Competitive and cooperative interactions between medial temporal and striatal learning systems

The well-worn route revisited: Striatal and hippocampal system contributions to familiar route navigation

Classic research has shown a division in the neuroanatomical structures that support flexible (e.g., short-cutting) and habitual (e.g., familiar route following) navigational behavior, with hippocampal-caudate systems associated with the former and putamen systems with the latter. There is, however, disagreement about whether the neural structures involved in navigation process particular forms of spatial information, such as associations between constellations of cues forming a cognitive map, versus single landmark-action associations, or alternatively, perform particular reinforcement learning algorithms that allow the use of different spatial strategies, so-called model-based (flexible) or model-free (habitual) forms of learning. We sought to test these theories by asking participants (N = 24) to navigate within a virtual environment through a previously learned, 9-junction route with distinctive landmarks at each junction while undergoing functional magnetic resonance imaging (fMRI). In a series of probe trials, we distinguished knowledge of individual landmark-action associations along the route versus knowledge of the correct sequence of landmark-action associations, either by having absent landmarks, or "out-of-sequence" landmarks. Under a map-based perspective, sequence knowledge would not require hippocampal systems, because there are no constellations of cues available for cognitive map formation. Within a learning-based model, however, responding based on knowledge of sequence would require hippocampal systems because prior context has to be utilized. We found that hippocampal-caudate systems were more active in probes requiring sequence knowledge, supporting the learning-based model. However, we also found greater putamen activation in probes where navigation based purely on sequence memory could be planned, supporting models of putamen function that emphasize its role in action sequencing.

Evidence for a competitive relationship between executive functions and statistical learning

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 (NStudy1 = 186, NStudy2 = 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.

Iron content affects age group differences in associative learning-related fMRI activity

Brain regions accumulate different amounts of iron with age, with older adults having higher iron in the basal ganglia (globus pallidus, putamen, caudate) relative to the hippocampus. This has important implications for functional magnetic resonance imaging (fMRI) studies in aging as the presence of iron may influence both neuronal functioning as well as the measured fMRI (BOLD) signal, and these effects will vary across age groups and brain regions. To test this hypothesis, the current study examined the effect of iron on age group differences in task-related activity within each basal nuclei and the hippocampus. Twenty-eight younger and 22 older adults completed an associative learning task during fMRI acquisition. Iron content (QSM, R2*) was estimated from a multi-echo gradient echo sequence. As previously reported, older adults learned significantly less than younger adults and age group differences in iron content were largest in the basal ganglia (putamen, caudate). In the hippocampus (early task stage) and globus pallidus (late task stage), older adults had significantly higher learning-related activity than younger adults both before and after controlling for iron. In the putamen (late task stage), however, younger adults had significantly higher learning-related activity than older adults that was only seen after controlling for iron. These findings support the notion that age-related differences in iron influence both neuronal functioning and the measured fMRI signal in select basal nuclei. Moreover, previous fMRI studies in aging populations may have under-reported age group differences in task-related activity by not accounting for iron within these regions.

The balance of hippocampal and caudate network functional connectivity is associated with episodic memory performance and its decline across adulthood

The hippocampal and caudate networks interact to support episodic memory, but the relationship between hippocampal and caudate connectivity strength and episodic memory is unclear. In general, cognition is optimally supported when connectivity within a functional network dominates connectivity from other networks. For example, episodic memory may be optimally supported when the hippocampal and caudate networks express this pattern of connectivity, consistent with research showing that the two networks are organized competitively. Alternatively, episodic memory may be optimally supported when connectivity in both networks is more balanced, consistent with fMRI reports showing cooperation between networks. Using cross-sectional behavioral and resting state fMRI data from a diverse sample (N = 347; Ages 18-85), I tested the hypothesis that reduced hippocampal and caudate network dominance would be associated with reduced episodic memory across individuals and age. Consistent with this hypothesis, lower caudate network dominance in bilateral thalamic regions was associated with worse episodic memory regardless of age. Age-related differences in caudate network dominance in the pallidum and putamen were also associated with worse episodic memory performance, but through their shared variance with age. I found no evidence that network dominance was related to processing speed or executive function, or that hippocampal network dominance was relate to episodic memory performance. These results show that ongoing biological dynamics between the hippocampal and caudate networks throughout adulthood are related to episodic memory performance and support a growing literature specifying the role of the caudate network in episodic memory.

