Learning robust cortico-cortical associations with the basal ganglia: An integrative review

Cortical-subcortical neural networks for motor learning and storing sequence memory

Motor sequence learning relies on the synergistic collaboration of multiple brain regions. However, most existing models for motor sequence learning primarily focus on functional-level analyses of sequence memory mechanisms, providing limited neurophysiological insights into how biological neural systems intrinsically encode the ordering of sequential element. Based on physiological and anatomical evidence, this study establishes a cortico-subcortical neuronal network model that differs from existing functional frameworks, emphasizing the neural mechanisms of sequence learning in the brain. The proposed model is biological plausibility and represents a potential mechanism for human sequential learning. It achieves the sequential selection and learning of elements through the cortico-basal ganglia-thalamic circuit, where the working memory function of the prefrontal cortex serves as the basis for Hebbian learning among cortical neurons, enabling the encoding of sequential order. The model successfully reproduces physiological experimental phenomena, validating its biological rationality. Furthermore, we explore the role of cholinergic interneurons in sequence learning, revealing their ability to enhance the robustness of learning. Finally, we demonstrate the model's applicability by deploying it to control a robotic arm in drawing and handwriting tasks, highlighting its adaptability to complex real-world scenarios. These biologically inspired results aim to offer a mechanistic explanation for sequence learning and memory formation in the human brain, providing valuable insights into brain-like control systems and neural networks.

Mindfulness as a Way of Reducing Automatic Constraints on Thought

The number of mindfulness-based wellness promotion programs offered by institutions, by governments, and through mobile apps has grown exponentially in the last decade. However, the scientific understanding of what mindfulness is and how it works is still evolving. Here, I focus on 2 common mindfulness practices: focused attention (FA) and open monitoring (OM). First, I summarize what is known about FA and OM meditation at the psychological level. While they share similar emotion regulation goals, they differ in terms of some of their attention regulation goals. Second, I turn to the neuroscientific literature, showing that FA meditation is associated with consistent activations of cortical control network regions and deactivations of cortical default network regions. In contrast, OM meditation seems to be most consistently associated with changes in the functional connectivity patterns of subcortical structures, including the basal ganglia and cerebellum. Finally, I present a novel account of the mental changes that occur during FA and OM meditation as understood from within the Dynamic Framework of Thought-a conceptual framework that distinguishes between deliberate and automatic constraints on thought. Although deliberate self-regulation processes are often emphasized in scientific and public discourse on mindfulness, here I argue that mindfulness may primarily involve changes in automatic constraints on thought. In particular, I argue that mindfulness reduces the occurrence of automatized sequences of mental states or habits of thought. In this way, mindfulness may increase the spontaneity of thought and reduce automatically constrained forms of thought such as rumination and obsessive thought.

Alterations of subcortical structural volume in pediatric bipolar disorder patients with and without psychotic symptoms

BACKGROUND

Pediatric bipolar disorder (PBD) with psychotic symptoms may predict more severe impairment in social functioning, but the underlying biological mechanisms remain unclear. The aim of this study was to investigate alterations in subcortical structural volume in PBD with and without psychotic symptoms.

METHODS

We recruited 24 psychotic PBD (P-PBD) patients, 24 non-psychotic PBD (NP-PBD) patients, and 18 healthy controls (HCs). All participants underwent scanning with a 3.0 T Siemens Trio scanner. The FreeSurfer 7.4.0 software was employed to calculate the volume of each subcortical structure. An analysis of covariance (ANCOVA) was performed to identify brain regions with significant volume differences among the three groups, and then the inter-group comparisons were calculated. Partial correlation analyses were conducted to identify relationships between subcortical structural volumes and clinical features. Finally, receiver operating characteristic curve (ROC) analysis was employed to verify the capacity to distinguish between P-PBD and NP-PBD, P-PBD and HCs, and NP-PBD and HCs.

RESULTS

ANCOVA revealed significant differences in the volumes of bilateral lateral ventricles, third ventricle, left thalamus, and right pallidum among three groups. Compared with HC, the third ventricle volume was increased in both groups of PBD patients, whereas the left thalamus and right pallidum volumes were decreased, and the bilateral lateral ventricles were enlarged in P-PBD patients. In contrast, only the third ventricle showed further enlargement in the group of P-PBD patients compared with NP-PBD patients. Partial correlation analyses revealed that episode times were associated with the third ventricle volume in P-PBD patients. Furthermore, ROC analyses indicated that volume in the left lateral ventricle exhibited the greatest capacity to distinguish between the P-PBD and NP-PBD, and the third ventricle performed best in distinguishing both the P-PBD group from HCs and the NP-PBD group from HCs. The combined metrics demonstrated greater diagnostic value in two-by-two comparisons.

CONCLUSION

Current research suggests that PBD with psychotic symptoms may have more extensive lateral and third ventricular volume enlargement. Bilateral lateral ventricles may serve as potential neurobiomarkers to distinguish P- PBD patients from NP-PBD patients.

Probabalistic reinforcement learning impairments predict negative symptom severity and risk for conversion in youth at clinical high-risk for psychosis

BACKGROUND

Elucidation of transphasic mechanisms (i.e., mechanisms that occur across illness phases) underlying negative symptoms could inform early intervention and prevention efforts and additionally identify treatment targets that could be effective regardless of illness stage. This study examined whether a key reinforcement learning behavioral pattern characterized by reduced difficulty learning from rewards that have been found to underlie negative symptoms in those with a schizophrenia diagnosis also contributes to negative symptoms in those at clinical high-risk (CHR) for psychosis.

METHODS

CHR youth (n = 46) and 51 healthy controls (CN) completed an explicit reinforcement learning task with two phases. During the acquisition phase, participants learned to select between pairs of stimuli probabilistically reinforced with feedback indicating receipt of monetary gains or avoidance of losses. Following training, the transfer phase required participants to select between pairs of previously presented stimuli during the acquisition phase and novel stimuli without receiving feedback. These test phase pairings allowed for inferences about the contributions of prediction error and value representation mechanisms to reinforcement learning deficits.

RESULTS

In acquisition, CHR participants displayed impaired learning from gains specifically that were associated with greater negative symptom severity. Transfer performance indicated these acquisition deficits were largely driven by value representation deficits. In addition to negative symptoms, this profile of deficits was associated with a greater risk of conversion to psychosis and lower functioning.

CONCLUSIONS

Impairments in positive reinforcement learning, specifically effectively representing reward value, may be an important transphasic mechanism of negative symptoms and a marker of psychosis liability.

Longitudinal markers of cognitive procedural learning in fronto-striatal circuits and putative effects of a BDNF plasticity-related variant

Procedural learning and automatization have widely been studied in behavioral psychology and typically involves a rapid improvement, followed by a plateau in performance throughout repeated training. More recently, brain imaging studies have implicated frontal-striatal brain circuits in skill learning. However, it is largely unknown whether frontal-striatal activation during skill learning and behavioral changes follow a similar learning curve pattern. To address this gap in knowledge, we performed a longitudinal brain imaging study using a procedural working memory (pWM) task with repeated measurements across two weeks to map the temporal dynamics of skill learning. We additionally explored the effect of the BDNF Val66Met polymorphism, a common genetic polymorphism impacting neural plasticity, to further inform the relevance of the identified neural markers. We used linear and exponential modeling to characterize procedural learning by means of learning curves on the behavioral and brain functional level. We show that repeated training led to an exponential decay in a distributed set of brain regions including fronto-striatal circuits, which paralleled the exponential improvement in task performance. In addition, we show that both behavioral and neurofunctional readouts were sensitive to the BDNF Val66Met polymorphism, suggesting less efficient learning in 66Met-allele carriers along with protracted signal decay in frontal and striatal brain regions. Our results extend existing literature by showing the temporal relationship between procedural learning and frontal-striatal brain function and suggest a role of BDNF in mediating neural plasticity for establishing automatized behavior.

