Mathematics is differentially related to reading comprehension and word decoding: Evidence from a genetically-sensitive design

PubMed Central

Harlaar, Nicole; Kovas, Yulia; Dale, Philip S.; Petrill, Stephen A.; Plomin, Robert

2013-01-01

Although evidence suggests that individual differences in reading and mathematics skills are correlated, this relationship has typically only been studied in relation to word decoding or global measures of reading. It is unclear whether mathematics is differentially related to word decoding and reading comprehension. The current study examined these relationships at both a phenotypic and etiological level in a population-based cohort of 5162 twin pairs at age 12. Multivariate genetic analyses of latent phenotypic factors of mathematics, word decoding and reading comprehension revealed substantial genetic and shared environmental correlations among all three domains. However, the phenotypic and genetic correlations between mathematics and reading comprehension were significantly greater than between mathematics and word decoding. Independent of mathematics, there was also evidence for genetic and nonshared environmental links between word decoding and reading comprehension. These findings indicate that word decoding and reading comprehension have partly distinct relationships with mathematics in the middle school years. PMID:24319294

Mathematics is differentially related to reading comprehension and word decoding: Evidence from a genetically-sensitive design.

PubMed

Harlaar, Nicole; Kovas, Yulia; Dale, Philip S; Petrill, Stephen A; Plomin, Robert

2012-08-01

Although evidence suggests that individual differences in reading and mathematics skills are correlated, this relationship has typically only been studied in relation to word decoding or global measures of reading. It is unclear whether mathematics is differentially related to word decoding and reading comprehension. The current study examined these relationships at both a phenotypic and etiological level in a population-based cohort of 5162 twin pairs at age 12. Multivariate genetic analyses of latent phenotypic factors of mathematics, word decoding and reading comprehension revealed substantial genetic and shared environmental correlations among all three domains. However, the phenotypic and genetic correlations between mathematics and reading comprehension were significantly greater than between mathematics and word decoding. Independent of mathematics, there was also evidence for genetic and nonshared environmental links between word decoding and reading comprehension. These findings indicate that word decoding and reading comprehension have partly distinct relationships with mathematics in the middle school years.

Decoding a wide range of hand configurations from macaque motor, premotor, and parietal cortices.

PubMed

Schaffelhofer, Stefan; Agudelo-Toro, Andres; Scherberger, Hansjörg

2015-01-21

Despite recent advances in decoding cortical activity for motor control, the development of hand prosthetics remains a major challenge. To reduce the complexity of such applications, higher cortical areas that also represent motor plans rather than just the individual movements might be advantageous. We investigated the decoding of many grip types using spiking activity from the anterior intraparietal (AIP), ventral premotor (F5), and primary motor (M1) cortices. Two rhesus monkeys were trained to grasp 50 objects in a delayed task while hand kinematics and spiking activity from six implanted electrode arrays (total of 192 electrodes) were recorded. Offline, we determined 20 grip types from the kinematic data and decoded these hand configurations and the grasped objects with a simple Bayesian classifier. When decoding from AIP, F5, and M1 combined, the mean accuracy was 50% (using planning activity) and 62% (during motor execution) for predicting the 50 objects (chance level, 2%) and substantially larger when predicting the 20 grip types (planning, 74%; execution, 86%; chance level, 5%). When decoding from individual arrays, objects and grip types could be predicted well during movement planning from AIP (medial array) and F5 (lateral array), whereas M1 predictions were poor. In contrast, predictions during movement execution were best from M1, whereas F5 performed only slightly worse. These results demonstrate for the first time that a large number of grip types can be decoded from higher cortical areas during movement preparation and execution, which could be relevant for future neuroprosthetic devices that decode motor plans. Copyright © 2015 the authors 0270-6474/15/351068-14$15.00/0.

Neural Decoding Reveals Impaired Face Configural Processing in the Right Fusiform Face Area of Individuals with Developmental Prosopagnosia

PubMed Central

Zhang, Jiedong; Liu, Jia

2015-01-01

Most of human daily social interactions rely on the ability to successfully recognize faces. Yet ∼2% of the human population suffers from face blindness without any acquired brain damage [this is also known as developmental prosopagnosia (DP) or congenital prosopagnosia]). Despite the presence of severe behavioral face recognition deficits, surprisingly, a majority of DP individuals exhibit normal face selectivity in the right fusiform face area (FFA), a key brain region involved in face configural processing. This finding, together with evidence showing impairments downstream from the right FFA in DP individuals, has led some to argue that perhaps the right FFA is largely intact in DP individuals. Using fMRI multivoxel pattern analysis, here we report the discovery of a neural impairment in the right FFA of DP individuals that may play a critical role in mediating their face-processing deficits. In seven individuals with DP, we discovered that, despite the right FFA's preference for faces and it showing decoding for the different face parts, it exhibited impaired face configural decoding and did not contain distinct neural response patterns for the intact and the scrambled face configurations. This abnormality was not present throughout the ventral visual cortex, as normal neural decoding was found in an adjacent object-processing region. To our knowledge, this is the first direct neural evidence showing impaired face configural processing in the right FFA in individuals with DP. The discovery of this neural impairment provides a new clue to our understanding of the neural basis of DP. PMID:25632131

Towards the control of individual fingers of a prosthetic hand using surface EMG signals.

PubMed

Tenore, Francesco; Ramos, Ander; Fahmy, Amir; Acharya, Soumyadipta; Etienne-Cummings, Ralph; Thakor, Nitish V

2007-01-01

The fast pace of development of upper-limb prostheses requires a paradigm shift in EMG-based controls. Traditional control schemes are only capable of providing 2 degrees of freedom, which is insufficient for dexterous control of individual fingers. We present a framework where myoelectric signals from natural hand and finger movements can be decoded with a high accuracy. 32 surface-EMG electrodes were placed on the forearm of an able-bodied subject while performing individual finger movements. Using time-domain feature extraction methods as inputs to a neural network classifier, we show that 12 individuated flexion and extension movements of the fingers can be decoded with an accuracy higher than 98%. To our knowledge, this is the first instance in which such movements have been successfully decoded using surface-EMG. These preliminary findings provide a framework that will allow the results to be extended to non-invasive control of the next generation of upper-limb prostheses for amputees.

Decoding flexion of individual fingers using electrocorticographic signals in humans

NASA Astrophysics Data System (ADS)

Kubánek, J.; Miller, K. J.; Ojemann, J. G.; Wolpaw, J. R.; Schalk, G.

2009-12-01

Brain signals can provide the basis for a non-muscular communication and control system, a brain-computer interface (BCI), for people with motor disabilities. A common approach to creating BCI devices is to decode kinematic parameters of movements using signals recorded by intracortical microelectrodes. Recent studies have shown that kinematic parameters of hand movements can also be accurately decoded from signals recorded by electrodes placed on the surface of the brain (electrocorticography (ECoG)). In the present study, we extend these results by demonstrating that it is also possible to decode the time course of the flexion of individual fingers using ECoG signals in humans, and by showing that these flexion time courses are highly specific to the moving finger. These results provide additional support for the hypothesis that ECoG could be the basis for powerful clinically practical BCI systems, and also indicate that ECoG is useful for studying cortical dynamics related to motor function.

Testing interconnected VLSI circuits in the Big Viterbi Decoder

NASA Technical Reports Server (NTRS)

Onyszchuk, I. M.

1991-01-01

The Big Viterbi Decoder (BVD) is a powerful error-correcting hardware device for the Deep Space Network (DSN), in support of the Galileo and Comet Rendezvous Asteroid Flyby (CRAF)/Cassini Missions. Recently, a prototype was completed and run successfully at 400,000 or more decoded bits per second. This prototype is a complex digital system whose core arithmetic unit consists of 256 identical very large scale integration (VLSI) gate-array chips, 16 on each of 16 identical boards which are connected through a 28-layer, printed-circuit backplane using 4416 wires. Special techniques were developed for debugging, testing, and locating faults inside individual chips, on boards, and within the entire decoder. The methods are based upon hierarchical structure in the decoder, and require that chips or boards be wired themselves as Viterbi decoders. The basic procedure consists of sending a small set of known, very noisy channel symbols through a decoder, and matching observables against values computed by a software simulation. Also, tests were devised for finding open and short-circuited wires which connect VLSI chips on the boards and through the backplane.

De-Coding Writing Assignments.

ERIC Educational Resources Information Center

Simon, Linda

1991-01-01

Argues that understanding assignments is the first step toward successful college writing. Urges instructors to support students by helping them to decode assignments. Breaks down instructions into individual tasks including (1) writing an essay, (2) examining an issue, (3) reviewing articles and books, and (4) focusing on some texts. Defines each…

Is Native-Language Decoding Skill Related to Second-Language Learning?

ERIC Educational Resources Information Center

Meschyan, Gayane; Hernandez, Arturo

2002-01-01

Investigated the mechanisms through which native-language (English) word decoding ability predicted individual differences in native- and second-language (Spanish) learning. Results are consistent with the hypothesis that second-language learning is founded on native-language phonological-orthographic ability among college-age adults, especially…

Brain basis of cognitive resilience: Prefrontal cortex predicts better reading comprehension in relation to decoding

PubMed Central

Patael, Smadar Z.; Farris, Emily A.; Black, Jessica M.; Hancock, Roeland; Gabrieli, John D. E.; Cutting, Laurie E.; Hoeft, Fumiko

2018-01-01

Objective The ultimate goal of reading is to understand written text. To accomplish this, children must first master decoding, the ability to translate printed words into sounds. Although decoding and reading comprehension are highly interdependent, some children struggle to decode but comprehend well, whereas others with good decoding skills fail to comprehend. The neural basis underlying individual differences in this discrepancy between decoding and comprehension abilities is virtually unknown. Methods We investigated the neural basis underlying reading discrepancy, defined as the difference between reading comprehension and decoding skills, in a three-part study: 1) The neuroanatomical basis of reading discrepancy in a cross-sectional sample of school-age children with a wide range of reading abilities (Experiment-1; n = 55); 2) Whether a discrepancy-related neural signature is present in beginning readers and predictive of future discrepancy (Experiment-2; n = 43); and 3) Whether discrepancy-related regions are part of a domain-general or a language specialized network, utilizing the 1000 Functional Connectome data and large-scale reverse inference from Neurosynth.org (Experiment-3). Results Results converged onto the left dorsolateral prefrontal cortex (DLPFC), as related to having discrepantly higher reading comprehension relative to decoding ability. Increased gray matter volume (GMV) was associated with greater discrepancy (Experiment-1). Region-of-interest (ROI) analyses based on the left DLPFC cluster identified in Experiment-1 revealed that regional GMV within this ROI in beginning readers predicted discrepancy three years later (Experiment-2). This region was associated with the fronto-parietal network that is considered fundamental for working memory and cognitive control (Experiment-3). Interpretation Processes related to the prefrontal cortex might be linked to reading discrepancy. The findings may be important for understanding cognitive resilience, which we operationalize as those individuals with greater higher-order reading skills such as reading comprehension compared to lower-order reading skills such as decoding skills. Our study provides insights into reading development, existing theories of reading, and cognitive processes that are potentially significant to a wide range of reading disorders. PMID:29902208

A computationally efficient method for incorporating spike waveform information into decoding algorithms.

PubMed

Ventura, Valérie; Todorova, Sonia

2015-05-01

Spike-based brain-computer interfaces (BCIs) have the potential to restore motor ability to people with paralysis and amputation, and have shown impressive performance in the lab. To transition BCI devices from the lab to the clinic, decoding must proceed automatically and in real time, which prohibits the use of algorithms that are computationally intensive or require manual tweaking. A common choice is to avoid spike sorting and treat the signal on each electrode as if it came from a single neuron, which is fast, easy, and therefore desirable for clinical use. But this approach ignores the kinematic information provided by individual neurons recorded on the same electrode. The contribution of this letter is a linear decoding model that extracts kinematic information from individual neurons without spike-sorting the electrode signals. The method relies on modeling sample averages of waveform features as functions of kinematics, which is automatic and requires minimal data storage and computation. In offline reconstruction of arm trajectories of a nonhuman primate performing reaching tasks, the proposed method performs as well as decoders based on expertly manually and automatically sorted spikes.

Preserved Affective Sharing But Impaired Decoding of Contextual Complex Emotions in Alcohol Dependence.

PubMed

Grynberg, Delphine; Maurage, Pierre; Nandrino, Jean-Louis

2017-04-01

Prior research has repeatedly shown that alcohol dependence is associated with a large range of impairments in psychological processes, which could lead to interpersonal deficits. Specifically, it has been suggested that these interpersonal difficulties are underpinned by reduced recognition and sharing of others' emotional states. However, this pattern of deficits remains to be clarified. This study thus aimed to investigate whether alcohol dependence is associated with impaired abilities in decoding contextual complex emotions and with altered sharing of others' emotions. Forty-one alcohol-dependent individuals (ADI) and 37 matched healthy individuals completed the Multifaceted Empathy Test, in which they were instructed to identify complex emotional states expressed by individuals in contextual scenes and to state to what extent they shared them. Compared to healthy individuals, ADI were impaired in identifying negative (Cohen's d = 0.75) and positive (Cohen's d = 0.46) emotional states but, conversely, presented preserved abilities in sharing others' emotional states. This study shows that alcohol dependence is characterized by an impaired ability to decode complex emotional states (both positive and negative), despite the presence of complementary contextual cues, but by preserved emotion-sharing. Therefore, these results extend earlier data describing an impaired ability to decode noncontextualized emotions toward contextualized and ecologically valid emotional states. They also indicate that some essential emotional competences such as emotion-sharing are preserved in alcohol dependence, thereby offering potential therapeutic levers. Copyright © 2017 by the Research Society on Alcoholism.

Grotesque Gestures or Sensuous Signs? Rethinking Notions of Apprenticeship in Early Childhood Education

ERIC Educational Resources Information Center

Knight, Linda

2012-01-01

Deleuze asserts that education is a mass of signs. Children learn to decode these signs, albeit in randomized and individual ways, displaying great skill in decoding some signs but not others, and demonstrating different acuities with different clusters of signs. Deleuzian notions of apprenticeship, a fluid becoming to knowledges as formal…

Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance

NASA Astrophysics Data System (ADS)

Omurtag, Ahmet; Aghajani, Haleh; Onur Keles, Hasan

2017-12-01

Objective. Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system’s ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results. EEG+fNIRS’s decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. Significance. Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.

Evidence for Trait Related Theory of Mind Impairment in First Episode Psychosis Patients and Its Relationship with Processing Speed: A 3 Year Follow-up Study.

PubMed

Ayesa-Arriola, Rosa; Setién-Suero, Esther; Neergaard, Karl D; Ferro, Adele; Fatjó-Vilas, Mar; Ríos-Lago, Marcos; Otero, Soraya; Rodríguez-Sánchez, Jose M; Crespo-Facorro, Benedicto

2016-01-01

This study aimed to confirm whether first-episode psychosis patients present a stable trait impairment in theory of mind (ToM) and to examine the potential relationship between ToM and clinical symptomatology and neurocognition. Patients with a first episode of psychosis (N = 160) and healthy controls (N = 159) were assessed with an extensive neuropsychological test battery, which included a mental state decoding task known as "The Reading the Mind in the Eyes" (Eyes test), at baseline and reassessed after 1 and 3 years. The clinical group performed below healthy controls on the Eyes test while not showing test-retest differences between baseline and follow-up administrations. Analyses revealed age, education and premorbid IQ as potential moderators. Poorer performance on the Eyes test was not linked to clinical symptomatology but was associated with greater neurocognitive deficit, particularly related to processing speed. The persistence of ToM deficits in patients suggests that there are trait related metalizing impairments in first episode psychosis. This study shows the influence of processing speed and moderator variables on efficient ToM.

Evidence for Trait Related Theory of Mind Impairment in First Episode Psychosis Patients and Its Relationship with Processing Speed: A 3 Year Follow-up Study

PubMed Central

Ayesa-Arriola, Rosa; Setién-Suero, Esther; Neergaard, Karl D.; Ferro, Adele; Fatjó-Vilas, Mar; Ríos-Lago, Marcos; Otero, Soraya; Rodríguez-Sánchez, Jose M.; Crespo-Facorro, Benedicto

2016-01-01

This study aimed to confirm whether first-episode psychosis patients present a stable trait impairment in theory of mind (ToM) and to examine the potential relationship between ToM and clinical symptomatology and neurocognition. Patients with a first episode of psychosis (N = 160) and healthy controls (N = 159) were assessed with an extensive neuropsychological test battery, which included a mental state decoding task known as “The Reading the Mind in the Eyes” (Eyes test), at baseline and reassessed after 1 and 3 years. The clinical group performed below healthy controls on the Eyes test while not showing test-retest differences between baseline and follow-up administrations. Analyses revealed age, education and premorbid IQ as potential moderators. Poorer performance on the Eyes test was not linked to clinical symptomatology but was associated with greater neurocognitive deficit, particularly related to processing speed. The persistence of ToM deficits in patients suggests that there are trait related metalizing impairments in first episode psychosis. This study shows the influence of processing speed and moderator variables on efficient ToM. PMID:27199826

Towards Efficient Decoding of Multiple Classes of Motor Imagery Limb Movements Based on EEG Spectral and Time Domain Descriptors.

PubMed

Samuel, Oluwarotimi Williams; Geng, Yanjuan; Li, Xiangxin; Li, Guanglin

2017-10-28

To control multiple degrees of freedom (MDoF) upper limb prostheses, pattern recognition (PR) of electromyogram (EMG) signals has been successfully applied. This technique requires amputees to provide sufficient EMG signals to decode their limb movement intentions (LMIs). However, amputees with neuromuscular disorder/high level amputation often cannot provide sufficient EMG control signals, and thus the applicability of the EMG-PR technique is limited especially to this category of amputees. As an alternative approach, electroencephalograph (EEG) signals recorded non-invasively from the brain have been utilized to decode the LMIs of humans. However, most of the existing EEG based limb movement decoding methods primarily focus on identifying limited classes of upper limb movements. In addition, investigation on EEG feature extraction methods for the decoding of multiple classes of LMIs has rarely been considered. Therefore, 32 EEG feature extraction methods (including 12 spectral domain descriptors (SDDs) and 20 time domain descriptors (TDDs)) were used to decode multiple classes of motor imagery patterns associated with different upper limb movements based on 64-channel EEG recordings. From the obtained experimental results, the best individual TDD achieved an accuracy of 67.05 ± 3.12% as against 87.03 ± 2.26% for the best SDD. By applying a linear feature combination technique, an optimal set of combined TDDs recorded an average accuracy of 90.68% while that of the SDDs achieved an accuracy of 99.55% which were significantly higher than those of the individual TDD and SDD at p < 0.05. Our findings suggest that optimal feature set combination would yield a relatively high decoding accuracy that may improve the clinical robustness of MDoF neuroprosthesis. The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Systematic Basic Phonics. A Handbook for the 20th Century.

ERIC Educational Resources Information Center

Albert, Elaine Acker

Designed for use in the home, this booklet describes how someone can be taught how the alphabet works; that is, by decoding the ABC's into spoken language. Among the steps to decoding discussed in this booklet are these: (1) teaching the sounds of individual letters; (2) teaching the different sounds of the vowels; (3) sounding out little words;…

Decoding DNA labels by melting curve analysis using real-time PCR.

PubMed

Balog, József A; Fehér, Liliána Z; Puskás, László G

2017-12-01

Synthetic DNA has been used as an authentication code for a diverse number of applications. However, existing decoding approaches are based on either DNA sequencing or the determination of DNA length variations. Here, we present a simple alternative protocol for labeling different objects using a small number of short DNA sequences that differ in their melting points. Code amplification and decoding can be done in two steps using quantitative PCR (qPCR). To obtain a DNA barcode with high complexity, we defined 8 template groups, each having 4 different DNA templates, yielding 158 (>2.5 billion) combinations of different individual melting temperature (Tm) values and corresponding ID codes. The reproducibility and specificity of the decoding was confirmed by using the most complex template mixture, which had 32 different products in 8 groups with different Tm values. The industrial applicability of our protocol was also demonstrated by labeling a drone with an oil-based paint containing a predefined DNA code, which was then successfully decoded. The method presented here consists of a simple code system based on a small number of synthetic DNA sequences and a cost-effective, rapid decoding protocol using a few qPCR reactions, enabling a wide range of authentication applications.

Reconstructing Perceived and Retrieved Faces from Activity Patterns in Lateral Parietal Cortex.

PubMed

Lee, Hongmi; Kuhl, Brice A

2016-06-01

Recent findings suggest that the contents of memory encoding and retrieval can be decoded from the angular gyrus (ANG), a subregion of posterior lateral parietal cortex. However, typical decoding approaches provide little insight into the nature of ANG content representations. Here, we tested whether complex, multidimensional stimuli (faces) could be reconstructed from ANG by predicting underlying face components from fMRI activity patterns in humans. Using an approach inspired by computer vision methods for face recognition, we applied principal component analysis to a large set of face images to generate eigenfaces. We then modeled relationships between eigenface values and patterns of fMRI activity. Activity patterns evoked by individual faces were then used to generate predicted eigenface values, which could be transformed into reconstructions of individual faces. We show that visually perceived faces were reliably reconstructed from activity patterns in occipitotemporal cortex and several lateral parietal subregions, including ANG. Subjective assessment of reconstructed faces revealed specific sources of information (e.g., affect and skin color) that were successfully reconstructed in ANG. Strikingly, we also found that a model trained on ANG activity patterns during face perception was able to successfully reconstruct an independent set of face images that were held in memory. Together, these findings provide compelling evidence that ANG forms complex, stimulus-specific representations that are reflected in activity patterns evoked during perception and remembering. Neuroimaging studies have consistently implicated lateral parietal cortex in episodic remembering, but the functional contributions of lateral parietal cortex to memory remain a topic of debate. Here, we used an innovative form of fMRI pattern analysis to test whether lateral parietal cortex actively represents the contents of memory. Using a large set of human face images, we first extracted latent face components (eigenfaces). We then used machine learning algorithms to predict face components from fMRI activity patterns and, ultimately, to reconstruct images of individual faces. We show that activity patterns in a subregion of lateral parietal cortex, the angular gyrus, supported successful reconstruction of perceived and remembered faces, confirming a role for this region in actively representing remembered content. Copyright © 2016 the authors 0270-6474/16/366069-14$15.00/0.

