Repetition priming is the enhancement of a behavioural response when stimuli are given repeatedly. Accuracy or reaction time improvements might occur when the repeated stimuli are either the same or similar to the preceding stimuli. It has been demonstrated that these improvements are cumulative, so that as the number of repetitions increases, responses become progressively quicker, up to a maximum of approximately seven repetitions.
Repetition priming effects can occur without a person’s awareness of either the repetitions or the improvement in his/her response, so it is believed that it involves implicit memory processes that are distinct from explicit memory processes.
The study of repeated priming has been utilized to understand more about the mechanisms behind the behavioural impacts of rapid learning. In neuroimaging studies (e.g., fMRI), stimulus repetition paradigms are widely employed to infer the nature of neocortical representations in a range of cognitive domains.
Researchers are attempting to index regions and their processing biases along perceptual, conceptual, and response dimensions by using measures of repetition suppression, the putative neural correlate of repetition priming, and measuring changes in the neural response associated with changing the presented stimuli.
Models of Repetition Priming
Various models have been proposed to explain behavioural efficiencies gained from repeated exposure to the same or similar stimuli. The first is the fatigue model. In this model, neural response attenuation is thought to be caused by a reduction in the amplitude of a neuron’s firing.
It’s still unclear whether this reduction affects all neurons that responded to the initial stimulus or just a critical subset of those that responded maximally at first. However, evidence suggests that such a mechanism reduces redundant neural firing and improves
processing efficiencies in the early visual cortex.
Although repetition priming is most commonly associated with neural attenuation for repeated presentation of stimuli, increases in neural responses have been measured in a variety of experimental contexts. Examples include when performing mathematical calculations, when repeated stimuli are degraded, and in studies involving a backward masking paradigm.
The central idea of this repetition effects model is that information travels through the network faster when the current stimulus representation overlaps with a previous representation as a result of the more rapid onset of neural activation caused by repeated presentations.
Functional magnetic resonance imaging studies have attempted to measure these potential latency differences; however, the temporal resolution is not precise, and single-cell recordings typically do not reveal shortened latencies in response to repeated stimuli.
The sharpening model proposes that when a stimulus is repeated, neurons that contribute less to its representation cease firing. As a result, the representation is maintained by a sparser response over time, resulting in an adaptive reduction in metabolic requirements and enhanced efficiency in information transmission via the neuronal hierarchy.
This adaptation may be the result of lateral inhibition within representational levels in a competitive Hebbian learning system, in which strong connections strengthen and inhibit weaker connections. Primate studies of the inferotemporal cortex and single-cell recordings with extended training periods provide significant evidence for this.
This theory is based on the premise that synchronized activation can improve processing efficiency because downstream neurons are sensitive to both the firing rates and the timing of inputs.
Evidence of synchronization associated with repeated stimuli includes phase locking found between two regions of the cat visual cortex while measuring spike synchronization for trained compared with novel stimuli. Other evidence comes from suppressed firing and increased synchrony of spikes with repetition of odour puffs to locust’s antennae.
According to this idea, repeated priming occurs as a result of immediately linking the initial stimulus to the response while bypassing the intervening layers of computation. Several hypotheses have been advanced regarding the mechanism that mediates this direct binding, which has not yet been clarified.
According to one idea, there is a race between automatic activation of a previous stimulus-response channel and re-engagement of the “algorithmic” route. Another theory proposes an “action-trigger” mechanism in which repeated stimuli prompt the prior response via perceptual or intellectual links with the original stimulus.
Repetition priming is associated with a deceased fMRI signal in multiple brain regions for repeated primed vs. unprimed stimuli – this is sometimes referred to as “repetition suppression.” (RS) The phenomenon of repetition suppression is hypothesized to be influenced by processing overlaps between repeated items. It is widely thought to be the neural correlate of repeated priming.
However, the relationship between repetition priming and repetition suppression also poses a significant puzzle: how reductions in neural activity are able to facilitate improved behavioural performance.
According to studies examining the nature of representations across various levels of the visual processing hierarchy, multiple processing levels appear to be involved in repetition suppression. Suppression appears to be reliant on the stimuli being processed as well as the processing level at which the experimental manipulation is directed, with decreases in brain activity to repeated stimuli happening in regions involved in the initial processing of those aspects.
A meta-analysis of fMRI and PET studies was conducted by psychologist Hongkeun Kim in 2016 to clarify which brain regions exhibit reliable RS. The results consistently showed bilateral inferior frontal cortex and ventral occipitotemporal cortex RS effects.
Kim suggested that RS in the ventral occipitotemporal cortex reflects facilitated perceptual processing (because all of the experiments used visual stimuli). In contrast, repetition suppression in the inferior frontal cortex reflects a combination of facilitated conceptual processing, automatized stimulus-response mapping, less demand for top-down enhancement, and reductions in novelty.
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