Subthalamic control of impulsive actions: insights from deep brain stimulation in Parkinson's disease.

Control of actions allows adaptive, goal-directed behaviour. The basal ganglia, including the subthalamic nucleus, are thought to play a central role in dynamically controlling actions through recurrent negative feedback loops with the cerebral cortex. Here, we summarize recent translational studies that used deep brain stimulation to record neural activity from and apply electrical stimulation to the subthalamic nucleus in people with Parkinson's disease. These studies have elucidated spatial, spectral and temporal features of the neural mechanisms underlying the controlled delay of actions in cortico-subthalamic networks and demonstrated their causal effects on behaviour in distinct processing windows. While these mechanisms have been conceptualized as control signals for suppressing impulsive response tendencies in conflict tasks and as decision threshold adjustments in value-based and perceptual decisions, we propose a common framework linking decision-making, cognition and movement. Within this framework subthalamic deep brain stimulation can lead to suboptimal choices by reducing the time that patients take for deliberation before committing to an action. However, clinical studies have consistently shown that the occurrence of impulse control disorders is reduced, not increased, after subthalamic deep brain stimulation surgery. This apparent contradiction can be reconciled when recognizing the multifaceted nature of impulsivity, its underlying mechanisms and modulation by treatment. While subthalamic deep brain stimulation renders patients susceptible to making decisions without proper forethought, this can be disentangled from effects related to dopamine comprising sensitivity to benefits vs. costs, reward delay aversion and learning from outcomes. Alterations in these dopamine-mediated mechanisms are thought to underlie the development of impulse control disorders, and can be relatively spared with reduced dopaminergic medication after subthalamic deep brain stimulation. Together, results from studies using deep brain stimulation as an experimental tool have improved our understanding of action control in the human brain and have important implications for treatment of patients with Neurological disorders.

United States-China differences in cognition and perception across 12 tasks: Replicability, robustness, and within-culture variation.

Cultural differences between the United States and China have been investigated using a broad array of psychological tasks measuring differences between cognition, language, perception, and reasoning. Using online convenience samples of adults, we conducted two large-scale replications of 12 tasks previously reported to show differences between Western and East Asian cultures. Our results showed a heterogeneous pattern of successes and failures: five tasks yielded robust cultural differences, while five showed no difference between cultures, and two showed a small difference in the opposite direction. We observed moderate reliability for all multitrial tasks, but there was little relation between task scores. As in prior work, cross-cultural differences in cognition (in those tasks showing differences) were not strongly related to explicit measures of cultural identity and behavior. All of our tasks, data, and analyses are openly available for reuse, providing a foundation for future studies that seek to establish a robust and replicable science of cross-cultural difference. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Enhancing the substrate selectivity of enzyme mimetics in biosensing and bioassay: Novel approaches.

A substantial development in nanoscale materials possessing catalytic activities comparable with natural enzymes has been accomplished. Their advantages were owing to the excellent sturdiness in an extreme environment, possibilities of their large-scale production resulting in higher profitability, and easy manipulation for modification. Despite these advantages, the main challenge for artificial enzyme mimetics is the lack of substrate selectivity where natural enzymes flourish. This review addresses this vital problem by introducing substrate selectivity strategies to three classes of artificial enzymes: molecularly imprinted polymers, nanozymes (NZs), and DNAzymes. These rationally designed strategies enhance the substrate selectivity and are discussed and exemplified throughout the review. Various functional mechanisms associated with applying enzyme mimetics in biosensing and bioassays are also given. Eventually, future directives toward enhancing the substrate selectivity of biomimetics and related challenges are discussed and evaluated based on their efficiency and convenience in biosensing and bioassays.

Learning the Meanings of Function Words From Grounded Language Using a Visual Question Answering Model.

Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question answering models apparently can learn to use function words as part of answering questions about complex visual scenes. In this paper, we study what these models learn about function words, in the hope of better understanding how the meanings of these words can be learned by both models and children. We show that recurrent models trained on visually grounded language learn gradient semantics for function words requiring spatial and numerical reasoning. Furthermore, we find that these models can learn the meanings of logical connectives and and or without any prior knowledge of logical reasoning as well as early evidence that they are sensitive to alternative expressions when interpreting language. Finally, we show that word learning difficulty is dependent on the frequency of models' input. Our findings offer proof-of-concept evidence that it is possible to learn the nuanced interpretations of function words in a visually grounded context by using non-symbolic general statistical learning algorithms, without any prior knowledge of linguistic meaning.

The challenge of learning adaptive mental behavior.

