A methodology for formally modeling and analyzing software architecture of mobile agent systems

A methodology for formally modeling and analyzing software architecture of mobile agent systems provides a solid basis to develop high quality mobile agent systems, and the methodology is helpful to study other distributed and concurrent systems as well. However, it is a challenge to provide the methodology because of the agent mobility in mobile agent systems.^ The methodology was defined from two essential parts of software architecture: a formalism to define the architectural models and an analysis method to formally verify system properties. The formalism is two-layer Predicate/Transition (PrT) nets extended with dynamic channels, and the analysis method is a hierarchical approach to verify models on different levels. The two-layer modeling formalism smoothly transforms physical models of mobile agent systems into their architectural models. Dynamic channels facilitate the synchronous communication between nets, and they naturally capture the dynamic architecture configuration and agent mobility of mobile agent systems. Component properties are verified based on transformed individual components, system properties are checked in a simplified system model, and interaction properties are analyzed on models composing from involved nets. Based on the formalism and the analysis method, this researcher formally modeled and analyzed a software architecture of mobile agent systems, and designed an architectural model of a medical information processing system based on mobile agents. The model checking tool SPIN was used to verify system properties such as reachability, concurrency and safety of the medical information processing system. ^ From successful modeling and analyzing the software architecture of mobile agent systems, the conclusion is that PrT nets extended with channels are a powerful tool to model mobile agent systems, and the hierarchical analysis method provides a rigorous foundation for the modeling tool. The hierarchical analysis method not only reduces the complexity of the analysis, but also expands the application scope of model checking techniques. The results of formally modeling and analyzing the software architecture of the medical information processing system show that model checking is an effective and an efficient way to verify software architecture. Moreover, this system shows a high level of flexibility, efficiency and low cost of mobile agent technologies. ^

Language learning strategy use by colombian adult English language learners: A phenomenological study

The purpose of this phenomenological study was to describe how Colombian adult English language learners (ELL) select and use language learning strategies (LLS). This study used Oxford’s (1990a) taxonomy for LLS as its theoretical framework. Semi-structured interviews and a focus group interview, were conducted, transcribed, and analyzed for 12 Colombian adult ELL. A communicative activity known as strip story (Gibson, 1975) was used to elicit participants’ use of LLS. This activity preceded the focus group session. Additionally, participants’ reflective journals were collected and analyzed. Data were analyzed using inductive, deductive, and comparative analyses. Four themes emerged from the inductive analysis of the data: (a) learning conditions, (b) problem-solving resources, (c) information processing, and (d) target language practice. Oxford’s classification of LLS was used as a guide in deductively analyzing data concerning the participants’ experiences. The deductive analysis revealed that participants do not use certain strategies included in Oxford’s taxonomy at the third level. For example, semantic mapping, or physical response or sensation was not reported by participants. The findings from the inductive and deductive analyses were then compared to look for patterns and answers to the research questions. The comparative analysis revealed that participants used additional LLS that are not included in Oxford’s taxonomy. Some examples of these strategies are: using sound transcription in native language and help from children. The study was conducted at the MDC InterAmerican campus in South Florida, one of the largest Hispanic-influenced communities in the U.S. Based on the findings from this study, the researcher proposed a framework to study LLS that includes both external (i.e., learning context, community) and internal (i.e., culture, prior education) factors that influence the selection and use of LLS. The findings from this study imply that given the importance of the both external and internal factors in learners’ use of LLS, these factors should be considered for inclusion in any study of language learner strategies use by adult learners. Implications for teaching and learning as well as recommendations for further research are provided.

The impact of institutional complexity and top management characteristics on executive compensation and firm performance

