Multidimensional sequence learning in patients with focal basal ganglia lesions

Parkinson's patients have been found to be impaired in learning movement sequences. In the current study, patients with unilateral basal ganglia lesions due to stroke were tested on a serial reaction time task in which responses were based on the spatial location of each stimulus. The spatial locations either followed a fixed sequence or were selected at random, with learning operationalized as the difference in reaction time between these two conditions. In addition, three response-to-stimulus intervals were used, and these either followed a fixed sequence or were randomized. Compared to control participants, the patients showed normal learning of the spatial and temporal sequences, as well as normal cross-dimensional learning. This was true for performance with either the contralesional or ipsilesional hand. Sequence learning was not correlated with maximum tapping rate, a simple measure of motor impairment. These results raise questions concerning the use of Parkinson's disease as a model for studying basal ganglia dysfunction.     

The differential role of premotor frontal cortex and basal ganglia in motor sequence learning: evidence from focal basal ganglia lesions

There has been a growing interest in the differential role of various neural structures in implicit learning processes. The goal of our study was to clarify how focal lesions restricted to the basal ganglia interfere with different aspects of implicit visuo-motor sequence learning. A version of the Serial Reaction Time Task (SRTT) of Nissen and Bullemer using a 12-trial sequence was administered. A total of 20 subjects with focal basal ganglia lesions caused by ischemic or hemorrhagic infarction and 20 matched control subjects participated in this study. The results indicate that subjects with focal basal ganglia lesions showed unimpaired implicit learning of a 12-item motor sequence. Subjects with basal ganglia lesions, however, had more difficulties improving their general proficiency with the reaction-time task independent of sequence-specific learning. We observed a tendency toward smaller regional volumes in the cerebellum and left pre-supplementary motor area (pre-SMA) of subjects with basal ganglia lesions. Smaller cerebellar and pre-SMA volumes were related to lower implicit learning performance in the lesion group. The size of lesions in the basal ganglia was not related to sequence-specific implicit learning but had a significant influence on subjects' general proficiency for execution of the reaction-time task. We propose that implicit learning is achieved by a distributed network of cortical and subcortical structures. The basal ganglia seem to be responsible for adjusting to the general requirements of a task rather than for learning specific associations between stimuli that might be accomplished by premotor frontal areas and the cerebellum instead.     

Providing explicit information disrupts implicit motor learning after basal ganglia stroke

Despite their purported neuroanatomic and functional isolation, empirical evidence suggests that sometimes conscious explicit processes can influence implicit motor skill learning. Our goal was to determine if the provision of explicit information affected implicit motor-sequence learning after damage to the basal ganglia. Individuals with stroke affecting the basal ganglia (BG) and healthy controls (HC) practiced a continuous implicit motor-sequencing task; half were provided with explicit information (EI) and half were not (No-EI). The focus of brain damage for both BG groups was in the putamen. All of the EI participants were at least explicitly aware of the repeating sequence. Across three days of practice, explicit information had a differential effect on the groups. Explicit information disrupted acquisition performance in participants with basal ganglia stroke but not healthy controls. By retention (day 4), a dissociation was apparent--explicit information hindered implicit learning in participants with basal ganglia lesions but aided healthy controls. It appears that after basal ganglia stroke explicit information is less helpful in the development of the motor plan than is discovering a motor solution using the implicit system alone. This may be due to the increased demand placed on working memory by explicit information. Thus, basal ganglia integrity may be a crucial factor in determining the efficacy of explicit information for implicit motor-sequence learning.     

The automaticity of visual statistical learning

The visual environment contains massive amounts of information involving the relations between objects in space and time, and recent studies of visual statistical learning (VSL) have suggested that this information can be automatically extracted by the visual system. The experiments reported in this article explore the automaticity of VSL in several ways, using both explicit familiarity and implicit response-time measures. The results demonstrate that (a) the input to VSL is gated by selective attention, (b) VSL is nevertheless an implicit process because it operates during a cover task and without awareness of the underlying statistical patterns, and (c) VSL constructs abstracted representations that are then invariant to changes in extraneous surface features. These results fuel the conclusion that VSL both is and is not automatic: It requires attention to select the relevant population of stimuli, but the resulting learning then occurs without intent or awareness.     

