A Unified Theoretical Framework for Cognitive Sequencing

Role of the basal ganglia in innate and learned behavioural sequences

Integrating individual actions into coherent, organised behavioural units, a process called chunking, is a fundamental, evolutionarily conserved process that renders actions automatic. In vertebrates, evidence points to the basal ganglia - a complex network believed to be involved in action selection - as a key component of action sequence encoding, although the underlying mechanisms are only just beginning to be understood. Central pattern generators control many innate automatic behavioural sequences that form some of the most basic behaviours in an animal's repertoire, and in vertebrates, brainstem and spinal pattern generators are under the control of higher order structures such as the basal ganglia. Evidence suggests that the basal ganglia play a crucial role in the concatenation of simpler behaviours into more complex chunks, in the context of innate behavioural sequences such as chain grooming in rats, as well as sequences in which innate capabilities and learning interact such as birdsong, and sequences that are learned from scratch, such as lever press sequences in operant behaviour. It has been proposed that the role of the striatum, the largest input structure of the basal ganglia, might lie in selecting and allowing the relevant central pattern generators to gain access to the motor system in the correct order, while inhibiting other behaviours. As behaviours become more complex and flexible, the pattern generators seem to become more dependent on descending signals. Indeed, during learning, the striatum itself may adopt the functional characteristics of a higher order pattern generator, facilitated at the microcircuit level by striatal neuropeptides.

A study on pharmaceutical text relationship extraction based on heterogeneous graph neural networks

Effective information extraction of pharmaceutical texts is of great significance for clinical research. The ancient Chinese medicine text has streamlined sentences and complex semantic relationships, and the textual relationships may exist between heterogeneous entities. The current mainstream relationship extraction model does not take into account the associations between entities and relationships when extracting, resulting in insufficient semantic information to form an effective structured representation. In this paper, we propose a heterogeneous graph neural network relationship extraction model adapted to traditional Chinese medicine (TCM) text. First, the given sentence and predefined relationships are embedded by bidirectional encoder representation from transformers (BERT fine-tuned) word embedding as model input. Second, a heterogeneous graph network is constructed to associate words, phrases, and relationship nodes to obtain the hidden layer representation. Then, in the decoding stage, two-stage subject-object entity identification method is adopted, and the identifier adopts a binary classifier to locate the start and end positions of the TCM entities, identifying all the subject-object entities in the sentence, and finally forming the TCM entity relationship group. Through the experiments on the TCM relationship extraction dataset, the results show that the precision value of the heterogeneous graph neural network embedded with BERT is 86.99% and the F1 value reaches 87.40%, which is improved by 8.83% and 10.21% compared with the relationship extraction models CNN, Bert-CNN, and Graph LSTM.

What sticks after statistical learning: The persistence of implicit versus explicit memory traces

Statistical learning is a powerful mechanism that extracts even subtle regularities from our information-dense worlds. Recent theories argue that statistical learning can occur through multiple mechanisms-both the conventionally assumed automatic process that precipitates unconscious learning, and an attention-dependent process that brings regularities into conscious awareness. While this view has gained popularity, there are few empirical dissociations of the hypothesized implicit and explicit forms of statistical learning. Here we provide strong evidence for this dissociation in two ways. First, we show in healthy adults (N = 60) that implicit and explicit traces have divergent consolidation trajectories, with implicit knowledge of structure strengthened over a 24-h period, while precise explicit representations tend to decay. Second, we demonstrate that repeated testing strengthens the retention of explicit representations but that implicit statistical learning is uninfluenced by testing. Together these dissociations provide much needed support for the reconceptualization of statistical learning as a multi-component construct.

Different Markov chains modulate visual stimuli processing in a Go-Go experiment in 2D, 3D, and augmented reality

The introduction of Augmented Reality (AR) has attracted several developments, although the people's experience of AR has not been clearly studied or contrasted with the human experience in 2D and 3D environments. Here, the directional task was applied in 2D, 3D, and AR using simplified stimulus in video games to determine whether there is a difference in human answer reaction time prediction using context stimulus. Testing of the directional task adapted was also done. Research question: Are the main differences between 2D, 3D, and AR able to be predicted using Markov chains? Methods: A computer was fitted with a digital acquisition card in order to record, test and validate the reaction time (RT) of participants attached to the arranged RT for the theory of Markov chain probability. A Markov chain analysis was performed on the participants' data. Subsequently, the way certain factors influenced participants RT amongst the three tasks time on the accuracy of the participants was sought in the three tasks (environments) were statistically tested using ANOVA. Results: Markov chains of order 1 and 2 successfully reproduced the average reaction time by participants in 3D and AR tasks, having only 2D tasks with the variance predicted with the current state. Moreover, a clear explanation of delayed RT in every environment was done. Mood and coffee did not show significant differences in RTs on a simplified videogame. Gender differences were found in 3D, where endogenous directional goals are in 3D, but no gender differences appeared in AR where exogenous AR buttons can explain the larger RT that compensate for the gender difference. Our results suggest that unconscious preparation of selective choices is not restricted to current motor preparation. Instead, decisions in different environments and gender evolve from the dynamics of preceding cognitive activity can fit and improve neurocomputational models.

