Visuospatial Research Articles

Analogical Visuospatial Matrix Reasoning, Verbal Relational Reasoning, Verbal IQ and Memory Relationships With Maths and Science: A Behavioural and fMRI Study

There is no research that combines behavioural and functional magnetic resonance imaging (fMRI) research approaches to investigate the relationships between analogical reasoning and the mediating and moderating effects of working memory, verbal IQ, visuospatial and verbal reasoning on students’ performance of maths and science. This paper investigates all these multiple relationships between working memory (WM), verbal IQ, visuospatial and verbal reasoning with performance in maths and science accuracy. The multimethod research consists of a behavioural survey and a fMRI neuroscience investigating the interactive and multiple relationships of all cognitive independent variables (IVs) with the dependent variables (DVs) of maths and science performance. Using structural Equation Modelling (SEM) and Warp Partial Least Squares (Warp PLS) analytical approach, the research discusses the findings of both, the behavioural and fMRI data. The adolescent sample (N=34) for the behavioural and fMRI study, was recruited from consenting schools in London, UK, and consisted of equal numbers of girls and boys between 11-15 years old. The hypothesised behavioural SEM model predicted positive relationships between all the independent variables (IV) of visuospatial matrix reasoning (VSMatAR), verbal analogical reasoning (VerbAR), verbal working memory (VWM), visuospatial working memory (VSWM) and verbal IQ, with performance in maths and science accuracy. The findings support all hypotheses except two and identifies verbal IQ, Verbal WM and VerbAR as the three strongest predictors of maths and science accuracy. The hypothesised fMRI SEM, produced mixed results, which supported some of the hypothesised relationships between the IVs of verbal AR and VSMatrix AR associations and four brain regions, namely, the bilateral dorso lateral prefrontal cortex (DLPFC), Parietal, Temporal and pre-supplementary motor area (PSMA). The paper makes two original contributions, firstly, by testing the hypothesis that Verbal WM mediates the independent variables’ effects on maths and science outcomes. And secondly, by using Warp PLS to test the SEM (behavioural and fMRI) models’ multiple non-linear interactions simultaneously between the IVs with the DVs of maths and science accuracy. The research produced some interesting new insights relevant for educational practitioners regarding the strong relationships between Verbal analogical reasoning and maths and science performance for adolescent students.

Association of disruption of the right posterior arcuate fasciculus with spatial neglect.

Spatial neglect is a debilitating condition observed in patients with right-sided brain injuries in whom there is defective awareness of the contralesional space. Although classically considered a right parietal lobe deficit, there has been increasing interest in the specific white matter (WM) architecture subserving spatial neglect. Patients who have lesions associated with chronic disruptions in visuospatial networks are of significant relevance in elucidating the WM tracts associated with spatial attention. In this study, the authors used two independent analytical methods to examine the relationship between WM connectivity changes and spatial attention. Thirty patients with right-sided glioma underwent diffusion tensor imaging (DTI) tractography and neuropsychological testing prior to tumor resection. Spatial neglect was assessed using the Bells Test. Diffusion connectometry analysis was performed to calculate the probability of injury to 55 WM tracts. Next, quantitative DTI tractography was used to reconstruct 9 major WM tracts and obtain fractional anisotropy (FA) and streamline number values as indices of connectivity. Differences in connectivity were assessed between patients with neglect and controls. Of the WM tracts analyzed by diffusion connectometry, only the right posterior segment of the arcuate fasciculus (psAF) showed a higher probability of disconnection in patients with evidence of hemispatial neglect compared to tract reconstructions of previously published healthy controls (hemineglect: 42% ± 12.5%, vs control: 6.3% ± 4.8% [mean ± SEM]; p < 0.05). Of the WM tracts reconstructed by DTI tractography, only the right psAF demonstrated consistently lower indices of connectivity based on the mean streamline number (hemineglect: 550.35 ± 183.41, vs control: 1407.01 ± 319.93; p < 0.05) and FA value (hemineglect: 0.40 ± 0.013, vs control: 0.44 ± 0.0063; p < 0.05) in patients who demonstrated neglect compared to controls. The right long segment of the arcuate fasciculus, inferior frontooccipital fasciculus, and inferior longitudinal fasciculus also demonstrated a lower streamline number, but not a lower FA value, in patients with evidence of hemineglect. These findings suggest that parietotemporal networks mediated by the right psAF may play a critical role in visuospatial attention. This analysis may help to disentangle the organization of the visuospatial attention networks, predict deficits in patients with glioma, and optimize surgical planning.

