Spatiotemporal dissociation of fMRI activity in the caudate nucleus underlies human de novo motor skill learning

Longitudinal Evolution of the Brain Microstructure in Cirrhotic Patients on Diffusion Kurtosis Imaging

BACKGROUND

Although improvement of cognitive function after liver transplantation has been demonstrated in several neuropsychological studies, there is limited research on longitudinal changes in the cirrhotic patients' brain structure before and after transplantation.

PURPOSE

To investigate longitudinal changes of brain microstructure in cirrhotic patients using diffusion kurtosis imaging (DKI).

STUDY TYPE

Prospective.

SUBJECTS

A total of 153 cirrhosis patients, comprising 60 hepatic encephalopathy (HE) patients (16 females/44 males) and 93 no-HE patients (35 females/58 males), along with 93 healthy controls (HCs) (53 females/40 males) were enrolled. Subsequently, 58 recipients completed 1-month postoperative follow-up, 29 patients completed 1-, 3-months, and 17 patients completed 1-, 3-, 6-month follow-up.

SEQUENCE

Spin-echo single-shot echo-planar sequence using a 3.0 T scanner.

ASSESSMENT

Diffusion kurtosis estimator software was used to estimate the DKI parameter maps by a MR imaging physicist (Y.-Y.C. with 12 years of experience).

STATISTICAL TESTS

The diffusion metrics (eg, radial kurtosis [RK], mean kurtosis, fractional anisotropy, mean diffusivity) of the patients before transplantation were compared with those of the HCs using voxel-wise analysis of variance (ANOVA), along with t tests for post hoc analysis. Linear mixed-effects models were applied to the longitudinal data. We imposed a cluster level Family Wise Error (FWE) correction rate of PFWE = 0.05 with voxel-wise cutoff of P = 0.001 together with a cluster-size cutoff of N ≥ 56, and generated smoothness estimates from the preprocessed data using the mixed-model autocorrelation function.

RESULTS

The RK metrics of the patients decreased significantly in the anterior cingulate cortex (HE/no-HE < HC, ANOVA-F = 21.91). After transplantation, the RK of the pallidum showed a continuous upward trend (time effect T = 11.26); whereas the RK of the right postcentral gyrus showed a continuous downward trend (time effect T = -9.56). In addition, the RK in superior longitudinal fasciculus showed new-onset decrease after transplantation.

DATA CONCLUSION

Longitudinal changes in DKI metrics reveal the course of brain microstructural changes before and after transplantation in cirrhotic patients, potentially associated with cognitive alterations after surgery.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 4.

Sense of agency for a new motor skill emerges via the formation of a structural internal model

Sense of agency (SoA) refers to the feeling of controlling one's body and the external environment. The traditional comparator model posits that SoA arises from a match between predicted and actual action outcomes. However, when learning new motor skills, individuals initially lack outcome predictions and gradually develop an internal model of action-outcome mapping through trial-and-error, a process known as motor exploration. To investigate the development of SoA in such scenarios, we employed a de novo motor learning task that participants had never experienced before. Using a data glove, participants controlled a cursor on a screen through finger movements. In Experiment 1, participants learned a spatial hand-to-screen mapping from scratch via motor exploration. At different learning phases, we measured and compared participants' SoA for cursor movements that either conformed to the learned mapping or incorporated spatial or temporal biases. Initially, SoA was driven solely by temporal contiguity between finger and cursor movements. As learning progressed, SoA increased for cursor movements following the learned mapping compared to those following the spatially biased, unlearned mapping. In contrast, such changes did not occur in Experiment 2, where participants only imitated gesture images and memorized corresponding screen positions. The findings enhance existing SoA theories by elucidating the origins of the comparator process and highlighting the critical role of motor exploration.

Effective Motor Skill Learning Induces Inverted-U Load-Dependent Activation in Contralateral Pre-Motor and Supplementary Motor Area

Motor learning involves complex interactions between the cognitive and sensorimotor systems, which are susceptible to different levels of task load. While the mechanism underlying load-dependent regulations in cognitive functions has been extensively investigated, their influence on downstream execution in motor skill learning remains less understood. The current study extends the understanding of whether and how learning alters the load-dependent activation pattern by a longitudinal functional near-infrared spectroscopy (fNIRS) study in which 30 healthy participants (15 females) engaged in extensive practice on a two-dimensional continuous hand tracking task with varying task difficulty. We proposed the index of difficulty (ID) as a quantitative measure of task difficulty, which was monotonically associated with a psychometric measure of subjective workload. As learning progressed, participants exhibited enhanced behavioral and metacognitive performance. Behavioral improvements were accompanied by plastic changes in the inferior prefrontal cortex, reflecting a shift in control strategy during motor learning. Most importantly, we found robust evidence of the learning-induced alteration in load-dependent cortical activation patterns, indicating that effective motor skill learning may lead to the emergence of an inverted-U relationship between cortical activation and load level in the contralateral pre-motor and supplementary motor areas. Our findings provide new insights into the learning-induced plasticity in brain and behavior, highlighting the load-dependent contributions in motor skill learning.

