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A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning
Abstract
A meta-analysis of non-human primates performing three different tasks (Object-Match, Category-Match, and Category-Saccade associations) revealed signatures of explicit and implicit learning. Performance improved equally following correct and error trials in the Match (explicit) tasks, but it improved more after correct trials in the Saccade (implicit) task, a signature of explicit versus implicit learning. Likewise, error-related negativity, a marker for error processing, was greater in the Match (explicit) tasks. All tasks showed an increase in alpha/beta (10-30 Hz) synchrony after correct choices. However, only the implicit task showed an increase in theta (3-7 Hz) synchrony after correct choices that decreased with learning. In contrast, in the explicit tasks, alpha/beta synchrony increased with learning and decreased thereafter. Our results suggest that explicit versus implicit learning engages different neural mechanisms that rely on different patterns of oscillatory synchrony.
... Theta (4-7 Hz) oscillations are associated with new knowledge formation and are considered a neuropsychological marker of learning (Rozengurt et al., 2016;Köster et al., 2019). Enhanced theta activity has been observed during implicit learning tasks (Loonis et al., 2017;Meissner et al., 2018). Successful modulation of learning benefits (RT reduction) was achieved by applying repetitive TMS on parietal theta power (Whybird et al., 2021). ...
... 0.193, h p 2 0.09; Fig. 7b). These results suggested that theta oscillation is associated with learning, which is in line with numerous previous studies (Rozengurt et al., 2016;Loonis et al., 2017;Meissner et al., 2018), and that its location shifts toward the frontal region with the transition. ...
... Similarly, analysis of sourcelevel MEG data from experiment 3 indicated a comparable effect at the superior frontal cortex. These results provide evidence supporting the critical involvement of the PFC in explicit learning by facilitating knowledge awareness, which aligns with previous research (Aizenstein et al., 2006;Loonis et al., 2017;Robertson and Pascual-Leone, 2003). Intriguingly, we also observed an elevated parietal theta power just before the emergence of awareness (pretransition session), suggesting engagement of parietal theta activity in the transition. ...
Unconscious acquisition of sequence structure from experienced events can lead to explicit awareness of the pattern through extended practice. Although the implicit-to-explicit transition has been extensively studied in humans using the serial reaction time (SRT) task, the subtle neural activity supporting this transition remains unclear. Here, we investigated whether frequency-specific neural signal transfer contributes to this transition. A total of 208 participants (107 females) learned a sequence pattern through a multi-session SRT task, allowing us to observe the transitions. Session-by-session measures of participants' awareness for sequence knowledge was conducted during the SRT task to identify the session when the transition occurred. By analyzing time-course RT data using switchpoint modeling, we identified an increase in learning benefit specifically at the transition session. Electro/magnetoencephalogram recordings revealed increased theta power in parietal (precuneus) regions one session before the transition (pre-transition) and a prefrontal (superior frontal gyrus, SFG) one at the transition session. Phase transfer entropy analysis confirmed that directional theta transfer from precuneus → SFG occurred at the pre-transition session and its strength positively predicted learning improvement at the subsequent transition session. Furthermore, repetitive transcranial magnetic stimulation modulated precuneus theta power and altered transfer strength from precuneus to SFG, resulting in changes in both transition rate and learning benefit at that specific point of transition. Our brain-stimulation evidence supports a role for parietal → prefrontal theta signal transfer in igniting conscious awareness of implicitly acquired knowledge.
Significance Statement
There exists a pervasive phenomenon wherein individuals unconsciously acquire sequence patterns from their environment, gradually becoming aware of the underlying regularities through repeated practice. While previous studies have established the robustness of this implicit-to-explicit transition in humans, the refined neural mechanisms facilitating conscious access to implicit knowledge remain poorly understood. Here, we demonstrate that prefrontal activity, known to be crucial for conscious awareness, is triggered by neural signal transfer originating from the posterior brain region, specifically the precuneus. By employing brain stimulation techniques, we establish a causal link between neural signal transfer and the occurrence of awareness. Our findings unveil a mechanism by which implicit knowledge becomes consciously accessible in human cognition.
... In all five experiment we manipulated explicit and implicit knowledge. With the discovery that amnesia patients were still able to learn new skills, without being able to report knowledge (Cohen & Squire, 1980), a distinction between explicit and implicit learning was made, where before learning was defined as a unitary process (Loonis et al., 2017). The distinction between explicit and implicit knowledge can also be described as "knowing that" and "knowing how". ...
... Furthermore, implicit learning improvements are driven by correct responses only, in contrast to the hypothesis testing in explicit learning where the corrections after a wrong response enable the formation of explicit knowledge. Amnesia patients benefit from errorless learning more than non-errorless learning protocols (Loonis et al., 2017;Maxwell et al., 2001;Roberts et al., 2018), characterizing implicit learning as a non-discerning type of learning. Implicit learning seems to function like a sponge, soaking up regularities in the environment uncritically. ...
... A methodological issue regarding explicit vs implicit knowledge experiments in general, is that while the systems and processes involved in explicit and implicit learning are separable, as evidenced by implicit learning remaining intact in amnesics and brain activity measurements (Cohen & Squire, 1980;Loonis et al., 2017), these systems might operate in parallel. Indeed, data ...
Predictability is increasingly recognized as an important principle in perception and motor learning. The pursuit of increased predictability seems to one of the main goals that the human system pursues. Therefore, providing predictability in one of the most challenging situations that humans face, namely multitasking, a promising line of research. In this thesis the impact of predictability was systematically investigated in five experiments. In the first four experiments predictability was achieved by implementing a repeating pattern in one task, or both tasks. Participants acquired knowledge of these patterns either explicitly or implicitly in several training sessions, under single-task or dual-task conditions. We tested whether this increased predictability helped dual-task performance after the training sessions. The results suggest that predictability is helpful for dual-task performance, although the benefits are confined to the predictable task itself. In a fifth experiment we focused on providing between task predictability, which led to a large performance improvement in both tasks, prompting the discussion about what constitutes a task, in the sense of when can two tasks be perceived as a single task comprising both, a theoretical problem we tried to tackle in one of the articles. Explanations for the findings, theoretical implications, methodological issues and suggestions for future research are given in the general discussion
... It is thought that RL, however, can occur in a purely associative way without the use of internal models of motor dynamics (Haith and Krakauer 2013). Furthermore, the P300 is typically localized to parietal regions, which are heavily implicated in visuomotor adaptation (Bledowski et al. 2004;Diedrichsen et al. 2005;Linden 2005;Tanaka et al. 2009). We tested whether the P300 is modulated by sensory error induced by VMR and whether P300 amplitude correlated to behavioral adaptation induced by sensory error feedback. ...
... It is possible that the P300 reflects a general aspect of feedback processing that is common to both sensorimotor and cognitive function. The P300 is typically localized to parietal regions, which are implicated in processing sensory error during adaptation to VMR (Bledowski et al. 2004;Diedrichsen et al. 2005;Linden 2005;Tanaka et al. 2009). Consistent with the P300 underlying sensory error processing, cerebellar damage impairs sensory error-based adaptation and results in P300 abnormalities (Mannarelli et al. 2015;Martin et al. 1996;Maschke et al. 2004;Paulus et al. 2004;Smith and Shadmehr 2005;Tachibana et al. 1995;Therrien et al. 2016). ...
... It is not clear whether this residual adaptation can be attributed to an implicit form of reward learning or whether it reflects use-dependent plasticity, but it suggests that implicit reward learning may occur for small changes in reach angle, such as those observed in the present study. Future work should determine whether the FRN and P300 are specifically related to strategic or explicit reward-based motor adaptation, especially considering evidence from sequence and cognitive learning domains that the FRN relates more closely to explicit processes (Loonis et al. 2017;Rüsseler et al. 2003). ...
At least two distinct processes have been identified by which motor commands are adapted according to movement-related feedback: reward based learning and sensory error based learning. In sensory error based learning, mappings between sensory targets and motor commands are recalibrated according to sensory error feedback. In reward based learning, motor commands are associated with subjective value, such that successful actions are reinforced. We designed two tasks to isolate reward and sensory error based motor adaptation, and we used electroencephalography in humans to identify and dissociate the neural correlates of reward and sensory error feedback processing. We designed a visuomotor rotation task to isolate sensory error based learning which was induced by altered visual feedback of hand position. In a reward learning task, we isolated reward based learning induced by binary reward feedback that was decoupled from the visual target. A fronto-central event related potential called the feedback related negativity (FRN) was elicited specifically by binary reward feedback but not sensory error feedback. A more posterior component called the P300 was evoked by feedback in both tasks. In the visuomotor rotation task, P300 amplitude was increased by sensory error induced by perturbed visual feedback, and was correlated with learning rate. In the reward learning task, P300 amplitude was increased by reward relative to non reward and by surprise regardless of feedback valence. We propose that during motor adaptation, the FRN specifically reflects a reward based learning signal while the P300 reflects feedback processing which is related to adaptation more generally.
... Therefore, we sought data from a recent study where we employed both 6 Hz and Sham tACS as comparisons [5]. This previous study had the same electrode locations (F3-F4), age group (ages [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35], and outcome measure in Neu-roRacer. In this study participants completed 16 NeuroRacer multitasking runs with a short break between runs 8 and 9. ...
... As such, frontal theta activity, and theta tACS by extension, may be important only during the acquisition of the mechanics required during the cognitive control tasks. However, once the task is learned (e.g., rules, motor mapping, etc.) frontal theta activity may play a less prominent role [25], resulting in limited utility of multi-day theta tACS as multitasking (and the associated game mechanics) becomes more natural to perform. This would not only explain why theta tACS did not continually improve performance in young adults (who are generally adept at learning new video games/technologies), but it would account for why older adults benefitted from multiple theta tACS sessionsbecause older adults are slower to learn new skills [26,27]. ...
The use of noninvasive transcranial electrical stimulation (tES) has rapidly increased over the past two decades. Yet, tES continues to be largely implemented in laboratory and rehabilitation settings, thereby limiting accessibility to the broader population. We have previously demonstrated that transcranial alternating current stimulation (tACS) in the theta (4-7 Hz) band improves cognitive control, such as multitasking, in younger adults following a single tACS session, as well as in older adults following three tACS sessions. Here, the goal was to extend our in-lab results by 1) assessing the feasibility for at-home tACS and 2) evaluating whether five tACS sessions may yield continuing improvements in multitasking ability in young adults. Participants (aged 18 – 34 years) received bilateral prefrontal tACS while engaged in an adaptive multitasking training over five consecutive days in their home settings. Participants were randomly assigned to receive either 20-minutes of theta or delta tACS during daily multitasking training. Prior to and on the day immediately following five days of tACS, we assessed performance on single task, multitask, and sustained attention ability with analyses of variance statistics. 92.1% of participants were able to self-administer tACS at home without researcher assistance. However, we observed that both theta and delta tACS groups exhibited improvements in both single and multitask performance. Compared to previously collected data, five days of theta tACS was comparable to one day of theta tACS. However, theta tACS has continued benefits in older, but not younger adults as evidenced by previous research. Both groups similarly improved in sustained attention. These results demonstrate that laboratory paradigms utilizing neurostimulation can be effectively deployed in a home environment without direct support from research personnel. Moreover, these results suggest that while theta tACS may facilitate multitasking improvements over one session, multiple sessions of theta tACS results in diminishing returns in young adults. Additional research will be required to confirm if delta activity plays an important role in multitasking ability.
... Our results indicate that subjects who were unable to learn the full rotation made smaller and less variable changes in response to errors and this was primarily driven by their sensitivity to the outcome of the previous trial. Learning from errors has been suggested to be a signature of explicit reinforcement learning, in contrast to learning from success in implicit learning (Loonis et al. 2017). Therefore, the finding that the difference between successful and unsuccessful subjects in the present experiments was in response to errors further supports the idea that it is the sensitivity of the explicit system that is important for this task. ...
... However, from the data presented here it is impossible to determine whether the corrections following errors are explicit in nature or due to implicit motor variability (He et al. 2016;Wu et al. 2014). In future, similar experiments investigating the presence of neural signatures of explicit learning in tasks such as this may be able to shed light on which process underlie trial-by-trial changes (Loonis et al. 2017). Interestingly, the pattern of reduced sensitivity to errors found for unsuccessful subjects in the present experiments was similar to that described for parkinsonian patients (Pekny et al. 2015). ...
