Andrea Moreno

Functional MRI of long-term potentiation: imaging network plasticity

Neurons are able to express long-lasting and activity-dependent modulations of their synapses. This plastic property supports memory and conveys an extraordinary adaptive value, because it allows an individual to learn from, and respond to, changes in the environment. Molecular and physiological changes at the cellular level as well as network interactions are required in order to encode a pattern of synaptic activity into a long-term memory. While the cellular mechanisms linking synaptic plasticity to memory have been intensively studied, those regulating network interactions have received less attention. Combining high-resolution fMRI and in vivo electrophysiology in rats, we have previously reported a functional remodelling of long-range hippocampal networks induced by long-term potentiation (LTP) of synaptic plasticity in the perforant pathway. Here, we present new results demonstrating an increased bilateral coupling in the hippocampus specifically supported by the mossy cell commissural/associational pathway in response to LTP. This fMRI-measured increase in bilateral connectivity is accompanied by potentiation of the corresponding polysynaptically evoked commissural potential in the contralateral dentate gyrus and depression of the inactive convergent commissural pathway to the ipsilateral dentate. We review these and previous findings in the broader context of memory consolidation.

Neurophysiological, metabolic and cellular compartments that drive neurovascular coupling and neuroimaging signals

Complete understanding of the mechanisms that coordinate work and energy supply of the brain, the so called neurovascular coupling, is fundamental to interpreting brain energetics and their influence on neuronal coding strategies, but also to interpreting signals obtained from brain imaging techniques such as functional magnetic resonance imaging. Interactions between neuronal activity and cerebral blood flow regulation are largely compartmentalized. First, there exists a functional compartmentalization in which glutamatergic peri-synaptic activity and its electrophysiological events occur in close proximity to vascular responses. Second, the metabolic processes that fuel peri-synaptic activity are partially segregated between glycolytic and oxidative compartments. Finally, there is cellular segregation between astrocytic and neuronal compartments, which has potentially important implications on neurovascular coupling. Experimental data is progressively showing a tight interaction between the products of energy consumption and neurotransmission-driven signaling molecules that regulate blood flow. Here, we review some of these issues in light of recent findings with special attention to the neuron-glia interplay on the generation of neuroimaging signals.

Influence of Vanadium or Cobalt Oxides on the CO Oxidation Behavior of Au/MOx/CeO2–Al2O3 Systems

A series of V2O5‐ and Co3O4‐modified ceria/alumina supports and their corresponding gold catalysts were synthesized and their catalytic activities evaluated in the CO oxidation reaction. V2O5‐doped solids demonstrated a poor capacity to abate CO, even lower than that of the original ceria/alumina support, owing to the formation of CeVO4. XRD, Raman spectroscopy, and H2‐temperature programmed reduction studies confirmed the presence of this stoichiometric compound, in which cerium was present as Ce3+ and its redox properties were avoided. Co3O4‐doped supports showed a high activity in CO oxidation at subambient temperatures. The vanadium oxide‐doped gold catalysts were not efficient because of gold particle agglomeration and CeVO4 formation. However, the gold–cobalt oxide–ceria/alumina catalysts demonstrated a high capacity to abate CO at and below room temperature. Total conversion was achieved at −70 °C. The calculated apparent activation energy values revealed a theoretical optimum loading of a half‐monolayer.

Finding influential nodes for integration in brain networks using optimal percolation theory

Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.Complex networks can be used to model brain networks. Here the authors identify the essential nodes in a model of a brain network and then validate these predictions by means of in vivo pharmacogenetic interventions. They find that the nucleus accumbens is a central region for brain integration.

Multi-modal MRI classifiers identify excessive alcohol consumption and treatment effects in the brain

Robust neuroimaging markers of neuropsychiatric disorders have proven difficult to obtain. In alcohol use disorders, profound brain structural deficits can be found in severe alcoholic patients, but the heterogeneity of unimodal MRI measurements has so far precluded the identification of selective biomarkers, especially for early diagnosis. In the present work we used a combination of multiple MRI modalities to provide comprehensive and insightful descriptions of brain tissue microstructure. We performed a longitudinal experiment using Marchigian–Sardinian (msP) rats, an established model of chronic excessive alcohol consumption, and acquired multi‐modal images before and after 1 month of alcohol consumption (6.8 ± 1.4 g/kg/day, mean ± SD), as well as after 1 week of abstinence with or without concomitant treatment with the antirelapse opioid antagonist naltrexone (2.5 mg/kg/day). We found remarkable sensitivity and selectivity to accurately classify brains affected by alcohol even after the relative short exposure period. One month drinking was enough to imprint a highly specific signature of alcohol consumption. Brain alterations were regionally specific and affected both gray and white matter and persisted into the early abstinence state without any detectable recovery. Interestingly, naltrexone treatment during early abstinence resulted in subtle brain changes that could be distinguished from non‐treated abstinent brains, suggesting the existence of an intermediate state associated with brain recovery from alcohol exposure induced by medication. The presented framework is a promising tool for the development of biomarkers for clinical diagnosis of alcohol use disorders, with capacity to further inform about its progression and response to treatment.

Functional MRI of Synaptic Plasticity

Abstract Since its discovery in the early 1990s, blood oxygen level dependent signal-based functional magnetic resonance imaging (fMRI) has become a fundamental technique for the study of brain activity in basic and clinical research. Functional MRI provides an indirect but robust and quantitative readout of brain activity through the tight coupling between cerebral blood flow and neuronal activation, the so-called neurovascular coupling. Combined with experimental techniques such as electrophysiology, intracerebral microstimulation, optogenetics, or pharmacogenetics, it provides a powerful framework to investigate the impact of specific circuit manipulations on overall brain dynamics. In this chapter we review the contribution of some of these techniques to the understanding of short- and long-term plasticity processes and provide a comprehensive account of the protocols used in our laboratory. Considerations on the interpretation of the results and the limitations of the approach are also discussed.

Publisher Correction: Finding influential nodes for integration in brain networks using optimal percolation theory

The original version of this Article contained an error in the last sentence of the first paragraph of the Introduction, which incorrectly read ‘Correlation of brain activity is typically measured using functional magnetic resonance imaging (fMRI), and the correlation structure is often referred to as “fu’. The correct version states ‘referred to as “functional connectivity”2–6’ in place of ‘referred to as “fu’. This has been corrected in both the PDF and HTML versions of the Article.