Subthalamic nucleus neurons encode syllable sequence and phonetic characteristics during speech

Speech is a complex behavior that can be used to study unique contributions of the basal ganglia to motor control in the human brain. Computational models suggest that the basal ganglia encode either the phonetic content or the sequence of speech elements. To explore this question, we investigated the relationship between phoneme and sequence features of a spoken syllable triplet and the firing rate of subthalamic nucleus (STN) neurons recorded during the implantation of deep brain stimulation (DBS) electrodes in individuals with Parkinson's disease. Patients repeated aloud a random sequence of three consonant-vowel (CV) syllables in response to audio cues. Single-unit extracellular potentials were sampled from the sensorimotor STN; a total of 227 unit recordings were obtained from the left STN of 25 subjects (4 females). Of these, 113 (50%) units showed significant task-related increased firing and 53 (23%) showed decreased firing (t test relative to inter-trial period baseline, P < 0.05). Linear regression analysis revealed that both populations of STN neurons encode phoneme and sequence features of produced speech. Maximal phoneme encoding occurred at the time of phoneme production, suggesting efference copy- or sensory-related processing, rather than speech motor planning (-50 ms and +175 ms relative to CV transition for consonant and vowel encoding, respectively). These findings demonstrate that involvement of the basal ganglia in speaking includes separate single unit representations of speech sequencing and phoneme selection in the STN.NEW & NOTEWORTHY Speech is a unique human behavior that requires dynamic execution of precisely timed and coordinated movements, resulting in intelligible vocalizations. Here, we demonstrate that activity of individual neurons in the subthalamic nucleus (STN) of the basal ganglia encode syllable sequence order and phoneme identity during a speech production task. These findings advance our understanding of neural substrates of human speech and shed light on potential involvement of the STN in complex human behaviors.

Declarative memory supports children's math skills: A longitudinal study

Substantial progress has been made in understanding the neurocognitive underpinnings of learning math. Building on this work, it has been hypothesized that declarative and procedural memory, two domain-general learning and memory systems, play important roles in acquiring math skills. In a longitudinal study, we tested whether in fact declarative and procedural memory predict children's math skills during elementary school years. A sample of 109 children was tested across grades 2, 3 and 4. Linear mixed-effects regression and structural equation modeling revealed the following. First, learning in declarative but not procedural memory was associated with math skills within each grade. Second, declarative but not procedural memory in each grade was related to math skills in all later grades (e.g., declarative memory in grade 2 was related to math skills in grade 4). Sensitivity analyses showed that the pattern of results was robust, except for the longitudinal prediction of later math skills when accounting for stable inter-individual differences via the inclusion of random intercepts. Our findings highlight the foundational role of early domain-general learning and memory in children's acquisition of math.

Subcortical Brain Volumes and Neurocognitive Function in Children With Perinatal HIV Exposure: A Population-Based Cohort Study in South Africa

Background

Children who are HIV-exposed and uninfected (HEU) are at risk for early neurodevelopmental impairment. Smaller basal ganglia nuclei have been reported in neonates who are HEU compared to HIV-unexposed (HU); however, neuroimaging studies outside infancy are scarce. We examined subcortical brain structures and associations with neurocognition in children who are HEU.

Methods

This neuroimaging study was nested within the Drakenstein Child Health Study birth cohort in South Africa. We compared (T1-weighted) magnetic resonance imaging-derived subcortical brain volumes between children who were HEU (n = 70) and HU (n = 92) at age 2-3 years using linear regression. Brain volumes were correlated with neurodevelopmental outcomes measured with the Bayley Scales of Infant and Toddler Development III.

Results

Compared to HU children, on average children who were HEU had 3% lower subcortical grey matter volumes. Analyses of individual structures found smaller volume of the putamen nucleus in the basal ganglia (-5% difference, P = .016) and the hippocampus (-3% difference, P = .044), which held on adjustment for potential confounders (P < .05). Maternal viremia and lower CD4 count in pregnancy were associated with smaller child putamen volumes. Children who were HEU had lower language scores than HU; putamen and hippocampus volumes were positively correlated with language outcomes.

Conclusions

Overall, children who are HEU had a pattern of smaller subcortical volumes in the basal ganglia and hippocampal regions compared to HU children, which correlated with language function. Findings suggest that optimizing maternal perinatal HIV care is important for child brain development. Further studies are needed to investigate underlying mechanisms and long-term outcomes.

Encoding-related Brain Activity Predicts Subsequent Trial-level Control of Proactive Interference in Working Memory

Proactive interference (PI) appears when familiar information interferes with newly acquired information and is a major cause of forgetting in working memory. It has been proposed that encoding of item-context associations might help mitigate familiarity-based PI. Here, we investigate whether encoding-related brain activation could predict subsequent level of PI at retrieval using trial-specific parametric modulation. Participants were scanned with event-related fMRI while performing a 2-back working memory task with embedded 3-back lures designed to induce PI. We found that the ability to control interference in working memory was modulated by level of activation in the left inferior frontal gyrus, left hippocampus, and bilateral caudate nucleus during encoding. These results provide insight to the processes underlying control of PI in working memory and suggest that encoding of temporal context details support subsequent interference control.

The neuroanatomy of developmental language disorder: a systematic review and meta-analysis

Developmental language disorder (DLD) is a common neurodevelopmental disorder with adverse impacts that continue into adulthood. However, its neural bases remain unclear. Here we address this gap by systematically identifying and quantitatively synthesizing neuroanatomical studies of DLD using co-localization likelihood estimation, a recently developed neuroanatomical meta-analytic technique. Analyses of structural brain data (22 peer-reviewed papers, 577 participants) revealed highly consistent anomalies only in the basal ganglia (100% of participant groups in which this structure was examined, weighted by group sample sizes; 99.8% permutation-based likelihood the anomaly clustering was not due to chance). These anomalies were localized specifically to the anterior neostriatum (again 100% weighted proportion and 99.8% likelihood). As expected given the task dependence of activation, functional neuroimaging data (11 peer-reviewed papers, 414 participants) yielded less consistency, though anomalies again occurred primarily in the basal ganglia (79.0% and 95.1%). Multiple sensitivity analyses indicated that the patterns were robust. The meta-analyses elucidate the neuroanatomical signature of DLD, and implicate the basal ganglia in particular. The findings support the procedural circuit deficit hypothesis of DLD, have basic research and translational implications for the disorder, and advance our understanding of the neuroanatomy of language.