Despite increasing interest in the role of reward in motor learning, the underlying mechanisms remain ill-defined. In particular, the contribution of explicit processes to reward-based motor learning is unclear. To address this, we examined subject's (n=30) ability to learn to compensate for a gradually introduced 25⁰ visuomotor rotation with only reward-based feedback (binary success/failure). Only two-thirds of subjects (n=20) were successful at the maximum angle. The remaining subjects initially followed the rotation but after a variable number of trials began to reach at an insufficiently large angle and subsequently returned to near baseline performance (n=10). Furthermore, those that were successful accomplished this largely via a large explicit component, evidenced by a reduction in reach angle when asked to remove any strategy they employed. However, both groups displayed a small degree of remaining retention even after the removal of this explicit component. All subjects made greater and more variable changes in reach angle following incorrect (unrewarded) trials. However, subjects who failed to learn showed decreased sensitivity to errors, even in the initial period in which they followed the rotation, a pattern previously found in Parkinsonian patients. In a second experiment, the addition of a secondary mental rotation task completely abolished learning (n=10), whilst a control group replicated the results of the first experiment (n=10). These results emphasize a pivotal role of explicit processes during reinforcement-based motor learning, and the susceptibility of this form of learning to disruption has important implications for its potential therapeutic benefits.
... episodic content) or implicit learning (i.e. outside of conscious awareness), given that both processes involve different brain systems and neural mechanisms [58]. ...
Background and Hypothesis
Abnormalities in the encoding of the space close to the body, named peripersonal space (PPS), is thought to play a crucial role in the disruption of the bodily self observed in schizophrenia (SCZ). Empirical evidence indicates a narrower extension of the PPS in SCZ compared to controls but preserved plasticity of the PPS. Computational studies suggest that increased excitation of sensory neurons could explain the smaller PPS observed in SCZ. However, it is unclear why SCZ patients preserve PPS plasticity and how such an excitation imbalance influences learning during the extension of the PPS boundaries.
Study Design
We hypothesise that Hebbian plasticity can account for PPS expansion after active tool use training, which occurs in spite of E/I imbalance and reduced synaptic density. Using simulations in a SCZ network model, we explored the effects of such impairments on PPS plasticity and fitted the model to behavioural data before and after a training routine.
Study Results
We found that increased excitation of sensory neurons does not impede the expansion of PPS and could explain a sharper demarcation of PPS boundaries after training. In addition, we found that a reduction in the learning rate is required to reproduce the post-training PPS representation of SCZ patients.
Conclusions
We discuss how the neural mechanisms behind the plasticity of PPS in the SCZ spectrum are related to the core pathophysiology of the disease.
... In human fear conditioning research, psychophysiological indices are extensively used thanks to their advantage of not being subject to self-report biases [12,18], since implicit and explicit learning rely on different neural pathways [19]. The most commonly used index of fear conditioning is the electrodermal activity, usually measured as skin conductance response (SCR), which is a phasic response to a stimulus and reflects enhanced autonomic arousal [20]. ...
In the last century, the paradigm of fear conditioning has greatly evolved in a variety of scientific fields. The techniques, protocols, and analysis methods now most used have undergone a progressive development, theoretical and technological, improving the quality of scientific productions. Fear-induced bradycardia is among these techniques and represents the temporary deceleration of heart beats in response to negative outcomes. However, it has often been used as a secondary measure to assess defensive responding to threat, along other more popular techniques. In this review, we aim at paving the road for its employment as an additional tool in fear conditioning experiments in humans. After an overview of the studies carried out throughout the last century, we describe more recent evidence up to the most contemporary research insights. Lastly, we provide some guidelines concerning the best practices to adopt in human fear conditioning studies which aim to investigate fear-induced bradycardia.
... Support for this theory has come not only from the effects of PFC disruption on learning 48-53 and from computational modelling 34 studies, but also from neural data. For example, a meta-analysis of multiple primate studies by Loonis et al. 74 has revealed distinct patterns of post-choice oscillatory synchrony within PFC during implicit versus explicit learning, such that Delta/Theta band synchrony increased after correct choices during implicit learning, but after incorrect choices during explicit learning. Moreover, their results also suggested that whereas explicit learning was associated with increased synchrony between PFC and hippocampus in the alpha and beta bands, implicit learning was associated with decreased synchrony between PFC and caudate in the theta band. ...
The ability of the brain to extract patterns from the environment and predict future events, known as statistical learning, has been proposed to interact in a competitive manner with prefrontal lobe-related networks and their characteristic cognitive or executive functions. However, it remains unclear whether these cognitive functions also possess a competitive relationship with implicit statistical learning across individuals and at the level of latent executive function components. In order to address this currently unknown aspect, we investigated, in two independent experiments (N Study1 = 186, N Study2 = 157), the relationship between implicit statistical learning, measured by the Alternating Serial Reaction Time task, and executive functions, measured by multiple neuropsychological tests. In both studies, a modest, but consistent negative correlation between implicit statistical learning and most executive function measures was observed. Factor analysis further revealed that a factor representing verbal fluency and complex working memory seemed to drive these negative correlations. Thus, the antagonistic relationship between implicit statistical learning and executive functions might specifically be mediated by the updating component of executive functions or/and long-term memory access.
... [45][46][47][48] There is additional evidence of the ability of pulsed, nearinfrared PBM to modulate neural oscillations, 49 suggesting the possibility of entrainment, which may be used to improve learning given that alterations in brainwaves have been correlated with explicit and implicit learning. 50 While some of these studies make use of individualized PBM devices applied to the head, there is also a marked influence of ambient lighting on cognitive health. Exposure to bright light in the morning improved symptoms of agitation in Alzheimer's disease or related dementia (ADRD) patients, 51-54 as well as motor restlessness. ...
Background
The relationship between the quality of the learning environment and student outcomes is receiving more serious attention from educational psychologists, neurologists, ophthalmologists, orthopedists, surgeons, oncologists, architects, ergonomists, nutritionists, and Michelin star chefs. There is a role for ergonomic office and school design to positively impact worker and student productivity, and one design attribute drawing attention is the indoor lit environment. In this review, we expand upon the role that light plays in education, as it has enabled millions of pupils to read at late hours, which were previously too dark. However, still unappreciated is the biological effects of artificial light on circadian rhythm and its subsequent impacts on health and learning outcomes.
Summary
This review describes the current state of light in the educational environment, its impact, and the effect of certain inexpensive and easy-to-implement adaptations to better support student growth, learning and development. We find that the current lighting environment for pupils is sub-optima based on biological mechanism and may be improved through cost effective interventions. These interventions can achieve greater biological harmonization and improve learner outcomes.
Key Message
The impact of the lighting environment in educational institutions on pupil biology has received minimal attention thus far. The current lighting environment in schools is not conducive to student health and educational performance. Cost-effective approaches can have an outsized impact on student health and educational attainment. We strongly recommend educational institutions take the lit environment into account when designing educational programs.
... Theta Waves are most frequent during sleep, although they are also prominent during deep meditation (Lomas et al., 2015). They are considered the portal to learning and memory and especially implicit learning (Loonis et al., 2017). In this state of theta brain waves, the senses are pulled away from the outside world and turn inward on information coming from the inside. ...
Brain–Computer Interfaces (BCIs) are specialized systems that allow users to control computer applications using their brain waves.With thearrival of consumer-grade electroencephalography (EEG) equipment, brain-controlled systems began to find fertile ground in mental training.One particular area that is gradually gainingattention is thatof mindfulnesstraining. In this paper, theresults of a literaturereview ofBCI-assistedmindfulness trainingusingBCI’sare presented.The specific aim is toreview the effects of BCIs embedded in mindfulness interventionsontrainingmetacognitive, emotional,and attentionregulation skills.Papers published the last10years were reviewed.The results showed that the useof BCIsprovidessubjects the unique opportunity to self-regulate mental and emotional functionsusing thefeedback derived from their own brain activity.Subjects were found toraise better awareness about the waysnon-conscious operations influence mental and emotional states.It was observedthat subjects by learning to dealwith the neurofeedback within immersive worlds or with the aidof mobile devices can better develop awarenessand self-regulation skills including inhibitionand flexibility.Learning environments havebeen undergoingrapid change driven by the evolution and availability of digital technologies.In that vein,BCIscombined with mobiles and immersive technologies could support mindfulness as an innovative practice for cognitive, emotional,and metacognitive development.This studyaimsto contribute to the debate about theuse of BCI-assisted mindfulness practices as proactive methods and trainingstrategies forvarious target groups such asstudents, teachers,and workers to achievewell-beingand peak performance.
... Support for this theory has come not only from the effects of PFC disruption on learning (Ambrus et al., 2020;Borragán et al., 2016;Filoteo et al., 2010;Smalle et al., 2017Smalle et al., , 2022 and from computational modelling (Lee et al., 2014) studies, but also from neural data. For example, a meta-analysis of multiple primate studies by Loonis et al. (2017) has revealed distinct patterns of post-choice oscillatory synchrony within PFC during implicit versus explicit learning, such that Delta/Theta band synchrony increased after correct choices during implicit learning, but after incorrect choices during explicit learning. Moreover, their results also suggested that whereas explicit learning was associated with increased synchrony between PFC and hippocampus in the alpha and beta bands, implicit learning was associated with decreased synchrony between PFC and caudate in the theta band. ...
The ability of the brain to extract patterns from the environment and predict future events, known as statistical learning, has been proposed to interact in a competitive manner with prefrontal lobe related networks and their characteristic cognitive or executive functions. However, it remains unclear whether these cognitive functions also show competitive relationship with implicit statistical learning across individuals and at the level of latent executive function components. In order to address this currently unknown aspect, we investigated, in two independent experiments (NStudy1 = 186, NStudy2 = 180), the relationship between implicit statistical learning, measured by the Alternating Serial Reaction Time task, and executive functions, measured by multiple neuropsychological tests. In both studies, a modest, but consistent negative correlation between implicit statistical learning and most executive function measures was observed. Factor analysis further revealed that a factor representing the latent updating component of executive functions seemed to drive these negative correlations. Thus, an antagonism between implicit statistical learning and executive functions might specifically be mediated by updating.
... significantly correlated with one another here, tap into different underlying mechanisms, as many others have suggested (48)(49)(50). Due to the current limited sample size and inconsistency with our previous findings, we are inclined to trust the result from our previous study with a much larger size. It would be important to replicate the positive association between implicit meat disgust and meat intake in larger samples, perhaps using other measures of implicit attitudes (such as affective priming) in addition to the IAT, before interpreting this effect. ...
Feelings of disgust toward meat have been researched for at least 30 years, but so far the causal relationship that may link meat disgust and meat consumption has remained elusive. Two possible pathways have been proposed in previous literature: the more common pathway seems to be that meat disgust is developed after a transition to vegetarianism, potentially via the process of moralization and recruitment of (moral) disgust. Other accounts suggest the existence of a second pathway in which disgust initiates the avoidance of meat and this can be explained by existing theories of disgust functioning as a pathogen avoidance mechanism and meat serving as a pathogen cue. However, the evidence base for either relationship remains thin and to our knowledge no research has examined whether temporary meat abstention can lead to increases in meat disgust, as the first pathway suggests. We measured meat disgust and meat intake in n = 40 meat eaters before and after attempting a meat-free diet for 1 month (while taking part in the annual vegan campaign Veganuary). Although most participants lapsed to eating meat during this period, we found that reductions in meat intake during the month were predictive of increases in meat disgust afterwards. This supports the view that meat disgust is expressed as a result of meat avoidance in meat eaters. Implications for theoretical understanding of the relationship between meat disgust and meat avoidance, as well as the development of disgust based interventions are discussed.
... (18) The theta rhythm is implicated in several activities, such as establishment of word pattern for speech recognition and microsaccadic eye movement synchronization, which are often observed in the context of attentive and exploratory behavior and in implicit learning, a largely unconscious non-hippocampus-dependent learning category. (19)(20)(21) Alpha waves are related to cognitive processing and self-regulation and are increased in situations associated with attention gains. (22,23) Beta oscillations are a strong predictor of perceptual and motor performance. ...
Objective:
To describe electrocorticographic, electromyographic and electrocardiographic profiles to report the electrophysiological effects of caffeine in Wistar rats.
Methods:
Male adult Wistar rats weighing 230g to 250g were used. Rats were allocated to one of two groups, as follows: Group 1, Control, intraperitoneal injection of 0.9% saline solution (n=27); and Group 2, treated with intraperitoneal injection of caffeine (50mg/kg; n=27). The rats were submitted to electrocorticographic, electromyographic and electrocardiographic assessment.
