values, suggesting that isoflurane interferes with the vasodilatory mechanisms of CO(2). This behavior was observed for both cortical and subcortical structures. Under either anesthetic, CO(2) reactivity values in adult SHR were decreased, confirming that hypertension, when combined with age, increases cerebrovascular resistance and reduces cerebrovascular compliance.

Longitudinal Functional Magnetic Resonance Imaging in Animal Models

Functional magnetic resonance imaging (fMRI) has had an essential role in furthering our understanding of brain physiology and function. fMRI techniques are nowadays widely applied in neuroscience research, as well as in translational and clinical studies. The use of animal models in fMRI studies has been fundamental in helping elucidate the mechanisms of cerebral blood-flow regulation, and in the exploration of basic neuroscience questions, such as the mechanisms of perception, behavior, and cognition. Because animals are inherently non-compliant, most fMRI performed to date have required the use of anesthesia, which interferes with brain function and compromises interpretability and applicability of results to our understanding of human brain function. An alternative approach that eliminates the need for anesthesia involves training the animal to tolerate physical restraint during the data acquisition. In the present chapter, we review these two different approaches to obtaining fMRI data from animal models, with a specific focus on the acquisition of longitudinal data from the same subjects.

Beta2 oscillations (23-30 Hz) in the mouse hippocampus during novel object recognition.

The oscillatory activity of hippocampal neuronal networks is believed to play a role in memory acquisition and consolidation. Particular focus has been given to characterising theta (4–12 Hz), gamma (40–100 Hz) and ripple (150–250 Hz) oscillations. Beyond these well‐described network states, few studies have investigated hippocampal beta2 (23–30 Hz) activity in vivo and its link to behaviour. A previous sudy showed that the exploration of novel environments may lead to the appearance of beta2 oscillations in the mouse hippocampus. In the present study we characterised hippocampal beta2 oscillations in mice during an object recognition task. We found prominent bursts of beta2 oscillations in the beginning of novel exploration sessions (four new objects), which could be readily observed by spectral analysis and visual inspection of local field potentials. Beta2 modulated hippocampal but not neocortical neurons and its power decreased along the session. We also found increased beta2 power in the beginning of a second exploration session performed 24 h later in a slightly modified environment (two new, two familiar objects), but to a lesser extent than in the first session. However, the increase in beta2 power in the second exploration session became similar to the first session when we pharmacologically impaired object recognition in a new set of experiments performed 1 week later. Our results suggest that hippocampal beta2 activity is associated with a dynamic network state tuned for novelty detection and which may allow new learning to occur.

D2 dopamine receptor regulation of learning, sleep and plasticity.

Dopamine and sleep have been independently linked with hippocampus-dependent learning. Since D2 dopaminergic transmission is required for the occurrence of rapid-eye-movement (REM) sleep, it is possible that dopamine affects learning by way of changes in post-acquisition REM sleep. To investigate this hypothesis, we first assessed whether D2 dopaminergic modulation in mice affects novel object preference, a hippocampus-dependent task. Animals trained in the dark period, when sleep is reduced, did not improve significantly in performance when tested 24h after training. In contrast, animals trained in the sleep-rich light period showed significant learning after 24h. When injected with the D2 inverse agonist haloperidol immediately after the exploration of novel objects, animals trained in the light period showed reduced novelty preference upon retesting 24h later. Next we investigated whether haloperidol affected the protein levels of plasticity factors shown to be up-regulated in an experience-dependent manner during REM sleep. Haloperidol decreased post-exploration hippocampal protein levels at 3h, 6h and 12h for phosphorylated Ca(2+)/calmodulin-dependent protein kinase II, at 6h for Zif-268; and at 12h for the brain-derived neurotrophic factor. Electrophysiological and kinematic recordings showed a significant decrease in the amount of REM sleep following haloperidol injection, while slow-wave sleep remained unaltered. Importantly, REM sleep decrease across animals was strongly correlated with deficits in novelty preference (Rho=0.56, p=0.012). Altogether, the results suggest that the dopaminergic regulation of REM sleep affects learning by modulating post-training levels of calcium-dependent plasticity factors.

Object recognition impairment and rescue by a dopamine D2 antagonist in hyperdopaminergic mice

Genetically-modified mice without the dopamine transporter (DAT) are hyperdopaminergic, and serve as models for studies of addiction, mania and hyperactive disorders. Here we investigated the capacity for object recognition in mildly hyperdopaminergic mice heterozygous for DAT (DAT +/-), with synaptic dopaminergic levels situated between those shown by DAT -/- homozygous and wild-type (WT) mice. We used a classical dopamine D2 antagonist, haloperidol, to modulate the levels of dopaminergic transmission in a dose-dependent manner, before or after exploring novel objects. In comparison with WT mice, DAT +/- mice showed a deficit in object recognition upon subsequent testing 24h later. This deficit was compensated by a single 0.05mg/kg haloperidol injection 30min before training. In all mice, a 0.3mg/kg haloperidol injected immediately after training impaired object recognition. The results indicate that a mild enhancement of dopaminergic levels can be detrimental to object recognition, and that this deficit can be rescued by a low dose of a D2 dopamine receptor antagonist. This suggests that novel object recognition is optimal at intermediate levels of D2 receptor activity.

