The evolutionary neuroscience of tool making

The appearance of the first intentionally modified stone tools over 2.5 million years ago marked a watershed in human evolutionary history, expanding the human adaptive niche and initiating a trend of technological elaboration that continues to the present day. However, the cognitive foundations of this behavioral revolution remain controversial, as do its implications for the nature and evolution of modern human technological abilities. Here we shed new light on the neural and evolutionary foundations of human tool making skill by presenting functional brain imaging data from six inexperienced subjects learning to make stone tools of the kind found in the earliest archaeological record. Functional imaging of this complex, naturalistic task was accomplished through positron emission tomography with the slowly decaying radiological tracer (18)flouro-2-deoxyglucose. Results show that simple stone tool making is supported by a mosaic of primitive and derived parietofrontal perceptual-motor systems, including recently identified human specializations for representation of the central visual field and perception of three-dimensional form from motion. In the naive tool makers reported here, no activation was observed in prefrontal executive cortices associated with strategic action planning or in inferior parietal cortex thought to play a role in the representation of everyday tool use skills. We conclude that uniquely human capacities for sensorimotor adaptation and affordance perception, rather than abstract conceptualization and planning, were central factors in the initial stages of human technological evolution. The appearance of the first intentionally modified stone tools over 2.5 million years ago marked a watershed in human evolutionary history, expanding the human adaptive niche and initiating a trend of technological elaboration that continues to the present day. However, the cognitive foundations of this behavioral revolution remain controversial, as do its implications for the nature and evolution of modern human technological abilities. Here we shed new light on the neural and evolutionary foundations of human tool making skill by presenting functional brain imaging data from six inexperienced subjects learning to make stone tools of the kind found in the earliest archaeological record. Functional imaging of this complex, naturalistic task was accomplished through positron emission tomography with the slowly decaying radiological tracer (18)flouro-2-deoxyglucose. Results show that simple stone tool making is supported by a mosaic of primitive and derived parietofrontal perceptual-motor systems, including recently identified human specializations for representation of the central visual field and perception of three-dimensional form from motion. In the naive tool makers reported here, no activation was observed in prefrontal executive cortices associated with strategic action planning or in inferior parietal cortex thought to play a role in the representation of everyday tool use skills. We conclude that uniquely human capacities for sensorimotor adaptation and affordance perception, rather than abstract conceptualization and planning, were central factors in the initial stages of human technological evolution

Longitudinal EEG power in the first postnatal year differentiates autism outcomes

An aim of autism spectrum disorder (ASD) research is to identify early biomarkers that inform ASD pathophysiology and expedite detection. Brain oscillations captured in electroencephalography (EEG) are thought to be disrupted as core ASD pathophysiology. We leverage longitudinal EEG power measurements from 3 to 36 months of age in infants at low- and high-risk for ASD to test how and when power distinguishes ASD risk and diagnosis by age 3-years. Power trajectories across the first year, second year, or first three years postnatally were submitted to data-driven modeling to differentiate ASD outcomes. Power dynamics during the first postnatal year best differentiate ASD diagnoses. Delta and gamma frequency power trajectories consistently distinguish infants with ASD diagnoses from others. There is also a developmental shift across timescales towards including higher-frequency power to differentiate outcomes. These findings reveal the importance of developmental timing and trajectory in understanding pathophysiology and classifying ASD outcomes.R01 DC010290 - NIDCD NIH HHS; T32 MH112510 - NIMH NIH HHS; U54 HD090255 - NICHD NIH HHSPublished versio

Extending External Agent Capabilities in Healthcare Social Networks

A social health care system, such as palliative care, can be viewed as a social network of interacting patients and care providers. Each patient in the network has a set of capabilities to perform his or her intended daily tasks. However, some patients may not have the required capabilities to carry out their desired tasks. Consequently, different groups of care providers - consist of doctors, volunteers, nurses, etc.- offer the patients support by providing them with a variety of needed services. Assuming there are a cost and resource limitations for providing care within the system, where each care provider can support a limited number of patients, the problem is to find a set of suitable care providers to match the needs of the maximum number of patients. In this dissertation, we propose a novel agent-based model to address this problem by extending the agent\u27s capabilities using the benefit of the social network. Our assumption is that each agent, or patient, can cover its disabilities and perform its desired tasks through collaboration with other agents, or care providers, in the network. The goal of this work is to improve the quality of services in the network at both individual and system levels. On the one hand, an individual patient wants to maximize the quality of his/her life, while at the system level we want to achieve quality care for as many patients as possible with minimum cost. The performance and functionality of this proposed model have been evaluated based on various synthetic networks. The results demonstrate a significant reduction in the operational costs and enhancement of the service quality

The Effects of Parental Behavior on Infants' Neural Processing of Emotion Expressions

Infants become sensitive to emotion expressions early in the 1st year and such sensitivity is likely crucial for social development and adaptation. Social interactions with primary caregivers may play a key role in the development of this complex ability. This study aimed to investigate how variations in parenting behavior affect infants' neural responses to emotional faces. Event-related potentials (ERPs) to emotional faces were recorded from 40 healthy 7-month-old infants (24 males). Parental behavior was assessed and coded using the Emotional Availability Scales during free-play interaction. Sensitive parenting was associated with increased amplitudes to positive facial expressions on the face-sensitive ERP component, the negative central. Findings are discussed in relation to the interactive mechanisms influencing how infants neurally encode positive emotions

A new perspective for the training assessment: Machine learning-based neurometric for augmented user's evaluation