Declarative Learning Mechanisms Support Declarative but Not Probabilistic Feedback-Based Learning in Children with Developmental Language Disorder (DLD)

Declarative and probabilistic feedback-based learning was evaluated in 8-12-year-old school-age children with developmental language disorder (DLD; n = 14) and age-matched children with typical development (TD; n = 15). Children performed a visual two-choice word-learning task and a visual probabilistic classification task while their electroencephalogram (EEG) was recorded non-invasively from the scalp. Behavioral measures of accuracy and response to feedback, and electrophysiological responses to feedback were collected and compared between the two groups. While behavioral data indicated poorer performance by children with DLD in both learning paradigms, and similar response patterns to positive and negative feedback, electrophysiological data highlighted processing patterns in the DLD group that differed by task. More specifically, in this group, feedback processing in the context of declarative learning, which is known to be dominated by the medial temporal lobe (MTL), was associated with enhanced N170, an event-related brain potential (ERP) associated with MTL activation. The N170 amplitude was found to be correlated with declarative task performance in the DLD group. During probabilistic learning, known to be governed by the striatal-based learning system, the feedback-related negativity (FRN) ERP, which is the product of the cortico-striatal circuit dominated feedback processing. Within the context of probabilistic learning, enhanced N170 was associated with poor learning in the TD group, suggesting that MTL activation during probabilistic learning disrupts learning. These results are interpreted within the context of a proposed feedback parity hypothesis suggesting that in children with DLD, the system that dominates learning (i.e., MTL during declarative learning and the striatum during probabilistic learning) dominates and supports feedback processing.

A neurophysiological perspective on the integration between incidental learning and cognitive control

Adaptive behaviour requires interaction between neurocognitive systems. Yet, the possibility of concurrent cognitive control and incidental sequence learning remains contentious. We designed an experimental procedure of cognitive conflict monitoring that follows a pre-defined sequence unknown to participants, in which either statistical or rule-based regularities were manipulated. We show that participants learnt the statistical differences in the sequence when stimulus conflict was high. Neurophysiological (EEG) analyses confirmed but also specified the behavioural results: the nature of conflict, the type of sequence learning, and the stage of information processing jointly determine whether cognitive conflict and sequence learning support or compete with each other. Especially statistical learning has the potential to modulate conflict monitoring. Cognitive conflict and incidental sequence learning can engage in cooperative fashion when behavioural adaptation is challenging. Three replication and follow-up experiments provide insights into the generalizability of these results and suggest that the interaction of learning and cognitive control is dependent on the multifactorial aspects of adapting to a dynamic environment. The study indicates that connecting the fields of cognitive control and incidental learning is advantageous to achieve a synergistic view of adaptive behaviour.

Intra- and inter-regional dynamics in cortical-striatal-tegmental networks

It is increasingly recognized that networks of brain areas work together to accomplish computational goals. However, functional connectivity networks are not often compared between different behavioral states and across different frequencies of electrical oscillatory signals. In addition, connectivity is always defined as the strength of signal relatedness between two atlas-based anatomical locations. Here, we performed an exploratory analysis using data collectected from high density arrays in the prefrontal cortex (PFC), striatum (STR), and ventral tegmental area (VTA) of male rats. These areas have all been implicated in a wide range of different tasks and computations including various types of memory as well as reward valuation, habit formation and execution, and skill learning. Novel intra-regional clustering analyses identified patterns of spatially restricted, temporally coherent, and frequency specific signals that were reproducible across days and were modulated by behavioral states. Multiple clusters were identified within each anatomical region, indicating a mesoscopic scale of organization. Generalized eigendecomposition (GED) was used to dimension-reduce each cluster to a single component time series. Dense inter-cluster connectivity was modulated by behavioral state, with connectivity becoming reduced when the animals were exposed to a novel object, compared to a baseline condition. Behavior-modulated connectivity changes were seen across the spectrum, with delta, theta, and gamma all being modulated. These results demonstrate the brain's ability to reorganize functionally at both the intra- and inter-regional levels during different behavioral states.

