Learning-induced Cortical Plasticity Research Articles

Short- and long-term neuroplasticity interact during the perceptual learning of concurrent speech.

Plasticity from auditory experience shapes the brain's encoding and perception of sound. However, whether such long-term plasticity alters the trajectory of short-term plasticity during speech processing has yet to be investigated. Here, we explored the neural mechanisms and interplay between short- and long-term neuroplasticity for rapid auditory perceptual learning of concurrent speech sounds in young, normal-hearing musicians and nonmusicians. Participants learned to identify double-vowel mixtures during ~ 45min training sessions recorded simultaneously with high-density electroencephalography (EEG). We analyzed frequency-following responses (FFRs) and event-related potentials (ERPs) to investigate neural correlates of learning at subcortical and cortical levels, respectively. Although both groups showed rapid perceptual learning, musicians showed faster behavioral decisions than nonmusicians overall. Learning-related changes were not apparent in brainstem FFRs. However, plasticity was highly evident in cortex, where ERPs revealed unique hemispheric asymmetries between groups suggestive of different neural strategies (musicians: right hemisphere bias; nonmusicians: left hemisphere). Source reconstruction and the early (150-200ms) time course of these effects localized learning-induced cortical plasticity to auditory-sensory brain areas. Our findings reinforce the domain-general benefits of musicianship but reveal that successful speech sound learning is driven by a critical interplay between long- and short-term mechanisms of auditory plasticity, which first emerge at a cortical level.

Histone Deacetylase Inhibition via RGFP966 Releases the Brakes on Sensory Cortical Plasticity and the Specificity of Memory Formation.

Research over the past decade indicates a novel role for epigenetic mechanisms in memory formation. Of particular interest is chromatin modification by histone deacetylases (HDACs), which, in general, negatively regulate transcription. HDAC deletion or inhibition facilitates transcription during memory consolidation and enhances long-lasting forms of synaptic plasticity and long-term memory. A key open question remains: How does blocking HDAC activity lead to memory enhancements? To address this question, we tested whether a normal function of HDACs is to gate information processing during memory formation. We used a class I HDAC inhibitor, RGFP966 (C21H19FN4O), to test the role of HDAC inhibition for information processing in an auditory memory model of learning-induced cortical plasticity. HDAC inhibition may act beyond memory enhancement per se to instead regulate information in ways that lead to encoding more vivid sensory details into memory. Indeed, we found that RGFP966 controls memory induction for acoustic details of sound-to-reward learning. Rats treated with RGFP966 while learning to associate sound with reward had stronger memory and additional information encoded into memory for highly specific features of sounds associated with reward. Moreover, behavioral effects occurred with unusually specific plasticity in primary auditory cortex (A1). Class I HDAC inhibition appears to engage A1 plasticity that enables additional acoustic features to become encoded in memory. Thus, epigenetic mechanisms act to regulate sensory cortical plasticity, which offers an information processing mechanism for gating what and how much is encoded to produce exceptionally persistent and vivid memories. Significance statement: Here we provide evidence of an epigenetic mechanism for information processing. The study reveals that a class I HDAC inhibitor (Malvaez et al., 2013; Rumbaugh et al., 2015; RGFP966, chemical formula C21H19FN4O) alters the formation of auditory memory by enabling more acoustic information to become encoded into memory. Moreover, RGFP966 appears to affect cortical plasticity: the primary auditory cortex reorganized in a manner that was unusually "tuned-in" to the specific sound cues and acoustic features that were related to reward and subsequently remembered. We propose that HDACs control "informational capture" at a systems level for what and how much information is encoded by gating sensory cortical plasticity that underlies the sensory richness of newly formed memories.

Decoding the Formation of New Semantics: MVPA Investigation of Rapid Neocortical Plasticity during Associative Encoding through Fast Mapping.