Brain volumetric changes in menopausal women and its association with cognitive function: a structured review

The menopausal transition has been proposed to put women at risk for undesirable neurological symptoms, including cognitive decline. Previous studies suggest that alterations in the hormonal milieu modulate brain structures associated with cognitive function. This structured review provides an overview of the relevant studies that have utilized MRI to report volumetric differences in the brain following menopause, and its correlations with the evaluated cognitive functions. We performed an electronic literature search using Medline (Ovid) and Scopus to identify studies that assessed the influence of menopause on brain structure with MRI. Fourteen studies met the inclusion criteria. Brain volumetric differences have been reported most frequently in the frontal and temporal cortices as well as the hippocampus. These regions are important for higher cognitive tasks and memory. Additionally, the deficit in verbal and visuospatial memory in postmenopausal women has been associated with smaller regional brain volumes. Nevertheless, the limited number of eligible studies and cross-sectional study designs warrant further research to draw more robust conclusions.

An fMRI study of inflectional encoding in spoken word production: Role of domain-general inhibition

A major issue concerning inflectional encoding in spoken word production is whether or not regular forms (e.g., past tense walked) are encoded by rule application and irregular forms (e.g., swam) by retrieval from associative memory and inhibition of the regular rule. We used functional magnetic resonance imaging (fMRI) to examine the involvement of domain-general inhibition, thought to be underpinned by right inferior frontal gyrus (IFG), right pre-supplementary motor area (SMA), and right basal ganglia. Participants were presented with infinitive verbs that take either regular or irregular past tense. They switched between producing the past tense of these regular and irregular verbs in one block, and between inflecting or reading these infinitive verbs aloud in another block. As concerns corticobasal areas, compared to reading, inflecting activated left IFG and left preSMA/SMA. Regulars yielded higher activation than irregulars in these frontal areas, both on switch and repeat trials, which did not differ in activation. Switching between inflecting and reading activated left preSMA/SMA. These results indicate that inflectional encoding, and switching between inflecting and reading, engage frontal areas in the left hemisphere, including left preSMA/SMA for both and left IFG for inflecting, without recruiting the domain-general inhibition circuitry in the right hemisphere. We advance an account of inflectional encoding in spoken word production that assumes a distinction between regulars and irregulars, but without engaging domain-general inhibition.

A computational model of prefrontal and striatal interactions in perceptual category learning

Work on multiple-system theories of cognition mostly focused on the systems themselves, while limited work has been devoted to understanding the interactions between systems. Generally, multiple-system theories include a model-based decision system supported by the prefrontal cortex and a model-free decision system supported by the striatum. Here we propose a neurobiological model to describe the interactions between model-based and model-free decision systems in category learning. The proposed model used spiking neurons to simulate activity of the hyperdirect pathway of the basal ganglia. The hyperdirect pathway acts as a gate for the response signal from the model-free system located in the striatum. We propose that the model-free system's response is inhibited when the model-based system is in control of the response. The new model was used to simulate published data from young adults, people with Parkinson's disease, and aged-matched older adults. The simulation results further suggest that system-switching ability may be related to individual differences in executive function. A new behavioral experiment tested this model prediction. The results show that an updating score predicts the ability to switch system in a categorization task. The article concludes with new model predictions and implications of the results for research on system interactions.

GM1 Reduced the Symptoms of Autism Spectrum Disorder by Suppressing α-Syn Through Activating Autophagy

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that cannot be cured. The ASD rat model was developed in this study to demonstrate the role and mechanism of ganglioside GM1 (GM1). Rats were given valproic acid (VPA) to create the ASD rat model. The rats' behaviors were assessed using the Y-maze test, open-field test, three-chamber social interaction test, and Morris water maze test. Relative levels of glutathione (GSH), malondialdehyde (MDA), catalase (CAT), reactive oxygen species (ROS), and superoxide dismutase (SOD) were quantitated using relative kits. Nissl, TUNEL, immunofluorescent, and immunohistochemistry staining techniques were used. GM1 treatment improved the ASD model rats' behavior disorders, including locomotor activity and exploratory behavior, social interaction, learning and memory capacity, and repetitive behavior. Following GM1 injection, striatal neurons grew and apoptosis decreased. GM1 reduced the excessively elevated α-Syn in ASD by encouraging autophagy. The behavior disorder of ASD model rats was exacerbated by autophagy inhibition, which also increased α-Syn levels. By increasing autophagy, GM1 reduced α-Syn levels and, ultimately, improved behavioral abnormalities in ASD model rats.

Evaluating instrumental learning and striatal-cortical functional connectivity in adolescent alcohol and cannabis use

Adolescence is a vulnerable time for the acquisition of substance use disorders, potentially relating to ongoing development of neural circuits supporting instrumental learning. Striatal-cortical circuits undergo dynamic changes during instrumental learning and are implicated in contemporary addiction theory. Human studies have not yet investigated these dynamic changes in relation to adolescent substance use. Here, functional magnetic resonance imaging was used while 135 adolescents without (AUD-CUDLow ) and with significant alcohol (AUDHigh ) or cannabis use disorder symptoms (CUDHigh ) performed an instrumental learning task. We assessed how cumulative experience with instrumental cues altered cue selection preferences and functional connectivity strength between reward-sensitive striatal and cortical regions. Adolescents in AUDHigh and CUDHigh groups were slower in learning to select optimal instrumental cues relative to AUD-CUDLow adolescents. The relatively fast learning observed for AUD-CUDLow adolescents coincided with stronger functional connectivity between striatal and frontoparietal regions during early relative to later periods of task experience, whereas the slower learning for the CUDHigh group coincided with the opposite pattern. The AUDHigh group not only exhibited slower learning but also produced more instrumental choice errors relative to AUD-CUDLow adolescents. For the AUDHigh group, Bayesian analyses evidenced moderate support for no experience-related changes in striatal-frontoparietal connectivity strength during the task. Findings suggest that adolescent cannabis use is related to slowed instrumental learning and delays in peak functional connectivity strength between the striatal-frontoparietal regions that support this learning, whereas adolescent alcohol use may be more closely linked to broader impairments in instrumental learning and a general depression of the neural circuits supporting it.

Motor constellation theory: A model of infants' phonological development

Every normally developing human infant solves the difficult problem of mapping their native-language phonology, but the neural mechanisms underpinning this behavior remain poorly understood. Here, motor constellation theory, an integrative neurophonological model, is presented, with the goal of explicating this issue. It is assumed that infants' motor-auditory phonological mapping takes place through infants' orosensory "reaching" for phonological elements observed in the language-specific ambient phonology, via reference to kinesthetic feedback from motor systems (e.g., articulators), and auditory feedback from resulting speech and speech-like sounds. Attempts are regulated by basal ganglion-cerebellar speech neural circuitry, and successful attempts at reproduction are enforced through dopaminergic signaling. Early in life, the pace of anatomical development constrains mapping such that complete language-specific phonological mapping is prohibited by infants' undeveloped supralaryngeal vocal tract and undescended larynx; constraints gradually dissolve with age, enabling adult phonology. Where appropriate, reference is made to findings from animal and clinical models. Some implications for future modeling and simulation efforts, as well as clinical settings, are also discussed.

Thalamocortical contribution to flexible learning in neural systems

Animal brains evolved to optimize behavior in dynamic environments, flexibly selecting actions that maximize future rewards in different contexts. A large body of experimental work indicates that such optimization changes the wiring of neural circuits, appropriately mapping environmental input onto behavioral outputs. A major unsolved scientific question is how optimal wiring adjustments, which must target the connections responsible for rewards, can be accomplished when the relation between sensory inputs, action taken, and environmental context with rewards is ambiguous. The credit assignment problem can be categorized into context-independent structural credit assignment and context-dependent continual learning. In this perspective, we survey prior approaches to these two problems and advance the notion that the brain's specialized neural architectures provide efficient solutions. Within this framework, the thalamus with its cortical and basal ganglia interactions serves as a systems-level solution to credit assignment. Specifically, we propose that thalamocortical interaction is the locus of meta-learning where the thalamus provides cortical control functions that parametrize the cortical activity association space. By selecting among these control functions, the basal ganglia hierarchically guide thalamocortical plasticity across two timescales to enable meta-learning. The faster timescale establishes contextual associations to enable behavioral flexibility, while the slower one enables generalization to new contexts.

