Language problems in the elderly with AD are due to the fact that deterioration occurs not only in semantic memory, but in a group of cognitive factors, evidenced by a deficiency in search strategies for linguistic information.

Veterinarians often give advice in a persuasive form, a style that has been shown to evoke resistance to change in clients experiencing psychological ambivalence (i.e. those who see both advantages and disadvantages to changing). With this style of communication, veterinarians run the risk of counteracting their purpose to encourage clients to follow recommendations. Motivational interviewing (MI) is a client-centered communication methodology that aims to facilitate clients' internal motivation to change. In MI, Change Talk represents clients' own statements expressing consideration of, motivation for or commitment to behavior change and has been shown to be strongly correlated with behavior change. Sustain Talk is corresponding statements related to maintaining the status quo. The aim of this exploratory study was to evaluate the potential of MI to facilitate behavior change in veterinary herd health management (VHHM) by investigating the effect of dairy cattle veterinarians' MI skills on client Change and Sustain Talk. We recorded VHHM consultancies on 170 Swedish cattle farms performed by 36 veterinarians, randomly distributed into 2 groups: MI veterinarians (n = 18) had received 6-month training in MI and control veterinarians (n = 18) had not received any training. Veterinarians' MI skills were assessed using the Motivational Interviewing Treatment Integrity coding system 4.2.1 and categorized as poor_untrained, poor_trained, near moderate and moderate. Client communication was coded using the Client Language Easy Rating coding system. The effect of MI skills on Change Talk, Sustain Talk and Proportion of Change Talk(Change Talk divided by the sum of Sustain Talk plus Change Talk) was investigated using cross-classified regression models with random intercepts for veterinarian and client (farm). The models also included additional explanatory variables (e.g. type of veterinarian and client's satisfaction with the consultation). The veterinarian's MI skills were associated with the client's Change Talk, but results regarding Sustain Talk or Proportion of Change Talk were inconclusive. Clients of veterinarians reaching the highest (i.e. moderate) MI skills expressed 1.5 times more Change Talk than clients of untrained veterinarians. Clients of general large animal practitioners expressed less Sustain Talk than clients of animal health veterinarians and had higher Proportion of Change Talk. Results indicate that learning to practice MI may be one means to improve adherence to veterinary recommendations and to improve efficiency in VHHM services.

The purpose of this study is to provide content validity evidence for the Verbal Behavior Milestones Assessment and Placement Program (VB-MAPP). A national panel of 13 experts provided an evaluation of the domain relevance, age appropriateness, method of measurement appropriateness, and domain representation across the three levels of the Milestones Assessment, Early Echoic Skills Assessment (EESA), and Barriers Assessment. Overall, the content validity evidence for the VB-MAPP Milestones, EESA, and Barriers Assessment was moderate to strong across the evaluated areas although there were areas with limited or conflicting support. The evidence suggests that the scores of the VB-MAPP provide information relevant to the target behaviors of interest but a few domains may not be fully represented by their specific items.

Tests of verbal fluency have been widely used to assess the cognitive functioning of persons, and are typically classified into two categories (semantic and phonological fluency). While widely-distributed divergent and convergent brain regions have been found to be involved in semantic and phonological fluency, the anatomical connectivity underlying the fluency is not well understood. The present study aims to construct a comprehensive white-matter network associated with semantic and phonological fluency by investigating the relationship between the integrity of 22 major tracts in the whole brain and semantic fluency (measured by 3 cues) and phonological fluency (measured by 2 cues) in a group of 51 stroke patients. We found five left-lateralized tracts including the anterior thalamic radiation (ATR), inferior fronto-occipital fasciculus (IFOF), uncinate fasciculus (UF), superior longitudinal fasciculus (SLF) and frontal aslant tract (FAT) were significantly correlated with the scores of both semantic and phonological fluencies. These effects persisted even when we ruled out the influence of potential confounding factors (e.g., total lesion volume). Moreover, the damage to the first three tracts caused additional impairments in the semantic compared to the phonological fluency. These findings reveal the white-matter neuroanatomical connectivity underlying semantic and phonological fluency, and deepen the understanding of the neural network of verbal fluency.

