In summary, the data from tactile training-independent sensory learning experiments have demonstrated the following. First, tactile perception can be bi-directionally altered by protocols that present stimuli at a pace resembling that of protocols used to induce LTP and LTD at a cellular level. Second, changes in tactile perception are paralleled by alterations in cortical maps, cortical activation and cortical excitability in the primary somatosensory cortex, which points to a susceptibility of early cortical processing stages. Third, cortical changes correlate with the individual change in perception, suggesting a causal role of cortical changes in mediating perception. And fourth, perceptual and cortical changes depend on NMDA receptor activation and can be potentiated by application of amphetamine, indicating involvement of neuromodulatory systems.

While many drugs block learning, a few drugs are known to enhance cortical plasticity. In vitro experiments have shown that alterations in synaptic efficacy can be modulated by adrenergic agents, which gate synaptic plasticity. In fact, a single dose of amphetamine [] resulted in almost a two-fold increase in both the normally observed improvement of tactile acuity and the cortical reorganization. These findings indicate that the processes underlying repetitive stimulation are further controlled by neuromodulatory systems (compare [] for cellular data and modelling).

Cellular studies have implicated the N-methyl--aspartate (NMDA) receptor as a major player in synaptic plasticity. A possible dependency of exposure-based learning on NMDA receptor activation was directly tested in humans using memantine, a substance that blocks NMDA receptors selectively []. It was found that a single dose of memantine eliminated learning, both psychophysically and cortically ( Figure 3 C), providing strong evidence of NMDA receptor involvement in training-independent sensory learning. Importantly, this finding implied that training-independent sensory learning is a plasticity-based process, which was debatable at that time.

As outlined above, LTP and LTD are activity-dependent changes in the strength of synaptic connections which are leading candidate mechanisms of neuronal plasticity []. Therefore, we explored the efficacy of in vitro stimulation protocols in driving perceptual changes by applying high-frequency and low-frequency stimulation ( Figure 3 B). High-frequency stimulation consisted of cutaneous pulse trains applied to the tip of the right index finger with a stimulation frequency of 20 Hz. Each train consisted of 20 single pulses of 20 Hz lasting one second with an inter-train interval of five seconds. Low-frequency stimulation was applied at 1 Hz with stimulus trains consisting of 1200 pulses ( Figure 3 B). We found that 20 minutes of high-frequency stimulation induced a lowering of tactile discrimination thresholds, whereas low-frequency stimulation resulted in an impaired discrimination performance. Most interestingly, 24 hours after high-frequency stimulation, we found that spatial two-point discrimination thresholds were still lower than the baseline values. In contrast, 24 hours after low-frequency stimulation, the discrimination thresholds had recovered to the baseline values []. These results indicate that brief stimulation protocols resembling those used in cellular LTP and LTD studies can induce meaningful and persistent alterations in tactile discrimination behaviour of humans.

To demonstrate the Hebbian nature of the co-activation protocol, the effects of co-activation were compared to those of a so-called ‘single-site stimulation’, where only a small ‘point-like’ skin area was stimulated. Stimulating the finger at a single site did not induce changes in discrimination performance or brain activity []. This indicates a lack of brain reorganization and suggests that it is unlikely that other tasks beyond discrimination might have benefitted from single-site stimulation. These results imply that a Hebbian ‘co-activation’ is crucial for the induction of plasticity effects and point to the requirement of spatial cooperative processes. Furthermore, the data emphasize that not all types of sensory stimulation can lead to perceptual changes, and that there are ‘simple’ forms of stimulation that remain ineffective in driving plasticity.

A similar result was obtained for changes in cortical excitability. Cellular studies have shown that increased excitability is a typical signature of effective LTP induction. In humans, so-called ‘paired-pulse stimulation’, the application of two stimuli in close succession, provides a reliable marker of excitability: the paired-pulse behaviour is characterized by a significant suppression of the second response at short inter-stimulus intervals. Paired-pulse suppression was reduced after co-activation, and the amount of suppression was positively correlated with the individual gain in performance []. Taken together, these data show that training-independent sensory learning results in selective reorganization in the primary somatosensory cortical areas. These observations also suggest the important idea that the effect size differences typically observed across individuals reflect true differences in individual brain reorganization.