Neural substrates of saccadic adaptation: Plastic changes versus error processing and forward versus backward learning

Previous behavioral, clinical, and neuroimaging studies suggest that the neural substrates of adaptation of saccadic eye movements involve, beyond the central role of the cerebellum, several, still incompletely determined, cortical areas. Furthermore, no neuroimaging study has yet tackled the differences between saccade lengthening ("forward adaptation") and shortening ("backward adaptation") and neither between their two main components, i.e. error processing and oculomotor changes. The present fMRI study was designed to fill these gaps. Blood-oxygen-level-dependent (BOLD) signal and eye movements of 24 healthy volunteers were acquired while performing reactive saccades under 4 conditions repeated in short blocks of 16 trials: systematic target jump during the saccade and in the saccade direction (forward: FW) or in the opposite direction (backward: BW), randomly directed FW or BW target jump during the saccade (random: RND) and no intra-saccadic target jump (stationary: STA). BOLD signals were analyzed both through general linear model (GLM) approaches applied at the whole-brain level and through sensitive Multi-Variate Pattern Analyses (MVPA) applied to 34 regions of interest (ROIs) identified from independent 'Saccade Localizer' functional data. Oculomotor data were consistent with successful induction of forward and backward adaptation in FW and BW blocks, respectively. The different analyses of voxel activation patterns (MVPAs) disclosed the involvement of 1) a set of ROIs specifically related to adaptation in the right occipital cortex, right and left MT/MST, right FEF and right pallidum; 2) several ROIs specifically involved in error signal processing in the left occipital cortex, left PEF, left precuneus, Medial Cingulate cortex (MCC), left inferior and right superior cerebellum; 3) ROIs specific to the direction of adaptation in the occipital cortex and MT/MST (left and right hemispheres for FW and BW, respectively) and in the pallidum of the right hemisphere (FW). The involvement of the left PEF and of the (left and right) occipital cortex were further supported and qualified by the whole brain GLM analysis: clusters of increased activity were found in PEF for the RND versus STA contrast (related to error processing) and in the left (right) occipital cortex for the FW (BW) versus STA contrasts [related to the FW (BW) direction of error and/or adaptation]. The present study both adds complementary data to the growing literature supporting a role of the cerebral cortex in saccadic adaptation through feedback and feedforward relationships with the cerebellum and provides the basis for improving conceptual frameworks of oculomotor plasticity and of its link with spatial cognition.

Learning under social versus nonsocial uncertainty: A meta-analytic approach

Much of the uncertainty that clouds our understanding of the world springs from the covert values and intentions held by other people. Thus, it is plausible that specialized mechanisms that compute learning signals under uncertainty of exclusively social origin operate in the brain. To test this hypothesis, we scoured academic databases for neuroimaging studies involving learning under uncertainty, and performed a meta‐analysis of brain activation maps that compared learning in the face of social versus nonsocial uncertainty. Although most of the brain activations associated with learning error signals were shared between social and nonsocial conditions, we found some evidence for functional segregation of error signals of exclusively social origin during learning in limited regions of ventrolateral prefrontal cortex and insula. This suggests that most behavioral adaptations to navigate social environments are reused from frontal and subcortical areas processing generic value representation and learning, but that a specialized circuitry might have evolved in prefrontal regions to deal with social context representation and strategic action.

Neural correlates of sequence learning in children with developmental dyslexia

Developmental Dyslexia (DD) is a condition in which reading accuracy and/or fluency falls substantially below what is expected based on the individuals age, general level of cognitive ability, and educational opportunities. The procedural circuit deficit hypothesis (PDH) proposes that DD may be largely explained in terms of alterations of the cortico‐basal ganglia procedural memory system (in particular of the striatum) whereas the (hippocampus‐dependent) declarative memory system is intact, and may serve a compensatory role in the condition. The present study was designed to test this hypothesis. Using Magnetic Resonance Imaging, we examined the functional and structural brain correlates of sequence‐specific procedural learning (SL) on the serial reaction time task, in 17 children with DD and 18 typically developing (TD) children. The study was performed over 2 days with a 24‐h interval between sessions. In line with the PDH, the DD group showed less activation of the striatum during the processing of sequential statistical regularities. These alterations predicted the amount of SL at day 2, which in turn explained variance in children's reading fluency. Additionally, reduced hippocampal activation predicted larger SL gains between day 1 and day 2 in the TD group, but not in the DD group. At the structural level, caudate nucleus volume predicted the amount of acquired SL at day 2 in the TD group, but not in the DD group. The findings encourage further research into factors that promote learning in children with DD, including through compensatory mechanisms.

Metastable attractors explain the variable timing of stable behavioral action sequences

The timing of self-initiated actions shows large variability even when they are executed in stable, well-learned sequences. Could this mix of reliability and stochasticity arise within the same neural circuit? We trained rats to perform a stereotyped sequence of self-initiated actions and recorded neural ensemble activity in secondary motor cortex (M2), which is known to reflect trial-by-trial action-timing fluctuations. Using hidden Markov models, we established a dictionary between activity patterns and actions. We then showed that metastable attractors, representing activity patterns with a reliable sequential structure and large transition timing variability, could be produced by reciprocally coupling a high-dimensional recurrent network and a low-dimensional feedforward one. Transitions between attractors relied on correlated variability in this mesoscale feedback loop, predicting a specific structure of low-dimensional correlations that were empirically verified in M2 recordings. Our results suggest a novel mesoscale network motif based on correlated variability supporting naturalistic animal behavior.

Category learning in a recurrent neural network with reinforcement learning

It is known that humans and animals can learn and utilize category information quickly and efficiently to adapt to changing environments, and several brain areas are involved in learning and encoding category information. However, it is unclear that how the brain system learns and forms categorical representations from the view of neural circuits. In order to investigate this issue from the network level, we combine a recurrent neural network with reinforcement learning to construct a deep reinforcement learning model to demonstrate how the category is learned and represented in the network. The model consists of a policy network and a value network. The policy network is responsible for updating the policy to choose actions, while the value network is responsible for evaluating the action to predict rewards. The agent learns dynamically through the information interaction between the policy network and the value network. This model was trained to learn six stimulus-stimulus associative chains in a sequential paired-association task that was learned by the monkey. The simulated results demonstrated that our model was able to learn the stimulus-stimulus associative chains, and successfully reproduced the similar behavior of the monkey performing the same task. Two types of neurons were found in this model: one type primarily encoded identity information about individual stimuli; the other type mainly encoded category information of associated stimuli in one chain. The two types of activity-patterns were also observed in the primate prefrontal cortex after the monkey learned the same task. Furthermore, the ability of these two types of neurons to encode stimulus or category information was enhanced during this model was learning the task. Our results suggest that the neurons in the recurrent neural network have the ability to form categorical representations through deep reinforcement learning during learning stimulus-stimulus associations. It might provide a new approach for understanding neuronal mechanisms underlying how the prefrontal cortex learns and encodes category information.

