In celebration of the 2014 Nobel Prize in Physiology or Medicine, this issue of Hippocampus includes a collection of commentaries from a broad range of perspectives on the significance of position coding neurons in th...
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In celebration of the 2014 Nobel Prize in Physiology or Medicine, this issue of Hippocampus includes a collection of commentaries from a broad range of perspectives on the significance of position coding neurons in the hippocampal region. From the perspective of this student of hippocampal physiology, it is argued that place cells and grid cells reflect the outcome of experiments that strongly select the information available and correspondingly observe singular trigger features of these neurons. Notably, however, in more naturalistic situations where multiple dimensions of information are available, hippocampal neurons have mixed selectivity wherein population-firing patterns reflect the organization of many features of experience. Thus, while discoveries on position coding were major breakthroughs in penetrating the hippocampal code, future studies exploring more complex behaviors hold the promise of revealing the full contribution of the hippocampal region to cognition and memory. (c) 2015 Wiley Periodicals, Inc.
We investigated the role of feedback gain in optimal feedback control (OFC) theory using a neuromotor system. Neural studies have shown that directional tuning, known as the "preferred direction" (PD), is a ...
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ISBN:
(纸本)9781479957637
We investigated the role of feedback gain in optimal feedback control (OFC) theory using a neuromotor system. Neural studies have shown that directional tuning, known as the "preferred direction" (PD), is a basic functional property of cell activity in the primary motor cortex (Ml). However, it is not clear which directions the Ml codes for, because neural activities can correlate with several directional parameters, such as joint torque and end-point motion. Thus, to examine the computational mechanism in the Ml, we modeled the isometric motor task of a musculoskeletal system required to generate the desired joint torque. Then, we computed the optimal feedback gain according to OFC. The feedback gain indicated directional tunings of the joint torque and end-point motion in Cartesian space that were similar to the Ml neuron PDs observed in previous studies. Thus, we suggest that the Ml acts as a feedback gain in OFC.
Many concepts in neuromuscular physiology can be difficult for instructors to teach, and for students to understand. The behaviors of various components in neuromuscular systems do not always interact in obvious ways,...
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Many concepts in neuromuscular physiology can be difficult for instructors to teach, and for students to understand. The behaviors of various components in neuromuscular systems do not always interact in obvious ways, and the function of hundreds of components can be very different from the function of just one or two ''representatives.'' In this paper, a simulator is presented that can model both small and large spinal circuitry systems thus allowing students to explore the dynamic functional implications of the static circuitry diagrams that are common in many neuroscience textbooks. The simulator brings to life many concepts in neuromuscular physiology and permits students to explore such concepts without extensive supervision. The benefits and drawbacks of using this kind of simulator in the classroom are discussed, based on initial field tests with undergraduate and graduate students as well as input from the literature. It was found that such a simulation can be very useful as a teaching tool if it is used properly with the right audience.
In the brain, information is encoded, transmitted and used to inform behaviour at the level of timing of action potentials distributed over population of neurons. To implement neural-like systems in silico, to emulate...
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In the brain, information is encoded, transmitted and used to inform behaviour at the level of timing of action potentials distributed over population of neurons. To implement neural-like systems in silico, to emulate neural function, and to interface successfully with the brain, neuromorphic circuits need to encode information in a way compatible to that used by populations of neuron in the brain. To facilitate the cross-talk between neuromorphic engineering and neuroscience, in this review we first critically examine and summarize emerging recent findings about how population of neurons encode and transmit information. We examine the effects on encoding and readout of information for different features of neural population activity, namely the sparseness of neural representations, the heterogeneity of neural properties, the correlations among neurons, and the timescales (from short to long) at which neurons encode information and maintain it consistently over time. Finally, we critically elaborate on how these facts constrain the design of information coding in neuromorphic circuits. We focus primarily on the implications for designing neuromorphic circuits that communicate with the brain, as in this case it is essential that artificial and biological neurons use compatible neural codes. However, we also discuss implications for the design of neuromorphic systems for implementation or emulation of neural computation.
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