While most studies take a dyadic view when examining the environmental difference between the home country of a multinational enterprise (MNE) and a particular foreign country, they ignore that an MNE is managing a network of subsidiaries embedded in diverse environments. Additionally, neither the impacts of global environments on top executives nor the effects of top executives’ capabilities to handle institutional complexity are fully explored. Thus, using a three-essay format, this dissertation tried to fill these gaps by addressing the effects of institutional complexity and top management characteristics on top executive compensation and firm performance. ^ Essay 1 investigated the impact of an MNE’s institutional complexity, or the diversity of national institutions facing an MNE’s network of subsidiaries, on the top management team (TMT) compensation. This essay proposed that greater political and cultural complexity leads to not only greater TMT total compensation but also to a greater portion of TMT compensation linked with long-term performance. The arguments are supported in this essay by using an unbalanced panel dataset including 296 U.S. firms with 1,340 observations. ^ Essay 2 explored TMT social capital and its moderating role on value creation and appropriation by the chief executive officer (CEO). Using a sample with 548 U.S. firms and 2,010 observations, it found that greater TMT social capital does facilitate the effects of CEO intellectual capital and social capital on firm growth. Finally, essay 3 examined the performance implications for the fit between managerial information-processing capabilities and institutional complexity. It proposed that institutional complexity is associated with the needs of information-processing. On the other hand, smaller TMT turnover and larger TMT size reflect larger managerial information-processing capabilities. Consequently, superior performance is achieved by the match among institutional complexity, TMT turnover, and TMT size. All hypotheses in essay 3 are supported in a sample of 301 U.S. firms and 1,404 observations. ^ To conclude, this dissertation advances and extends our knowledge on the roles of institutional environments and top executives on firm performance and top executive compensation.^

Ensemble Stream Model for Data-Cleaning in Sensor Networks

Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as ƒ-test is performed during each node's split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

Towards the prediction of mutations in genomic sequences

Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^

What does board capital really bring to the table? Exploring the effect of directors' human and social capital on effective governance during international expansion

What constitutes effective corporate governance? Which director characteristics render boards effective at positively influencing firm-level performance outcomes? This dissertation examines these questions by taking a multilevel, multidisciplinary approach to corporate governance. I explore the individual-, team-, and firm- level factors that enable directors to serve effectively as strategic resources during international expansion. I argue that directors' international experience improves their ability to serve as effective strategic consultants and resource providers to firms during the complex internationalization process. However, unlike prior research, which tends to assume that directors with the potential to provide important resources uniformly do so, I acknowledge contextual factors (i.e. board cohesiveness, strategic relevance of directors' experience) that affect their propensity to actually influence outcomes. I explore these issues in three essays: one review essay and two empirical essays.^ In the first empirical essay, I integrate resource dependence theory with insights from social-psychological research to explore the influence of board capital on firms' cross-border M&A performance. Using a sample of cross-border M&As completed by S&P 500 firms from 2004-2009, I find evidence that directors' depth of international experience is associated with superior pre-deal outcomes. This suggests that boards' deep, market-specific knowledge is valuable during the target selection phase. I further find that directors' breadth of international experience is associated with superior post-deal performance, suggesting that these directors' global mindset helps firms in the post-M&A integration phase. I also find that these relationships are positively moderated by board cohesiveness, measured by boards' internal social ties.^ In the second empirical essay, I explore the boundary conditions of international board capital by examining how the characteristics of firms' internationalization strategy moderate the relationship between board capital and firm performance. Using a panel of 377 S&P 500 firms observed from 2004-2011, I find that boards' depth of international experience and social capital are more important during early stages of internationalization, when firms tend to lack market knowledge and legitimacy in the host markets. On the other hand, I find that breadth of international experience has a stronger relationship with performance when firms' have higher scope of internationalization, when information-processing demands are higher.^

The effect of study skills instruction on the study strategies and attitudes of college students with learning disabilities

The purpose of this study was to determine the effects of participating in an existing study skills course, developed for use with a general college population, on the study strategies and attitudes of college students with learning disabilities. This study further investigated whether there would be differential effectiveness for segregated and mainstreamed sections of the course.^ The sample consisted of 42 students with learning disabilities attending a southeastern university. Students were randomly assigned to either a segregated or mainstreamed section of the study skills course. In addition, a control group consisted of students with learning disabilities who received no study skills instruction.^ All subjects completed the Learning and Study Strategies Inventory (LASSI) before and after the study skills course. The subjects in the segregated group showed significant improvement on six of the 10 scales of the LASSI: Time Management, Concentration, Information Processing, Selecting Main Ideas, Study Aids, and Self Testing. Subjects in the mainstreamed section showed significant improvement on five scales: Anxiety, Selecting Main Ideas, Study Aids, Self Testing, and Test Strategies. The subjects in the control group did not significantly improve on any of the scales.^ This study showed that college students with learning disabilities improved their study strategies and attitudes by participating in a study skills course designed for a general student population. Further, these students benefitted whether by taking the course only with other students with learning disabilities, or by taking the course in a mixed group of students with or without learning disabilities. These results have important practical implications in that it appears that colleges can use existing study skills courses without having to develop special courses and schedules of course offerings targeted specifically for students with learning disabilities. ^