Results:
Brain oscillations (delta, theta, alpha, beta and gamma) in the frequency range up to 40Hz varied after caffeine administration to rats. Powers in delta and theta oscillations ranges were preponderant. The contractile force of the skeletal striated and cardiac muscles increased. Electrocardiogram analysis revealed shorter RR, QRS and QT intervals under the effect of caffeine.
Conclusion:
In the central nervous system, there was an increase in the delta, theta and alpha amplitude spectrum, which are related to memory encoding and enhanced learning. With regard to skeletal muscle, increased contraction of the gastrocnemius muscle was demonstrated, a clear indication of how caffeine can be used to enhance performance of some physical activities. Electrocardiographic changes observed after caffeine administration are primarily related to increased heart rate and energy consumption.
... Although some aspects of implicit and explicit memory formation are shared, implicit memory recruits distinct neural mechanisms. 9 Although direct evidence regarding the extent of implicit memory formation under anesthesia is limited, 10,11 previous studies 12, 13 suggest a preserved capacity to learn and recall information presented under anesthetics. These studies point to functioning amygdala circuits as the possible substrate. ...
Background
Anesthetics aim to prevent memory of unpleasant experiences. The amygdala and dorsal anterior cingulate cortex participate in forging emotional and valence-driven memory formation. It was hypothesized that this circuitry maintains its role under sedation.
Methods
Two nonhuman primates underwent aversive tone–odor conditioning under sedative states induced by ketamine or midazolam (1 to 8 and 0.1 to 0.8 mg/kg, respectively). The primary outcome was behavioral and neural evidence suggesting memory formation. This study simultaneously measured conditioned inspiratory changes and changes in firing rate of single neurons in the amygdala and the dorsal anterior cingulate cortex in response to an expected aversive olfactory stimulus appearing during acquisition and tested their retention after recovery.
Results
Aversive memory formation occurred in 26 of 59 sessions under anesthetics (16 of 29 and 10 of 30, 5 of 30 and 21 of 29 for midazolam and ketamine at low and high doses, respectively). Single-neuron responses in the amygdala and dorsal anterior cingulate cortex were positively correlated between acquisition and retention (amygdala, n = 101, r = 0.51, P < 0.001; dorsal anterior cingulate cortex, n = 121, r = 0.32, P < 0.001). Neural responses during acquisition under anesthetics were stronger in sessions exhibiting memory formation than those that did not (amygdala median response ratio, 0.52 versus 0.33, n = 101, P = 0.021; dorsal anterior cingulate cortex median response ratio, 0.48 versus 0.32, n = 121, P = 0.012). The change in firing rate of amygdala neurons during acquisition was correlated with the size of stimuli-conditioned inspiratory response during retention (n = 101, r = 0.22 P = 0.026). Thus, amygdala and dorsal anterior cingulate cortex responses during acquisition under anesthetics predicted retention. Respiratory unconditioned responses to the aversive odor anesthetics did not differ from saline controls.
Conclusions
These results suggest that the amygdala–dorsal anterior cingulate cortex circuit maintains its role in acquisition and maintenance of aversive memories in nonhuman primates under sedation with ketamine and midazolam and that the stimulus valence is sufficient to drive memory formation.
Editor’s Perspective
What We Already Know about This Topic
What This Article Tells Us That Is New
... However, it remains unclear how cross-area dynamics between M1 and M2 are coordinated and change with long-term skill learning. Previous work on cross-area interactions during motor learning has focused on macroscopic population activity, such as local field potentials [12][13][14] and wide-field calcium signals 4,15 . However, such measures of aggregate activity collapse signals from a heterogeneous population of neurons into a single signal, making it difficult to resolve potentially important multiplexed signals within that population [16][17][18] . ...
Mammalian cortex has both local and cross-area connections, suggesting vital roles for both local and cross-area neural population dynamics in cortically-dependent tasks, like movement learning. Prior studies of movement learning have focused on how single-area population dynamics change during short-term adaptation. It is unclear how cross-area dynamics contribute to movement learning, particularly long-term learning and skill acquisition. Using simultaneous recordings of rodent motor (M1) and premotor (M2) cortex and computational methods, we show how cross-area activity patterns evolve during reach-to-grasp learning in rats. The emergence of reach-related modulation in cross-area activity correlates with skill acquisition, and single-trial modulation in cross-area activity predicts reaction time and reach duration. Local M2 neural activity precedes local M1 activity, supporting top–down hierarchy between the regions. M2 inactivation preferentially affects cross-area dynamics and behavior, with minimal disruption of local M1 dynamics. Together, these results indicate that cross-area population dynamics are necessary for learned motor skills. Learning skilled movements requires evolution in neural population dynamics both within and across cortical regions. Here, the authors combine simultaneous recordings of motor and premotor cortex with computational methods to show that single-trial cross-area dynamics correlate with single-trial behavior performance and skill acquisition.
... A prominent theta oscillation has been observed previously in the OFC when rodents learn the significance of reward-predictive cues (van Wingerden et al., 2010), but the function of this oscillation is unknown. Oscillations may be important for organizing cognitive processes (Canolty et al., 2006(Canolty et al., , 2010Loonis et al., 2017;Lundqvist et al., 2018). Such oscillations could facilitate spike timing-dependent plasticity (Buzsá ki et al., 2013) and ensure synchronization of neuronal populations responsible for processing different aspects of task-relevant events (van Atteveldt et al., 2014). ...
Neuronal oscillations in the frontal cortex have been hypothesized to play a role in the organization of high-level cognition. Within the orbitofrontal cortex (OFC), there is a prominent oscillation in the theta frequency (4–8 Hz) during reward-guided behavior, but it is unclear whether this oscillation has causal significance. One methodological challenge is that it is difficult to manipulate theta without affecting other neural signals, such as single-neuron firing rates. A potential solution is to use closed-loop control to record theta in real time and use this signal to control the application of electrical microstimulation to the OFC. Using this method, we show that theta oscillations in the OFC are critically important for reward-guided learning and that they are driven by theta oscillations in the hippocampus (HPC). The ability to disrupt OFC computations via spatially localized and temporally precise stimulation could lead to novel treatment strategies for neuropsychiatric disorders involving OFC dysfunction.
... This was demonstrated by showing that an arithmetic distracting task during AO did not affect subsequent performance when compared to observation without such a distracting task (see also Vinter and Perruchet, 2002). Indeed, a recent meta-analysis of nonhuman primates (Loonis et al., 2017) showed that explicit vs. implicit learning engages different neural mechanisms that rely on different patterns of oscillatory synchrony. Also, from the behavioral point of view, it was suggested that the implicit motor learning of golf-putting could be beneficial for children with a low motor ability, in contrast to children with a high motor ability, who tend to benefit from explicit motor learning (Maxwell et al., 2017). ...
The effects of action observation (AO) on motor performance can be modulated by instruction. The effects of two top-down aspects of the instruction on motor performance have not been fully resolved: those related to attention to the observed task and the incorporation of motor imagery (MI) during AO. In addition, the immediate vs. 24-h retention test effects of those instruction’s aspects are yet to be elucidated. Forty-eight healthy subjects were randomly instructed to: (1) observe reaching movement (RM) sequences toward five lighted units with the intention of reproducing the same sequence as fast and as accurate as possible (Intentional + Attentional group; AO+At); (2) observe the RMs sequence with the intention of reproducing the same sequence as fast and as accurate as possible and simultaneously to the observation to imagine performing the RMs (Intentional + attentional + MI group; AO+At+MI); and (3) observe the RMs sequence (Passive AO group). Subjects’ performance was tested before and immediately after the AO and retested after 24 h. During each of the pretest, posttest, and retest, the subject performed RMs toward the units that were activated in the same order as the observed sequence. Occasionally, the sequence order was changed by beginning the sequence with a different activated unit. The outcome measures were: averaged response time of the RMs during the sequences, difference between the response time of the unexpected and expected RMs and percent of failures to reach the target within 1 s. The averaged response time and the difference between the response time of the unexpected and expected RMs were improved in all groups at posttest compared to pretest, regardless of instruction. Averaged response time was improved in the retest compared to the posttest only in the Passive AO group. The percent of failures across groups was higher in pretest compared to retest. Our findings suggest that manipulating top-down aspects of instruction by adding attention and MI to AO in an RM sequence task does not improve subsequent performance more than passive observation. Off-line learning of the sequence in the retention test was improved in comparison to posttest following passive observation only.
... Local field potentials recorded in animals support the idea that the PFC acts as an interface between memory systems. Loonis et al. (2017) demonstrated changes in communication between the PFC and each memory system according to whether primates performed explicit (declarative) vs. implicit (nondeclarative) tasks. Implicit learning was associated with a decrease in theta band synchrony between the PFC and striatum, while explicit learning was associated with an increase in the ratio of alpha/beta synchrony between the PFC and the hippocampus. ...
The striatum and medial temporal lobes (MTL) exhibit dissociable roles during learning. Whereas the striatum and its network of thalamic relays and cortical nodes are necessary for nondeclarative learning, the MTL and associated network are required for declarative learning. Several studies have suggested that these networks are functionally competitive during learning. Since these discoveries, however, evidence has accumulated that they can operate in a cooperative fashion. In this review, we discuss evidence for both competition and cooperation between these systems during learning, with the aim of reconciling these seemingly contradictory findings. Examples of cooperation between the striatum and MTL have been provided, especially during consolidation and generalization of knowledge, and do not appear to be precluded by differences in functional specialization. However, whether these systems cooperate or compete does seem to depend on the phase of learning and cognitive or motor aspects of the task. The involvement of other regions, such as midbrain dopaminergic nuclei and the prefrontal cortex, may promote and mediate cooperation between the striatum and the MTL during learning. Building on this body of research, we propose a model for striatum-MTL interactions in learning and memory and attempt to predict, in general terms, when cooperation or competition will occur.
... How can these two views be reconciled? In reward-based motor learning tasks, it is observed that participants begin to reflect upon task structure and develop strategies upon encountering negative outcomes (Maxwell et al., 2001;Leow et al., 2016;Loonis et al., 2017), which occurs nearly immediately in the Preserve task after the introduction of binary feedback, due to a lack of generalization of cerebellar memory . In contrast, in the Acquire task, participants experience an early learning phase with mainly rewarding outcomes, possibly suppressing development of explicit control and allowing for this early window of implicit reward-based learning. ...
The addition of rewarding feedback to motor learning tasks has been shown to increase the retention of learning, spurring interest in its possible utility for rehabilitation. However, motor tasks employing rewarding feedback have repeatedly been shown to lead to great inter-individual variability in performance. Understanding the causes of such variability is vital for maximising the potential benefits of reward-based motor learning. Thus, using a large human cohort of both sexes (n=241), we examined whether spatial (SWM), verbal (VWM) and mental rotation (RWM) working memory capacity and dopamine-related genetic profiles were associated with performance in two reward-based motor tasks. The first task assessed participant's ability to follow a slowly shifting reward region based on hit/miss (binary) feedback. The second task investigated participant's capacity to preserve performance with binary feedback after adapting to the rotation with full visual feedback. Our results demonstrate that higher SWM is associated with greater success and an enhanced capacity to reproduce a successful motor action, measured as change in reach angle following reward. In contrast, higher RWM was predictive of an increased propensity to express an explicit strategy when required to make large reach angle adjustments. Therefore, SWM and RWM were reliable but dissociable predictors of success during reward-based motor learning. Change in reach direction following failure was also a strong predictor of success rate, although we observed no consistent relationship with working memory. Surprisingly, no dopamine-related genotypes predicted performance. Therefore, working memory capacity plays a pivotal role in determining individual ability in reward-based motor learning.SIGNIFICANCE STATEMENTReward-based motor learning tasks have repeatedly been shown to lead to idiosyncratic behaviours that cause varying degrees of task success. Yet, the factors determining an individual's capacity to use reward-based feedback are unclear. Here, we assessed a wide range of possible candidate predictors, and demonstrate that domain-specific working memory plays an essential role in determining individual capacity to use reward-based feedback. Surprisingly, genetic variations in dopamine availability were not found to play a role. This is in stark contrast with seminal work in the reinforcement and decision-making literature, which show strong and replicated effects of the same dopaminergic genes in decision-making. Therefore, our results provide novel insights into reward-based motor learning, highlighting a key role for domain-specific working memory capacity.
Objectives
This study examined how varying angular perturbations in a visuomotor adaptation task (VMAT) influence implicit and explicit motor learning. The goal was to assess whether implicit adaptation can compensate for limitations in explicit learning, particularly in the context of neurological rehabilitation. The study was designed to map the implicit and explicit learning processes in response to a specific perturbation angle in a VMAT using mean directional errors and adaptation as outcome variables.
