Expander Chunked Codes

Chunked codes are efficient random linear network coding (RLNC) schemes with low computational cost, where the input packets are encoded into small chunks (i.e., subsets of the coded packets). During the network transmission, RLNC is performed within each chunk. In this paper, we first introduce a simple transfer matrix model to characterize the transmission of chunks, and derive some basic properties of the model to facilitate the performance analysis. We then focus on the design of overlapped chunked codes, a class of chunked codes whose chunks are non-disjoint subsets of input packets, which are of special interest since they can be encoded with negligible computational cost and in a causal fashion. We propose expander chunked (EC) codes, the first class of overlapped chunked codes that have an analyzable performance,where the construction of the chunks makes use of regular graphs. Numerical and simulation results show that in some practical settings, EC codes can achieve rates within 91 to 97 percent of the optimum and outperform the state-of-the-art overlapped chunked codes significantly.Comment: 26 pages, 3 figures, submitted for journal publicatio

The role of planning in motor learning

Humans can learn a remarkable diversity of motor skills. While these skills are sometimes long lasting, they may also be subject to interference. For example, people can learn to reach in the presence of a dynamic (force-field) perturbation generated by a robotic interface. However, when two force fields that act in opposing directions are presented alternately, there is substantial interference, preventing learning of either. Here we examine the role of motor planning in motor memory formation and interference. We challenge a predominant view of motor learning, which suggests that multiple perturbations can only be learned when each is associated (closely in time) with a different physical (or perceived) state of the body. Instead, we show that two opposing perturbations which interfere when experienced over the same movement, can be learned if each is associated with a different neural state (i.e. motor plan). That is, distinct motor memories can be formed by planning each movement through the perturbation as part of a different, wider motor sequence, even if not executed. Exploring the implications of this result, we subsequently show that like planning, motor imagery of different future movements can change the neural state to affect the separation of motor memories. These results lead us to propose that situations which generate different neural responses in motor-related regions will naturally act as different contexts for learning. Interestingly however, we show that the same principle does not appear to underlie motor memory decay. Finally, having established the importance of planning in motor adaptation, we attempt to predict how motor plans should be divided and recombined when task sets become more complex. We simulate normative control policies under the hypothesis that motor chunking may arise from the need to efficiently represent motor commands, and test the implications for concurrent field learning. Together, these results highlight that the actions that humans plan are critical to the representation of motor skills that are learned. This suggests a key role for motor planning in the broad control repertoire humans develop.PhD funding by a Cambridge-Rutherford Memorial Scholarship, awarded by the Rutherford Foundatio

Micro-, Meso- and Macro-Dynamics of the Brain

Neurosciences, Neurology, Psychiatr

The global vulnerability discovery and disclosure system: a thematic system dynamics approach

Vulnerabilities within software are the fundamental issue that provide both the means, and opportunity for malicious threat actors to compromise critical IT systems (Younis et al., 2016). Consequentially, the reduction of vulnerabilities within software should be of paramount importance, however, it is argued that software development practitioners have historically failed in reducing the risks associated with software vulnerabilities. This failure is illustrated in, and by the growth of software vulnerabilities over the past 20 years. This increase which is both unprecedented and unwelcome has led to an acknowledgement that novel and radical approaches to both understand the vulnerability discovery and disclosure system (VDDS) and to mitigate the risks associate with software vulnerability centred risk is needed (Bradbury, 2015; Marconato et al., 2012). The findings from this research show that whilst technological mitigations are vital, the social and economic features of the VDDS are of critical importance. For example, hitherto unknown systemic themes identified by this research are of key and include; Perception of Punishment; Vendor Interactions; Disclosure Stance; Ethical Considerations; Economic factors for Discovery and Disclosure and Emergence of New Vulnerability Markets. Each theme uniquely impacts the system, and ultimately the scale of vulnerability based risks. Within the research each theme within the VDDS is represented by several key variables which interact and shape the system. Specifically: Vender Sentiment; Vulnerability Removal Rate; Time to fix; Market Share; Participants within VDDS, Full and Coordinated Disclosure Ratio and Participant Activity. Each variable is quantified and explored, defining both the parameter space and progression over time. These variables are utilised within a system dynamic model to simulate differing policy strategies and assess the impact of these policies upon the VDDS. Three simulated vulnerability disclosure futures are hypothesised and are presented, characterised as depletion, steady and exponential with each scenario dependent upon the parameter space within the key variables

Machine Learning

Machine Learning can be defined in various ways related to a scientific domain concerned with the design and development of theoretical and implementation tools that allow building systems with some Human Like intelligent behavior. Machine learning addresses more specifically the ability to improve automatically through experience

Spatio-Temporal and Multisensory Integration: the relationship between sleep and the cerebellum

