105 research outputs found

    Electrophysiological correlates of high-level perception during spatial navigation

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    We studied the electrophysiological basis of object recognition by recording scalp\ud electroencephalograms while participants played a virtual-reality taxi driver game.\ud Participants searched for passengers and stores during virtual navigation in simulated\ud towns. We compared oscillatory brain activity in response to store views that were targets or\ud nontargets (during store search) or neutral (during passenger search). Even though store\ud category was solely defined by task context (rather than by sensory cues), frontal ...\ud \u

    Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

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    Changes of synaptic connections between neurons are thought to be the physiological basis of learning. These changes can be gated by neuromodulators that encode the presence of reward. We study a family of reward-modulated synaptic learning rules for spiking neurons on a learning task in continuous space inspired by the Morris Water maze. The synaptic update rule modifies the release probability of synaptic transmission and depends on the timing of presynaptic spike arrival, postsynaptic action potentials, as well as the membrane potential of the postsynaptic neuron. The family of learning rules includes an optimal rule derived from policy gradient methods as well as reward modulated Hebbian learning. The synaptic update rule is implemented in a population of spiking neurons using a network architecture that combines feedforward input with lateral connections. Actions are represented by a population of hypothetical action cells with strong mexican-hat connectivity and are read out at theta frequency. We show that in this architecture, a standard policy gradient rule fails to solve the Morris watermaze task, whereas a variant with a Hebbian bias can learn the task within 20 trials, consistent with experiments. This result does not depend on implementation details such as the size of the neuronal populations. Our theoretical approach shows how learning new behaviors can be linked to reward-modulated plasticity at the level of single synapses and makes predictions about the voltage and spike-timing dependence of synaptic plasticity and the influence of neuromodulators such as dopamine. It is an important step towards connecting formal theories of reinforcement learning with neuronal and synaptic properties

    Spatial memory in the grey mouse lemur (Microcebus murinus)

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    Wild animals face the challenge of locating feeding sites distributed across broad spatial and temporal scales. Spatial memory allows animals to find a goal, such as a productive feeding patch, even when there are no goal-specific sensory cues available. Because there is little experimental information on learning and memory capabilities in free-ranging primates, the aim of this study was to test whether grey mouse lemurs (Microcebus murinus), as short-term dietary specialists, rely on spatial memory in relocating productive feeding sites. In addition, we asked what kind of spatial representation might underlie their orientation in their natural environment. Using an experimental approach, we set eight radio-collared grey mouse lemurs a memory task by confronting them with two different spatial patterns of baited and non-baited artificial feeding stations under exclusion of sensory cues. Positional data were recorded by focal animal observations within a grid system of small foot trails. A change in the baiting pattern revealed that grey mouse lemurs primarily used spatial cues to relocate baited feeding stations and that they were able to rapidly learn a new spatial arrangement. Spatially concentrated, non-random movements revealed preliminary evidence for a route-based restriction in mouse lemur space; during a subsequent release experiment, however, we found high travel efficiency in directed movements. We therefore propose that mouse lemur spatial memory is based on some kind of mental representation that is more detailed than a route-based network map

    Whisker Movements Reveal Spatial Attention: A Unified Computational Model of Active Sensing Control in the Rat

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    Spatial attention is most often investigated in the visual modality through measurement of eye movements, with primates, including humans, a widely-studied model. Its study in laboratory rodents, such as mice and rats, requires different techniques, owing to the lack of a visual fovea and the particular ethological relevance of orienting movements of the snout and the whiskers in these animals. In recent years, several reliable relationships have been observed between environmental and behavioural variables and movements of the whiskers, but the function of these responses, as well as how they integrate, remains unclear. Here, we propose a unifying abstract model of whisker movement control that has as its key variable the region of space that is the animal's current focus of attention, and demonstrate, using computer-simulated behavioral experiments, that the model is consistent with a broad range of experimental observations. A core hypothesis is that the rat explicitly decodes the location in space of whisker contacts and that this representation is used to regulate whisker drive signals. This proposition stands in contrast to earlier proposals that the modulation of whisker movement during exploration is mediated primarily by reflex loops. We go on to argue that the superior colliculus is a candidate neural substrate for the siting of a head-centred map guiding whisker movement, in analogy to current models of visual attention. The proposed model has the potential to offer a more complete understanding of whisker control as well as to highlight the potential of the rodent and its whiskers as a tool for the study of mammalian attention

    PLACE CELLS IN THE VENTRAL HIPPOCAMPUS OF RATS

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