Materials and Methods
Participants performed reaching tasks under visuomotor rotations of different angles (30°, 45° and 60°), presented in block sequences. Performance was measured using mean directional errors and adaptation levels, reaction time (RT) and movement time (MT). The design allowed for the distinction between implicit and explicit learning based on changes in performance across blocks.
Results
As expected deterioration in performance was observed (as indicated by mean directional errors) on exposure to altered perturbation during each block. Participants struggled to adapt for smaller angle (the RT and MT failed to improve across block), as they used sensory feedback rather than relying on implicit strategy. Partial adaptation was observed until block 2 for sequences with smaller angles presented together. Small angles (30° and 45°) showed no improvement, indicating that magnitude of movement is critical for precise motor control.
Conclusion
This approach is especially important for tasks that require explicit knowledge of subsequent actions. The study highlights the importance of visual representations of hand position in motor learning, and its findings could be applied to specialized rehabilitation training.
In ephaptic coupling, physically adjacent neurons influence one another’s activity via the electric fields they generate. To date, the molecular mechanisms that mediate and modulate ephaptic coupling’s effects remain poorly understood. Here, we show that the hyperpolarization-activated cyclic nucleotide–gated (HCN) channel lateralizes the potentially mutual ephaptic inhibition between Drosophila gustatory receptor neurons (GRNs). While sweet-sensing GRNs (sGRNs) engage in ephaptic suppression of the adjacent bitter-sensing GRNs (bGRNs), HCN expression in sGRNs enables them to resist ephaptic suppression from the bGRNs. This one-sided ephaptic inhibition confers sweetness dominance, facilitating ingestion of bitter-laced sweets. The role of fly HCN in this process can be replaced by human HCN2. Furthermore, unlike the mechanism in olfaction, gustatory ephaptic inhibition is independent of sensillum potential changes, suggesting that the compartmentalized arrangement of neighboring GRNs is dispensable for gustatory ephaptic inhibition. These findings indicate a role for the gating of ephaptic coding to ensure the intake of the essential nutrient despite bitter contaminants present in the feeding niche of Drosophila , and propose that studies in Drosophila gustation could reveal ephaptic principles conserved across diverse animals.
The belief that we can exert an influence in our environment is dependent on distinct components of perceived control. Here, we investigate the neural representations that differentially code for self-efficacy (belief in successfully executing a behavior) and response-efficacy (belief that the behavior leads to an expected outcome) and how such signals may be integrated to inform decision-making. Participants provided confidence ratings related to executing a behavior (self-efficacy), and the potential for a rewarding outcome (response-efficacy). Computational modeling was used to measure the subjective weight of self-efficacy and response-efficacy while making decisions and to examine the neural mechanisms of perceived control computation. While participants factored in both self-efficacy and response-efficacy during decision-making, we observed that integration of these two components was dependent on neural responses within the vmPFC, OFC and striatum. Further, the dlPFC was observed to assign importance to self-efficacy and response-efficacy in specific trials, while dACC computed the trade-off between both components, taking into account individual differences. These findings highlight the contributions of perceived control components in decision-making, and identify key neural pathways involved in computing perceived control.
Introduction. The article evaluates contemporary research on psycholinguistics and neurolinguistics to find answers related to why child first language (L1) acquisition relies on different processing methods compared to adult second language (L2) acquisition, and why an L2 can be complex for adults to learn. This paper is basically a critical appraisal of language acquisition (LA) research proposing new venues to explore. Aims. The primary goals of this article are to emphasize the need for treating the brain as a testable scientific hypothesis, rather than merely a philosophical theory and to illustrate the need to integrate L2, brain, mind and the learner at every moment to account for LA. Method and Results. To achieve these intriguing goals, previous research on psycholinguistics and neurolinguistics is critically reviewed. The review has shown that that the brain in SLA research has been treated simply as a philosophical theory. This, in my view, has serious impacts on the progress and development of the field in two ways: It causes the research to be held back by assumptions that have hardened into dogmas and act against open-minded thinking. It leads researchers to depend solely on learners’ performances (the actual use of language) to describe and explain the nature of the linguistic systems that L2 learners develop (competence) and to explain how an L2 is acquired. However, we all know that performance is not on all occasions a perfect reflection of competence (cf. Chomsky, 1965, 1988) These two points emphasize the need for treating the brain as a testable scientific hypothesis rather than merely a philosophical theory and exemplify the necessity of continuously integrating second language (L2), brain, mind, and the learner at every moment to explain both why learning occurs and why it fails to occur. Conclusions. The paper offers a critical appraisal of previous research into psycholinguistics and neurolinguistics. It argues that the brain in second language acquisition (SLA/L2A) research has been treated merely as a philosophical theory for a long time, resulting in findings that lack actual neurolinguistic analysis. The paper suggests that theoretical explanations for why children acquire L1 faster and more easily than adults acquiring L2 align with recent testing of the brain, revealing differences in brain activity waves between early and middle childhood compared to adulthood. This indicates distinctions in language acquisition between children and adults in terms of brain wave activity, size of grey matter, and other factors.
Non-invasive brain stimulations have drawn attention in remediating memory decline in older adults. However, it remains unclear regarding the cognitive and neural mechanisms underpinning the neurostimulation effects on memory rehabilitation. We evaluated the intervention effects of 2-weeks of neurostimulations (high-definition transcranial direct current stimulation, HD-tDCS, and electroacupuncture, EA versus controls, CN) on brain activities and functional connectivity during a working memory task in normally cognitive older adults (age 60+, n = 60). Results showed that HD-tDCS and EA significantly improved the cognitive performance, potentiated the brain activities of overlapping neural substrates (i.e. hippocampus, dlPFC, and lingual gyrus) associated with explicit and implicit memory, and modulated the nodal topological properties and brain modular interactions manifesting as increased intramodular connection of the limbic-system dominated network, decreased intramodular connection of default-mode-like network, as well as stronger intermodular connection between frontal-dominated network and limbic-system–dominated network. Predictive model further identified the neuro-behavioral association between modular connections and working memory. This preliminary study provides evidence that noninvasive neurostimulations can improve older adults’ working memory through potentiating the brain activity of working memory-related areas and mediating the modular interactions of related brain networks. These findings have important implication for remediating older adults’ working memory and cognitive declines.
The international organizations of education have already pointed out that the way students learn, what they learn, and the skills needed, will be radically transformed in the coming years. Smart technologies are ready to come into play, changing the conditions of learning, providing opportunities for transformative learning experiences, and promising more conscious, self-directed and self-motivated learning. Meta-learning refers to a set of mental meta-processes by which learners consciously create and manage personal models of learning. Meta-learning entails a cluster of meta-skills that are progressively and hierarchically transformed, ensuring the transition to the highest levels of understanding termed meta-comprehension. The current article aims to investigate the concept of meta-learning and describe the meta-levels of learning through the lens of metacognition. In addition, the potential of smart technologies to provide fertile ground for the implementation of meta-learning training strategies is examined. The results of this article provide a new meta-learning theoretical framework supported by smart devices capable of supporting future meta-learners or, more accurately, meta-thinkers, to transcend the usual states of knowing and move to the next meta-levels of human intelligence.
Categories help us make sense of sensory input. A new study has directly compared category-related brain signals between human infants and adults, discovering delayed and temporally highly compressed processing in infants.
Feedback on success or failure is critical to increase rewards through behavioral adaptation or learning of dependencies from trial and error. Learning from reward feedback is thereby treated as embedded in a reinforcement learning framework. Due to temporal discounting of reward, learning in this framework is suspected to be vulnerable to feedback delay. Together, investigations of reinforcement learning in learned decision making tasks show that performance and learning impairments due to feedback delay vary as a function of task type. Performance in tasks that require implicit processing is affected by the delayed availability of feedback compared to tasks that can be accomplished with explicit processing. At the same time, the feedback related negativity, an event related potential component in the electroencephalogram that is associated with feedback processing, is affected by feedback delay similarly independent of task type. With the idea of fully implicit or explicit processing as opposite endpoints of a continuum of reciprocal shares of the implicit and explicit processing systems with feedback delay as the determinant of where on this continuum processing can be located, a common explanatory approach of both, behavioral and electrophysiological findings, is suggested.
Implicit Learning (IL) involves the fundamental problem of human potential development, and it has been a hot and difficult topic for many years. Traditional artificial neural networks can simulate IL, but there are some shortcomings. A few years ago, people used a morphological neural network (MNN) to simulate IL, but the support in theory and practice is weak. The contribution of this study is threefold. Firstly, based on the theory of unified framework of morphological associative memories (UFMAM), this paper makes a deep exploration for simulating IL by MNNs. Since both MNN and UFMAM are based on strict mathematical morphology, the research is established on a solid theoretical basis. Secondly, three experiments were designed, and the results were analyzed and discussed according to the theory of UFMAM. Thus, the depth and breadth of this research of IL were further expanded, new simulation methods and research examples were provided, and the MNN model of IL was established. Thirdly, it provides an example for the coordinated development of artificial neural networks, artificial intelligence, cognitive psychology, neural science and brain science. The research shows that the IL model based on MNN is superior to the traditional IL model in automation, comprehension, abstraction and anti-interference. Therefore, it will play an important role in the future study of IL and bring new inspiration to reveal the neural mechanism of IL. There is an inseparable relationship between MNN and IL, i.e. the former provides new research tools and means for the latter, while the latter provides psychological and neuroscientific supports for the former, which will make both of them have a more solid scientific foundation. It is reasonable to believe that computer simulation of IL and other cognitive phenomena will have an important impact on promoting the coordinated development of multidisciplinary.
In this paper, a morphological neural network (MNN) cognitive tree model related to multi disciplines is proposed. The model has four layers: soil layer, primary layer, growth layer and presentation layer. Through the study of MNN at different levels, the cognitive function and mechanism of MNN are profoundly revealed, and the theoretical framework of MNN cognition is established. This paper can be seen as an example of multi-disciplinary crossover and fusion research, which not only helps to improve the understanding of MNN itself, but also brings some inspirations to promote the interdisciplinary research and coordinated development of computer science, artificial intelligence, neurobiology, cognitive psychology and so on.
A common view of learning in infancy emphasizes the role of incidental sensory experiences from which increasingly abstract statistical regularities are extracted. In this view, infant brains initially support basic sensory and motor functions, followed by maturation of higher-level association cortex. Here, we critique this view and posit that, by contrast and more like adults, infants are active, endogenously motivated learners who structure their own learning through flexible selection of attentional targets and active interventions on their environment. We further argue that the infant brain, and particularly the prefrontal cortex (PFC), is well equipped to support these learning behaviors. We review recent progress in characterizing the function of the infant PFC, which suggests that, as in adults, the PFC is functionally specialized and highly connected. Together, we present an integrative account of infant minds and brains, in which the infant PFC represents multiple intrinsic motivations, which are leveraged for active learning.