Neocortical structures typically only support slow acquisition of declarative memory; however, learning through fast mapping may facilitate rapid learning-induced cortical plasticity and hippocampal-independent integration of novel associations into existing semantic networks. During fast mapping the meaning of new words and concepts is inferred, and durable novel associations are incidentally formed, a process thought to support early childhood's exuberant learning. The anterior temporal lobe, a cortical semantic memory hub, may critically support such learning. We investigated encoding of semantic associations through fast mapping using fMRI and multivoxel pattern analysis. Subsequent memory performance following fast mapping was more efficiently predicted using anterior temporal lobe than hippocampal voxels, while standard explicit encoding was best predicted by hippocampal activity. Searchlight algorithms revealed additional activity patterns that predicted successful fast mapping semantic learning located in lateral occipitotemporal and parietotemporal neocortex and ventrolateral prefrontal cortex. By contrast, successful explicit encoding could be classified by activity in medial and dorsolateral prefrontal and parahippocampal cortices. We propose that fast mapping promotes incidental rapid integration of new associations into existing neocortical semantic networks by activating related, nonoverlapping conceptual knowledge. In healthy adults, this is better captured by unique anterior and lateral temporal lobe activity patterns, while hippocampal involvement is less predictive of this kind of learning.

Interneurons containing somatostatin are affected by learning-induced cortical plasticity

The maintenance of neural circuit stability is a dynamic process that requires the plasticity of many cellular and synaptic components. By changing the excitatory/inhibitory balance, inhibitory GABAergic plasticity can regulate excitability, and contribute to neural circuit function and refinement in learning and memory. Increased inhibitory GABAergic neurotransmission has been shown in brain structures involved in the learning process. Previously, we showed that classical conditioning in which tactile stimulation of one row of vibrissae (conditioned stimulus, CS) was paired with a tail shock (unconditioned stimulus, UCS) in adult mice results in the increased density of GABAergic interneurons and increased expression of glutamic acid decarboxylase (GAD)-67 in barrels of the “trained” row cortical representation. In inhibitory neurons of the rat cortex GAD co-localizes with several proteins and peptides. We found previously that the density of the parvalbumin (GAD+/Prv+)-containing subpopulation is not changed after conditioning. In the present study, we examined GABAergic somatostatin (Som)-, calbindin (CB)- and calretinin (CR)-positive interneurons in the cortical representation of “trained” vibrissae after training. Cells showing double immunostaining for GAD/Som, GAD/CR and GAD/CB were counted in the barrels representing vibrissae activated during the training and in control, untouched rows. We found a substantial increase of GAD/Som-containing cells in the trained row representation. No changes in the density of GAD/CR or GAD/CB neurons were observed. These results suggest that Som-containing interneurons are involved in learning-induced changes in the inhibitory cortical network.

Cognitive training in schizophrenia: a neuroscience-based approach

Meta-analytic data from over a decade of research in cognitive remediation, when combined with recent findings from basic and clinical neuroscience, have resulted in a new understanding of the critical elements that can contribute to successful cognitive training approaches for schizophrenia. Some of these elements include: the use of computerized repetitive practice methods, high dosing schedules, a focus on sensory processing, and carefully constrained and individually adapted learning trials. In a preliminary randomized controlled trial of cognitive training exercises based on these principles, we demonstrated significant improvements in working memory, verbal learning and memory, and global cognition in patients with schizophrenia. These cognitive improvements were accompanied by neurobiological findings suggestive of learning-induced cortical plasticity. Future directions for research and essential remaining questions are discussed.

Remodeling the cortex in memory: Increased use of a learning strategy increases the representational area of relevant acoustic cues

Associative learning induces plasticity in the representation of sensory information in sensory cortices. Such high-order associative representational plasticity (HARP) in the primary auditory cortex (A1) is a likely substrate of auditory memory: it is specific, rapidly acquired, long-lasting and consolidates. Because HARP is likely to support the detailed content of memory, it is important to identify the necessary behavioral factors that dictate its induction. Learning strategy is a critical factor for the induction of plasticity ( Bieszczad & Weinberger, 2010b). Specifically, use of a strategy that relies on tone onsets induces HARP in A1 in the form of signal-specific decreased threshold and bandwidth. The present study tested the hypothesis that the form and degree of HARP in A1 reflects the amount of use of an “onset strategy”. Adult male rats ( n = 7) were trained in a protocol that increased the use of this strategy from ∼20% in prior studies to ∼80%. They developed signal-specific gains in representational area, transcending plasticity in the form of local changes in threshold and bandwidth. Furthermore, the degree of area gain was proportional to the amount of use of the onset strategy. A second complementary experiment demonstrated that use of a learning strategy that specifically did not rely on tone onsets did not produce gains in representational area; but rather produced area loss. Together, the findings indicate that the amount of strategy use is a dominant factor for the induction of learning-induced cortical plasticity along a continuum of both form and degree.