Humans rely on at least two modes of thought: verbal (inner speech) and visual (imagery). Are these modes independent, or does engaging in one entail engaging in the other? To address this question, we performed a behavioral and an fMRI study. In the behavioral experiment, participants received a prompt and were asked to either silently generate a sentence or create a visual image in their mind. They were then asked to judge the vividness of the resulting representation, and of the potentially accompanying representation in the other format. In the fMRI experiment, participants had to recall sentences or images (that they were familiarized with prior to the scanning session) given prompts, or read sentences and view images, in the control, perceptual, condition. An asymmetry was observed between inner speech and visual imagery. In particular, inner speech was engaged to a greater extent during verbal than visual thought, but visual imagery was engaged to a similar extent during both modes of thought. Thus, it appears that people generate more robust verbal representations during deliberate inner speech compared to when their intent is to visualize. However, they generate visual images regardless of whether their intent is to visualize or to think verbally. One possible interpretation of these results is that visual thinking is somehow primary, given the relatively late emergence of verbal abilities during human development and in the evolution of our species.

To determine if sleep talkers with REM sleep behavior disorder (RBD) would utter during REM sleep sentences learned before sleep, and to evaluate their verbal memory consolidation during sleep.

Down syndrome (DS) is an intellectual disability (ID) disorder in which language and specifically, verbal fluency are strongly impaired domains; nearly all adults show neuropathology of Alzheimer's disease (AD), including amyloid deposition by their fifth decade of life. In the general population, verbal fluency deficits are considered a strong AD predictor being the semantic verbal fluency task (SVFT) a useful tool for enhancing early diagnostic. However, there is a lack of information about the association between the semantic verbal fluency pattern (SVFP) and the biological amyloidosis markers in DS. In the current study, we used the SVFT in young adults with DS to characterize their SVFP, assessing total generated words, clustering, and switching. We then explored its association with early indicators of dementia, adaptive behavior and amyloidosis biomarkers, using the Dementia Questionnaire for Persons with Intellectual Disability (DMR), the Adaptive Behavior Assessment System-Second Edition (ABAS-II), and plasma levels of Aβ peptides (Aβ40 and Aβ42), as a potent biomarker of AD. In DS, worse performance in SVFT and poorer communication skills were associated with higher plasma Aβ42 concentrations, a higher DMR score and impaired communication skills (ABAS-II). The total word production and switching ability in SVFT were good indicators of plasma Aβ42 concentration. In conclusion, we propose the SVFT as a good screening test for early detection of dementia and amyloidosis in young adults with DS.

THERE IS A VAST AMOUNT OF POTENTIAL MAPPINGS BETWEEN BEHAVIORS AND INTENTIONS IN COMMUNICATION: a behavior can indicate a multitude of different intentions, and the same intention can be communicated with a variety of behaviors. Humans routinely solve these many-to-many referential problems when producing utterances for an Addressee. This ability might rely on social cognitive skills, for instance, the ability to manipulate unobservable summary variables to disambiguate ambiguous behavior of other agents ("mentalizing") and the drive to invest resources into changing and understanding the mental state of other agents ("communicative motivation"). Alternatively, the ambiguities of verbal communicative interactions might be solved by general-purpose cognitive abilities that process cues that are incidentally associated with the communicative interaction. In this study, we assess these possibilities by testing which cognitive traits account for communicative success during a verbal referential task. Cognitive traits were assessed with psychometric scores quantifying motivation, mentalizing abilities, and general-purpose cognitive abilities, taxing abstract visuo-spatial abilities. Communicative abilities of participants were assessed by using an on-line interactive task that required a speaker to verbally convey a concept to an Addressee. The communicative success of the utterances was quantified by measuring how frequently a number of Evaluators would infer the correct concept. Speakers with high motivational and general-purpose cognitive abilities generated utterances that were more easily interpreted. These findings extend to the domain of verbal communication the notion that motivational and cognitive factors influence the human ability to rapidly converge on shared communicative innovations.