The Dopamine System and Automatization of Movement Sequences: A Review With Relevance for Speech and Stuttering

The last decades of research have gradually elucidated the complex functions of the dopamine system in the vertebrate brain. The multiple roles of dopamine in motor function, learning, attention, motivation, and the emotions have been difficult to reconcile. A broad and detailed understanding of the physiology of cerebral dopamine is of importance in understanding a range of human disorders. One of the core functions of dopamine involves the basal ganglia and the learning and execution of automatized sequences of movements. Speech is one of the most complex and highly automatized sequential motor behaviors, though the exact roles that the basal ganglia and dopamine play in speech have been difficult to determine. Stuttering is a speech disorder that has been hypothesized to be related to the functions of the basal ganglia and dopamine. The aim of this review was to provide an overview of the current understanding of the cerebral dopamine system, in particular the mechanisms related to motor learning and the execution of movement sequences. The primary aim was not to review research on speech and stuttering, but to provide a platform of neurophysiological mechanisms, which may be utilized for further research and theoretical development on speech, speech disorders, and other behavioral disorders. Stuttering and speech are discussed here only briefly. The review indicates that a primary mechanism for the automatization of movement sequences is the merging of isolated movements into chunks that can be executed as units. In turn, chunks can be utilized hierarchically, as building blocks of longer chunks. It is likely that these mechanisms apply also to speech, so that frequent syllables and words are produced as motor chunks. It is further indicated that the main learning principle for sequence learning is reinforcement learning, with the phasic release of dopamine as the primary teaching signal indicating successful sequences. It is proposed that the dynamics of the dopamine system constitute the main neural basis underlying the situational variability of stuttering.

A Process-Oriented View of Procedural Memory Can Help Better Understand Tourette's Syndrome

Tourette's syndrome (TS) is a neurodevelopmental disorder characterized by repetitive movements and vocalizations, also known as tics. The phenomenology of tics and the underlying neurobiology of the disorder have suggested that the altered functioning of the procedural memory system might contribute to its etiology. However, contrary to the robust findings of impaired procedural memory in neurodevelopmental disorders of language, results from TS have been somewhat mixed. We review the previous studies in the field and note that they have reported normal, impaired, and even enhanced procedural performance. These mixed findings may be at least partially be explained by the diversity of the samples in both age and tic severity, the vast array of tasks used, the low sample sizes, and the possible confounding effects of other cognitive functions, such as executive functions, working memory or attention. However, we propose that another often overlooked factor could also contribute to the mixed findings, namely the multiprocess nature of the procedural system itself. We propose that a process-oriented view of procedural memory functions could serve as a theoretical framework to help integrate these varied findings. We discuss evidence suggesting heterogeneity in the neural regions and their functional contributions to procedural memory. Our process-oriented framework can help to deepen our understanding of the complex profile of procedural functioning in TS and atypical development in general.

Neural dynamics underlying the acquisition of distinct auditory category structures

Despite the multidimensional and temporally fleeting nature of auditory signals we quickly learn to assign novel sounds to behaviorally relevant categories. The neural systems underlying the learning and representation of novel auditory categories are far from understood. Current models argue for a rigid specialization of hierarchically organized core regions that are fine-tuned to extracting and mapping relevant auditory dimensions to meaningful categories. Scaffolded within a dual-learning systems approach, we test a competing hypothesis: the spatial and temporal dynamics of emerging auditory-category representations are not driven by the underlying dimensions but are constrained by category structure and learning strategies. To test these competing models, we used functional Magnetic Resonance Imaging (fMRI) to assess representational dynamics during the feedback-based acquisition of novel non-speech auditory categories with identical dimensions but differing category structures: rule-based (RB) categories, hypothesized to involve an explicit sound-to-rule mapping network, and information integration (II) based categories, involving pre-decisional integration of dimensions via a procedural-based sound-to-reward mapping network. Adults were assigned to either the RB (n = 30, 19 females) or II (n = 30, 22 females) learning tasks. Despite similar behavioral learning accuracies, learning strategies derived from computational modeling and involvements of corticostriatal systems during feedback processing differed across tasks. Spatiotemporal multivariate representational similarity analysis revealed an emerging representation within an auditory sensory-motor pathway exclusively for the II learning task, prominently involving the superior temporal gyrus (STG), inferior frontal gyrus (IFG), and posterior precentral gyrus. In contrast, the RB learning task yielded distributed neural representations within regions involved in cognitive-control and attentional processes that emerged at different time points of learning. Our results unequivocally demonstrate that auditory learners' neural systems are highly flexible and show distinct spatial and temporal patterns that are not dimension-specific but reflect underlying category structures and learning strategies.

Computational benefits of structural plasticity, illustrated in songbirds

The plasticity of nervous systems allows animals to quickly adapt to a changing environment. In particular, the structural plasticity of brain networks is often critical to the development of the central nervous system and the acquisition of complex behaviors. As an example, structural plasticity is central to the development of song-related brain circuits and may be critical for song acquisition in juvenile songbirds. Here, we review current evidences for structural plasticity and their significance from a computational point of view. We start by reviewing evidence for structural plasticity across species and categorizing them along the spatial axes as well as the along the time course during development. We introduce the vocal learning circuitry in zebra finches, as a useful example of structural plasticity, and use this specific case to explore the possible contributions of structural plasticity to computational models. Finally, we discuss current modeling studies incorporating structural plasticity and unexplored questions which are raised by such models.

A multi-representation approach to the contextual interference effect: effects of sequence length and practice

The present study investigated the long-term benefit of Random-Practice (RP) over Blocked-Practice (BP) within the contextual interference (CI) effect for motor learning. We addressed the extent to which motor sequence length and practice amount factors moderate the CI effect given that previous reports, often in applied research, have reported no long-term advantage from RP. Based on predictions arising from the Cognitive framework of Sequential Motor Behavior (C-SMB) and using the Discrete Sequence Production (DSP) task, two experiments were conducted to compare limited and extended practice amounts of 4- and 7-key sequences under RP and BP schedules. Twenty-four-hour delayed retention performance confirmed the C-SMB prediction that the CI-effect occurs only with short sequences that receive little practice. The benefit of RP with limited practice was associated with overnight motor memory consolidation. Further testing with single-stimulus as well as novel and unstructured (i.e., random) sequences indicated that limited practice under RP schedules enhances both reaction and chunking modes of sequence execution with the latter mode benefitting from the development of implicit and explicit forms of sequence representation. In the case of 7-key sequences, extended practice with RP and BP schedules provided for equivalent development of sequence representations. Higher explicit awareness of sequence structures was associated with faster completion of practiced but also of novel and unstructured sequences.

