Mushroom body

…not Hebbian, for instance in the fly mushroom body, where plasticity depends on high-dimensional presynaptic activity

This webinar on learning and memory features three experts—Nicolas Brunel, Ashok Litwin-Kumar, and Julijana Gjorgieva—who present theoretical and computational approaches to understanding how neural circuits acquire and store information across different scales. Brunel discusses calcium-based plasticity and how standard “Hebbian-like” plasticity rules inferred from in vitro or in vivo datasets constrain synaptic dynamics, aligning with classical observations (e.g., STDP) and explaining how synaptic connectivity shapes memory. Litwin-Kumar explores insights from the fruit fly connectome, emphas

For the olfactory associative learning to be specific, stimulus representation in the Kenyon cell (KC) population should be accurate with minimal activity overlap between different stimuli, which is achieved by the sparse and highly odor-specific KC response patterns. While a multitude of cellular and network mechanisms substantially increase the KC population sparsity, the proportion of KCs responding unreliably to a given odor over multiple trials is roughly three times larger than that of reliable responders [1, 3], leading to substantial response correlations between different odors. Consi

…fly brain, dopaminergic neurons in the mushroom body, a central structure for learning and memory, have been suggested to compute such

Neuronal circuits universally recognize novel stimuli, but unpredicted features in a stimulus amplify its importance, shaping attentive reactions. Habituation, the gradual reduction of responses to repetitive stimuli, and its counterpart, dishabituation, the reversal of habituated responses upon exposure to novel stimuli, are fundamental processes that organisms employ to navigate their environment efficiently. Although mechanisms driving Habituation/Dishabituation remain partly understood, the communication within neuronal circuits, which ostensibly underlies these choices, is an emerging fie

In insects, Olfactory Receptor Neurons ('ORNs') are grouped together into sensory hairs ('sensilla') in a stereotypical manner. Grouped ORNs: (i) antagonistically regulate the same behaviors, (ii) mutually inhibit each other via electrical interactions, and (iii) have a systematic size-asymmetry, resulting in asymmetric inhibitory interactions. The functional significance of this highly conserved organization is not known. We constructed a phenomenological model of nonlinearly coupled ORNs, which shows that inhibition between ORNs transiently amplifies the hedonic value ('valence') of an odor

A number of recent studies have explored the analysis of multi-area neural recording data and, in particular, the shared communication, computation and representational subspaces between brain areas. These have largely relied upon model-based methods to quantify shared variability between areas, but a standard, model-free measure is lacking. In this work we 1) present a candidate for this measure that we call the effective number of shared dimensions (ENSD), 2) demonstrate the utility and computational efficiency of our measure by visiting results from two recent studies (the "communication su

The availability and scale of synapse-resolution connectomes containing the wiring of neural systems has grown rapidly in recent years. In order to exploit these rich datasets and extract neural circuit mechanisms underlying behavior, scalable connectome analysis tools capable of predicting information routing principles in circuit pathways are necessary. Current methods to extract neurons mediating information flow only consider a limited set of pathway lengths and do not scale to large connectome datasets. Here, we develop an efficient framework to identify such bottlenecks in pathways betwe

Drosophila olfactory sensory hairs ("sensilla") typically house two olfactory receptor neurons (ORNs) which can laterally inhibit each other via electrical ("ephaptic") coupling. ORN pairing is highly stereotyped and genetically determined. Thus, olfactory signals arriving in the Antennal Lobe (AL) have been pre-processed by a fixed and shallow network at the periphery. To uncover the functional significance of this organization, we developed a nonlinear phenomenological model of asymmetrically coupled ORNs responding to odor mixture stimuli. We derived an analytical solution to the ORNs’ dyna

…us to identify interconnections in the mushroom body neuropil that form an 'incentive circuit', supporting rich dynamics of memory acquisition, consolidation and forgetting. In addition, new insights into dopamine function in the fruit fly brain motivate a novel 'dopaminergic plasticity rule' that alters the weights between input sensory patterns and output neurons of the mushroom body

Animals learn when punishment or reward is predicted by neutral stimuli like tones or odors. Synaptic plasticity maps the predictor to the appropriate behavioral drive, forming a memory trace. But if the predictor is presented as one of two options, the optimal response is uncertain and depends on the alternative. Can a single memory trace evoke different behaviors, depending on stimulus context? We used optogenetics in Drosophila to form an odor-punishment association restricted to a single set of synapses, ie. a single memory trace. These flies showed flexible behavioral responses to a given

Foraging animals make decisions based on cues that are unreliable predictors of reward. In these situations, the ratio with which an animal divides its choices between cues matches the ratios with which they provide reward. This operant matching strategy is widespread amongst vertebrates. Performing operant matching requires animals to possess a valuation of available cues, and to update them when cue-reward relationships change. While neurons that represent value information have been found in several brain regions, less is known about how value is updated. Theoretical studies suggest that th

…in two major downstream areas - the mushroom body (MB) and lateral horn (LH). These areas are thought to support different aspects of olfactory information processing: the MB supports ongoing learning, while the LH mediates innate behavioral responses. Here, we provide a geometric analysis of representations in these different areas. We model odorant represe

…In Drosophila mushroom body (MB), ~20 pairs of dopamine neurons (DANs) and mushroom body output neurons (MBON) together form compartmental units of associative learning. Each DAN cell type is selectively tuned to rewards or punishments and write and update memories with cell-type-s

High-dimensional neural representations are observed in many brain areas and are believed to be a powerful substrate for flexible computation. Theories have suggested that the vertebrate cerebellum and other cerebellum-like structures produce such high-dimensional representations by expanding their input into a vast layer of granule-like cells. Signals are typically routed to such expanded representations by anatomical “bottlenecks”: in the mammalian cortico-cerebellar pathway, input from across the cortex converges in the pontine nuclei, from which roughly half of the mossy fiber input to gra

Brain networks possess many non-random features that might present a key to the computational effectiveness and robustness of the nervous system. Information-transmission pathways in neuronal structure, especially in complex connectomes, seem to favor specific recurrent motifs. For intrinsically directional and weighted networks such as those in the brain, it is particularly important to use methods that are sensitive to the weight-encoded information. We use new weighted methods to assess statistics of motives in the connectomes of various animals: \textit{C. elegans}, tadpole, drosophila,

…in the neural ensemble of the mushroom bodies. Dopamine directed synaptic depression alters the route of odour-driven activity through the mushroom body output network. This circuit configuration and influence of internal state guide the expression of appropriate behaviour. Importantly, learned behavi

Olfactory navigation provides a tractable model for studying the circuit basis of sensori-motor transformations and goal-directed behaviour. Macroscopic organisms typically navigate in odor plumes that provide a noisy and uncertain signal about the location of an odor source. Work in many species has suggested that animals accomplish this task by combining temporal processing of dynamic odor information with an estimate of wind direction. Our lab has been using adult walking Drosophila to understand both the computational algorithms and the neural circuits that support navigation in a plume