A direct test of competitive versus cooperative episodic-procedural network dynamics in human memory

Classical lesion studies led to a consensus that episodic and procedural memory arises from segregated networks identified with the hippocampus and the caudate nucleus, respectively. Neuroimaging studies, however, show that competitive and cooperative interactions occur between networks during memory tasks. Furthermore, causal experiments to manipulate connectivity between these networks have not been performed in humans. Although nodes common to both networks, such as the precuneus and ventrolateral thalamus, may mediate their interaction, there is no experimental evidence for this. We tested how network-targeted noninvasive brain stimulation affects episodic-procedural network interactions and how these network manipulations affect episodic and procedural memory in healthy young adults. Compared to control (vertex) stimulation, hippocampal network-targeted stimulation increased within-network functional connectivity and hippocampal connectivity with the caudate. It also increased episodic, relative to procedural, memory, and this persisted one week later. The differential effect on episodic versus procedural memory was associated with increased functional connectivity between the caudate, precuneus, and ventrolateral thalamus. These findings provide direct evidence of episodic-procedural network competition, mediated by regions common to both networks. Enhanced hippocampal network connectivity may boost episodic, but decrease procedural, memory by co-opting resources shared between networks.

A Study on the Construction of Emotion Recognition Based on Multimodal Information Fusion in English Learning Cooperative and Competitive Mode

With the development of science and education, English learning has become increasingly important. In the past, English learning was mainly based on missionaries, and students were not very motivated to learn. The purpose of this article is to use the English cooperative model to improve the enthusiasm and initiative of students in learning, and to improve the efficiency of students in learning English. A team learning model based on the game is proposed. This article constructs a cooperative and competitive model of English learning based on multimodal information fusion. The main manifestation is that students form groups in small groups, and there is a competitive relationship between the groups. The competition among students in learning is the common interest of the entire group, so that the overall interests of each student will be more competitive. This article refers to the main body association model in the literature to adjust English grammar, vocabulary, and language perception ability: learn together in team communication to improve students' multifaceted abilities. Finally, a questionnaire was designed. The results show that after changing the English team learning mode and optimizing the English team learning support system of the students' English learning team, the English learning cooperation and competition model based on multimode information fusion proposed in this article can improve the learning effect by 55%-60%. In all English teaching, the two dimensions of professional knowledge and English ability training are not mutually orthogonal and mutually exclusive, but mutually supportive and interdependent. To form an effective teaching model of “student-centered and teacher-led,” active and rich communication and feedback in the classroom are the keys, and they also help to form a gradual teaching and learning cycle.

Age group differences in learning-related activity reflect task stage, not learning stage

Healthy aging is accompanied by declines in the ability to learn associations between events, even when their relationship cannot be described. Previous functional magnetic resonance imaging (fMRI) studies have attributed these implicit associative learning (IAL) deficits to differential engagement of the hippocampus and basal ganglia in older relative to younger adults in early and late stages of the task, respectively. However, these task stages have been confounded with age group differences in learning performance that emerge later and to a lesser degree in older adults. To disentangle the effects of task stage from learning stage (i.e., when there is significant evidence of learning) on age group differences in the neural substrates of IAL, we acquired fMRI data while 28 younger (20.8 ± 2.3 years) and 22 older (73.6 ± 6.8 years) healthy adults completed the Triplets Learning Task, in which the location of two cues predicted the location of a target with high (HF) or low (LF) frequency. When matched for task stage, results revealed worse learning performance and increased IAL-related activity in the hippocampus during the early stage and in the globus pallidum during the late stage in older relative to younger adults. However, when matched for learning stage, there were no significant age group differences in learning performance or IAL-related activity. Thus, although learning emerges later for older adults, they are engaging similar brain regions as younger adults when learning the associations, suggesting that previous reports of age group differences reflect effects of age on task stage, but not learning stage.