Large constraint length high speed viterbi decoder based on a modular hierarchial decomposition of the deBruijn graph

NASA Technical Reports Server (NTRS)

Collins, Oliver (Inventor); Dolinar, Jr., Samuel J. (Inventor); Hus, In-Shek (Inventor); Bozzola, Fabrizio P. (Inventor); Olson, Erlend M. (Inventor); Statman, Joseph I. (Inventor); Zimmerman, George A. (Inventor)

1991-01-01

A method of formulating and packaging decision-making elements into a long constraint length Viterbi decoder which involves formulating the decision-making processors as individual Viterbi butterfly processors that are interconnected in a deBruijn graph configuration. A fully distributed architecture, which achieves high decoding speeds, is made feasible by novel wiring and partitioning of the state diagram. This partitioning defines universal modules, which can be used to build any size decoder, such that a large number of wires is contained inside each module, and a small number of wires is needed to connect modules. The total system is modular and hierarchical, and it implements a large proportion of the required wiring internally within modules and may include some external wiring to fully complete the deBruijn graph. pg,14.

Decoding Individual Finger Movements from One Hand Using Human EEG Signals

PubMed Central

Gonzalez, Jania; Ding, Lei

2014-01-01

Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals generated by the human brain and translates them into control signals to control external devices, e.g., wheelchairs. One problem challenging noninvasive BCI technologies is the limited control dimensions from decoding movements of, mainly, large body parts, e.g., upper and lower limbs. It has been reported that complicated dexterous functions, i.e., finger movements, can be decoded in electrocorticography (ECoG) signals, while it remains unclear whether noninvasive electroencephalography (EEG) signals also have sufficient information to decode the same type of movements. Phenomena of broadband power increase and low-frequency-band power decrease were observed in EEG in the present study, when EEG power spectra were decomposed by a principal component analysis (PCA). These movement-related spectral structures and their changes caused by finger movements in EEG are consistent with observations in previous ECoG study, as well as the results from ECoG data in the present study. The average decoding accuracy of 77.11% over all subjects was obtained in classifying each pair of fingers from one hand using movement-related spectral changes as features to be decoded using a support vector machine (SVM) classifier. The average decoding accuracy in three epilepsy patients using ECoG data was 91.28% with the similarly obtained features and same classifier. Both decoding accuracies of EEG and ECoG are significantly higher than the empirical guessing level (51.26%) in all subjects (p<0.05). The present study suggests the similar movement-related spectral changes in EEG as in ECoG, and demonstrates the feasibility of discriminating finger movements from one hand using EEG. These findings are promising to facilitate the development of BCIs with rich control signals using noninvasive technologies. PMID:24416360

Nurturing a lexical legacy: reading experience is critical for the development of word reading skill

NASA Astrophysics Data System (ADS)

Nation, Kate

2017-12-01

The scientific study of reading has taught us much about the beginnings of reading in childhood, with clear evidence that the gateway to reading opens when children are able to decode, or `sound out' written words. Similarly, there is a large evidence base charting the cognitive processes that characterise skilled word recognition in adults. Less understood is how children develop word reading expertise. Once basic reading skills are in place, what factors are critical for children to move from novice to expert? This paper outlines the role of reading experience in this transition. Encountering individual words in text provides opportunities for children to refine their knowledge about how spelling represents spoken language. Alongside this, however, reading experience provides much more than repeated exposure to individual words in isolation. According to the lexical legacy perspective, outlined in this paper, experiencing words in diverse and meaningful language environments is critical for the development of word reading skill. At its heart is the idea that reading provides exposure to words in many different contexts, episodes and experiences which, over time, sum to a rich and nuanced database about their lexical history within an individual's experience. These rich and diverse encounters bring about local variation at the word level: a lexical legacy that is measurable during word reading behaviour, even in skilled adults.

Decodability of Reward Learning Signals Predicts Mood Fluctuations.

PubMed

Eldar, Eran; Roth, Charlotte; Dayan, Peter; Dolan, Raymond J

2018-05-07

Our mood often fluctuates without warning. Recent accounts propose that these fluctuations might be preceded by changes in how we process reward. According to this view, the degree to which reward improves our mood reflects not only characteristics of the reward itself (e.g., its magnitude) but also how receptive to reward we happen to be. Differences in receptivity to reward have been suggested to play an important role in the emergence of mood episodes in psychiatric disorders [1-16]. However, despite substantial theory, the relationship between reward processing and daily fluctuations of mood has yet to be tested directly. In particular, it is unclear whether the extent to which people respond to reward changes from day to day and whether such changes are followed by corresponding shifts in mood. Here, we use a novel mobile-phone platform with dense data sampling and wearable heart-rate and electroencephalographic sensors to examine mood and reward processing over an extended period of one week. Subjects regularly performed a trial-and-error choice task in which different choices were probabilistically rewarded. Subjects' choices revealed two complementary learning processes, one fast and one slow. Reward prediction errors [17, 18] indicative of these two processes were decodable from subjects' physiological responses. Strikingly, more accurate decodability of prediction-error signals reflective of the fast process predicted improvement in subjects' mood several hours later, whereas more accurate decodability of the slow process' signals predicted better mood a whole day later. We conclude that real-life mood fluctuations follow changes in responsivity to reward at multiple timescales. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Predicting individual differences in reading comprehension: a twin study

PubMed Central

Cutting, Laurie; Deater-Deckard, Kirby; DeThorne, Laura S.; Justice, Laura M.; Schatschneider, Chris; Thompson, Lee A.; Petrill, Stephen A.

2010-01-01

We examined the Simple View of reading from a behavioral genetic perspective. Two aspects of word decoding (phonological decoding and word recognition), two aspects of oral language skill (listening comprehension and vocabulary), and reading comprehension were assessed in a twin sample at age 9. Using latent factor models, we found that overlap among phonological decoding, word recognition, listening comprehension, vocabulary, and reading comprehension was primarily due to genetic influences. Shared environmental influences accounted for associations among word recognition, listening comprehension, vocabulary, and reading comprehension. Independent of phonological decoding and word recognition, there was a separate genetic link between listening comprehension, vocabulary, and reading comprehension and a specific shared environmental link between vocabulary and reading comprehension. There were no residual genetic or environmental influences on reading comprehension. The findings provide evidence for a genetic basis to the “Simple View” of reading. PMID:20814768

Decoding Intention at Sensorimotor Timescales

PubMed Central

Salvaris, Mathew; Haggard, Patrick

2014-01-01

The ability to decode an individual's intentions in real time has long been a ‘holy grail’ of research on human volition. For example, a reliable method could be used to improve scientific study of voluntary action by allowing external probe stimuli to be delivered at different moments during development of intention and action. Several Brain Computer Interface applications have used motor imagery of repetitive actions to achieve this goal. These systems are relatively successful, but only if the intention is sustained over a period of several seconds; much longer than the timescales identified in psychophysiological studies for normal preparation for voluntary action. We have used a combination of sensorimotor rhythms and motor imagery training to decode intentions in a single-trial cued-response paradigm similar to those used in human and non-human primate motor control research. Decoding accuracy of over 0.83 was achieved with twelve participants. With this approach, we could decode intentions to move the left or right hand at sub-second timescales, both for instructed choices instructed by an external stimulus and for free choices generated intentionally by the participant. The implications for volition are considered. PMID:24523855

Clusterless Decoding of Position From Multiunit Activity Using A Marked Point Process Filter

PubMed Central

Deng, Xinyi; Liu, Daniel F.; Kay, Kenneth; Frank, Loren M.; Eden, Uri T.

2016-01-01

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. As the unsupervised spike-sorting problem remains unsolved, we took an alternative approach that takes advantage of recent insights about 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’ rule to estimate spatial location from hippocampal neural activity. We validate our approach with a simulation study and with 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 equivalently 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. PMID:25973549

Impaired emotional facial expression decoding in alcoholism is also present for emotional prosody and body postures.

PubMed

Maurage, Pierre; Campanella, Salvatore; Philippot, Pierre; Charest, Ian; Martin, Sophie; de Timary, Philippe

2009-01-01

Emotional facial expression (EFE) decoding impairment has been repeatedly reported in alcoholism (e.g. Philippot et al., 1999). Nevertheless, several questions are still under debate concerning this alteration, notably its generalization to other emotional stimuli and its variation according to the emotional valence of stimuli. Eighteen recently detoxified alcoholic subjects and 18 matched controls performed a decoding test consisting in emotional intensity ratings on various stimuli (faces, voices, body postures and written scenarios) depicting different emotions (anger, fear, happiness, neutral, sadness). Perceived threat and difficulty were also assessed for each stimulus. Alcoholic individuals had a preserved decoding performance for happiness stimuli, but alcoholism was associated with an underestimation of sadness and fear, and with a general overestimation of anger. More importantly, these decoding impairments were observed for faces, voices and postures but not for written scenarios. We observed for the first time a generalized emotional decoding impairment in alcoholism, as this impairment is present not only for faces but also for other visual (i.e. body postures) and auditory stimuli. Moreover, we report that this alteration (1) is mainly indexed by an overestimation of anger and (2) cannot be explained by an 'affect labelling' impairment, as the semantic comprehension of written emotional scenarios is preserved. Fundamental and clinical implications are discussed.

Decoding with limited neural data: a mixture of time-warped trajectory models for directional reaches.

PubMed

Corbett, Elaine A; Perreault, Eric J; Körding, Konrad P

2012-06-01

Neuroprosthetic devices promise to allow paralyzed patients to perform the necessary functions of everyday life. However, to allow patients to use such tools it is necessary to decode their intent from neural signals such as electromyograms (EMGs). Because these signals are noisy, state of the art decoders integrate information over time. One systematic way of doing this is by taking into account the natural evolution of the state of the body--by using a so-called trajectory model. Here we use two insights about movements to enhance our trajectory model: (1) at any given time, there is a small set of likely movement targets, potentially identified by gaze; (2) reaches are produced at varying speeds. We decoded natural reaching movements using EMGs of muscles that might be available from an individual with spinal cord injury. Target estimates found from tracking eye movements were incorporated into the trajectory model, while a mixture model accounted for the inherent uncertainty in these estimates. Warping the trajectory model in time using a continuous estimate of the reach speed enabled accurate decoding of faster reaches. We found that the choice of richer trajectory models, such as those incorporating target or speed, improves decoding particularly when there is a small number of EMGs available.

Dissociable roles of internal feelings and face recognition ability in facial expression decoding.

PubMed

Zhang, Lin; Song, Yiying; Liu, Ling; Liu, Jia

2016-05-15

The problem of emotion recognition has been tackled by researchers in both affective computing and cognitive neuroscience. While affective computing relies on analyzing visual features from facial expressions, it has been proposed that humans recognize emotions by internally simulating the emotional states conveyed by others' expressions, in addition to perceptual analysis of facial features. Here we investigated whether and how our internal feelings contributed to the ability to decode facial expressions. In two independent large samples of participants, we observed that individuals who generally experienced richer internal feelings exhibited a higher ability to decode facial expressions, and the contribution of internal feelings was independent of face recognition ability. Further, using voxel-based morphometry, we found that the gray matter volume (GMV) of bilateral superior temporal sulcus (STS) and the right inferior parietal lobule was associated with facial expression decoding through the mediating effect of internal feelings, while the GMV of bilateral STS, precuneus, and the right central opercular cortex contributed to facial expression decoding through the mediating effect of face recognition ability. In addition, the clusters in bilateral STS involved in the two components were neighboring yet separate. Our results may provide clues about the mechanism by which internal feelings, in addition to face recognition ability, serve as an important instrument for humans in facial expression decoding. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision.

PubMed

Wen, Haiguang; Shi, Junxing; Zhang, Yizhen; Lu, Kun-Han; Cao, Jiayue; Liu, Zhongming

2017-10-20

Convolutional neural network (CNN) driven by image recognition has been shown to be able to explain cortical responses to static pictures at ventral-stream areas. Here, we further showed that such CNN could reliably predict and decode functional magnetic resonance imaging data from humans watching natural movies, despite its lack of any mechanism to account for temporal dynamics or feedback processing. Using separate data, encoding and decoding models were developed and evaluated for describing the bi-directional relationships between the CNN and the brain. Through the encoding models, the CNN-predicted areas covered not only the ventral stream, but also the dorsal stream, albeit to a lesser degree; single-voxel response was visualized as the specific pixel pattern that drove the response, revealing the distinct representation of individual cortical location; cortical activation was synthesized from natural images with high-throughput to map category representation, contrast, and selectivity. Through the decoding models, fMRI signals were directly decoded to estimate the feature representations in both visual and semantic spaces, for direct visual reconstruction and semantic categorization, respectively. These results corroborate, generalize, and extend previous findings, and highlight the value of using deep learning, as an all-in-one model of the visual cortex, to understand and decode natural vision. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Decoding visual object categories from temporal correlations of ECoG signals.

PubMed

Majima, Kei; Matsuo, Takeshi; Kawasaki, Keisuke; Kawai, Kensuke; Saito, Nobuhito; Hasegawa, Isao; Kamitani, Yukiyasu

2014-04-15

How visual object categories are represented in the brain is one of the key questions in neuroscience. Studies on low-level visual features have shown that relative timings or phases of neural activity between multiple brain locations encode information. However, whether such temporal patterns of neural activity are used in the representation of visual objects is unknown. Here, we examined whether and how visual object categories could be predicted (or decoded) from temporal patterns of electrocorticographic (ECoG) signals from the temporal cortex in five patients with epilepsy. We used temporal correlations between electrodes as input features, and compared the decoding performance with features defined by spectral power and phase from individual electrodes. While using power or phase alone, the decoding accuracy was significantly better than chance, correlations alone or those combined with power outperformed other features. Decoding performance with correlations was degraded by shuffling the order of trials of the same category in each electrode, indicating that the relative time series between electrodes in each trial is critical. Analysis using a sliding time window revealed that decoding performance with correlations began to rise earlier than that with power. This earlier increase in performance was replicated by a model using phase differences to encode categories. These results suggest that activity patterns arising from interactions between multiple neuronal units carry additional information on visual object categories. Copyright © 2013 Elsevier Inc. All rights reserved.

Towards a symbiotic brain-computer interface: exploring the application-decoder interaction

NASA Astrophysics Data System (ADS)

Verhoeven, T.; Buteneers Wiersema, P., Jr.; Dambre, J.; Kindermans, PJ

2015-12-01

Objective. State of the art brain-computer interface (BCI) research focuses on improving individual components such as the application or the decoder that converts the user’s brain activity to control signals. In this study, we investigate the interaction between these components in the P300 speller, a BCI for communication. We introduce a synergistic approach in which the stimulus presentation sequence is modified to enhance the machine learning decoding. In this way we aim for an improved overall BCI performance. Approach. First, a new stimulus presentation paradigm is introduced which provides us flexibility in tuning the sequence of visual stimuli presented to the user. Next, an experimental setup in which this paradigm is compared to other paradigms uncovers the underlying mechanism of the interdependence between the application and the performance of the decoder. Main results. Extensive analysis of the experimental results reveals the changing requirements of the decoder concerning the data recorded during the spelling session. When few data is recorded, the balance in the number of target and non-target stimuli shown to the user is more important than the signal-to-noise rate (SNR) of the recorded response signals. Only when more data has been collected, the SNR becomes the dominant factor. Significance. For BCIs in general, knowing the dominant factor that affects the decoder performance and being able to respond to it is of utmost importance to improve system performance. For the P300 speller, the proposed tunable paradigm offers the possibility to tune the application to the decoder’s needs at any time and, as such, fully exploit this application-decoder interaction.

Nonlinear decoding of a complex movie from the mammalian retina

PubMed Central

Deny, Stéphane; Martius, Georg

2018-01-01

Retina is a paradigmatic system for studying sensory encoding: the transformation of light into spiking activity of ganglion cells. The inverse problem, where stimulus is reconstructed from spikes, has received less attention, especially for complex stimuli that should be reconstructed “pixel-by-pixel”. We recorded around a hundred neurons from a dense patch in a rat retina and decoded movies of multiple small randomly-moving discs. We constructed nonlinear (kernelized and neural network) decoders that improved significantly over linear results. An important contribution to this was the ability of nonlinear decoders to reliably separate between neural responses driven by locally fluctuating light signals, and responses at locally constant light driven by spontaneous-like activity. This improvement crucially depended on the precise, non-Poisson temporal structure of individual spike trains, which originated in the spike-history dependence of neural responses. We propose a general principle by which downstream circuitry could discriminate between spontaneous and stimulus-driven activity based solely on higher-order statistical structure in the incoming spike trains. PMID:29746463

Episodic autobiographical memory is associated with variation in the size of hippocampal subregions.

PubMed

Palombo, Daniela J; Bacopulos, Agnes; Amaral, Robert S C; Olsen, Rosanna K; Todd, Rebecca M; Anderson, Adam K; Levine, Brian

2018-02-01

Striking individual differences exist in the human capacity to recollect past events, yet, little is known about the neural correlates of such individual differences. Studies investigating hippocampal volume in relation to individual differences in laboratory measures of episodic memory in young adults suggest that whole hippocampal volume is unrelated (or even negatively associated) with episodic memory. However, anatomical and functional specialization across hippocampal subregions suggests that individual differences in episodic memory may be linked to particular hippocampal subregions, as opposed to whole hippocampal volume. Given that the DG/CA 2/3 circuitry is thought to be especially critical for supporting episodic memory in humans, we predicted that the volume of this region would be associated with individual variability in episodic memory. This prediction was supported using high-resolution MRI of the hippocampal subfields and measures of real-world (autobiographical) episodic memory. In addition to the association with DG/CA 2/3 , we further observed a relationship between episodic autobiographical memory and subiculum volume, whereas no association was observed with CA 1 or with whole hippocampal volume. These findings provide insight into the possible neural substrates that mediate individual differences in real-world episodic remembering in humans. © 2017 Wiley Periodicals, Inc.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex.

PubMed

Tong, Frank; Harrison, Stephenie A; Dewey, John A; Kamitani, Yukiyasu

2012-11-15

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. Copyright © 2012 Elsevier Inc. All rights reserved.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex

PubMed Central

Tong, Frank; Harrison, Stephenie A.; Dewey, John A.; Kamitani, Yukiyasu

2012-01-01

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. PMID:22917989

Principal components of hand kinematics and neurophysiological signals in motor cortex during reach to grasp movements

PubMed Central

Aggarwal, Vikram; Thakor, Nitish V.; Schieber, Marc H.

2014-01-01

A few kinematic synergies identified by principal component analysis (PCA) account for most of the variance in the coordinated joint rotations of the fingers and wrist used for a wide variety of hand movements. To examine the possibility that motor cortex might control the hand through such synergies, we collected simultaneous kinematic and neurophysiological data from monkeys performing a reach-to-grasp task. We used PCA, jPCA and isomap to extract kinematic synergies from 18 joint angles in the fingers and wrist and analyzed the relationships of both single-unit and multiunit spike recordings, as well as local field potentials (LFPs), to these synergies. For most spike recordings, the maximal absolute cross-correlations of firing rates were somewhat stronger with an individual joint angle than with any principal component (PC), any jPC or any isomap dimension. In decoding analyses, where spikes and LFP power in the 100- to 170-Hz band each provided better decoding than other LFP-based signals, the first PC was decoded as well as the best decoded joint angle. But the remaining PCs and jPCs were predicted with lower accuracy than individual joint angles. Although PCs, jPCs or isomap dimensions might provide a more parsimonious description of kinematics, our findings indicate that the kinematic synergies identified with these techniques are not represented in motor cortex more strongly than the original joint angles. We suggest that the motor cortex might act to sculpt the synergies generated by subcortical centers, superimposing an ability to individuate finger movements and adapt the hand to grasp a wide variety of objects. PMID:24990564

Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.

PubMed

Mourao-Miranda, J; Reinders, A A T S; Rocha-Rego, V; Lappin, J; Rondina, J; Morgan, C; Morgan, K D; Fearon, P; Jones, P B; Doody, G A; Murray, R M; Kapur, S; Dazzan, P

2012-05-01

To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode. One hundred patients at their first psychotic episode and 91 healthy controls had an MRI scan. Patients were re-evaluated 6.2 years (s.d.=2.3) later, and were classified as having a continuous, episodic or intermediate illness course. Twenty-eight subjects with a continuous course were compared with 28 patients with an episodic course and with 28 healthy controls. We trained each SVM classifier independently for the following contrasts: continuous versus episodic, continuous versus healthy controls, and episodic versus healthy controls. At baseline, patients with a continuous course were already distinguishable, with significance above chance level, from both patients with an episodic course (p=0.004, sensitivity=71, specificity=68) and healthy individuals (p=0.01, sensitivity=71, specificity=61). Patients with an episodic course could not be distinguished from healthy individuals. When patients with an intermediate outcome were classified according to the discriminating pattern episodic versus continuous, 74% of those who did not develop other episodes were classified as episodic, and 65% of those who did develop further episodes were classified as continuous (p=0.035). We provide preliminary evidence of MRI application in the individualized prediction of future illness course, using a simple and automated SVM pipeline. When replicated and validated in larger groups, this could enable targeted clinical decisions based on imaging data.

Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study

PubMed Central

Mourao-Miranda, J.; Reinders, A. A. T. S.; Rocha-Rego, V.; Lappin, J.; Rondina, J.; Morgan, C.; Morgan, K. D.; Fearon, P.; Jones, P. B.; Doody, G. A.; Murray, R. M.; Kapur, S.; Dazzan, P.

2012-01-01

Background To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode. Method One hundred patients at their first psychotic episode and 91 healthy controls had an MRI scan. Patients were re-evaluated 6.2 years (s.d.=2.3) later, and were classified as having a continuous, episodic or intermediate illness course. Twenty-eight subjects with a continuous course were compared with 28 patients with an episodic course and with 28 healthy controls. We trained each SVM classifier independently for the following contrasts: continuous versus episodic, continuous versus healthy controls, and episodic versus healthy controls. Results At baseline, patients with a continuous course were already distinguishable, with significance above chance level, from both patients with an episodic course (p=0.004, sensitivity=71, specificity=68) and healthy individuals (p=0.01, sensitivity=71, specificity=61). Patients with an episodic course could not be distinguished from healthy individuals. When patients with an intermediate outcome were classified according to the discriminating pattern episodic versus continuous, 74% of those who did not develop other episodes were classified as episodic, and 65% of those who did develop further episodes were classified as continuous (p=0.035). Conclusions We provide preliminary evidence of MRI application in the individualized prediction of future illness course, using a simple and automated SVM pipeline. When replicated and validated in larger groups, this could enable targeted clinical decisions based on imaging data. PMID:22059690

Taurine supplementation for prevention of stroke-like episodes in MELAS: a multicentre, open-label, 52-week phase III trial.

