A holographic model for associative memory chains

Wess, Othmar; Röder, U.

doi:10.1007/bf00337260

Cited by 13 publications

(7 citation statements)

References 16 publications

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“…Rather, the thresholding influence of ventral cortico-striatal activities on convergent cortical and striatonigrostriatal information passing through the dorsal striatum could generate new functional interactions in networks involved in expressing instrumental behaviors. Although highly speculative, the higherorder components of such an interference pattern (Wess and Roder, 1977) could provide a compact subcortical mechanism for generating the sort of higher-order cortical interactions that are the basis of brain function in general (Friston, 2002). Such a mechanism would explain why disruptions in subcortical structures, like the degradation of nigrostriatal projections in Parkinson's disease, lead to maladaptive functional interactions in cortical networks.…”

Section: Connection Between Reinforcement Signals and Task-specific Nmentioning

confidence: 96%

Error detection in the stop signal task

Chevrier

Schachar

2010

NeuroImage

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Section: Connection Between Reinforcement Signals and Task-specific Nmentioning

confidence: 96%

Error detection in the stop signal task

Chevrier

Schachar

2010

NeuroImage

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“…Associative memory chains based on non-linear concepts and three-dimensional storage mediums were developed by Mager et al [21], Wess et al [22].…”

Section: Holographic Memory Modelmentioning

confidence: 99%

A neural model for chronic pain and pain relief by extracorporeal shock wave treatment

Wess

2008

Urol Res

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The paper develops a new theory of chronic pain and pain relief by extracorporeal shock wave treatment. Chronic pain without underlying anatomical disorder is looked at as a pathological control function of memory. Conditioned reXexes are considered to be engraved memory traces linking sensory input of aVerent signals with motor response of eVerent signals. This feature can be described by associative memory functions of the nervous system. Some conditioned reXexes may cause inappropriate or pathological reactions. Consequently, a circulus vitiosus of pain sensation and muscle and/or vessel contraction is generated when pain becomes chronic (pain spiral). The key feature is a dedicated engram responsible for a pathological (painful) reaction. The pain memory may be explained by the concept of a holographic memory model published by several authors. According to this model it is shown how nervous systems may generate and recall memory contents. The paper shows how extracorporeal shock wave treatment may reorganize pathologic memory traces, thus giving cause to real and permanent pain relief. In a generalized manner, the idea of associative memory functions may help in the understanding of conditioning as a learning process and explain extracorporeal shock wave application as an eYcient treatment concept for chronic pain. This concept may open the door for new treatment approaches to chronic pain and several other disorders of the nervous system.

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“…Once we do this, biology is rife with polycomputing on all scales. An example of this includes the storage of a (very large) number of memories in the same neuronal real-estate of the brain [ 156 , 157 ], and many others are summarized in Table 2 . We do not yet know whether the prevalence of polycomputing is because of its efficiency, robustness, or other gains that override the evolutionary difficulty of finding such solutions.…”

Section: Biology Is Massively Overloaded: Polycomputingmentioning

confidence: 99%

There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines

Bongard

Levin

2023

Biomimetics

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The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as “polycomputing”—the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design principle that helps to understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as to evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.

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A holographic model for associative memory chains

Cited by 13 publications

References 16 publications

Error detection in the stop signal task

Error detection in the stop signal task

A neural model for chronic pain and pain relief by extracorporeal shock wave treatment

There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines

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