Many psychotherapies aim to help people replace maladaptive mental behaviors (such as those leading to unproductive worry) with more adaptive ones (such as those leading to active problem solving). Yet, little is known empirically about how challenging it is to learn adaptive mental behaviors. Mental behaviors entail taking mental operations and thus may be more challenging to perform than motor actions; this challenge may enhance or impair learning. In particular, challenge when learning is often desirable because it improves retention. Yet, it is also plausible that the necessity of carrying out mental operations interferes with learning the expected values of mental actions by impeding credit assignment: the process of updating an action's value after reinforcement. Then, it may be more challenging not only to perform-but also to learn the consequences of-mental (vs. motor) behaviors. We designed a task to assess learning to take adaptive mental versus motor actions via matched probabilistic feedback. In two experiments (N = 300), most participants found it more difficult to learn to select optimal mental (vs. motor) actions, as evident in worse accuracy not only in a learning but also test (retention) phase. Computational modeling traced this impairment to an indicator of worse credit assignment (impaired construction and maintenance of expected values) when learning mental actions, accounting for worse accuracy in the learning and retention phases. The results suggest that people have particular difficulty learning adaptive mental behavior and pave the way for novel interventions to scaffold credit assignment and promote adaptive thinking. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Ethological computational psychiatry: Challenges and opportunities.

Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions and well-constrained behaviors over short timescales (e.g., trials, hours), many mental health conditions involve complex interactions of mood and cognition that are non-stationary across behavioral contexts and evolve over extended timescales. Here, we discuss opportunities, challenges, and possible future directions in computational psychiatry to quantify non-stationary continuously monitored behaviors. We suggest that this exploratory effort may contribute to a more precision-based approach to treating mental disorders and facilitate a more robust reverse translation across animal species. We conclude with ethical considerations for any field that aims to bridge artificial intelligence and patient monitoring.

Evidence for Infant-directed Speech Preference Is Consistent Across Large-scale, Multi-site Replication and Meta-analysis.

There is substantial evidence that infants prefer infant-directed speech (IDS) to adult-directed speech (ADS). The strongest evidence for this claim has come from two large-scale investigations: i) a community-augmented meta-analysis of published behavioral studies and ii) a large-scale multi-lab replication study. In this paper, we aim to improve our understanding of the IDS preference and its boundary conditions by combining and comparing these two data sources across key population and design characteristics of the underlying studies. Our analyses reveal that both the meta-analysis and multi-lab replication show moderate effect sizes (d ≈ 0.35 for each estimate) and that both of these effects persist when relevant study-level moderators are added to the models (i.e., experimental methods, infant ages, and native languages). However, while the overall effect size estimates were similar, the two sources diverged in the effects of key moderators: both infant age and experimental method predicted IDS preference in the multi-lab replication study, but showed no effect in the meta-analysis. These results demonstrate that the IDS preference generalizes across a variety of experimental conditions and sampling characteristics, while simultaneously identifying key differences in the empirical picture offered by each source individually and pinpointing areas where substantial uncertainty remains about the influence of theoretically central moderators on IDS preference. Overall, our results show how meta-analyses and multi-lab replications can be used in tandem to understand the robustness and generalizability of developmental phenomena.

An inexpensive UV-LED photoacoustic based real-time sensor-system detecting exhaled trace-acetone.

In this research we present a low-cost system for breath acetone analysis based on UV-LED photoacoustic spectroscopy. We considered the end-tidal phase of exhalation, which represents the systemic concentrations of volatile organic compounds (VOCs) - providing clinically relevant information about the human health. This is achieved via the development of a CO2-triggered breath sampling system, which collected alveolar breath over several minutes in sterile and inert containers. A real-time mass spectrometer is coupled to serve as a reference device for calibration measurements and subsequent breath analysis. The new sensor system provided a 3σ detection limit of 8.3 ppbV and an NNEA of 1.4E-9 Wcm-1Hz-0.5. In terms of the performed breath analysis measurements, 12 out of 13 fell within the error margin of the photoacoustic measurement system, demonstrating the reliability of the measurements in the field.

Assessing Trial-by-Trial Electrophysiological and Behavioral Markers of Attentional Control and Sensory Precision in Psychotic and Mood Disorders.