PubMed

Ohsawa, Yutaka; Hagiwara, Hiroki; Nishimatsu, Shin-Ichiro; Hirakawa, Akihiro; Kamimura, Naomi; Ohtsubo, Hideaki; Fukai, Yuta; Murakami, Tatsufumi; Koga, Yasutoshi; Goto, Yu-Ichi; Ohta, Shigeo; Sunada, Yoshihide

2018-04-17

The aim of this study was to evaluate the efficacy and safety of high-dose taurine supplementation for prevention of stroke-like episodes of MELAS (mitochondrial myopathy, encephalopathy, lactic acidosis and stroke-like episodes), a rare genetic disorder caused by point mutations in the mitochondrial DNA that lead to a taurine modification defect at the first anticodon nucleotide of mitochondrial tRNA Leu(UUR) , resulting in failure to decode codons accurately. After the nationwide survey of MELAS, we conducted a multicentre, open-label, phase III trial in which 10 patients with recurrent stroke-like episodes received high-dose taurine (9 g or 12 g per day) for 52 weeks. The primary endpoint was the complete prevention of stroke-like episodes during the evaluation period. The taurine modification rate of mitochondrial tRNA Leu(UUR) was measured before and after the trial. The proportion of patients who reached the primary endpoint (100% responder rate) was 60% (95% CI 26.2% to 87.8%). The 50% responder rate, that is, the number of patients achieving a 50% or greater reduction in frequency of stroke-like episodes, was 80% (95% CI 44.4% to 97.5%). Taurine reduced the annual relapse rate of stroke-like episodes from 2.22 to 0.72 (P=0.001). Five patients showed a significant increase in the taurine modification of mitochondrial tRNA Leu(UUR) from peripheral blood leukocytes (P<0.05). No severe adverse events were associated with taurine. The current study demonstrates that oral taurine supplementation can effectively reduce the recurrence of stroke-like episodes and increase taurine modification in mitochondrial tRNA Leu(UUR) in MELAS. UMIN000011908. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Distinct neural patterns enable grasp types decoding in monkey dorsal premotor cortex.

PubMed

Hao, Yaoyao; Zhang, Qiaosheng; Controzzi, Marco; Cipriani, Christian; Li, Yue; Li, Juncheng; Zhang, Shaomin; Wang, Yiwen; Chen, Weidong; Chiara Carrozza, Maria; Zheng, Xiaoxiang

2014-12-01

Recent studies have shown that dorsal premotor cortex (PMd), a cortical area in the dorsomedial grasp pathway, is involved in grasp movements. However, the neural ensemble firing property of PMd during grasp movements and the extent to which it can be used for grasp decoding are still unclear. To address these issues, we used multielectrode arrays to record both spike and local field potential (LFP) signals in PMd in macaque monkeys performing reaching and grasping of one of four differently shaped objects. Single and population neuronal activity showed distinct patterns during execution of different grip types. Cluster analysis of neural ensemble signals indicated that the grasp related patterns emerged soon (200-300 ms) after the go cue signal, and faded away during the hold period. The timing and duration of the patterns varied depending on the behaviors of individual monkey. Application of support vector machine model to stable activity patterns revealed classification accuracies of 94% and 89% for each of the two monkeys, indicating a robust, decodable grasp pattern encoded in the PMd. Grasp decoding using LFPs, especially the high-frequency bands, also produced high decoding accuracies. This study is the first to specify the neuronal population encoding of grasp during the time course of grasp. We demonstrate high grasp decoding performance in PMd. These findings, combined with previous evidence for reach related modulation studies, suggest that PMd may play an important role in generation and maintenance of grasp action and may be a suitable locus for brain-machine interface applications.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

PubMed

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder

PubMed Central

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive. PMID:28018162

Music models aberrant rule decoding and reward valuation in dementia

PubMed Central

Clark, Camilla N; Golden, Hannah L; McCallion, Oliver; Nicholas, Jennifer M; Cohen, Miriam H; Slattery, Catherine F; Paterson, Ross W; Fletcher, Phillip D; Mummery, Catherine J; Rohrer, Jonathan D; Crutch, Sebastian J; Warren, Jason D

2018-01-01

Abstract Aberrant rule- and reward-based processes underpin abnormalities of socio-emotional behaviour in major dementias. However, these processes remain poorly characterized. Here we used music to probe rule decoding and reward valuation in patients with frontotemporal dementia (FTD) syndromes and Alzheimer’s disease (AD) relative to healthy age-matched individuals. We created short melodies that were either harmonically resolved (‘finished’) or unresolved (‘unfinished’); the task was to classify each melody as finished or unfinished (rule processing) and rate its subjective pleasantness (reward valuation). Results were adjusted for elementary pitch and executive processing; neuroanatomical correlates were assessed using voxel-based morphometry. Relative to healthy older controls, patients with behavioural variant FTD showed impairments of both musical rule decoding and reward valuation, while patients with semantic dementia showed impaired reward valuation but intact rule decoding, patients with AD showed impaired rule decoding but intact reward valuation and patients with progressive non-fluent aphasia performed comparably to healthy controls. Grey matter associations with task performance were identified in anterior temporal, medial and lateral orbitofrontal cortices, previously implicated in computing diverse biological and non-biological rules and rewards. The processing of musical rules and reward distils cognitive and neuroanatomical mechanisms relevant to complex socio-emotional dysfunction in major dementias. PMID:29186630

Continuous decoding of human grasp kinematics using epidural and subdural signals

NASA Astrophysics Data System (ADS)

Flint, Robert D.; Rosenow, Joshua M.; Tate, Matthew C.; Slutzky, Marc W.

2017-02-01

Objective. Restoring or replacing function in paralyzed individuals will one day be achieved through the use of brain-machine interfaces. Regaining hand function is a major goal for paralyzed patients. Two competing prerequisites for the widespread adoption of any hand neuroprosthesis are accurate control over the fine details of movement, and minimized invasiveness. Here, we explore the interplay between these two goals by comparing our ability to decode hand movements with subdural and epidural field potentials (EFPs). Approach. We measured the accuracy of decoding continuous hand and finger kinematics during naturalistic grasping motions in five human subjects. We recorded subdural surface potentials (electrocorticography; ECoG) as well as with EFPs, with both standard- and high-resolution electrode arrays. Main results. In all five subjects, decoding of continuous kinematics significantly exceeded chance, using either EGoG or EFPs. ECoG decoding accuracy compared favorably with prior investigations of grasp kinematics (mean ± SD grasp aperture variance accounted for was 0.54 ± 0.05 across all subjects, 0.75 ± 0.09 for the best subject). In general, EFP decoding performed comparably to ECoG decoding. The 7-20 Hz and 70-115 Hz spectral bands contained the most information about grasp kinematics, with the 70-115 Hz band containing greater information about more subtle movements. Higher-resolution recording arrays provided clearly superior performance compared to standard-resolution arrays. Significance. To approach the fine motor control achieved by an intact brain-body system, it will be necessary to execute motor intent on a continuous basis with high accuracy. The current results demonstrate that this level of accuracy might be achievable not just with ECoG, but with EFPs as well. Epidural placement of electrodes is less invasive, and therefore may incur less risk of encephalitis or stroke than subdural placement of electrodes. Accurately decoding motor commands at the epidural level may be an important step towards a clinically viable brain-machine interface.

Continuous decoding of human grasp kinematics using epidural and subdural signals

PubMed Central

Flint, Robert D.; Rosenow, Joshua M.; Tate, Matthew C.; Slutzky, Marc W.

2017-01-01

Objective Restoring or replacing function in paralyzed individuals will one day be achieved through the use of brain-machine interfaces (BMIs). Regaining hand function is a major goal for paralyzed patients. Two competing prerequisites for the widespread adoption of any hand neuroprosthesis are: accurate control over the fine details of movement, and minimized invasiveness. Here, we explore the interplay between these two goals by comparing our ability to decode hand movements with subdural and epidural field potentials. Approach We measured the accuracy of decoding continuous hand and finger kinematics during naturalistic grasping motions in five human subjects. We recorded subdural surface potentials (electrocorticography; ECoG) as well as with epidural field potentials (EFPs), with both standard- and high-resolution electrode arrays. Main results In all five subjects, decoding of continuous kinematics significantly exceeded chance, using either EGoG or EFPs. ECoG decoding accuracy compared favorably with prior investigations of grasp kinematics (mean± SD grasp aperture variance accounted for was 0.54± 0.05 across all subjects, 0.75± 0.09 for the best subject). In general, EFP decoding performed comparably to ECoG decoding. The 7–20 Hz and 70–115 Hz spectral bands contained the most information about grasp kinematics, with the 70–115 Hz band containing greater information about more subtle movements. Higher-resolution recording arrays provided clearly superior performance compared to standard-resolution arrays. Significance To approach the fine motor control achieved by an intact brain-body system, it will be necessary to execute motor intent on a continuous basis with high accuracy. The current results demonstrate that this level of accuracy might be achievable not just with ECoG, but with EFPs as well. Epidural placement of electrodes is less invasive, and therefore may incur less risk of encephalitis or stroke than subdural placement of electrodes. Accurately decoding motor commands at the epidural level may be an important step towards a clinically viable brain-machine interface. PMID:27900947

Parietal neural prosthetic control of a computer cursor in a graphical-user-interface task

NASA Astrophysics Data System (ADS)

Revechkis, Boris; Aflalo, Tyson NS; Kellis, Spencer; Pouratian, Nader; Andersen, Richard A.

2014-12-01

Objective. To date, the majority of Brain-Machine Interfaces have been used to perform simple tasks with sequences of individual targets in otherwise blank environments. In this study we developed a more practical and clinically relevant task that approximated modern computers and graphical user interfaces (GUIs). This task could be problematic given the known sensitivity of areas typically used for BMIs to visual stimuli, eye movements, decision-making, and attentional control. Consequently, we sought to assess the effect of a complex, GUI-like task on the quality of neural decoding. Approach. A male rhesus macaque monkey was implanted with two 96-channel electrode arrays in area 5d of the superior parietal lobule. The animal was trained to perform a GUI-like ‘Face in a Crowd’ task on a computer screen that required selecting one cued, icon-like, face image from a group of alternatives (the ‘Crowd’) using a neurally controlled cursor. We assessed whether the crowd affected decodes of intended cursor movements by comparing it to a ‘Crowd Off’ condition in which only the matching target appeared without alternatives. We also examined if training a neural decoder with the Crowd On rather than Off had any effect on subsequent decode quality. Main results. Despite the additional demands of working with the Crowd On, the animal was able to robustly perform the task under Brain Control. The presence of the crowd did not itself affect decode quality. Training the decoder with the Crowd On relative to Off had no negative influence on subsequent decoding performance. Additionally, the subject was able to gaze around freely without influencing cursor position. Significance. Our results demonstrate that area 5d recordings can be used for decoding in a complex, GUI-like task with free gaze. Thus, this area is a promising source of signals for neural prosthetics that utilize computing devices with GUI interfaces, e.g. personal computers, mobile devices, and tablet computers.

Parietal neural prosthetic control of a computer cursor in a graphical-user-interface task.

PubMed

Revechkis, Boris; Aflalo, Tyson N S; Kellis, Spencer; Pouratian, Nader; Andersen, Richard A

2014-12-01

To date, the majority of Brain-Machine Interfaces have been used to perform simple tasks with sequences of individual targets in otherwise blank environments. In this study we developed a more practical and clinically relevant task that approximated modern computers and graphical user interfaces (GUIs). This task could be problematic given the known sensitivity of areas typically used for BMIs to visual stimuli, eye movements, decision-making, and attentional control. Consequently, we sought to assess the effect of a complex, GUI-like task on the quality of neural decoding. A male rhesus macaque monkey was implanted with two 96-channel electrode arrays in area 5d of the superior parietal lobule. The animal was trained to perform a GUI-like 'Face in a Crowd' task on a computer screen that required selecting one cued, icon-like, face image from a group of alternatives (the 'Crowd') using a neurally controlled cursor. We assessed whether the crowd affected decodes of intended cursor movements by comparing it to a 'Crowd Off' condition in which only the matching target appeared without alternatives. We also examined if training a neural decoder with the Crowd On rather than Off had any effect on subsequent decode quality. Despite the additional demands of working with the Crowd On, the animal was able to robustly perform the task under Brain Control. The presence of the crowd did not itself affect decode quality. Training the decoder with the Crowd On relative to Off had no negative influence on subsequent decoding performance. Additionally, the subject was able to gaze around freely without influencing cursor position. Our results demonstrate that area 5d recordings can be used for decoding in a complex, GUI-like task with free gaze. Thus, this area is a promising source of signals for neural prosthetics that utilize computing devices with GUI interfaces, e.g. personal computers, mobile devices, and tablet computers.

On brain activity mapping: insights and lessons from Brain Decoding Project to map memory patterns in the hippocampus.

PubMed

Tsien, Joe Z; Li, Meng; Osan, Remus; Chen, Guifen; Lin, Longnian; Wang, Phillip Lei; Frey, Sabine; Frey, Julietta; Zhu, Dajiang; Liu, Tianming; Zhao, Fang; Kuang, Hui

2013-09-01

The BRAIN project recently announced by the president Obama is the reflection of unrelenting human quest for cracking the brain code, the patterns of neuronal activity that define who we are and what we are. While the Brain Activity Mapping proposal has rightly emphasized on the need to develop new technologies for measuring every spike from every neuron, it might be helpful to consider both the theoretical and experimental aspects that would accelerate our search for the organizing principles of the brain code. Here we share several insights and lessons from the similar proposal, namely, Brain Decoding Project that we initiated since 2007. We provide a specific example in our initial mapping of real-time memory traces from one part of the memory circuit, namely, the CA1 region of the mouse hippocampus. We show how innovative behavioral tasks and appropriate mathematical analyses of large datasets can play equally, if not more, important roles in uncovering the specific-to-general feature-coding cell assembly mechanism by which episodic memory, semantic knowledge, and imagination are generated and organized. Our own experiences suggest that the bottleneck of the Brain Project is not only at merely developing additional new technologies, but also the lack of efficient avenues to disseminate cutting edge platforms and decoding expertise to neuroscience community. Therefore, we propose that in order to harness unique insights and extensive knowledge from various investigators working in diverse neuroscience subfields, ranging from perception and emotion to memory and social behaviors, the BRAIN project should create a set of International and National Brain Decoding Centers at which cutting-edge recording technologies and expertise on analyzing large datasets analyses can be made readily available to the entire community of neuroscientists who can apply and schedule to perform cutting-edge research.

Short-Range Temporal Interactions in Sleep; Hippocampal Spike Avalanches Support a Large Milieu of Sequential Activity Including Replay

PubMed Central

Mahoney, J. Matthew; Titiz, Ali S.; Hernan, Amanda E.; Scott, Rod C.

2016-01-01

Hippocampal neural systems consolidate multiple complex behaviors into memory. However, the temporal structure of neural firing supporting complex memory consolidation is unknown. Replay of hippocampal place cells during sleep supports the view that a simple repetitive behavior modifies sleep firing dynamics, but does not explain how multiple episodes could be integrated into associative networks for recollection during future cognition. Here we decode sequential firing structure within spike avalanches of all pyramidal cells recorded in sleeping rats after running in a circular track. We find that short sequences that combine into multiple long sequences capture the majority of the sequential structure during sleep, including replay of hippocampal place cells. The ensemble, however, is not optimized for maximally producing the behavior-enriched episode. Thus behavioral programming of sequential correlations occurs at the level of short-range interactions, not whole behavioral sequences and these short sequences are assembled into a large and complex milieu that could support complex memory consolidation. PMID:26866597

Impact of personality on the cerebral processing of emotional prosody.

PubMed

Brück, Carolin; Kreifelts, Benjamin; Kaza, Evangelia; Lotze, Martin; Wildgruber, Dirk

2011-09-01

While several studies have focused on identifying common brain mechanisms governing the decoding of emotional speech melody, interindividual variations in the cerebral processing of prosodic information, in comparison, have received only little attention to date: Albeit, for instance, differences in personality among individuals have been shown to modulate emotional brain responses, personality influences on the neural basis of prosody decoding have not been investigated systematically yet. Thus, the present study aimed at delineating relationships between interindividual differences in personality and hemodynamic responses evoked by emotional speech melody. To determine personality-dependent modulations of brain reactivity, fMRI activation patterns during the processing of emotional speech cues were acquired from 24 healthy volunteers and subsequently correlated with individual trait measures of extraversion and neuroticism obtained for each participant. Whereas correlation analysis did not indicate any link between brain activation and extraversion, strong positive correlations between measures of neuroticism and hemodynamic responses of the right amygdala, the left postcentral gyrus as well as medial frontal structures including the right anterior cingulate cortex emerged, suggesting that brain mechanisms mediating the decoding of emotional speech melody may vary depending on differences in neuroticism among individuals. Observed trait-specific modulations are discussed in the light of processing biases as well as differences in emotion control or task strategies which may be associated with the personality trait of neuroticism. Copyright © 2011 Elsevier Inc. All rights reserved.

Good Phonic Generalizations for Decoding

ERIC Educational Resources Information Center

Gates, Louis

2007-01-01

An exhaustive analysis of 88,641 individual letters and letter combinations within 16,928 words drawn from the Zeno, et al. word list unveiled remarkable phonic transparency. The individual letter and letter combinations sorted into just six general categories: three basic categories of vowels (single vowels, vowel digraphs, and final…

Distinct neural patterns enable grasp types decoding in monkey dorsal premotor cortex

NASA Astrophysics Data System (ADS)

Hao, Yaoyao; Zhang, Qiaosheng; Controzzi, Marco; Cipriani, Christian; Li, Yue; Li, Juncheng; Zhang, Shaomin; Wang, Yiwen; Chen, Weidong; Chiara Carrozza, Maria; Zheng, Xiaoxiang

2014-12-01

Objective. Recent studies have shown that dorsal premotor cortex (PMd), a cortical area in the dorsomedial grasp pathway, is involved in grasp movements. However, the neural ensemble firing property of PMd during grasp movements and the extent to which it can be used for grasp decoding are still unclear. Approach. To address these issues, we used multielectrode arrays to record both spike and local field potential (LFP) signals in PMd in macaque monkeys performing reaching and grasping of one of four differently shaped objects. Main results. Single and population neuronal activity showed distinct patterns during execution of different grip types. Cluster analysis of neural ensemble signals indicated that the grasp related patterns emerged soon (200-300 ms) after the go cue signal, and faded away during the hold period. The timing and duration of the patterns varied depending on the behaviors of individual monkey. Application of support vector machine model to stable activity patterns revealed classification accuracies of 94% and 89% for each of the two monkeys, indicating a robust, decodable grasp pattern encoded in the PMd. Grasp decoding using LFPs, especially the high-frequency bands, also produced high decoding accuracies. Significance. This study is the first to specify the neuronal population encoding of grasp during the time course of grasp. We demonstrate high grasp decoding performance in PMd. These findings, combined with previous evidence for reach related modulation studies, suggest that PMd may play an important role in generation and maintenance of grasp action and may be a suitable locus for brain-machine interface applications.

Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning.

PubMed

Kia, Seyed Mostafa; Pedregosa, Fabian; Blumenthal, Anna; Passerini, Andrea

2017-06-15

The use of machine learning models to discriminate between patterns of neural activity has become in recent years a standard analysis approach in neuroimaging studies. Whenever these models are linear, the estimated parameters can be visualized in the form of brain maps which can aid in understanding how brain activity in space and time underlies a cognitive function. However, the recovered brain maps often suffer from lack of interpretability, especially in group analysis of multi-subject data. To facilitate the application of brain decoding in group-level analysis, we present an application of multi-task joint feature learning for group-level multivariate pattern recovery in single-trial magnetoencephalography (MEG) decoding. The proposed method allows for recovering sparse yet consistent patterns across different subjects, and therefore enhances the interpretability of the decoding model. Our experimental results demonstrate that the mutli-task joint feature learning framework is capable of recovering more meaningful patterns of varying spatio-temporally distributed brain activity across individuals while still maintaining excellent generalization performance. We compare the performance of the multi-task joint feature learning in terms of generalization, reproducibility, and quality of pattern recovery against traditional single-subject and pooling approaches on both simulated and real MEG datasets. These results can facilitate the usage of brain decoding for the characterization of fine-level distinctive patterns in group-level inference. Considering the importance of group-level analysis, the proposed approach can provide a methodological shift towards more interpretable brain decoding models. Copyright © 2017 Elsevier B.V. All rights reserved.

Decoding illusory self-location from activity in the human hippocampus.

PubMed

Guterstam, Arvid; Björnsdotter, Malin; Bergouignan, Loretxu; Gentile, Giovanni; Li, Tie-Qiang; Ehrsson, H Henrik

2015-01-01

Decades of research have demonstrated a role for the hippocampus in spatial navigation and episodic and spatial memory. However, empirical evidence linking hippocampal activity to the perceptual experience of being physically located at a particular place in the environment is lacking. In this study, we used a multisensory out-of-body illusion to perceptually 'teleport' six healthy participants between two different locations in the scanner room during high-resolution functional magnetic resonance imaging (fMRI). The participants were fitted with MRI-compatible head-mounted displays that changed their first-person visual perspective to that of a pair of cameras placed in one of two corners of the scanner room. To elicit the illusion of being physically located in this position, we delivered synchronous visuo-tactile stimulation in the form of an object moving toward the cameras coupled with touches applied to the participant's chest. Asynchronous visuo-tactile stimulation did not induce the illusion and served as a control condition. We found that illusory self-location could be successfully decoded from patterns of activity in the hippocampus in all of the participants in the synchronous (P < 0.05) but not in the asynchronous condition (P > 0.05). At the group-level, the decoding accuracy was significantly higher in the synchronous than in the asynchronous condition (P = 0.012). These findings associate hippocampal activity with the perceived location of the bodily self in space, which suggests that the human hippocampus is involved not only in spatial navigation and memory but also in the construction of our sense of bodily self-location.

