14 papers · ranked by Valyu relevance
Max F. Burg, Santiago A. Cadena, George H. Denfield, Edgar Y. Walker + 4 more
'Andreas S. Tolias' 'Matthias Bethge' 'Alexander S. Ecker' 'Blake A. Richards'] Divisive normalization (DN) is a prominent computational building block in the brain that has been proposed as a canonical cortical operation. Numerous experimental studies have verified its importance for capturing nonlinear neural…
Stefan F. Bucher, Adam M. Brandenburger
Title: Significance Divisive normalization is a ubiquitous computation commonly thought to be an implementation of the efficient coding principle. Despite empirical evidence that it reduces statistical redundancy present in naturalistic stimuli, making the relationship between this neural code and the statistics of a…
Flaviano Morone, Shivang Rawat, David J. Heeger, Stefano Martiniani
Stability is a fundamental requirement for both biological and engineered neural circuits, yet it is surprisingly difficult to guarantee in the presence of recurrent interactions. Standard linear dynamical models of recurrent networks are unreasonably sensitive to the precise values of the synaptic weights, since…
Jaelyn R. Peiso, Stephanie E. Palmer, Steven K. Shevell
Our visual system usually provides a unique and functional representation of the external world. At times, however, there is more than one compelling interpretation of the same retinal stimulus; in this case, neural populations compete for perceptual dominance to resolve ambiguity. Spatial and temporal context can…
Waitsang Keung, Todd A. Hagen, Robert C. Wilson
Divisive normalization has long been used to account for computations in various neural processes and behaviours. The model proposes that inputs into a neural system are divisively normalized by the system’s total activity. More recently, dynamical versions of divisive normalization have been shown to account for how…
Fabian Sinz, Matthias Bethge, Laurence T. Maloney
Divisive normalization in primary visual cortex has been linked to adaptation to natural image statistics in accordance to Barlow's redundancy reduction hypothesis. Using recent advances in natural image modeling, we show that the previously studied static model of divisive normalization is rather inefficient in…
Udo A. Ernst, Xiao Chen, Lisa Bohnenkamp, Fingal Orlando Galashan + 2 more
'Detlef Wegener' 'Martin Giese'] Sudden changes in visual scenes often indicate important events for behavior. For their quick and reliable detection, the brain must be capable to process these changes as independently as possible from its current activation state. In motion-selective area MT, neurons respond to…
Yanbo Lian, Anthony N. Burkitt, Boris S. Gutkin
Sparse coding, predictive coding and divisive normalization have each been found to be principles that underlie the function of neural circuits in many parts of the brain, supported by substantial experimental evidence. However, the connections between these related principles are still poorly understood. Sparse coding…
Kathy L. Ruddy, David M. Cole, Colin Simon, Marc T. Bächinger
The occurrence of neuronal spikes recorded directly from sensory cortex is highly irregular within and between presentations of an invariant stimulus. The traditional solution has been to average responses across many trials. However, with this approach, response variability is downplayed as noise, so it is assumed…
Joonkoo Park, David E Huber, John T Serences, Joshua I Gold
Many species of animals exhibit an intuitive sense of number, suggesting a fundamental neural mechanism for representing numerosity in a visual scene. Recent empirical studies demonstrate that early feedforward visual responses are sensitive to numerosity of a dot array but substantially less so to continuous…
Aurel A. Lazar, Yiyin Zhou
Divisive normalization is a model of canonical computation of brain circuits. We demonstrate that two cascaded divisive normalization processors (DNPs), carrying out intensity/contrast gain control and elementary motion detection, respectively, can model the robust motion detection realized by the early visual system…
Matthew Chalk, Paul Masset, Sophie Deneve, Boris Gutkin + 1 more
'Wolfgang Einhäuser'] In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition…
Alok Sharma, Yosvany López, Tatsuhiko Tsunoda
Background Biological data comprises various topologies or a mixture of forms, which makes its analysis extremely complicated. With this data increasing in a daily basis, the design and development of efficient and accurate statistical methods has become absolutely necessary. Specific analyses, such as those related to…
Gustavo Glusman, Juan Caballero, Max Robinson, Burak Kutlu + 2 more
'Leroy Hood' 'I. King Jordan'] Deep sequencing of transcriptomes has become an indispensable tool for biology, enabling expression levels for thousands of genes to be compared across multiple samples. Since transcript counts scale with sequencing depth, counts from different samples must be normalized to a common scale…