BACKGROUND AND HYPOTHESIS: The current study investigated the extent to which changes in attentional control contribute to performance on a visual perceptual discrimination task, on a trial-by-trial basis in a transdiagnostic clinical sample. STUDY DESIGN: Participants with schizophrenia (SZ; N = 58), bipolar disorder (N = 42), major depression disorder (N = 51), and psychiatrically healthy controls (N = 92) completed a visual perception task in which stimuli appeared briefly. The design allowed us to estimate the lapse rate and the precision of perceptual representations of the stimuli. Electroencephalograms (EEG) were recorded to examine pre-stimulus activity in the alpha band (8-13 Hz), overall and in relation to behavior performance on the task. STUDY RESULTS: We found that the attention lapse rate was elevated in the SZ group compared with all other groups. We also observed group differences in pre-stimulus alpha activity, with control participants showing the highest levels of pre-stimulus alpha when averaging across trials. However, trial-by-trial analyses showed within-participant fluctuations in pre-stimulus alpha activity significantly predicted the likelihood of making an error, in all groups. Interestingly, our analysis demonstrated that aperiodic contributions to the EEG signal (which affect power estimates across frequency bands) serve as a significant predictor of behavior as well. CONCLUSIONS: These results confirm the elevated attention lapse rate that has been observed in SZ, validate pre-stimulus EEG markers of attentional control and their use as a predictor of behavior on a trial-by-trial basis, and suggest that aperiodic contributions to the EEG signal are an important target for further research in this area, in addition to alpha-band activity.

Cognitive Signatures of Depressive and Anhedonic Symptoms and Affective States Using Computational Modeling and Neurocognitive Testing.

BACKGROUND: Deeper phenotyping may improve our understanding of depression. Because depression is heterogeneous, extracting cognitive signatures associated with severity of depressive symptoms, anhedonia, and affective states is a promising approach. METHODS: Sequential sampling models decomposed behavior from an adaptive approach-avoidance conflict task into computational parameters quantifying latent cognitive signatures. Fifty unselected participants completed clinical scales and the approach-avoidance conflict task by either approaching or avoiding trials offering monetary rewards and electric shocks. RESULTS: Decision dynamics were best captured by a sequential sampling model with linear collapsing boundaries varying by net offer values, and with drift rates varying by trial-specific reward and aversion, reflecting net evidence accumulation toward approach or avoidance. Unlike conventional behavioral measures, these computational parameters revealed distinct associations with self-reported symptoms. Specifically, passive avoidance tendencies, indexed by starting point biases, were associated with greater severity of depressive symptoms (R = 0.34, p = .019) and anhedonia (R = 0.49, p = .001). Depressive symptoms were also associated with slower encoding and response execution, indexed by nondecision time (R = 0.37, p = .011). Higher reward sensitivity for offers with negative net values, indexed by drift rates, was linked to more sadness (R = 0.29, p = .042) and lower positive affect (R = -0.33, p = .022). Conversely, higher aversion sensitivity was associated with more tension (R = 0.33, p = .025). Finally, less cautious response patterns, indexed by boundary separation, were linked to more negative affect (R = -0.40, p = .005). CONCLUSIONS: We demonstrated the utility of multidimensional computational phenotyping, which could be applied to clinical samples to improve characterization and treatment selection.

Human Curriculum Effects Emerge with In-Context Learning in Neural Networks.

Human learning is sensitive to rule-like structure and the curriculum of examples used for training. In tasks governed by succinct rules, learning is more robust when related examples are blocked across trials, but in the absence of such rules, interleaving is more effective. To date, no neural model has simultaneously captured these seemingly contradictory effects. Here we show that this same tradeoff spontaneously emerges with "in-context learning" (ICL) both in neural networks trained with metalearning and in large language models (LLMs). ICL is the ability to learn new tasks "in context" - without weight changes - via an inner-loop algorithm implemented in activation dynamics. Experiments with pretrained LLMs and metalearning transformers show that ICL exhibits the blocking advantage demonstrated in humans on a task involving rule-like structure, and conversely, that concurrent in-weight learning reproduces the interleaving advantage observed in humans on tasks lacking such structure.

Parallel developmental changes in children's production and recognition of line drawings of visual concepts.

Childhood is marked by the rapid accumulation of knowledge and the prolific production of drawings. We conducted a systematic study of how children create and recognize line drawings of visual concepts. We recruited 2-10-year-olds to draw 48 categories via a kiosk at a children's museum, resulting in >37K drawings. We analyze changes in the category-diagnostic information in these drawings using vision algorithms and annotations of object parts. We find developmental gains in children's inclusion of category-diagnostic information that are not reducible to variation in visuomotor control or effort. Moreover, even unrecognizable drawings contain information about the animacy and size of the category children tried to draw. Using guessing games at the same kiosk, we find that children improve across childhood at recognizing each other's line drawings. This work leverages vision algorithms to characterize developmental changes in children's drawings and suggests that these changes reflect refinements in children's internal representations.

Prolonged exposure to dexamethasone alters the proteome and cellular phenotype of human testicular peritubular cells.