Cerebellum and Emotion in Social Behavior

Accumulating evidence suggests that the cerebellum plays a crucial role not only in the motor and cognitive domains but also in emotions and social behavior. In the present chapter, after a general introduction on the significance of the emotional components of social behavior, we describe recent efforts to understand the contributions of the cerebellum in social cognition focusing on the emotional and affective aspects. Specifically, starting from the description of the cerebello-cortical networks subtending the social-affective domains, we illustrate the most recent findings on the social cerebellum and the possible functional mechanisms by which the cerebellum modulate social-affective behavior. Finally, we discuss the possible consequences of cerebellar dysfunction in the social-affective domain, focusing on those neurological and psychopathological conditions in which emotional and social behavior difficulties have been described as being associated with cerebellar structural or functional alterations.

Cognition and Daily Life Activities in Stroke: A Network Analysis

Understanding complex dynamics of cognitive constructs and the interplay between cognition and daily life activities is possible through network analysis. The objectives of this study are to characterize the cognition network and identify central cognitive constructs, and identify the cognitive constructs bridging cognition and daily life activities. In 210 community-dwelling stroke survivors, we employed network analysis to characterize the cognition network, identify the central cognitive constructs, and examine the bridge pathway connecting cognition and daily life activities. Cognitive constructs were positively correlated within the network, forming clusters of fluid (e.g., components of active problem-solving), crystallized (e.g., world knowledge), and functional cognition. Central constructs included inhibition, organization, and cognitive flexibility, whereas bridge constructs included organization, sequencing, and inhibition. Central and bridge constructs identified by this study are potential targets for future research and intervention. The emergence of functional cognition as central and bridge constructs may support its inclusion in occupational therapy practice.

Cognitive and Motor Learning in Internally-Guided Motor Skills

Several canonical experimental paradigms (e.g., serial reaction time task, discrete sequence production task, m × n task) have been proposed to study the typical behavioral phenomenon and the nature of learning in sequential keypress tasks. A characteristic feature of most paradigms is that they are representative of externally-specified sequencing—motor tasks where the environment or task paradigm extrinsically provides the sequence of stimuli, i.e., the responses are stimulus-driven. Previous studies utilizing such canonical paradigms have largely overlooked the learning behaviors in a more realistic class of motor tasks that involve internally-guided sequencing—where the sequence of motor actions is self-generated or internally-specified. In this work, we use the grid-navigation task as an instance of internally-guided sequencing to investigate the nature of learning in such paradigms. The participants performed Grid-Sailing Task (GST), which required navigating (by executing sequential keypresses) a 5 × 5 grid from start to goal (SG) position while using a particular key-mapping (KM) among the three cursor-movement directions and the three keyboard buttons. The participants performed two behavioral experiments—Single-SG and Mixed-SG condition. The Single-SG condition required performing GST on a single SG position repeatedly, whereas the Mixed-SG condition involved performing GST using the same KM on two novel SG positions presented in a random, inter-mixed manner. In the Single-SG condition, we show that motor learning contributes to the sequence-specific learning in GST with the repeated execution of the same trajectories. In the Mixed-SG condition, since the participants utilize the previously learned KM, we anticipate a transfer of learning from the Single-SG condition. The acquisition and transfer of a KM-specific internal model facilitates efficient trajectory planning on novel SG conditions. The acquisition of such a KM-specific internal model amounts to trajectory-independent cognitive learning in GST. We show that cognitive learning contributes to the learning in GST by showing transfer-related performance improvements in the Mixed-SG condition. In sum, we show the role of cognitive and motor learning processes in internally-guided sequencing and further make a case for using GST-like grid-navigation paradigms in investigating internally guided skill learning.