Decoding illusory self-location from activity in the human hippocampus

PubMed Central

Guterstam, Arvid; Björnsdotter, Malin; Bergouignan, Loretxu; Gentile, Giovanni; Li, Tie-Qiang; Ehrsson, H. Henrik

2015-01-01

Decades of research have demonstrated a role for the hippocampus in spatial navigation and episodic and spatial memory. However, empirical evidence linking hippocampal activity to the perceptual experience of being physically located at a particular place in the environment is lacking. In this study, we used a multisensory out-of-body illusion to perceptually ‘teleport’ six healthy participants between two different locations in the scanner room during high-resolution functional magnetic resonance imaging (fMRI). The participants were fitted with MRI-compatible head-mounted displays that changed their first-person visual perspective to that of a pair of cameras placed in one of two corners of the scanner room. To elicit the illusion of being physically located in this position, we delivered synchronous visuo-tactile stimulation in the form of an object moving toward the cameras coupled with touches applied to the participant’s chest. Asynchronous visuo-tactile stimulation did not induce the illusion and served as a control condition. We found that illusory self-location could be successfully decoded from patterns of activity in the hippocampus in all of the participants in the synchronous (P < 0.05) but not in the asynchronous condition (P > 0.05). At the group-level, the decoding accuracy was significantly higher in the synchronous than in the asynchronous condition (P = 0.012). These findings associate hippocampal activity with the perceived location of the bodily self in space, which suggests that the human hippocampus is involved not only in spatial navigation and memory but also in the construction of our sense of bodily self-location. PMID:26236222

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

PubMed

Portugal, Liana C L; Rosa, Maria João; Rao, Anil; Bebko, Genna; Bertocci, Michele A; Hinze, Amanda K; Bonar, Lisa; Almeida, Jorge R C; Perlman, Susan B; Versace, Amelia; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Demeter, Christine; Diwadkar, Vaibhav A; Ciuffetelli, Gary; Rodriguez, Eric; Forbes, Erika E; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Horwitz, Sarah M; Arnold, Eugene L; Fristad, Mary A; Youngstrom, Eric A; Findling, Robert L; Pereira, Mirtes; Oliveira, Leticia; Phillips, Mary L; Mourao-Miranda, Janaina

2016-01-01

High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points. A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels. Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included cerebellum, sensory-motor and fronto-limbic areas. The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.

Neural population encoding and decoding of sound source location across sound level in the rabbit inferior colliculus

PubMed Central

Delgutte, Bertrand

2015-01-01

At lower levels of sensory processing, the representation of a stimulus feature in the response of a neural population can vary in complex ways across different stimulus intensities, potentially changing the amount of feature-relevant information in the response. How higher-level neural circuits could implement feature decoding computations that compensate for these intensity-dependent variations remains unclear. Here we focused on neurons in the inferior colliculus (IC) of unanesthetized rabbits, whose firing rates are sensitive to both the azimuthal position of a sound source and its sound level. We found that the azimuth tuning curves of an IC neuron at different sound levels tend to be linear transformations of each other. These transformations could either increase or decrease the mutual information between source azimuth and spike count with increasing level for individual neurons, yet population azimuthal information remained constant across the absolute sound levels tested (35, 50, and 65 dB SPL), as inferred from the performance of a maximum-likelihood neural population decoder. We harnessed evidence of level-dependent linear transformations to reduce the number of free parameters in the creation of an accurate cross-level population decoder of azimuth. Interestingly, this decoder predicts monotonic azimuth tuning curves, broadly sensitive to contralateral azimuths, in neurons at higher levels in the auditory pathway. PMID:26490292

EEG resolutions in detecting and decoding finger movements from spectral analysis

PubMed Central

Xiao, Ran; Ding, Lei

2015-01-01

Mu/beta rhythms are well-studied brain activities that originate from sensorimotor cortices. These rhythms reveal spectral changes in alpha and beta bands induced by movements of different body parts, e.g., hands and limbs, in electroencephalography (EEG) signals. However, less can be revealed in them about movements of different fine body parts that activate adjacent brain regions, such as individual fingers from one hand. Several studies have reported spatial and temporal couplings of rhythmic activities at different frequency bands, suggesting the existence of well-defined spectral structures across multiple frequency bands. In the present study, spectral principal component analysis (PCA) was applied on EEG data, obtained from a finger movement task, to identify cross-frequency spectral structures. Features from identified spectral structures were examined in their spatial patterns, cross-condition pattern changes, detection capability of finger movements from resting, and decoding performance of individual finger movements in comparison to classic mu/beta rhythms. These new features reveal some similar, but more different spatial and spectral patterns as compared with classic mu/beta rhythms. Decoding results further indicate that these new features (91%) can detect finger movements much better than classic mu/beta rhythms (75.6%). More importantly, these new features reveal discriminative information about movements of different fingers (fine body-part movements), which is not available in classic mu/beta rhythms. The capability in decoding fingers (and hand gestures in the future) from EEG will contribute significantly to the development of non-invasive BCI and neuroprosthesis with intuitive and flexible controls. PMID:26388720

Developmental origins of recoding and decoding in memory.

PubMed

Kibbe, Melissa M; Feigenson, Lisa

2014-12-01

Working memory is severely limited in both adults and children, but one way that adults can overcome this limit is through the process of recoding. Recoding happens when representations of individual items are chunked together into a higher order representation, and the chunk is assigned a label. That label can then be decoded to retrieve the individual items from long-term memory. Whereas this ability has been extensively studied in adults (as, for example, in classic studies of memory in chess), little is known about recoding's developmental origins. Here we asked whether 2- to 3-year-old children also can recode-that is, can they restructure representations of individual objects into a higher order chunk, assign this new representation a verbal label, and then later decode the label to retrieve the represented individuals from memory. In Experiments 1 and 2, we showed children identical blocks that could be connected to make tools. Children learned a novel name for a tool that could be built from two blocks, and for a tool that could be built from three blocks. Later we told children that one of the tools was hidden in a box, with no visual information provided. Children were allowed to search the box and retrieve varying numbers of blocks. Critically, the retrieved blocks were identical and unconnected, so the only way children could know whether any blocks remained was by using the verbal label to recall how many objects comprised each tool (or chunk). We found that even children who could not yet count adjusted their searching of the box depending on the label they had heard. This suggests that they had recoded representations of individual blocks into higher-order chunks, attached labels to the chunks, and then later decoded the labels to infer how many blocks were hidden. In Experiments 3 and 4 we asked whether recoding also can expand the number of individual objects children could remember, as in the classic studies with adults. We found that when no information was provided to support recoding, children showed the standard failure to remember more than three hidden objects at once. But when provided recoding information, children successfully represented up to five individual objects in the box, thereby overcoming typical working memory limits. These results are the first demonstration of recoding by young children; we close by discussing their implications for understanding the structure of memory throughout the lifespan. Copyright © 2014 Elsevier Inc. All rights reserved.

Error Control Coding Techniques for Space and Satellite Communications

NASA Technical Reports Server (NTRS)

Lin, Shu

2000-01-01

This paper presents a concatenated turbo coding system in which a Reed-Solomom outer code is concatenated with a binary turbo inner code. In the proposed system, the outer code decoder and the inner turbo code decoder interact to achieve both good bit error and frame error performances. The outer code decoder helps the inner turbo code decoder to terminate its decoding iteration while the inner turbo code decoder provides soft-output information to the outer code decoder to carry out a reliability-based soft-decision decoding. In the case that the outer code decoding fails, the outer code decoder instructs the inner code decoder to continue its decoding iterations until the outer code decoding is successful or a preset maximum number of decoding iterations is reached. This interaction between outer and inner code decoders reduces decoding delay. Also presented in the paper are an effective criterion for stopping the iteration process of the inner code decoder and a new reliability-based decoding algorithm for nonbinary codes.

An Interactive Concatenated Turbo Coding System

NASA Technical Reports Server (NTRS)

Liu, Ye; Tang, Heng; Lin, Shu; Fossorier, Marc

1999-01-01

This paper presents a concatenated turbo coding system in which a Reed-Solomon outer code is concatenated with a binary turbo inner code. In the proposed system, the outer code decoder and the inner turbo code decoder interact to achieve both good bit error and frame error performances. The outer code decoder helps the inner turbo code decoder to terminate its decoding iteration while the inner turbo code decoder provides soft-output information to the outer code decoder to carry out a reliability-based soft- decision decoding. In the case that the outer code decoding fails, the outer code decoder instructs the inner code decoder to continue its decoding iterations until the outer code decoding is successful or a preset maximum number of decoding iterations is reached. This interaction between outer and inner code decoders reduces decoding delay. Also presented in the paper are an effective criterion for stopping the iteration process of the inner code decoder and a new reliability-based decoding algorithm for nonbinary codes.

Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers

PubMed Central

Zoccolotti, Pierluigi; De Luca, Maria; Marinelli, Chiara V.; Spinelli, Donatella

2014-01-01

This study was aimed at predicting individual differences in text reading fluency. The basic proposal included two factors, i.e., the ability to decode letter strings (measured by discrete pseudo-word reading) and integration of the various sub-components involved in reading (measured by Rapid Automatized Naming, RAN). Subsequently, a third factor was added to the model, i.e., naming of discrete digits. In order to use homogeneous measures, all contributing variables considered the entire processing of the item, including pronunciation time. The model, which was based on commonality analysis, was applied to data from a group of 43 typically developing readers (11- to 13-year-olds) and a group of 25 chronologically matched dyslexic children. In typically developing readers, both orthographic decoding and integration of reading sub-components contributed significantly to the overall prediction of text reading fluency. The model prediction was higher (from ca. 37 to 52% of the explained variance) when we included the naming of discrete digits variable, which had a suppressive effect on pseudo-word reading. In the dyslexic readers, the variance explained by the two-factor model was high (69%) and did not change when the third factor was added. The lack of a suppression effect was likely due to the prominent individual differences in poor orthographic decoding of the dyslexic children. Analyses on data from both groups of children were replicated by using patches of colors as stimuli (both in the RAN task and in the discrete naming task) obtaining similar results. We conclude that it is possible to predict much of the variance in text-reading fluency using basic processes, such as orthographic decoding and integration of reading sub-components, even without taking into consideration higher-order linguistic factors such as lexical, semantic and contextual abilities. The approach validity of using proximal vs. distal causes to predict reading fluency is discussed. PMID:25477856

Multiclass fMRI data decoding and visualization using supervised self-organizing maps.

PubMed

Hausfeld, Lars; Valente, Giancarlo; Formisano, Elia

2014-08-01

When multivariate pattern decoding is applied to fMRI studies entailing more than two experimental conditions, a most common approach is to transform the multiclass classification problem into a series of binary problems. Furthermore, for decoding analyses, classification accuracy is often the only outcome reported although the topology of activation patterns in the high-dimensional features space may provide additional insights into underlying brain representations. Here we propose to decode and visualize voxel patterns of fMRI datasets consisting of multiple conditions with a supervised variant of self-organizing maps (SSOMs). Using simulations and real fMRI data, we evaluated the performance of our SSOM-based approach. Specifically, the analysis of simulated fMRI data with varying signal-to-noise and contrast-to-noise ratio suggested that SSOMs perform better than a k-nearest-neighbor classifier for medium and large numbers of features (i.e. 250 to 1000 or more voxels) and similar to support vector machines (SVMs) for small and medium numbers of features (i.e. 100 to 600voxels). However, for a larger number of features (>800voxels), SSOMs performed worse than SVMs. When applied to a challenging 3-class fMRI classification problem with datasets collected to examine the neural representation of three human voices at individual speaker level, the SSOM-based algorithm was able to decode speaker identity from auditory cortical activation patterns. Classification performances were similar between SSOMs and other decoding algorithms; however, the ability to visualize decoding models and underlying data topology of SSOMs promotes a more comprehensive understanding of classification outcomes. We further illustrated this visualization ability of SSOMs with a re-analysis of a dataset examining the representation of visual categories in the ventral visual cortex (Haxby et al., 2001). This analysis showed that SSOMs could retrieve and visualize topography and neighborhood relations of the brain representation of eight visual categories. We conclude that SSOMs are particularly suited for decoding datasets consisting of more than two classes and are optimally combined with approaches that reduce the number of voxels used for classification (e.g. region-of-interest or searchlight approaches). Copyright © 2014. Published by Elsevier Inc.

Relationships among low-frequency local field potentials, spiking activity, and three-dimensional reach and grasp kinematics in primary motor and ventral premotor cortices

PubMed Central

Vargas-Irwin, Carlos E.; Truccolo, Wilson; Donoghue, John P.

2011-01-01

A prominent feature of motor cortex field potentials during movement is a distinctive low-frequency local field potential (lf-LFP) (<4 Hz), referred to as the movement event-related potential (mEP). The lf-LFP appears to be a global signal related to regional synaptic input, but its relationship to nearby output signaled by single unit spiking activity (SUA) or to movement remains to be established. Previous studies comparing information in primary motor cortex (MI) lf-LFPs and SUA in the context of planar reaching tasks concluded that lf-LFPs have more information than spikes about movement. However, the relative performance of these signals was based on a small number of simultaneously recorded channels and units, or for data averaged across sessions, which could miss information of larger-scale spiking populations. Here, we simultaneously recorded LFPs and SUA from two 96-microelectrode arrays implanted in two major motor cortical areas, MI and ventral premotor (PMv), while monkeys freely reached for and grasped objects swinging in front of them. We compared arm end point and grip aperture kinematics′ decoding accuracy for lf-LFP and SUA ensembles. The results show that lf-LFPs provide enough information to reconstruct kinematics in both areas with little difference in decoding performance between MI and PMv. Individual lf-LFP channels often provided more accurate decoding of single kinematic variables than any one single unit. However, the decoding performance of the best single unit among the large population usually exceeded that of the best single lf-LFP channel. Furthermore, ensembles of SUA outperformed the pool of lf-LFP channels, in disagreement with the previously reported superiority of lf-LFP decoding. Decoding results suggest that information in lf-LFPs recorded from intracortical arrays may allow the reconstruction of reach and grasp for real-time neuroprosthetic applications, thus potentially supplementing the ability to decode these same features from spiking populations. PMID:21273313

Neural decoding with kernel-based metric learning.

PubMed

Brockmeier, Austin J; Choi, John S; Kriminger, Evan G; Francis, Joseph T; Principe, Jose C

2014-06-01

In studies of the nervous system, the choice of metric for the neural responses is a pivotal assumption. For instance, a well-suited distance metric enables us to gauge the similarity of neural responses to various stimuli and assess the variability of responses to a repeated stimulus-exploratory steps in understanding how the stimuli are encoded neurally. Here we introduce an approach where the metric is tuned for a particular neural decoding task. Neural spike train metrics have been used to quantify the information content carried by the timing of action potentials. While a number of metrics for individual neurons exist, a method to optimally combine single-neuron metrics into multineuron, or population-based, metrics is lacking. We pose the problem of optimizing multineuron metrics and other metrics using centered alignment, a kernel-based dependence measure. The approach is demonstrated on invasively recorded neural data consisting of both spike trains and local field potentials. The experimental paradigm consists of decoding the location of tactile stimulation on the forepaws of anesthetized rats. We show that the optimized metrics highlight the distinguishing dimensions of the neural response, significantly increase the decoding accuracy, and improve nonlinear dimensionality reduction methods for exploratory neural analysis.

Moral judgment in episodic amnesia.

PubMed

Craver, Carl F; Keven, Nazim; Kwan, Donna; Kurczek, Jake; Duff, Melissa C; Rosenbaum, R Shayna

2016-08-01

To investigate the role of episodic thought about the past and future in moral judgment, we administered a well-established moral judgment battery to individuals with hippocampal damage and deficits in episodic thought (insert Greene et al. 2001). Healthy controls select deontological answers in high-conflict moral scenarios more frequently when they vividly imagine themselves in the scenarios than when they imagine scenarios abstractly, at some personal remove. If this bias is mediated by episodic thought, individuals with deficits in episodic thought should not exhibit this effect. We report that individuals with deficits in episodic memory and future thought make moral judgments and exhibit the biasing effect of vivid, personal imaginings on moral judgment. These results strongly suggest that the biasing effect of vivid personal imagining on moral judgment is not due to episodic thought about the past and future. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Text-to-Speech and Reading While Listening: Reading Support for Individuals with Severe Traumatic Brain Injury

ERIC Educational Resources Information Center

Harvey, Judy

2013-01-01

Individuals with severe traumatic brain injury (TBI) often have reading challenges. They maintain or reestablish basic decoding and word recognition skills following injury, but problems with reading comprehension often persist. Practitioners have the potential to accommodate struggling readers by changing the presentational mode of text in a…

Successful Strategies of Individuals with Dyslexia in the Field of Music: A Comparative Case Study

ERIC Educational Resources Information Center

Nelson, Kent Peter

2014-01-01

Many of the symptoms of dyslexia--such as difficulties with decoding written symbols, phonemic awareness, physical coordination, and readable handwriting--may adversely affect music learning. Despite challenges, some individuals with dyslexia succeed in music. The purpose of this study was to examine the perceptions of five professional musicians…

Decoding Visual Location From Neural Patterns in the Auditory Cortex of the Congenitally Deaf

PubMed Central

Almeida, Jorge; He, Dongjun; Chen, Quanjing; Mahon, Bradford Z.; Zhang, Fan; Gonçalves, Óscar F.; Fang, Fang; Bi, Yanchao

2016-01-01

Sensory cortices of individuals who are congenitally deprived of a sense can exhibit considerable plasticity and be recruited to process information from the senses that remain intact. Here, we explored whether the auditory cortex of congenitally deaf individuals represents visual field location of a stimulus—a dimension that is represented in early visual areas. We used functional MRI to measure neural activity in auditory and visual cortices of congenitally deaf and hearing humans while they observed stimuli typically used for mapping visual field preferences in visual cortex. We found that the location of a visual stimulus can be successfully decoded from the patterns of neural activity in auditory cortex of congenitally deaf but not hearing individuals. This is particularly true for locations within the horizontal plane and within peripheral vision. These data show that the representations stored within neuroplastically changed auditory cortex can align with dimensions that are typically represented in visual cortex. PMID:26423461

Memory and Obstructive Sleep Apnea: A Meta-Analysis

PubMed Central

Wallace, Anna; Bucks, Romola S.

2013-01-01

Study Objectives: To examine episodic memory performance in individuals with obstructive sleep apnea (OSA). Design Meta-analysis was used to synthesize results from individual studies examining the impact of OSA on episodic memory performance. The performance of individuals with OSA was compared to healthy controls or normative data. Participants Forty-two studies were included, comprising 2,294 adults with untreated OSA and 1,364 healthy controls. Studies that recorded information about participants at baseline prior to treatment interventions were included in the analysis. Measurements Participants were assessed with tasks that included a measure of episodic memory: immediate recall, delayed recall, learning, and/or recognition memory. Results: The results of the meta-analyses provide evidence that individuals with OSA are significantly impaired when compared to healthy controls on verbal episodic memory (immediate recall, delayed recall, learning, and recognition) and visuo-spatial episodic memory (immediate and delayed recall), but not visual immediate recall or visuo-spatial learning. When patients were compared to norms, negative effects of OSA were found only in verbal immediate and delayed recall. Conclusions: This meta-analysis contributes to understanding of the nature of episodic memory deficits in individuals with OSA. Impairments to episodic memory are likely to affect the daily functioning of individuals with OSA. Citation Wallace A; Bucks RS. Memory and obstructive sleep apnea: a meta-analysis. SLEEP 2013;36(2):203-220. PMID:23372268

Individual and group sensitivity to remedial reading program design: Examining reading gains across three middle school reading projects

PubMed Central

Calhoon, Mary Beth; Petscher, Yaacov

2015-01-01

The purpose of this project was to examine group- and individual-level responses by struggling adolescents readers (6th – 8th grades; N = 155) to three different modalities of the same reading program, Reading Achievement Multi-Component Program (RAMP-UP). The three modalities differ in the combination of reading components (phonological decoding, spelling, fluency, comprehension) that are taught and their organization. Latent change scores were used to examine changes in phonological decoding, fluency, and comprehension for each modality at the group level. In addition, individual students were classified as gainers versus non-gainers (a reading level increase of a year or more vs. less than one year) so that characteristics of gainers and differential sensitivity to instructional modality could be investigated. Findings from both group and individual analyses indicated that reading outcomes were related to modalities of reading instruction. Furthermore, differences in reading gains were seen between students who began treatment with higher reading scores than those with lower reading scores; dependent on modality of treatment. Results, examining group and individual analyses similarities and differences, and the effect the different modalities have on reading outcomes for older struggling readers will be discussed. PMID:25657503

Hamming and Accumulator Codes Concatenated with MPSK or QAM

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Dolinar, Samuel

2009-01-01

In a proposed coding-and-modulation scheme, a high-rate binary data stream would be processed as follows: 1. The input bit stream would be demultiplexed into multiple bit streams. 2. The multiple bit streams would be processed simultaneously into a high-rate outer Hamming code that would comprise multiple short constituent Hamming codes a distinct constituent Hamming code for each stream. 3. The streams would be interleaved. The interleaver would have a block structure that would facilitate parallelization for high-speed decoding. 4. The interleaved streams would be further processed simultaneously into an inner two-state, rate-1 accumulator code that would comprise multiple constituent accumulator codes - a distinct accumulator code for each stream. 5. The resulting bit streams would be mapped into symbols to be transmitted by use of a higher-order modulation - for example, M-ary phase-shift keying (MPSK) or quadrature amplitude modulation (QAM). The novelty of the scheme lies in the concatenation of the multiple-constituent Hamming and accumulator codes and the corresponding parallel architectures of the encoder and decoder circuitry (see figure) needed to process the multiple bit streams simultaneously. As in the cases of other parallel-processing schemes, one advantage of this scheme is that the overall data rate could be much greater than the data rate of each encoder and decoder stream and, hence, the encoder and decoder could handle data at an overall rate beyond the capability of the individual encoder and decoder circuits.

Abstraction and generalization in statistical learning: implications for the relationship between semantic types and episodic tokens

PubMed Central

2017-01-01

Statistical approaches to emergent knowledge have tended to focus on the process by which experience of individual episodes accumulates into generalizable experience across episodes. However, there is a seemingly opposite, but equally critical, process that such experience affords: the process by which, from a space of types (e.g. onions—a semantic class that develops through exposure to individual episodes involving individual onions), we can perceive or create, on-the-fly, a specific token (a specific onion, perhaps one that is chopped) in the absence of any prior perceptual experience with that specific token. This article reviews a selection of statistical learning studies that lead to the speculation that this process—the generation, on the basis of semantic memory, of a novel episodic representation—is itself an instance of a statistical, in fact associative, process. The article concludes that the same processes that enable statistical abstraction across individual episodes to form semantic memories also enable the generation, from those semantic memories, of representations that correspond to individual tokens, and of novel episodic facts about those tokens. Statistical learning is a window onto these deeper processes that underpin cognition. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872378

Abstraction and generalization in statistical learning: implications for the relationship between semantic types and episodic tokens.

