Overlapping Structures in Sensory-Motor Mappings

This paper examines a biologically-inspired representation technique designed for the support of sensory-motor learning in developmental robotics. An interesting feature of the many topographic neural sheets in the brain is that closely packed receptive fields must overlap in order to fully cover a spatial region. This raises interesting scientific questions with engineering implications: e.g. is overlap detrimental? does it have any benefits? This paper examines the effects and properties of overlap between elements arranged in arrays or maps. In particular we investigate how overlap affects the representation and transmission of spatial location information on and between topographic maps. Through a series of experiments we determine the conditions under which overlap offers advantages and identify useful ranges of overlap for building mappings in cognitive robotic systems. Our motivation is to understand the phenomena of overlap in order to provide guidance for application in sensory-motor learning robots

A psychology based approach for longitudinal development in cognitive robotics.

A major challenge in robotics is the ability to learn, from novel experiences, new behavior that is useful for achieving new goals and skills. Autonomous systems must be able to learn solely through the environment, thus ruling out a priori task knowledge, tuning, extensive training, or other forms of pre-programming. Learning must also be cumulative and incremental, as complex skills are built on top of primitive skills. Additionally, it must be driven by intrinsic motivation because formative experience is gained through autonomous activity, even in the absence of extrinsic goals or tasks. This paper presents an approach to these issues through robotic implementations inspired by the learning behavior of human infants. We describe an approach to developmental learning and present results from a demonstration of longitudinal development on an iCub humanoid robot. The results cover the rapid emergence of staged behavior, the role of constraints in development, the effect of bootstrapping between stages, and the use of a schema memory of experiential fragments in learning new skills. The context is a longitudinal experiment in which the robot advanced from uncontrolled motor babbling to skilled hand/eye integrated reaching and basic manipulation of objects. This approach offers promise for further fast and effective sensory-motor learning techniques for robotic learning

Sensitive MRD detection from lymphatic fluid after surgery in HPV-associated oropharyngeal cancer

PURPOSE: Our goal was to demonstrate that lymphatic drainage fluid (lymph) has improved sensitivity in quantifying postoperative minimal residual disease (MRD) in locally advanced human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) compared with plasma, and leverage this novel biofluid for patient risk stratification. EXPERIMENTAL DESIGN: We prospectively collected lymph samples from neck drains of 106 patients with HPV (+) OPSCC, along with 67 matched plasma samples, 24 hours after surgery. PCR and next-generation sequencing were used to quantify cancer-associated cell-free HPV (cf-HPV) and tumor-informed variants in lymph and plasma. Next, lymph cf-HPV and variants were compared with TNM stage, extranodal extension (ENE), and composite definitions of high-risk pathology. We then created a machine learning model, informed by lymph MRD and clinicopathologic features, to compare with progression-free survival (PFS). RESULTS: Postoperative lymph was enriched with cf-HPV compared with plasma (P \u3c 0.0001) and correlated with pN2 stage (P = 0.003), ENE (P \u3c 0.0001), and trial-defined pathologic risk criteria (mean AUC = 0.78). In addition, the lymph mutation number and variant allele frequency were higher in pN2 ENE (+) necks than in pN1 ENE (+) (P = 0.03, P = 0.02) or pN0-N1 ENE (-) (P = 0.04, P = 0.03, respectively). The lymph MRD-informed risk model demonstrated inferior PFS in high-risk patients (AUC = 0.96, P \u3c 0.0001). CONCLUSIONS: Variant and cf-HPV quantification, performed in 24-hour postoperative lymph samples, reflects single- and multifeature high-risk pathologic criteria. Incorporating lymphatic MRD and clinicopathologic feature analysis can stratify PFS early after surgery in patients with HPV (+) head and neck cancer. See related commentary by Shannon and Iyer, p. 1223

Field coverage.

<p>Areas of overlap with increasing field radius. Abscissa is field radius; ordinate gives coverage per unit area of the 2D plane.</p

Vector based reaching performance.

<p>Shows the average percentage of extra distance travelled over the ideal distance whilst moving the hand of the robot through a set of points in the gaze space. Each bar demonstrates the change in performance with increasing field radius . The experiment was performed with random (left) and rectangular based grid (right) topologies.</p

Response curve comparison.

<p>Response curves for Cosine 0.8, Gaussian 0.4 and Sigmoid 2.4. The input is along the abscissa and the response is along the ordinate.</p

Example mapping. An to mapping with many-to-one structure.

<p>Example mapping. An to mapping with many-to-one structure.</p

Total connectivity.

<p>Typical structure in artificial neural nets.</p

Transformation error comparisons.

<p>Error plots of cross modal maps using a compression transformation function and varying: distance (top), radius (middle) and placement error (bottom). The results compare the behaviours of the many-to-one and the weighted link many-to-many method. In each graph the transmitting map is fixed at , distance spacing and zero placement error, whilst the receiving map is adjusted as described in the abscissa.</p

Overlap examples.

<p>Field overlap on regular triangular mesh, 10×10 fields, (left) and (right)</p