Generative semantic verbal fluency (SVF) tests show early and disproportionate decline relative to other abilities in individuals developing Alzheimer's disease. Optimal performance on SVF tests depends on the efficiency of using clustered organization of semantically related items and the ability to switch between clusters. Traditional approaches to clustering and switching have relied on manual determination of clusters. We evaluated a novel automated computational linguistic approach for quantifying clustering behavior. Our approach is based on Latent Semantic Analysis (LSA) for computing strength of semantic relatedness between pairs of words produced in response to SVF test. The mean size of semantic clusters (MCS) and semantic chains (MChS) are calculated based on pairwise relatedness values between words. We evaluated the predictive validity of these measures on a set of 239 participants in the Nun Study, a longitudinal study of aging. All were cognitively intact at baseline assessment, measured with the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery, and were followed in 18-month waves for up to 20 years. The onset of either dementia or memory impairment were used as outcomes in Cox proportional hazards models adjusted for age and education and censored at follow-up waves 5 (6.3 years) and 13 (16.96 years). Higher MCS was associated with 38% reduction in dementia risk at wave 5 and 26% reduction at wave 13, but not with the onset of memory impairment. Higher [+1 standard deviation (SD)] MChS was associated with 39% dementia risk reduction at wave 5 but not wave 13, and association with memory impairment was not significant. Higher traditional SVF scores were associated with 22-29% memory impairment and 35-40% dementia risk reduction. SVF scores were not correlated with either MCS or MChS. Our study suggests that an automated approach to measuring clustering behavior can be used to estimate dementia risk in cognitively normal individuals.

Individual differences in children's math performance have been associated with math anxiety, attention problems, working memory (WM), and reading skills, but the mechanisms by which these factors jointly contribute to children's math achievement are unknown. Here, we use structural equation modeling to characterize the relation between these factors and their influence on non-verbal Numerical Operations (NO) and verbal Math Reasoning (MR) in 330 children (M=8.34years). Our findings indicate that WM plays a central role in both non-verbal NO and verbal MR, whereas math anxiety and reading comprehension have unique and more pronounced influences on MR, compared to NO. Our study elucidates how affective and cognitive factors distinctly influence non-verbal and verbal mathematical problem solving.

In instructional-learning contexts, the relationship between teacher verbal and non-verbal immediacy and student motivation has gained increasing attention. However, no systematic research has been done to review the empirical studies conducted on the impact of teacher immediacy on students' motivation. Hence, the aim of the present study was to systematically review the available literature on different types of teacher immediacy and student motivation. Some common databases were searched and 30 eligible manuscripts were identified. With regard to the key features of the included studies, the review's findings were categorized into different sections, namely "the measures of teacher immediacy employed," "the measures of student motivation employed," "designs," and "educational contexts". The main findings of the studies were also discussed. The reviewed studies pointed to positive associations between teacher immediacy and student motivation. Finally, limitations of the included studies are discussed and some practical directions for further research are offered, accordingly.

Approach-avoidance behaviors are observed across a broad range of species. For humans, we tend move toward things we like, and away from things we dislike. Previous research tested whether repeatedly shifting visuo-spatial attention toward an object in response to eye gaze cues can increase liking for that object. Here, we tested whether a gaze-liking effect can occur for verbal descriptions of looking behavior without shifts of attention. Also, we tested the gaze specificity hypothesis - that the liking effect is specific to gaze cues - by comparing the effect of different types of cue (pointing gestures and arrow cues). In Experiment 1, participants (N = 205) were split into 5 groups according to the type of cue that was described as directed either toward or away from an object. The results show that (1) attention is not necessary; the liking effect was recorded for verbal descriptions of looking, (2) the effect also occurs for descriptions of pointing and arrows, and (3) the liking effect is enhanced for gaze cues compared to arrows, consistent with the gaze specificity hypothesis. Results from a further experiment suggest that the effect is not due to demand compliance. We conclude that the gaze-liking effect occurs for verbal descriptions of eye gaze. Indeed, because our method bypasses altogether the use of visual cues, objects, and shifts in visual selective attention, our paradigm appears to be more sensitive at tapping into the fundamental approach-avoidance response that mediate the implicit liking effect. As such, it offers new opportunities for research investigations in the future.

Verbal instructions allow humans to acquire and implement complex novel rules in few seconds. A major question that remains elusive is how the brain represents this information prior to successful task execution. In this experiment, we studied the brain regions involved in representing categorical stimulus information during the encoding of novel instructions, their preparation and also their implementation, as well as the relation of the fidelity of these representations to observable behavior. To do so, we devised a novel instructions paradigm to delimitate these three stages. Using univariate and multivariate analyses of functional magnetic resonance data, our study revealed that the semantic content (faces or letters) of complex novel instructions can be decoded several seconds before the onset of a target, as soon as instructions are encoded. Crucially, the quality of the information represented in domain-general and category-selective regions correlated with subsequent behavioral performance. This suggests that the rapid transformation of novel instructions into coherent behavior is supported by control mechanisms that use available, relevant information about the current rule prior to its execution. In addition, our results highlight the relation between these control processes and others such as prospective memory and maintenance of future intentions.