PubMed

Altmann, Gerry T M

2017-01-05

Statistical approaches to emergent knowledge have tended to focus on the process by which experience of individual episodes accumulates into generalizable experience across episodes. However, there is a seemingly opposite, but equally critical, process that such experience affords: the process by which, from a space of types (e.g. onions-a semantic class that develops through exposure to individual episodes involving individual onions), we can perceive or create, on-the-fly, a specific token (a specific onion, perhaps one that is chopped) in the absence of any prior perceptual experience with that specific token. This article reviews a selection of statistical learning studies that lead to the speculation that this process-the generation, on the basis of semantic memory, of a novel episodic representation-is itself an instance of a statistical, in fact associative, process. The article concludes that the same processes that enable statistical abstraction across individual episodes to form semantic memories also enable the generation, from those semantic memories, of representations that correspond to individual tokens, and of novel episodic facts about those tokens. Statistical learning is a window onto these deeper processes that underpin cognition.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

Goal-Directed Modulation of Neural Memory Patterns: Implications for fMRI-Based Memory Detection.

PubMed

Uncapher, Melina R; Boyd-Meredith, J Tyler; Chow, Tiffany E; Rissman, Jesse; Wagner, Anthony D

2015-06-03

Remembering a past event elicits distributed neural patterns that can be distinguished from patterns elicited when encountering novel information. These differing patterns can be decoded with relatively high diagnostic accuracy for individual memories using multivoxel pattern analysis (MVPA) of fMRI data. Brain-based memory detection--if valid and reliable--would have clear utility beyond the domain of cognitive neuroscience, in the realm of law, marketing, and beyond. However, a significant boundary condition on memory decoding validity may be the deployment of "countermeasures": strategies used to mask memory signals. Here we tested the vulnerability of fMRI-based memory detection to countermeasures, using a paradigm that bears resemblance to eyewitness identification. Participants were scanned while performing two tasks on previously studied and novel faces: (1) a standard recognition memory task; and (2) a task wherein they attempted to conceal their true memory state. Univariate analyses revealed that participants were able to strategically modulate neural responses, averaged across trials, in regions implicated in memory retrieval, including the hippocampus and angular gyrus. Moreover, regions associated with goal-directed shifts of attention and thought substitution supported memory concealment, and those associated with memory generation supported novelty concealment. Critically, whereas MVPA enabled reliable classification of memory states when participants reported memory truthfully, the ability to decode memory on individual trials was compromised, even reversing, during attempts to conceal memory. Together, these findings demonstrate that strategic goal states can be deployed to mask memory-related neural patterns and foil memory decoding technology, placing a significant boundary condition on their real-world utility. Copyright © 2015 the authors 0270-6474/15/358531-15$15.00/0.

Lindamood Phonemic Sequencing (LiPS) [R]. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2008

2008-01-01

The Lindamood Phonemic Sequencing (LiPS)[R] program (formerly called the Auditory Discrimination in Depth[R] [ADD] program) is designed to teach students skills to decode words and to identify individual sounds and blends in words. The program is individualized to meet student needs and is often used with students who have learning disabilities or…

Enhanced decoding for the Galileo low-gain antenna mission: Viterbi redecoding with four decoding stages

NASA Technical Reports Server (NTRS)

Dolinar, S.; Belongie, M.

1995-01-01

The Galileo low-gain antenna mission will be supported by a coding system that uses a (14,1/4) inner convolutional code concatenated with Reed-Solomon codes of four different redundancies. Decoding for this code is designed to proceed in four distinct stages of Viterbi decoding followed by Reed-Solomon decoding. In each successive stage, the Reed-Solomon decoder only tries to decode the highest redundancy codewords not yet decoded in previous stages, and the Viterbi decoder redecodes its data utilizing the known symbols from previously decoded Reed-Solomon codewords. A previous article analyzed a two-stage decoding option that was not selected by Galileo. The present article analyzes the four-stage decoding scheme and derives the near-optimum set of redundancies selected for use by Galileo. The performance improvements relative to one- and two-stage decoding systems are evaluated.

Atypical neurophysiology underlying episodic and semantic memory in adults with autism spectrum disorder.

PubMed

Massand, Esha; Bowler, Dermot M

2015-02-01

Individuals with autism spectrum disorder (ASD) show atypicalities in episodic memory (Boucher et al. in Psychological Bulletin, 138 (3), 458-496, 2012). We asked participants to recall the colours of a set of studied line drawings (episodic judgement), or to recognize line drawings alone (semantic judgement). Cycowicz et al. (Journal of Experimental Child Psychology, 65, 171-237, 2001) found early (300 ms onset) posterior old-new event-related potential effects for semantic judgements in typically developing (TD) individuals, and occipitally focused negativity (800 ms onset) for episodic judgements. Our results replicated findings in TD individuals and demonstrate attenuated early old-new effects in ASD. Late posterior negativity was present in the ASD group, but was not specific to this time window. This non-specificity may contribute to the atypical episodic memory judgements characteristic of individuals with ASD.

Multifamily group psychoeducation and cognitive remediation for first-episode psychosis: a randomized controlled trial.

PubMed

Breitborde, Nicholas Jk; Moreno, Francisco A; Mai-Dixon, Natalie; Peterson, Rachele; Durst, Linda; Bernstein, Beth; Byreddy, Seenaiah; McFarlane, William R

2011-01-12

Multifamily group psychoeducation (MFG) has been shown to reduce relapse rates among individuals with first-episode psychosis. However, given the cognitive demands associated with participating in this intervention (e.g., learning and applying a structured problem-solving activity), the cognitive deficits that accompany psychotic disorders may limit the ability of certain individuals to benefit from this intervention. Thus, the goal of this study is to examine whether individuals with first-episode psychosis who participate simultaneously in MFG and cognitive remediation--an intervention shown to improve cognitive functioning among individuals with psychotic disorders--will be less likely to experience a relapse than individuals who participate in MFG alone. Forty individuals with first-episode psychosis and their caregiving relative will be recruited to participate in this study. Individuals with first-episode psychosis will be randomized to one of two conditions: (i) MFG with concurrent participation in cognitive remediation or (ii) MFG alone. The primary outcome for this study is relapse of psychotic symptoms. We will also examine secondary outcomes among both individuals with first-episode psychosis (i.e., social and vocational functioning, health-related quality of life, service utilization, independent living status, and cognitive functioning) and their caregiving relatives (i.e., caregiver burden, anxiety, and depression) Cognitive remediation offers the possibility of ameliorating a specific deficit (i.e., deficits in cognitive functioning) that often accompanies psychotic symptoms and may restrict the magnitude of the clinical benefits derived from MFG. ClinicalTrials (NCT): NCT01196286.

Evaluation of classifier topologies for the real-time classification of simultaneous limb motions.

PubMed

Ortiz-Catalan, Max; Branemark, Rickard; Hakansson, Bo

2013-01-01

The prediction of motion intent through the decoding of myoelectric signals has the potential to improve the functionally of limb prostheses. Considerable research on individual motion classifiers has been done to exploit this idea. A drawback with the individual prediction approach, however, is its limitation to serial control, which is slow, cumbersome, and unnatural. In this work, different classifier topologies suitable for the decoding of mixed classes, and thus capable of predicting simultaneous motions, were investigated in real-time. These topologies resulted in higher offline accuracies than previously achieved, but more importantly, positive indications of their suitability for real-time systems were found. Furthermore, in order to facilitate further development, benchmarking, and cooperation, the algorithms and data generated in this study are freely available as part of BioPatRec, an open source framework for the development of advanced prosthetic control strategies.

Scalable SCPPM Decoder

NASA Technical Reports Server (NTRS)

Quir, Kevin J.; Gin, Jonathan W.; Nguyen, Danh H.; Nguyen, Huy; Nakashima, Michael A.; Moision, Bruce E.

2012-01-01

A decoder was developed that decodes a serial concatenated pulse position modulation (SCPPM) encoded information sequence. The decoder takes as input a sequence of four bit log-likelihood ratios (LLR) for each PPM slot in a codeword via a XAUI 10-Gb/s quad optical fiber interface. If the decoder is unavailable, it passes the LLRs on to the next decoder via a XAUI 10-Gb/s quad optical fiber interface. Otherwise, it decodes the sequence and outputs information bits through a 1-GB/s Ethernet UDP/IP (User Datagram Protocol/Internet Protocol) interface. The throughput for a single decoder unit is 150-Mb/s at an average of four decoding iterations; by connecting a number of decoder units in series, a decoding rate equal to that of the aggregate rate is achieved. The unit is controlled through a 1-GB/s Ethernet UDP/IP interface. This ground station decoder was developed to demonstrate a deep space optical communication link capability, and is unique in the scalable design to achieve real-time SCPP decoding at the aggregate data rate.

Human Orbitofrontal Cortex Represents a Cognitive Map of State Space.

PubMed

Schuck, Nicolas W; Cai, Ming Bo; Wilson, Robert C; Niv, Yael

2016-09-21

Although the orbitofrontal cortex (OFC) has been studied intensely for decades, its precise functions have remained elusive. We recently hypothesized that the OFC contains a "cognitive map" of task space in which the current state of the task is represented, and this representation is especially critical for behavior when states are unobservable from sensory input. To test this idea, we apply pattern-classification techniques to neuroimaging data from humans performing a decision-making task with 16 states. We show that unobservable task states can be decoded from activity in OFC, and decoding accuracy is related to task performance and the occurrence of individual behavioral errors. Moreover, similarity between the neural representations of consecutive states correlates with behavioral accuracy in corresponding state transitions. These results support the idea that OFC represents a cognitive map of task space and establish the feasibility of decoding state representations in humans using non-invasive neuroimaging. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural signatures of attention: insights from decoding population activity patterns.

PubMed

Sapountzis, Panagiotis; Gregoriou, Georgia G

2018-01-01

Understanding brain function and the computations that individual neurons and neuronal ensembles carry out during cognitive functions is one of the biggest challenges in neuroscientific research. To this end, invasive electrophysiological studies have provided important insights by recording the activity of single neurons in behaving animals. To average out noise, responses are typically averaged across repetitions and across neurons that are usually recorded on different days. However, the brain makes decisions on short time scales based on limited exposure to sensory stimulation by interpreting responses of populations of neurons on a moment to moment basis. Recent studies have employed machine-learning algorithms in attention and other cognitive tasks to decode the information content of distributed activity patterns across neuronal ensembles on a single trial basis. Here, we review results from studies that have used pattern-classification decoding approaches to explore the population representation of cognitive functions. These studies have offered significant insights into population coding mechanisms. Moreover, we discuss how such advances can aid the development of cognitive brain-computer interfaces.

Resting-state functional brain networks in first-episode psychosis: A 12-month follow-up study.

PubMed

Ganella, Eleni P; Seguin, Caio; Pantelis, Christos; Whittle, Sarah; Baune, Bernhard T; Olver, James; Amminger, G Paul; McGorry, Patrick D; Cropley, Vanessa; Zalesky, Andrew; Bartholomeusz, Cali F

2018-05-01

Schizophrenia is increasingly conceived as a disorder of brain network connectivity and organization. However, reports of network abnormalities during the early illness stage of psychosis are mixed. This study adopted a data-driven whole-brain approach to investigate functional connectivity and network architecture in a first-episode psychosis cohort relative to healthy controls and whether functional network properties changed abnormally over a 12-month period in first-episode psychosis. Resting-state functional connectivity was performed at two time points. At baseline, 29 first-episode psychosis individuals and 30 healthy controls were assessed, and at 12 months, 14 first-episode psychosis individuals and 20 healthy controls completed follow-up. Whole-brain resting-state functional connectivity networks were mapped for each individual and analyzed using graph theory to investigate whether network abnormalities associated with first-episode psychosis were evident and whether functional network properties changed abnormally over 12 months relative to controls. This study found no evidence of abnormal resting-state functional connectivity or topology in first-episode psychosis individuals relative to healthy controls at baseline or at 12-months follow-up. Furthermore, longitudinal changes in network properties over a 12-month period did not significantly differ between first-episode psychosis individuals and healthy control. Network measures did not significantly correlate with symptomatology, duration of illness or antipsychotic medication. This is the first study to show unaffected resting-state functional connectivity and topology in the early psychosis stage of illness. In light of previous literature, this suggests that a subgroup of first-episode psychosis individuals who have a neurotypical resting-state functional connectivity and topology may exist. Our preliminary longitudinal analyses indicate that there also does not appear to be deterioration in these network properties over a 12-month period. Future research in a larger sample is necessary to confirm our longitudinal findings.

A novel parallel pipeline structure of VP9 decoder

NASA Astrophysics Data System (ADS)

Qin, Huabiao; Chen, Wu; Yi, Sijun; Tan, Yunfei; Yi, Huan

2018-04-01

To improve the efficiency of VP9 decoder, a novel parallel pipeline structure of VP9 decoder is presented in this paper. According to the decoding workflow, VP9 decoder can be divided into sub-modules which include entropy decoding, inverse quantization, inverse transform, intra prediction, inter prediction, deblocking and pixel adaptive compensation. By analyzing the computing time of each module, hotspot modules are located and the causes of low efficiency of VP9 decoder can be found. Then, a novel pipeline decoder structure is designed by using mixed parallel decoding methods of data division and function division. The experimental results show that this structure can greatly improve the decoding efficiency of VP9.

Singer product apertures-A coded aperture system with a fast decoding algorithm

NASA Astrophysics Data System (ADS)

Byard, Kevin; Shutler, Paul M. E.

2017-06-01

A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.

Decoding negative affect personality trait from patterns of brain activation to threat stimuli.

PubMed

Fernandes, Orlando; Portugal, Liana C L; Alves, Rita de Cássia S; Arruda-Sanchez, Tiago; Rao, Anil; Volchan, Eliane; Pereira, Mirtes; Oliveira, Letícia; Mourao-Miranda, Janaina

2017-01-15

Pattern recognition analysis (PRA) applied to functional magnetic resonance imaging (fMRI) has been used to decode cognitive processes and identify possible biomarkers for mental illness. In the present study, we investigated whether the positive affect (PA) or negative affect (NA) personality traits could be decoded from patterns of brain activation in response to a human threat using a healthy sample. fMRI data from 34 volunteers (15 women) were acquired during a simple motor task while the volunteers viewed a set of threat stimuli that were directed either toward them or away from them and matched neutral pictures. For each participant, contrast images from a General Linear Model (GLM) between the threat versus neutral stimuli defined the spatial patterns used as input to the regression model. We applied a multiple kernel learning (MKL) regression combining information from different brain regions hierarchically in a whole brain model to decode the NA and PA from patterns of brain activation in response to threat stimuli. The MKL model was able to decode NA but not PA from the contrast images between threat stimuli directed away versus neutral with a significance above chance. The correlation and the mean squared error (MSE) between predicted and actual NA were 0.52 (p-value=0.01) and 24.43 (p-value=0.01), respectively. The MKL pattern regression model identified a network with 37 regions that contributed to the predictions. Some of the regions were related to perception (e.g., occipital and temporal regions) while others were related to emotional evaluation (e.g., caudate and prefrontal regions). These results suggest that there was an interaction between the individuals' NA and the brain response to the threat stimuli directed away, which enabled the MKL model to decode NA from the brain patterns. To our knowledge, this is the first evidence that PRA can be used to decode a personality trait from patterns of brain activation during emotional contexts. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Differences in the Predictors of Reading Comprehension in First Graders from Low Socio-Economic Status Families with Either Good or Poor Decoding Skills

PubMed Central

Gentaz, Edouard; Sprenger-Charolles, Liliane; Theurel, Anne

2015-01-01

Based on the assumption that good decoding skills constitute a bootstrapping mechanism for reading comprehension, the present study investigated the relative contribution of the former skill to the latter compared to that of three other predictors of reading comprehension (listening comprehension, vocabulary and phonemic awareness) in 392 French-speaking first graders from low SES families. This large sample was split into three groups according to their level of decoding skills assessed by pseudoword reading. Using a cutoff of 1 SD above or below the mean of the entire population, there were 63 good decoders, 267 average decoders and 62 poor decoders. 58% of the variance in reading comprehension was explained by our four predictors, with decoding skills proving to be the best predictor (12.1%, 7.3% for listening comprehension, 4.6% for vocabulary and 3.3% for phonemic awareness). Interaction between group versus decoding skills, listening comprehension and phonemic awareness accounted for significant additional variance (3.6%, 1.1% and 1.0%, respectively). The effects on reading comprehension of decoding skills and phonemic awareness were higher in poor and average decoders than in good decoders whereas listening comprehension accounted for more variance in good and average decoders than in poor decoders. Furthermore, the percentage of children with impaired reading comprehension skills was higher in the group of poor decoders (55%) than in the two other groups (average decoders: 7%; good decoders: 0%) and only 6 children (1.5%) had impaired reading comprehension skills with unimpaired decoding skills, listening comprehension or vocabulary. These results challenge the outcomes of studies on “poor comprehenders” by showing that, at least in first grade, poor reading comprehension is strongly linked to the level of decoding skills. PMID:25793519

Differences in the predictors of reading comprehension in first graders from low socio-economic status families with either good or poor decoding skills.

PubMed

Gentaz, Edouard; Sprenger-Charolles, Liliane; Theurel, Anne

2015-01-01

Based on the assumption that good decoding skills constitute a bootstrapping mechanism for reading comprehension, the present study investigated the relative contribution of the former skill to the latter compared to that of three other predictors of reading comprehension (listening comprehension, vocabulary and phonemic awareness) in 392 French-speaking first graders from low SES families. This large sample was split into three groups according to their level of decoding skills assessed by pseudoword reading. Using a cutoff of 1 SD above or below the mean of the entire population, there were 63 good decoders, 267 average decoders and 62 poor decoders. 58% of the variance in reading comprehension was explained by our four predictors, with decoding skills proving to be the best predictor (12.1%, 7.3% for listening comprehension, 4.6% for vocabulary and 3.3% for phonemic awareness). Interaction between group versus decoding skills, listening comprehension and phonemic awareness accounted for significant additional variance (3.6%, 1.1% and 1.0%, respectively). The effects on reading comprehension of decoding skills and phonemic awareness were higher in poor and average decoders than in good decoders whereas listening comprehension accounted for more variance in good and average decoders than in poor decoders. Furthermore, the percentage of children with impaired reading comprehension skills was higher in the group of poor decoders (55%) than in the two other groups (average decoders: 7%; good decoders: 0%) and only 6 children (1.5%) had impaired reading comprehension skills with unimpaired decoding skills, listening comprehension or vocabulary. These results challenge the outcomes of studies on "poor comprehenders" by showing that, at least in first grade, poor reading comprehension is strongly linked to the level of decoding skills.

Multifamily Group Psychoeducation and Cognitive Remediation for First-Episode Psychosis: A Randomized Controlled Trial

PubMed Central

2011-01-01

Background Multifamily group psychoeducation (MFG) has been shown to reduce relapse rates among individuals with first-episode psychosis. However, given the cognitive demands associated with participating in this intervention (e.g., learning and applying a structured problem-solving activity), the cognitive deficits that accompany psychotic disorders may limit the ability of certain individuals to benefit from this intervention. Thus, the goal of this study is to examine whether individuals with first-episode psychosis who participate simultaneously in MFG and cognitive remediation--an intervention shown to improve cognitive functioning among individuals with psychotic disorders--will be less likely to experience a relapse than individuals who participate in MFG alone. Methods/Design Forty individuals with first-episode psychosis and their caregiving relative will be recruited to participate in this study. Individuals with first-episode psychosis will be randomized to one of two conditions: (i) MFG with concurrent participation in cognitive remediation or (ii) MFG alone. The primary outcome for this study is relapse of psychotic symptoms. We will also examine secondary outcomes among both individuals with first-episode psychosis (i.e., social and vocational functioning, health-related quality of life, service utilization, independent living status, and cognitive functioning) and their caregiving relatives (i.e., caregiver burden, anxiety, and depression) Discussion Cognitive remediation offers the possibility of ameliorating a specific deficit (i.e., deficits in cognitive functioning) that often accompanies psychotic symptoms and may restrict the magnitude of the clinical benefits derived from MFG. Trial Registration ClinicalTrials (NCT): NCT01196286 PMID:21226941

Examining Duration of Binge Eating Episodes in Binge Eating Disorder

PubMed Central

Schreiber-Gregory, Deanna N.; Lavender, Jason M.; Engel, Scott G.; Wonderlich, Steve A.; Crosby, Ross D.; Peterson, Carol B.; Simonich, Heather; Crow, Scott; Durkin, Nora; Mitchell, James E.

2013-01-01

Objective The primary goal of this paper is to examine and clarify characteristics of binge eating in individuals with binge eating disorder (BED), particularly the duration of binge eating episodes, as well as potential differences between individuals with shorter compared to longer binge eating episodes. Method Two studies exploring binge eating characteristics in BED were conducted. Study 1 examined differences in clinical variables among individuals (N = 139) with BED who reported a short (< 2 hours) versus long (≥ 2 hours) average binge duration. Study 2 utilized an ecological momentary assessment (EMA) design to examine the duration and temporal pattern of binge eating episodes in the natural environment in a separate sample of nine women with BED. Results Participants in Study 1 who were classified as having long duration binge eating episodes displayed greater symptoms of depression and lower self-esteem, but did not differ on other measures of eating disorder symptoms, compared to those with short duration binge eating episodes. In Study 2, the average binge episode duration was approximately 42 minutes, and binge eating episodes were most common during the early afternoon and evening hours, as well as more common on weekdays versus weekends. Discussion Past research on binge episode characteristics, particularly duration, has been limited to studies of binge eating episodes in BN. This study contributes to the existing literature on characteristics of binge eating in BED. PMID:23881639

Architecture for time or transform domain decoding of reed-solomon codes

NASA Technical Reports Server (NTRS)

Hsu, In-Shek (Inventor); Truong, Trieu-Kie (Inventor); Deutsch, Leslie J. (Inventor); Shao, Howard M. (Inventor)

1989-01-01

Two pipeline (255,233) RS decoders, one a time domain decoder and the other a transform domain decoder, use the same first part to develop an errata locator polynomial .tau.(x), and an errata evaluator polynominal A(x). Both the time domain decoder and transform domain decoder have a modified GCD that uses an input multiplexer and an output demultiplexer to reduce the number of GCD cells required. The time domain decoder uses a Chien search and polynomial evaluator on the GCD outputs .tau.(x) and A(x), for the final decoding steps, while the transform domain decoder uses a transform error pattern algorithm operating on .tau.(x) and the initial syndrome computation S(x), followed by an inverse transform algorithm in sequence for the final decoding steps prior to adding the received RS coded message to produce a decoded output message.