Human testicular peritubular cells (HTPCs) are smooth muscle cells, which in the testis form a small compartment surrounding the seminiferous tubules. Contractions of HTPCs are responsible for sperm transport, HTPCs contribute to spermatogenesis, have immunological roles and are a site of glucocorticoid receptor expression. Importantly, HTPCs maintain their characteristics in vitro, and thus can serve as an experimental window into the male gonad. Previously we reported consequences of 3-day treatment with Dexamethasone (Dex), a synthetic glucocorticoid and multi-purpose anti-inflammatory drug. However, as glucocorticoid therapies in man often last longer, we now studied consequences of a prolonged 7-day exposure to 1 µM Dex. Combining live cell imaging with quantative proteomics of samples taken from men, we confirmed our recent findings but more importantly, found numerous novel proteomic alterations induced by prolonged Dex treatment. The comparison of the 7-day treatment with the 3-day treatment dataset revealed that extracellular matrix- and focal adhesion-related proteins become more prominent after 7 days of treatment. In contrast, extended stimulation is, for example, associated with a decrease of proteins related to cholesterol and steroid metabolism. Our dataset, which describes phenotypic and proteomic alterations, is a valuable resource for further research projects investigating effects of Dex on human testicular cells.

[Testicular adrenal rest tumors (TARTs) and adrenogenital syndrome (AGS) - Do not mix up with malignant testicular tumors!] / Testikuläre adrenale Resttumoren beim adrenogenitalen Syndrom.

Testicular adrenal rest tumors and adrenogenital syndrome (AGS) - Do not mix up with malignant testicular tumors! Testicular adrenal residual tumors (TARTs) frequently occur in men with adrenogenital syndrome. Without knowledge of AGS, diagnosis is problematic due to difficult differentiation from other testicular tumors. However, early treatment is crucial for maintaining or regaining fertility, among other aspects. This article provides background knowledge for general practitioners.

Can perioperative pCO2 gaps predict complications in patients undergoing major elective abdominal surgery randomized to goal-directed therapy or standard care? A secondary analysis.

The difference between venous and arterial carbon dioxide pressure (pCO2 gap), has been used as a diagnostic and prognostic tool. We aimed to assess whether perioperative pCO2 gaps can predict postoperative complications. This was a secondary analysis of a multicenter RCT comparing goal-directed therapy (GDT) to standard care in which 464 patients undergoing high-risk elective abdominal surgery were included. Arterial and central venous blood samples were simultaneously obtained at four time points: after induction, at the end of surgery, at PACU/ICU admission, and PACU/ICU discharge. Complications within the first 30 days after surgery were recorded. Similar pCO2 gaps were found in patients with and without complications, except for the pCO2 gap at the end of surgery, which was higher in patients with complications (6.0 mmHg [5.0-8.0] vs. 6.0 mmHg [4.1-7.5], p = 0.005). The area under receiver operating characteristics curves for predicting complications from pCO2 gaps at all time points were between 0.5 and 0.6. A weak correlation between ScvO2 and pCO2 gaps was found for all timepoints (ρ was between - 0.40 and - 0.29 for all timepoints, p < 0.001). The pCO2 gap did not differ between GDT and standard care at any of the selected time points. In our study, pCO2 gap was a poor predictor of major postoperative complications at all selected time points. Our research does not support the use of pCO2 gap as a prognostic tool after high-risk abdominal surgery. pCO2 gaps were comparable between GDT and standard care. Clinical trial registration Netherlands Trial Registry NTR3380.

The role of translation equivalents in bilingual word learning.

Bilingual environments present an important context for word learning. One feature of bilingual environments is the existence of translation equivalents (TEs)-words in different languages that share similar meanings. Documenting TE learning over development may give us insight into the mechanisms underlying word learning in young bilingual children. Prior studies of TE learning have often been confounded by the fact that increases in overall vocabulary size with age lead to greater opportunities for learning TEs. To address this confound, we employed an item-level analysis, which controls for the age trajectory of each item independently. We used Communicative Development Inventory data from four bilingual datasets (two English-Spanish and two English-French; total N = 419) for modeling. Results indicated that knowing a word's TE increased the likelihood of knowing that word for younger children and for TEs that are more similar phonologically. These effects were consistent across datasets, but varied across lexical categories. Thus, TEs may allow bilingual children to bootstrap their early word learning in one language using their knowledge of the other language. RESEARCH HIGHLIGHTS: Bilingual children must learn words that share a common meaning across both languages, that is, translation equivalents, like dog in English and perro in Spanish. Item-level models explored how translation equivalents affect word learning, in addition to child-level (e.g., exposure) and item-level (e.g., phonological similarity) factors. Knowing a word increased the probability of knowing its corresponding translation equivalent, particularly for younger children and for more phonologically-similar translation equivalents. These findings suggest that young bilingual children use their word knowledge in one language to bootstrap their learning of words in the other language.