Expected final online publication date for the Annual Review of Developmental Psychology, Volume 2 is December 15, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Les populations d’enfants nés grands prématurés représentent 7% des naissances, soit 15 millions de bébés par an dont 40 % vont présenter des troubles neurodéveloppementaux. Les échecs scolaires sont surreprésentés par rapport à des enfants nés à terme et la lecture est alors constamment atteinte. Nous étudions, au sein d’un travail longitudinal en trois parties, leur langage oral puis leur lecture par les potentiels évoqués. La lecture s’acquiert sur des compétences langagières et visuo-attentionnelles. Nous avons émis l’hypothèse qu’ils présenteraient des troubles moteurs à minima, qui selon la théorie motrice de la perception de la parole, gêneraient le développement de la phonologie. Nous avons, dans une première partie, au sein d’un PHRC national, inclus des enfants nés grands prématurés de 3 ans pour caractériser et stimuler leur langage oral. Nous les avons randomisés en un groupe rééduqué (n=87) et un bras groupe non rééduqué (n= 78) (LAMOPRESCO 1). Les résultats ont montré l’efficacité de la stimulation courte et protocolisée sur des aspects sensorimoteurs du langage à 4 ans. Les enfants rééduqués ont une meilleure progression de leur score en phonologie (p=0.07), et des scores significativement améliorés en lexique de réception (p=0.02) et de production (p<0.01), et en compréhension (p<0.01). Les scores de phonologie étaient corrélés à des scores moteurs, motricité fine et de latéralité (p=0.019). Nous avons développé une méthodologie de PEV en lecture, avec des stimuli mots simples et contrastés dans l’hypothèse de distinguer la voie phonologique motrice de la voie visuelle. Les résultats en Décision Lexicale et en Oddball, de notre population normative adulte (n=19) et enfants normo lecteurs de 12 ans (n=19), questionnent l’onde N170. La population d’enfants appariés dyslexiques (n=16) enregistrée a permis de confirmer les fluctuations maturationnelles de l’onde N170 et de sa co-construction avec l’onde P100 attentionnelle. Le couple P1N1 semble être un marqueur neuro développemental précoce avant l’automatisation de la N170. Le décours temporel positif de P1N1 est corrélé (p=-0.51) pour l’ensemble des populations (n=48) de normo lecteurs et de dyslexiques à notre paramètre de leximétrie (VL). Au décours de cette deuxième partie, la N170, apparait bien être la spécialisation et l’automatisation de la lecture experte, mais le couple P1N1 nous renseigne sur sa construction neurodéveloppementale par le biais d’un probable effet top down maturationnel sur la P100. La position de la N170, est positive chez 56% des enfants nés grands prématurés appariés (n=19) alors qu’on la retrouve chez 39% des enfants dyslexiques. En Oddball, la latence de la P300 mots cibles est corrélée à la leximétrie VL (r=-0.39) dans toutes nos populations étudiées. Pour la troisième partie qui est l’enregistrement par les PEVc de nos enfants de la première partie, maintenant âgés de 8 ans, nous avons simplifié nos stimuli mots. Nous avons enregistré de nouvelles populations normatives : adultes normo lecteurs (n=26), enfants appariés de 8 ans normo lecteurs (n=18) et enfants dyslexiques (n=11). Ils se différencient tous, par les paramètres hétérogènes de la N170. Dans le test de lecture en une minute (LUM), les enfants dyslexiques ont de moindres performances que les enfants nés prématurés (p=.01), eux même différents des normo lecteurs. En DL, le taux de bonnes réponses et le temps de réponse différencient les enfants nés prématurés des enfants dyslexiques (p=.01). En Oddball, les enfants nés grands prématurés rééduqués (n=8) se distinguent des enfants nés grands prématurés non rééduqués (n=9) sur le plan comportemental par de meilleurs TBR et des TR plus longs (p=.01). Les enfants non rééduqués ont une absence d’effet OB. Nous démontrons l’effet d’une rééducation à 4 ans en langage oral à court terme qui modifie les stratégies de lecture à 8 ans. Prématurés. Langage Oral . Pev en lecture . Dyslexie. Rééducation.
Losing a point in tennis could result from poor shot selection or faulty stroke execution. To explore how the brain responds to these different types of errors, we examined feedback-locked EEG activity while participants completed a modified version of a standard three-armed bandit probabilistic reward task. Our task framed unrewarded outcomes as either the result of errors of selection or errors of execution. We examined whether amplitude of the medial frontal negativity (the Feedback-Related Negativity/Reward Positivity; FRN/RewP) was sensitive to the different forms of error attribution. Consistent with previous reports, selection errors elicited a large FRN/RewP relative to rewards and amplitude of this signal correlated behavioral adjustment following these errors. A different pattern was observed in response to execution errors. These outcomes produced a larger FRN/RewP, a frontal attenuation in activity preceding this component, and a subsequent enhanced error positivity in parietal sites. Notably, the only correlations with behavioral adjustment were with the early frontal attenuation and amplitude of the parietal signal; FRN/RewP differences between execution errors and rewarded trials did not correlate with subsequent changes in behavior. Our findings highlight distinct neural correlates of selection and execution error processing, providing insight into how the brain responds to the different classes of error that determine future action.
Primates use saccades to gather information about objects and their relative spatial arrangement, a process essential for visual perception and memory. It has been proposed that signals linked to saccades reset the phase of local field potential (LFP) oscillations in the hippocampus, providing a temporal window for visual signals to activate neurons in this region and influence memory formation. We investigated this issue by measuring hippocampal LFPs and spikes in two macaques performing different tasks with unconstrained eye movements. We found that LFP phase clustering (PC) in the alpha/beta (8–16 Hz) frequencies followed foveation onsets, while PC in frequencies lower than 8 Hz followed spontaneous saccades, even on a homogeneous background. Saccades to a solid grey background were not followed by increases in local neuronal firing, whereas saccades toward appearing visual stimuli were. Finally, saccade parameters correlated with LFPs phase and amplitude: saccade direction correlated with delta (≤4 Hz) phase, and saccade amplitude with theta (4–8 Hz) power. Our results suggest that signals linked to saccades reach the hippocampus, producing synchronization of delta/theta LFPs without a general activation of local neurons. Moreover, some visual inputs co‐occurring with saccades produce LFP synchronization in the alpha/beta bands and elevated neuronal firing. Our findings support the hypothesis that saccade‐related signals enact sensory input‐dependent plasticity and therefore memory formation in the primate hippocampus.
Associative learning requires mapping between complex stimuli and behavioural responses. When multiple stimuli are involved, conditional associative learning is a gradual process with learning based on trial and error. It is established that a distributed network of regions track associative learning, however the role of neural oscillations in human learning remains less clear. Here we used scalp EEG to test how neural oscillations change during learning of arbitrary visuo-motor associations. Participants learned to associative 48 different abstract shapes to one of four button responses through trial and error over repetitions of the shapes. To quantify how well the associations were learned for each trial, we used a state-space computational model of learning that provided a probability of each trial being correct given past performance for that stimulus, that we take as a measure of the strength of the association. We used linear modelling to relate single-trial neural oscillations to single-trial measures of association strength. We found frontal midline theta oscillations during the delay period tracked learning, where theta activity was strongest during the early stages of learning and declined as the associations were formed. Further, posterior alpha and low-beta oscillations in the cue period showed strong desynchronised activity early in learning, while stronger alpha activity during the delay period was seen as associations became well learned. Moreover, the magnitude of these effects during early learning, before the associations were learned, related to improvements in memory seen on the next presentation of the stimulus. The current study provides clear evidence that frontal theta and posterior alpha/beta oscillations play a key role during associative memory formation.
The frontal eye fields (FEFs) and the anterior cingulate cortex (ACC) are commonly coactivated for cognitive saccade tasks, but whether this joined activation indexes coordinated activity underlying successful guidance of sensorimotor mapping is unknown. Here we test whether ACC and FEF circuits coordinate through phase synchronization of local field potential and neural spiking activity in macaque monkeys performing memory-guided and pro- and anti-saccades. We find that FEF and ACC showed prominent synchronization at a 3–9 Hz theta and a 12–30 Hz beta frequency band during the delay and preparation periods with a strong Granger-causal influence from ACC to FEF. The strength of theta- and beta-band coherence between ACC and FEF but not variations in power predict correct task performance. Taken together, the results support a role of ACC in cognitive control of frontoparietal networks and suggest that narrow-band theta and to some extent beta rhythmic activity indexes the coordination of relevant information during periods of enhanced control demands.
The prototype distortion task demonstrates that it is possible to learn about a category of physically similar stimuli through mere observation. However, there have been few attempts to test whether different encoding conditions affect learning in this task. This study compared prototypicality gradients produced under incidental learning conditions in which participants performed a visual search task, with those produced under intentional learning conditions in which participants were required to memorize the stimuli. Experiment 1 showed that similar prototypicality gradients could be obtained for category endorsement and familiarity ratings, but also found (weaker) prototypicality gradients in the absence of exposure. In Experiments 2 and 3, memorization was found to strengthen prototypicality gradients in familiarity ratings in comparison to visual search, but there were no group differences in participants' ability to discriminate between novel and presented exemplars. Although the Search groups in Experiments 2 and 3 produced prototypicality gradients, they were no different in magnitude to those produced in the absence of stimulus exposure in Experiment 1, suggesting that incidental learning during visual search was not conducive to producing prototypicality gradients. This study suggests that learning in the prototype distortion task is not implicit in the sense of resulting automatically from exposure, is affected by the nature of encoding, and should be considered in light of potential learning-at-test effects.
The idea that there are multiple learning systems has become increasingly influential in recent years, with many studies providing evidence that there is both a quick, similarity-based or feature-based system and a more effortful rule-based system. A smaller number of imaging studies have also examined whether neurally dissociable learning systems are detectable. We further investigate this by employing for the first time in an imaging study a combined positive and negative patterning procedure originally developed by Shanks and Darby [Shanks, D. R., & Darby, R. J. Feature- and rule-based generalization in human associative learning. Journal of Experimental Psychology: Animal Behavior Processes, 24, 405–415, 1998]. Unlike previous related studies employing other procedures, rule generalization in the Shanks–Darby task is beyond any simple non-rule-based (e.g., associative) account. We found that rule- and similarity-based generalization evoked common activation in diverse regions including the pFC and the bilateral parietal and occipital lobes indicating that both strategies likely share a range of common processes. No differences between strategies were identified in whole-brain comparisons, but exploratory analyses indicated that rule-based generalization led to greater activation in the right middle frontal cortex than similarity-based generalization. Conversely, the similarity group activated the anterior medial frontal lobe and right inferior parietal lobes more than the rule group did. The implications of these results are discussed.
The aim of this study was to explore whether errorless learning leads to better outcomes than errorful learning in people with amnestic mild cognitive impairment (MCI), and to examine whether accuracy in error recognition relates to any observed benefit of errorless over errorful learning. Nineteen participants with a clinical diagnosis of amnestic MCI were recruited. A word-list learning task was used and learning was assessed by free recall, cued recall and recognition tasks. Errorless learning was significantly superior to errorful learning for both free recall and cued recall. The benefits of errorless learning were less marked in participants with better error recognition ability. Errorless learning methods are likely to prove more effective than errorful methods for those people with MCI whose ability to monitor and detect their own errors is impaired.
Objective:
Generalization is the application of existing knowledge to novel situations. Questions remain about the precise role of the hippocampus in this facet of learning, but a connectionist model by Gluck and Myers (1993) predicts that generalization should be enhanced following hippocampal damage.
Method:
In a two-category learning task, a group of amnesic patients (n = 9) learned the training items to a similar level of accuracy as matched controls (n = 9). Both groups then classified new items at various levels of distortion.
Results:
The amnesic group showed significantly more accurate generalization to high-distortion novel items, a difference also present compared to a larger group of unmatched controls (n = 33).
Conclusions:
The model prediction of a broadening of generalization gradients in amnesia, at least for items near category boundaries, was supported by the results. Our study shows for the first time that amnesia can sometimes improve generalization. (PsycINFO Database Record
The influential competition between verbal and implicit systems (COVIS) model proposes that category learning is driven by two competing neural systems-an explicit, verbal, system, and a procedural-based, implicit, system. In the current fMRI study, participants learned either a conjunctive, rule-based (RB), category structure that is believed to engage the explicit system, or an information-integration category structure that is thought to preferentially recruit the implicit system. The RB and information-integration category structures were matched for participant error rate, the number of relevant stimulus dimensions, and category separation. Under these conditions, considerable overlap in brain activation, including the prefrontal cortex, basal ganglia, and the hippocampus, was found between the RB and information-integration category structures. Contrary to the predictions of COVIS, the medial temporal lobes and in particular the hippocampus, key regions for explicit memory, were found to be more active in the information-integration condition than in the RB condition. No regions were more activated in RB than information-integration category learning. The implications of these results for theories of category learning are discussed. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.
Unlabelled:
Recollection of contextual information represents the core of human recognition memory. It has been associated with theta (4-8 Hz) power in electrophysiological recordings and, independently, with BOLD effects in a network including the hippocampus and frontal cortex. Although the notion of the hippocampus coordinating neocortical activity by synchronization in the theta range is common among theoretical models of recollection, direct evidence supporting this hypothesis is scarce. To address this apparent gap in our understanding of memory processes, we combined EEG and fMRI during a remember/know recognition task. We can show that recollection-specific theta-alpha (4-13 Hz) effects are correlated with increases in hippocampal connectivity with the PFC and, importantly, the striatum, areas that have been linked repeatedly to retrieval success. Together, our results provide compelling evidence that low-frequency oscillations in the theta and alpha range provide a mechanism to functionally bind the hippocampus, PFC, and striatum during successful recollection.
Significance statement:
Low-frequency oscillations are supposed to drive the binding of information across a large-scale network centered on the hippocampus, which supports mnemonic functions. The electrophysiological means to investigate this phenomenon in humans (EEG/MEG), however, are inherently limited by their spatial resolution and therefore do not allow a precise localization of the brain regions involved. By combining EEG with BOLD-derived estimates of hippocampal connectivity during recognition, we can identify the striatum and specific areas in the medial and lateral PFC as part of a circuit linked to low-frequency oscillations (4-13 Hz) that promotes hippocampus-dependent context retrieval. Therefore, the current study closes an apparent gap in our understanding of the network dynamics of memory retrieval.
