Champalimaud Center for the Unknown

Pedrouços, Portugal

Champalimaud Center for the Unknown

Pedrouços, Portugal
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News Article | April 25, 2017

Scientists have known for decades that what we eat can change the balance of microbes in our digestive tracts. Choosing between a BLT sandwich or a yogurt parfait for lunch can increase the populations of some types of bacteria and diminish others—and as their relative numbers change they secrete different substances, activate different genes and absorb different nutrients. And those food choices are probably a two-way street. Gut microbes have also been shown to influence diet and behavior as well as anxiety, depression, hypertension and a variety of other conditions. But exactly how these trillions of tiny guests—collectively called the microbiome—influence our decisions on which foods to stuff into our mouths has been a mystery. Now neuroscientists have found specific types of gut flora help a host animal detect which nutrients are missing in food, and then finely titrate how much of those nutrients the host really needs to eat. “What the bacteria do for appetite is kind of like optimizing how long a car can run without needing to add more petrol to the tank,” says senior author Carlos Ribeiro, who studies the eating behaviors of Drosophila melanogaster, a type of fruit fly, at Champalimaud Center for the Unknown in Lisbon. In a paper published Tuesday in PLoS Biology Ribeiro and his team demonstrated how the microbiome influences drosophila’s nutritional decisions. First, they fed one group of flies a sucrose solution containing all the necessary amino acids. Another group got a mix that had some of the amino acids needed to make protein but lacked essential amino acids that the host cannot synthesize by itself. For a third group of flies, the scientists removed essential amino acids from the food one by one to determine which was being detected by the microbiome. After 72 hours on the various diets, flies in the all three groups were presented with a buffet offering their normal sugary solution alongside  protein-rich yeast. The researchers found that flies in the two groups whose diet lacked any single essential amino acid got a strong craving for yeast to make up for the missing nutrients. But when scientists increased five different types of bacteria found in the flies’ digestive tracts—Lactobacillus plantarum, L. brevis, Acetobacter pomorum, Commensalibacter intestini and Enterococcus faecalis—the flies completely lost the urge to eat more protein. The researchers found the flies’ amino acid levels were still low, indicating the bacteria were not simply replacing nutrients missing from the flies’ diet by producing the amino acids themselves. Instead, the microbes were functioning as little metabolic factories, transforming the food they got into new chemicals: metabolites that the researchers believe might be telling the host animal it could carry on without the amino acids. As a result of this microbial trick, the flies were able to continue reproducing, for example—even though an amino acid deficiency usually hampers cell growth and regeneration, and therefore reproduction, Ribeiro explains. Two kinds of bacteria were particularly effective in influencing the appetite of flies this way: Acetobacter and Lactobacillus. Increasing both was enough to suppress the flies’ protein cravings and increase their appetite for sugar. These two bacteria also restored the flies’ reproductive abilities, indicating their bodies were carrying out normal functions that typically get restricted when there is a nutritional deficiency. “How the brain handles this trade-off of nutritional information is very fascinating, and our study shows that the microbiome plays a key role in telling the animal what to do,” Ribeiro says. Next the team removed an enzyme needed to process the amino acid tyrosine in flies, making it necessary for the flies to get tyrosine via their food, just like other essential amino acids. Surprisingly, they found that Acetobacter and Lactobacillus were unable to suppress the craving for tyrosine in the modified flies. “This shows that the gut microbiome has evolved to titrate only the normal essential amino acid intake,” Ribeiro explains. The research adds a new perspective on coevolution of microbes and their hosts. “The findings show that there is a unique pathway that has coevolved between animals and the resident bacteria in their gut, and there is a bottom-up communication about diet,” says Jane Foster, who is a neuroscientist at McMaster University in Ontario and not associated with the study. Although the study does not specify the exact mechanism of communication, Ribeiro thinks it could take various forms. Strong evidence from the study indicates microbially derived metabolites carry information from the gut to the brain, telling the host whether it needs a particular kind of food. “One of the big evolutionary mysteries is why we lost the ability to produce essential amino acids,” he says. “Maybe these metabolites gave animals more leeway to be independent of these nutrients, and to deal without them sometimes.” Microbes may also have their own evolutionary reasons for communicating with the brain, he adds. For one thing, they feed on whatever the host animal eats. For another, they need host animals to be social so the guests can spread through the population. The data is limited to animal models so far but Ribeiro believes that gut–brain communication can provide fertile ground for developing treatments for humans in the future. “It’s an interesting therapeutic window that could be utilized to improve behaviors related to diet one day,” he says.