Frontal Deactivation and the Efficacy of Statistical Learning: Neural Mechanisms Accompanying Exposure to Visual Statistical Sequences

Statistical learning is the cognitive ability to rapidly identify structure and meaning in unfamiliar streams of sensory experience, even in the absence of feedback. Despite extensive studies, the neurocognitive mechanisms underlying this phenomenon still require further clarification under varying cognitive conditions. Here, we examined neural mechanisms during the first exposure to visually presented sequences in 47 healthy participants. We used two types of visual objects: abstract symbols and pictures of cartoon-like animals. This allowed us to compare informational processing mechanisms with defined distinguishing features. Participants achieved better performance for sequences with easy-to-name than difficult-to-name abstract stimuli. fMRI results revealed greater activation in widespread brain regions in response to random versus statistical sequences for all stimuli types. Behavioral accuracy was associated with increased deactivation of the ventromedial PFC for easy-to-name statistical versus random sequences. For difficult-to-name statistical versus random sequences, performance correlated with dorsomedial prefrontal cortex deactivation. ROI analysis showed a generally positive involvement of the caudate head in sequence processing with significantly stronger activity during the first run of performing the task. Functional connectivity analysis of prefrontal deactivation regions revealed significant connectivity with nodes of the salience network for both object types and inverse connectivity with the caudate head only for easy-to-name objects. The results indicated that distinct subregions of PFC modulate task performance depending on the visual stimulus characteristic. They also showed that among striatal regions, only the head of the caudate was sensitive to initial exposure to visual statistical information.

Brain networks and intelligence: A graph neural network based approach to resting state fMRI data

Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating the relationship between brain function and cognitive processes as it allows for the functional organization of the brain to be captured without relying on a specific task or stimuli. In this paper, we present a novel modeling architecture called BrainRGIN for predicting intelligence (fluid, crystallized and total intelligence) using graph neural networks on rsfMRI derived static functional network connectivity matrices. Extending from the existing graph convolution networks, our approach incorporates a clustering-based embedding and graph isomorphism network in the graph convolutional layer to reflect the nature of the brain sub-network organization and efficient network expression, in combination with TopK pooling and attention-based readout functions. We evaluated our proposed architecture on a large dataset, specifically the Adolescent Brain Cognitive Development Dataset, and demonstrated its effectiveness in predicting individual differences in intelligence. Our model achieved lower mean squared errors and higher correlation scores than existing relevant graph architectures and other traditional machine learning models for all of the intelligence prediction tasks. The middle frontal gyrus exhibited a significant contribution to both fluid and crystallized intelligence, suggesting their pivotal role in these cognitive processes. Total composite scores identified a diverse set of brain regions to be relevant which underscores the complex nature of total intelligence. Our GitHub implementation is publicly available on https://github.com/bishalth01/BrainRGIN/.

Neural substrates of choking under pressure: A 7T-fMRI study

Performance decrement under excessive psychological pressure is known as "choking," yet its mechanisms and neural foundations remain underexplored. Hypothesizing that changes in the internal model could induce choking, we conducted a 7 T functional MRI introducing excessive pressure through a rare Jackpot condition that offers high rewards for successful performance. Twenty-nine volunteers underwent a visual reaching task. We monitored practice and main sessions to map the task's internal model through learning. Participants were pre-informed of four potential reward conditions upon success at the beginning of the main session task. The success rates in the Jackpot condition were significantly lower than in other conditions, indicative of choking. During the preparation phase, activations in the cerebellum and the middle temporal visual area (hMT+) were associated with Jackpot-specific failures. The cluster in the cerebellar hemisphere overlapped with the internal model regions identified by a learning-related decrease in activation during the practice session. We observed task-specific functional connectivity between the cerebellum and hMT+. These findings suggest a lack of sensory attenuation when an internal model predicting the outcome of one's actions is preloaded during motor preparation. Within the active inference framework of motor control, choking stems from the cerebellum's internal model modulation by psychological pressure, manifested through improper sensory attenuation.

Emergence of Categorical Representations in Parietal and Ventromedial Prefrontal Cortex across Extended Training

How do the neural representations underlying category learning change as skill develops? We examined perceptual category learning using a prototype learning task known to recruit a corticostriatal system including the posterior striatum, motor cortex, visual cortex, and intraparietal sulcus (IPS). Male and female human participants practiced categorizing stimuli as category members or nonmembers (A vs not-A) across 3 d, with fMRI data collected at the beginning and end. Univariate analyses found that corticostriatal activity in regions associated with habitual instrumental learning was recruited across both sessions, but activity in regions associated with goal-directed instrumental learning decreased from Day 1 to Day 3. Multivoxel pattern analysis (MVPA) indicated that after training, the trained category could be more easily decoded from the IPS when compared with a novel category. Representational similarity analysis (RSA) showed development of category representations in the IPS and motor cortex. In addition, RSA revealed evidence for category-related representations including prototype representation in the ventromedial prefrontal cortex which may reflect parallel development of schematic memory for the category structure. Overall, the results converge to show how performance of category decisions and representations of the category structure emerge after extensive training across the corticostriatal system underlying perceptual category learning.