Arterial Spin Labeling Measurements of Cerebral Perfusion Territories in Experimental Ischemic Stroke

Collateral circulation, defined as the supplementary vascular network that maintains cerebral blood flow (CBF) when the main vessels fail, constitutes one important defense mechanism of the brain against ischemic stroke. In the present study, continuous arterial spin labeling (CASL) was used to quantify CBF and obtain perfusion territory maps of the major cerebral arteries in spontaneously hypertensive rats (SHRs) and their normotensive Wistar-Kyoto (WKY) controls. Results show that both WKY and SHR have complementary, yet significantly asymmetric perfusion territories. Right or left dominances were observed in territories of the anterior (ACA), middle and posterior cerebral arteries, and the thalamic artery. Magnetic resonance angiography showed that some of the asymmetries were correlated with variations of the ACA. The leptomeningeal circulation perfusing the outer layers of the cortex was observed as well. Significant and permanent changes in perfusion territories were obtained after temporary occlusion of the right middle cerebral artery in both SHR and WKY, regardless of their particular dominance. However, animals with right dominance presented a larger volume change of the left perfusion territory (23 ± 9%) than animals with left dominance (7 ± 5%, P < 0.002). The data suggest that animals with contralesional dominance primarily safeguard local CBF values with small changes in contralesional perfusion territory, while animals with ipsilesional dominance show a reversal of dominance and a substantial increase in contralesional perfusion territory. These findings show the usefulness of CASL to probe the collateral circulation.

On the photovoltaic effect in local field potential recordings

Abstract. Optogenetics allows light activation of genetically defined cell populations and the study of their link to specific brain functions. While it is a powerful method that has revolutionized neuroscience in the last decade, the shortcomings of directly stimulating electrodes and living tissue with light have been poorly characterized. Here, we assessed the photovoltaic effects in local field potential (LFP) recordings of the mouse hippocampus. We found that light leads to several artifacts that resemble genuine LFP features in animals with no opsin expression, such as stereotyped peaks at the power spectrum, phase shifts across different recording channels, coupling between low and high oscillation frequencies, and sharp signal deflections that are detected as spikes. Further, we tested how light stimulation affected hippocampal LFP recordings in mice expressing channelrhodopsin 2 in parvalbumin neurons (PV/ChR2 mice). Genuine oscillatory activity at the frequency of light stimulation could not be separated from light-induced artifacts. In addition, light stimulation in PV/ChR2 mice led to an overall decrease in LFP power. Thus, genuine LFP changes caused by the stimulation of specific cell populations may be intermingled with spurious changes caused by photovoltaic effects. Our data suggest that care should be taken in the interpretation of electrophysiology experiments involving light stimulation.

Predictability of arousal in mouse slow wave sleep by accelerometer data

Arousals can be roughly characterized by punctual intrusions of wakefulness into sleep. In a standard perspective, using human electroencephalography (EEG) data, arousals are associated to slow-wave rhythms and K-complex brain activity. The physiological mechanisms that give rise to arousals during sleep are not yet fully understood. Moreover, subtle body movement patterns, which may characterize arousals both in human and in animals, are usually not detectable by eye perception and are not in general present in sleep studies. In this paper, we focus attention on accelerometer records (AR) to characterize and predict arousal during slow wave sleep (SWS) stage of mice. Furthermore, we recorded the local field potentials (LFP) from the CA1 region in the hippocampus and paired with accelerometer data. The hippocampus signal was also used here to identify the SWS stage. We analyzed the AR dynamics of consecutive arousals using recurrence technique and the determinism (DET) quantifier. Recurrence is a fundamental property of dynamical systems, which can be exploited to characterize time series properties. The DET index evaluates how similar are the evolution of close trajectories: in this sense, it computes how accurate are predictions based on past trajectories. For all analyzed mice in this work, we observed, for the first time, the occurrence of a universal dynamic pattern a few seconds that precedes the arousals during SWS sleep stage based only on the AR signal. The predictability success of an arousal using DET from AR is nearly 90%, while similar analysis using LFP of hippocampus brain region reveal 88% of success. Noteworthy, our findings suggest an unique dynamical behavior pattern preceding an arousal of AR data during sleep. Thus, the employment of this technique applied to AR data may provide useful information about the dynamics of neuronal activities that control sleep-waking switch during SWS sleep period. We argue that the predictability of arousals observed through DET(AR) can be functionally explained by a respiratory-driven modification of neural states. Finally, we believe that the method associating AR data with other physiologic events such as neural rhythms can become an accurate, convenient and non-invasive way of studying the physiology and physiopathology of movement and respiratory processes during sleep.

Optimizing the detection of nonstationary signals by using recurrence analysis

Recurrence analysis and its quantifiers are strongly dependent on the evaluation of the vicinity threshold parameter, i.e., the threshold to regard two points close enough in phase space to be considered as just one. We develop a new way to optimize the evaluation of the vicinity threshold in order to assure a higher level of sensitivity to recurrence quantifiers to allow the detection of even small changes in the dynamics. It is used to promote recurrence analysis as a tool to detect nonstationary behavior of time signals or space profiles. We show that the ability to detect small changes provides information about the present status of the physical process responsible to generate the signal and offers mechanisms to predict future states. Here, a higher sensitive recurrence analysis is proposed as a precursor, a tool to predict near future states of a particular system, based on just (experimentally) obtained signals of some available variables of the system. Comparisons with traditional methods of recurrence analysis show that the optimization method developed here is more sensitive to small variations occurring in a signal. The method is applied to numerically generated time series as well as experimental data from physiology.