Using TD learning to simulate working memory performance in a model of the prefrontal cortex and basal ganglia

Delayed-response tasks (DRTs) have been used to assess working memory (WM) processes in human and nonhuman animals. Experiments have shown that the basal ganglia (BG) and dorsolateral prefrontal cortex (DLPFC) subserve DRT performance. Here, we report the results of simulation studies of a systems-level model of DRT performance. The model was trained using the temporal difference (TD) algorithm and uses an actor-critic architecture. The matrisomes of the BG represent the actor and the striosomes represent the critic. Unlike existing models, we hypothesize that the BG subserve the selection of both motor- and cognitive-related information in these tasks. We also assume that the learning of both processes is based on reward presentation. A novel feature of the model is the incorporation of delay-active neurons in the matrisomes, in addition to DLPFC. Another novel feature of the model is the subdivision of the matrisomal neurons into segregated winner-take-all (WTA) networks consisting of delay- versus transiently-active units.Our simulation model proposes a new neural mechanism to account for the occurrence of perseverative responses in WM tasks in striatal-, as well as in prefrontal damaged subjects. Simulation results also show that the model both accounts for the phenomenon of time shifting of dopamine phasic signals and the effects of partial reinforcement and reward magnitude on WM performance at both behavioral and neural levels. Our simulation results also found that the TD algorithm can subserve learning in delayed-reversal tasks.     

Active and passive contributions to spatial learning

It seems intuitively obvious that active exploration of a new environment will lead to better spatial learning than will passive exposure. However, the literature on this issue is decidedly mixed—in part, because the concept itself is not well defined. We identify five potential components of active spatial learning and review the evidence regarding their role in the acquisition of landmark, route, and survey knowledge. We find that (1) idiothetic information in walking contributes to metric survey knowledge, (2) there is little evidence as yet that decision making during exploration contributes to route or survey knowledge, (3) attention to place–action associations and relevant spatial relations contributes to route and survey knowledge, although landmarks and boundaries appear to be learned without effort, (4) route and survey information are differentially encoded in subunits of working memory, and (5) there is preliminary evidence that mental manipulation of such properties facilitates spatial learning. Idiothetic information appears to be necessary to reveal the influence of attention and, possibly, decision making in survey learning, which may explain the mixed results in desktop virtual reality. Thus, there is indeed an active advantage in spatial learning, which manifests itself in the task-dependent acquisition of route and survey knowledge.     

The role of the basal ganglia in learning and memory: insight from Parkinson's disease

It has long been known that memory is not a single process. Rather, there are different kinds of memory that are supported by distinct neural systems. This idea stemmed from early findings of dissociable patterns of memory impairments in patients with selective damage to different brain regions. These studies highlighted the role of the basal ganglia in non-declarative memory, such as procedural or habit learning, contrasting it with the known role of the medial temporal lobes in declarative memory. In recent years, major advances across multiple areas of neuroscience have revealed an important role for the basal ganglia in motivation and decision making. These findings have led to new discoveries about the role of the basal ganglia in learning and highlighted the essential role of dopamine in specific forms of learning. Here we review these recent advances with an emphasis on novel discoveries from studies of learning in patients with Parkinson's disease. We discuss how these findings promote the development of current theories away from accounts that emphasize the verbalizability of the contents of memory and towards a focus on the specific computations carried out by distinct brain regions. Finally, we discuss new challenges that arise in the face of accumulating evidence for dynamic and interconnected memory systems that jointly contribute to learning.     

Change in the relative contributions of habit and working memory facilitates serial reversal learning expertise in rhesus monkeys

Functionally distinct memory systems likely evolved in response to incompatible demands placed on learning by distinct environmental conditions. Working memory appears adapted, in part, for conditions that change frequently, making rapid acquisition and brief retention of information appropriate. In contrast, habits form gradually over many experiences, adapting organisms to contingencies of reinforcement that are stable over relatively long intervals. Serial reversal learning provides an opportunity to simultaneously examine the processes involved in adapting to rapidly changing and relatively stable contingencies. In serial reversal learning, selecting one of the two simultaneously presented stimuli is positively reinforced, while selection of the other is not. After a preference for the positive stimulus develops, the contingencies of reinforcement reverse. Naïve subjects adapt to such reversals gradually, perseverating in selection of the previously rewarded stimulus. Experts reverse rapidly according to a win-stay, lose-shift response pattern. We assessed whether a change in the relative control of choice by habit and working memory accounts for the development of serial reversal learning expertise. Across three experiments, we applied manipulations intended to attenuate the contribution of working memory but leave the contribution of habit intact. We contrasted performance following long and short intervals in Experiments 1 and 2, and we interposed a competing cognitive load between trials in Experiment 3. These manipulations slowed the acquisition of reversals in expert subjects, but not naïve subjects, indicating that serial reversal learning expertise is facilitated by a shift in the control of choice from passively acquired habit to actively maintained working memory.     