Carey M.R.,Champalimaud Center for the Unknown
Current Opinion in Neurobiology | Year: 2011

The cerebellum plays an essential role in motor learning. The ability to identify specific sensory and motor signals carried by neurons with known connectivity makes the cerebellum an attractive system for investigating how synaptic plasticity relates to learning. Early studies focused primarily on a single form of plasticity, long-term depression at parallel fiber-Purkinje cell synapses. Recent work has highlighted both the diversity of synaptic plasticity that exists within the cerebellum and the fact that individual plasticity mechanisms can have unexpected consequences when they act within neural circuits. © 2011 Elsevier Ltd.

Koralek A.,University of California at Berkeley | Costa R.,Champalimaud Center for the Unknown | Carmena J.,University of California at Berkeley
Neuron | Year: 2013

It has been postulated that selective temporal coordination between neurons and development of functional neuronal assemblies are fundamental for brain function and behavior. Still, there is little evidence that functionally relevant coordination emerges preferentially in neuronal assemblies directly controlling behavioral output. We investigated coherence between primary motor cortex and the dorsal striatum as rats learn an abstract operant task. Striking coherence developed between these regions during learning. Interestingly, coherence was selectively increased in cells controlling behavioral output relative to adjacent cells. Furthermore, the temporal offset of these interactions aligned closely with corticostriatal conduction delays, demonstrating highly precise timing. Spikes from either region were followed by a consistent phase in the other, suggesting that network feedback reinforces coherence. Together, these results demonstrate that temporally precise coherence develops during learning specifically in output-relevant neuronal populations and further suggest that correlations in oscillatory activity serve to synchronize widespread brain networks to produce behavior

Morgenstern N.A.,Champalimaud Center for the Unknown | Bourg J.,Champalimaud Center for the Unknown | Petreanu L.,Champalimaud Center for the Unknown
Nature Neuroscience | Year: 2016

Neurons in the thalamorecipient layers of sensory cortices integrate thalamic and recurrent cortical input. Cortical neurons form fine-scale, functionally cotuned networks, but whether interconnected cortical neurons within a column process common thalamocortical inputs is unknown. We tested how local and thalamocortical connectivity relate to each other by analyzing cofluctuations of evoked responses in cortical neurons after photostimulation of thalamocortical axons. We found that connected pairs of pyramidal neurons in layer (L) 4 of mouse visual cortex share more inputs from the dorsal lateral geniculate nucleus than nonconnected pairs. Vertically aligned connected pairs of L4 and L2/3 neurons were also preferentially contacted by the same thalamocortical axons. Our results provide a circuit mechanism for the observed amplification of sensory responses by L4 circuits. They also show that sensory information is concurrently processed in L4 and L2/3 by columnar networks of interconnected neurons contacted by the same thalamocortical axons. © 2016 Nature America, Inc.

Jin X.,Salk Institute for Biological Studies | Costa R.M.,Champalimaud Center for the Unknown
Current Opinion in Neurobiology | Year: 2015

Many behaviors necessary for organism survival are learned anew and become organized as complex sequences of actions. Recent studies suggest that cortico-basal ganglia circuits are important for chunking isolated movements into precise and robust action sequences that permit the achievement of particular goals. During sequence learning many neurons in the basal ganglia develop sequence-related activity. - related to the initiation, execution, and termination of sequences. - suggesting that action sequences are processed as action units. Corticostriatal plasticity is critical for the crystallization of action sequences, and for the development of sequence-related neural activity. Furthermore, this sequence-related activity is differentially expressed in direct and indirect basal ganglia pathways. These findings have implications for understanding the symptoms associated with movement and psychiatric disorders. © 2015 Elsevier Ltd.

Murakami M.,Champalimaud Center for the Unknown | Mainen Z.F.,Champalimaud Center for the Unknown
Current Opinion in Neurobiology | Year: 2015

How the brain selects one action among multiple alternatives is a central question of neuroscience. An influential model is that action preparation and selection arise from subthreshold activation of the very neurons encoding the action. Recent work, however, shows a much greater diversity of decision-related and action-related signals coexisting with other signals in populations of motor and parietal cortical neurons. We discuss how such distributed signals might be decoded by biologically plausible mechanisms. We also discuss how neurons within cortical circuits might interact with each other during action selection and preparation and how recurrent network models can help to reveal dynamical principles underlying cortical computation. © 2015 The Authors.