Learning strategy determines auditory cortical plasticity

Learning modifies the primary auditory cortex (A1) to emphasize the processing and representation of behaviorally relevant sounds. However, the factors that determine cortical plasticity are poorly understood. While the type and amount of learning are assumed to be important, the actual strategies used to solve learning problems might be critical. To investigate this possibility, we trained two groups of adult male Sprague–Dawley rats to bar-press (BP) for water contingent on the presence of a 5.0 kHz tone using two different strategies: BP during tone presence or BP from tone-onset until receiving an error signal after tone cessation. Both groups achieved the same high levels of correct performance and both groups revealed equivalent learning of absolute frequency during training. Post-training terminal “mapping” of A1 showed no change in representational area of the tone signal frequency but revealed other substantial cue-specific plasticity that developed only in the tone-onset-to-error strategy group. Threshold was decreased ∼10 dB and tuning bandwidth was narrowed by ∼0.7 octaves. As sound onsets have greater perceptual weighting and cortical discharge efficacy than continual sound presence, the induction of specific learning-induced cortical plasticity may depend on the use of learning strategies that best exploit cortical proclivities. The present results also suggest a general principle for the induction and storage of plasticity in learning, viz., that the representation of specific acquired information may be selected by neurons according to a match between behaviorally selected stimulus features and circuit/network response properties.

Effects of sensory learning on intracortical synaptic transmission in the barrel cortex of mice

Pairing tactile stimulation of a row of whiskers with a tail shock results in an expansion of the functional representation of the stimulated whiskers within the primary somatosensory cortex of mice. Using the same paradigm, the present study examined field potentials evoked in ex vivo slices of the barrel cortex. The amplitude of responses, evoked by single and repetitive stimuli in layer IV–layer II/III pathway contained within the barrel column corresponding to the whisker stimulated during training, was unchanged. In contrast, in a transcolumnar pathway from the “trained” barrel to layer II/III of the neighboring, “untrained” column, the amplitude of responses was reduced and responses to trains of stimuli applied at 40 Hz, but not at lower frequencies, depressed faster. These data are suggestive of a selective weakening of excitatory transmission and/or enhancement of inhibitory transmission in transcolumnar pathways, which accompany associative learning-induced cortical plasticity.

Changes in NMDA receptor expression in auditory cortex after learning

Extensive practice on auditory learning tasks dramatically alters the functional organization and response properties of neurons in the auditory cortex. The cellular mechanisms responsible for this auditory learning-induced cortical plasticity are unclear; however, changes in synaptic function involving NMDA receptors have been strongly implicated. To test this hypothesis, we measured the change in gene expression of NMDA receptors and associated proteins in the auditory cortex of adult rats trained to perform an auditory identification task. NMDA receptor 2A and 2B gene expression in auditory cortex decreased significantly as auditory discrimination improved whereas expression of Arc, an immediate early gene involved in memory stabilization, increased. These results suggest that changes in NMDA receptors 2A and 2B and Arc enhance synaptic plasticity, thereby facilitating experience-dependent cortical remodeling and auditory learning.

Learning modifies subsequent induction of long-term potentiation-like and long-term depression-like plasticity in human motor cortex.

Learning may alter rapidly the output organization of adult motor cortex. It is a long-held hypothesis that modification of synaptic strength along cortical horizontal connections through long-term potentiation (LTP) and long-term depression (LTD) forms one important mechanism for learning-induced cortical plasticity. Strong evidence in favor of this hypothesis was provided for rat primary motor cortex (M1) by showing that motor learning reduced subsequent LTP but increased LTD. Whether a similar relationship exists in humans is unknown. Here, we induced LTP-like and LTD-like plasticity in the intact human M1 by an established paired associative stimulation (PAS) protocol. PAS consisted of 200 pairs of electrical stimulation of the right median nerve, followed by focal transcranial magnetic stimulation of the hand area of the left M1 at an interval equaling the individual N20 latency of the median nerve somatosensory-evoked cortical potential (PAS(N20)) or N20-5 msec (PAS(N20-5)). PAS(N20) induced reproducibly a LTP-like long-lasting (>30 min) increase in motor-evoked potentials from the left M1 to a thumb abductor muscle of the right hand, whereas PAS(N20-5) induced a LTD-like decrease. Repeated fastest possible thumb abduction movements resulted in learning, defined by an increase in maximum peak acceleration of the practiced movements, and prevented subsequent PAS(N20)-induced LTP-like plasticity but enhanced subsequent PAS(N20-5)-induced LTD-like plasticity. The same number of repeated slow thumb abduction movements did not result in learning and had no effects on PAS-induced plasticity. Findings support the view that learning in human M1 occurs through LTP-like mechanisms.