How children learn to communicate discriminatively

How do children learn to communicate, and what do they learn? Traditionally, most theories have taken an associative, compositional approach to these questions, supposing children acquire an inventory of form-meaning associations, and procedures for composing / decomposing them; into / from messages in production and comprehension. This paper presents an alternative account of human communication and its acquisition based on the systematic, discriminative approach embodied in psychological and computational models of learning, and formally described by communication theory. It describes how discriminative learning theory offers an alternative perspective on the way that systems of semantic cues are conditioned onto communicative codes, while information theory provides a very different view of the nature of the codes themselves. It shows how the distributional properties of languages satisfy the communicative requirements described in information theory, enabling language learners to align their expectations despite the vastly different levels of experience among language users, and to master communication systems far more abstract than linguistic intuitions traditionally assume. Topics reviewed include morphological development, the acquisition of verb argument structures, and the functions of linguistic systems that have proven to be stumbling blocks for compositional theories: grammatical gender and personal names.

Hippocampal and striatal responses during motor learning are modulated by prefrontal cortex stimulation

While it is widely accepted that motor sequence learning (MSL) is supported by a prefrontal-mediated interaction between hippocampal and striatal networks, it remains unknown whether the functional responses of these networks can be modulated in humans with targeted experimental interventions. The present proof-of-concept study employed a multimodal neuroimaging approach, including functional magnetic resonance (MR) imaging and MR spectroscopy, to investigate whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex can modulate responses in the hippocampus and the basal ganglia during motor learning. Our results indicate that while stimulation did not modulate motor performance nor task-related brain activity, it influenced connectivity patterns within hippocampo-frontal and striatal networks. Stimulation also altered the relationship between the levels of gamma-aminobutyric acid (GABA) in the stimulated prefrontal cortex and learning-related changes in both activity and connectivity in fronto-striato-hippocampal networks. This study provides the first experimental evidence, to the best of our knowledge, that brain stimulation can alter motor learning-related functional responses in the striatum and hippocampus.

Causal role of cross-frequency coupling in distinct components of cognitive control

Cognitive control is the capacity to guide motor and perceptual systems towards abstract goals. High-frequency neural oscillations related to motor activity in the beta band (13-30 Hz) and to visual processing in the gamma band (>30 Hz) are known to be modulated by cognitive control signals. One proposed mechanism for cognitive control is via cross-frequency coupling whereby low frequency network oscillations in prefrontal cortex (delta from 2-3 Hz and theta from 4-8 Hz) guide the expression of motor-related activity in action planning and guide perception-related activity in memory access. However, there is no causal evidence for cross-frequency coupling in these dissociable components of cognitive control. To address this important gap in knowledge, we delivered cross-frequency transcranial alternating current stimulation (CF-tACS) during performance of a task that manipulated cognitive control demands along two dimensions: the abstraction of the rules of the task (nested levels of action selection) that increased delta-beta coupling and the number of rules (set-size held in memory) that increased theta-gamma coupling. As hypothesized, we found that CF-tACS increased the targeted phase-amplitude coupling and modulated task performance of the associated cognitive control component. These findings provide causal evidence that prefrontal cortex orchestrates different components of cognitive control via two different cross-frequency coupling modalities.

On the functional role of striatal and anterior cingulate GABA+ in stimulus-response binding

Successful response selection relies on constantly updating stimulus-response associations. The Theory of Event Coding (TEC) proposes that perception and action are conjointly coded in event files, for which fronto-striatal networks seem to play an important role. However, the exact neurobiochemical mechanism behind event file coding has remained unknown. We investigated the functional relevance of the striatal and anterior cingulate (ACC) GABAergic system using magnetic resonance spectroscopy (MRS). Specifically, the striatal and ACC concentrations of GABA+ referenced against N-acetylaspartate (NAA) were assessed in 35 young healthy males, who subsequently performed a standard event file task. As predicted by the TEC, the participants' responses were modulated by pre-established stimulus response bindings in event files. GABA+/NAA concentrations in the striatum and ACC were not correlated with the overall event binding effect. However, higher GABA+/NAA concentrations in the ACC were correlated with stronger event file binding processes in the early phase of the task. This association disappeared by the end of the task. Taken together, our findings show that striatal GABA+ levels does not seem to modulate event file binding, while ACC GABA+ seem to improve event file binding, but only as long as the participants have not yet gathered sufficient task experience. To the best of our knowledge, this is the first study providing direct evidence for the role of striatal and ACC GABA+ in stimulus-response bindings and thus insights into the brain structure-specific neurobiological aspects of the TEC.