The primate putamen processes cognitive flexibility alongside the caudate and ventral striatum with similar speeds of updating values

The putamen is thought to generate habitual actions by processing value information relayed from the ventral striatum through the caudate nucleus. However, it is a question what value the putamen neurons process and whether the putamen receives serially processed value through the striatal structures. We found that neurons in the primate putamen, caudate, and ventral striatum selectively encoded flexibly updated values for adaptive behaviors with similar learning speeds, rather than stably sustained values for habit. In reversal value learning, rostral striatum neurons dynamically adjusted their responses to object values in alignment with changes in saccade reaction times following reversals. Notably, the value acquisition speeds within trials were similar, proposing a parallel value update in each striatal region. However, in stable value retrieval, most did not encode the values for habitual saccades. Our findings suggest that the rostral striatum including the putamen is selectively involved in the parallel processing of cognitive flexibility.

Optimising children's movement assessment batteries through application of motivational and attentional manipulations

An external focus of attention, enhanced expectancies, and autonomy support (i.e., OPTIMAL factors) are key factors to optimise motor performance and uncover latent movement capabilities. However, research on the combination of OPTIMAL factors, particularly in children's dynamic movement settings is limited. Therefore, this study examined the combined effects of OPTIMAL factors on children's performance on a dynamic movement assessment battery, hypothesising higher performance scores in the optimised version of the assessment battery versus standardised version of the assessment. Forty-nine children (15 boys, 34 girls; mean age 10.61 ± 1.38 years) completed the Dragon Challenge (DC) dynamic movement assessment battery. Performance was measured via a summation of movement process (technique), outcome, and time-to-completion scores (max score N = 54) with higher scores representing better performance. Participants completed a standardised and an optimised version of the DC in a counterbalanced fashion. For the latter, DC protocols were optimised via the provision of choice (autonomy support); external focus instructions augmented by simple knowledge statement, positive feedback and promotion of a growth mindset (Enhanced expectancies). Results indicate that motor performance (DC score) was better in the optimised (M = 31.08 ± 6.66) vs. standardised (M = 29.04 ± 5.88). The findings indicate that the combination of OPTIMAL factors can improve children's motor performance in dynamic movement settings and that standardised motor assessment may not reveal children's true movement capabilities.

Cingulate and striatal hubs are linked to early skill learning

Early skill learning develops in the context of activity changes in distributed cortico-subcortical regions. Here, we investigated network hubs-centers of information integration and transmission-within the brain network supporting early skill learning. We recorded magnetoencephalographic (MEG) brain activity in healthy human subjects who learned a moderately difficult sequence skill with their non-dominant left hand. We then computed network hub strength by summing top 10% functional connectivity over 86 parcellated brain regions (AAL3 atlas) and five brain oscillatory frequency bands (alpha, low-, high-beta, low- and high-gamma). Virtually all skill gains developed during rest intervals of early learning (micro-offline gains). MEG hub strength in the alpha band (8-13Hz) in bilateral anterior cingulate (ACC) and caudate and in the low-beta band (13-16Hz) in bilateral caudate and right putamen correlated with micro-offline gains. These regions linked strongly with the hippocampus, parahippocampal cortex, and lingual and fusiform gyri. Thus, alpha and low-beta brain oscillatory activity in cingulate and striatal regions appear to contribute as hubs of information integration and transmission during early skill learning.

Motor learning is modulated by dopamine availability in the sensorimotor putamen

Successful motor skill acquisition requires the dynamic interaction of multiple brain regions, with the striatum playing a critical role in this network. Animal studies suggest that dopaminergic mechanisms are involved in the regulation of motor learning-associated striatal plasticity. In humans, however, the contribution of nigrostriatal dopaminergic transmission to motor learning remains elusive beyond its well-characterized role in initiation and fluent execution of movements. In this prospective observational study, we investigated motor sequence learning in individuals who had undergone 123I-N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane single-photon emission computed tomography for the differential diagnosis of Parkinson's disease (n = 41) and age-matched healthy controls (n = 20). We found that striatal dopamine transporter depletion exhibited distinct spatial patterns that were associated with impairments in motor sequence learning and the manifestation of Parkinsonian motor symptoms, respectively. Specifically, significant associations between striatal dopamine transporter depletion and impairments in motor sequence learning were confined to posterior putaminal regions, whereas significant associations of striatal dopamine transporter depletion with Parkinsonian motor symptom severity showed a widespread spatial pattern across the entire striatal volume with an anterior maximum. Normative functional connectivity analysis revealed that both behavioural domains shared largely overlapping connectivity patterns with the basal ganglia and supplementary motor area. However, apart from connectivity with more posterior parts of the supplementary motor area, significant functional connectivity with primary motor cortical areas was only present for striatal dopamine transporter availability-related modulation of online motor learning. Our findings indicate that striatal dopaminergic signalling plays a specific role in motor sequence learning beyond its influence on mere motor execution, implicating learning-related sensorimotor striatum recruitment and cortico-striatal plasticity as dopamine-dependent mechanisms.

