The iso-response method

Throughout the nervous system, neurons integrate high-dimensional input streams and transform them into an output of their own. This integration of incoming signals involves filtering processes and complex non-linear operations. The shapes of these filters and non-linearities determine the computational features of single neurons and their functional roles within larger networks. A detailed characterization of signal integration is thus a central ingredient to understanding information processing in neural circuits. Conventional methods for measuring single-neuron response properties, such as reverse correlation, however, are often limited by the implicit assumption that stimulus integration occurs in a linear fashion. Here, we review a conceptual and experimental alternative that is based on exploring the space of those sensory stimuli that result in the same neural output. As demonstrated by recent results in the auditory and visual system, such iso-response stimuli can be used to identify the non-linearities relevant for stimulus integration, disentangle consecutive neural processing steps, and determine their characteristics with unprecedented precision. Automated closed-loop experiments are crucial for this advance, allowing rapid search strategies for identifying iso-response stimuli during experiments. Prime targets for the method are feed-forward neural signaling chains in sensory systems, but the method has also been successfully applied to feedback systems. Depending on the specific question, “iso-response” may refer to a predefined firing rate, single-spike probability, first-spike latency, or other output measures. Examples from different studies show that substantial progress in understanding neural dynamics and coding can be achieved once rapid online data analysis and stimulus generation, adaptive sampling, and computational modeling are tightly integrated into experiments

From cognitive maps to spatial schemas

A schema refers to a structured body of prior knowledge that captures common patterns across related experiences. Schemas have been studied separately in the realms of episodic memory and spatial navigation across different species and have been grounded in theories of memory consolidation, but there has been little attempt to integrate our understanding across domains, particularly in humans. We propose that experiences during navigation with many similarly structured environments give rise to the formation of spatial schemas (for example, the expected layout of modern cities) that share properties with but are distinct from cognitive maps (for example, the memory of a modern city) and event schemas (such as expected events in a modern city) at both cognitive and neural levels. We describe earlier theoretical frameworks and empirical findings relevant to spatial schemas, along with more targeted investigations of spatial schemas in human and non-human animals. Consideration of architecture and urban analytics, including the influence of scale and regionalization, on different properties of spatial schemas may provide a powerful approach to advance our understanding of spatial schemas

Primary interoceptive cortex activity during simulated experiences of the body

Studies of the classic exteroceptive sensory systems (e.g., vision, touch) consistently demonstrate that vividly imagining a sensory experience of the world – simulating it – is associated with increased activity in the corresponding primary sensory cortex. We hypothesized, analogously, that simulating internal bodily sensations would be associated with increased neural activity in primary interoceptive cortex. An immersive, language-based mental imagery paradigm was used to test this hypothesis (e.g., imagine your heart pounding during a roller coaster ride, your face drenched in sweat during a workout). During two neuroimaging experiments, participants listened to vividly described situations and imagined “being there” in each scenario. In Study 1, we observed significantly heightened activity in primary interoceptive cortex (of dorsal posterior insula) during imagined experiences involving vivid internal sensations. This effect was specific to interoceptive simulation: it was not observed during a separate affect focus condition in Study 1, nor during an independent Study 2 that did not involve detailed simulation of internal sensations (instead involving simulation of other sensory experiences). These findings underscore the large-scale predictive architecture of the brain and reveal that words can be powerful drivers of bodily experiences

"Consciousness". Selected Bibliography 1970 - 2001

This is a bibliography of books and articles on consciousness in philosophy, cognitive science, and neuroscience over the last 30 years. There are three main sections, devoted to monographs, edited collections of papers, and articles. The first two of these sections are each divided into three subsections containing books in each of the main areas of research. The third section is divided into 12 subsections, with 10 subject headings for philosophical articles along with two additional subsections for articles in cognitive science and neuroscience. Of course the division is somewhat arbitrary, but I hope that it makes the bibliography easier to use. This bibliography has first been compiled by Thomas Metzinger and David Chalmers to appear in print in two philosophical anthologies on conscious experience (Metzinger 1995a, b). From 1995 onwards it has been continuously updated by Thomas Metzinger, and now is freely available as a PDF-, RTF-, or HTML-file. This bibliography mainly attempts to cover the Anglo-Saxon and German debates, in a non-annotated, fully formatted way that makes it easy to "cut and paste" from the original file. To a certain degree this bibliography also contains items in other languages than English and German - all submissions in other languages are welcome. Last update of current version: July 13th, 2001

Computational Biology and High Performance Computing 2000

Tutorial to be presented at Supercomputing 2000, Dallas TX, 6-10 November 2000.This work was supported by the Director, Office of Science, Office of Advanced Scientific computing Research, Mathematical, Information, and Computational Sciences Division of the U.S. Department of Energy under Contract No. DE-AC03-76SF0009