Inappropriate training assessment might have either high social costs and economic impacts, especially in high risks categories, such as Pilots, Air Traffic Controllers, or Surgeons. One of the current limitations of the standard training assessment procedures is the lack of information about the amount of cognitive resources requested by the user for the correct execution of the proposed task. In fact, even if the task is accomplished achieving the maximum performance, by the standard training assessment methods, it would not be possible to gather and evaluate information about cognitive resources available for dealing with unexpected events or emergency conditions. Therefore, a metric based on the brain activity (neurometric) able to provide the Instructor such a kind of information should be very important. As a first step in this direction, the Electroencephalogram (EEG) and the performance of 10 participants were collected along a training period of 3 weeks, while learning the execution of a new task. Specific indexes have been estimated from the behavioral and EEG signal to objectively assess the users' training progress. Furthermore, we proposed a neurometric based on a machine learning algorithm to quantify the user's training level within each session by considering the level of task execution, and both the behavioral and cognitive stabilities between consecutive sessions. The results demonstrated that the proposed methodology and neurometric could quantify and track the users' progresses, and provide the Instructor information for a more objective evaluation and better tailoring of training programs. © 2017 Borghini, Aricò, Di Flumeri, Sciaraffa, Colosimo, Herrero, Bezerianos, Thakor and Babiloni

Modulation of Saccadic Curvature by Spatial Memory and Associative Learning

The way the eye travels during a saccade typically does not follow a straight line but rather shows some curvature instead. Converging empirical evidence has demonstrated that curvature results from conflicting saccade goals when multiple stimuli in the visual periphery compete for selection as the saccade target (Van der Stigchel, Meeter, & Theeuwes, 2006). Curvature away from a competing stimulus has been proposed to result from the inhibitory deselection of the motor program representing the saccade towards that stimulus (Sheliga, Riggio, & Rizzolatti, 1994; Tipper, Howard, & Houghton, 2000). For example, if participants are instructed to perform a saccade towards a defined target stimulus and to ignore a simultaneously presented nearby distractor stimulus, a saccade landing on the target typically exhibits curvature away from the distractor (e. g. Doyle & Walker, 2001). The present thesis reports how trajectories of saccadic eye movements are affected by spatial memory and associative learning. The final objective was to explore if the curvature effect can be used to investigate associative learning in an experimental paradigm where competing saccade targets are retrieved from associative memory rather than being sensory events. The thesis incorporates manuscripts on the following working steps to accomplish this objective: The first manuscript presents the computer software that was written in order to derive measure of saccadic curvature from the recorded eye movement traces. The second manuscript replicates and extends prior reports on the effect of (non-associative) spatial working memory on saccade deviations (Theeuwes, Olivers, & Chizk, 2005). The third manuscript uses a novel associative learning task to demonstrate that changes in saccadic curvature during associative learning comply with the acquisition and extinction of competing associations as predicted by the Rescorla-Wagner model (Rescorla & Wagner, 1972), originally put forward to explain classical conditioning in animals

Making tools and making sense: complex, intentional behaviour in human evolution

Stone tool-making is an ancient and prototypically human skill characterized by multiple levels of intentional organization. In a formal sense, it displays surprising similarities to the multi-level organization of human language. Recent functional brain imaging studies of stone tool-making similarly demonstrate overlap with neural circuits involved in language processing. These observations consistent with the hypothesis that language and tool-making share key requirements for the construction of hierarchically structured action sequences and evolved together in a mutually reinforcing way

Understanding Coordination in the Information Systems Domain: Conceptualization and Implications

In this paper, we suggest a new conceptualization of coordination in the information systems (IS) domain. The conceptualization builds on neurobiological predispositions for coordinating actions. We assume that human evolution has led to the development of a neurobiological substrate that enables individuals to coordinate everyday actions. At heart, we discuss six activity modalities: contextualization, objectivation, spatialization, temporalization, stabilization, and transition. Specifically, we discuss that these modalities need to collectively function for successful coordination. To illustrate as much, we apply our conceptualization to important IS research areas, including project management and interface design. Generally, our new conceptualization holds value for coordination research on all four levels of analysis that we identified based on reviewing the IS literature (i.e., group, intra-organization, inter-organization, and IT artifact). In this way, our new approach, grounded in neurobiological findings, provides a high-level theory to explain coordination success or coordination failure and, hence, is independent from a specific level of analysis. From a practitioner’s perspective, the conceptualization provides a guideline for designing organizational interventions and IT artifacts. Because social initiatives are essential in multiple IS domains (e.g., software development, implementation of enterprise systems) and because the design of collaborative software tools is an important IS topic, this paper contributes to a fundamental phenomenon in the IS domain and does so from a new conceptual perspective

Can Information Systems Foster Emotional Intelligence? A Design Theory-Based Approach

Researchers in Information Systems (IS) have conducted extensive research into various kinds of collaboration systems over the last twenty-five years. A parallel stream of inquiry in psychology and management has developed research in organizational Emotional Intelligence, which contributes to the effectiveness of group interactions by increasing cooperation and reducing conflict. Collaboration systems present a special opportunity to introduce soft management functions such as Emotional Intelligence because they are designed as an intelligent channel of interaction between group members. This research used an Information Systems Design Theory approach to guide the integration of Emotional Intelligence functions into collaboration systems. Two artifact systems were constructed based on these designs, and the systems were utilized and compared in a lab exercise that required group interaction. The findings of the research provide validation of the design approach, evaluation of emotional communication effects, and implications for new dimensions of emotion-based subtext and advisory capabilities that enhance Emotional Intelligence