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How Generative AI is Revolutionizing the Software Developer Industry
Generative AI is fundamentally transforming the software development industry by improving processes such as software testing, bug detection, bug fixes, and developer productivity. This talk explores how AI-driven techniques, particularly large language models (LLMs), are being utilized to generate realistic test scenarios, automate bug detection and repair, and streamline development workflows. As these technologies evolve, they promise to improve software quality and efficiency significantly. The discussion will cover key methodologies, challenges, and the future impact of generative AI on the software development lifecycle, offering a comprehensive overview of its revolutionary potential in the industry.
Exploring Lifespan Memory Development and Intervention Strategies for Memory Decline through a Unified Model-Based Assessment
Understanding and potentially reversing memory decline necessitates a comprehensive examination of memory's evolution throughout life. Traditional memory assessments, however, suffer from a lack of comparability across different age groups due to the diverse nature of the tests employed. Addressing this gap, our study introduces a novel, ACT-R model-based memory assessment designed to provide a consistent metric for evaluating memory function across a lifespan, from 5 to 85-year-olds. This approach allows for direct comparison across various tasks and materials tailored to specific age groups. Our findings reveal a pronounced U-shaped trajectory of long-term memory function, with performance at age 5 mirroring those observed in elderly individuals with impairments, highlighting critical periods of memory development and decline. Leveraging this unified assessment method, we further investigate the therapeutic potential of rs-fMRI-guided TBS targeting area 8AV in individuals with early-onset Alzheimer’s Disease—a region implicated in memory deterioration and mood disturbances in this population. This research not only advances our understanding of memory's lifespan dynamics but also opens new avenues for targeted interventions in Alzheimer’s Disease, marking a significant step forward in the quest to mitigate memory decay.
Enabling witnesses to actively explore faces and reinstate study-test pose during a lineup increases discrimination accuracy
In 2014, the US National Research Council called for the development of new lineup technologies to increase eyewitness identification accuracy (National Research Council, 2014). In a police lineup, a suspect is presented alongside multiple individuals known to be innocent who resemble the suspect in physical appearance know as fillers. A correct identification decision by an eyewitness can lead to a guilty suspect being convicted or an innocent suspect being exonerated from suspicion. An incorrect decision can result in the perpetrator remaining at large, or even a wrongful conviction of a mistakenly identified person. Incorrect decisions carry considerable human and financial costs, so it is essential to develop and enact lineup procedures that maximise discrimination accuracy, or the witness’ ability to distinguish guilty from innocent suspects. This talk focuses on new technology and innovation in the field of eyewitness identification. We will focus on the interactive lineup, which is a procedure that we developed based on research and theory from the basic science literature on face perception and recognition. The interactive lineup enables witnesses to actively explore and dynamically view the lineup members. The procedure has been shown to maximize discrimination accuracy, which is the witness’ ability to discriminate guilty from innocent suspects. The talk will conclude by reflecting on emerging technological frontiers and research opportunities.
Conversations with Caves? Understanding the role of visual psychological phenomena in Upper Palaeolithic cave art making
How central were psychological features deriving from our visual systems to the early evolution of human visual culture? Art making emerged deep in our evolutionary history, with the earliest art appearing over 100,000 years ago as geometric patterns etched on fragments of ochre and shell, and figurative representations of prey animals flourishing in the Upper Palaeolithic (c. 40,000 – 15,000 years ago). The latter reflects a complex visual process; the ability to represent something that exists in the real world as a flat, two-dimensional image. In this presentation, I argue that pareidolia – the psychological phenomenon of seeing meaningful forms in random patterns, such as perceiving faces in clouds – was a fundamental process that facilitated the emergence of figurative representation. The influence of pareidolia has often been anecdotally observed in Upper Palaeolithic art examples, particularly cave art where the topographic features of cave wall were incorporated into animal depictions. Using novel virtual reality (VR) light simulations, I tested three hypotheses relating to pareidolia in the caves of Upper Palaeolithic cave art in the caves of Las Monedas and La Pasiega (Cantabria, Spain). To evaluate this further, I also developed an interdisciplinary VR eye-tracking experiment, where participants were immersed in virtual caves based on the cave of El Castillo (Cantabria, Spain). Together, these case studies suggest that pareidolia was an intrinsic part of artist-cave interactions (‘conversations’) that influenced the form and placement of figurative depictions in the cave. This has broader implications for conceiving of the role of visual psychological phenomena in the emergence and development of figurative art in the Palaeolithic.
Investigating face processing impairments in Developmental Prosopagnosia: Insights from behavioural tasks and lived experience
The defining characteristic of development prosopagnosia is severe difficulty recognising familiar faces in everyday life. Numerous studies have reported that the condition is highly heterogeneous in terms of both presentation and severity with many mixed findings in the literature. I will present behavioural data from a large face processing test battery (n = 24 DPs) as well as some early findings from a larger survey of the lived experience of individuals with DP and discuss how insights from individuals' real-world experience can help to understand and interpret lab-based data.
