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Dopaminergic neurons (DANs) drive learning across the animal kingdom, but the upstream circuits that regulate their activity and thereby learning remain poorly understood. We provide a synaptic-resolution connectome of the circuitry upstream of all DANs in a learning center, the mushroom body of Drosophila larva. We discover afferent sensory pathways and a large population of neurons that provide feedback from mushroom body output neurons and link distinct memory systems (aversive and appetitive). We combine this with functional studies of DANs and their presynaptic partners and with comprehensive circuit modeling. We find that DANs compare convergent feedback from aversive and appetitive systems, which enables the computation of integrated predictions that may improve future learning. Computational modeling reveals that the discovered feedback motifs increase model flexibility and performance on learning tasks. Our study provides the most detailed view to date of biological circuit motifs that support associative learning.
This article was published in the following journal.
Name: Nature neuroscience
Extracting the structure of complex environments is at the core of our ability to interpret the present and predict the future. This skill is important for a range of behaviours from navigating a new ...
Learning to produce spatiotemporal sequences is a common task that the brain has to solve. The same neural substrate may be used by the brain to produce different sequential behaviours. The way the br...
It has been recently shown that deep learning models such as convolutional neural networks (CNN), deep belief networks (DBN) and recurrent neural networks (RNN), exhibited remarkable ability in modeli...
Implicit motor learning, which is a non-conscious form of learning characterized by motor performance improvement with practice, plays an essential role in various daily activities. Earlier study usin...
Neuromorphic systems consisting of artificial neurons and memristive synapses could provide a much better performance and a significantly more energy-efficient approach to the implementation of differ...
Glioblastoma (GBM) adaptive, global, innovative learning environment (GBM AGILE) is an international, seamless Phase II/III response adaptive randomization platform trial designed to evalu...
This study evaluates the length of time an insect repellent product can protect against three species of ticks. Participants will have one arm treated with the repellent, and throughout th...
Artificial Intelligence and Machine Learning techniques may provide insight into exploring the potential covert association behind and reveal some early ocular architecture changes in indi...
Cognitive deficits in HIV reflect degraded brain network functioning that may be amenable to remediation through cognitive training. In this sub-study, we will make use of Plasticity-based...
Currently, treatment of Parkinson's Disease with deep brain stimulation (DBS) uses continuous high frequency stimulation. The investigators have previously shown that by controlling the st...
Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)
A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.
Behavioral treatment that uses drill and practice, compensatory and adaptive strategies to facilitate improvement in targeted learning areas.
Adjustment of BRAIN WAVES from two or more neuronal groups within or across a brain structure (e.g., cortical and limbic brain structures) to become uniform in EEG oscillation patterns in response to a stimulus. It is interpreted as a brain integration sign during many processes such as learning, memory, and perception and involves reciprocal neural connections.
Free-standing or supported light weight meshwork fabric made of cotton, silk, polyester or other material having openings too small to allow entry of mosquitoes or other insects, thereby protecting against INSECT BITES; INSECT STINGS, and insect-borne diseases.
Biological therapy involves the use of living organisms, substances derived from living organisms, or laboratory-produced versions of such substances to treat disease. Some biological therapies for cancer use vaccines or bacteria to stimulate the body&rs...