Reduced Visuospatial Attention in Personal Space is Not Limited to the Affected Limb in Complex Regional Pain Syndrome.

Alterations in spatial attention have been reported in people with chronic pain and may be relevant to understanding its cortical mechanisms and developing novel treatments. There is conflicting evidence as to whether people with Complex Regional Pain Syndrome (CRPS) have reduced visuospatial attention to their affected limb and/or its surrounding space, with some evidence that these deficits may be greater in personal (bodily) space. We aimed to test the competing hypotheses of whether the visuospatial attentional bias is specific to the personal space of the affected limb or generalizes to the personal space of other parts of the affected side of the body. Using visual Temporal Order Judgement tasks, we measured spatial attention in the personal space of the hands and feet of patients with upper (n=14) or lower (n=14) limb CRPS and pain-free controls (n=17). Participants judged the order of two light flashes presented at different temporal offsets on each of their hands or feet. Slower processing of the flash on one side relative to the other reflects reduced attention to that side of space. Controls prioritized stimuli on the non-dominant (left) relative to dominant side, consistent with the well-documented normal leftward bias of attention (ie "pseudoneglect"). Regardless of the location (upper or lower limb) of the pain or visual stimuli, people with CRPS showed no such asymmetry, representing reduced attention to the affected side (compared to the greater attention of controls to their non-dominant side). More severe CRPS symptoms were associated with a greater tendency to deprioritize stimuli on the affected side. Our findings suggest that relative visuospatial bias in CRPS is generalized to the personal space of the affected side of the body, rather than being specific to the personal space of the CRPS-affected limb.

Visuospatial cueing differences as a function of autistic traits.

Atypical orienting of visuospatial attention in autistic individuals or individuals with a high level of autistic-like traits (ALTs) has been well documented and viewed as a core feature underlying the development of autism. However, there has been limited testing of three alternative theoretical positions advanced to explain atypical orienting - difficulty in disengagement, cue indifference, and delay in orienting. Moreover, research commonly has not separated facilitation (reaction time difference between neutral and valid cues) and cost effects (reaction time difference between invalid and neutral cues) in orienting tasks. We addressed these limitations in two experiments that compared groups selected for Low- and High-ALT levels on exogenous and endogenous versions of the Posner cueing paradigm. Experiment 1 showed that High-ALT participants exhibited a significantly reduced cost effect compared to Low-ALT participants in the endogenous cueing task, although the overall orienting effect remained small. In Experiment 2, we increased task difficulty of the endogenous task to augment cueing effects. Results were comparable to Experiment 1 regarding the finding of a reduced cost effect for High-ALT participants on the endogenous cueing task and additionally demonstrated a reduced facilitation effect in High-ALT participants on the same task. No ALT group differences were observed on an exogenous cueing task included in Experiment 2. These findings suggest atypical orienting in High-ALT individuals may be attributable to general cue indifference, which implicates differences in top-down attentional processes between Low- and High-ALT individuals. We discuss how indifference to endogenous cues may contribute to social cognitive differences in autism.

An analysis of the essential understandings in elementary geometry and a comparison to the common core standards with teaching implications

Geometry and spatial reasoning form the foundations of learning in mathematics. However, geometry is a subject often ignored by curriculum writers and teachers until high school, leading to students lacking in critical skills in geometric reasoning. As the United States moves into a new curriculum epoch, heralding the commencement of the national common core standards (CCS), one could question if CCS in geometry align with the essential understandings children need to be successful geometric thinkers. This paper begins with an examination of the essential understandings of geometric reasoning leading to an interpretation and critique of the elementary geometry CCS. Finally, the instructional implications are discussed, considering the common core progression through what we know about how children learn geometry.