Function and Regulation of ALDH1A1-Positive Nigrostriatal Dopaminergic Neurons in Motor Control and Parkinson's Disease

Dopamine is an important chemical messenger in the brain, which modulates movement, reward, motivation, and memory. Different populations of neurons can produce and release dopamine in the brain and regulate different behaviors. Here we focus our discussion on a small but distinct group of dopamine-producing neurons, which display the most profound loss in the ventral substantia nigra pas compacta of patients with Parkinson's disease. This group of dopaminergic neurons can be readily identified by a selective expression of aldehyde dehydrogenase 1A1 (ALDH1A1) and accounts for 70% of total nigrostriatal dopaminergic neurons in both human and mouse brains. Recently, we presented the first whole-brain circuit map of these ALDH1A1-positive dopaminergic neurons and reveal an essential physiological function of these neurons in regulating the vigor of movement during the acquisition of motor skills. In this review, we first summarize previous findings of ALDH1A1-positive nigrostriatal dopaminergic neurons and their connectivity and functionality, and then provide perspectives on how the activity of ALDH1A1-positive nigrostriatal dopaminergic neurons is regulated through integrating diverse presynaptic inputs and its implications for potential Parkinson's disease treatment.

More dynamical and more symbiotic: Cortico-striatal models of resolve, suppression, and routine habit

I extend Ainslie's core claims with three cortico-striatal models that respectively subserve the key constructs of resolve, suppression, and routine habit. I show that these models suggest a more dynamical and symbiotic relation among the constructs: there are more ways they interact to reinforce willpower, and the temporal dimension of the interactions can often determine the effectiveness of the reinforcement.

The impact of training methodology and representation on rule-based categorization: An fMRI study

Hélie, Shamloo, & Ell (2017) showed that regular classification learning instructions (A/B) promote between-category knowledge in rule-based categorization whereas conceptual learning instructions (YES/NO) promote learning within-category knowledge with the same categories. Here we explore how these tasks affect brain activity using fMRI. Participants learned two sets of two categories. Computational models were fit to the behavioral data to determine the type of knowledge learned by each participant. fMRI contrasts were computed to compare BOLD signal between the tasks and between the types of knowledge. The results show that participants in the YES/NO task had more activity in the pre-supplementary motor area, prefrontal cortex, and the angular/supramarginal gyrus. These brain areas are related to working memory and part of the dorsal attention network, which showed increased task-based functional connectivity with the medial temporal lobes. In contrast, participants in the A/B task had more activity in the thalamus and caudate. These results suggest that participants in the YES/NO task used bivalent rules and may have treated each contextual question as a separate task, switching task each time the question changed. Activity in the A/B condition was more consistent with participants applying direct Stimulus → Response rules. With regards to knowledge representation, there was a large shared network of brain areas, but participants learning between-category information showed additional posterior parietal activity, which may be related to the inhibition of incorrect motor programs.

A global framework for a systemic view of brain modeling

The brain is a complex system, due to the heterogeneity of its structure, the diversity of the functions in which it participates and to its reciprocal relationships with the body and the environment. A systemic description of the brain is presented here, as a contribution to developing a brain theory and as a general framework where specific models in computational neuroscience can be integrated and associated with global information flows and cognitive functions. In an enactive view, this framework integrates the fundamental organization of the brain in sensorimotor loops with the internal and the external worlds, answering four fundamental questions (what, why, where and how). Our survival-oriented definition of behavior gives a prominent role to pavlovian and instrumental conditioning, augmented during phylogeny by the specific contribution of other kinds of learning, related to semantic memory in the posterior cortex, episodic memory in the hippocampus and working memory in the frontal cortex. This framework highlights that responses can be prepared in different ways, from pavlovian reflexes and habitual behavior to deliberations for goal-directed planning and reasoning, and explains that these different kinds of responses coexist, collaborate and compete for the control of behavior. It also lays emphasis on the fact that cognition can be described as a dynamical system of interacting memories, some acting to provide information to others, to replace them when they are not efficient enough, or to help for their improvement. Describing the brain as an architecture of learning systems has also strong implications in Machine Learning. Our biologically informed view of pavlovian and instrumental conditioning can be very precious to revisit classical Reinforcement Learning and provide a basis to ensure really autonomous learning.

Altered Prefrontal-Basal Ganglia Effective Connectivity in Patients With Poststroke Cognitive Impairment

We investigated the association between poststroke cognitive impairment and a specific effective network connectivity in the prefrontal-basal ganglia circuit. The resting-state effective connectivity of this circuit was modeled by employing spectral dynamic causal modeling in 11 poststroke patients with cognitive impairment (PSCI), 8 poststroke patients without cognitive impairment (non-PSCI) at baseline and 3-month follow-up, and 28 healthy controls. Our results showed that different neuronal models of effective connectivity in the prefrontal-basal ganglia circuit were observed among healthy controls, non-PSCI, and PSCI patients. Additional connected paths (extra paths) appeared in the neuronal models of stroke patients compared with healthy controls. Moreover, changes were detected in the extra paths of non-PSCI between baseline and 3-month follow-up poststroke, indicating reorganization in the ipsilesional hemisphere and suggesting potential compensatory changes in the contralesional hemisphere. Furthermore, the connectivity strengths of the extra paths from the contralesional ventral anterior nucleus of thalamus to caudate correlated significantly with cognitive scores in non-PSCI and PSCI patients. These suggest that the neuronal model of effective connectivity of the prefrontal-basal ganglia circuit may be sensitive to stroke-induced cognitive decline, and it could be a biomarker for poststroke cognitive impairment 3 months poststroke. Importantly, contralesional brain regions may play an important role in functional compensation of cognitive decline.

Cognitive Capacity Limits Are Remediated by Practice-Induced Plasticity between the Putamen and Pre-Supplementary Motor Area

Humans show striking limitations in information processing when multitasking yet can modify these limits with practice. Such limitations have been linked to a frontal-parietal network, but recent models of decision-making implicate a striatal-cortical network. We adjudicated these accounts by investigating the circuitry underpinning multitasking in 100 human individuals and the plasticity caused by practice. We observed that multitasking costs, and their practice-induced remediation, are best explained by modulations in information transfer between the striatum and the cortical areas that represent stimulus-response mappings. Specifically, our results support the view that multitasking stems at least in part from taxation in information sharing between the putamen and pre-supplementary motor area (pre-SMA). Moreover, we propose that modulations to information transfer between these two regions leads to practice-induced improvements in multitasking.

Distinct Connectivity and Functionality of Aldehyde Dehydrogenase 1a1-Positive Nigrostriatal Dopaminergic Neurons in Motor Learning

Parkinson's disease causes the most profound loss of the aldehyde dehydrogenase 1A1-positive (ALDH1A1⁺) nigrostriatal dopaminergic neuron (nDAN) subpopulation. The connectivity and functionality of ALDH1A1⁺ nDANs, however, remain poorly understood. Here, we show in rodent brains that ALDH1A1⁺ nDANs project predominantly to the rostral dorsal striatum, from which they also receive most monosynaptic inputs, indicating extensive reciprocal innervations with the striatal spiny projection neurons (SPNs). Functionally, genetic ablation of ALDH1A1⁺ nDANs causes severe impairments in motor skill learning, along with a reduction in high-speed walking. While dopamine replacement therapy accelerated walking speed, it failed to improve motor skill learning in ALDH1A1⁺ nDAN-ablated mice. Altogether, our study provides a comprehensive whole-brain connectivity map and reveals a key physiological function of ALDH1A1⁺ nDANs in motor skill acquisition, suggesting the motor learning processes require ALDH1A1⁺ nDANs to integrate diverse presynaptic inputs and supply dopamine with dynamic precision.