Reliability of directional information in unsorted spikes and local field potentials recorded in human motor cortex.

PubMed

Perge, János A; Zhang, Shaomin; Malik, Wasim Q; Homer, Mark L; Cash, Sydney; Friehs, Gerhard; Eskandar, Emad N; Donoghue, John P; Hochberg, Leigh R

2014-08-01

Action potentials and local field potentials (LFPs) recorded in primary motor cortex contain information about the direction of movement. LFPs are assumed to be more robust to signal instabilities than action potentials, which makes LFPs, along with action potentials, a promising signal source for brain-computer interface applications. Still, relatively little research has directly compared the utility of LFPs to action potentials in decoding movement direction in human motor cortex. We conducted intracortical multi-electrode recordings in motor cortex of two persons (T2 and [S3]) as they performed a motor imagery task. We then compared the offline decoding performance of LFPs and spiking extracted from the same data recorded across a one-year period in each participant. We obtained offline prediction accuracy of movement direction and endpoint velocity in multiple LFP bands, with the best performance in the highest (200-400 Hz) LFP frequency band, presumably also containing low-pass filtered action potentials. Cross-frequency correlations of preferred directions and directional modulation index showed high similarity of directional information between action potential firing rates (spiking) and high frequency LFPs (70-400 Hz), and increasing disparity with lower frequency bands (0-7, 10-40 and 50-65 Hz). Spikes predicted the direction of intended movement more accurately than any individual LFP band, however combined decoding of all LFPs was statistically indistinguishable from spike-based performance. As the quality of spiking signals (i.e. signal amplitude) and the number of significantly modulated spiking units decreased, the offline decoding performance decreased 3.6[5.65]%/month (for T2 and [S3] respectively). The decrease in the number of significantly modulated LFP signals and their decoding accuracy followed a similar trend (2.4[2.85]%/month, ANCOVA, p = 0.27[0.03]). Field potentials provided comparable offline decoding performance to unsorted spikes. Thus, LFPs may provide useful external device control using current human intracortical recording technology. ( NCT00912041.).

FPGA implementation of low complexity LDPC iterative decoder

NASA Astrophysics Data System (ADS)

Verma, Shivani; Sharma, Sanjay

2016-07-01

Low-density parity-check (LDPC) codes, proposed by Gallager, emerged as a class of codes which can yield very good performance on the additive white Gaussian noise channel as well as on the binary symmetric channel. LDPC codes have gained lots of importance due to their capacity achieving property and excellent performance in the noisy channel. Belief propagation (BP) algorithm and its approximations, most notably min-sum, are popular iterative decoding algorithms used for LDPC and turbo codes. The trade-off between the hardware complexity and the decoding throughput is a critical factor in the implementation of the practical decoder. This article presents introduction to LDPC codes and its various decoding algorithms followed by realisation of LDPC decoder by using simplified message passing algorithm and partially parallel decoder architecture. Simplified message passing algorithm has been proposed for trade-off between low decoding complexity and decoder performance. It greatly reduces the routing and check node complexity of the decoder. Partially parallel decoder architecture possesses high speed and reduced complexity. The improved design of the decoder possesses a maximum symbol throughput of 92.95 Mbps and a maximum of 18 decoding iterations. The article presents implementation of 9216 bits, rate-1/2, (3, 6) LDPC decoder on Xilinx XC3D3400A device from Spartan-3A DSP family.

Effects of episodic future thinking on discounting: Personalized age-progressed pictures improve risky long-term health decisions.

PubMed

Kaplan, Brent A; Reed, Derek D; Jarmolowicz, David P

2016-03-01

Many everyday choices are associated with both delayed and probabilistic outcomes. The temporal attention hypothesis suggests that individuals' decision making can be improved by focusing attention on temporally distal events and implies that environmental manipulations that bring temporally distal outcomes into focus may alter an individual's degree of discounting. One such manipulation, episodic future thinking, has shown to lower discount rates; however, several questions remain about the applicability of episodic future thinking to domains other than delay discounting. The present experiments examine the effects of a modified episodic-future-thinking procedure in which participants viewed age-progressed computer-generated images of themselves and answered questions related to their future, on probability discounting in the context of both a delayed health gain and loss. Results indicate that modified episodic future thinking effectively altered individuals' degree of discounting in the predicted directions and demonstrate the applicability of episodic future thinking to decision making of socially significant outcomes. © 2015 Society for the Experimental Analysis of Behavior.

Mood-congruent bias and attention shifts in the different episodes of bipolar disorder.

PubMed

García-Blanco, Ana C; Perea, Manuel; Livianos, Lorenzo

2013-01-01

An "affective" go/no-go task was used in the different episodes of bipolar patients (euthymic, depressed, and manic) to examine (1) the presence of a mood-congruent attentional bias; and (2) the patients' ability to inhibit and invert associations between stimuli and responses through blocks. A group of healthy individuals served as controls. Results revealed a mood-congruent attentional bias: patients in the manic episode processed positive information faster, whereas those in the depressive episode processed negative information faster. In contrast, neither euthymic patients nor healthy individuals showed any mood-congruent biases. Furthermore, there was a shift cost across blocks for healthy individuals, but not for the patients. This may reflect a general impairment at selecting relevant information (e.g., in terms of disability to inhibit and invert associations between stimuli and responses) in bipolar participants, regardless of their episode. This state/trait dissociation in an episodic and chronic disorder such as bipolar disorder is important for its appropriate characterisation.

The design plan of a VLSI single chip (255, 223) Reed-Solomon decoder

NASA Technical Reports Server (NTRS)

Hsu, I. S.; Shao, H. M.; Deutsch, L. J.

1987-01-01

The very large-scale integration (VLSI) architecture of a single chip (255, 223) Reed-Solomon decoder for decoding both errors and erasures is described. A decoding failure detection capability is also included in this system so that the decoder will recognize a failure to decode instead of introducing additional errors. This could happen whenever the received word contains too many errors and erasures for the code to correct. The number of transistors needed to implement this decoder is estimated at about 75,000 if the delay for received message is not included. This is in contrast to the older transform decoding algorithm which needs about 100,000 transistors. However, the transform decoder is simpler in architecture than the time decoder. It is therefore possible to implement a single chip (255, 223) Reed-Solomon decoder with today's VLSI technology. An implementation strategy for the decoder system is presented. This represents the first step in a plan to take advantage of advanced coding techniques to realize a 2.0 dB coding gain for future space missions.

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao

1991-01-01

Various types of multistage decoding for multilevel block modulation codes, in which the decoding of a component code at each stage can be either soft decision or hard decision, maximum likelihood or bounded distance are discussed. Error performance for codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. It was found that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. It was found that the difference in performance between the suboptimum multi-stage soft decision maximum likelihood decoding of a modulation code and the single stage optimum decoding of the overall code is very small, only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

The serial message-passing schedule for LDPC decoding algorithms

NASA Astrophysics Data System (ADS)

Liu, Mingshan; Liu, Shanshan; Zhou, Yuan; Jiang, Xue

2015-12-01

The conventional message-passing schedule for LDPC decoding algorithms is the so-called flooding schedule. It has the disadvantage that the updated messages cannot be used until next iteration, thus reducing the convergence speed . In this case, the Layered Decoding algorithm (LBP) based on serial message-passing schedule is proposed. In this paper the decoding principle of LBP algorithm is briefly introduced, and then proposed its two improved algorithms, the grouped serial decoding algorithm (Grouped LBP) and the semi-serial decoding algorithm .They can improve LBP algorithm's decoding speed while maintaining a good decoding performance.

Mapping visual stimuli to perceptual decisions via sparse decoding of mesoscopic neural activity.

PubMed

Sajda, Paul

2010-01-01

In this talk I will describe our work investigating sparse decoding of neural activity, given a realistic mapping of the visual scene to neuronal spike trains generated by a model of primary visual cortex (V1). We use a linear decoder which imposes sparsity via an L1 norm. The decoder can be viewed as a decoding neuron (linear summation followed by a sigmoidal nonlinearity) in which there are relatively few non-zero synaptic weights. We find: (1) the best decoding performance is for a representation that is sparse in both space and time, (2) decoding of a temporal code results in better performance than a rate code and is also a better fit to the psychophysical data, (3) the number of neurons required for decoding increases monotonically as signal-to-noise in the stimulus decreases, with as little as 1% of the neurons required for decoding at the highest signal-to-noise levels, and (4) sparse decoding results in a more accurate decoding of the stimulus and is a better fit to psychophysical performance than a distributed decoding, for example one imposed by an L2 norm. We conclude that sparse coding is well-justified from a decoding perspective in that it results in a minimum number of neurons and maximum accuracy when sparse representations can be decoded from the neural dynamics.

Sport Engagement by Accelerometry under Field Conditions in German Adolescents: Results from GINIPlus.

PubMed

Smith, Maia; Berdel, Dietrich; Nowak, Dennis; Heinrich, Joachim; Schulz, Holger

2015-01-01

Sporting activities differ in their ability to promote moderate-to-vigorous physical activity (MVPA). To assess adolescents' engagement in sport under field conditions we used accelerometers to measure their MVPA levels during sport. We pay special attention to differences between team and individual sport and between common sports. Diary data and 7-day accelerometry from 1054 Germans ages 15-17 were combined to measure physical activity. 1373 diaried episodes of more than 40 common sports were identified from 626 participants and grouped into team and individual sport. We modeled the effect of team and individual sport, and described levels of MVPA and episodes of no MVPA for all recorded sports. German boys and girls averaged 43 (SD 21) and 37 (SD 24) minutes MVPA per day. Boys got 2.2 times as much MVPA per minute during team compared to individual sport (p<0.0001) but there was no significant difference for girls. Percent of time spent in MVPA during sport ranged from 6% for weight training to 74% for jogging, with individual sports averaging 10-30% and team sports 30-50%. 11% of sport episodes had no MVPA: half of episodes of cycling, 5% of jogging, and none for tennis or badminton. An episode of individual sport was 17 times more likely to have no MVPA than an episode of team sport (p<0.0001). Under field condition, adolescents were active for only a fraction of diaried sporting time. As measured by accelerometry, individual sport often produced no MVPA. Characteristics of the sport, such as team vs. individual, were more predictive of MVPA than were characteristics of the participant, such as background activity levels.

Sport Engagement by Accelerometry under Field Conditions in German Adolescents: Results from GINIPlus

PubMed Central

Smith, Maia; Berdel, Dietrich; Nowak, Dennis; Heinrich, Joachim; Schulz, Holger

2015-01-01

Introduction Sporting activities differ in their ability to promote moderate-to-vigorous physical activity (MVPA). To assess adolescents’ engagement in sport under field conditions we used accelerometers to measure their MVPA levels during sport. We pay special attention to differences between team and individual sport and between common sports. Methods Diary data and 7-day accelerometry from 1054 Germans ages 15–17 were combined to measure physical activity. 1373 diaried episodes of more than 40 common sports were identified from 626 participants and grouped into team and individual sport. We modeled the effect of team and individual sport, and described levels of MVPA and episodes of no MVPA for all recorded sports. Results German boys and girls averaged 43 (SD 21) and 37 (SD 24) minutes MVPA per day. Boys got 2.2 times as much MVPA per minute during team compared to individual sport (p<0.0001) but there was no significant difference for girls. Percent of time spent in MVPA during sport ranged from 6% for weight training to 74% for jogging, with individual sports averaging 10–30% and team sports 30–50%. 11% of sport episodes had no MVPA: half of episodes of cycling, 5% of jogging, and none for tennis or badminton. An episode of individual sport was 17 times more likely to have no MVPA than an episode of team sport (p<0.0001). Conclusion Under field condition, adolescents were active for only a fraction of diaried sporting time. As measured by accelerometry, individual sport often produced no MVPA. Characteristics of the sport, such as team vs. individual, were more predictive of MVPA than were characteristics of the participant, such as background activity levels. PMID:26291984

Image transmission system using adaptive joint source and channel decoding

NASA Astrophysics Data System (ADS)

Liu, Weiliang; Daut, David G.

2005-03-01

In this paper, an adaptive joint source and channel decoding method is designed to accelerate the convergence of the iterative log-dimain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec, which makes it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. Due to the error resilience modes, some bits are known to be either correct or in error. The positions of these bits are then fed back to the channel decoder. The log-likelihood ratios (LLR) of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. That is, for lower channel SNR, a larger factor is assigned, and vice versa. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the non-source controlled decoding method up to 5dB in terms of PSNR for various reconstructed images.

Variability in memory performance in aged healthy individuals: an fMRI study.

PubMed

Grön, Georg; Bittner, Daniel; Schmitz, Bernd; Wunderlich, Arthur P; Tomczak, Reinhard; Riepe, Matthias W

2003-01-01

Episodic memory performance varies in older subjects but underlying biological correlates remain as yet ambiguous. We investigated episodic memory in healthy older individuals (n=24; mean age: 64.4+/-6.7 years) without subjective memory complaints or objective cognitive impairment. Episodic memory was assessed with repetitive learning and recall of abstract geometric patterns during fMRI. Group analysis of brain activity during initial learning and maximum recall revealed hippocampal activation. Correlation analysis of brain activation and task performance demonstrated significant hippocampal activity during initial learning and maximum recall in a success-dependent manner. Neither age nor gray matter densities correlated with hippocampal activation. Functional imaging of episodic memory thus permits to detect objectively variability in hippocampal recruitment in healthy aged individuals without subjective memory complaints. Correlation analysis of brain activation and performance during an episodic memory task may be used to determine and follow-up hippocampal malfunction in a very sensitive manner.

Image barcodes

NASA Astrophysics Data System (ADS)

Damera-Venkata, Niranjan; Yen, Jonathan

2003-01-01

A Visually significant two-dimensional barcode (VSB) developed by Shaked et. al. is a method used to design an information carrying two-dimensional barcode, which has the appearance of a given graphical entity such as a company logo. The encoding and decoding of information using the VSB, uses a base image with very few graylevels (typically only two). This typically requires the image histogram to be bi-modal. For continuous-tone images such as digital photographs of individuals, the representation of tone or "shades of gray" is not only important to obtain a pleasing rendition of the face, but in most cases, the VSB renders these images unrecognizable due to its inability to represent true gray-tone variations. This paper extends the concept of a VSB to an image bar code (IBC). We enable the encoding and subsequent decoding of information embedded in the hardcopy version of continuous-tone base-images such as those acquired with a digital camera. The encoding-decoding process is modeled by robust data transmission through a noisy print-scan channel that is explicitly modeled. The IBC supports a high information capacity that differentiates it from common hardcopy watermarks. The reason for the improved image quality over the VSB is a joint encoding/halftoning strategy based on a modified version of block error diffusion. Encoder stability, image quality vs. information capacity tradeoffs and decoding issues with and without explicit knowledge of the base-image are discussed.

Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.

PubMed

Li, Yuanning; Richardson, Robert Mark; Ghuman, Avniel Singh

2017-11-15

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitative evaluation of muscle synergy models: a single-trial task decoding approach

PubMed Central

Delis, Ioannis; Berret, Bastien; Pozzo, Thierry; Panzeri, Stefano

2013-01-01

Muscle synergies, i.e., invariant coordinated activations of groups of muscles, have been proposed as building blocks that the central nervous system (CNS) uses to construct the patterns of muscle activity utilized for executing movements. Several efficient dimensionality reduction algorithms that extract putative synergies from electromyographic (EMG) signals have been developed. Typically, the quality of synergy decompositions is assessed by computing the Variance Accounted For (VAF). Yet, little is known about the extent to which the combination of those synergies encodes task-discriminating variations of muscle activity in individual trials. To address this question, here we conceive and develop a novel computational framework to evaluate muscle synergy decompositions in task space. Unlike previous methods considering the total variance of muscle patterns (VAF based metrics), our approach focuses on variance discriminating execution of different tasks. The procedure is based on single-trial task decoding from muscle synergy activation features. The task decoding based metric evaluates quantitatively the mapping between synergy recruitment and task identification and automatically determines the minimal number of synergies that captures all the task-discriminating variability in the synergy activations. In this paper, we first validate the method on plausibly simulated EMG datasets. We then show that it can be applied to different types of muscle synergy decomposition and illustrate its applicability to real data by using it for the analysis of EMG recordings during an arm pointing task. We find that time-varying and synchronous synergies with similar number of parameters are equally efficient in task decoding, suggesting that in this experimental paradigm they are equally valid representations of muscle synergies. Overall, these findings stress the effectiveness of the decoding metric in systematically assessing muscle synergy decompositions in task space. PMID:23471195

Emergence of representations through repeated training on pronouncing novel letter combinations leads to efficient reading.

PubMed

Takashima, Atsuko; Hulzink, Iris; Wagensveld, Barbara; Verhoeven, Ludo

2016-08-01

Printed text can be decoded by utilizing different processing routes depending on the familiarity of the script. A predominant use of word-level decoding strategies can be expected in the case of a familiar script, and an almost exclusive use of letter-level decoding strategies for unfamiliar scripts. Behavioural studies have revealed that frequently occurring words are read more efficiently, suggesting that these words are read in a more holistic way at the word-level, than infrequent and unfamiliar words. To test whether repeated exposure to specific letter combinations leads to holistic reading, we monitored both behavioural and neural responses during novel script decoding and examined changes related to repeated exposure. We trained a group of Dutch university students to decode pseudowords written in an unfamiliar script, i.e., Korean Hangul characters. We compared behavioural and neural responses to pronouncing trained versus untrained two-character pseudowords (equivalent to two-syllable pseudowords). We tested once shortly after the initial training and again after a four days' delay that included another training session. We found that trained pseudowords were pronounced faster and more accurately than novel combinations of radicals (equivalent to letters). Imaging data revealed that pronunciation of trained pseudowords engaged the posterior temporo-parietal region, and engagement of this network was predictive of reading efficiency a month later. The results imply that repeated exposure to specific combinations of graphemes can lead to emergence of holistic representations that result in efficient reading. Furthermore, inter-individual differences revealed that good learners retained efficiency more than bad learners one month later. Copyright © 2016 Elsevier Ltd. All rights reserved.

Teleradiology network system and computer-aided diagnosis workstation using the web medical image conference system with a new information security solution

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Ohmatsu, Hironobu; Kaneko, Masahiro; Kakinuma, Ryutaru; Moriyama, Noriyuki

2011-03-01

We have developed the teleradiology network system with a new information security solution that provided with web medical image conference system. In the teleradiology network system, the security of information network is very important subjects. We are studying the secret sharing scheme as a method safely to store or to transmit the confidential medical information used with the teleradiology network system. The confidential medical information is exposed to the risk of the damage and intercept. Secret sharing scheme is a method of dividing the confidential medical information into two or more tallies. Individual medical information cannot be decoded by using one tally at all. Our method has the function of RAID. With RAID technology, if there is a failure in a single tally, there is redundant data already copied to other tally. Confidential information is preserved at an individual Data Center connected through internet because individual medical information cannot be decoded by using one tally at all. Therefore, even if one of the Data Centers is struck and information is damaged, the confidential medical information can be decoded by using the tallies preserved at the data center to which it escapes damage. We can safely share the screen of workstation to which the medical image of Data Center is displayed from two or more web conference terminals at the same time. Moreover, Real time biometric face authentication system is connected with Data Center. Real time biometric face authentication system analyzes the feature of the face image of which it takes a picture in 20 seconds with the camera and defends the safety of the medical information. We propose a new information transmission method and a new information storage method with a new information security solution.

Neighborhood income and major depressive disorder in a large Dutch population: results from the LifeLines Cohort study.

PubMed

Klijs, Bart; Kibele, Eva U B; Ellwardt, Lea; Zuidersma, Marij; Stolk, Ronald P; Wittek, Rafael P M; Mendes de Leon, Carlos M; Smidt, Nynke

2016-08-11

Previous studies are inconclusive on whether poor socioeconomic conditions in the neighborhood are associated with major depressive disorder. Furthermore, conceptual models that relate neighborhood conditions to depressive disorder have not been evaluated using empirical data. In this study, we investigated whether neighborhood income is associated with major depressive episodes. We evaluated three conceptual models. Conceptual model 1: The association between neighborhood income and major depressive episodes is explained by diseases, lifestyle factors, stress and social participation. Conceptual model 2: A low individual income relative to the mean income in the neighborhood is associated with major depressive episodes. Conceptual model 3: A high income of the neighborhood buffers the effect of a low individual income on major depressive disorder. We used adult baseline data from the LifeLines Cohort Study (N = 71,058) linked with data on the participants' neighborhoods from Statistics Netherlands. The current presence of a major depressive episode was assessed using the MINI neuropsychiatric interview. The association between neighborhood income and major depressive episodes was assessed using a mixed effect logistic regression model adjusted for age, sex, marital status, education and individual (equalized) income. This regression model was sequentially adjusted for lifestyle factors, chronic diseases, stress, and social participation to evaluate conceptual model 1. To evaluate conceptual models 2 and 3, an interaction term for neighborhood income*individual income was included. Multivariate regression analysis showed that a low neighborhood income is associated with major depressive episodes (OR (95 % CI): 0.82 (0.73;0.93)). Adjustment for diseases, lifestyle factors, stress, and social participation attenuated this association (ORs (95 % CI): 0.90 (0.79;1.01)). Low individual income was also associated with major depressive episodes (OR (95 % CI): 0.72 (0.68;0.76)). The interaction of individual income*neighborhood income on major depressive episodes was not significant (p = 0.173). Living in a low-income neighborhood is associated with major depressive episodes. Our results suggest that this association is partly explained by chronic diseases, lifestyle factors, stress and poor social participation, and thereby partly confirm conceptual model 1. Our results do not support conceptual model 2 and 3.

A long constraint length VLSI Viterbi decoder for the DSN

NASA Technical Reports Server (NTRS)

Statman, J. I.; Zimmerman, G.; Pollara, F.; Collins, O.

