Sparse distributed memory using rank-order neural codes.

A variant of a sparse distributed memory (SDM) is shown to have the capability of storing and recalling patterns containing rank-order information. These are patterns where information is encoded not only in the subset of neuron outputs that fire, but also in the order in which that subset fires. This is an interesting companion to several recent works in the neuroscience literature, showing that human memories may be stored in terms of neural spike timings. In our model, the ordering is stored in static synaptic weights using a Hebbian single-shot learning algorithm, and can be reliably recovered whenever the associated input is supplied. It is shown that the memory can operate using only unipolar binary connections throughout. The behavior of the memory under noisy input conditions is also investigated. It is shown that the memory is capable of improving the quality of the data that passes through it. That is, under appropriate conditions the output retrieved from the memory is less noisy than the input used to retrieve it. Thus, this memory architecture could be used as a component in a complex system with stable noise properties and, we argue, it can be implemented using spiking neurons.

Development of a questionnaire weighted scoring system to target diagnostic examinations for asthma in adults: a modelling study.

BACKGROUND: Identification and treatment of unrecognised asthmatics in the community is important for improving the health of the individual and minimising cost and quality of life burden. It is not practical to offer clinical diagnostic assessment to whole communities, and a simple tool such as a questionnaire is required to identify a smaller target group. Conventional questionnaire screening methods which separate individuals into positive and negative categories have resulted in large numbers of individuals requiring clinical assessment. This study has therefore developed and tested a weighted scoring system that prioritises those most urgently in need, based on their questionnaire responses. METHODS: A stratified random sample of adult respondents to a general practice postal questionnaire survey were categorised 'asthmatic' or 'non-asthmatic' according to three expert physicians' opinions. Based on this categorisation, logistic regression was used to derive weights reflecting the relative importance of each question in predicting asthma, allowing calculation of weighted scores reflecting likelihood of asthma. Respondents scoring higher than a chosen threshold would be offered diagnostic examination. RESULTS: Age and presence of wheeze were most influential (weight 3) and overall weighted scores ranged from -1 to 13. Positive predictive values (PPV) were estimated. For example, setting the threshold score at nine gave an estimated PPV for asthma diagnosis of 93.5%, a threshold score of seven corresponded to PPV 78.8%. PPV estimates were supported by examining 145 individuals from a new survey. CONCLUSION: Weighted scoring of questionnaire responses provides a method for evaluating the priority level of an individual 'at a glance', minimising the resource wastage of examining false positives.