Glia-augmented artificial neural networks: foundations and applications

Information processing in the human brain has always been considered as a source of inspiration in Artificial Intelligence; in particular, it has led researchers to develop different tools such as artificial neural networks. Recent findings in Neurophysiology provide evidence that not only neurons but also isolated and networks of astrocytes are responsible for processing information in the human brain. Artificial neural net- works (ANNs) model neuron-neuron communications. Artificial neuron-glia networks (ANGN), in addition to neuron-neuron communications, model neuron-astrocyte con- nections. In continuation of the research on ANGNs, first we propose, and evaluate a model of adaptive neuro fuzzy inference systems augmented with artificial astrocytes. Then, we propose a model of ANGNs that captures the communications of astrocytes in the brain; in this model, a network of artificial astrocytes are implemented on top of a typical neural network. The results of the implementation of both networks show that on certain combinations of parameter values specifying astrocytes and their con- nections, the new networks outperform typical neural networks. This research opens a range of possibilities for future work on designing more powerful architectures of artificial neural networks that are based on more realistic models of the human brain.

Resonance fluorescence spectrum of a \Lambda-type quantum emitter close to a metallic nanoparticle

We theoretically study the resonance fluorescence spectrum of a three-level quantum emitter coupled to a spherical metallic nanoparticle. We consider the case that the quantum emitter is driven by a single laser field along one of the optical transitions. We show that the development of the spectrum depends on the relative orientation of the dipole moments of the optical transitions in relation to the metal nanoparticle. In addition, we demonstrate that the location and width of the peaks in the spectrum are strongly modified by the exciton-plasmon coupling and the laser detuning, allowing to achieve controlled strongly subnatural spectral line. A strong antibunching of the fluorescent photons along the undriven transition is also obtained. Our results may be used for creating a tunable source of photons which could be used for a probabilistic entanglement scheme in the field of quantum information processing.

Iterative Phase Optimization of Elementary Quantum Error Correcting Codes

Performing experiments on small-scale quantum computers is certainly a challenging endeavor. Many parameters need to be optimized to achieve high-fidelity operations. This can be done efficiently for operations acting on single qubits, as errors can be fully characterized. For multiqubit operations, though, this is no longer the case, as in the most general case, analyzing the effect of the operation on the system requires a full state tomography for which resources scale exponentially with the system size. Furthermore, in recent experiments, additional electronic levels beyond the two-level system encoding the qubit have been used to enhance the capabilities of quantum-information processors, which additionally increases the number of parameters that need to be controlled. For the optimization of the experimental system for a given task (e.g., a quantum algorithm), one has to find a satisfactory error model and also efficient observables to estimate the parameters of the model. In this manuscript, we demonstrate a method to optimize the encoding procedure for a small quantum error correction code in the presence of unknown but constant phase shifts. The method, which we implement here on a small-scale linear ion-trap quantum computer, is readily applicable to other AMO platforms for quantum-information processing.

Investigating the encoding of visual stimuli by forming neural circuits in the cat primary visual cortex

