Evidence for Human Fronto-Central Gamma Activity during Long-Term Memory Encoding of Word Sequences

Although human gamma activity (30–80 Hz) associated with visual processing is often reported, it is not clear to what extend gamma activity can be reliably detected non-invasively from frontal areas during complex cognitive tasks such as long term memory (LTM) formation. We conducted a memory experiment composed of 35 blocks each having three parts: LTM encoding, working memory (WM) maintenance and LTM retrieval. In the LTM encoding and WM maintenance parts, participants had to respectively encode or maintain the order of three sequentially presented words. During LTM retrieval subjects had to reproduce these sequences. Using magnetoencephalography (MEG) we identified significant differences in the gamma and beta activity. Robust gamma activity (55–65 Hz) in left BA6 (supplementary motor area (SMA)/pre-SMA) was stronger during LTM rehearsal than during WM maintenance. The gamma activity was sustained throughout the 3.4 s rehearsal period during which a fixation cross was presented. Importantly, the difference in gamma band activity correlated with memory performance over subjects. Further we observed a weak gamma power difference in left BA6 during the first half of the LTM rehearsal interval larger for successfully than unsuccessfully reproduced word triplets. In the beta band, we found a power decrease in left anterior regions during LTM rehearsal compared to WM maintenance. Also this suppression of beta power correlated with memory performance over subjects. Our findings show that an extended network of brain areas, characterized by oscillatory activity in different frequency bands, supports the encoding of word sequences in LTM. Gamma band activity in BA6 possibly reflects memory processes associated with language and timing, and suppression of beta activity at left frontal sensors is likely to reflect the release of inhibition directly associated with the engagement of language functions

Shape Blending of 2-D Piecewise Curves

This paper presents an algorithm for blending #that is, smoothly transforming between# two 2#D shapes bounded by piecewise curves. The algorithm searches for the point correspondence between the two shapes which will minimize the energy required to bend and stretch one shape into the other. The new algorithm runs several times faster than does splitting each curve into #ve line segments and applying a polygon based shape blend algorithm. x1

Implicitization using Moving Curves and Surfaces

This paper presents a radically new approach to the century old problem of computing the implicit equation of a parametric surface. For surfaces without base points, the new method expresses the implicit equation in a determinant which is one fourth the size of the conventional expression based on Dixon's resultant. If base points do exist, previous implicitization methods either fail or become much more complicated, while the new method actually simplifies

S-splines: A simple surface solution for IGA and CAD

This paper introduces S-spline curves and surfaces. Local refinement of S-spline surfaces is much simpler to understand and to implement than T-spline refinement. Furthermore, no unwanted control points arise in S-spline refinement, unlike T-spline refinement. The refinement algorithm assures linear independence of blending functions. Thus, for isogeometric analysis, S-spline surfaces provide optimal degrees of freedom during adaptive local refinement. S-splines are compatible with NURBS and T-splines, and can easily be added to existing T-spline implementations

A Physically Based Approach to 2-D Shape Blending

This paper presents a new algorithm for smoothly blending between two 2#D polygonal shapes. The algorithm is based on a physical model wherein one of the shapes is considered to be constructed of wire, and a solution is found whereby the #rst shape can be bent and#or stretched into the second shape with a minimum amountofwork. The resulting solution tends to associate regions on the two shapes which look alike. If the two polygons have m and n vertices respectively, the algorithm is O#mn#. The algorithm avoids local shape inversions in whichintermediate polygons self-intersect, if such a solution exists. Categories and Subject Descriptors: I.3.3 #Computer Graphics #: Picture#Image Generation; I.3.5 #Computer Graphics#: Computational Geometry and Object Modeling. General Terms: Algorithms Additional Key Words and Phrases: Computer graphics, shape blending, animation, physically based algorithms. 1 Introduction The topic of this paper is illustrated in Figures 1#3. Given two polygonal..

Free-form deformation of solid geometric models

A technique is presented for deforming solid geometric models in a free-form manner. The technique can be used with any solid modeling system, such as CSG or B-rep. It can deform surface primitives of any type or degree: planes, quadrics, parametric surface patches, or implicitly defined surfaces, for example. The deformation can be applied either globally or locally. Local deformations can be imposed with any desired degree of derivative continuity. It is also possible to deform a solid model in such a way that its volume is preserved. The scheme is based on trivariate Bernstein polynomials, and provides the designer with an intuitive appreciation for its effects