Meyniel F.,University Paris - Sud | Sigman M.,Torcuato Di Tella University | Mainen Z.F.,Champalimaud Center for the Unknown
Neuron | Year: 2015

Research on confidence spreads across several sub-fields of psychology and neuroscience. Here, we explore how a definition of confidence as Bayesian probability can unify these viewpoints. This computational view entails that there are distinct forms in which confidence is represented and used in the brain, including distributional confidence, pertaining to neural representations of probability distributions, and summary confidence, pertaining to scalar summaries of those distributions. Summary confidence is, normatively, derived or "read out" from distributional confidence. Neural implementations of readout will trade off optimality versus flexibility of routing across brain systems, allowing confidence to serve diverse cognitive functions. © 2015 Elsevier Inc.

Kepecs A.,Cold Spring Harbor Laboratory | Mainen Z.F.,Champalimaud Center for the Unknown
Philosophical Transactions of the Royal Society B: Biological Sciences | Year: 2012

Confidence judgements, self-assessments about the quality of a subject's knowledge, are considered a central example of metacognition. Prima facie, introspection and self-report appear the only way to access the subjective sense of confidence or uncertainty. Contrary to this notion, overt behavioural measures can be used to study confidence judgements by animals trained in decision-making tasks with perceptual or mnemonic uncertainty. Here, we suggest that a computational approach can clarify the issues involved in interpreting these tasks and provide a much needed springboard for advancing the scientific understanding of confidence. We first review relevant theories of probabilistic inference and decision-making. We then critically discuss behavioural tasks employed to measure confidence in animals and show how quantitative models can help to constrain the computational strategies underlying confidence-reporting behaviours. In our view, post-decision wagering tasks with continuous measures of confidence appear to offer the best available metrics of confidence. Since behavioural reports alone provide a limited window into mechanism, we argue that progress calls for measuring the neural representations and identifying the computations underlying confidence reports. We present a case study using such a computational approach to study the neural correlates of decision confidence in rats. This work shows that confidence assessments may be considered higher order, but can be generated using elementary neural computations that are available to a wide range of species. Finally, we discuss the relationship of confidence judgements to the wider behavioural uses of confidence and uncertainty. © 2012 The Royal Society.

Deneve S.,Ecole Normale Superieure de Paris | Machens C.K.,Champalimaud Center for the Unknown
Nature Neuroscience | Year: 2016

Recent years have seen a growing interest in inhibitory interneurons and their circuits. A striking property of cortical inhibition is how tightly it balances excitation. Inhibitory currents not only match excitatory currents on average, but track them on a millisecond time scale, whether they are caused by external stimuli or spontaneous fluctuations. We review, together with experimental evidence, recent theoretical approaches that investigate the advantages of such tight balance for coding and computation. These studies suggest a possible revision of the dominant view that neurons represent information with firing rates corrupted by Poisson noise. Instead, tight excitatory/inhibitory balance may be a signature of a highly cooperative code, orders of magnitude more precise than a Poisson rate code. Moreover, tight balance may provide a template that allows cortical neurons to construct high-dimensional population codes and learn complex functions of their inputs. © 2016 Nature America, Inc. All rights reserved.

Ahrens M.B.,Howard Hughes Medical Institute | Orger M.B.,Champalimaud Center for the Unknown | Robson D.N.,Harvard University | Li J.M.,Harvard University | Keller P.J.,Howard Hughes Medical Institute
Nature Methods | Year: 2013

Brain function relies on communication between large populations of neurons across multiple brain areas, a full understanding of which would require knowledge of the time-varying activity of all neurons in the central nervous system. Here we use light-sheet microscopy to record activity, reported through the genetically encoded calcium indicator GCaMP5G, from the entire volume of the brain of the larval zebrafish in vivo at 0.8 Hz, capturing more than 80% of all neurons at single-cell resolution. Demonstrating how this technique can be used to reveal functionally defined circuits across the brain, we identify two populations of neurons with correlated activity patterns. One circuit consists of hindbrain neurons functionally coupled to spinal cord neuropil. The other consists of an anatomically symmetric population in the anterior hindbrain, with activity in the left and right halves oscillating in antiphase, on a timescale of 20 s, and coupled to equally slow oscillations in the inferior olive. © 2013 Nature America, Inc. All rights reserved.

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