Enhancing Teachers’ Pedagogical Awareness of Teaching Early Mathematical Skills – A Mixed Methods Study of Tailored Professional Development Program

ABSTRACT The purpose of this mixed methods study was to explore changes in pedagogical awareness of teaching early mathematical skills among teachers in early childhood education (N =7) when participating in a tailored professional development (PD) program in mathematics. The program, which was designed around principles of transformative learning, was aimed at strengthening the conscious and holistic teaching of early mathematical skills to 3- to 7-year-old children. Research Findings: Thematic analysis of semi-structured interviews revealed that teachers enhanced their pedagogical awareness of teaching early mathematical skills concerning developmentally appropriate mathematical content, child-initiated mathematical learning and holistic mathematical teaching in different daily situations and play. Data obtained from pre-PD and follow-up questionnaires completed by teachers confirmed a sustainable increase in their pedagogical awareness of numerical and spatial reasoning. Recognizing children’s interests, reflecting on and examining one’s own practices individually and collaboratively, and taking actions to develop teaching and learning practices aligned with those of the PD program comprised the foundation for the transformative process. Practice or Policy: It was concluded that PD programs in mathematics enhance teachers’ pedagogical awareness of teaching early mathematical skills holistically when they are tailored to the needs of teachers, include reflective elements, and follow principles of transformative learning.

Computer-Assisted Rehabilitation Shows Greater Efficacy Than Traditional in Visuospatial Skills and Cognition in Neglect Patients

This study is crucial for improving unilateral spatial neglect (USN) treatments, focusing on comparing the effectiveness of computer-assisted cognitive rehabilitation (CACR) against conventional rehabilitation (CR) methods. It aimed to address a significant research gap and improve patient outcomes by evaluating the impact of CACR versus CR on visuospatial perception, visual field and attention, and visual memory in patients with USN. This study was a randomized controlled trial. Forty-five consecutive patients with USN from a university rehabilitation center were divided into two groups: 22 patients received CACR with Rehacom software, focusing on saccadic eye movement, visual field, and visual-motor coordination, while 23 underwent CR that combined hemispheric activation approach, mental imagery training, and vibration therapy. Assessments included the Motor-Free Visual Perception Test (MVPT), Line Bisection Test (LBT), Visual Span Test (VST), and Visual Recognition Test (VRT). The study employed ANCOVA and effect size calculations to evaluate the effectiveness of CACR compared to CR in treating patients with USN. Results indicated that CACR significantly outperformed CR in improving visuospatial perception, visual field, attention, and memory, showcasing its effectiveness in treating USN. These findings demonstrate the superiority of CACR over CR, particularly in enhancing visual memory and attention, as evidenced by the large effect size in VRT and moderate effects in LBT and VST. This suggests CACR's potential as a more effective approach for rehabilitation in patients with USN due to brain injuries.

The Influence of Space Standards on Housing Typologies: The Evolution of the Nuclear Family Dwelling in England

This article explores the evolution of dwelling typologies in London, examining how regulations and standards have transformed housing layouts and indirectly informed personal and social interactions at home. Housing policy of the past century, as reflected through space standards, type plans, housing manuals, and reports, reveal a socio-political agenda of promoting nuclear family dwellings, traditionally a household of parents and their children. This article contributes to this discussion by exploring the contextual drivers, spatial reasoning, and evidence underpinning the decisions of housing reports such as the &lt;em&gt;Tudor Walters Report&lt;/em&gt; (1918), the &lt;em&gt;Dudley Report&lt;/em&gt; (1944), and the &lt;em&gt;Parker Morris Report&lt;/em&gt; (1961). Changes in household structures can be seen through regulations: from multiple families sharing a house, to the separation of individual families into single homes, to prioritising the individual over the family unit. This article analyses how five historical moments in which typological shifts promoted nuclear family dwellings that have determined spatial hierarchies and family dynamics around cooking, eating, and socialising. Similarly, societal shifts in housing expectations, such as the changing perceptions of social status symbols, privacy, gender roles, and household dynamics have contributed to the spatial arrangement and layout of homes. By shedding light on the socio-technical transformations, this research highlights the need for innovative design solutions and evidence-based space standards to meet contemporary needs.