Prior context influences motor brain areas in an auditory oddball task and prefrontal cortex multitasking modelling

In this study, the relationship of orienting of attention, motor control and the Stimulus- (SDN) and Goal-Driven Networks (GDN) was explored through an innovative method for fMRI analysis considering all voxels in four experimental conditions: standard target (Goal; G), novel (N), neutral (Z) and noisy target (NG). First, average reaction times (RTs) for each condition were calculated. In the second-level analysis, 'distracted' participants, as indicated by slower RTs, evoked brain activations and differences in both hemispheres' neural networks for selective attention, while the participants, as a whole, demonstrated mainly left cortical and subcortical activations. A context analysis was run in the behaviourally distracted participant group contrasting the trials immediately prior to the G trials, namely one of the Z, N or NG conditions, i.e. Z.G, N.G, NG.G. Results showed different prefrontal activations dependent on prior context in the auditory modality, recruiting between 1 to 10 prefrontal areas. The higher the motor response and influence of the previous novel stimulus, the more prefrontal areas were engaged, which extends the findings of hierarchical studies of prefrontal control of attention and better explains how auditory processing interferes with movement. Also, the current study addressed how subcortical loops and models of previous motor response affected the signal processing of the novel stimulus, when this was presented laterally or simultaneously with the target. This multitasking model could enhance our understanding on how an auditory stimulus is affecting motor responses in a way that is self-induced, by taking into account prior context, as demonstrated in the standard condition and as supported by Pulvinar activations complementing visual findings. Moreover, current BCI works address some multimodal stimulus-driven systems.

How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning

Despite a growing body of research devoted to the study of how humans encode environmental patterns, there is still no clear consensus about the nature of the neurocognitive mechanisms underpinning statistical learning nor what factors constrain or promote its emergence across individuals, species, and learning situations. Based on a review of research examining the roles of input modality and domain, input structure and complexity, attention, neuroanatomical bases, ontogeny, and phylogeny, ten core principles are proposed. Specifically, there exist two sets of neurocognitive mechanisms underlying statistical learning. First, a "suite" of associative-based, automatic, modality-specific learning mechanisms are mediated by the general principle of cortical plasticity, which results in improved processing and perceptual facilitation of encountered stimuli. Second, an attention-dependent system, mediated by the prefrontal cortex and related attentional and working memory networks, can modulate or gate learning and is necessary in order to learn nonadjacent dependencies and to integrate global patterns across time. This theoretical framework helps clarify conflicting research findings and provides the basis for future empirical and theoretical endeavors.

The Implementation of Predictions During Sequencing

Optimal control mechanisms require prediction capabilities. If one cannot predict the consequences of a motor act or behavior, one will continually collide with walls or become a social pariah. "Looking into the future" is thus one of the most important prerequisites for smooth movements and social interactions. To achieve this goal, the brain must constantly predict future events. This principle applies to all domains of information processing, including motor and cognitive control, as well as the development of decision-making skills, theory of mind, and virtually all cognitive processes. Sequencing is suggested to support the predictive capacity of the brain. To recognize that events are related, the brain must discover links among them in the spatiotemporal domain. To achieve this, the brain must often hold one event in working memory and compare it to a second one, and the characteristics of the two must be compared and correctly placed in space and time. Among the different brain structures involved in sequencing, the cerebellum has been proposed to have a central function. We have suggested that the operational mode of the cerebellum is based on "sequence detection" and that this process is crucial for prediction. Patterns of temporally or spatially structured events are conveyed to the cerebellum via the pontine nuclei and compared with actual ones conveyed through the climbing fibers olivary inputs. Through this interaction, data on previously encountered sequences can be obtained and used to generate internal models from which predictions can be made. This mechanism would allow the cerebellum not only to recognize sequences but also to detect sequence violations. Cerebellar pattern detection and prediction would thus be a means to allow feedforward control based on anticipation. We will argue that cerebellar sequencing allows implementation of prediction by setting the correct excitatory levels in defined brain areas to implement the adaptive response for a given pattern of stimuli that embeds sufficient information to be recognized as a previously encountered template. Here, we will discuss results from human and animal studies and correlate them with the present understanding of cerebellar function in cognition and behavior.