The relation between learning-induced changes in behaviour and individual changes in brain organization has been studied using a combination of psychophysical tests and non-invasive imaging. Neuroimaging and electric source localization by multi-channel electroencephalography (EEG) showed that co-activation led to an increase in the size of the cortical representation specific to the co-activated finger [], which can be regarded as a recruitment of processing resources. The changes observed in cortical map representation were found to be linearly related to the degree of improvement in two-point discrimination thresholds. Accordingly, a large gain in spatial discrimination abilities was associated with large changes in cortical maps [].

(A) Schematic representation of a stimulation device placed on the top of an index finger. The red circles denote the different receptive fields that were stimulated in the area underneath the stimulation patch. (B) Depiction of LTP- and LTD-like stimulation protocols, together with their effects on tactile two-point discrimination threshold. Acuity thresholds are lowered after LTP-like stimulation, but increased after LTD-like stimulation. (C) Results of pharmacological manipulation using memantine (NMDA-R blocker) and amphetamine on tactile-discrimination performance, together with changes in the cortical representation of the stimulated finger in somatosensory cortex

In the ‘co-activation’ stimulation protocol, the fingertip is repeatedly stimulated, either cutaneously or electrically, for many minutes to hours in order to induce plasticity in the corresponding primary and secondary somatosensory cortices []. Co-activation closely follows the idea of Hebbian learning: synchronous neural activity is generated by simultaneous tactile ‘co-stimulation’ of a large number of receptive fields ( Figure 3 A). Because of the induced plasticity, tactile perception at the stimulated skin sites is altered. Spatial tactile discrimination, ‘tactile acuity’, is often assessed as a simple measure of changes in tactile perception abilities. In a typical co-activation experiment, two-point discrimination thresholds are lowered, indicating improved tactile acuity, which reaches baseline levels after 24 hours []. This co-activation-induced improvement does not transfer to fingers of the unstimulated hand, and there is no (or only weak) transfer to the neighbouring fingers of the stimulated hand.

Visual Modality

48 Frenkel M.Y.

Sawtell N.B.

Diogo A.C.

Yoon B.

Neve R.L.

Bear M.F. Instructive effect of visual experience in mouse visual cortex. 49 Sale A.

De Pasquale R.

Bonaccorsi J.

Pietra G.

Olivieri D.

Berardi N.

Maffei L. Visual perceptual learning induces long-term potentiation in the visual cortex. 50 Cooke S.F.

Bear M.F. Visual experience induces long-term potentiation in the primary visual cortex. 51 Teyler T.J.

Hamm J.P.

Clapp W.C.

Johnson B.W.

Corballis M.C.

Kirk I.J. Long-term potentiation of human visual evoked responses. 42 Clapp W.C.

Zaehle T.

Lutz K.

Marcar V.L.

Kirk I.J.

Hamm J.P.

Teyler T.J.

Corballis M.C.

Jancke L. Effects of long-term potentiation in the human visual cortex: A functional magnetic resonance imaging study. 52 Aberg K.C.

Herzog M.H. About similar characteristics of visual perceptual learning and LTP. In contrast to the numerous studies that have been done on training-independent sensory learning in the tactile domain, fewer studies have looked at training-independent sensory learning in the visual domain. Animal studies provided the first evidence that the visual cortex (V1) undergoes plastic changes following pure exposure: repeated presentations of grating stimuli with a single orientation resulted in a persistent enhancement of responses evoked by these stimuli []. Conversely, perceptual learning has been shown to induce LTP in the visual cortex of rats, and to enhance cortical excitability in humans []. A study on humans found that visual sensory stimulation with checkerboard patterns at 9 Hz for a few minutes resulted in changes in early processing in the visual cortex, as indicated by an amplitude enhancement of the N1 event-related potential (ERP) component of the visual evoked potential []. Similarly, a functional magnetic resonance imaging (fMRI) study found an increase in hemodynamic responses in the extrastriate visual cortex after brief periods of 9 Hz checkerboard stimulation []. While these data show that visual cortical processing is modifiable, direct evidence for the induction of perceptual changes by LTP-like protocols has been lacking. Interestingly, however, a recent paper [] suggested that perceptual learning has many features that are typical of LTP, such as the requirement of a minimal number of trials or the hindrance of learning by the interleaved presentation of more than one stimulus type.