Does the cerebellum sleep? If so, does sleep contribute to cerebellar cognition? In this thesis, the sleep contribution to the consolidation process of spatial-temporal and multisensory integration was investigated in relation to the human cerebellum. Multiple experimental approaches were used to answer research questions addressed in the various chapters. Summarizing the evidence of the electrophysiology and neuroimaging studies, in Chapter1 we present intriguing evidence that the cerebellum is involved in sleep physiology, and that cerebellar-dependent memory formation can be consolidated during sleep. In Chapter 2, using functional neuroimaging in healthy participants during various forms of the Serial interception sequential learning (SISL) task, i.e., predictive timing, motor coordination, and motor imagination, we assessed the cerebellar involvement in spatio-temporal predictive timing; and possible cerebellar interactions with other regions, most notably the hippocampus. In Chapter 3, we add to the findings of Chapter 2 that indicate the cerebellum and hippocampus are involved in the task, by showing that more than simply activated, the cerebellum is a necessary and responsible region for the establishment of the spatio-temporal prediction. This follows from the deficits in behavioral properties of the predictive and reactive timing in the cerebellar ataxia type 6 patients, using the modified version of the SISL task. In Chapter 4, we assessed the subsequent post-interval behavioral performances on the learning of the fixed and random timing sequences in the SISL task, comparing a sleep group and wake group in healthy participants. Our findings show that sleep consolidates the process of cerebellar-dependent spatio-temporal integration. In Chapter 5, we investigated the establishment of visual-tactile integration during sleep through the examination of tactile motion stimulation during sleep and showed that, subsequent to sleep, directional visual motion discrimination i

Music adapting to the brain: From diffusion chains to neurophysiology

During the last decade, the use of experimental approaches on cultural evolution research has provided novel insights, and supported theoretical predictions, on the principles driving the evolution of human cultural systems. Laboratory simulations of language evolution showed how general-domain constraints on learning, in addition to pressures for language to be expressive, may be responsible for the emergence of linguistic structure. Languages change when culturally transmitted, adapting to fit, among all, the cognitive abilities of their users. As a result, they become regular and compressed, easier to acquire and reproduce. Although a similar theory has been recently extended to the musical domain, the empirical investigation in this field is still scarce. In addition, no study to our knowledge directly addressed the role of cognitive constraints in cultural transmission with neurophysiological investigation. In my thesis I addressed both these issues with a combination of behavioral and neurophysiological methods, in three experimental studies. In study 1 (Chapter 2), I examined the evolution of structural regularities in artificial melodic systems while they were being transmitted across individuals via coordination and alignment. To this purpose I used a new laboratory model of music transmission: the multi-generational signaling games (MGSGs), a variant of the signaling games. This model combines classical aspects of lab-based semiotic models of communication, coordination and interaction (horizontal transmission), with the vertical transmission across generations of the iterated learning model (vertical transmission). Here, two-person signaling games are organized in diffusion chains of several individuals (generations). In each game, the two players (a sender and a receiver) must agree on a common code - here a miniature system where melodic riffs refer to emotions. The receiver in one game becomes the sender in the next game, possibly retransmitting the code previously learned to another generation of participants, and so on to complete the diffusion chain. I observed the gradual evolution of several structures features of musical phrases over generations: proximity, continuity, symmetry, and melodic compression. Crucially, these features are found in most of musical cultures of the world. I argue that we tapped into universal processing mechanisms of structured sequence processing, possibly at work in the evolution of real music. In study 2 (Chapter 3), I explored the link between cultural adaptation and neural information processing. To this purpose, I combined behavioral and EEG study on 2 successive days. I show that the latency of the mismatch negativity (MMN) recorded in a pre-attentive auditory sequence processing task on day 1, predicts how well participants learn and transmit an artificial tone system with affective semantics in two signaling games on day 2. Notably, MMN latencies also predict which structural changes are introduced by participants into the artificial tone system. In study 3 (Chapter 4), I replicated and extended behavioral and neurophysiological findings on the temporal domain of music, with two independent experiments. In the first experiment, I used MGSGs as a laboratory model of cultural evolution of rhythmic equitone patterns referring to distinct emotions. As a result of transmission, rhythms developed a universal property of music structure, namely temporal regularity (or isochronicity). In the second experiment, I anchored this result with neural predictors. I showed that neural information processing capabilities of individuals, as measured with the MMN on day 1, can predict learning, transmission, and regularization of rhythmic patterns in signaling games on day 2. In agreement with study 2, I observe that MMN brain timing may reflect the efficiency of sensory systems to process auditory patterns. Functional differences in those systems, across individuals, may produce a different sensitivity to pressures for regularities in the cultural system. Finally, I argue that neural variability can be an important source of variability of cultural traits in a population. My work is the first to systematically describe the emergence of structural properties of melodic and rhythmic systems in the laboratory, using an explicit game-theoretic model of cultural transmission in which agents freely interact and exchange information. Critically, it provides the first demonstration that social learning, transmission, and cultural adaptation are constrained and driven by individual differences in the functional organization of sensory systems