Advancing Spatial Reasoning in Large Language Models: An In-Depth Evaluation and Enhancement Using the StepGame Benchmark

Artificial intelligence (AI) has made remarkable progress across various domains, with large language models like ChatGPT gaining substantial attention for their human-like text-generation capabilities. Despite these achievements, improving spatial reasoning remains a significant challenge for these models. Benchmarks like StepGame evaluate AI spatial reasoning, where ChatGPT has shown unsatisfactory performance. However, the presence of template errors in the benchmark has an impact on the evaluation results. Thus there is potential for ChatGPT to perform better if these template errors are addressed, leading to more accurate assessments of its spatial reasoning capabilities. In this study, we refine the StepGame benchmark, providing a more accurate dataset for model evaluation. We analyze GPT’s spatial reasoning performance on the rectified benchmark, identifying proficiency in mapping natural language text to spatial relations but limitations in multi-hop reasoning. We provide a flawless solution to the benchmark by combining template-to-relation mapping with logic-based reasoning. This combination demonstrates proficiency in performing qualitative reasoning on StepGame without encountering any errors. We then address the limitations of GPT models in spatial reasoning. To improve spatial reasoning, we deploy Chain-of-Thought and Tree-of-thoughts prompting strategies, offering insights into GPT’s cognitive process. Our investigation not only sheds light on model deficiencies but also proposes enhancements, contributing to the advancement of AI with more robust spatial reasoning capabilities.

STAIR: Spatial-Temporal Reasoning with Auditable Intermediate Results for Video Question Answering

Recently we have witnessed the rapid development of video question answering models. However, most models can only handle simple videos in terms of temporal reasoning, and their performance tends to drop when answering temporal-reasoning questions on long and informative videos. To tackle this problem we propose STAIR, a Spatial-Temporal Reasoning model with Auditable Intermediate Results for video question answering. STAIR is a neural module network, which contains a program generator to decompose a given question into a hierarchical combination of several sub-tasks, and a set of lightweight neural modules to complete each of these sub-tasks. Though neural module networks are already widely studied on image-text tasks, applying them to videos is a non-trivial task, as reasoning on videos requires different abilities. In this paper, we define a set of basic video-text sub-tasks for video question answering and design a set of lightweight modules to complete them. Different from most prior works, modules of STAIR return intermediate outputs specific to their intentions instead of always returning attention maps, which makes it easier to interpret and collaborate with pre-trained models. We also introduce intermediate supervision to make these intermediate outputs more accurate. We conduct extensive experiments on several video question answering datasets under various settings to show STAIR's performance, explainability, compatibility with pre-trained models, and applicability when program annotations are not available. Code: https://github.com/yellow-binary-tree/STAIR

VELMA: Verbalization Embodiment of LLM Agents for Vision and Language Navigation in Street View

Incremental decision making in real-world environments is one of the most challenging tasks in embodied artificial intelligence. One particularly demanding scenario is Vision and Language Navigation (VLN) which requires visual and natural language understanding as well as spatial and temporal reasoning capabilities. The embodied agent needs to ground its understanding of navigation instructions in observations of a real-world environment like Street View. Despite the impressive results of LLMs in other research areas, it is an ongoing problem of how to best connect them with an interactive visual environment. In this work, we propose VELMA, an embodied LLM agent that uses a verbalization of the trajectory and of visual environment observations as contextual prompt for the next action. Visual information is verbalized by a pipeline that extracts landmarks from the human written navigation instructions and uses CLIP to determine their visibility in the current panorama view. We show that VELMA is able to successfully follow navigation instructions in Street View with only two in-context examples. We further finetune the LLM agent on a few thousand examples and achieve around 25% relative improvement in task completion over the previous state-of-the-art for two datasets.