Early-life risperidone alters locomotor responses to apomorphine and quinpirole in adulthood

An escalating trend of antipsychotic drug use in children with ADHD, disruptive behavior disorder, or mood disorders has raised concerns about the impact of these drugs on brain development. Since antipsychotics chiefly target dopamine receptors, it is important to assay the function of these receptors after early-life antipsychotic administration. Using rats as a model, we examined the effects of early-life risperidone, the most prescribed antipsychotic drug in children, on locomotor responses to the dopamine D1/D2 receptor agonist, apomorphine, and the D2/D3 receptor agonist, quinpirole. Female and male Long-Evans rats received daily subcutaneous injections of risperidone (1.0 and 3.0 mg/kg) or vehicle from postnatal day 14-42. Locomotor responses to one of three doses (0.03, 0.1, and 0.3 mg/kg) of apomorphine or quinpirole were tested once a week for four weeks beginning on postnatal day 76 and 147 for each respective drug. The locomotor activity elicited by the two lower doses of apomorphine was significantly greater in adult rats, especially females, administered risperidone early in life. Adult rats administered risperidone early in life also showed more locomotor activity after the low dose of quinpirole. Overall, female rats were more sensitive to the locomotor effects of each agonist. In a separate group of rats administered risperidone early in life, autoradiography of forebrain D2 receptors at postnatal day 62 revealed a modest increase in D2 receptor density in the medial caudate. These results provide evidence that early-life risperidone administration can produce long-lasting changes in dopamine receptor function and density.

Double dissociation of visuomotor interaction mediated by visual feedback during continuous de novo motor learning

While the sensorimotor cortices are central neural substrates for motor control and learning, how the interaction between their subregions with visual cortices contributes to acquiring de novo visuomotor skills is poorly understood. We design a continuous visuomotor task in fMRI where participants control a cursor using their fingers while learning an arbitrary finger-to-cursor mapping. To investigate visuomotor interaction in the de novo motor task, we manipulate visual feedback of a cursor such that they learn to control using fingers under two alternating conditions: online cursor feedback is available or unavailable except when a target is reached. As a result, we find double dissociation of fMRI activity in subregions of the sensorimotor and visual cortices. Specifically, motor and late visual cortices are more active with online cursor feedback, and somatosensory and early visual cortices are more active without online cursor feedback. We also find a significant reduction in functional connectivity between somatosensory cortices and early visual cortices, which is highly correlated with performance improvement. These findings support the distinct interaction between subregions of sensorimotor cortices and visual cortices, while the connectivity analysis highlights the critical role of somatosensory cortices during de novo motor learning.

OPTIMAL theory's claims about motivation lack evidence in the motor learning literature

Motivation is commonly recognized by researchers and practitioners as a key factor for motor learning. The OPTIMAL theory of motor learning (Wulf & Lewthwaite, 2016) claims that practice conditions that enhance learners' expectancies for future successful outcomes or that are autonomy supportive are motivating, thus leading to better learning. To examine the current evidence of the association between motivation and motor learning, we searched the literature for studies that manipulated expectancies and/or autonomy support. Specifically, our goals were to assess whether these manipulations resulted in group differences in motivation and, if so, whether increased motivation was associated with learning advantages. Results showed that out of 166 experiments, only 21% (n = 35) included at least one measure of motivation, even though this is the main factor proposed by OPTIMAL theory to explain the learning benefits of these manipulations. Among those, only 23% (n = 8) found group-level effects on motivation, suggesting that these manipulations might not be as motivating as expected. Of the eight experiments that found a group-level effect on motivation, five also observed learning benefits, offering limited evidence that when practice conditions increase motivation, learning is more likely to occur. Overall, the small number of studies assessing motivation precludes any reliable conclusions on the association between motivation and motor learning from being drawn. Together, our results question whether manipulations implemented in the research lines supporting OPTIMAL theory are indeed motivating and highlight the lack of sufficient evidence in these literatures to support that increased motivation benefits motor learning.

Mechanisms of Action Anticipation in Table Tennis Players: A Multivoxel Pattern Analysis Study

An exceptional ability to accurately anticipate an opponent's action is paramount for competitive athletes and highlights their experiential mastery. Despite conventional associations of action observation with specific brain regions, neuroimaging discrepancies persist. To explore the brain regions and neural mechanisms undergirding action anticipation, we compared distinct brain activation patterns involved in table tennis serve anticipation of expert table tennis athletes vs. non-experts by using both univariate analysis and multivoxel pattern analysis (MVPA). We collected functional magnetic resonance imaging data from 29 table tennis experts and 34 non-experts as they pressed a button to predict the trajectory of a ball in a table tennis serve video truncated at the moment of racket-ball contact vs. pressing any button while viewing a static image of the first video frame. MVPA was applied to assess whether it could accurately differentiate experts from non-experts. MVPA results indicated moderate accuracy (90.48%) for differentiating experts from non-experts. Brain regions contributing most to the differentiation included the left cerebellum, the vermis, the right middle temporal pole, the inferior parietal cortex, the bilateral paracentral lobule, and the left supplementary motor area. The findings suggest that brain regions associated with cognitive conflict monitoring and motor cognition contribute to the action anticipation ability of expert table tennis players.