Contexte La connectomique, ou la cartographie des connexions neuronales, est un champ de recherche des neurosciences évoluant rapidement, promettant des avancées majeures en ce qui concerne la compréhension du fonctionnement cérébral. La formation de circuits neuronaux en réponse à des stimuli environnementaux est une propriété émergente du cerveau. Cependant, la connaissance que nous avons de la nature précise de ces réseaux est encore limitée. Au niveau du cortex visuel, qui est l’aire cérébrale la plus étudiée, la manière dont les informations se transmettent de neurone en neurone est une question qui reste encore inexplorée. Cela nous invite à étudier l’émergence des microcircuits en réponse aux stimuli visuels. Autrement dit, comment l’interaction entre un stimulus et une assemblée cellulaire est-elle mise en place et modulée? Méthodes En réponse à la présentation de grilles sinusoïdales en mouvement, des ensembles neuronaux ont été enregistrés dans la couche II/III (aire 17) du cortex visuel primaire de chats anesthésiés, à l’aide de multi-électrodes en tungstène. Des corrélations croisées ont été effectuées entre l’activité de chacun des neurones enregistrés simultanément pour mettre en évidence les liens fonctionnels de quasi-synchronie (fenêtre de ± 5 ms sur les corrélogrammes croisés corrigés). Ces liens fonctionnels dévoilés indiquent des connexions synaptiques putatives entre les neurones. Par la suite, les histogrammes peri-stimulus (PSTH) des neurones ont été comparés afin de mettre en évidence la collaboration synergique temporelle dans les réseaux fonctionnels révélés. Enfin, des spectrogrammes dépendants du taux de décharges entre neurones ou stimulus-dépendants ont été calculés pour observer les oscillations gamma dans les microcircuits émergents. Un indice de corrélation (Rsc) a également été calculé pour les neurones connectés et non connectés. Résultats Les neurones liés fonctionnellement ont une activité accrue durant une période de 50 ms contrairement aux neurones fonctionnellement non connectés. Cela suggère que les connexions entre neurones mènent à une synergie de leur inter-excitabilité. En outre, l’analyse du spectrogramme dépendant du taux de décharge entre neurones révèle que les neurones connectés ont une plus forte activité gamma que les neurones non connectés durant une fenêtre d’opportunité de 50ms. L’activité gamma de basse-fréquence (20-40 Hz) a été associée aux neurones à décharge régulière (RS) et l’activité de haute fréquence (60-80 Hz) aux neurones à décharge rapide (FS). Aussi, les neurones fonctionnellement connectés ont systématiquement un Rsc plus élevé que les neurones non connectés. Finalement, l’analyse des corrélogrammes croisés révèle que dans une assemblée neuronale, le réseau fonctionnel change selon l’orientation de la grille. Nous démontrons ainsi que l’intensité des relations fonctionnelles dépend de l’orientation de la grille sinusoïdale. Cette relation nous a amené à proposer l’hypothèse suivante : outre la sélectivité des neurones aux caractères spécifiques du stimulus, il y a aussi une sélectivité du connectome. En bref, les réseaux fonctionnels «signature » sont activés dans une assemblée qui est strictement associée à l’orientation présentée et plus généralement aux propriétés des stimuli. Conclusion Cette étude souligne le fait que l’assemblée cellulaire, plutôt que le neurone, est l'unité fonctionnelle fondamentale du cerveau. Cela dilue l'importance du travail isolé de chaque neurone, c’est à dire le paradigme classique du taux de décharge qui a été traditionnellement utilisé pour étudier l'encodage des stimuli. Cette étude contribue aussi à faire avancer le débat sur les oscillations gamma, en ce qu'elles surviennent systématiquement entre neurones connectés dans les assemblées, en conséquence d’un ajout de cohérence. Bien que la taille des assemblées enregistrées soit relativement faible, cette étude suggère néanmoins une intrigante spécificité fonctionnelle entre neurones interagissant dans une assemblée en réponse à une stimulation visuelle. Cette étude peut être considérée comme une prémisse à la modélisation informatique à grande échelle de connectomes fonctionnels.

Utilização de pulsos de radiofrequência fortemente modulados no processamento de informação quântica via ressonância magnética nuclear