Spatial-Logic-Aware Weakly Supervised Learning for Flood Mapping on Earth Imagery

Flood mapping on Earth imagery is crucial for disaster management, but its efficacy is hampered by the lack of high-quality training labels. Given high-resolution Earth imagery with coarse and noisy training labels, a base deep neural network model, and a spatial knowledge base with label constraints, our problem is to infer the true high-resolution labels while training neural network parameters. Traditional methods are largely based on specific physical properties and thus fall short of capturing the rich domain constraints expressed by symbolic logic. Neural-symbolic models can capture rich domain knowledge, but existing methods do not address the unique spatial challenges inherent in flood mapping on high-resolution imagery. To fill this gap, we propose a spatial-logic-aware weakly supervised learning framework. Our framework integrates symbolic spatial logic inference into probabilistic learning in a weakly supervised setting. To reduce the time costs of logic inference on vast high-resolution pixels, we propose a multi-resolution spatial reasoning algorithm to infer true labels while training neural network parameters. Evaluations of real-world flood datasets show that our model outperforms several baselines in prediction accuracy. The code is available at https://github.com/spatialdatasciencegroup/SLWSL.

BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions

Vision Language Models (VLMs), which extend Large Language Models (LLM) by incorporating visual understanding capability, have demonstrated significant advancements in addressing open-ended visual question-answering (VQA) tasks. However, these models cannot accurately interpret images infused with text, a common occurrence in real-world scenarios. Standard procedures for extracting information from images often involve learning a fixed set of query embeddings. These embeddings are designed to encapsulate image contexts and are later used as soft prompt inputs in LLMs. Yet, this process is limited to the token count, potentially curtailing the recognition of scenes with text-rich context. To improve upon them, the present study introduces BLIVA: an augmented version of InstructBLIP with Visual Assistant. BLIVA incorporates the query embeddings from InstructBLIP and also directly projects encoded patch embeddings into the LLM, a technique inspired by LLaVA. This approach assists the model to capture intricate details potentially missed during the query decoding process. Empirical evidence demonstrates that our model, BLIVA, significantly enhances performance in processing text-rich VQA benchmarks (up to 17.76% in OCR-VQA benchmark) and in undertaking general (not particularly text-rich) VQA benchmarks (up to 7.9% in Visual Spatial Reasoning benchmark), and achieved 17.72% overall improvement in a comprehensive multimodal LLM benchmark (MME), comparing to our baseline InstructBLIP. BLIVA demonstrates significant capability in decoding real-world images, irrespective of text presence. To demonstrate the broad industry applications enabled by BLIVA, we evaluate the model using a new dataset comprising YouTube thumbnails paired with question-answer sets across 11 diverse categories. For researchers interested in further exploration, our code and models are freely accessible at https://github.com/mlpc-ucsd/BLIVA.

Visuospatial cognition predicts performance on an obstructed vision obstacle walking task in older adults

Walking performance and cognitive function demonstrate strong associations in older adults, with both declining with advancing age. Walking requires the use of cognitive resources, particularly in complex environments like stepping over obstacles. A commonly implemented approach for measuring the cognitive control of walking is a dual-task walking assessment, in which walking is combined with a second task. However, dual-task assessments have shortcomings, including issues with scaling the task difficulty and controlling for task prioritization. Here we present a new assessment designed to be less susceptible to these shortcomings while still challenging cognitive control of walking: the Obstructed Vision Obstacle (OBVIO) task. During the task, participants hold a lightweight tray at waist level obstructing their view of upcoming foam blocks, which are intermittently spaced along a 10 m walkway. This forces the participants to use cognitive resources (e.g., attention and working memory) to remember the exact placement of upcoming obstacles to facilitate successful crossing. The results demonstrate that adding the obstructed vision board significantly slowed walking speed by an average of 0.26 m/s and increased the number of obstacle strikes by 8-fold in healthy older adults (n = 74). Additionally, OBVIO walking performance (a score based on both speed and number of obstacle strikes) significantly correlated with computer-based assessments of visuospatial working memory, attention, and verbal working memory. These results provide initial support that the OBVIO task is a feasible walking test that demands cognitive resources. This study lays the groundwork for using the OBVIO task in future assessment and intervention studies.