Distinctive intrinsic functional connectivity alterations of anterior cingulate cortex subdivisions in major depressive disorder: A systematic review and meta-analysis

Evidence of whether the intrinsic functional connectivity of anterior cingulate cortex (ACC) and its subregions is altered in major depressive disorder (MDD) remains inconclusive. A systematic review and meta-analysis were therefore performed on the whole-brain resting-state functional connectivity (rsFC) studies using the ACC and its subregions as seed regions in MDD, in order to draw more reliable conclusions. Forty-four ACC-based rsFC studies were included, comprising 25 subgenual ACC-based studies, 11 pregenual ACC-based studies, and 17 dorsal ACC-based studies. Specific alterations of rsFC were identified for each ACC subregion in patients with MDD, with altered rsFC of subgenual ACC in emotion-related brain regions, of pregenual ACC in sensorimotor-related regions, and of dorsal ACC in cognition-related regions. Furthermore, meta-regression analysis revealed a significant negative correlation between the pgACC-caudate hypoconnectivity and percentage of female patients in the study cohort. This meta-analysis provides robust evidence of altered intrinsic functional connectivity of the ACC subregions in MDD, which may hold relevance to understanding the origin of, and treating, the emotional, sensorimotor and cognitive dysfunctions that are often observed in these patients.

Corticostriatal activity related to performance during continuous de novo motor learning

Corticostriatal regions play a pivotal role in visuomotor learning. However, less research has been done on how fMRI activity in their subregions is related to task performance, which is provided as visual feedback during motor learning. To address this, we conducted an fMRI experiment in which participants acquired a complex de novo motor skill using continuous or binary visual feedback related to performance. We found a highly selective response related to performance in the entire striatum in both conditions and a relatively higher response in the caudate nucleus for the binary feedback condition. However, the ventromedial prefrontal cortex (vmPFC) response was significant only for the continuous feedback condition. Furthermore, we also found functional distinction of the striatal subregions in random versus goal-directed motor control. These findings underscore the substantial effects of the visual feedback indicating performance on distinct corticostriatal responses, thereby elucidating its significance in reinforcement-based motor learning.

Anatomical and Functional Comparison of the Caudate Tail in Primates and the Tail of the Striatum in Rodents: Implications for Sensory Information Processing and Habitual Behavior

The tail of the striatum (TS) is located at the caudal end in the striatum. Recent studies have advanced our knowledge of the anatomy and function of the TS but also raised questions about the differences between rodent and primate TS. In this review, we compare the anatomy and function of the TS in rodent and primate brains. The primate TS is expanded more caudally during brain development in comparison with the rodent TS. Additionally, five sensory inputs from the cortex and thalamus converge in the rodent TS, but this convergence is not observed in the primate TS. The primate TS, including the caudate tail and putamen tail, primarily receives inputs from the visual areas, implying a specialized function in processing visual inputs for action generation. This anatomical difference leads to further discussion of cellular circuit models to comprehend how the primate brain processes a wider range of complex visual stimuli to produce habitual behavior as compared with the rodent brain. Examining these differences and considering possible neural models may provide better understanding of the anatomy and function of the primate TS.

Investigation of brain iron levels in Chinese patients with Alzheimer's disease

Introduction

We aimed (i) to explore the diagnostic value of deep gray matter magnetic susceptibility in Alzheimer's disease (AD) in China and (ii) to analyze its correlation with neuropsychiatric scales. Moreover, we conducted subgroup analysis based on the presence of the APOE-ε4 gene to improve the diagnosis of AD.

Methods

From the prospective studies of the China Aging and Neurodegenerative Initiative (CANDI), a total of 93 subjects who could undergo complete quantitative magnetic susceptibility imaging and APOE-ε4 gene detection were selected. Differences in quantitative susceptibility mapping (QSM) values between and within groups, including AD patients, individuals with mild cognitive impairment (MCI), and healthy controls (HCs), both APOE-ε4 carriers and non-carriers, were analyzed.

Results

In primary analysis, the magnetic susceptibility values of the bilateral caudate nucleus and right putamen in the AD group and of the right caudate nucleus in the MCI group were significantly higher than those in the HCs group (P < 0.05). In APOE-ε4 non-carriers, there were significant differences in more regions between the AD, MCI, and HCs groups, such as the left putamen and the right globus pallidus (P < 0.05). In subgroup analysis, the correlation between QSM values in some brain regions and neuropsychiatric scales was even stronger.

Discussion

Exploration of the correlation between deep gray matter iron levels and AD may provide insight into the pathogenesis of AD and facilitate early diagnosis in elderly Chinese. Further subgroup analysis based on the presence of the APOE-ε4 gene may further improve the diagnostic efficiency and sensitivity.

On the Relationship between Value- and Threat-Driven Attentional Capture and Approach-Avoidance Biases

Reward learning and aversive conditioning have consequences for attentional selection, such that stimuli that come to signal reward and threat bias attention regardless of their valence. Appetitive and aversive stimuli have distinctive influences on response selection, such that they activate an approach and an avoidance response, respectively. However, whether the involuntary influence of reward- and threat-history-laden stimuli extends to the manner in which a response is directed remains unclear. Using a feedback-joystick task and a manikin task, which are common paradigms for examining valence-action bias, we demonstrate that reward- and threat-signalling stimuli do not modulate response selection. Stimuli that came to signal reward and threat via training biased attention and invigorated action in general, but they did not facilitate an approach and avoidance response, respectively. We conclude that attention can be biased towards a stimulus as a function of its prior association with reward or aversive outcomes without necessarily influencing approach vs. avoidance tendencies, such that the mechanisms underlying the involuntary control of attention and behaviour evoked by valent stimuli can be decoupled.

