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A Novel Nonparametric Approach for Neural Encoding and decoding Models of Multimodal Receptive Fields

NEURAL COMPUTATION 2016年第7期28卷 1356-1387页

作者： Agarwal, Rahul Chen, Zhe Kloosterman, Fabian Wilson, Matthew A. Sarma, Sridevi V. Johns Hopkins Univ Dept Biomed Engn Baltimore MD 21218 USA NYU Sch Med Dept Psychiat New York NY 10016 USA NYU Sch Med Dept Neurosci & Physiol New York NY 10016 USA Neuroelect Res Flanders Leuven Belgium IMEC Leuven Belgium Katholieke Univ Leuven Brain & Cognit Res Unit B-3000 Leuven Belgium MIT Picower Inst Learning & Memory 77 Massachusetts Ave Cambridge MA 02139 USA

Pyramidal neurons recorded from the rat hippocampus and entorhinal cortex, such as place and grid cells, have diverse receptive fields, which are either unimodal or multimodal. Spiking activity from these cells encodes information about the spatial position of a freely foraging rat. At fine timescales, a neuron's spike activity also depends significantly on its own spike history. However, due to limitations of current parametric modeling approaches, it remains a challenge to estimate complex, multimodal neuronal receptive fields while incorporating spike history dependence. Furthermore, efforts to decode the rat's trajectory in one- or two-dimensional space from hippocampal ensemble spiking activity have mainly focused on spike history-independent neuronal encoding models. In this letter, we address these two important issues by extending a recently introduced nonparametric neural encoding framework that allows modeling both complex spatial receptive fields and spike history dependencies. Using this extended nonparametric approach, we develop novel algorithms for decoding a rat's trajectory based on recordings of hippocampal place cells and entorhinal grid cells. Results show that both encoding and decoding models derived from our new method performed significantly better than state-of-the-art encoding and decoding models on 6 minutes of test data. In addition, our model's performance remains invariant to the apparent modality of the neuron's receptive field.

关键词： NONPARAMETRIC estimation NEURAL codes ENCODING decoding algorithms PYRAMIDAL neurons PARAMETRIC modeling ACTION potentials (Electrophysiology)

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Noncoherent Spectral Optical CDMA System Using 1D Active Weight Two-Code Keying Codes

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MATHEMATICAL PROBLEMS IN ENGINEERING 2016年第1期2016卷 1-9页

作者： Yeh, Bih-Chyun Chang Gung Univ Coll Engn Sch Elect & Comp Engn Dept Elect Engn Taoyuan Taiwan

We propose a new family of one-dimensional (1D) active weight two-code keying (TCK) in spectral amplitude coding (SAC) optical code divisionmultiple access (OCDMA) networks. We use encoding and decoding transfer functions to operate the 1D active weight TCK. The proposed structure includes an optical line terminal (OLT) and optical network units (ONUs) to produce the encoding and decoding codes of the proposed OLT and ONUs, respectively. The proposed ONU uses the modified cross-correlation to remove interferences from other simultaneous users, that is, the multiuser interference (MUI). When the phase-induced intensity noise (PIIN) is the most important noise, the modified cross-correlation suppresses the PIIN. In the numerical results, we find that the bit error rate (BER) for the proposed system using the 1D active weight TCK codes outperforms that for two other systems using the 1D M-Seq codes and 1D balanced incomplete block design (BIBD) codes. The effective source power for the proposed system can achieve -10 dBm, which has less power than that for the other systems.

关键词： CODE division multiple access TRANSFER functions (Mathematics) decoding algorithms INTERFERENCE (Telecommunication) BLOCK designs NUMERICAL analysis

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Volitional and Real-Time Control Cursor Based on Eye Movement decoding Using a Linear decoding Model

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2016年第1期2016卷 4069790-4069790页

作者： Zhang, Jinhua Wang, Baozeng Zhang, Cheng Hong, Jun Xi An Jiao Tong Univ Sch Mech Engn State Key Lab Mfg Syst Engn Xian 710049 Peoples R China

The aim of this study is to build a linear decoding model that reveals the relationship between the movement information and the EOG (electrooculogram) data to online control a cursor continuously with blinks and eye pursuit movements. First of all, a blink detection method is proposed to reject a voluntary single eye blink or double-blink information from EOG. Then, a linear decoding model of time series is developed to predict the position of gaze, and the model parameters are calibrated by the RLS (Recursive Least Square) algorithm;besides, the assessment of decoding accuracy is assessed through cross-validation procedure. Additionally, the subsection processing, increment control, and online calibration are presented to realize the online control. Finally, the technology is applied to the volitional and online control of a cursor to hit the multiple predefined targets. Experimental results show that the blink detection algorithm performs well with the voluntary blink detection rate over 95%. Through combining the merits of blinks and smooth pursuit movements, the movement information of eyes can be decoded in good conformity with the average Pearson correlation coefficient which is up to 0.9592, and all signal-to-noise ratios are greater than 0. The novel system allows people to successfully and economically control a cursor online with a hit rate of 98%.