1988-01-01

A Viterbi decoder, capable of decoding convolutional codes with constraint lengths up to 15, is under development for the Deep Space Network (DSN). The objective is to complete a prototype of this decoder by late 1990, and demonstrate its performance using the (15, 1/4) encoder in Galileo. The decoder is expected to provide 1 to 2 dB improvement in bit SNR, compared to the present (7, 1/2) code and existing Maximum Likelihood Convolutional Decoder (MCD). The decoder will be fully programmable for any code up to constraint length 15, and code rate 1/2 to 1/6. The decoder architecture and top-level design are described.

Decoding small surface codes with feedforward neural networks

NASA Astrophysics Data System (ADS)

Varsamopoulos, Savvas; Criger, Ben; Bertels, Koen

2018-01-01

Surface codes reach high error thresholds when decoded with known algorithms, but the decoding time will likely exceed the available time budget, especially for near-term implementations. To decrease the decoding time, we reduce the decoding problem to a classification problem that a feedforward neural network can solve. We investigate quantum error correction and fault tolerance at small code distances using neural network-based decoders, demonstrating that the neural network can generalize to inputs that were not provided during training and that they can reach similar or better decoding performance compared to previous algorithms. We conclude by discussing the time required by a feedforward neural network decoder in hardware.

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Adaptive decoding of convolutional codes

NASA Astrophysics Data System (ADS)

Hueske, K.; Geldmacher, J.; Götze, J.

2007-06-01

Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.

A method for the automated long-term monitoring of three-spined stickleback Gasterosteus aculeatus shoal dynamics.

PubMed

Kleinhappel, T K; Al-Zoubi, A; Al-Diri, B; Burman, O; Dickinson, P; John, L; Wilkinson, A; Pike, T W

2014-04-01

This paper describes and evaluates a flexible, non-invasive tagging system for the automated identification and long-term monitoring of individual three-spined sticklebacks Gasterosteus aculeatus. The system is based on barcoded tags, which can be reliably and robustly detected and decoded to provide information on an individual's identity and location. Because large numbers of fish can be individually tagged, it can be used to monitor individual- and group-level dynamics within fish shoals. © 2014 The Fisheries Society of the British Isles.

Individual Differences in Reprocessing of Text.

ERIC Educational Resources Information Center

Haenggi, Dieter; Perfetti, Charles A.

1992-01-01

Decoding, working memory, and domain-specific prior knowledge were studied as predictors of comprehension for 48 university undergraduate students after rewriting notes, rereading notes, or rereading a text. Working memory was most important for comprehension of text-implicit information, whereas knowledge was relatively more important for…

Television News Without Pictures?

ERIC Educational Resources Information Center

Graber, Doris A.

1987-01-01

Describes "gestalt" coding procedures that concentrate on the meanings conveyed by audio-visual messages rather than on coding individual pictorial elements shown in a news story. Discusses the totality of meaning that results from the interaction of verbal and visual story elements, external settings, and the decoding proclivities of…

Name that tune: decoding music from the listening brain.

PubMed

Schaefer, Rebecca S; Farquhar, Jason; Blokland, Yvonne; Sadakata, Makiko; Desain, Peter

2011-05-15

In the current study we use electroencephalography (EEG) to detect heard music from the brain signal, hypothesizing that the time structure in music makes it especially suitable for decoding perception from EEG signals. While excluding music with vocals, we classified the perception of seven different musical fragments of about three seconds, both individually and cross-participants, using only time domain information (the event-related potential, ERP). The best individual results are 70% correct in a seven-class problem while using single trials, and when using multiple trials we achieve 100% correct after six presentations of the stimulus. When classifying across participants, a maximum rate of 53% was reached, supporting a general representation of each musical fragment over participants. While for some music stimuli the amplitude envelope correlated well with the ERP, this was not true for all stimuli. Aspects of the stimulus that may contribute to the differences between the EEG responses to the pieces of music are discussed. Copyright © 2010 Elsevier Inc. All rights reserved.

For love or money? What motivates people to know the minds of others?

PubMed

Harkness, Kate L; Jacobson, Jill A; Sinclair, Brooke; Chan, Emilie; Sabbagh, Mark A

2012-01-01

Mood affects social cognition and "theory of mind", such that people in a persistent negative mood (i.e., dysphoria) have enhanced abilities at making subtle judgements about others' mental states. Theorists have argued that this hypersensitivity to subtle social cues may have adaptive significance in terms of solving interpersonal problems and/or minimising social risk. We tested whether increasing the social salience of a theory of mind task would preferentially increase dyspshoric individuals' performance on the task. Forty-four dysphoric and 51 non-dysphoric undergraduate women participated in a theory of mind decoding task following one of three motivational manipulations: (i) social motivation (ii) monetary motivation, or (iii) no motivation. Social motivation was associated with the greatest accuracy of mental state decoding for the dysphoric group, whereas the non-dysphoric group showed the highest accuracy in the monetary motivation condition. These results suggest that dysphoric individuals may be especially, and preferentially, motivated to understand the mental states of others.

Fault tolerance in space-based digital signal processing and switching systems: Protecting up-link processing resources, demultiplexer, demodulator, and decoder

NASA Technical Reports Server (NTRS)

Redinbo, Robert

1994-01-01

Fault tolerance features in the first three major subsystems appearing in the next generation of communications satellites are described. These satellites will contain extensive but efficient high-speed processing and switching capabilities to support the low signal strengths associated with very small aperture terminals. The terminals' numerous data channels are combined through frequency division multiplexing (FDM) on the up-links and are protected individually by forward error-correcting (FEC) binary convolutional codes. The front-end processing resources, demultiplexer, demodulators, and FEC decoders extract all data channels which are then switched individually, multiplexed, and remodulated before retransmission to earth terminals through narrow beam spot antennas. Algorithm based fault tolerance (ABFT) techniques, which relate real number parity values with data flows and operations, are used to protect the data processing operations. The additional checking features utilize resources that can be substituted for normal processing elements when resource reconfiguration is required to replace a failed unit.

State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements

PubMed Central

Mollazadeh, Mohsen; Davidson, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

2013-01-01

The performance of brain-machine interfaces (BMIs) that continuously control upper limb neuroprostheses may benefit from distinguishing periods of posture and movement so as to prevent inappropriate movement of the prosthesis. Few studies, however, have investigated how decoding behavioral states and detecting the transitions between posture and movement could be used autonomously to trigger a kinematic decoder. We recorded simultaneous neuronal ensemble and local field potential (LFP) activity from microelectrode arrays in primary motor cortex (M1) and dorsal (PMd) and ventral (PMv) premotor areas of two male rhesus monkeys performing a center-out reach-and-grasp task, while upper limb kinematics were tracked with a motion capture system with markers on the dorsal aspect of the forearm, hand, and fingers. A state decoder was trained to distinguish four behavioral states (baseline, reaction, movement, hold), while a kinematic decoder was trained to continuously decode hand end point position and 18 joint angles of the wrist and fingers. LFP amplitude most accurately predicted transition into the reaction (62%) and movement (73%) states, while spikes most accurately decoded arm, hand, and finger kinematics during movement. Using an LFP-based state decoder to trigger a spike-based kinematic decoder [r = 0.72, root mean squared error (RMSE) = 0.15] significantly improved decoding of reach-to-grasp movements from baseline to final hold, compared with either a spike-based state decoder combined with a spike-based kinematic decoder (r = 0.70, RMSE = 0.17) or a spike-based kinematic decoder alone (r = 0.67, RMSE = 0.17). Combining LFP-based state decoding with spike-based kinematic decoding may be a valuable step toward the realization of BMI control of a multifingered neuroprosthesis performing dexterous manipulation. PMID:23536714

Effects of tutoring in phonological and early reading skills on students at risk for reading disabilities.

PubMed

Vadasy, P F; Jenkins, J R; Pool, K

2000-01-01

This study examined the effectiveness of nonprofessional tutors in a phonologically based reading treatment similar to those in which successful reading outcomes have been demonstrated. Participants were 23 first graders at risk for learning disability who received intensive one-to-one tutoring from noncertified tutors for 30 minutes, 4 days a week, for one school year. Tutoring included instruction in phonological skills, letter-sound correspondence, explicit decoding, rime analysis, writing, spelling, and reading phonetically controlled text. At year end, tutored students significantly outperformed untutored control students on measures of reading, spelling, and decoding. Effect sizes ranged from .42 to 1.24. Treatment effects diminished at follow-up at the end of second grade, although tutored students continued to significantly outperform untutored students in decoding and spelling. Findings suggest that phonologically based reading instruction for first graders at risk for learning disability can be delivered by nonteacher tutors. Our discussion addresses the character of reading outcomes associated with tutoring, individual differences in response to treatment, and the infrastructure required for nonprofessional tutoring programs.

The Contribution of Phonological Awareness to Reading Fluency and Its Individual Sub-skills in Readers Aged 9- to 12-years

PubMed Central

Elhassan, Zena; Crewther, Sheila G.; Bavin, Edith L.

2017-01-01

Research examining phonological awareness (PA) contributions to reading in established readers of different skill levels is limited. The current study examined the contribution of PA to phonological decoding, visual word recognition, reading rate, and reading comprehension in 124 fourth to sixth grade children (aged 9–12 years). On the basis of scores on the FastaReada measure of reading fluency participants were allocated to one of three reading ability categories: dysfluent (n = 47), moderate (n = 38) and fluent (n = 39). For the dysfluent group, PA contributed significantly to all reading measures except rate, but in the moderate group only to phonological decoding. PA did not influence performances on any of the reading measures examined for the fluent reader group. The results support the notion that fluency is characterized by a shift from conscious decoding to rapid and accurate visual recognition of words. Although PA may be influential in reading development, the results of the current study show that it is not sufficient for fluent reading. PMID:28443048

The Contribution of Phonological Awareness to Reading Fluency and Its Individual Sub-skills in Readers Aged 9- to 12-years.

PubMed

Elhassan, Zena; Crewther, Sheila G; Bavin, Edith L

2017-01-01

Research examining phonological awareness (PA) contributions to reading in established readers of different skill levels is limited. The current study examined the contribution of PA to phonological decoding, visual word recognition, reading rate, and reading comprehension in 124 fourth to sixth grade children (aged 9-12 years). On the basis of scores on the FastaReada measure of reading fluency participants were allocated to one of three reading ability categories: dysfluent ( n = 47), moderate ( n = 38) and fluent ( n = 39). For the dysfluent group, PA contributed significantly to all reading measures except rate, but in the moderate group only to phonological decoding. PA did not influence performances on any of the reading measures examined for the fluent reader group. The results support the notion that fluency is characterized by a shift from conscious decoding to rapid and accurate visual recognition of words. Although PA may be influential in reading development, the results of the current study show that it is not sufficient for fluent reading.

Cognitive reactivity, self-depressed associations, and the recurrence of depression.

PubMed

Elgersma, Hermien J; de Jong, Peter J; van Rijsbergen, Gerard D; Kok, Gemma D; Burger, Huibert; van der Does, Willem; Penninx, Brenda W J H; Bockting, Claudi L H

2015-09-01

Mixed evidence exists regarding the role of cognitive reactivity (CR; cognitive responsivity to a negative mood) as a risk factor for recurrences of depression. One explanation for the mixed evidence may lie in the number of previous depressive episodes. Heightened CR may be especially relevant as a risk factor for the development of multiple depressive episodes and less so for a single depressive episode. In addition, it is theoretically plausible but not yet tested that the relationship between CR and number of episodes is moderated by the strength of automatic depression-related self-associations. To investigate (i) the strength of CR in remitted depressed individuals with a history of a single vs. multiple episodes, and (ii) the potentially moderating role of automatic negative self-associations in the relationship between the number of episodes and CR. Cross-sectional analysis of data obtained in a cohort study (Study 1) and during baseline assessments in two clinical trials (Study 2). Study 1 used data from the Netherlands Study of Depression and Anxiety (NESDA) and compared never-depressed participants (n=901) with remitted participants with either a single (n=336) or at least 2 previous episodes (n=273). Study 2 included only remitted participants with at least two previous episodes (n=273). The Leiden Index of Depression Sensitivity Revised (LEIDS-R) was used to index CR and an Implicit Association Test (IAT) to measure implicit self-associations. In Study 1, remitted depressed participants with multiple episodes had significantly higher CR than those with a single or no previous episode. The remitted individuals with multiple episodes of Study 2 had even higher CR scores than those of Study 1. Within the group of individuals with multiple episodes, CR was not heightened as a function of the number of episodes, even if individual differences in automatic negative self-associations were taken into account. The study employed a cross-sectional design, which precludes a firm conclusion with regard to the direction of this relationship. The findings are consistent with the view that high CR puts people at risk for recurrent depression and is less relevant for the development of an incidental depressive episode. This suggests that CR is an important target for interventions that aim to prevent the recurrence of depression. Copyright © 2015 Elsevier B.V. All rights reserved.

Bayesian decoding using unsorted spikes in the rat hippocampus

PubMed Central

Layton, Stuart P.; Chen, Zhe; Wilson, Matthew A.

2013-01-01

A fundamental task in neuroscience is to understand how neural ensembles represent information. Population decoding is a useful tool to extract information from neuronal populations based on the ensemble spiking activity. We propose a novel Bayesian decoding paradigm to decode unsorted spikes in the rat hippocampus. Our approach uses a direct mapping between spike waveform features and covariates of interest and avoids accumulation of spike sorting errors. Our decoding paradigm is nonparametric, encoding model-free for representing stimuli, and extracts information from all available spikes and their waveform features. We apply the proposed Bayesian decoding algorithm to a position reconstruction task for freely behaving rats based on tetrode recordings of rat hippocampal neuronal activity. Our detailed decoding analyses demonstrate that our approach is efficient and better utilizes the available information in the nonsortable hash than the standard sorting-based decoding algorithm. Our approach can be adapted to an online encoding/decoding framework for applications that require real-time decoding, such as brain-machine interfaces. PMID:24089403

Achievable Information Rates for Coded Modulation With Hard Decision Decoding for Coherent Fiber-Optic Systems

NASA Astrophysics Data System (ADS)

Sheikh, Alireza; Amat, Alexandre Graell i.; Liva, Gianluigi

2017-12-01

We analyze the achievable information rates (AIRs) for coded modulation schemes with QAM constellations with both bit-wise and symbol-wise decoders, corresponding to the case where a binary code is used in combination with a higher-order modulation using the bit-interleaved coded modulation (BICM) paradigm and to the case where a nonbinary code over a field matched to the constellation size is used, respectively. In particular, we consider hard decision decoding, which is the preferable option for fiber-optic communication systems where decoding complexity is a concern. Recently, Liga \\emph{et al.} analyzed the AIRs for bit-wise and symbol-wise decoders considering what the authors called \\emph{hard decision decoder} which, however, exploits \\emph{soft information} of the transition probabilities of discrete-input discrete-output channel resulting from the hard detection. As such, the complexity of the decoder is essentially the same as the complexity of a soft decision decoder. In this paper, we analyze instead the AIRs for the standard hard decision decoder, commonly used in practice, where the decoding is based on the Hamming distance metric. We show that if standard hard decision decoding is used, bit-wise decoders yield significantly higher AIRs than symbol-wise decoders. As a result, contrary to the conclusion by Liga \\emph{et al.}, binary decoders together with the BICM paradigm are preferable for spectrally-efficient fiber-optic systems. We also design binary and nonbinary staircase codes and show that, in agreement with the AIRs, binary codes yield better performance.

Using Hierarchical Linear Modeling to Examine How Individual SLPs Differentially Contribute to Children's Language and Literacy Gains in Public Schools.

PubMed

Farquharson, Kelly; Tambyraja, Sherine R; Logan, Jessica; Justice, Laura M; Schmitt, Mary Beth

2015-08-01

The purpose of this study was twofold: (a) to determine the unique contributions in children's language and literacy gains, over 1 academic year, that are attributable to the individual speech-language pathologist (SLP) and (b) to explore possible child- and SLP-level factors that may further explain SLPs' contributions to children's language and literacy gains. Participants were 288 kindergarten and 1st-grade children with language impairment who were currently receiving school-based language intervention from SLPs. Using hierarchical linear modeling, we partitioned the variance in children's gains in language (i.e., grammar, vocabulary) and literacy (i.e., word decoding) that could be attributed to their individual SLP. Results revealed a significant contribution of individual SLPs to children's gains in grammar, vocabulary, and word decoding. Children's fall language scores and grade were significant predictors of SLPs' contributions, although no SLP-level predictors were significant. The present study makes a first step toward incorporating implementation science and suggests that, for children receiving school-based language intervention, variance in child language and literacy gains in an academic year is at least partially attributable to SLPs. Continued work in this area should examine the possible SLP-level characteristics that may further explicate the relative contributions of SLPs.

Mental state decoding impairment in major depression and borderline personality disorder: meta-analysis.

PubMed

Richman, Mara J; Unoka, Zsolt

2015-12-01

Patients with major depression and borderline personality disorder are characterised by a distorted perception of other people's intentions. Deficits in mental state decoding are thought to be the underlying cause of this clinical feature. To examine, using meta-analysis, whether mental state decoding abilities in patients with major depression and borderline personality disorder differ from those of healthy controls. A systematic review of 13 cross-sectional studies comparing Reading in the Mind of the Eyes Test (RMET) accuracy performance of patients with major depression or borderline personality disorder and healthy age-matched controls (n = 976). Valence scores, where reported, were also assessed. Large significant deficits were seen for global RMET performance in patients with major depression (d = -0.751). The positive RMET valence scores of patients with depression were significantly worse; patients with borderline personality disorder had worse neutral scores. Both groups were worse than controls. Moderator analysis revealed that individuals with comorbid borderline personality disorder and major depression did better than those with borderline personality disorder alone on accuracy. Those with comorbid borderline personality disorder and any cluster B or C personality disorder did worse than borderline personality disorder alone. Individuals with both borderline personality disorder and major depression performed better then those with borderline personality disorder without major depression for positive valence. These findings highlight the relevance of RMET performance in patients with borderline personality disorder and major depression, and the importance of considering comorbidity in future analysis. © The Royal College of Psychiatrists 2015.

Aspects of Theory of Mind that attenuate the relationship between persecutory delusions and social functioning in schizophrenia spectrum disorders.

PubMed

Phalen, Peter L; Dimaggio, Giancarlo; Popolo, Raffaele; Lysaker, Paul H

2017-09-01

Despite the apparent relevance of persecutory delusions to social relationships, evidence linking these beliefs to social functioning has been inconsistent. In this study, we examined the hypothesis that theory of mind moderates the relationship between persecutory delusions and social functioning. 88 adults with schizophrenia or schizoaffective disorder were assessed concurrently for social functioning, severity of persecutory delusions, and two components of theory of mind: mental state decoding and mental state reasoning. Mental state decoding was assessed using the Eyes Test, mental state reasoning using the Hinting Task, and social functioning assessed with the Social Functioning Scale. Moderation effects were evaluated using linear models and the Johnson-Neyman procedure. Mental state reasoning was found to moderate the relationship between persecutory delusions and social functioning, controlling for overall psychopathology. For participants with reasoning scores in the bottom 78th percentile, persecutory delusions showed a significant negative relationship with social functioning. However, for those participants with mental state reasoning scores in the top 22nd percentile, more severe persecutory delusions were not significantly associated with worse social functioning. Mental state decoding was not a statistically significant moderator. Generalizability is limited as participants were generally men in later phases of illness. Mental state reasoning abilities may buffer the impact of persecutory delusions on social functioning, possibly by helping individuals avoid applying global beliefs of persecution to specific individuals or by allowing for the correction of paranoid inferences. Published by Elsevier Ltd.

47 CFR 11.33 - EAS Decoder.

Code of Federal Regulations, 2010 CFR

2010-10-01

... decoders manufactured after August 1, 2003 must provide a means to permit the selective display and logging... upgrade their decoders on an optional basis to include a selective display and logging capability for EAS... decoders after February 1, 2004 must install decoders that provide a means to permit the selective display...

A real-time MPEG software decoder using a portable message-passing library

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kwong, Man Kam; Tang, P.T. Peter; Lin, Biquan

1995-12-31

We present a real-time MPEG software decoder that uses message-passing libraries such as MPL, p4 and MPI. The parallel MPEG decoder currently runs on the IBM SP system but can be easil ported to other parallel machines. This paper discusses our parallel MPEG decoding algorithm as well as the parallel programming environment under which it uses. Several technical issues are discussed, including balancing of decoding speed, memory limitation, 1/0 capacities, and optimization of MPEG decoding components. This project shows that a real-time portable software MPEG decoder is feasible in a general-purpose parallel machine.

NP-hardness of decoding quantum error-correction codes

NASA Astrophysics Data System (ADS)

Hsieh, Min-Hsiu; Le Gall, François

2011-05-01

Although the theory of quantum error correction is intimately related to classical coding theory and, in particular, one can construct quantum error-correction codes (QECCs) from classical codes with the dual-containing property, this does not necessarily imply that the computational complexity of decoding QECCs is the same as their classical counterparts. Instead, decoding QECCs can be very much different from decoding classical codes due to the degeneracy property. Intuitively, one expects degeneracy would simplify the decoding since two different errors might not and need not be distinguished in order to correct them. However, we show that general quantum decoding problem is NP-hard regardless of the quantum codes being degenerate or nondegenerate. This finding implies that no considerably fast decoding algorithm exists for the general quantum decoding problems and suggests the existence of a quantum cryptosystem based on the hardness of decoding QECCs.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; The Map and Related Decoding Algirithms

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc

1998-01-01

In a coded communication system with equiprobable signaling, MLD minimizes the word error probability and delivers the most likely codeword associated with the corresponding received sequence. This decoding has two drawbacks. First, minimization of the word error probability is not equivalent to minimization of the bit error probability. Therefore, MLD becomes suboptimum with respect to the bit error probability. Second, MLD delivers a hard-decision estimate of the received sequence, so that information is lost between the input and output of the ML decoder. This information is important in coded schemes where the decoded sequence is further processed, such as concatenated coding schemes, multi-stage and iterative decoding schemes. In this chapter, we first present a decoding algorithm which both minimizes bit error probability, and provides the corresponding soft information at the output of the decoder. This algorithm is referred to as the MAP (maximum aposteriori probability) decoding algorithm.