Recent empirical evidence reveals that creative idea generation builds upon an interplay of multiple neural networks. Measures of temporal complexity yield important information about the underlying mechanisms of these co-activated neural networks. A few neurophysiological studies investigated brain signal complexity (BSC) during the production of creative verbal associations and resting states, aiming to relate it with creative task performance. However, it is unknown whether the complexity of brain signals can distinguish between productions of typical and original verbal associations. In the present study, we investigated verbal creativity with multiscale entropy (MSE) of electroencephalography (EEG) signals, which quantifies complexity over multiple timescales, capturing unique dynamic features of neural networks. MSE was measured in verbal divergent thinking (DT) states while emphasizing on producing either typical verbal associations or original verbal associations. We hypothesized that MSE differentiates between brain states characterizing the production of typical and original associations and is a sensitive neural marker of individual differences in producing original associations. Results from a sample of N = 92 young adults revealed slightly higher average MSE for original as compared with typical association production in small and medium timescales at frontal electrodes and slightly higher average MSE for typical association production in higher timescales at parietal electrodes. However, measurement models failed to uncover specificity of individual differences as MSE in typical vs. original associations was perfectly correlated. Hence, individuals with higher MSE in original association condition also exhibit higher MSE during the production of typical associations. The difference between typical and original association MSE was not significantly associated with human-rated originality of the verbal associations. In sum, we conclude that MSE is a potential marker of creative verbal association states, but replications and extensions are needed, especially with respect to the brain-behavior relationships.

The hippocampus is a critical site for alterations that are responsible for age-related changes in memory. Here, we present a relatively novel approach of examining the relationship between memory performance and glutamate-glutamine levels using short echo time magnetic resonance spectroscopy. Specifically, we investigated the relationship between Glx (a composite of glutamate and glutamine) levels in the hippocampus, performance on a word-recall task, and resting-state functional connectivity. While there was no overall difference in Glx intensity between young and aging adults, we identified a positive correlation between delayed word-list recall and Glx, bilaterally in older adults, but not in young adults. Collapsed across age, we also discovered a negative relationship between Glx intensity and resting-state functional connectivity between the anterior hippocampus and regions in the subcallosal gyrus. These findings demonstrate the possible utility of Glx in identifying age-related changes in the brain and behavior and provide encouragement that magnetic resonance spectroscopy can be useful in predicting age-related decline before any physical abnormalities are present.

Non-verbal number sense has been shown to significantly correlate with arithmetic fluency. Accumulated behavioral evidence indicates that the cognitive mechanism relies on visual perception. However, few studies have investigated the neural mechanism underlying this association. Following the visual perception account, we hypothesized that there would be a neural association in occipital areas of the brain between non-verbal number sense, arithmetic fluency, and visual perception. We analyzed event-related potentials that are sensitive to neural responses while participants performed five cognitive tasks: simple addition, simple subtraction, numerosity comparison, figure matching, and character rhyming. The single-trial ERP-behavior correlation approach was used to enhance the statistical power. The results showed that the N1 component significantly correlated with reaction time at occipital electrodes on all tasks except for character rhyming. The N1 component for arithmetic fluency (simple addition and subtraction) and character rhyming correlated with the reaction time for numerosity comparison and figure matching. The results suggest that there are neural associations between arithmetic fluency, non-verbal number sense, and visual perception in the occipital cortex, and that visual perception is the shared mechanism for both non-verbal number sense and arithmetic fluency.

Trust is the foundation of successful human collaboration. This has also been found to be true for human-robot collaboration, where trust has also influence on over- and under-reliance issues. Correspondingly, the study of trust in robots is usually concerned with the detection of the current level of the human collaborator trust, aiming at keeping it within certain limits to avoid undesired consequences, which is known as trust calibration. However, while there is intensive research on human-robot trust, there is a lack of knowledge about the factors that affect it in synchronous and co-located teamwork. Particularly, there is hardly any knowledge about how these factors impact the dynamics of trust during the collaboration. These factors along with trust evolvement characteristics are prerequisites for a computational model that allows robots to adapt their behavior dynamically based on the current human trust level, which in turn is needed to enable a dynamic and spontaneous cooperation. To address this, we conducted a two-phase lab experiment in a mixed-reality environment, in which thirty-two participants collaborated with a virtual CoBot on disassembling traction batteries in a recycling context. In the first phase, we explored the (dynamics of) relevant trust factors during physical human-robot collaboration. In the second phase, we investigated the impact of robot's reliability and feedback on human trust in robots. Results manifest stronger trust dynamics while dissipating than while accumulating and highlight different relevant factors as more interactions occur. Besides, the factors that show relevance as trust accumulates differ from those appear as trust dissipates. We detected four factors while trust accumulates (perceived reliability, perceived dependability, perceived predictability, and faith) which do not appear while it dissipates. This points to an interesting conclusion that depending on the stage of the collaboration and the direction of trust evolvement, different factors might shape trust. Further, the robot's feedback accuracy has a conditional effect on trust depending on the robot's reliability level. It preserves human trust when a failure is expected but does not affect it when the robot works reliably. This provides a hint to designers on when assurances are necessary and when they are redundant.