关键词： EYE movements decoding algorithms ELECTROOCULOGRAPHY TIME series analysis PEARSON correlation (Statistics)

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Taste Quality decoding Parallels Taste Sensations

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CURRENT BIOLOGY 2015年第7期25卷 890-896页

作者： Crouzet, Sebastien M. Busch, Niko A. Ohla, Kathrin Charite Inst Med Psychol D-10117 Berlin Germany Humboldt Univ Berlin Sch Mind & Brain D-10099 Berlin Germany German Inst Human Nutr Potsdam Rehbrucke Psychophysiol Food Percept D-14558 Nuthetal Germany

In most species, the sense of taste is key in the distinction of potentially nutritious and harmful food constituents and thereby in the acceptance (or rejection) of food. Taste quality is encoded by specialized receptors on the tongue, which detect chemicals corresponding to each of the basic tastes (sweet, salty, sour, bitter, and savory [1]), before taste quality information is transmitted via segregated neuronal fibers [2], distributed coding across neuronal fibers [3], or dynamic firing patterns [4] to the gustatory cortex in the insula. In rodents, both hardwired coding by labeled lines [2] and flexible, learning-dependent representations [5] and broadly tuned neurons [6] seem to coexist. It is currently unknown how, when, and where taste quality representations are established in the cortex and whether these representations are used for perceptual decisions. Here, we show that neuronal response patterns allow to decode which of four tastants (salty, sweet, sour, and bitter) participants tasted in a given trial by using time-resolved multivariate pattern analyses of large-scale electrophysiological brain responses. The onset of this prediction coincided with the earliest taste-evoked responses originating from the insula and opercular cortices, indicating that quality is among the first attributes of a taste represented in the central gustatory system. These response patterns correlated with perceptual decisions of taste quality: tastes that participants discriminated less accurately also evoked less discriminated brain response patterns. The results therefore provide the first evidence for a link between taste-related decision-making and the predictive value of these brain response patterns.

关键词： TASTE PATTERN perception ELECTROPHYSIOLOGY CONFIDENCE intervals decoding algorithms PSYCHOLOGICAL aspects

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Clusterless decoding of Position from Multiunit Activity Using a Marked Point Process Filter

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NEURAL COMPUTATION 2015年第7期27卷 1438-1460页

作者： Deng, Xinyi Liu, Daniel F. Kay, Kenneth Frank, Loren M. Eden, Uri T. Boston Univ Dept Math & Stat Boston MA 02215 USA Univ Calif San Francisco Grad Program Bioengn Univ Calif Berkeley San Francisco CA 94158 USA Univ Calif San Francisco Dept Physiol San Francisco CA 94158 USA

Point process filters have been applied successfully to decode neural signals and track neural dynamics. Traditionally these methods assume that multiunit spiking activity has already been correctly spike-sorted. As a result, these methods are not appropriate for situations where sorting cannot be performed with high precision, such as real-time decoding for brain-computer interfaces. Because the unsupervised spike-sorting problem remains unsolved, we took an alternative approach that takes advantage of recent insights into clusterless decoding. Here we present a new point process decoding algorithm that does not require multiunit signals to be sorted into individual units. We use the theory of marked point processes to construct a function that characterizes the relationship between a covariate of interest (in this case, the location of a rat on a track) and features of the spike waveforms. In our example, we use tetrode recordings, and the marks represent a four-dimensional vector of the maximum amplitudes of the spike waveform on each of the four electrodes. In general, the marks may represent any features of the spike waveform. We then use Bayes's rule to estimate spatial location from hippocampal neural activity. We validate our approach with a simulation study and experimental data recorded in the hippocampus of a rat moving through a linear environment. Our decoding algorithm accurately reconstructs the rat's position from unsorted multiunit spiking activity. We then compare the quality of our decoding algorithm to that of a traditional spike-sorting and decoding algorithm. Our analyses show that the proposed decoding algorithm performs equivalent to or better than algorithms based on sorted single-unit activity. These results provide a path toward accurate real-time decoding of spiking patterns that could be used to carry out content-specific manipulations of population activity in hippocampus or elsewhere in the brain.

关键词： NEUROPHYSIOLOGY POINT processes decoding algorithms CLUSTER analysis (Statistics) COMPUTER simulation HIPPOCAMPUS (Brain)

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Chaotic sequences for noisy environments

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CHAOS 2016年第10期26卷 103104-103104页

作者： Carroll, T. L. Rachford, F. J. US Naval Res Lab Washington DC 20375 USA

There have been many attempts to apply chaotic signals to communications or radar, but one obstacle has been that there is no effective way to recover chaotic signals from noise larger than the signal. In this work, we create "pseudo-chaotic" signals by concatenating dictionary sequences generated from a chaotic attractor. Because the number of dictionary sequences is finite, these pseudo-chaotic signals are not actually chaotic, but they can still contain some of the desirable properties of chaos. Using dictionary sequences allows the pseudo-chaotic signal to be recovered from noise using a correlation detector and a Viterbi decoder, so the signal can be recovered from noise or interference that is larger than the signal itself.