Discrete finger sequences are widely represented in human striatum

Research in primates and rodents ascribes the striatum a critical role in integrating elementary movements into unitary action sequences through reinforcement-based learning. Yet it remains to be shown whether the human striatum represents action sequence-specific information. Young right-handed volunteers underwent functional magnetic resonance imaging while they performed four discrete finger sequences with their right hand, consisting of five button presses. Specific finger sequences could be discriminated based on the distributed activity patterns in left and right striatum, but not by average differences in single-voxel activity. Multiple bilateral clusters in putamen and caudate nucleus belonging to motor, associative, parietal and limbic territories contributed to classification sensitivity. The results show that individual finger movement sequences are widely represented in human striatum, supporting functional integration rather than segregation. The findings are compatible with the idea that the basal ganglia simultaneously integrate motor, associative and limbic aspects in the control of complex overlearned behaviour.

Psychotherapy in pain management: New viewpoints and treatment targets based on a brain theory

The current paper provides an explanation of neurophysiological pain processing based the Dimensional Systems Model (DSM), a theory of higher cortical functions in which the cortical column is considered the binary digit for all cortical functions. Within the discussion, novel views on the roles of the basal ganglia, cerebellum, and cingulate cortex are presented. Additionally, an applied Clinical Biopsychological Model (CBM) based on the DSM will be discussed as related to psychological treatment with chronic pain patients. Three specific areas that have not been adequately addressed in the psychological treatment of chronic pain patients will be discussed based on the CBM. The treatment approaches have been effectively used in a clinical setting. Conclusions focus on a call for researchers and clinicians to fully evaluate the value of both the DSM and CBM.

Psychomotor Slowing in Schizophrenia: Implications for Endophenotype and Biomarker Development

Motor abnormalities (e.g., dyskinesia, psychomotor slowing, neurological soft signs) are core features of schizophrenia that occur independent of drug treatment and are associated with the genetic vulnerability and pathophysiology for the illness. Among this list, psychomotor slowing in particular is one of the most consistently observed and robust findings in the field. Critically, psychomotor slowing may serve as a uniquely promising endophenotype and/or biomarker for schizophrenia considering it is frequently observed in those with genetic vulnerability for the illness, predicts transition in subjects at high-risk for the disorder, and is associated with symptoms and recovery in patients. The purpose of the present review is to provide an overview of the history of psychomotor slowing in psychosis, discuss its possible neural underpinnings, and review the current literature supporting slowing as a putative endophenotype and/or biomarker for the illness. This review summarizes substantial evidence from a diverse array of methodologies and research designs that supports the notion that psychomotor slowing not only reflects genetic vulnerability, but is also sensitive to disease processes and the pathophysiology of the illness. Furthermore, there are unique deficits across the cognitive (prefix "psycho") and motor execution (root word "motor") aspects of slowing, with cognitive processes such as planning and response selection being particularly affected. These findings suggest that psychomotor slowing may serve as a promising endophenotype and biomarker for schizophrenia that may prove useful for identifying individuals at greatest risk and tracking the course of the illness and recovery.

Previously Reward-Associated Stimuli Capture Spatial Attention in the Absence of Changes in the Corresponding Sensory Representations as Measured with MEG

Studies of selective attention typically consider the role of task goals or physical salience, but attention can also be captured by previously reward-associated stimuli, even if they are currently task irrelevant. One theory underlying this value-driven attentional capture (VDAC) is that reward-associated stimulus representations undergo plasticity in sensory cortex, thereby automatically capturing attention during early processing. To test this, we used magnetoencephalography to probe whether stimulus location and identity representations in sensory cortex are modulated by reward learning. We furthermore investigated the time course of these neural effects, and their relationship to behavioral VDAC. Male and female human participants first learned stimulus-reward associations. Next, we measured VDAC in a separate task by presenting these stimuli in the absence of reward contingency and probing their effects on the processing of separate target stimuli presented at different time lags. Using time-resolved multivariate pattern analysis, we found that learned value modulated the spatial selection of previously rewarded stimuli in posterior visual and parietal cortex from ∼260 ms after stimulus onset. This value modulation was related to the strength of participants' behavioral VDAC effect and persisted into subsequent target processing. Importantly, learned value did not influence cortical signatures of early processing (i.e., earlier than ∼200 ms); nor did it influence the decodability of stimulus identity. Our results suggest that VDAC is underpinned by learned value signals that modulate spatial selection throughout posterior visual and parietal cortex. We further suggest that VDAC can occur in the absence of changes in early visual processing in cortex.SIGNIFICANCE STATEMENT Attention is our ability to focus on relevant information at the expense of irrelevant information. It can be affected by previously learned but currently irrelevant stimulus-reward associations, a phenomenon termed "value-driven attentional capture" (VDAC). The neural mechanisms underlying VDAC remain unclear. It has been speculated that reward learning induces visual cortical plasticity, which modulates early visual processing to capture attention. Although we find that learned value modulates spatial signals in visual cortical areas, an effect that correlates with VDAC, we find no relevant signatures of changes in early visual processing in cortex.

The Simon effect in a discrete sequence production task: Key-specific stimuli cannot be ignored due to attentional capture

Two experiments examined whether practicing discrete key pressing sequences eventually leads to a disregard of the key-specific stimuli, as suggested by sequence learning models, or whether these stimuli continue to be relied upon because the associated luminance increase attracts visuospatial attention. Participants practiced two sequences by reacting to two fixed series of seven letter stimuli, each displayed at a location that did or did not correspond with the required response location. Stimulus use was indicated by a Simon effect in that key presses were slowed when stimulus and key locations did not correspond. Experiment 1 demonstrated that letter stimuli continued to be used as the Simon effect occurred with each sequence element, and this remained quite stable across practice and did not differ for familiar and unfamiliar sequences. Experiment 2 showed that the Simon effect remained present even with meaningless stimuli that were often even harmful. These findings suggest that even in motor sequences that can be executed without element-specific stimuli attention attraction enforces stimulus use. The data further supported the assumptions that S-R translation and sequencing systems are racing to trigger individual responses, and that explicit sequence representations include spatial and verbal knowledge.

A unified model of rule-set learning and selection

The ability to focus on relevant information and ignore irrelevant information is a fundamental part of intelligent behavior. It not only allows faster acquisition of new tasks by reducing the size of the problem space but also allows for generalizations to novel stimuli. Task-switching, task-sets, and rule-set learning are all intertwined with this ability. There are many models that attempt to individually describe these cognitive abilities. However, there are few models that try to capture the breadth of these topics in a unified model and fewer still that do it while adhering to the biological constraints imposed by the findings from the field of neuroscience. Presented here is a comprehensive model of rule-set learning and selection that can capture the learning curve results, error-type data, and transfer effects found in rule-learning studies while also replicating the reaction time data and various related effects of task-set and task-switching experiments. The model also factors in many disparate neurological findings, several of which are often disregarded by similar models.

Involvement of the Cortico-Basal Ganglia-Thalamocortical Loop in Developmental Stuttering

Stuttering is a complex neurodevelopmental disorder that has to date eluded a clear explication of its pathophysiological bases. In this review, we utilize the Directions Into Velocities of Articulators (DIVA) neurocomputational modeling framework to mechanistically interpret relevant findings from the behavioral and neurological literatures on stuttering. Within this theoretical framework, we propose that the primary impairment underlying stuttering behavior is malfunction in the cortico-basal ganglia-thalamocortical (hereafter, cortico-BG) loop that is responsible for initiating speech motor programs. This theoretical perspective predicts three possible loci of impaired neural processing within the cortico-BG loop that could lead to stuttering behaviors: impairment within the basal ganglia proper; impairment of axonal projections between cerebral cortex, basal ganglia, and thalamus; and impairment in cortical processing. These theoretical perspectives are presented in detail, followed by a review of empirical data that make reference to these three possibilities. We also highlight any differences that are present in the literature based on examining adults versus children, which give important insights into potential core deficits associated with stuttering versus compensatory changes that occur in the brain as a result of having stuttered for many years in the case of adults who stutter. We conclude with outstanding questions in the field and promising areas for future studies that have the potential to further advance mechanistic understanding of neural deficits underlying persistent developmental stuttering.