Verbal insight problem solving means to break mental sets, to select the novel semantic information and to form novel, task-related associations. Although previous studies have identified the brain regions associated with these key processes, the interaction among these regions during insight is still unclear. In the present study, we explored the functional connectivity between the key regions during solving Chinese 'chengyu' riddles by using event-related functional magnetic resonance imaging. Results showed that both insight and noninsight solutions activated the bilateral inferior frontal gyri, middle temporal gyri and hippocampi, and these regions constituted a frontal to temporal to hippocampal neural pathway. Compared with noninsight solution, insight solution had a stronger functional connectivity between the inferior frontal gyrus and middle temporal gyrus in the right hemisphere. Our study reveals the neural pathway of information processing during verbal insight problem solving, and supports the right-hemisphere advantage theory of insight.

Working memory (WM) is central to the acquisition of knowledge and skills throughout childhood and adolescence. While numerous behavioral and task-based functional magnetic resonance imaging (fMRI) studies have examined WM development, few have used resting-state fMRI (R-fMRI). Here, we present a systematic R-fMRI examination of age-related differences in the neural indices of verbal WM performance in a cross-sectional pediatric sample (ages: 7-17; n=68), using data-driven approaches. Verbal WM capacity was measured with the digit span task, a commonly used educational and clinical assessment. We found distinct neural indices of digit span forward (DSF) and backward (DSB) performance, reflecting their unique neuropsychological demands. Regardless of age, DSB performance was related to intrinsic properties of brain areas previously implicated in attention and cognitive control, while DSF performance was related to areas less commonly implicated in verbal WM storage (precuneus, lateral visual areas). From a developmental perspective, DSF exhibited more robust age-related differences in brain-behavior relationships than DSB, and implicated a broader range of networks (ventral attention, default, somatomotor, limbic networks)--including a number of regions not commonly associated with verbal WM (angular gyrus, subcallosum). These results highlight the importance of examining the neurodevelopment of verbal WM and of considering regions beyond the "usual suspects".

Verbal memory is the most commonly impaired cognitive domain in patients with temporal lobe epilepsy (TLE). Although damage to the hippocampus and adjacent temporal lobe structures is known to contribute to memory impairment, little is known of the relative contributions of white versus gray matter structures, or whether microstructural versus morphometric measures of temporal lobe pathology are stronger predictors of impairment. We evaluate whether measures of temporal lobe pathology derived from diffusion tensor imaging (DTI; microstructural) versus structural MRI (sMRI; morphometric) contribute the most to memory performances in TLE, after controlling for hippocampal volume (HCV). DTI and sMRI were performed on 26 patients with TLE and 35 controls. Verbal memory was measured with the Logical Memory (LM) subtest of the Wechsler Memory Scale-III. Hierarchical regression analyses were performed to examine unique contributions of DTI and sMRI measures to verbal memory with HCV entered in block 1. In patients, impaired recall was associated with increased mean diffusivity (MD) of multiple fiber tracts that project through the temporal lobes. In addition, increased MD of the left cortical and bilateral pericortical white matter was associated with impaired recall. After controlling for left HCV, only microstructural measures of white matter pathology contributed to verbal recall. The best predictive model included left HCV and MD of the left inferior longitudinal fasciculus (ILF) and pericortical white matter beneath the left entorhinal cortex. This model explained 60% of the variance in delayed recall and revealed that MD of the left ILF was the strongest predictor. These data reveal that white matter microstructure within the temporal lobe can be used in conjunction with left HCV to enhance the prediction of verbal memory impairment, and speak to the complementary nature of DTI and sMRI for understanding cognitive dysfunction in epilepsy and possibly other memory disorders.