Hippocampus, cortex, and basal ganglia: insights from computational models of complementary learning systems

We present a framework for understanding how the hippocampus, neocortex, and basal ganglia work together to support cognitive and behavioral function in the mammalian brain. This framework is based on computational tradeoffs that arise in neural network models, where achieving one type of learning function requires very different parameters from those necessary to achieve another form of learning. For example, we dissociate the hippocampus from cortex with respect to general levels of activity, learning rate, and level of overlap between activation patterns. Similarly, the frontal cortex and associated basal ganglia system have important neural specializations not required of the posterior cortex system. Taken together, this overall cognitive architecture, which has been implemented in functioning computational models, provides a rich and often subtle means of explaining a wide range of behavioral and cognitive neuroscience data. Here, we summarize recent results in the domains of recognition memory, contextual fear conditioning, effects of basal ganglia lesions on stimulus-response and place learning, and flexible responding.     

Motor functions of the basal ganglia

Summary A study of movement disorders such as Parkinson's disease and Huntington's disease can provide an indication of the motor functions of the basal ganglia. Basal-ganglia diseases affect voluntary movement and can cause involuntary movement. Deficits are often manifested during the coordination of fine multi-joint movements (e. g., handwriting). The disturbances of motor control (e.g. akinesia, bradykinesia) caused by basal-ganglia disorders are illustrated. Data suggest that the basal ganglia play an important role in the automatic execution of serially ordered complex movements.     

Semisupervised category learning facilitates the development of automaticity

In the human category of learning, learning is studied in a supervised, an unsupervised, or a semisupervised way. The rare human semisupervised category of learning studies all focus on early learning. However, the impact of the semisupervised category learning late in learning, when automaticity develops, is unknown. Therefore, in Experiment 1, all participants were first trained on the information-integration category structure for 2 days until they reached an expert level. Afterwards, half of the participants learned in a supervised way and the other half in a semisupervised way over two successive days. Both groups received an equal number of feedback trials. Finally, all participants took part in a test day where they were asked to respond as quickly as possible. Participants were significantly faster on this test in the semisupervised group than in the supervised group. This difference was not found on day 2, implying that the no-feedback trials in the semisupervised condition facilitated automaticity. Experiment 2 was designed to test whether the higher number of trials in the semisupervised condition of Experiment 1 caused the faster response times. We therefore created an almost supervised condition where participants almost always received feedback (95%) and an almost unsupervised condition where participants almost never received feedback (5%). All conditions now contained an equal number of trials to the semisupervised condition of Experiment 1. The results show that receiving feedback almost always or almost never led to slower response times than the semisupervised condition of Experiment 1. This confirms the advantage of semisupervised learning late in learning.     

On the automaticity of pure perceptual sequence learning

We investigated the automaticity of implicit sequence learning by varying perceptual load in a pure perceptual sequence learning paradigm. Participants responded to the randomly changing identity of a target, while the irrelevant target location was structured. In Experiment 1, the target was presented under low or high perceptual load during training, whereas testing occurred without load. Unexpectedly, no sequence learning was observed. In Experiment 2, perceptual load was introduced during the test phase to determine whether load is required to express perceptual knowledge. Learning itself was unaffected by visuospatial demands, but more learning was expressed under high load test conditions. In Experiment 3, we demonstrated that perceptual load is not required for the acquisition of perceptual sequence knowledge. These findings suggest that perceptual load does not mediate the perceptual sequence learning process itself, supporting the automaticity of implicit learning, but is mandatory for the expression of pure perceptual sequence knowledge.     

Delayed reinforcement,selective learning and habit reversal

The Psychological Record - Three groups of hungry rats were trained in a T maze position response under conditions of 20-sec. delay of food reinforcement on 0, 50, and 100 per cent of the correct...     

The transition to increased automaticity during finger sequence learning in adult males who stutter

The present study compared the automaticity levels of persons who stutter (PWS) and persons who do not stutter (PNS) on a practiced finger sequencing task under dual task conditions. Automaticity was defined as the amount of attention required for task performance. Twelve PWS and 12 control subjects practiced finger tapping sequences under single and then dual task conditions. Control subjects performed the sequencing task significantly faster and less variably under single versus dual task conditions while PWS' performance was consistently slow and variable (comparable to the dual task performance of control subjects) under both conditions. Control subjects were significantly more accurate on a colour recognition distracter task than PWS under dual task conditions. These results suggested that control subjects transitioned to quick, accurate and increasingly automatic performance on the sequencing task after practice, while PWS did not. Because most stuttering treatment programs for adults include practice and automatization of new motor speech skills, findings of this finger sequencing study and future studies of speech sequence learning may have important implications for how to maximize stuttering treatment effectiveness. Educational objectives: As a result of this activity, the participant will be able to: (1) Define automaticity and explain the importance of dual task paradigms to investigate automaticity; (2) Relate the proposed relationship between motor learning and automaticity as stated by the authors; (3) Summarize the reviewed literature concerning the performance of PWS on dual tasks; and (4) Explain why the ability to transition to automaticity during motor learning may have important clinical implications for stuttering treatment effectiveness.