De Novo Brain-Computer Interfacing Deforms Manifold of Populational Neural Activity Patterns in Human Cerebral Cortex

Human brains are capable of modulating innate activities to adapt to novel environments and tasks; for sensorimotor neural system this means acquisition of a rich repertoire of activity patterns that improve behavioral performance. To directly map the process of acquiring the neural repertoire during tasks onto performance improvement, we analyzed net neural populational activity during the learning of its voluntary modulation by brain-computer interface (BCI) operation in female and male humans. The recorded whole-head high-density scalp electroencephalograms (EEGs) were subjected to dimensionality reduction algorithm to capture changes in cortical activity patterns represented by the synchronization of neuronal oscillations during adaptation. Although the preserved variance of targeted features in the reduced dimensions was 20%, we found systematic interactions between the activity patterns and BCI classifiers that detected motor attempt; the neural manifold derived in the embedded space was stretched along with motor-related features of EEG by model-based fixed classifiers but not with adaptive classifiers that were constantly recalibrated to user activity. Moreover, the manifold was deformed to be orthogonal to the boundary by de novo classifiers with a fixed decision boundary based on biologically unnatural features. Collectively, the flexibility of human cortical signaling patterns (i.e., neural plasticity) is only induced by operation of a BCI whose classifier required fixed activities, and the adaptation could be induced even the requirement is not consistent with biologically natural responses. These principles of neural adaptation at a macroscopic level may underlie the ability of humans to learn wide-ranging behavioral repertoires and adapt to novel environments.

Representations and decodability of diverse cognitive functions are preserved across the human cortex, cerebellum, and subcortex

Which part of the brain contributes to our complex cognitive processes? Studies have revealed contributions of the cerebellum and subcortex to higher-order cognitive functions; however, it has been unclear whether such functional representations are preserved across the cortex, cerebellum, and subcortex. In this study, we use functional magnetic resonance imaging data with 103 cognitive tasks and construct three voxel-wise encoding and decoding models independently using cortical, cerebellar, and subcortical voxels. Representational similarity analysis reveals that the structure of task representations is preserved across the three brain parts. Principal component analysis visualizes distinct organizations of abstract cognitive functions in each part of the cerebellum and subcortex. More than 90% of the cognitive tasks are decodable from the cerebellum and subcortical activities, even for the novel tasks not included in model training. Furthermore, we show that the cerebellum and subcortex have sufficient information to reconstruct activity in the cerebral cortex.

Predictive models demonstrate age-dependent association of subcortical volumes and cognitive measures

Whether brain matter volume is correlated with cognitive functioning and higher intelligence is controversial. We explored this relationship by analysis of data collected on 193 healthy young and older adults through the "Leipzig Study for Mind-Body-Emotion Interactions" (LEMON) study. Our analysis involved four cognitive measures: fluid intelligence, crystallized intelligence, cognitive flexibility, and working memory. Brain subregion volumes were determined by magnetic resonance imaging. We normalized each subregion volume to the estimated total intracranial volume and conducted training simulations to compare the predictive power of normalized volumes of large regions of the brain (i.e., gray matter, cortical white matter, and cerebrospinal fluid), normalized subcortical volumes, and combined normalized volumes of large brain regions and normalized subcortical volumes. Statistical tests showed significant differences in the performance accuracy and feature importance of the subregion volumes in predicting cognitive skills for young and older adults. Random forest feature selection analysis showed that cortical white matter was the key feature in predicting fluid intelligence in both young and older adults. In young adults, crystallized intelligence was best predicted by caudate nucleus, thalamus, pallidum, and nucleus accumbens volumes, whereas putamen, amygdala, nucleus accumbens, and hippocampus volumes were selected for older adults. Cognitive flexibility was best predicted by the caudate, nucleus accumbens, and hippocampus in young adults and caudate and amygdala in older adults. Finally, working memory was best predicted by the putamen, pallidum, and nucleus accumbens in the younger group, whereas amygdala and hippocampus volumes were predictive in the older group. Thus, machine learning predictive models demonstrated an age-dependent association between subcortical volumes and cognitive measures. These approaches may be useful in predicting the likelihood of age-related cognitive decline and in testing of approaches for targeted improvement of cognitive functioning in older adults.

Cerebellar Transcranial Direct Current Stimulation Reconfigures Brain Networks Involved in Motor Execution and Mental Imagery

Transcranial direct current stimulation (tDCS) is growingly applied to the cerebellum to modulate the activity of cerebellar circuitry, affecting both motor and cognitive performances in a polarity-specific manner. The remote effects of tDCS are mediated in particular via the dentato-thalamo-cortical pathway. We showed recently that tDCS of the cerebellum exerts dynamic effects on resting state networks. We tested the neural hypothesis that tDCS reconfigurates brain networks involved in motor execution (ME) and motor mental imagery (MMI). We combined tDCS applied over the right cerebellum and fMRI to investigate tDCS-induced reconfiguration of ME- and MMI-related networks using a randomized, sham-controlled design in 21 right-handed healthy volunteers. Subjects were instructed to draw circles at comfortable speed and to imagine drawing circles with their right hand. fMRI data were recorded after real anodal stimulation (1.5 mA, 20 min) or sham tDCS. Real tDCS compared with SHAM specifically reconfigurated the functional links between the main intrinsic connected networks, especially the central executive network, in relation with lobule VII, and the salience network. The right cerebellum mainly influenced prefrontal and anterior cingulate areas in both tasks, and improved the overt motor performance. During MMI, the cerebellum also modulated the default-mode network and associative visual areas. These results demonstrate that tDCS of the cerebellum represents a novel tool to modulate cognitive brain networks controlling motor execution and mental imagery, tuning the activity of remote cortical regions. This approach opens novel doors for the non-invasive neuromodulation of disorders involving cerebello-thalamo-cortical paths.