Exploring and exploiting a rich visual environment requires perceiving, attending, and remembering multiple objects simultaneously. Recent studies have suggested that this mental "juggling" of multiple objects may depend on oscillatory neural dynamics. We recorded local field potentials from the lateral intraparietal area, frontal eye fields, and lateral prefrontal cortex while monkeys maintained variable numbers of visual stimuli in working memory. Behavior suggested independent processing of stimuli in each hemifield. During stimulus presentation, higher-frequency power (50-100 Hz) increased with the number of stimuli (load) in the contralateral hemifield, whereas lower-frequency power (8-50 Hz) decreased with the total number of stimuli in both hemifields. During the memory delay, lower-frequency power increased with contralateral load. Load effects on higher frequencies during stimulus encoding and lower frequencies during the memory delay were stronger when neural activity also signaled the location of the stimuli. Like power, higher-frequency synchrony increased with load, but beta synchrony (16-30 Hz) showed the opposite effect, increasing when power decreased (stimulus presentation) and decreasing when power increased (memory delay). Our results suggest roles for lower-frequency oscillations in top-down processing and higher-frequency oscillations in bottom-up processing.
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Behavioral, neuropsychological, and neuroimaging evidence has suggested that categories can often be learned via either an explicit rule-based (RB) mechanism critically dependent on medial temporal and prefrontal brain regions, or via an implicit information-integration (II) mechanism relying on the basal ganglia. In this study, participants viewed sine-wave gratings (Gabor patches) that varied on two dimensions and learned to categorize them via trial-by-trial feedback. Two different stimulus distributions were used; one was intended to encourage an explicit RB process and the other an implicit II process. We monitored brain activity with scalp electroencephalography (EEG) while each participant: (1) passively observed stimuli represented of both distributions; (2) categorized stimuli from one distribution, and, 1 week later; (3) categorized stimuli from the other distribution. Categorization accuracy was similar for the two distributions. Subtractions of Event-Related Potentials (ERPs) for correct and incorrect trials were used to identify neural differences in RB and II categorization processes. We identified an occipital brain potential that was differentially modulated by categorization condition accuracy at an early latency (150–250 ms), likely reflecting the degree of holistic processing. A stimulus-locked Late Positive Complex (LPC) associated with explicit memory updating was modulated by accuracy in the RB, but not the II task. Likewise, a feedback-locked P300 ERP associated with expectancy was correlated with performance only in the RB, but not the II condition. These results provide additional evidence for distinct brain mechanisms supporting RB vs. implicit II category learning and use.
To understand object categorization, participants are tested in experiments often quite different from how people experience object categories in the real world. Learning and knowledge of categories is measured in discrete experimental trials, those trials may or may not provide feedback, trials appear one after another, after some fixed inter-trial interval, with hundreds of trials in a row, within experimental blocks with some structure dictated by the experimental design. In the real world, outside of certain educational and vocational contexts, opportunities to learn and use categories are intermixed over time with a whole multitude of intervening experiences. It is clear from any elementary understanding of human cognition that sequential effects matter, yet this understanding is often ignored, and categorization trials are often instead treated as independent events, immune to local trial context. In this perspective, we use some of our work to illustrate some of the consequences of the fact that categorization experiments have a particular trial structure. Experimental trial context can affect performance in category learning and categorization experiments in ways that can profoundly affect theoretical conclusions.
We present nine experiments, in three study phases, which test the hypothesis that learning methods which prevent the making of errors (''errorless learning'') will lead to greater learning than ''trial-and-error'' learning methods amongst individuals who are memory impaired as a result of acquired brain injury. Results suggest that tasks and situations which facilitate retrieval of implicit memory for the learned material (such as learning names with a first letter cue) will benefit from errorless learning methods, whilst those that require the explicit recall of novel associations (such as learning routes or programming an electronic organiser) will not benefit from errorless learning. The more severely amnesic patients benefit to a greater extent from errorless learning methods than those who are less severely memory impaired, but this may only apply when the interval between learning and recall is relatively short.
Functional connectivity between the prefrontal cortex (PFC) and striatum (STR) is thought critical for cognition and has been linked to conditions like autism and schizophrenia. We recorded from multiple electrodes in PFC and STR while monkeys acquired new categories. Category learning was accompanied by an increase in beta band synchronization of LFPs between, but not within, the PFC and STR. After learning, different pairs of PFC-STR electrodes showed stronger synchrony for one or the other category, suggesting category-specific functional circuits. This category-specific synchrony was also seen between PFC spikes and STR LFPs, but not the reverse, reflecting the direct monosynaptic connections from the PFC to STR. However, causal connectivity analyses suggested that the polysynaptic connections from STR to the PFC exerted a stronger overall influence. This supports models positing that the basal ganglia "train" the PFC. Category learning may depend on the formation of functional circuits between the PFC and STR.
Errorless learning (EL) is a principle used to teach new information or skills to people with cognitive impairment. In people with dementia, EL principles have mostly been studied in laboratory tasks that have little practical relevance for the participants concerned, yet show positive effects. This is the first paper to exclusively review the literature concerning the effects of EL on the performance of useful everyday tasks in people with dementia. The role of factors such as type of dementia, type of task, training intensity, EL elements, outcome measures, quality of experimental design, and follow-up are discussed. The results indicate that, compared with errorful learning (EF) or no treatment, EL is more effective in teaching adults with dementia a variety of meaningful daily tasks or skills, with gains being generally maintained at follow-up. The effectiveness of EL is highly relevant for clinical practice because it shows that individuals with dementia are still able to acquire meaningful skills and engage in worthwhile activities, which may potentially increase their autonomy and independence, and ultimately their quality of life, as well as reduce caregiver burden and professional dependency. Suggestions for future research are given, along with recommendations for effective EL-based training programs, with the aim of developing a clinical manual for professionals working in dementia care.
Primates explore the visual world through the use of saccadic eye movements. Neuronal activity in the hippocampus, a structure known to be essential for memory, is modulated by this saccadic activity, but the relationship between visual exploration through saccades and memory formation is not well understood. Here, we identify a link between theta-band (3-12 Hz) oscillatory activity in the hippocampus and saccadic activity in monkeys performing a recognition memory task. As monkeys freely explored novel images, saccades produced a theta-band phase reset, and the reliability of this phase reset was predictive of subsequent recognition. In addition, enhanced theta-band power before stimulus onset predicted stronger stimulus encoding. Together, these data suggest that hippocampal theta-band oscillations act in concert with active exploration in the primate and possibly serve to establish the optimal conditions for stimulus encoding.
From its discovery in the early 1990s until this day, the error-related negativity (ERN) remains the most widely investigated electrophysiological index of cortical error processing. When researchers began addressing the electrophysiology of subjective error awareness more than a decade ago, the role of the ERN, alongside the subsequently occurring error positivity (Pe), was an obvious locus of attention. However, the first two studies explicitly addressing the role of error-related event-related brain potentials (ERPs) would already set the tone for what still remains a controversy today: in contrast to the clear-cut findings that link the amplitude of the Pe to error awareness, the association between ERN amplitude and error awareness is vastly unclear. An initial study reported significant differences in ERN amplitude with respect to subjective error awareness, whereas the second failed to report this result, leading to a myriad of follow-up studies that seemed to back up or contradict either view. Here, I review those studies that explicitly dealt with the role of the error-related ERPs in subjective error awareness, and try to explain the differences in reported effects of error awareness on ERN amplitude. From the point of view presented here, different findings between studies can be explained by disparities in experimental design and data analysis, specifically with respect to the quantification of subjective error awareness. Based on the review of these results, I will then try to embed the error-related negativity into a widely known model of the implementation of access consciousness in the brain, the global neuronal workspace (GNW) model, and speculate as the ERN's potential role in such a framework. At last, I will outline future challenges in the investigation of the cortical electrophysiology of error awareness, and offer some suggestions on how they could potentially be addressed.
Short-term memory requires communication between multiple brain regions that collectively mediate the encoding and maintenance of sensory information. It has been suggested that oscillatory synchronization underlies intercortical communication. Yet, whether and how distant cortical areas cooperate during visual memory remains elusive. We examined neural interactions between visual area V4 and the lateral prefrontal cortex using simultaneous local field potential (LFP) recordings and single-unit activity (SUA) in monkeys performing a visual short-term memory task. During the memory period, we observed enhanced between-area phase synchronization in theta frequencies (3-9 Hz) of LFPs together with elevated phase locking of SUA to theta oscillations across regions. In addition, we found that the strength of intercortical locking was predictive of the animals' behavioral performance. This suggests that theta-band synchronization coordinates action potential communication between V4 and prefrontal cortex that may contribute to the maintenance of visual short-term memories.
Learning to classify diverse experiences into meaningful groups, like categories, is fundamental to normal cognition. To understand its neural basis, we simultaneously recorded from multiple electrodes in lateral prefrontal cortex and dorsal striatum, two interconnected brain structures critical for learning. Each day, monkeys learned to associate novel abstract, dot-based categories with a right versus left saccade. Early on, when they could acquire specific stimulus-response associations, striatum activity was an earlier predictor of the corresponding saccade. However, as the number of exemplars increased and monkeys had to learn to classify them, PFC activity began to predict the saccade associated with each category before the striatum. While monkeys were categorizing novel exemplars at a high rate, PFC activity was a strong predictor of their corresponding saccade early in the trial before the striatal neurons. These results suggest that striatum plays a greater role in stimulus-response association and PFC in abstraction of categories.
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The differences between erroneous actions that are consciously perceived as errors and those that go unnoticed have recently become an issue in the field of performance monitoring. In EEG studies, error awareness has been suggested to influence the error positivity (Pe) of the response-locked event-related brain potential, a positive voltage deflection prominent approximately 300 msec after error commission, whereas the preceding error-related negativity (ERN) seemed to be unaffected by error awareness. Erroneous actions, in general, have been shown to promote several changes in ongoing autonomic nervous system (ANS) activity, yet such investigations have only rarely taken into account the question of subjective error awareness. In the first part of this study, heart rate, pupillometry, and EEG were recorded during an antisaccade task to measure autonomic arousal and activity of the CNS separately for perceived and unperceived errors. Contrary to our expectations, we observed differences in both Pe and ERN with respect to subjective error awareness. This was replicated in a second experiment, using a modified version of the same task. In line with our predictions, only perceived errors provoke the previously established post-error heart rate deceleration. Also, pupil size yields a more prominent dilatory effect after an erroneous saccade, which is also significantly larger for perceived than unperceived errors. On the basis of the ERP and ANS results as well as brain–behavior correlations, we suggest a novel interpretation of the implementation and emergence of error awareness in the brain. In our framework, several systems generate input signals (e.g., ERN, sensory input, proprioception) that influence the emergence of error awareness, which is then accumulated and presumably reflected in later potentials, such as the Pe.
During the 1990s and early 2000s, cognitive neuroscience investigations of human category learning focused on the primary goal of showing that humans have multiple category-learning systems and on the secondary goals of identifying key qualitative properties of each system and of roughly mapping out the neural networks that mediate each system. Many researchers now accept the strength of the evidence supporting multiple systems, and as a result, during the past few years, work has begun on the second generation of research questions-that is, on questions that begin with the assumption that humans have multiple category-learning systems. This article reviews much of this second generation of research. Topics covered include (1) How do the various systems interact? (2) Are there different neural systems for categorization and category representation? (3) How does automaticity develop in each system? and (4) Exactly how does each system learn?
The prefrontal cortex (PFC) is important for flexible, context-dependent behavioral control. It also plays a critical role in short-term memory maintenance. Though many studies have investigated these functions independently, it is unclear how these two very different processes are realized by a single brain area. To address this, we trained two monkeys on two variants of an object sequence memory task. These tasks had the same memory requirements but differed in how information was read out and used. For the "recognition" task, the monkeys had to remember two sequentially presented objects and then release a bar when a matching sequence was recognized. For the "recall" task, the monkeys had to remember the same sequence of objects but were instead required to recall the sequence and reproduce it with saccadic eye movements when presented with an array of objects. After training, we recorded the activity of PFC neurons during task performance. We recorded 222 neurons during the recognition task, 177 neurons during the recall task, and 248 neurons during the switching task (interleaved blocks of recognition and recall). Task context had a profound influence on neural selectivity for objects. During the recall task, the first object was encoded more strongly than the second object, while during the recognition task, the second object was encoded more strongly. In addition, most of the neurons encoded both the task and the objects, evidence for a single population responsible for these two critical prefrontal functions.