Dopaminergic Modulation of Goal-Directed Behavior in a Rodent Model of Attention-Deficit/Hyperactivity Disorder

Aside from its clinical symptoms of inattention, impulsivity and hyperactivity, patients with Attention/Deficit-Hyperactivity Disorder (ADHD) display reward and motivational impairments. These impairments may reflect a deficit in action control, that is, an inability to flexibly adapt behavior to changing consequences. We previously showed that spontaneously hypertensive rats (SHR), an inbred rodent model of ADHD, show impairments in goal-directed action control, and instead are predominated by habits. In this study, we examined the effects of specific dopamine receptor sub-type (D1 and D2) agonists and antagonists on goal-directed behavior in SHR and the normotensive inbred control strain Wistar-Kyoto (WKY) rats. Rats acquired an instrumental response for different-flavored food rewards. A selective-satiety outcome devaluation procedure followed by a choice test in extinction revealed outcome-insensitive habitual behavior in SHR rats. Outcome-sensitive goal-directed behavior was restored in SHR rats following injection prior to the choice test of the dopamine D2 receptor agonist Quinpirole or dopamine D1 receptor antagonist SCH23390, whereas WKY rats showed habitual responding following exposure to these drugs. This novel finding indicates that the core behavioral deficit in ADHD might not be a consequence of dopamine hypofunction, but rather is due to a misbalance between activation of dopamine D1 and D2 receptor pathways that govern action control.

Developmental Lead and/or Prenatal Stress Exposures Followed by Different Types of Behavioral Experience Result in the Divergence of Brain Epigenetic Profiles in a Sex, Brain Region, and Time-Dependent Manner: Implications for Neurotoxicology

Over a lifetime, early developmental exposures to neurocognitive risk factors, such as lead (Pb) exposures and prenatal stress (PS), will be followed by multiple varied behavioral experiences. Pb, PS and behavioral experience can each influence brain epigenetic profiles. Our recent studies show a greater level of complexity, however, as all three factors interact within each sex to generate differential adult variation in global post-translational histone modifications (PTHMs), which may result in fundamentally different consequences for life-long learning and behavioral function. We have reported that PTHM profiles differ by sex, brain region and time point of measurement following developmental exposures to Pb±PS, resulting in different profiles for each unique combination of these parameters. Imposing differing behavioral experience following developmental Pb±PS results in additional divergence of PTHM profiles, again in a sex, brain region and time-dependent manner, further increasing complexity. Such findings underscore the need to link highly localized and variable epigenetic changes along single genes to the highly-integrated brain functional connectome that is ultimately responsible for governing behavioral function. Here we advance the idea that increased understanding may be achieved through iterative reductionist and holistic approaches. Implications for experimental design of animal studies of developmental exposures to neurotoxicants include the necessity of a 'no behavioral experience' group, given that epigenetic changes in response to behavioral testing can confound effects of the neurotoxicant itself. They also suggest the potential utility of the inclusion of salient behavioral experiences as a potential effect modifier in epidemiological studies.

Striatal Neuropeptides Enhance Selection and Rejection of Sequential Actions

The striatum is the primary input nucleus for the basal ganglia, and receives glutamatergic afferents from the cortex. Under the hypothesis that basal ganglia perform action selection, these cortical afferents encode potential “action requests.” Previous studies have suggested the striatum may utilize a mutually inhibitory network of medium spiny neurons (MSNs) to filter these requests so that only those of high salience are selected. However, the mechanisms enabling the striatum to perform clean, rapid switching between distinct actions that form part of a learned action sequence are still poorly understood. Substance P (SP) and enkephalin are neuropeptides co-released with GABA in MSNs preferentially expressing D₁ or D₂ dopamine receptors respectively. SP has a facilitatory effect on subsequent glutamatergic inputs to target MSNs, while enkephalin has an inhibitory effect. Blocking the action of SP in the striatum is also known to affect behavioral transitions. We constructed phenomenological models of the effects of SP and enkephalin, and integrated these into a hybrid model of basal ganglia comprising a spiking striatal microcircuit and rate–coded populations representing other major structures. We demonstrated that diffuse neuropeptide connectivity enhanced the selection of unordered action requests, and that for true action sequences, where action semantics define a fixed structure, a patterning of the SP connectivity reflecting this ordering enhanced selection of actions presented in the correct sequential order and suppressed incorrect ordering. We also showed that selective pruning of SP connections allowed context–sensitive inhibition of specific undesirable requests that otherwise interfered with selection of an action group. Our model suggests that the interaction of SP and enkephalin enhances the contrast between selection and rejection of action requests, and that patterned SP connectivity in the striatum allows the “chunking” of actions and improves selection of sequences. Efficient execution of action sequences may therefore result from a combination of ordered cortical inputs and patterned neuropeptide connectivity within striatum.