Human body odor increases familiarity for faces during encoding-retrieval task

Odors can increase memory performance when presented as context during both encoding and retrieval phases. Since information from different sensory modalities is integrated into a unified conceptual knowledge, we hypothesize that the social information from body odors and faces would be integrated during encoding. The integration of such social information would enhance retrieval more so than when the encoding occurs in the context of common odors. To examine this hypothesis and to further explore the underlying neural correlates of this behavior, we have conducted a functional magnetic resonance imaging study in which participants performed an encoding‐retrieval memory task for faces during the presentation of common odor, body odor or clean air. At the behavioral level, results show that participants were less biased and faster in recognizing faces when presented in concomitance with the body odor compared to the common odor. At the neural level, the encoding of faces in the body odor condition, compared to common odor and clean air conditions, showed greater activation in areas related to associative memory (dorsolateral prefrontal cortex), odor perception and multisensory integration (orbitofrontal cortex). These results suggest that face and body odor information were integrated and as a result, participants were faster in recognizing previously presented material.

The Neurocognition of Developmental Disorders of Language

Developmental disorders of language include developmental language disorder, dyslexia, and motor-speech disorders such as articulation disorder and stuttering. These disorders have generally been explained by accounts that focus on their behavioral rather than neural characteristics; their processing rather than learning impairments; and each disorder separately rather than together, despite their commonalities and comorbidities. Here we update and review a unifying neurocognitive account—the Procedural circuit Deficit Hypothesis (PDH). The PDH posits that abnormalities of brain structures underlying procedural memory (learning and memory that rely on the basal ganglia and associated circuitry) can explain numerous brain and behavioral characteristics across learning and processing, in multiple disorders, including both commonalities and differences. We describe procedural memory, examine its role in various aspects of language, and then present the PDH and relevant evidence across language-related disorders. The PDH has substantial explanatory power, and both basic research and translational implications.

Basal ganglia volumetric changes in psychotic spectrum disorders

BACKGROUND

Basal ganglia are particularly important for understanding the pathobiology of psychosis given their key roles in dopaminergic neurotransmission which are associated with psychotic symptoms and one of the target sites of antipsychotic drugs. Psychotic symptoms are prevalent in both schizophrenia (SZ) and bipolar disorder (BD). Although the components of basal ganglia are implicated in psychosis, comparative structural changes of components of the basal ganglia between SZ and BD are less clear after disentanglement of clinical effects of antipsychotic dose, duration and severity of illness.

METHODS

In this study, we examined the morphology of the basal ganglia in 326 subjects comprising of 45 patients of BD type I with psychotic symptoms, 97 first-episode SZ (FE-SZ) patients, 86 non-first-episode chronic SZ (NFE-SZ) patients, in comparison with 98 healthy controls (HC).

RESULTS

Results showed increased volumes in subregions of caudate, putamen, and pallidum in chronic SZ patients compared with HC after controlling for age, gender, and total intracranial volume. No change was found between FE-SZ patients, psychotic BD patients, and HC. Furthermore, hierarchical regressions showed that the dosage of antipsychotics had a significant contribution to basal ganglia volumetric enlargement in NFE-SZ after controlling for the effects of age, gender, total intracranial volume, age at illness onset, as well as illness duration and severity.

LIMITATIONS

Lack of information about the cumulative history of exposure to medication for all the three groups of patients is a major limitation in our study.

CONCLUSIONS

There are distinct basal ganglia structural changes in SZ and psychotic BD. Basal ganglia are enlarged in chronic SZ but not in FE-SZ and BD and this enlargement is significantly associated with antipsychotic dosage over and beyond the effects of illness duration and severity.

Altered amplitude of low-frequency fluctuation in basal ganglia correlates to pulmonary ventilation function in COPD patients: A resting-state fMRI study

INTRODUCTION

Patients under chronic obstructive pulmonary disease (COPD) has been reported to be associated with a higher prevalence of cognitive impairment (CI). However, it is still largely unknown whether the aberrant resting-state spontaneous neuronal activity pattern reflected by the amplitude of low-frequency fluctuation (ALFF) analysis will be associated with the CI in COPD patients.

MATERIALS

A total of 28 COPD patients and 26 healthy controls were enrolled in this study. Of all the subjects, structural and functional MRI data, spirometry tests performance and neuropsychological assessments of different cognitive domains were collected. Voxel-based two-sample t tests were used to detect brain regions showing differences in the ALFF value between COPD patients and healthy controls. An additional fMRI runs with supplementary oxygen delivery were employed to explore the impact of elevated partial pressure of oxygen (PaO₂ ) or moderate hyperoxia on ALFF in COPD patients and healthy controls respectively.

RESULTS

More extensive white matter lesion was detected in COPD patients. COPD patients exhibit decreased ALFF value in bilateral basal ganglia areas and right thalamus, and aberrant ALFF value is correlated with PaO₂ and pulmonary ventilation function (FEV1%pred). COPD patients performed worse in the Digit Span Test (reverse), Digit Symbol Substitution Test, Trail-making test (A and B) than controls. After supplementary oxygen inhalation, the ALFF value of basal ganglia and right thalamus significantly increased in the controls, but not in the COPD patients.

CONCLUSIONS

COPD patients mainly exhibit impaired executive function but not long-term memory in cognitive function assessment. Aberrant ALFF alteration in the deep brain may be directly related to lower PaO₂ in COPD patients.

Basal Ganglia-Cortical Circuit Disruption in Subcortical Silent Lacunar Infarcts

To investigate the alterations of basal ganglia (BG)-cortical structural and functional connectivity induced by subcortical silent lacunar infarct (SLI), and their associations with cognitive impairment in SLI subjects. All participants were recruited from communities, including 30 subcortical SLIs and 30 age-, gender-, and education-matched healthy controls. The structural and functional connectivity of BG-cortical circuits using diffusion and resting-state functional magnetic resonance imaging data were obtained. Diffusion abnormalities of the white matter tracts connecting the BG and cortical areas were observed in SLI subjects, including the BG-lateral frontal, BG-orbital frontal, and BG-insula tracts. Multiple regions showed a reduced BG-cortical functional connectivity in SLI patients, including direct connectivities with the BG, such as the BG-limbic, BG-insula, and BG-frontal connectivities, and others that showed no direct causation with the BG, such as the insula-limbic, insula-parietal, and frontal-parietal connectivities. Coupling of structural and functional BG-cortical connectivity was observed in healthy controls but not in SLI patients. Significant correlations between structural and functional BG-cortical connectivity and cognitive performance were demonstrated in SLI patients, indicating the potential use of BG-cortical connectivities as MRI biomarkers to assess cognitive impairment. These findings suggest that subcortical SLIs can impair BG-cortical circuits, and these changes may be the pathological basis of cognitive impairment in SLI patients.