Chronic exposure to odors at naturally occurring concentrations triggers limited plasticity in early stages of Drosophila olfactory processing

In insects and mammals, olfactory experience in early life alters olfactory behavior and function in later life. In the vinegar fly Drosophila, flies chronically exposed to a high concentration of a monomolecular odor exhibit reduced behavioral aversion to the familiar odor when it is re-encountered. This change in olfactory behavior has been attributed to selective decreases in the sensitivity of second-order olfactory projection neurons (PNs) in the antennal lobe that respond to the overrepresented odor. However, since odorant compounds do not occur at similarly high concentrations in natural sources, the role of odor experience-dependent plasticity in natural environments is unclear. Here, we investigated olfactory plasticity in the antennal lobe of flies chronically exposed to odors at concentrations that are typically encountered in natural odor sources. These stimuli were chosen to each strongly and selectively excite a single class of primary olfactory receptor neuron (ORN), thus facilitating a rigorous assessment of the selectivity of olfactory plasticity for PNs directly excited by overrepresented stimuli. Unexpectedly, we found that chronic exposure to three such odors did not result in decreased PN sensitivity, but rather mildly increased responses to weak stimuli in most PN types. Odor-evoked PN activity in response to stronger stimuli was mostly unaffected by odor experience. When present, plasticity was observed broadly in multiple PN types and thus was not selective for PNs receiving direct input from the chronically active ORNs. We further investigated the DL5 olfactory coding channel and found that chronic odor-mediated excitation of its input ORNs did not affect PN intrinsic properties, local inhibitory innervation, ORN responses, or ORN-PN synaptic strength; however, broad-acting lateral excitation evoked by some odors was increased. These results show that PN odor coding is only mildly affected by strong persistent activation of a single olfactory input, highlighting the stability of early stages of insect olfactory processing to significant perturbations in the sensory environment.

Comprehensive chronic laminar single-unit, multi-unit, and local field potential recording performance with planar single shank electrode arrays

BACKGROUND

Intracortical electrode arrays that can record extracellular action potentials from small, targeted groups of neurons are critical for basic neuroscience research and emerging clinical applications. In general, these electrode devices suffer from reliability and variability issues, which have led to comparative studies of existing and emerging electrode designs to optimize performance. Comparisons of different chronic recording devices have been limited to single-unit (SU) activity and employed a bulk averaging approach treating brain architecture as homogeneous with respect to electrode distribution.

NEW METHOD

In this study, we optimize the methods and parameters to quantify evoked multi-unit (MU) and local field potential (LFP) recordings in eight mice visual cortices.

RESULTS

These findings quantify the large recording differences stemming from anatomical differences in depth and the layer dependent relative changes to SU and MU recording performance over 6-months. For example, performance metrics in Layer V and stratum pyramidale were initially higher than Layer II/III, but decrease more rapidly. On the other hand, Layer II/III maintained recording metrics longer. In addition, chronic changes at the level of layer IV are evaluated using visually evoked current source density.

COMPARISON WITH EXISTING METHOD(S)

The use of MU and LFP activity for evaluation and tracking biological depth provides a more comprehensive characterization of the electrophysiological performance landscape of microelectrodes.

CONCLUSIONS

A more extensive spatial and temporal insight into the chronic electrophysiological performance over time will help uncover the biological and mechanical failure mechanisms of the neural electrodes and direct future research toward the elucidation of design optimization for specific applications.