Inducing a mental context for associative memory formation with real-time fMRI neurofeedback

Memory, one of the hallmarks of human cognition, can be modified when humans voluntarily modulate neural population activity using neurofeedback. However, it is currently unknown whether neurofeedback can influence the integration of memories, and whether memory is facilitated or impaired after such neural perturbation. In this study, participants memorized objects while we provided them with abstract neurofeedback based on their brain activity patterns in the ventral visual stream. This neurofeedback created an implicit face or house context in the brain while memorizing the objects. The results revealed that participants created associations between each memorized object and its implicit context solely due to the neurofeedback manipulation. Our findings shed light onto how memory formation can be influenced by synthetic memory tags with neurofeedback and advance our understanding of mnemonic processing

Dynamics and topographic organization of recursive self-organizing maps

Recently there has been an outburst of interest in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, there is no general consensus as to how best to process sequences using topographicmaps, and this topic remains an active focus of neurocomputational research. The representational capabilities and internal representations of the models are not well understood. Here, we rigorously analyze a generalization of the self-organizingmap (SOM) for processing sequential data, recursive SOM (RecSOM) (Voegtlin, 2002), as a nonautonomous dynamical system consisting of a set of fixed input maps. We argue that contractive fixed-input maps are likely to produce Markovian organizations of receptive fields on the RecSOM map. We derive bounds on parameter β (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed-input maps is guaranteed. Some generalizations of SOM contain a dynamic module responsible for processing temporal contexts as an integral part of the model. We show that Markovian topographic maps of sequential data can be produced using a simple fixed (nonadaptable) dynamic module externally feeding a standard topographic model designed to process static vectorial data of fixed dimensionality (e.g., SOM). However, by allowing trainable feedback connections, one can obtain Markovian maps with superior memory depth and topography preservation. We elaborate on the importance of non-Markovian organizations in topographic maps of sequential data. © 2006 Massachusetts Institute of Technology

Farmers on film in the fight against striga

With the widespread scaling back of agricultural extension services in Africa, those with a responsibility to deliver information to rural communities are learning to follow new channels. In West Africa, the International Crops Research Institute for the Semi Arid Tropics (ICRISAT) has built on experiences gained by the Africa Rice Center (AfricaRice) in developing a series of ten farmer-to-farmer videos. The ten films are now being widely shown to support rural learning on practical and affordable ways to control one of Africa's most serious weeds - striga..

Medium and Small Scale Analysis of Financial Data

A stochastic analysis of financial data is presented. In particular we investigate how the statistics of log returns change with different time delays $\tau$. The scale dependent behaviour of financial data can be divided into two regions. The first time-range, the small-timescale region (in the range of seconds) seems to be characterized by universal features. The second time-range, the medium-timescale range from several minutes upwards and can be characterized by a cascade process, which is given by a stochastic Markov process in the scale $\tau$. A corresponding Fokker-Planck equation can be extracted from given data and provides a non equilibrium thermodynamical description of the complexity of financial data.Comment: 4 pages, 5 figure

Het gekoppeld grond- en oppervlaktewatermodel MOGROW getest op het Hupselse Beekgebied

Bij het simuleren van een hydrologische situatie is de wisselwerking tussen oppervlaktewater en grondwater belangrijk. Het voor dit doel ontworpen gekoppelde grond- en oppervlaktewatermodel MoGrOW is getest op het Hupselse Beek gebied. Mogrow is een koppeling van de bestaande modellen Simwat (oppervlaktewatermodel) en Simgro (grondwatermodel)