关键词： CHAOTIC communication (Telecommunication) VITERBI decoding decoding algorithms FILTERING theory (Signal processing) SET theory

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Rare Earth Core/Shell Nanobarcodes for Multiplexed Trace Biodetection

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ANALYTICAL CHEMISTRY 2015年第11期87卷 5745-5752页

作者： Chen, Lei Li, Xiaomin Shen, Dengke Zhou, Lei Zhu, Dan Fan, Chunhai Zhang, Fan Fudan Univ Dept Chem IChEm Collaborat Innovat Ctr Chem Energy Mat State Key Lab Mol Engn Polymers Shanghai 200433 Peoples R China Chinese Acad Sci Shanghai Inst Appl Phys Phys Biol Lab Shanghai 201800 Peoples R China Chinese Acad Sci Ctr Environm & Energy Nanomat Anhui Key Lab Nanomat & Nanotechnol Key Lab Mat PhysInst Solid State PhysHefei Inst Hefei 230031 Peoples R China

Multiplexed detection technology has been attractive for its simultaneous assay of several analytes, which play significant roles in applications such as Screening for combinatorial chemistry, genetic analysis, and clinical diagnostics. This work reports a novel and potentially powerful encoding system based upon dispersible suspension arrays of multilayer rare earth core/shell nanoparticles that are capable of multiplexed, high-sensitivity reporting for biomolecule detection by the Z-contrast imaging. These nanobarcode arrays are encoded by nanostructure design based on different atomic numbers. With the Well-resolved high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) decoding technique, many thousands of unique nanobarcodes can be identified by multilayer core/shell nanostructure. Their applications to multiplexed biodetection of DNA demonstrated the highly sensitive (picomole) features of this novel nanobarcode system.

关键词： BAR codes RARE earth metal compounds COMBINATORIAL chemistry NANOPARTICLES BIOMOLECULES SCANNING transmission electron microscopy decoding algorithms DNA

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Energy Consumption of VLSI Decoders

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IEEE TRANSACTIONS ON INFORMATION THEORY 2015年第6期61卷 3185-3198页

作者： Blake, Christopher G. Kschischang, Frank R. Univ Toronto Dept Elect & Comp Engn Toronto ON M5S3G4 Canada

Thompson's model of very large scale integration computation relates the energy of a computation to the product of the circuit area and the number of clock cycles needed to carry out the computation. It is shown that for any sequence of increasing block-length decoder circuits implemented according to this model, if the probability of block error is asymptotically less than 1/2 then the energy of the computation scales at least as Omega(n(log n)(1/2)), and so the energy of decoding per bit must scale at least as Omega (log n)(1/2). This implies that the average energy per decoded bit must approach infinity for any sequence of decoders that approaches capacity. The analysis techniques used are then extended to show that for any sequence of increasing block-length serial decoders, if the asymptotic block error probability is less than 1/2 then the energy scales at least as fast as Omega (n log n). In a very general case that allows for the number of output pins to vary with block length, it is shown that the energy must scale as Omega (n(log n)(1/5)). A simple example is provided of a class of circuits performing low-density parity-check decoding whose energy complexity scales as O(n(2) log log n).

关键词： Channel capacity channel coding energy-efficient communication decoding algorithms

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Single trial analysis of field potentials in perception, learning and memory

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CURRENT OPINION IN NEUROBIOLOGY 2015年 31卷 148-155页

作者： Rey, Hernan Gonzalo Ahmadi, Maryam Quiroga, Rodrigo Quian Univ Leicester Ctr Syst Neurosci Leicester LE1 7QR Leics England

The analysis of single trial responses of field potentials is an important tool to study brain signals. Single trial analyses can indeed provide additional information that is obscured or simply not available in the average responses The importance of studying single trial responses is reinforced by the fact that different brain processes are correlated with trial-by-trial variation of the responses. Here, we review key studies implementing single trial analyses of field potentials using methods such as single trial latency, amplitude and power changes, spike and LFP relationships, correlations between areas, cross frequency coupling, decoding of the presented stimuli that bring light into the neural basis of perception, learning and memory.

关键词： PERCEPTION COGNITIVE ability decoding algorithms HISTOGRAMS RAYLEIGH model PSYCHOLOGICAL aspects

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Kernel Temporal Differences for Neural decoding

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2015年第1期2015卷 17-17页

作者： Bae, Jihye Giraldo, Luis G. Sanchez Pohlmeyer, Eric A. Francis, Joseph T. Sanchez, Justin C. Principe, Jose C. Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA Univ Miami Dept Biomed Engn Coral Gables FL 33146 USA Suny Downstate Med Ctr Dept Physiol & Pharmacol Robert F Furchgott Ctr Neural & Behav Sci Brooklyn NY 11203 USA

We study the feasibility and capability of the kernel temporal difference (KTD)(lambda) algorithm for neural decoding. KTD(lambda) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithmseeks a propermapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces.

关键词： FEASIBILITY studies MACHINE learning REINFORCEMENT learning KERNEL functions APPROXIMATION theory decoding algorithms

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