Motor context modulates substantia nigra pars reticulata spike activity in patients with Parkinson's disease

OBJECTIVE

The severity of motor symptoms in Parkinson's disease (PD) depends on environmental conditions. For example, the presence of external patterns such as a rhythmic tone can attenuate bradykinetic impairments. However, the neural mechanisms for this context-dependent attenuation (e.g., paradoxical kinesis) remain unknown. Here, we investigate whether context-dependent symptom attenuation is reflected in single-unit activity recorded in the operating room from the substantia nigra pars reticulata (SNr) of patients with PD undergoing deep brain stimulation surgery. The SNr is known to influence motor planning and execution in animal models, but its role in humans remains understudied.

METHODS

We recorded SNr activity while subjects performed cued directional movements in response to auditory stimuli under interleaved 'patterned' and 'unpatterned' contexts. SNr localisation was independently confirmed with expert intraoperative assessment as well as post hoc imaging-based reconstructions.

RESULTS

As predicted, we found that motor performance was improved in the patterned context, reflected in increased reaction speed and accuracy compared with the unpatterned context. These behavioural differences were associated with enhanced responsiveness of SNr neurons-that is, larger changes in activity from baseline-in the patterned context. Unsupervised clustering analysis revealed two distinct subtypes of SNr neurons: one exhibited context-dependent enhanced responsiveness exclusively during movement preparation, whereas the other showed enhanced responsiveness during portions of the task associated with both motor and non-motor processes.

CONCLUSIONS

Our findings indicate the SNr participates in motor planning and execution, as well as warrants greater attention in the study of human sensorimotor integration and as a target for neuromodulatory therapies.

Estimated Gray Matter Volume Rapidly Changes after a Short Motor Task

Skill learning induces changes in estimates of gray matter volume (GMV) in the human brain, commonly detectable with magnetic resonance imaging (MRI). Rapid changes in GMV estimates while executing tasks may however confound between- and within-subject differences. Fluctuations in arterial blood flow are proposed to underlie this apparent task-related tissue plasticity. To test this hypothesis, we acquired multiple repetitions of structural T1-weighted and functional blood-oxygen level-dependent (BOLD) MRI measurements from 51 subjects performing a finger-tapping task (FTT; á 2 min) repeatedly for 30-60 min. Estimated GMV was decreased in motor regions during FTT compared with rest. Motor-related BOLD signal changes did not overlap nor correlate with GMV changes. Nearly simultaneous BOLD signals cannot fully explain task-induced changes in T1-weighted images. These sensitive and behavior-related GMV changes pose serious questions to reproducibility across studies, and morphological investigations during skill learning can also open new avenues on how to study rapid brain plasticity.

Random Network and Non-rich-club Organization Tendency in Children With Non-syndromic Cleft Lip and Palate After Articulation Rehabilitation: A Diffusion Study

Objective

The neuroimaging pattern in brain networks after articulation rehabilitation can be detected using graph theory and multivariate pattern analysis (MVPA). In this study, we hypothesized that the characteristics of the topology pattern of brain structural network in articulation-rehabilitated children with non-syndromic cleft lip and palate (NSCLP) were similar to that in healthy comparisons.

Methods

A total of 28 children with NSCLP and 28 controls with typical development were scanned for diffusion tensor imaging on a 3T MRI scanner. Structural networks were constructed, and their topological properties were obtained. Besides, the Chinese language clear degree scale (CLCDS) scores were used for correlation analysis with topological features in patients with NSCLP.

Results

The NSCLP group showed a similar rich-club connection pattern, but decreased small-world index, normalized rich-club coefficient, and increased connectivity strength of connections compared to controls. The univariate and multivariate patterns of the structural network in articulation-rehabilitated children were primarily in the feeder and local connections, covering sensorimotor, visual, frontoparietal, default mode, salience, and language networks, and orbitofrontal cortex. In addition, the connections that were significantly correlated with the CLCDS scores, as well as the weighted regions for classification, were chiefly distributed in the dorsal and ventral stream associated with the language networks of the non-dominant hemisphere.

Conclusion

The average level rich-club connection pattern and the compensatory of the feeder and local connections mainly covering language networks may be related to the CLCDS in articulation-rehabilitated children with NSCLP. However, the patterns of small-world and rich-club structural organization in the articulation-rehabilitated children exhibited a random network and non-rich-club organization tendency. These findings enhanced the understanding of neuroimaging patterns in children with NSCLP after articulation rehabilitation.