Internet interventions targeting grief symptoms
Web-based self-help interventions for coping with prolonged grief have established their efficacy. However, few programs address recent losses and investigate the effect of self-tailoring of the content. In an international project, the text-based self-help program LIVIA was adapted and complemented with an Embodied Conversational Agent, an initial risk assessment and a monitoring tool. The new program SOLENA was evaluated in three trials in Switzerland, the Netherlands and Portugal. The aim of the trials was to evaluate the clinical efficacy for reducing grief, depression and loneliness and to examine client satisfaction and technology acceptance. The talk will present the SOLENA program and report results of the Portuguese and Dutch trial as well as preliminary results of the Swiss RCT. The ongoing Swiss trial compares a standardised to a self-tailored delivery format and analyses clinical outcomes, the helpfulness of specific content and the working alliance. Finally, lessons learned in the development and evaluation of a web-based self-help intervention for older adults will be discusses.
Brain and Behavior: Employing Frequency Tagging as a Tool for Measuring Cognitive Abilities
Frequency tagging based on fast periodic visual stimulation (FPVS) provides a window into ongoing visual and cognitive processing and can be leveraged to measure rule learning and high-level categorization. In this talk, I will present data demonstrating highly proficient categorization as living and non-living in preschool children, and characterize the development of this ability during infancy. In addition to associating cognitive functions with development, an intriguing question is whether frequency tagging also captures enduring individual differences, e.g. in general cognitive abilities. First studies indicate high psychometric quality of FPVS categorization responses (XU et al., Dzhelyova), providing a basis for research on individual differences. I will present results from a pilot study demonstrating high correlations between FPVS categorization responses and behavioral measures of processing speed and fluid intelligences. Drawing upon this first evidence, I will discuss the potential of frequency tagging for diagnosing cognitive functions across development.
Exploring the Potential of High-Density Data for Neuropsychological Testing with Coregraph
Coregraph is a tool under development that allows us to collect high-density data patterns during the administration of classic neuropsychological tests such as the Trail Making Test and Clock Drawing Test. These tests are widely used to evaluate cognitive function and screen for neurodegenerative disorders, but traditional methods of data collection only yield sparse information, such as test completion time or error types. By contrast, the high-density data collected with Coregraph may contribute to a better understanding of the cognitive processes involved in executing these tests. In addition, Coregraph may potentially revolutionize the field of cognitive evaluation by aiding in the prediction of cognitive deficits and in the identification of early signs of neurodegenerative disorders such as Alzheimer's dementia. By analyzing high-density graphomotor data through techniques like manual feature engineering and machine learning, we can uncover patterns and relationships that would be otherwise hidden with traditional methods of data analysis. We are currently in the process of determining the most effective methods of feature extraction and feature analysis to develop Coregraph to its full potential.
What's wrong with the prosopagnosia literature? A new approach to diagnosing and researching the condition
Developmental prosopagnosia is characterised by severe, lifelong difficulties when recognising facial identity. Most researchers require prosopagnosia cases exhibit ultra-conservative levels of impairment on the Cambridge Face Memory Test before they include them in their experiments. This results in the majority of people who believe that they have this condition being excluded from the scientific literature. In this talk I outline the many issues that will afflict prosopagnosia research if this continues, and show that these excluded cases do exhibit impairments on all commonly used diagnostic tests when a group-based method of assessment is utilised. I propose a paradigm shift away from cognitive task-based approaches to diagnosing prosopagnosia, and outline a new way that researchers can investigate this condition.
Biological and experience-based trajectories in adolescent brain and cognitive development
Adolescent development is not only shaped by the mere passing of time and accumulating experience, but it also depends on pubertal timing and the cascade of maturational processes orchestrated by gonadal hormones. Although individual variability in puberty onset confounds adolescent studies, it has not been efficiently controlled for. Here we introduce ultrasonic bone age assessment to estimate biological maturity and disentangle the independent effects of chronological and biological age on adolescent cognitive abilities, emotional development, and brain maturation. Comparing cognitive performance of participants with different skeletal maturity we uncover the impact of biological age on both IQ and specific abilities. With respect to emotional development, we find narrow windows of highest vulnerability determined by biological age. In terms of neural development, we focus on the relevance of neural states unrelated to sensory stimulation, such as cortical activity during sleep and resting states, and we uncover a novel anterior-to-posterior pattern of human brain maturation. Based on our findings, bone age is a promising biomarker of adolescent maturity.
Social Curiosity
In this lecture, I would like to share with the broad audience the empirical results gathered and the theoretical advancements made in the framework of the Lendület project entitled ’The cognitive basis of human sociality’. The main objective of this project was to understand the mechanisms that enable the unique sociality of humans, from the angle of cognitive science. In my talk, I will focus on recent empirical evidence in the study of three fundamental social cognitive functions (social categorization, theory of mind and social learning; mainly from the empirical lenses of developmental psychology) in order to outline a theory that emphasizes the need to consider their interconnectedness. The proposal is that the ability to represent the social world along categories and the capacity to read others’ minds are used in an integrated way to efficiently assess the epistemic states of fellow humans by creating a shared representational space. The emergence of this shared representational space is both the result of and a prerequisite to efficient learning about the physical and social environment.