Nesta dissertação apresentamos um trabalho de desenvolvimento e utilização de pulsos de radiofreqüência modulados simultaneamente em freqüência, amplitude e fase (pulsos fortemente modulados, SMP, do inglês Strongly Modulated Pulses) para criar estados iniciais e executar operações unitárias que servem como blocos básicos para processamento da informação quântica utilizando Ressonância Magnética Nuclear (RMN). As implementações experimentais foram realizas em um sistema de 3 q-bits constituído por spins nucleares de Césio 133 (spin nuclear 7/2) em uma amostra de cristal líquido em fase nemática. Os pulsos SMP´s foram construídos teoricamente utilizando um programa especialmente desenvolvido para esse fim, sendo o mesmo baseado no processo de otimização numérica Simplex Nelder-Mead. Através deste programa, os pulsos SMP foram otimizados de modo a executarem as operações lógicas desejadas com durações consideravelmente menores que aquelas realizadas usando o procedimento usual de RMN, ou seja, seqüências de pulsos e evoluções livres. Isso tem a vantagem de reduzir os efeitos de descoerência decorrentes da relaxação do sistema. Os conceitos teóricos envolvidos na criação dos SMPs são apresentados e as principais dificuldades (experimentais e teóricas) que podem surgir devido ao uso desses procedimentos são discutidas. Como exemplos de aplicação, foram produzidos os estados pseudo-puros usados como estados iniciais de operações lógicas em RMN, bem como operações lógicas que foram posteriormente aplicadas aos mesmos. Utilizando os SMP\'s também foi possível realizar experimentalmente os algoritmos quânticos de Grover e Deutsch-Jozsa para 3 q-bits. A fidelidade das implementações experimentais foi determinadas utilizando as matrizes densidade experimentais obtidas utilizando um método de tomografia da matriz densidade previamente desenvolvido.

Hand somatosensory sub-cortical sources arehypoactive in migraine interictally: a functionalsource separation analysis

Background: Recent morpho-functional evidences pointed out that abnormalities in the thalamus could play a major role in the expression of migraine neurophysiological and clinical correlates. Whether this phenomenon is primary or secondary to its functional disconnection from the brain stem remains to be determined.Aim: We used a Functional Source Separation algorithmof EEG signal to extract the activity of the different neuronal pools recruited at different latencies along the somatosensory pathway in interictal migraine without aura(MO) patients. Method: Twenty MO patients and 20 healthy volunteers(HV) underwent EEG recording. Four ad-hoc functional constraints, two sub-cortical (FS14 at brain stem andFS16 at thalamic level) and two cortical (FS20 radial andFS22 tangential parietal sources), were used to extract the activity of successive stages of somatosensory information processing in response to the separate left and right median nerve electric stimulation. A band-pass digital filter (450–750 Hz) was applied offline in order to extract high-frequency oscillatory (HFO) activity from the broadband EEG signal. Results: In both stimulated sides, significant reduced subcortical brain stem (FS14) and thalamic (FS16) HFO activations characterized MO patients when compared with HV. No difference emerged in the two cortical HFO activations between two groups. Conclusion: Present results are the first neurophysiological evidence supporting the hypothesis that a functional disconnection of the thalamus from the subcortical monoaminergicsystem may underline the interictal cortical abnormal information processing in migraine. Further studiesare needed to investigate the precise directional connectivity across the entire primary subcortical and cortical somatosensory pathway in interictal MO.

Stimulus Integration and Parsing in the Primate Auditory Midbrain

Integrating information from multiple sources is a crucial function of the brain. Examples of such integration include multiple stimuli of different modalties, such as visual and auditory, multiple stimuli of the same modality, such as auditory and auditory, and integrating stimuli from the sensory organs (i.e. ears) with stimuli delivered from brain-machine interfaces.

The overall aim of this body of work is to empirically examine stimulus integration in these three domains to inform our broader understanding of how and when the brain combines information from multiple sources.

First, I examine visually-guided auditory, a problem with implications for the general problem in learning of how the brain determines what lesson to learn (and what lessons not to learn). For example, sound localization is a behavior that is partially learned with the aid of vision. This process requires correctly matching a visual location to that of a sound. This is an intrinsically circular problem when sound location is itself uncertain and the visual scene is rife with possible visual matches. Here, we develop a simple paradigm using visual guidance of sound localization to gain insight into how the brain confronts this type of circularity. We tested two competing hypotheses. 1: The brain guides sound location learning based on the synchrony or simultaneity of auditory-visual stimuli, potentially involving a Hebbian associative mechanism. 2: The brain uses a ‘guess and check’ heuristic in which visual feedback that is obtained after an eye movement to a sound alters future performance, perhaps by recruiting the brain’s reward-related circuitry. We assessed the effects of exposure to visual stimuli spatially mismatched from sounds on performance of an interleaved auditory-only saccade task. We found that when humans and monkeys were provided the visual stimulus asynchronously with the sound but as feedback to an auditory-guided saccade, they shifted their subsequent auditory-only performance toward the direction of the visual cue by 1.3-1.7 degrees, or 22-28% of the original 6 degree visual-auditory mismatch. In contrast when the visual stimulus was presented synchronously with the sound but extinguished too quickly to provide this feedback, there was little change in subsequent auditory-only performance. Our results suggest that the outcome of our own actions is vital to localizing sounds correctly. Contrary to previous expectations, visual calibration of auditory space does not appear to require visual-auditory associations based on synchrony/simultaneity.