Whole-Brain Afferent Inputs to the Caudate Nucleus, Putamen, and Accumbens Nucleus in the Tree Shrew Striatum

Day-active tree shrews have a well-developed internal capsule (ic) that clearly separates the caudate nucleus (Cd) and putamen (Pu). The striatum consists of the Cd, ic, Pu, and accumbens nucleus (Acb). Here, we characterized the cytoarchitecture of the striatum and the whole-brain inputs to the Cd, Pu, and Acb in tree shrews by using immunohistochemistry and the retrograde tracer Fluoro-Gold (FG). Our data show the distribution patterns of parvalbumin (PV), nitric oxide synthase (NOS), calretinin (CR), and tyrosine hydroxylase (TH) immunoreactivity in the striatum of tree shrews, which were different from those observed in rats. The Cd and Pu mainly received inputs from the thalamus, motor cortex, somatosensory cortex, subthalamic nucleus, substantia nigra, and other cortical and subcortical regions, whereas the Acb primarily received inputs from the anterior olfactory nucleus, claustrum, infralimbic cortex, thalamus, raphe nucleus, parabrachial nucleus, ventral tegmental area, and so on. The Cd, Pu, and Acb received inputs from different neuronal populations in the ipsilateral (60, 67, and 63 brain regions, respectively) and contralateral (23, 20, and 36 brain regions, respectively) brain hemispheres. Overall, we demonstrate that there are species differences between tree shrews and rats in the density of PV, NOS, CR, and TH immunoreactivity in the striatum. Additionally, we mapped for the first time the distribution of whole-brain input neurons projecting to the striatum of tree shrews with FG injected into the Cd, Pu, and Acb. The similarities and differences in their brain-wide input patterns may provide new insights into the diverse functions of the striatal subregions.

Brain substrates for automatic retrieval of value memory in the primate basal ganglia

Our behavior is often carried out automatically. Automatic behavior can be guided by past experiences, such as learned values associated with objects. Passive-viewing and free-viewing tasks with no immediate outcomes provide a testable condition in which monkeys and humans automatically retrieve value memories and perform habitual searching. Interestingly, in these tasks, caudal regions of the basal ganglia structures are involved in automatic retrieval of learned object values and habitual gaze. In contrast, rostral regions do not participate in these activities but instead monitor the changes in outcomes. These findings indicate that automatic behaviors based on the value memories are processed selectively by the caudal regions of the primate basal ganglia system. Understanding the distinct roles of the caudal basal ganglia may provide insight into finding selective causes of behavioral disorders in basal ganglia disease.

Functional parcellation of human and macaque striatum reveals human-specific connectivity in the dorsal caudate

A wide homology between human and macaque striatum is often assumed as in both the striatum is involved in cognition, emotion and executive functions. However, differences in functional and structural organization between human and macaque striatum may reveal evolutionary divergence and shed light on human vulnerability to neuropsychiatric diseases. For instance, dopaminergic dysfunction of the human striatum is considered to be a pathophysiological underpinning of different disorders, such as Parkinson's disease (PD) and schizophrenia (SCZ). Previous investigations have found a wide similarity in structural connectivity of the striatum between human and macaque, leaving the cross-species comparison of its functional organization unknown. In this study, resting-state functional connectivity (RSFC) derived striatal parcels were compared based on their homologous cortico-striatal connectivity. The goal here was to identify striatal parcels whose connectivity is human-specific compared to macaque parcels. Functional parcellation revealed that the human striatum was split into dorsal, dorsomedial, and rostral caudate and ventral, central, and caudal putamen, while the macaque striatum was divided into dorsal, and rostral caudate and rostral, and caudal putamen. Cross-species comparison indicated dissimilar cortico-striatal RSFC of the topographically similar dorsal caudate. We probed clinical relevance of the striatal clusters by examining differences in their cortico-striatal RSFC and gray matter (GM) volume between patients (with PD and SCZ) and healthy controls. We found abnormal RSFC not only between dorsal caudate, but also between rostral caudate, ventral, central and caudal putamen and widespread cortical regions for both PD and SCZ patients. Also, we observed significant structural atrophy in rostral caudate, ventral and central putamen for both PD and SCZ while atrophy in the dorsal caudate was specific to PD. Taken together, our cross-species comparative results revealed shared and human-specific RSFC of different striatal clusters reinforcing the complex organization and function of the striatum. In addition, we provided a testable hypothesis that abnormalities in a region with human-specific connectivity, i.e., dorsal caudate, might be associated with neuropsychiatric disorders.

Value network engagement and effects of memory-related processing during encoding and retrieval of value

Decision makers rely on episodic memory to calculate choice values in everyday life, yet it is unclear how neural mechanisms of valuation differ when value-related information is encoded versus retrieved from episodic memory. The current fMRI study compared neural correlates of value while information was encoded versus retrieved from memory. Scanned tasks were followed by a behavioral episodic memory test for item-attribute associations. Our analyses sought to (i) identify neural correlates of value that were distinct and common across encoding and retrieval, and (ii) determine whether neural mechanisms of valuation and episodic memory interact. The study yielded three primary findings. First, value-related activation in the fronto-striatal reward circuit and posterior parietal cortex was comparable across valuation phases. Second, value-related activation in select fronto-parietal and salience regions was significantly greater at value retrieval than encoding. Third, there was no interaction between neural correlates of valuation and episodic memory. Taken with prior research, the present study indicates that fronto-parietal and salience regions play a key role in retrieval-dependent valuation and context-specific effects likely determine whether neural correlates of value interact with episodic memory.