The ability to group items and events into functional categories is a fundamental characteristic of sophisticated thought. It is subserved by plasticity in many neural systems, including neocortical regions (sensory, prefrontal, parietal, and motor cortex), the medial temporal lobe, the basal ganglia, and midbrain dopaminergic systems. These systems interact during category learning. Corticostriatal loops may mediate recursive, bootstrapping interactions between fast reward-gated plasticity in the basal ganglia and slow reward-shaded plasticity in the cortex. This can provide a balance between acquisition of details of experiences and generalization across them. Interactions between the corticostriatal loops can integrate perceptual, response, and feedback-related aspects of the task and mediate the shift from novice to skilled performance. The basal ganglia and medial temporal lobe interact competitively or cooperatively, depending on the demands of the learning task.
Objective: Errorless learning is an effective strategy for the cognitive rehabilitation of memory impairment, but there is little evidence to support its use for skill learning. This preliminary study investigates whether errorless learning is superior to treatment as usual (trial and error), when teaching people with amputations and comorbid risk of vascular cognitive impairment to fit a prosthetic limb.
Design: A randomized control design.
Setting: A regional limb-fitting clinic at the West of Scotland Mobility and Rehabilitation Centre in Glasgow.
Participants: Thirty adults with transtibial amputations, recruited from a regional limb-fitting clinic. Of these 42% were cognitively impaired.
Intervention: Random assignment to an errorless learning intervention (n = 15) or a treatment as usual control (n = 15). There were five training trials within a single session. Participants were then asked to fit their limb without assistance.
Main measures: Performance was scored from videotape recording of the first occasion when the participant attempted to fit their limb without assistance. Addenbrookes Cognitive Examination — Revised (ACE-R) was used to assess general cognitive functioning.
Results: The errorless learning group remembered more correct steps (mean 90.9, SD 12.1) than the control group (77.9; 8.4; P<0.001) and made fewer errors (mean 0.93, SD 1.3) than controls (2.1; 0.95); P =0.002).
Conclusions: Errorless learning can benefit people with amputations in learning the practical skill of fitting a prosthetic limb. Further study that includes follow-up is warranted.
An influential theoretical perspective differentiates in humans an explicit, rule-based system of category learning from an implicit system that slowly associates different regions of perceptual space with different response outputs. This perspective was extended for the 1st time to the category learning of nonhuman primates. Humans (Homo sapiens) and macaques (Macaca mulatta) learned categories composed of sine-wave gratings that varied across trials in bar width and bar orientation. The categories had either a single-dimensional, rule-based solution or a two-dimensional, information-integration solution. Humans strongly dimensionalized the stimuli and learned the rule-based task far more quickly. Six macaques showed the same performance advantage in the rule-based task. In humans, rule-based category learning is linked to explicit cognition, consciousness, and declarative reports about the contents of cognition. These results demonstrate an empirical continuity between human and nonhuman primate cognition, suggesting that nonhuman primates may have some structural components of humans' capacity for explicit cognition.
Increasing evidence suggests that neuronal synchronization in the gamma band (30-100 Hz) may play an important role in mediating cognitive processes. Gamma-band synchronization provides for the optimal temporal relationship between two signals to produce the long-term synaptic changes that have been theorized to underlie memory formation. Although neuronal populations in the hippocampus oscillate in the gamma range, the role of these oscillations in memory formation is still unclear. To address this issue, we recorded neuronal activity in the hippocampus while macaque monkeys performed a visual recognition memory task. During the encoding phase of this task, hippocampal neurons displayed gamma-band synchronization. Additionally, enhanced gamma-band synchronization during encoding predicted greater subsequent recognition memory performance. These changes in synchronization reflect enhanced coordination among hippocampal neurons and may facilitate synaptic changes necessary for successful memory encoding.
In tasks of associative learning, animals establish new links between unrelated items by using information about trial outcome to strengthen correct/rewarded associations and modify incorrect/unrewarded ones. To study how hippocampal neurons convey information about reward and trial outcome during new associative learning, we recorded hippocampal neurons as monkeys learned novel object-place associations. A large population of hippocampal neurons (50%) signaled trial outcome by differentiating between correct and error trials during the period after the behavioral response. About half these cells increased their activity following correct trials (correct up cells) while the remaining half fired more following error trials (error up cells). Moreover, correct up cells, but not error up cells, conveyed information about learning by increasing their stimulus-selective response properties with behavioral learning. These findings suggest that information about successful trial outcome conveyed by correct up cells may influence new associative learning through changes in the cell's stimulus-selective response properties.
The neural underpinnings of prototype learning are not well understood. A major source of confusion is that two versions of the prototype learning task have been used interchangeably in the literature; one where participants learn to categorize exemplars derived from two prototypes (A/B task), and one where participants learn to categorize exemplars derived from one prototype and noncategorical exemplars (A/non-A). We report results from an fMRI study of A/B and A/non-A prototype learning that allows for a direct contrast of the two learning methods. Accuracy in the two tasks did not correlate within subject despite equivalent average difficulty. The fMRI results revealed neural activation in a network of regions consistent with episodic memory retrieval for the A/B task while greater activation of a nondeclarative learning network was observed for the A/non-A task. The results demonstrate that learning in these two tasks is mediated by different neural systems and that recruitment of each system is dictated by the context of learning rather than the actual category structure.
A CONTINUATION OF EFFORTS TO DEVELOP A PSYCHOPHYSICS OF FORM SIMILARITY APPROPRIATE TO THE STUDY OF CONCEPT LEARNING. 5 CONFIGURATIONS OF DOTS (TRIANGLE, DIAMOND, M, F, AND RANDOM) WERE STUDIED. THE PSYCHOPHYSICAL FUNCTIONS RELATING PERCEIVED DISTANCE FROM THE ORIGINAL TO EACH LEVEL OF DISTORTION WERE LINEAR. THE LEVEL OF DISTORTION WAS CALCULATED FROM THE STATISTICAL RULE GENERATING THE DISTORTIONS AND EXPRESSED IN TERMS OF UNCERTAINTY. IT ALSO REFLECTED THE MEAN DISTANCE THAT EACH DOT ACTUALLY GRAVITATED OVER RANDOM SAMPLES OF THE RULE. THE PERCEIVED DISTANCE BETWEEN ANY PAIR OF DISTORTIONS INCREASED WITH THE LEVEL OF THE MORE DISTORTED FROM THE ORIGINAL. THE LEVEL OF DISTORTION OF A SAMPLE OF PATTERNS WAS RELATED TO THE RATE AT WHICH SS LEARNED A COMMON RESPONSE TO THAT SAMPLE. RATE OF LEARNING IN CLASSIFYING THESE PATTERNS, LIKE MULTIVARIATE CONCEPT LEARNING, IS A FUNCTION OF THE UNCERTAINTY WITHIN A CATEGORY. (18 REF.)
A fundamental question about cognition concerns how knowledge about a category is acquired through encounters with examples
of the category. Amnesic patients and control subjects performed similarly at classifying novel patterns according to whether
they belonged to the same category as a set of training patterns. In contrast, the amnesic patients were impaired at recognizing
which dot patterns had been presented for training. Category learning appears to be independent of declarative (explicit)
memory for training instances and independent of the brain structures essential for declarative memory that are damaged in
amnesia. Knowledge about categories can be acquired implicitly by cumulating information from multiple examples.
A fundamental question about memory and cognition concerns how information is acquired about categories and concepts as the result of encounters with specific instances. We describe a profoundly amnesic patient (E.P.) who cannot learn and remember specific instances--i.e., he has no detectable declarative memory. Yet after inspecting a series of 40 training stimuli, he was normal at classifying novel stimuli according to whether they did or did not belong to the same category as the training stimuli. In contrast, he was unable to recognize a single stimulus after it was presented 40 times in succession. These findings demonstrate that the ability to classify novel items, after experience with other items in the same category, is a separate and parallel memory function of the brain, independent of the limbic and diencephalic structures essential for remembering individual stimulus items (declarative memory). Category-level knowledge can be acquired implicitly by cumulating information from multiple training examples in the absence of detectable conscious memory for the examples themselves.
In standard protocols, the frequency of synaptic stimulation determines whether CA1 hippocampal synapses undergo long-term potentiation or depression. Here we show that during cholinergically induced theta oscillation (theta) synaptic plasticity is greatly sensitized and can be induced by a single burst (4 pulses, 100 Hz). A burst given at the peak of theta induces homosynaptic LTP; the same burst at a trough induces homosynaptic LTD of previously potentiated synapses. Heterosynaptic LTD is produced at inactive synapses when others undergo LTP. The synaptic modifications during theta require NMDA receptors and muscarinic receptors. The enhancement is cooperative and occludes with standard LTP. These results suggest that the similar bursts observed during theta rhythm in vivo may be a natural stimulus for inducing LTP/LTD.
We collected functional neuroimaging data while volunteers performed similar categorization and recognition memory tasks. In the categorization task, volunteers first studied a series of 40 dot patterns that were distortions of a nonstudied prototype dot pattern. After a delay, while fMRI data were collected, they categorized 72 novel dot patterns according to whether or not they belonged to the previously studied category. In the recognition task, volunteers first studied five dot patterns eight times each. After a delay, while fMRI data were collected, they judged whether each of 72 dot patterns had been studied earlier. We found strikingly different patterns of brain activity in visual processing areas for the two tasks. During the categorization task, the familiar stimuli were associated with decreased activity in posterior occipital cortex, whereas during the recognition task, the familiar stimuli were associated with increased activity in this area. The findings indicate that these two types of memory have contrasting effects on early visual processing and reinforce the view that declarative and nondeclarative memory operate independently.
Much of our knowledge of the world depends on learning associations (for example, face-name), for which the hippocampus (HPC) and prefrontal cortex (PFC) are critical. HPC-PFC interactions have rarely been studied in monkeys, whose cognitive and mnemonic abilities are akin to those of humans. We found functional differences and frequency-specific interactions between HPC and PFC of monkeys learning object pair associations, an animal model of human explicit memory. PFC spiking activity reflected learning in parallel with behavioral performance, whereas HPC neurons reflected feedback about whether trial-and-error guesses were correct or incorrect. Theta-band HPC-PFC synchrony was stronger after errors, was driven primarily by PFC to HPC directional influences and decreased with learning. In contrast, alpha/beta-band synchrony was stronger after correct trials, was driven more by HPC and increased with learning. Rapid object associative learning may occur in PFC, whereas HPC may guide neocortical plasticity by signaling success or failure via oscillatory synchrony in different frequency bands.
The controversy over multiple category-learning systems is reminiscent of the controversy over multiple memory systems. Researchers continue to seek paradigms to sharply dissociate explicit category-learning processes (featuring category rules that can be verbalized) from implicit category-learning processes (featuring learned stimulus-response associations that lie outside declarative cognition). We contribute a new dissociative paradigm, adapting the technique of deferred-rearranged reinforcement from comparative psychology. Participants learned matched category tasks that had either a one-dimensional, rule-based solution or a multidimensional, information-integration solution. They received feedback either immediately or after each block of trials, with the feedback organized such that positive outcomes were grouped and negative outcomes were grouped (deferred-rearranged reinforcement). Deferred reinforcement qualitatively eliminated implicit, information-integration category learning. It left intact explicit, rule-based category learning. Moreover, implicit-category learners facing deferred-rearranged reinforcement turned by default and information-processing necessity to rule-based strategies that poorly suited their nominal category task. The results represent one of the strongest explicit-implicit dissociations yet seen in the categorization literature.
The theta rhythm is one of the largest and most sinusoidal activity patterns in the brain. Here I survey progress in the field of theta rhythms research. I present arguments supporting the hypothesis that theta rhythms emerge owing to intrinsic cellular properties yet can be entrained by several theta oscillators throughout the brain. I review behavioral correlates of theta rhythms and consider how these correlates inform our understanding of theta rhythms' functions. I discuss recent work suggesting that one function of theta is to package related information within individual theta cycles for more efficient spatial memory processing. Studies examining the role of theta phase precession in spatial memory, particularly sequence retrieval, are also summarized. Additionally, I discuss how interregional coupling of theta rhythms facilitates communication across brain regions. Finally, I conclude by summarizing how theta rhythms may support cognitive operations in the brain, including learning. Expected final online publication date for the Annual Review of Neuroscience Volume 36 is July 08, 2013. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
Brain networks are commonly defined using correlations between blood oxygen level-dependent (BOLD) signals in different brain areas. Although evidence suggests that gamma-band (30-100 Hz) neural activity contributes to local BOLD signals, the neural basis of interareal BOLD correlations is unclear. We first defined a visual network in monkeys based on converging evidence from interareal BOLD correlations during a fixation task, task-free state, and anesthesia, and then simultaneously recorded local field potentials (LFPs) from the same four network areas in the task-free state. Low-frequency oscillations (<20 Hz), and not gamma activity, predominantly contributed to interareal BOLD correlations. The low-frequency oscillations also influenced local processing by modulating gamma activity within individual areas. We suggest that such cross-frequency coupling links local BOLD signals to BOLD correlations across distributed networks.
