Arc expression and neuroplasticity in primary auditory cortex during initial learning are inversely related to neural activity

Abstract

Models of learning-dependent sensory cortex plasticity require local activity and reinforcement. An alternative proposes that neural activity involved in anticipation of a sensory stimulus, or the preparatory set, can direct plasticity so that changes could occur in regions of sensory cortex lacking activity. To test the necessity of target-induced activity for initial sensory learning, we trained rats to detect a low-frequency sound. After learning, Arc expression and physiologically measured neuroplasticity were strong in a high-frequency auditory cortex region with very weak target-induced activity in control animals. After 14 sessions, Arc and neuroplasticity were aligned with target-induced activity. The temporal and topographic correspondence between Arc and neuroplasticity suggests Arc may be intrinsic to the neuroplasticity underlying perceptual learning. Furthermore, not all neuroplasticity could be explained by activity-dependent models but can be explained if the neural activity involved in the preparatory set directs plasticity.rat | instrumental learning | neurophysiology T he brain's ability to modify its own structure and function is currently used in diverse therapies involving remediation of language-learning impairment, reversing age-related cognitive decline, stroke rehabilitation, and others. These powers of neuroplasticity stem from the mammalian brain's ability to reorganize in response to experience (1-4). In sensory cortex, plasticity induced by sensory tasks optimizes the brain's capacity for future performance through amplifying activity that is most informative about reinforcement (4-6). Dominant models of this plasticity are activity-dependent (2,7,8), and associated learning is presumed to be a function of endogenous processes reliant on gene activation, because long-term plasticity and long-term memory require protein synthesis (9) following expression of immediate-early genes such as Arc (10, 11). Although models of sensory cortex plasticity are dependent on activity, these models fail to account for plasticity and behavioral phenomena observed shortly after learning.A prediction of activity-dependent models is that the strongest and most selective population responses to a target stimulus should grow the most. However, in contrast to this prediction, cortical patterns of activity early after learning enter a weakly selective and highly responsive state that is subsequently refined into a highly selective and less responsive state (3). The same phenomenon is reflected behaviorally. If auditory stimuli are paired with nucleus basalis stimulation, acoustically induced changes in respiratory rate can initially be induced by a wide range of sound frequencies, and these induced respiratory changes become more frequency-specific with time (12). These findings suggest that cortical regions representing sensory stimuli other than the learned sensory stimulus may be recruited in brain plasticity shortly after learning. This conclusion contrasts with activity-dependent models. Although memor...

Tone-detection training enhances spectral integration mediated by intracortical pathways in primary auditory cortex

“…Rats (n = 6) were trained to detect a 5 kHz (50 dB SPL) tone in order to receive a food reward, a procedure previously shown to induce plasticity in A1 (Carpenter-Hyland, et al, 2010). Training was repeated for 14 days and performance assessed using d′, as previously (Carpenter-Hyland, et al, 2010).…”

“…Training was repeated for 14 days and performance assessed using d′, as previously (Carpenter-Hyland, et al, 2010). For all animals, d′ improved over the course of training (Fig.…”

“…Although a number of studies have demonstrated learning-related plasticity in A1, fewer have examined cellular and molecular mechanisms (Carpenter-Hyland, Plummer, Vazdarjanova, & Blake, 2010; Guo et al, 2012). Even the locus of plasticity is not fully established, since changes observed in A1 may not originate there but instead could be relayed from subcortical structures (Ma & Suga, 2009).…”

Arc/Arg3.1 mRNA expression reveals a subcellular trace of prior sound exposure in adult primary auditory cortex

“…In the future it will be interesting to assess the importance of Arc expression for auditory plasticity by testing whether auditory learning is impaired in Arc knockout mice (Plath et al, 2006). The necessity of auditory cortical Arc for forming behaviorally-relevant auditory memories could also be tested by blocking Arc transcription (Guzowski et al, 2000) in an operant learning paradigm (Carpenter-Hyland et al, 2010) or in the natural context of acquiring a communication sound’s significance (Liu et al, 2006; Liu and Schreiner, 2007; Galindo-Leon et al, 2009). Furthermore, Arc ’s role in network homeostasis suggests that Arc expression must be tightly regulated during synaptic plasticity.…”

“…Arc ’s role in hippocampal-based memory consolidation (Guzowski et al, 2000; Plath et al, 2006) has therefore made it a promising target for investigating molecular mechanisms of long term cortical plasticity (Mahlke and Wallhäusser-Franke, 2004; Sun et al, 2005; Wang et al, 2006; Tan et al, 2007; Carpenter-Hyland et al, 2010; Gao et al, 2010; Gusev and Gubin, 2010). However, basic knowledge about Arc ’s pattern of expression across layer-dependent cortical networks is incomplete.…”