Music and learning-induced cortical plasticity.

Auditory stimuli are encoded by frequency-tuned neurons in the auditory cortex. There are a number of tonotopic maps, indicating that there are multiple representations, as in a mosaic. However, the cortical organization is not fixed due to the brain's capacity to adapt to current requirements of the environment. Several experiments on cerebral cortical organization in musicians demonstrate an astonishing plasticity. We used the MEG technique in a number of studies to investigate the changes that occur in the human auditory cortex when a skill is acquired, such as when learning to play a musical instrument. We found enlarged cortical representation of tones of the musical scale as compared to pure tones in skilled musicians. Enlargement was correlated with the age at which musicians began to practice. We also investigated cortical representations for notes of different timbre (violin and trumpet) and found that they are enhanced in violinists and trumpeters, preferentially for the timbre of the instrument on which the musician was trained. In recent studies we extended these findings in three ways. First, we show that we can use MEG to measure the effects of relatively short-term laboratory training involving learning to perceive virtual instead of spectral pitch and that the switch to perceiving virtual pitch is manifested in the gamma band frequency. Second, we show that there is cross-modal plasticity in that when the lips of trumpet players are stimulated (trumpet players assess their auditory performance by monitoring the position and pressure of their lips touching the mouthpiece of their instrument) at the same time as a trumpet tone, activation in the somatosensory cortex is increased more than it is during the sum of the separate lip and trumpet tone stimulation. Third, we show that musicians' automatic encoding and discrimination of pitch contour and interval information in melodies are specifically enhanced compared to those in nonmusicians in that musicians show larger functional mismatch negativity (MMNm) responses to occasional changes in melodic contour or interval, but that the two groups show similar MMNm responses to changes in the frequency of a pure tone.

Pursuing dynamic reorganization in auditory cortex using chronic, multichannel unit recordings in awake, behaving cats

We implanted microelectrode arrays bilaterally into auditory cortex of trained cats in order to assess dynamic cortical reorganization. Cats were trained to listen to a series of tone-pip pairs and respond to the pair that had different frequencies. Over several months of training, a gradual decrease (−4.2×10 −4 Weber Fractions/training day) in the frequency discrimination threshold occurred ( p<0.00001). Neural recordings from a trained cat not performing the task were obtained for 5 days. Temporal and frequency response properties remained stable over this time. These techniques are useful for a variety of studies on learning-induced cortical plasticity.

Conditioned changes in the basal forebrain: Relations with learning-induced cortical plasticity

Simultaneous recordings were performed in the auditory cortex and in the basal forebrain (BF) of rats subjected to habituation, conditioning (tone followed by a footshock), extinction, and reconditioning. Quantification of myographic activity from the neck muscles revealed behavioral conditioning in 10–20 trials. Short-latency, increased discharges of the BF neurons were observed within the first 5 conditioning trials, whereas tone-evoked responses above the level of the first habituation trials only started to occur between the 5th and the 10th trial in the auditory cortex. Increased discharges persisted in the BF during extinction; the cortical responses returned to their habituation level. Relative to conditioning, pseudoconditioning induced much smaller increased discharges in both structures. The role of the BF neurons in promoting learning-induced cortical plasticity is discussed in light of these results.

Functional organization of the auditory cortex: maps and mechanisms

Recent studies have led to a better understanding of several aspects of the organization and physiological mechanisms involved in the processing of information in the auditory cortex. A wide range of approaches have revealed new information regarding the histochemistry, cortico-cortical connections, single-unit physiology, and functional spatial organization, as well as mechanisms and effects of representational and learning-induced cortical plasticity.