Most neurons in peripheral sensory pathways initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. It is unclear how this phenomenon affects stimulus coding in the later stages of sensory processing. Here, we show that a temporally sparse and reliable stimulus representation develops naturally in sequential stages of a sensory network with adapting neurons. As a modeling framework we employ a mean-field approach together with an adaptive population density treatment, accompanied by numerical simulations of spiking neural networks. We find that cellular adaptation plays a critical role in the dynamic reduction of the trial-by-trial variability of cortical spike responses by transiently suppressing self-generated fast fluctuations in the cortical balanced network. This provides an explanation for a widespread cortical phenomenon by a simple mechanism. We further show that in the insect olfactory system cellular adaptation is sufficient to explain the emergence of the temporally sparse and reliable stimulus representation in the mushroom body. Our results reveal a generic, biophysically plausible mechanism that can explain the emergence of a temporally sparse and reliable stimulus representation within a sequential processing architecture.
Kenyon cells, the intrinsic neurons of the insect mushroom body, have the intriguing property of responding in a sparse way to odorants. Sparse neuronal codes are often invariant to changes in stimulus intensity and duration, and sparse coding often depends on global inhibition. We tested if this is the case for honeybees' Kenyon cells, too, and used in vivo Ca²⁺ imaging to record their responses to different odorant concentrations. Kenyon cells responded not only to the onset of odorant stimuli (ON responses), but also to their termination (OFF responses). Both, ON and OFF responses increased with increasing odorant concentration. ON responses were phasic and invariant to the duration of odorant stimuli, while OFF responses increased with increasing odorant duration. Pharmacological blocking of GABA receptors in the brain revealed that ionotropic GABA(A) and metabotropic GABA(B) receptors attenuate Kenyon cells' ON responses without changing their OFF responses. Ionotropic GABA(A) receptors attenuated Kenyon cell ON responses more strongly than metabotropic GABA(B) receptors. However, the response dynamic, temporal resolution and paired-pulse depression did not depend on GABA(A) transmission. These data are discussed in the context of mechanisms leading to sparse coding in Kenyon cells.
The in vivo and semi-in vivo preparation for calcium imaging has been developed in our lab by Joerges, Küttner and Galizia over ten years ago, to measure odor evoked activity in the antennal lobe. From then on, it has been continuously refined and applied to different neuropiles in the bee brain. Here, we describe the preparation currently used in the lab to measure activity in mushroom body neurons using a dextran coupled calcium-sensitive dye (Fura-2). We retrogradely stain mushroom body neurons by injecting dye into their axons or soma region. We focus on reducing the invasiveness, to achieve a preparation in which it is still possible to train the bee using PER conditioning. We are able to monitor and quantify the behavioral response by recording electro-myograms from the muscle which controls the PER (M17). After the physiological experiment the imaged structures are investigated in greater detail using confocal scanning microscopy to address the identity of the neurons.
In classical conditioning a predictive relationship between a neutral stimulus (conditioned stimulus; CS) and a meaningful stimulus (unconditioned stimulus; US) is learned when the CS precedes the US. In backward conditioning the sequence of the stimuli is reversed. In this situation animals might learn that the CS signals the end or the absence of the US. In honeybees 30 min and 24 h following backward conditioning a memory for the excitatory and inhibitory properties of the CS could be retrieved, but it remains unclear whether a late long-term memory is formed that can be retrieved 72 h following backward conditioning. Here we examine this question by studying late long-term memory formation in forward and backward conditioning of the proboscis extension response (PER). We report a difference in the stability of memory formed upon forward and backward conditioning with the same number of conditioning trials. We demonstrate a transcription-dependent memory 72 h after forward conditioning but do not observe a 72 h memory after backward conditioning. Moreover we find that protein degradation is differentially involved in memory formation following these two conditioning protocols. We report differences in the level of a transcription factor, the cAMP response element binding protein (CREB) known to induce transcription underlying long-term memory formation, following forward and backward conditioning. Our results suggest that these alterations in CREB levels might be regulated by the proteasome. We propose that the differences observed are due to the sequence of stimulus presentation between forward and backward conditioning and not to differences in the strength of the association of both stimuli.
In this study we describe egfp expression induced by two techniques: in vivo electroporation and viral transduction in several cell types of the adult honeybee brain. Non-neuronal and neuronal cell types were identified and the expression persisted at least during three days. Kenyon cells, optic lobe neurons and protocerebral lobe neurons were electroporated. Astrocyte-like glia cells, fibrous lamellar glia cells and cortex glia cells were identified. Viral transduction targeted one specific type of glia cells that could not be identified. EGFP positive cells types were rather variable after electroporation, and viral transduction resulted in more homogenous groups of positive cells. We propose that these techniques remain a good alternative to transgenic animals because they potentially target only somatic cells.
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