A Qualitative Description of Biochemistry Students’ Visuospatial Reasoning Difficulties Associated with Amino Acid Models

The adoption of multimedia learning tools, including visual models in biochemistry, has increased considerably over the last few decades. Adopting these tools necessitates the development of visual literacy competencies, such as visuospatial reasoning, for students to learn effectively. The extent to which biochemistry students have the necessary visuospatial reasoning skills to learn from visual models effectively is a subject of continuing research. The current qualitative research sought to describe biochemistry students’ visuospatial reasoning difficulties associated with amino acids. Seven purposively selected students were interviewed using a semi-structured protocol to solicit their learning difficulties when asked to perform specific tasks related to visuospatial reasoning. The research question explored in this study is: “What are biochemistry students’ visuospatial reasoning difficulties associated with amino acids models?” Learning difficulties related to perceiving spatial orientation, mental rotation, interpreting colour codes, and generating a visual model depicting spatial depth were identified. Identifying and describing these learning difficulties could help teachers adopt remediation strategies to enhance content understanding. The researcher concludes that students may not always have the visuospatial reasoning skills required for successful learning in biochemistry. Given the complex nature of visual literacy, the researcher recommends explicit remediation strategies to address learning difficulties associated with visuospatial reasoning in biochemistry.

CASPER: Cognitive Architecture for Social Perception and Engagement in Robots

AbstractOur world is being increasingly pervaded by intelligent robots with varying degrees of autonomy. To seamlessly integrate themselves in our society, these machines should possess the ability to navigate the complexities of our daily routines even in the absence of a human’s direct input. In other words, we want these robots to understand the intentions of their partners with the purpose of predicting the best way to help them. In this paper, we present the initial iteration of cognitive architecture for social perception and engagement in robots: a symbolic cognitive architecture that uses qualitative spatial reasoning to anticipate the pursued goal of another agent and to calculate the best collaborative behavior. This is performed through an ensemble of parallel processes that model a low-level action recognition and a high-level goal understanding, both of which are formally verified. We have tested this architecture in a simulated kitchen environment and the results we have collected show that the robot is able to both recognize an ongoing goal and to properly collaborate towards its achievement. This demonstrates a new use of qualitative spatial relations applied to the problem of intention reading in the domain of human–robot interaction.

Projective geometry and spatial reasoning for STEM learning

Projective geometry is a prominent area in many fields including art, design, architecture, and mathematics, but how it can contribute to children’s spatial reasoning as well as a supplementary geometry to that of Euclid’s in school mathematics curricula raises the need for further consideration. With emphasis on the dynamic relationship between 2D and 3D objects, projective geometry not only offers important concepts but a meaningful context in which to develop spatial reasoning for STEM learning. In this article, we overview spatial reasoning as it relates to STEM and in particular, mathematics. Making a case for projective geometry, we present activities for the classroom, demonstrating how this mathematics topic connects to and opens new possibilities to promote spatial reasoning for STEM learning in the elementary grades.

A systematic review of transcranial magnetic and direct current stimulation application on the improvement of reading ability of developmental dyslexia

Transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), two non-invasive brain stimulation techniques (NIBS), are modulatory tools to probe into a possible causal and interaction relationship between brain structure and function. Developmental dyslexia (DD) is a neurodevelopmental disorder, which is characterized by significant and persistent difficulty in learning and reading-related skills. Previous studies have shown that TMS and tDCS play an important role in reading ability and neurocognitive plasticity, such as visuospatial working memory, attention, speech recognition, and motor perception. However, research on the effectiveness of TMS/tDCS in treating DD is still limited. The current study aimed to systematically review the broadly application of TMS/tDCS in the treatment of dyslexic children and adolescents as well as adults. Twelve studies involving 128 dyslexic subjects (199 children/adolescents and 29 adults) were included in this systematic review. Overall, TMS/tDCS appeared to be an effective technique for treating dyslexia. However, further future studies with larger sample sizes as well as more different languages are essential to demonstrate its potential for successful intervention in DD. This systematic review suggested that the combination of tDCS and cognitive training was effective. Moreover, the treatment with multiple sessions and coupled with behavioral training appeared to result in greater efficacy than stand-alone NIBS treatment.

Sex-specific neuropsychological correlates of apathy and depression across neurodegenerative disorders.

Apathy and depression are common neuropsychiatric symptoms across neurodegenerative disorders and are associated with impairment in several cognitive domains, yet little is known about the influence of sex on these relationships. We examined the relationship between these symptoms with neuropsychological performance across a combined cohort with mild or major neurodegenerative disorders, then evaluated the impact of sex. We conducted a cohort analysis of participants in the COMPASS-ND study with mild cognitive impairment (MCI), vascular MCI, Alzheimer's disease, mixed dementia, Parkinson's disease, frontotemporal dementia, and cognitively unimpaired (CU) controls. Participants with neurodegenerative disease and CU controls were stratified by the presence (severity ≥1 on Neuropsychiatric Inventory Questionnaire) of either depressive symptoms alone, apathy symptoms alone, both symptoms, or neither. A neuropsychological battery evaluated executive function, verbal fluency, verbal learning, working memory, and visuospatial reasoning. Analysis of covariance was used to assess group differences with age, sex, and education as covariates. Groups included depressive symptoms only (n=70), apathy symptoms only (n=52), both (n=68), or neither (n=262). The apathy and depression+apathy groups performed worse than the neither group on tests of working memory (t(312) =-2.4, p=0.02 and t(328) =-3.8, p=0.001, respectively) and visuospatial reasoning (t(301) =-2.3, p=0.02 and t(321) =-2.6, p=0.01, respectively). The depression, apathy, and depression+apathy groups demonstrated a similar degree of impairment on tests of executive function, processing speed, verbal fluency, and verbal learning when compared to participants without apathy or depression. Sex-stratified analyses revealed that compared to the male neither group, the male apathy and depression+apathy groups were impaired broadly across all cognitive domains except for working memory. Females with depression alone showed deficits on tests of executive function (t(166) =2.4, p=0.01) and verbal learning (t(167) =-4.3, p=0.001) compared to the female neither group. This study demonstrated that in neurodegenerative diseases, apathy with or without depression in males was associated with broad cognitive impairments. In females, depression was associated with deficits in executive function and verbal learning. These findings highlight the importance of effectively treating apathy and depression across the spectrum of neurodegenerative disorders with the goal of optimizing neuropsychological outcomes.

The Complexity of Reading Revealed by a Study with Healthy Older Adults.

Aging, even when healthy, involves changes in cognitive functioning that can gradually affect the everyday activities and well-being of older people. Reading, which requires the integrity of several functions and their integration, is important to maintaining high cognitive and emotional stimulation over time. Our study aimed to investigate whether reading ability declines with aging. To explore also why reading would decline, we explored the changes in the performance of visual and attention tasks. A group of 58 neurologically healthy older people aged from 65 to 75 underwent neuropsychological assessment to investigate their global cognitive functioning, reading skills, crowding, and attention components. We found a decline in reading abilities as a function of aging (β = 0.34, p < 0.05). We did not find an increase in crowding or difficulties in visual acuity. Furthermore, we found no decline with age in tasks of simple reaction times, visuospatial attention, and other single components of attention. Interestingly, we instead found a worsening with age in the Symbol Digit Modalities Test (β = -0.26, p < 0.05), involving attention, working memory, and processing speed, which explains part of the reading decline. Our results suggest that task complexity is a fundamental aspect to account for aging changes.