Evidence for a neural model to evaluate symmetry in V1

50 years ago Hubel and Wiesel discovered simple and complex cells in V1, but there is still no consensus on their functional roles. It is agreed that complex cells are more often selective for direction of motion than simple cells, that there are differences in the way they combine information within their receptive fields, and that complex cells probably receive most of their input from simple cells, but what this serial hierarchy achieves is not understood. There is another puzzling dichotomy that we think is related, namely that of cross-correlation, which is widely accepted as the operation performed on the input image by simple cells, and auto-correlation, which some think underlies the perception of Glass patterns, and possibly motion. We propose the hypothesis that complex cells signal auto-correlations in the visual image, but to evaluate them they require the preliminary analysis done by simple cells, and also pinwheels - structures intervening between simple cells and complex cells that were quite unknown to Hubel and Wiesel. We shall first present psychophysical evidence, using a new kind of random dot display, which suggests that both cross-correlation and auto-correlation are performed in early vision. We then point to recent evidence on the micro-circuitry of pinwheels, and mappings of their intrinsic activity, which shows how pinwheels might enable complex cells to respond selectively to autocorrelations in the input image that activates the simple cells. Auto-correlation is a powerful tool for detecting symmetry, and many may be surprised by evidence that such an abstract property is detected so early in visual perception

Evidence for Auto-Correlation and Symmetry Detection in Primary Visual Cortex

The detectability of patterns in random dot arrays was measured as a function of dot density and compared with the statistical limit set by different methods of detecting the pattern. For filtering, cross-correlation, convolution, or template matching, the limit is expected to be inversely proportional to the square root of dot density. But for auto-correlation, which can detect symmetries of various types, the limit is unaffected by dot density under many conditions. Confirming previous results, we found that the coherence-threshold is often constant for Glass patterns, but the range of constancy depends on details of the display procedure. Coherence-thresholds were found to increase when the average number of dots expected at each location rose towards or exceeded a value of one; we therefore think it results from the non-linear effects of occlusion that occur when a later-programmed dot falls in the same location as an earlier one. To test this, these non-linear effects were prevented by arranging the luminance of each location to be directly proportional to the number of times that location was covered by a dot. Millions of dots can be used for these images, and they retain the streakiness of Glass patterns, while discrete dots disappear. The constant coherence threshold for detecting this streakiness is maintained over a huge range of dot densities, extending right down to the range where discrete dots become visible and up to patterns that are essentially full-tone images with no discrete dots. At threshold, all these patterns have similar auto-correlation functions, as we can see from the way both low dot-number Glass-patterns and these mega-dot, multi-tone, Glass-like images are formed. This startling fact raises the question whether primary visual cortex computes auto-correlations as well as, or even instead of, the local, Fourier-type, wavelet analysis of the currently popular paradigm

Therapeutic leave from secure mental health inpatient services::a review

I am delighted to have been invited to contribute a paper to this liber amicorum for Prof. dr. Frans Koenraadt in honour of his lifetime’s contribution to clinical and theoretical advances in forensic psychology, law, mental health, and education. I first had the pleasure of meeting Frans in Toronto when both he, I, and Lydia Dalhuisen, Frans’ then PhD student, were all presenting work on firesetters and firesetting. Our mutual interest led to further contact and an invitation was extended to me to join the examination panel for Dr Dalhuisen’s PhD thesis defence in Utrecht, a fascinating experience for me since it is not our tradition in the UK to conduct such a public defence. Since then, I have read with great interest and admiration the outputs of the PhD. It was my impression that Prof. Koenraadt provided a highly constructive and flexible educational experience which allowed the PhD room to breathe and grow. My acquaintance with Frans has been short, but I can say with sincerity that his natural curiosity, intellectual openness, and willingness to share his vast accumulated knowledge should serve as a model for us all. In this spirit of sharing, my colleague, EmilyMay Barlow, and I have chosen to address an issue which we feel passionate about. It is also an issue that lies firmly in those intersections between law, criminality, psychology, risk, and clinical practice in which Prof. Koenraadt excels. That issue is the use of therapeutic leave by patients in secure, forensic mental health care

Systematic review of therapeutic leave in inpatient mental health services

AimTo identify, critically evaluate, and synthesise the empirical evidence about therapeutic leave from mental health inpatient settings.Background“Leave” occurs when a mental health inpatient exits the hospital ward with the appropriate authorisation alone, or accompanied by staff, family, or friends. Limited research has previously addressed therapeutic as opposed to unauthorised leave, and the evidence-base has not been systematically evaluated.DesignSystematic review methodology following relevant Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement guidance.Data SourcesMultiple electronic databases (CINAHL; Criminal Justice database; PsycARTICLES; Scopus; OpenGrey; Cochrane; GoogleScholar) for papers published from January 1967 to July 2017.Review MethodsInformation was extracted under the following headings: study, purpose/aims, sample, country, setting, design and data collection method(s), data collection instrument, and results. Papers were assessed, as per the hierarchy of scientific evidence, and where there was sufficient data, we calculated a range of standardised rates of leave incidence.ResultsStandardised leave rates in forensic settings reflect security level. There was little meaningful information on which to base calculation of rates for civil settings. The strongest evidence supports leave used for supervised discharge; other forms of leave lack an evidence base and decisions appear to be made on the basis of heuristic rules and unsupported assumptions. Clinical decision making about therapeutic leave cannot claim to be evidence-based.ConclusionResearch is urgently needed to provide information about how leave is managed, the best ways to support leave, and what happens on leave