Forensic use of face recognition systems for investigation
With the increasing development of automatic systems and artificial intelligence, face recognition is becoming increasingly important in forensic and civil contexts. However, face recognition has yet to be thoroughly empirically studied to provide an adequate scientific and legal framework for investigative and court purposes. This observation sets the foundation for the research. We focus on issues related to face images and the use of automatic systems. Our objective is to validate a likelihood ratio computation methodology for interpreting comparison scores from automatic face recognition systems (score-based likelihood ratio, SLR). We collected three types of traces: portraits (ID), video surveillance footage recorded by ATM and by a wide-angle camera (CCTV). The performance of two automatic face recognition systems is compared: the commercial IDEMIA Morphoface (MFE) system and the open source FaceNet algorithm.
Untitled Seminar
The nature of facial information that is stored by humans to recognise large amounts of faces is unclear despite decades of research in the field. To complicate matters further, little is known about how representations may evolve as novel faces become familiar, and there are large individual differences in the ability to recognise faces. I will present a theory I am developing and that assumes that facial representations are cost-efficient. In that framework, individual facial representations would incorporate different diagnostic features in different faces, regardless of familiarity, and would evolve depending on the relative stability in appearance over time. Further, coarse information would be prioritised over fine details in order to decrease storage demands. This would create low-cost facial representations that refine over time if appearance changes. Individual differences could partly rest on that ability to refine representation if needed. I will present data collected in the general population and in participants with developmental prosopagnosia. In support of the proposed view, typical observers and those with developmental prosopagnosia seem to rely on coarse peripheral features when they have no reason to expect someone’s appearance will change in the future.
Developing a test to assess the ability of Zurich’s police cadets to discriminate, learn and recognize voices
The goal of this pilot study is to develop a test through which people with extraordinary voice recognition and discrimination skills can be found (for forensic purposes). Since interest in this field has emerged, three studies have been published with the goal of finding people with potential super-recognition skills in voice processing. One of them is a discrimination test and two are recognition tests, but neither combines the two test scenarios and their test designs cannot be directly compared to a casework scenario in forensics phonetics. The pilot study at hand attempts to bridge this gap and analyses if the skills of voice discrimination and recognition correlate. The study is guided by a practical, forensic application, which further complicates the process of creating a viable test. The participants for the pilot consist of different classes of police cadets, which means the test can be redone and adjusted over time.
What the fluctuating impact of memory load on decision speed tells us about thinking
Previous work with complex memory span tasks, in which simple choice decisions are imposed between presentations of to-be-remembered items, shows that these secondary tasks reduce memory span. It is less clear how reconfiguring and maintaining various amounts of information affects decision speeds. We documented and replicated a non-linear effect of accumulating memory items on concurrent processing judgments, showing that this pattern could be made linear by introducing "lead-in" processing judgments prior to the start of the memory list. With lead-in judgments, there was a large and consistent cost to processing response times with the introduction of the first item in the memory list, which increased gradually per item as the list accumulated. However, once presentation of the list was complete, decision responses sped rapidly: within a few seconds, decisions were at least as fast as when remembering a single item. This pattern of findings is inconsistent with the idea that merely holding information in mind conflicts with attention-demanding decision tasks. Instead, it is possible that reconfiguring memory items for responding provokes conflict between memory and processing in complex span tasks.
The contribution of the dorsal visual pathway to perception and action
The human visual system enables us to recognize objects (e.g., this is a cup) and act upon them (e.g., grasp the cup) with astonishing ease and accuracy. For decades, it was widely accepted that these different functions rely on two separated cortical pathways. The ventral occipitotemporal pathway subserves object recognition, while the dorsal occipitoparietal pathway promotes visually guided actions. In my talk, I will discuss recent evidence from a series of neuropsychological, developmental and neuroimaging studies that were aimed to explore the nature of object representations in the dorsal pathway. The results from these studies highlight the plausible role of the dorsal pathway in object perception and reveal an interplay between shape representations derived by the two pathways. Together, these findings challenge the binary distinction between the two pathways and are consistent with the view that object recognition is not the sole product of ventral pathway computations, but instead relies on a distributed network of regions.
Algorithmic advances in face matching: Stability of tests in atypical groups
Face matching tests have traditionally been developed to assess human face perception in the neurotypical range, but methods that underlie their development often make it difficult for these measures to be applied in atypical populations (developmental prosopagnosics, super recognizers) due to unadjusted difficulty. We have recently presented the development of the Oxford Face Matching Test, a measure that bases individual item-difficulty on algorithmically derived similarity of presented stimuli. The measure seems useful as it can be given online or in-laboratory, has good discriminability and high test-retest reliability in the neurotypical groups. In addition, it has good validity in separating atypical groups at either of the spectrum ends. In this talk, I examine the stability of the OFMT and other traditionally used measures in atypical groups. On top of the theoretical significance of determining whether reliability of tests is equivalent in atypical population, this is an important question because of the practical concerns of retesting the same participants across different lab groups. Theoretical and practical implications for further test development and data sharing are discussed.
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