11 Beste C.

Wascher E.

Güntürkün O.

Dinse H.R. Improvement and impairment of visually guided behavior through LTP- and LTD-like exposure-based visual learning. 53 Wascher E.

Beste C. Tuning perceptual competition. Beste et al. [] modified visual stimulation protocols that had been shown to be effective at the cellular level to modify visual perception in humans. In this study, we used a paradigm that resembles a change-detection task [], in which two bars that were either darker or brighter than the background were presented to subjects who had to report luminance changes was employed ( Figure 4 A). Four different types of change were possible in this task: on the left or right side of a fixation cross, changes could be made to either the luminance or the orientation of a single bar; both the luminance and orientation of one bar (luminance-orientation unilateral, LOU); or the luminance and orientation of the two bars (luminance-orientation bilateral, LOB). In the last condition, the occurrence of the change in orientation induced a highly salient apparent motion; the simultaneous change in luminance is much less salient and difficult to detect.

Figure 4 Training-independent sensory learning in the visual modality. Show full caption 11 Beste C.

Wascher E.

Güntürkün O.

Dinse H.R. Improvement and impairment of visually guided behavior through LTP- and LTD-like exposure-based visual learning. 15 Beste C.

Wascher E.

Dinse H.R.

Saft C. Faster perceptual learning through excitotoxic neurodegeneration. (A) Schematic overview of the task used to examine LTP- and LTD-like exposure-based perceptual learning in the visual domain. (B) Overview of the visual LTP- and LTD-like learning protocols, which can increase or decrease visual sensitivity, respectively. (C) Electrophysiological effects of LTP-like visual stimulation on attentional selection. Prior to stimulation, attention is allocated to the distracter (positive deflection), whereas after successful LTP-like learning, attention is allocated to the target (negative deflection). These processes occur in the extrastriate visual areas. Attentional reallocation processes mediated by areas located downwards from the ventral processing stream are not evident after LTP-like stimulation.

15 Beste C.

Wascher E.

Dinse H.R.

Saft C. Faster perceptual learning through excitotoxic neurodegeneration. 12 Cooke S.F.

Bear M.F. Stimulus-selective response plasticity in the visual cortex: an assay for the assessment of pathophysiology and treatment of cognitive impairment assocaited with psychiatric disorders. 48 Frenkel M.Y.

Sawtell N.B.

Diogo A.C.

Yoon B.

Neve R.L.

Bear M.F. Instructive effect of visual experience in mouse visual cortex. 50 Cooke S.F.

Bear M.F. Visual experience induces long-term potentiation in the primary visual cortex. 15 Beste C.

Wascher E.

Dinse H.R.

Saft C. Faster perceptual learning through excitotoxic neurodegeneration. 11 Beste C.

Wascher E.

Güntürkün O.

Dinse H.R. Improvement and impairment of visually guided behavior through LTP- and LTD-like exposure-based visual learning. 12 Cooke S.F.

Bear M.F. Stimulus-selective response plasticity in the visual cortex: an assay for the assessment of pathophysiology and treatment of cognitive impairment assocaited with psychiatric disorders. 48 Frenkel M.Y.

Sawtell N.B.

Diogo A.C.

Yoon B.

Neve R.L.

Bear M.F. Instructive effect of visual experience in mouse visual cortex. To increase the rate of detection of the luminance change, stimuli with varying luminance were used in an LTP-like protocol consisting of intermittent high-frequency stimulation ( Figure 4 B). In the re-test, participants exhibited an elevated detection performance that was of high spatial selectivity. Changes occurred only on the side of stimulation, and did not transfer to the non-stimulated hemifield. Even slight changes (∼3°) in the spatial position of stimuli presented during the exposure-based learning and testing within a visual hemifield reduced the amount of learning []. A similar pattern was observed in animal studies, where changes in the stimulus orientation of about 5° led to significantly lower effects of learning []. Furthermore, the degree of improvement depends on the duration of the LTP-like stimulation [], indicating a gradually developing plasticity. These effects were surprisingly stable for at least 10 days, depending on the saliency of the distracter. The exposure-based learning was less effective if the distracter was very salient []. Similar effects have been found in animal studies that examined stimulus-specific response potentiation [].