Intelligent behavior requires acquiring and following rules. Rules define how our behavior should fit different situations. To understand its neural mechanisms, we simultaneously recorded from multiple electrodes in dorsolateral prefrontal cortex (PFC) while monkeys switched between two rules (respond to color versus orientation). We found evidence that oscillatory synchronization of local field potentials (LFPs) formed neural ensembles representing the rules: there were rule-specific increases in synchrony at "beta" (19-40 Hz) frequencies between electrodes. In addition, individual PFC neurons synchronized to the LFP ensemble corresponding to the current rule (color versus orientation). Furthermore, the ensemble encoding the behaviorally dominant orientation rule showed increased "alpha" (6-16 Hz) synchrony when preparing to apply the alternative (weaker) color rule. This suggests that beta-frequency synchrony selects the relevant rule ensemble, while alpha-frequency synchrony deselects a stronger, but currently irrelevant, ensemble. Synchrony may act to dynamically shape task-relevant neural ensembles out of larger, overlapping circuits.
We measured local field potential (LFP) and blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in the medial temporal lobes of monkeys and humans, respectively, as they performed the same conditional motor associative learning task. Parallel analyses were used to examine both data sets. Despite significantly faster learning in humans relative to monkeys, we found equivalent neural signals differentiating new versus highly familiar stimuli, first stimulus presentation, trial outcome, and learning strength in the entorhinal cortex and hippocampus of both species. Thus, the use of parallel behavioral tasks and analyses in monkeys and humans revealed conserved patterns of neural activity across the medial temporal lobe during an associative learning task.
The VideoToolbox is a free collection of two hundred C subroutines for Macintosh computers that calibrates and controls the computer-display interface to create accurately specified visual stimuli. High-level platform-independent languages like MATLAB are best for creating the numbers that describe the desired images. Low-level, computer-specific VideoToolbox routines control the hardware that transforms those numbers into a movie. Transcending the particular computer and language, we discuss the nature of the computer-display interface, and how to calibrate and control it.
The report attempts to delineate certain residual learning capacities of H.M., a young man who became amnesic in 1953 following a bilateral removal in the hippocampal zone. In addition to being able to acquire new motor skills (CORKIN [2]), this patient shows some evidence of perceptual learning. He also achieves some retention of very simple visual and tactual mazes in which the sequence of required turns is short enough to fit into his immediate memory span; even then, the rate of acquisition is extremely slow. These vestigial abilies, which have their occasional parallels in the patient's everyday life, are assessed against the background of his continuing profound amnesia for most on-going events, an amnesia that persists in spite of above-average intelligence and superior performance on many perceptual tasks.
An influential multi-process model of category learning, COmpetition between Verbal and Implicit Systems (COVIS), suggests that a verbal or a procedural category learning process is adopted, depending on the nature of the learning problem. While the architectural assumptions of COVIS have been widely supported, there is still uncertainty regarding the types of category structures that are likely to engage each of the COVIS systems. We examined COVIS in an fMRI study with two novel (in terms of COVIS research) categorizations. One of the categorizations could be described by a simple, unidimensional, rule that was expected to favor the verbal system. The other categorization possessed characteristics typically associated with the procedural system, but could also potentially be verbalized using a rule more complex than the ones previously associated with the verbal system. We found that both categorizations engaged regions associated with the verbal system. Additionally, for both categorizations, frontal lobe regions (including left ventrolateral frontal cortex) were more engaged in the first compared to the second session, possibly reflecting the greater use of hypothesis-testing processes in the initial stages of category acquisition. In sum, our results extend our knowledge of the conditions under which the verbal system will operate. These findings indicate that much remains to be understood concerning the precise interplay of the verbal and procedural categorization systems.
To study the interplay between hippocampus and medial prefrontal cortex (Pfc) and its importance for learning and memory consolidation, we measured the coherence in theta oscillations between these two structures in rats learning new rules on a Y maze. Coherence peaked at the choice point, most strongly after task rule acquisition. Simultaneously, Pfc pyramidal neurons reorganized their phase, concentrating at hippocampal theta trough, and synchronous cell assemblies emerged. This synchronous state may result from increased inhibition exerted by interneurons on pyramidal cells, as measured by cross-correlation, and could be modulated by dopamine: we found similar hippocampal-Pfc theta coherence increases and neuronal phase shifts following local administration of dopamine in Pfc of anesthetized rats. Pfc cell assemblies emerging during high coherence were preferentially replayed during subsequent sleep, concurrent with hippocampal sharp waves. Thus, hippocampal/prefrontal coherence could lead to synchronization of reward predicting activity in prefrontal networks, tagging it for subsequent memory consolidation.
Oscillatory activity is a widespread phenomenon in nervous systems and has been implicated in numerous functions. Signals that are generated by two separate neuronal sources often demonstrate a consistent phase-relationship in a particular frequency-band, i.e., they demonstrate rhythmic neuronal synchronization. This consistency is conventionally measured by the PLV (phase-locking value) or the spectral coherence measure. Both statistical measures suffer from significant bias, in that their sample estimates overestimate the population statistics for finite sample sizes. This is a significant problem in the neurosciences where statistical comparisons are often made between conditions with a different number of trials or between neurons with a different number of spikes. We introduce a new circular statistic, the PPC (pairwise phase consistency). We demonstrate that the sample estimate of the PPC is a bias-free and consistent estimator of its corresponding population parameter. We show, both analytically and by means of numerical simulations, that the population statistic of the PPC is equivalent to the population statistic of the squared PLV. The variance and mean squared error of the PPC and PLV are compared. Finally, we demonstrate the practical relevance of the method in actual neuronal data recorded from the orbitofrontal cortex of rats that engage in a two-odour discrimination task. We find a strong increase in rhythmic synchronization of spikes relative to the local field potential (as measured by the PPC) for a wide range of low frequencies (including the theta-band) during the anticipation of sucrose delivery in comparison to the anticipation of quinine delivery.
Learning from experience requires knowing whether a past action resulted in a desired outcome. The prefrontal cortex and basal ganglia are thought to play key roles in such learning of arbitrary stimulus-response associations. Previous studies have found neural activity in these areas, similar to dopaminergic neurons' signals, that transiently reflect whether a response is correct or incorrect. However, it is unclear how this transient activity, which fades in under a second, influences actions that occur much later. Here, we report that single neurons in both areas show sustained, persistent outcome-related responses. Moreover, single behavioral outcomes influence future neural activity and behavior: behavioral responses are more often correct and single neurons more accurately discriminate between the possible responses when the previous response was correct. These long-lasting signals about trial outcome provide a way to link one action to the next and may allow reward signals to be combined over time to implement successful learning.
In the resting EEG, the percentage power in the delta, theta, alpha, and beta bands and the mean frequency were computed in an occipital-vertex derivation for two samples of subjects. The original sample (n = 79) and the new sample (n = 43) each contained a mild probable Alzheimer's disease (SDAT) group and a healthy elderly control group. Group medians in both samples were higher in the SDAT than in the healthy subjects for percentage delta and theta, and were lower for percentage alpha and beta and for mean frequency. Percentage theta and mean frequency were consistent across the two samples in showing statistically significant differences between SDAT and healthy groups. The ability of each EEG measure to detect individual subjects with SDAT was assessed. The most effective measure, percentage theta, had only modest sensitivity (about 20%), but this was attained at a specificity of 100%. The accurate detection of an individual at the mild stage requires that the predictive value of a positive test be high to avoid misclassification of non-SDAT subjects as SDAT. This, in turn, requires a specificity of virtually 100% when the prevalence is low. The low sensitivity puts several constraints on the usefulness of the EEG. For this reason, when the dementia is at the mild stage the EEG would be a useful detector of probable Alzheimer's disease only under certain limiting conditions, including high prevalence, high specificity, and a willingness to accept a high rate of falsely negative tests.
Most of our long-term memories of episodes or objects are organized so that we can retrieve them by association. Clinical neuropsychologists assess human memory by the paired-associate learning test, in which a series of paired words or figures is presented and the subject is then asked to retrieve the other pair member associated with each cue. Patients with lesions of the temporal lobe show marked impairment in this test. In our study, we trained monkeys in a pair-association task using a set of computer-generated paired patterns. We found two types of task-related neurons in the anterior temporal cortex. One type selectively responded to both pictures of the paired associates. The other type, which had the strongest response to one picture during the cue presentation, exhibited increasing activity during the delay period when the associate of that picture was used as a cue. These results provide new evidence that single neurons acquire selectivity for visual patterns through associative learning. They also indicate neural mechanisms for storage and retrieval in the long-term memory of paired associates.
Amnesic patients acquired a mirror-reading skill at a rate equivalent to that of matched control subjects and retained it
for at least 3 months. The results indicate that the class of preserved learning skills in amnesia is broader than previously
reported. Amnesia seems to spare information that is based on rules or procedures, as contrasted with information that is
data-based or declarative--"knowing how rather than "knowing that." The results support the hypothesis that such a distinction
is honored by the nervous system.
1. The companion paper reported that a substantial proportion of cells in the supplementary eye field (SEF) of macaque monkeys show significant evolution of neuronal activity as subjects learn new and arbitrary stimulus-saccade associations. The purpose of the present study was to compare and contrast the activity of the SEF and the frontal eye field (FEF) during such conditional oculomotor learning. 2. In both SEF and FEF, we observed learning-dependent and learning-selective activity, defined as significant evolution of task-related activity as monkeys learned which of four saccades was instructed by a novel stimulus. By definition, in addition to changes as the monkeys learned the instructional significance of a novel instruction stimulus, learning-dependent activity also showed task-related modulation for trials instructed by familiar stimuli, whereas learning-selective activity did not. Of the 186 SEF neurons adequately tested, 81 (44%) showed one of these two categories of learning-related change. By contrast, of the 90 FEF neurons adequately tested, only 14 (16%) showed similar properties. This difference was highly statistically significant (chi 2 = 21.1; P < 0.001). 3. We also observed persistent differences in activity for trials with familiar versus novel instruction stimuli, which we termed learning-static effects. In some cases, the learning-static effect coexisted with learning-dependent or learning-selective changes in activity, although in others it did not. In the former cases, activity changed systematically during learning, but reached a level that differed from that for familiar stimuli instructing the same saccade. In the latter cases, the activity did not change significantly as the monkey learned new conditional oculomotor associations, but did show a significant difference depending upon whether a novel or familiar stimulus instructed a given saccade. Overall, 66 of 186 (35%) cells in the SEF and 17 of 90 (19%) cells in the FEF showed learning-static effects in one or more task periods. This difference was statistically significant (chi 2 = 7.9; P < 0.005). 4. The significant difference in the properties of SEF and FEF cells suggests a functional dissociation of the two areas during conditional oculomotor learning. In this respect, the FEF resembles the primary motor cortex, whereas the SEF resembles the premotor cortex.
The Psychophysics Toolbox is a software package that supports visual psychophysics. Its routines provide an interface between a high-level interpreted language (MATLAB on the Macintosh) and the video display hardware. A set of example programs is included with the Toolbox distribution.
In two experiments involving verbal association learning by people with memory impairments, the effectiveness of errorless learning (EL) was compared with errorful learning (EF). Experiment 1 examined the effectiveness of both methods in learning remotely linked word pairs. There was an advantage for items learned by EL at immediate test which was not sustained over a delay of 1 hr. Learning appeared to be stable over this delay in the EF condition. Analysis of responses at delayed cued recall showed more evidence of spontaneous recovery in EF than in EL. Elimination of these items from analysis resulted in a similar pattern of forgetting in both methods. Experiment 2 examined the effectiveness of EL and EF in teaching novel associations, and showed an advantage for EL at immediate and delayed test. Forgetting was apparently observed following EL, but not EF. As in Experiment 1, this discrepancy was attributed to recovered responses at delayed test in EF. Eliminating these responses showed a similar pattern of forgetting in both methods for items correctly recalled at immediate test. The study shows an advantage for EL techniques in learning novel associations. The two methods also differ in that learning via EF is associated with more spontaneous recovery.