Opportunities and challenges in high pressure processing of foods

Consumers increasingly demand convenience foods of the highest quality in terms of natural flavor and taste, and which are freedom additives and preservatives. This demand has triggered the need for the development of a number of nonthermal approaches to food processing, of which high-pressure technology has proven to be very valuable. A number of recent publications have demonstrated novel and diverse uses of this technology. Its novel features, which include destruction of microorganisms at room temperature or lower, have made the technology commerically attractive. Enzymes forming bacteria can be by the application of pressure-thermal combinations. This review aims to identify the opportunities and challenges associated with this technology. In addition to discussing the effects of high pressure on food components, this review covers the combined effects of high pressure processing with: gamma irradiation, alternating current, ultrasound, and carbon dioxide or anti-microbial treatment. Further, the applications of this technology in various sectors-fruits and vegetables, dairy and meat processing-have been dealt with extensively. The integration of high-pressure with other matured processing operations such as blanching, dehydration, osmotic dehydration, rehyrdration, frying, freezing/thawing and solid-liquid extraction has been shown to open up new processing options. The key challenges identified include: heat transfer problems and resulting non-uniformity in processing, obtaining reliable and reproducible data, for process validation, lack of detailed knowledge about the interaction between high pressure, and a number of food constituents, packaging and statutory issues.

Does high-frequency repetitive transcranial magnetic stimulation produce residual and/or cumulative effects within an experimental session?

A common procedure for studying the effects on cognition of repetitive transcranial magnetic stimulation (rTMS) is to deliver rTMS concurrent with task performance, and to compare task performance on these trials versus on trials without rTMS. Recent evidence that TMS can have effects on neural activity that persist longer than the experimental session itself, however, raise questions about the assumption of the transient nature of rTMS that underlies many concurrent (or "online") rTMS designs. To our knowledge, there have been no studies in the cognitive domain examining whether the application of brief trains of rTMS during specific epochs of a complex task may have effects that spill over into subsequent task epochs, and perhaps into subsequent trials. We looked for possible immediate spill-over and longer-term cumulative effects of rTMS in data from two studies of visual short-term delayed recognition. In 54 subjects, 10-Hz rTMS trains were applied to five different brain regions during the 3-s delay period of a spatial task, and in a second group of 15 subjects, electroencephalography (EEG) was recorded while 10-Hz rTMS was applied to two brain areas during the 3-s delay period of both spatial and object tasks. No evidence for immediate effects was found in the comparison of the memory probe-evoked response on trials that were vs. were not preceded by delay-period rTMS. No evidence for cumulative effects was found in analyses of behavioral performance, and of EEG signal, as a function of task block. The implications of these findings, and their relation to the broader literature on acute vs. long-lasting effects of rTMS, are considered.

Causal evidence for frontal involvement in memory target maintenance by posterior brain areas during distracter interference of visual working memory

Dorsolateral prefrontal cortex (DLPFC) is recruited during visual working memory (WM) when relevant information must be maintained in the presence of distracting information. The mechanism by which DLPFC might ensure successful maintenance of the contents of WM is, however, unclear; it might enhance neural maintenance of memory targets or suppress processing of distracters. To adjudicate between these possibilities, we applied time-locked transcranial magnetic stimulation (TMS) during functional MRI, an approach that permits causal assessment of a stimulated brain region's influence on connected brain regions, and evaluated how this influence may change under different task conditions. Participants performed a visual WM task requiring retention of visual stimuli (faces or houses) across a delay during which visual distracters could be present or absent. When distracters were present, they were always from the opposite stimulus category, so that targets and distracters were represented in distinct posterior cortical areas. We then measured whether DLPFC-TMS, administered in the delay at the time point when distracters could appear, would modulate posterior regions representing memory targets or distracters. We found that DLPFC-TMS influenced posterior areas only when distracters were present and, critically, that this influence consisted of increased activity in regions representing the current memory targets. DLPFC-TMS did not affect regions representing current distracters. These results provide a new line of causal evidence for a top-down DLPFC-based control mechanism that promotes successful maintenance of relevant information in WM in the presence of distraction.

A dynamic causal model of the coupling between pulse stimulation and neural activity

We present a dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies. Neural responses were measured in terms of local field potentials. These were converted into current source density (CSD) data, and the time series of the CSD sink was extracted to provide a time series response train. The model structure consists of three layers (approximating the responses from the brain stem to the thalamus and then the barrel cortex), and the latter two layers contain nonlinearly coupled modules of linear second-order dynamic systems. The interaction of these modules forms a nonlinear regulatory system that determines the temporal structure of the neural response amplitude for the thalamic and cortical layers. The model is based on the measured population dynamics of neurons rather than the dynamics of a single neuron and was evaluated against CSD data from experiments with varying stimulation frequency (1–40 Hz), random pulse trains, and awake and anesthetized animals. The model parameters obtained by optimization for different physiological conditions (anesthetized or awake) were significantly different. Following Friston, Mechelli, Turner, and Price (2000), this work is part of a formal mathematical system currently being developed (Zheng et al., 2005) that links stimulation to the blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal through neural activity and hemodynamic variables. The importance of the model described here is that it can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity.