ChABC infusions into medial prefrontal cortex, but not posterior parietal cortex, improve the performance of rats tested on a novel, challenging delay in the touchscreen TUNL task

Abstract

Perineuronal nets (PNNs) are specialized extracellular matrix structures that surround subsets of neurons throughout the central nervous system (CNS). They are made up of chondroitin sulfate proteoglycans (CSPGs), hyaluronan, tenascin-R, and many other link proteins that together make up their rigid and lattice-like structure. Modulation of PNNs can alter synaptic plasticity and thereby affect learning, memory, and cognition. In the present study, we degraded PNNs in the medial prefrontal (mPFC) and posterior parietal (PPC) cortices of Long-Evans rats using the enzyme chondroitinase ABC (ChABC), which cleaves apart CSPGs. We then measured the consequences of PNN degradation on spatial working memory (WM) with a trial-unique, non-matching-to location (TUNL) automated touchscreen task. All rats were trained with a standard 6 sec delay and 20 sec inter-trial interval (ITI) and then tested under four different conditions: a 6 sec delay, a variable 2 or 6 sec delay, a 2 sec delay with a 1 sec ITI (interference condition), and a 20 sec delay. Rats that received mPFC ChABC treatment initially performed TUNL with higher accuracy, more selection trials completed, and fewer correction trials completed compared to controls in the 20 sec delay condition but did not perform differently from controls in any other condition. Rats that received PPC ChABC treatment did not perform significantly differently from controls in any condition. Posthumous immunohistochemistry confirmed an increase in CSPG degradation products (C4S stain) in the mPFC and PPC following ChABC infusions while WFA staining intensity and parvalbumin positive neuron number were decreased following mPFC, but not PPC, ChABC infusions. These findings suggest that PNNs in the mPFC play a subtle role in spatial WM, but PNNs in the PPC do not. Furthermore, it appears that PNNs in the mPFC are involved in adapting to a challenging novel delay, but that they do not play an essential role in spatial WM function.

Enzymatic Degradation of Cortical Perineuronal Nets Reverses GABAergic Interneuron Maturation

“…Considerable research efforts have focused on the modulation of synaptic plasticity after ChABC application, along with the effects on learning, memory and cognition [34,[39][40][41][42]. However, less is understood about the molecular phenotype induced.…”

How Stress Influences the Dynamic Plasticity of the Brain’s Extracellular Matrix

“…In some cases, PNNs have been associated with increased firing of neurons they surround, which are primarily parvalbumin+ inhibitory interneurons in the neocortex and hippocampus (Sorg et al, 2016;Wingert and Sorg, 2021). The functional consequences of PNNs seem to differ depending on brain region, cell type, and behavioral task, with some studies showing that PNNs facilitate learning and memory, while others show they have an inhibitory effect on these processes (Paylor et al, 2018;Anderson et al, 2020;Carulli et al, 2020;Cope et al, 2021;Wingert and Sorg, 2021). The overall picture that is emerging is one that is common in biology-an inverted U-shaped curve exists where atypically low or high PNNs impair function.…”

The Touchscreen‐Based Trial‐Unique, Nonmatching‐To‐Location (TUNL) Task as a Measure of Working Memory and Pattern Separation in Rats and Mice

“…Figure 12 also demonstrates the latency for reward collection. If an experimental manipulation impacts reward or motivational processes, the latency for reward collection may be affected (?Scott et al, 2020?). The TUNL task also allows for the investigation of performance following WM improvement, which can demonstrate an increase in percent accuracy, and an increase the amount of selection trials (Anderson et al, 2020).…”

“…If an experimental manipulation impacts reward or motivational processes, the latency for reward collection may be affected (?Scott et al, 2020?). The TUNL task also allows for the investigation of performance following WM improvement, which can demonstrate an increase in percent accuracy, and an increase the amount of selection trials (Anderson et al, 2020). As well, when WM performance stays consistent in the TUNL task, it may help highlight physiological processes not involved (Kumar, Olley, Steckler, & Talpos, 2015;Sokolenko, Hudson, Nithianantharajah, & Jones, 2019).…”

“…Extending sessions gives rats increased opportunities to learn the desired rules. Not only does this reduce training time to reach criterion and ultimately complete training, but it helps defend against confounding “mediating strategies” used by rats (Anderson et al., 2020; Davies et al., 2017; Scott et al., 2019; Scott et al., 2021). This approach is implemented throughout Must Touch, Must Initiate, and Punish Incorrect Training (Basic Protocols 3‐4).…”