My next line of research examines how electrical stimulation of the inferior colliculus influences perception of sounds in a nonhuman primate. The central nucleus of the inferior colliculus is the major ascending relay of auditory information before it reaches the forebrain, and thus an ideal target for understanding low-level information processing prior to the forebrain, as almost all auditory signals pass through the central nucleus of the inferior colliculus before reaching the forebrain. Thus, the inferior colliculus is the ideal structure to examine to understand the format of the inputs into the forebrain and, by extension, the processing of auditory scenes that occurs in the brainstem. Therefore, the inferior colliculus was an attractive target for understanding stimulus integration in the ascending auditory pathway.

Moreover, understanding the relationship between the auditory selectivity of neurons and their contribution to perception is critical to the design of effective auditory brain prosthetics. These prosthetics seek to mimic natural activity patterns to achieve desired perceptual outcomes. We measured the contribution of inferior colliculus (IC) sites to perception using combined recording and electrical stimulation. Monkeys performed a frequency-based discrimination task, reporting whether a probe sound was higher or lower in frequency than a reference sound. Stimulation pulses were paired with the probe sound on 50% of trials (0.5-80 µA, 100-300 Hz, n=172 IC locations in 3 rhesus monkeys). Electrical stimulation tended to bias the animals’ judgments in a fashion that was coarsely but significantly correlated with the best frequency of the stimulation site in comparison to the reference frequency employed in the task. Although there was considerable variability in the effects of stimulation (including impairments in performance and shifts in performance away from the direction predicted based on the site’s response properties), the results indicate that stimulation of the IC can evoke percepts correlated with the frequency tuning properties of the IC. Consistent with the implications of recent human studies, the main avenue for improvement for the auditory midbrain implant suggested by our findings is to increase the number and spatial extent of electrodes, to increase the size of the region that can be electrically activated and provide a greater range of evoked percepts.

My next line of research employs a frequency-tagging approach to examine the extent to which multiple sound sources are combined (or segregated) in the nonhuman primate inferior colliculus. In the single-sound case, most inferior colliculus neurons respond and entrain to sounds in a very broad region of space, and many are entirely spatially insensitive, so it is unknown how the neurons will respond to a situation with more than one sound. I use multiple AM stimuli of different frequencies, which the inferior colliculus represents using a spike timing code. This allows me to measure spike timing in the inferior colliculus to determine which sound source is responsible for neural activity in an auditory scene containing multiple sounds. Using this approach, I find that the same neurons that are tuned to broad regions of space in the single sound condition become dramatically more selective in the dual sound condition, preferentially entraining spikes to stimuli from a smaller region of space. I will examine the possibility that there may be a conceptual linkage between this finding and the finding of receptive field shifts in the visual system.

In chapter 5, I will comment on these findings more generally, compare them to existing theoretical models, and discuss what these results tell us about processing in the central nervous system in a multi-stimulus situation. My results suggest that the brain is flexible in its processing and can adapt its integration schema to fit the available cues and the demands of the task.

Putting together phylogenetic and ontogenetic perspectives on empathy.

The ontogeny of human empathy is better understood with reference to the evolutionary history of the social brain. Empathy has deep evolutionary, biochemical, and neurological underpinnings. Even the most advanced forms of empathy in humans are built on more basic forms and remain connected to core mechanisms associated with affective communication, social attachment, and parental care. In this paper, we argue that it is essential to consider empathy within a neurodevelopmental framework that recognizes both the continuities and changes in socioemotional understanding from infancy to adulthood. We bring together neuroevolutionary and developmental perspectives on the information processing and neural mechanisms underlying empathy and caring, and show that they are grounded in multiple interacting systems and processes. Moreover, empathy in humans is assisted by other abstract and domain-general high-level cognitive abilities such as executive functions, mentalizing and language, as well as the ability to differentiate another's mental states from one's own, which expand the range of behaviors that can be driven by empathy.