Because of its great genetic potential, the mouse (Mus musculus) has become a popular model species for studies on hearing and sound processing along the auditory pathways. Here, we present the first comparative study on the representation of neuronal response parameters to tones in primary and higher-order auditory cortical fields of awake mice. We quantified 12 neuronal properties of tone processing in order to estimate similarities and differences of function between the fields, and to discuss how far auditory cortex (AC) function in the mouse is comparable to that in awake monkeys and cats. Extracellular recordings were made from 1400 small clusters of neurons from cortical layers III/IV in the primary fields AI (primary auditory field) and AAF (anterior auditory field), and the higher-order fields AII (second auditory field) and DP (dorsoposterior field). Field specificity was shown with regard to spontaneous activity, correlation between spontaneous and evoked activity, tone response latency, sharpness of frequency tuning, temporal response patterns (occurrence of phasic responses, phasic-tonic responses, tonic responses, and off-responses), and degree of variation between the characteristic frequency (CF) and the best frequency (BF) (CF–BF relationship). Field similarities were noted as significant correlations between CFs and BFs, V-shaped frequency tuning curves, similar minimum response thresholds and non-monotonic rate-level functions in approximately two-thirds of the neurons. Comparative and quantitative analyses showed that the measured response characteristics were, to various degrees, susceptible to influences of anesthetics. Therefore, studies of neuronal responses in the awake AC are important in order to establish adequate relationships between neuronal data and auditory perception and acoustic response behavior.
Classical conditioning that involves mnemonic processing, that is, a "trace" period between conditioned and unconditioned stimulus, requires awareness of the association to be formed and is considered a simple model paradigm for declarative learning. Barrel cortex, the whisker representation of primary somatosensory cortex, is required for the learning of a tactile variant of trace eyeblink conditioning (TTEBC) and undergoes distinct map plasticity during learning. To investigate the cellular mechanism underpinning TTEBC and concurrent map plasticity, we used two-photon imaging of dendritic spines in barrel cortex of awake mice while being conditioned. Monitoring layer 5 neurons' apical dendrites in layer 1, we show that one cellular expression of barrel cortex plasticity is a substantial spine count reduction of ϳ15% of the dendritic spines present before learning. The number of eliminated spines and their time of elimination are tightly related to the learning success. Moreover, spine plasticity is highly specific for the principal barrel column receiving the main signals from the stimulated vibrissa. Spines located in other columns, even those directly adjacent to the principal column, are unaffected. Because layer 1 spines integrate signals from associative thalamocortical circuits, their column-specific elimination suggests that this spine plasticity may be the result of an association of top-down signals relevant for declarative learning and spatially precise ascending tactile signals.
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