Our daily life is a complex chain of decisions and actions that shapes our behaviors. Individuals tend to choose the best action possible (‘action-selection’) among different alternatives through “goal-directed†decision-making. To learn and achieve an optimal...
Our daily life is a complex chain of decisions and actions that shapes our behaviors. Individuals tend to choose the best action possible (‘action-selection’) among different alternatives through “goal-directed†decision-making. To learn and achieve an optimal behavior, individuals must: (i) Predict the potential cost (e.g. risk) and benefit (e.g. reward) that might occur as a consequence of an action (‘outcome’). This ‘action-value’ function is learned from the causal consequences of an action (‘action-outcome’ association), and the subjective value of different outcomes (‘outcome-value’ associations); (ii) Compare ‘action-value’ functions and select the action with the greatest value. The probability of selecting one of two choices is called ‘action-selection’ and determined by the difference in their ‘action-value’ functions; (iii) Update the ‘action-value’ function according to the difference between the predicted and the obtained reward.
The development of neuroeconomics and artificial intelligence, as well as maladaptive decision-making found in many neuropsychiatric disorders highlight the crucial importance of this process. However, despite the growing interest of action-outcome’ and ‘outcome-value’ associations over the past few years, the neuronal correlates of choices that drive goal-directed ‘action-selection’ as well as the synaptic underpinnings have been largely neglected. By developing new methods and sophisticated strategies in behaving mice, we aim to resolve several outstanding questions:
1. Given that the comparison between choice alternatives should occur in the cortex as a precursor of choice and action, are multiple choices represented in the cortex by specific patterns of cell activation? Are they pre-existing or encoded through learning?
2. Given that the reward values are supposed to be encoded in several cortical structures through the help of subcortical structures, how are these different systems interconnected, and how do they cooperate to implement action values in the cortex and further influence choice?
3. Given that maladaptive decision-making is found in many psychiatric disorders including autism, are the synaptic and cellular underpinnings of decision-making altered in our mouse model of autism?
Our experimental strategy rely on two-photon laser scanning microscopy (2PLSM) in vivo which is emerging as a prime method for the investigation of cognitive processes since it can record the activity of micrometer-scale compartments, genetically target specific cell groups, and monitor the same features over extended periods of time. For instance, we tracked the activity of FrA pyramidal neurons and axons over weeks and months, while mice learned a complex decision task. Indeed, a fundamental question usually not addressed in Neuroscience concerns the role of learning, and most of decision-making studies described the effect of changing reward in expert rodents.Our work combined so far a wide range of state-of-the-art techniques from different scientific disciplines: molecular biology and genetics (optogenetic constructs, transgenic mice, viral strategies), advanced microscopy, animal behavioral tasks, applied mathematics, computer science. This rich and complementary combination of skills and insights is a key strength of the project that allowed us to address unanswered questions by original means. Here, we determined for the first time how mice acquire their preference for actions associated with reward
The extraction of salient features from images, if precise enough, allowed characterizing neural firing sequences (WP1), the timing of axonal inputs (WP2), and plasticity at the level of single synapses (WP2). However, manual selection of regions of interest (ROIs) and events in images is plagued by human bias, experiment-to-experiment variations, and low throughput which considerably limits behavioral studies. Moreover, the few existing methods which automatically extract ROIs from Ca2+ images are not fit to low-level of fluorescence events and complex, elongated and micrometer-scale shapes that are typical of the type of sub-compartmental study we propose to conduct. In addition, handling large data is also required since our data sets for behavioral experiments typically consist of thousands of high-resolution images representing tens of Gigabytes. Therefore, we had to design 1) unbiased methods for the extraction of complex low-intensity fluorescent features such as axonal projections in FrA thanks to an original mathematical crafting of the problem; 2) new data reduction techniques and parallel processing algorithms to efficiently process very large data and maximize experimental throughput. We indeed considered the mathematical problem of dimensionality reduction and large data processing for this specific type of image data to perform large-scale, fully-automated, data analysis.
NEUROGOAL combines a wide range and unique set of optical, electrophysiological, genetic, optogenetic, and mathematical tools in vivo in the behaving animal to understand how computations are performed in prefrontal neuronal microcircuit during decision-making. The project will actively participate in strengthening both the excellence and competitiveness of the European scientific community in different ways:
It will develop and implement unique tools at the cutting edge of technology and innovation. Longitudinal in-vivo two-photon imaging and whole-cell recordings in the behaving animal are indeed at the forefront of the modern neuroscience techniques. When combined with the high temporal precision of optogenetics, calcium dynamics makes it possible to decipher the causal role of the interaction between different interconnected brain structures and decision-making during behavioral flexibility.
It will be part of a rare imaging infrastructure in Europe and in the world. This does not only underpin innovative research but also leads its development and creates a highly attractive climate for world-class postdocs and senior researchers.
It will tackle medical, societal and economical challenges by potent breakthrough discoveries. Our “learning under the microscope†strategy will tackle several outstanding issues that have never been addressed in the past most likely because of technical limitations. It will indeed give special insight into the higher-cognitive functions performed by the prefrontal cortex, including the cellular and synaptic mechanisms underlying choice-specific representations and action-selection, as well as the integration of cortical and subcortical valuation systems that may participate in motivation and behavioral flexibility. Studying such interactions in the context of decision-making is of crucial importance as many maladaptive behaviors in our daily life may arise from their dysfunctional use. In addition, our proposal will certainly bring novel cellular and synaptic knowledge regarding motivational alterations, repetitive behaviors and suboptimal decision-making that have been described in autism. As a consequence it will certainly help to advance the design of new diagnosis framework and strategies towards behavioral enhancement in a wide range of neuropsychiatric diseases, including drug addiction, schizophrenia, anxiety disorder, ADHD, and Parkinson’s disease.
More info: http://www.iins.u-bordeaux.fr/Team-Gambino.