11 Beste C.

Wascher E.

Güntürkün O.

Dinse H.R. Improvement and impairment of visually guided behavior through LTP- and LTD-like exposure-based visual learning. Remarkably, the opposite effect — a decrease in the detectability of the luminance change — was found when protocols resembling an LTD-pace were used []. However, the detection of luminance in these change-detection tasks is complicated because of the concomitant change in orientation. Therefore, an alternative intervention strategy was required to increase the detectability of the luminance change indirectly, and this was achieved by decreasing the saliency of the orientation change via stimulation using an LTD-pace, in which stimuli are presented at a time pace that is used in electrical stimulation to induce long-term depression effects. The data showed that the modulatory effects of LTP- and LTD-pace stimulation also depend on the feature used during stimulation. Although the temporal structure of the stimulation and the neural mechanisms involved in these two types of stimulation are identical, the outcomes can be opposing. This suggests that contrasting learning mechanisms may yield an equivalent behavioural outcome.

15 Beste C.

Wascher E.

Dinse H.R.

Saft C. Faster perceptual learning through excitotoxic neurodegeneration. To sum up, the results we have described show the following regarding training-independent sensory-learning-induced changes in visual processing []. First, stimulations using an LTP- or an LTD-pace modulates perception bi-directionally. Second, the effectiveness and stability of training-independent sensory learning effects depend on the saliency of competing stimuli. Third, the degree of training-independent sensory learning changes increases gradually with the duration of the stimulation. Fourth, contrasting learning mechanisms (LTP-pace versus LTD-pace) may have an equivalent behavioural outcome. And fifth, the effects of visual training-independent sensory learning are spatially very selective.

54 Alvarez G.A.

Cavanagh P. Independent resources for attentional tracking in the left and right visual hemifields. 55 Cavanagh P.

Alvarez G.A. Tracking multiple targets with multifocal attention. 56 Desimone R.

Duncan J. Neural mechanisms of selective visual attention. 57 Knudsen E.I. Fundamental components of attention. 56 Desimone R.

Duncan J. Neural mechanisms of selective visual attention. The fact that changes in visual processing are confined to the spatial positions targeted during stimulation and are not generalized across the visual field may be taken as evidence that attentional processes themselves are not affected by exposure-based learning, as attentional modulation tends to generalize across visual fields []. To explain the effects observed in the change-detection task, we suggested that changes occur at a perceptual level, which, in turn, affects subsequent attentional selection processes. Many lines of evidence [] have indicated that attention emerges at several points between the input and the response, and that objects in the visual field compete for limited processing capacity and control of behaviour []. This competition is largely determined by the saliency of stimuli []. In the context of training-independent sensory learning effects, attentional processes may emerge as a function of the perceptual evaluation that is determined by stimulus attributes. Therefore, it is possible that training-independent sensory learning changes perceptual sensitivities, which subsequently affect attentional selection processes and lead to better behavioural performance in the task.

58 Eimer M.

Kiss M. Involuntary attentional capture is determined by task set: evidence from event-related brain potentials. 15 Beste C.

Wascher E.

Dinse H.R.

Saft C. Faster perceptual learning through excitotoxic neurodegeneration. 57 Knudsen E.I. Fundamental components of attention. 59 Poghosyan V.

Shibata T.

Ioanniddes A.A. Effects of attention and arousal on early responses in striate cortex. Neurophysiological data obtained using ERPs and reflecting attentional processes [] underscore this assumption. These ERPs can be used to trace the time course of the spatial allocation of attention towards the target and the distracter ( Figure 4 C). Before exposure-based learning, ERPs show that attention is initially allocated to the distracter and is only subsequently allocated to the target. After successful training-independent sensory learning, attention is directly allocated to the target stimulus and distraction no longer occurs. These changes induced by exposure-based learning were attributed to the modulation of the extrastriate visual areas [], which are core structures in the selection of visual stimuli []. These results reveal further key properties of training-independent sensory learning in the visual domain: attentional allocation processes may be altered on the basis of the changes in perceptual sensitivities; and training-independent sensory learning alters the perceptual sensitivity of neuronal networks that represent the stimulus in the extrastriate visual areas.