Linking Cognition and Literacy in Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Carnahan, Christina R.; Williamson, Pamela S.; Christman, Jennifer

2011-01-01

Literacy skills, especially silent reading comprehension, serve as the foundation for learning, independence, and quality of life for all individuals. It is well documented that students on the autism spectrum have difficulties with reading comprehension even though they demonstrate adequate decoding skills. Unfortunately, communication…

Force spectroscopy of biomolecular folding and binding: theory meets experiment

NASA Astrophysics Data System (ADS)

Dudko, Olga

2015-03-01

Conformational transitions in biological macromolecules usually serve as the mechanism that brings biomolecules into their working shape and enables their biological function. Single-molecule force spectroscopy probes conformational transitions by applying force to individual macromolecules and recording their response, or ``mechanical fingerprints,'' in the form of force-extension curves. However, how can we decode these fingerprints so that they reveal the kinetic barriers and the associated timescales of a biological process? I will present an analytical theory of the mechanical fingerprints of macromolecules. The theory is suitable for decoding such fingerprints to extract the barriers and timescales. The application of the theory will be illustrated through recent studies on protein-DNA interactions and the receptor-ligand complexes involved in blood clot formation.

Decoding emotional valence from electroencephalographic rhythmic activity.

PubMed

Celikkanat, Hande; Moriya, Hiroki; Ogawa, Takeshi; Kauppi, Jukka-Pekka; Kawanabe, Motoaki; Hyvarinen, Aapo

2017-07-01

We attempt to decode emotional valence from electroencephalographic rhythmic activity in a naturalistic setting. We employ a data-driven method developed in a previous study, Spectral Linear Discriminant Analysis, to discover the relationships between the classification task and independent neuronal sources, optimally utilizing multiple frequency bands. A detailed investigation of the classifier provides insight into the neuronal sources related with emotional valence, and the individual differences of the subjects in processing emotions. Our findings show: (1) sources whose locations are similar across subjects are consistently involved in emotional responses, with the involvement of parietal sources being especially significant, and (2) even though the locations of the involved neuronal sources are consistent, subjects can display highly varying degrees of valence-related EEG activity in the sources.

On the importance of listening comprehension

PubMed Central

Hogan, Tiffany P.; Adlof, Suzanne M.; Alonzo, Crystle

2015-01-01

The simple view of reading highlights the importance of two primary components which account for individual differences in reading comprehension across development: word recognition (i.e., decoding) and listening comprehension. While assessments and interventions for decoding have been the focus of pedagogy in the past several decades, the importance of listening comprehension has received less attention. This paper reviews evidence showing that listening comprehension becomes the dominating influence on reading comprehension starting even in the elementary grades. It also highlights a growing number of children who fail to develop adequate reading comprehension skills, primarily due to deficient listening comprehension skills: poor comprehenders. Finally it discusses key language influences on listening comprehension for consideration during assessment and treatment of reading disabilities. PMID:24833426

On the importance of listening comprehension.

PubMed

Hogan, Tiffany P; Adlof, Suzanne M; Alonzo, Crystle N

2014-06-01

The simple view of reading highlights the importance of two primary components which account for individual differences in reading comprehension across development: word recognition (i.e., decoding) and listening comprehension. While assessments and interventions for decoding have been the focus of pedagogy in the past several decades, the importance of listening comprehension has received less attention. This paper reviews evidence showing that listening comprehension becomes the dominating influence on reading comprehension starting even in the elementary grades. It also highlights a growing number of children who fail to develop adequate reading comprehension skills, primarily due to deficient listening comprehension skills (i.e., poor comprehenders). Finally we discuss key language influences on listening comprehension for consideration during assessment and treatment of reading disabilities.

Expressive body movement responses to music are coherent, consistent, and low dimensional.

PubMed

Amelynck, Denis; Maes, Pieter-Jan; Martens, Jean Pierre; Leman, Marc

2014-12-01

Embodied music cognition stresses the role of the human body as mediator for the encoding and decoding of musical expression. In this paper, we set up a low dimensional functional model that accounts for 70% of the variability in the expressive body movement responses to music. With the functional principal component analysis, we modeled individual body movements as a linear combination of a group average and a number of eigenfunctions. The group average and the eigenfunctions are common to all subjects and make up what we call the commonalities. An individual performance is then characterized by a set of scores (the individualities), one score per eigenfunction. The model is based on experimental data which finds high levels of coherence/consistency between participants when grouped according to musical education. This shows an ontogenetic effect. Participants without formal musical education focus on the torso for the expression of basic musical structure (tempo). Musically trained participants decode additional structural elements in the music and focus on body parts having more degrees of freedom (such as the hands). Our results confirm earlier studies that different body parts move differently along with the music.

Preventing recurrence of bipolar I mood episodes and hospitalizations: family psychotherapy plus pharmacotherapy versus pharmacotherapy alone.

PubMed

Solomon, David A; Keitner, Gabor I; Ryan, Christine E; Kelley, Joan; Miller, Ivan W

2008-11-01

This study compared the efficacy of three treatment conditions in preventing recurrence of bipolar I mood episodes and hospitalization for such episodes: individual family therapy plus pharmacotherapy, multifamily group therapy plus pharmacotherapy, and pharmacotherapy alone. Patients with bipolar I disorder were enrolled if they met criteria for an active mood episode and were living with or in regular contact with relatives or significant others. Subjects were randomly assigned to individual family therapy plus pharmacotherapy, multifamily group therapy plus pharmacotherapy, or pharmacotherapy alone, which were provided on an outpatient basis. Individual family therapy involved one therapist meeting with a single patient and the patient's family members, with the content of each session and number of sessions determined by the therapist and family. Multifamily group psychotherapy involved two therapists meeting together for six sessions with multiple patients and their respective family members, with the content of each session preset. All subjects were prescribed a mood stabilizer, and other medications were used as needed. Subjects were assessed monthly for up to 28 months. Following recovery from the index mood episode, subjects were assessed for recurrence of a mood episode and for hospitalization for such episodes. Of a total of 92 subjects that were enrolled in the study, 53 (58%) recovered from their intake mood episode. The analyses in this report focus upon these 53 subjects, 42 (79%) of whom entered the study during an episode of mania. Of the 53 subjects who recovered from their intake mood episode, the proportion of subjects within each treatment group who suffered a recurrence by month 28 did not differ significantly between the three treatment conditions. However, only 5% of the subjects receiving adjunctive multifamily group therapy required hospitalization, compared to 31% of the subjects receiving adjunctive individual family therapy and 38% of those receiving pharmacotherapy alone, a significant difference. Time to recurrence and time to hospitalization did not differ significantly between the three treatment groups. For patients with bipolar I disorder, adjunctive multifamily group therapy may confer significant advantages in preventing hospitalization for a mood episode.

Bounded-Angle Iterative Decoding of LDPC Codes

NASA Technical Reports Server (NTRS)

Dolinar, Samuel; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush

2009-01-01

Bounded-angle iterative decoding is a modified version of conventional iterative decoding, conceived as a means of reducing undetected-error rates for short low-density parity-check (LDPC) codes. For a given code, bounded-angle iterative decoding can be implemented by means of a simple modification of the decoder algorithm, without redesigning the code. Bounded-angle iterative decoding is based on a representation of received words and code words as vectors in an n-dimensional Euclidean space (where n is an integer).

Reliability of directional information in unsorted spikes and local field potentials recorded in human motor cortex

PubMed Central

Perge, János A.; Zhang, Shaomin; Malik, Wasim Q.; Homer, Mark L.; Cash, Sydney; Friehs, Gerhard; Eskandar, Emad N.; Donoghue, John P.; Hochberg, Leigh R.

2014-01-01

Objective Action potentials and local field potentials (LFPs) recorded in primary motor cortex contain information about the direction of movement. LFPs are assumed to be more robust to signal instabilities than action potentials, which makes LFPs along with action potentials a promising signal source for brain-computer interface applications. Still, relatively little research has directly compared the utility of LFPs to action potentials in decoding movement direction in human motor cortex. Approach We conducted intracortical multielectrode recordings in motor cortex of two persons (T2 and [S3]) as they performed a motor imagery task. We then compared the offline decoding performance of LFPs and spiking extracted from the same data recorded across a one-year period in each participant. Main results We obtained offline prediction accuracy of movement direction and endpoint velocity in multiple LFP bands, with the best performance in the highest (200–400Hz) LFP frequency band, presumably also containing low-pass filtered action potentials. Cross-frequency correlations of preferred directions and directional modulation index showed high similarity of directional information between action potential firing rates (spiking) and high frequency LFPs (70–400Hz), and increasing disparity with lower frequency bands (0–7, 10–40 and 50–65Hz). Spikes predicted the direction of intended movement more accurately than any individual LFP band, however combined decoding of all LFPs was statistically indistinguishable from spike based performance. As the quality of spiking signals (i.e. signal amplitude) and the number of significantly modulated spiking units decreased, the offline decoding performance decreased 3.6[5.65]%/month (for T2 and [S3] respectively). The decrease in the number of significantly modulated LFP signals and their decoding accuracy followed a similar trend (2.4[2.85]%/month, ANCOVA, p=0.27[0.03]). Significance Field potentials provided comparable offline decoding performance to unsorted spikes. Thus, LFPs may provide useful external device control using current human intracortical recording technology. (Clinical trial registration number: NCT00912041) PMID:24921388

Decoding of finger trajectory from ECoG using deep learning.

PubMed

Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek

2018-06-01

Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the state transitions. The discussed network eliminated the need to separately train the model at each step in the decoding pipeline. The whole system can be jointly optimized using stochastic gradient descent and is capable of online learning.

Decoding of finger trajectory from ECoG using deep learning

NASA Astrophysics Data System (ADS)

Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek

2018-06-01

Objective. Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. Approach. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. Main results. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. Significance. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the state transitions. The discussed network eliminated the need to separately train the model at each step in the decoding pipeline. The whole system can be jointly optimized using stochastic gradient descent and is capable of online learning.

Information Processing Abilities and Reading.

ERIC Educational Resources Information Center

Samuels, S. Jay

1987-01-01

A major focus in reading difficulty is lack of automaticity in decoding, which overloads the attentional system, leads to the use of small, meaningless visual processing units such as the individual letter, places heavy demands on short-term memory, and interferes with comprehension. Techniques for diagnosis and remediation are noted. (Author/JW)

Matching Interventions to Reading Needs: A Case for Differentiation

ERIC Educational Resources Information Center

Jones, Jill S.; Conradi, Kristin; Amendum, Steven J.

2016-01-01

The purpose of this article is to highlight the importance of providing reading interventions that are differentiated and aligned with an individual student's most foundational reading skill need. The authors present profiles of different readers and suggest three principal areas for support: decoding words, reading at an appropriate rate, and…

Iterative channel decoding of FEC-based multiple-description codes.

PubMed

Chang, Seok-Ho; Cosman, Pamela C; Milstein, Laurence B

2012-03-01

Multiple description coding has been receiving attention as a robust transmission framework for multimedia services. This paper studies the iterative decoding of FEC-based multiple description codes. The proposed decoding algorithms take advantage of the error detection capability of Reed-Solomon (RS) erasure codes. The information of correctly decoded RS codewords is exploited to enhance the error correction capability of the Viterbi algorithm at the next iteration of decoding. In the proposed algorithm, an intradescription interleaver is synergistically combined with the iterative decoder. The interleaver does not affect the performance of noniterative decoding but greatly enhances the performance when the system is iteratively decoded. We also address the optimal allocation of RS parity symbols for unequal error protection. For the optimal allocation in iterative decoding, we derive mathematical equations from which the probability distributions of description erasures can be generated in a simple way. The performance of the algorithm is evaluated over an orthogonal frequency-division multiplexing system. The results show that the performance of the multiple description codes is significantly enhanced.

High rate concatenated coding systems using bandwidth efficient trellis inner codes

NASA Technical Reports Server (NTRS)

Deng, Robert H.; Costello, Daniel J., Jr.

1989-01-01

High-rate concatenated coding systems with bandwidth-efficient trellis inner codes and Reed-Solomon (RS) outer codes are investigated for application in high-speed satellite communication systems. Two concatenated coding schemes are proposed. In one the inner code is decoded with soft-decision Viterbi decoding, and the outer RS code performs error-correction-only decoding (decoding without side information). In the other, the inner code is decoded with a modified Viterbi algorithm, which produces reliability information along with the decoded output. In this algorithm, path metrics are used to estimate the entire information sequence, whereas branch metrics are used to provide reliability information on the decoded sequence. This information is used to erase unreliable bits in the decoded output. An errors-and-erasures RS decoder is then used for the outer code. The two schemes have been proposed for high-speed data communication on NASA satellite channels. The rates considered are at least double those used in current NASA systems, and the results indicate that high system reliability can still be achieved.

Efficient Decoding of Compressed Data.

ERIC Educational Resources Information Center

Bassiouni, Mostafa A.; Mukherjee, Amar

1995-01-01

Discusses the problem of enhancing the speed of Huffman decoding of compressed data. Topics addressed include the Huffman decoding tree; multibit decoding; binary string mapping problems; and algorithms for solving mapping problems. (22 references) (LRW)

A new VLSI architecture for a single-chip-type Reed-Solomon decoder

NASA Technical Reports Server (NTRS)

Hsu, I. S.; Truong, T. K.

1989-01-01

A new very large scale integration (VLSI) architecture for implementing Reed-Solomon (RS) decoders that can correct both errors and erasures is described. This new architecture implements a Reed-Solomon decoder by using replication of a single VLSI chip. It is anticipated that this single chip type RS decoder approach will save substantial development and production costs. It is estimated that reduction in cost by a factor of four is possible with this new architecture. Furthermore, this Reed-Solomon decoder is programmable between 8 bit and 10 bit symbol sizes. Therefore, both an 8 bit Consultative Committee for Space Data Systems (CCSDS) RS decoder and a 10 bit decoder are obtained at the same time, and when concatenated with a (15,1/6) Viterbi decoder, provide an additional 2.1-dB coding gain.

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

Real-time SHVC software decoding with multi-threaded parallel processing

NASA Astrophysics Data System (ADS)

Gudumasu, Srinivas; He, Yuwen; Ye, Yan; He, Yong; Ryu, Eun-Seok; Dong, Jie; Xiu, Xiaoyu

2014-09-01

This paper proposes a parallel decoding framework for scalable HEVC (SHVC). Various optimization technologies are implemented on the basis of SHVC reference software SHM-2.0 to achieve real-time decoding speed for the two layer spatial scalability configuration. SHVC decoder complexity is analyzed with profiling information. The decoding process at each layer and the up-sampling process are designed in parallel and scheduled by a high level application task manager. Within each layer, multi-threaded decoding is applied to accelerate the layer decoding speed. Entropy decoding, reconstruction, and in-loop processing are pipeline designed with multiple threads based on groups of coding tree units (CTU). A group of CTUs is treated as a processing unit in each pipeline stage to achieve a better trade-off between parallelism and synchronization. Motion compensation, inverse quantization, and inverse transform modules are further optimized with SSE4 SIMD instructions. Simulations on a desktop with an Intel i7 processor 2600 running at 3.4 GHz show that the parallel SHVC software decoder is able to decode 1080p spatial 2x at up to 60 fps (frames per second) and 1080p spatial 1.5x at up to 50 fps for those bitstreams generated with SHVC common test conditions in the JCT-VC standardization group. The decoding performance at various bitrates with different optimization technologies and different numbers of threads are compared in terms of decoding speed and resource usage, including processor and memory.

Error-trellis Syndrome Decoding Techniques for Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1984-01-01

An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decoding is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

The VLSI design of an error-trellis syndrome decoder for certain convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Jensen, J. M.; Hsu, I.-S.; Truong, T. K.

1986-01-01

A recursive algorithm using the error-trellis decoding technique is developed to decode convolutional codes (CCs). An example, illustrating the very large scale integration (VLSI) architecture of such a decode, is given for a dual-K CC. It is demonstrated that such a decoder can be realized readily on a single chip with metal-nitride-oxide-semiconductor technology.

Systolic VLSI Reed-Solomon Decoder

NASA Technical Reports Server (NTRS)

Shao, H. M.; Truong, T. K.; Deutsch, L. J.; Yuen, J. H.

1986-01-01

Decoder for digital communications provides high-speed, pipelined ReedSolomon (RS) error-correction decoding of data streams. Principal new feature of proposed decoder is modification of Euclid greatest-common-divisor algorithm to avoid need for time-consuming computations of inverse of certain Galois-field quantities. Decoder architecture suitable for implementation on very-large-scale integrated (VLSI) chips with negative-channel metaloxide/silicon circuitry.

The VLSI design of error-trellis syndrome decoding for convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Jensen, J. M.; Truong, T. K.; Hsu, I. S.

1985-01-01

A recursive algorithm using the error-trellis decoding technique is developed to decode convolutional codes (CCs). An example, illustrating the very large scale integration (VLSI) architecture of such a decode, is given for a dual-K CC. It is demonstrated that such a decoder can be realized readily on a single chip with metal-nitride-oxide-semiconductor technology.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3

NASA Technical Reports Server (NTRS)

Lin, Shu

1998-01-01

Decoding algorithms based on the trellis representation of a code (block or convolutional) drastically reduce decoding complexity. The best known and most commonly used trellis-based decoding algorithm is the Viterbi algorithm. It is a maximum likelihood decoding algorithm. Convolutional codes with the Viterbi decoding have been widely used for error control in digital communications over the last two decades. This chapter is concerned with the application of the Viterbi decoding algorithm to linear block codes. First, the Viterbi algorithm is presented. Then, optimum sectionalization of a trellis to minimize the computational complexity of a Viterbi decoder is discussed and an algorithm is presented. Some design issues for IC (integrated circuit) implementation of a Viterbi decoder are considered and discussed. Finally, a new decoding algorithm based on the principle of compare-select-add is presented. This new algorithm can be applied to both block and convolutional codes and is more efficient than the conventional Viterbi algorithm based on the add-compare-select principle. This algorithm is particularly efficient for rate 1/n antipodal convolutional codes and their high-rate punctured codes. It reduces computational complexity by one-third compared with the Viterbi algorithm.

A test of the role of the medial temporal lobe in single-word decoding.

PubMed

Osipowicz, Karol; Rickards, Tyler; Shah, Atif; Sharan, Ashwini; Sperling, Michael; Kahn, Waseem; Tracy, Joseph

2011-01-15

The degree to which the MTL system contributes to effective language skills is not well delineated. We sought to determine if the MTL plays a role in single-word decoding in healthy, normal skilled readers. The experiment follows from the implications of the dual-process model of single-word decoding, which provides distinct predictions about the nature of MTL involvement. The paradigm utilized word (regular and irregularly spelled words) and pseudoword (phonetically regular) stimuli that differed in their demand for non-lexical as opposed lexical decoding. The data clearly showed that the MTL system was not involved in single word decoding in skilled, native English readers. Neither the hippocampus nor the MTL system as a whole showed significant activation during lexical or non-lexical based decoding. The results provide evidence that lexical and non-lexical decoding are implemented by distinct but overlapping neuroanatomical networks. Non-lexical decoding appeared most uniquely associated with cuneus and fusiform gyrus activation biased toward the left hemisphere. In contrast, lexical decoding appeared associated with right middle frontal and supramarginal, and bilateral cerebellar activation. Both these decoding operations appeared in the context of a shared widespread network of activations including bilateral occipital cortex and superior frontal regions. These activations suggest that the absence of MTL involvement in either lexical or non-lexical decoding appears likely a function of the skilled reading ability of our sample such that whole-word recognition and retrieval processes do not utilize the declarative memory system, in the case of lexical decoding, and require only minimal analysis and recombination of the phonetic elements of a word, in the case of non-lexical decoding. Copyright © 2010 Elsevier Inc. All rights reserved.

A Test of the Role of the Medial Temporal Lobe in Single-Word Decoding

PubMed Central

Osipowicz, Karol; Rickards, Tyler; Shah, Atif; Sharan, Ashwini; Sperling, Michael; Kahn, Waseem; Tracy, Joseph

2012-01-01

The degree to which the MTL system contributes to effective language skills is not well delineated. We sought to determine if the MTL plays a role in single-word decoding in healthy, normal skilled readers. The experiment follows from the implications of the dual-process model of single-word decoding, which provides distinct predictions about the nature of MTL involvement. The paradigm utilized word (regular and irregularly spelled words) and pseudoword (phonetically regular) stimuli that differed in their demand for non-lexical as opposed lexical decoding. The data clearly showed that the MTL system was not involved in single word decoding in skilled, native English readers. Neither the hippocampus, nor the MTL system as a whole showed significant activation during lexical or non-lexical based decoding. The results provide evidence that lexical and non-lexical decoding are implemented by distinct but overlapping neuroanatomical networks. Non-lexical decoding appeared most uniquely associated with cuneus and fusiform gyrus activation biased toward the left hemisphere. In contrast, lexical decoding appeared associated with right middle frontal and supramarginal, and bilateral cerebellar activation. Both these decoding operations appeared in the context of a shared widespread network of activations including bilateral occipital cortex and superior frontal regions. These activations suggest that the absence of MTL involvement in either lexical or non-lexical decoding appears likely a function of the skilled reading ability of our sample such that whole-word recognition and retrieval processes do not utilize the declarative memory system, in the case of lexical decoding, and require only minimal analysis and recombination of the phonetic elements of a word, in the case of non-lexical decoding. PMID:20884357

From Perception to Metacognition: Auditory and Olfactory Functions in Early Blind, Late Blind, and Sighted Individuals

PubMed Central

Cornell Kärnekull, Stina; Arshamian, Artin; Nilsson, Mats E.; Larsson, Maria

2016-01-01

Although evidence is mixed, studies have shown that blind individuals perform better than sighted at specific auditory, tactile, and chemosensory tasks. However, few studies have assessed blind and sighted individuals across different sensory modalities in the same study. We tested early blind (n = 15), late blind (n = 15), and sighted (n = 30) participants with analogous olfactory and auditory tests in absolute threshold, discrimination, identification, episodic recognition, and metacognitive ability. Although the multivariate analysis of variance (MANOVA) showed no overall effect of blindness and no interaction with modality, follow-up between-group contrasts indicated a blind-over-sighted advantage in auditory episodic recognition, that was most pronounced in early blind individuals. In contrast to the auditory modality, there was no empirical support for compensatory effects in any of the olfactory tasks. There was no conclusive evidence for group differences in metacognitive ability to predict episodic recognition performance. Taken together, the results showed no evidence of an overall superior performance in blind relative sighted individuals across olfactory and auditory functions, although early blind individuals exceled in episodic auditory recognition memory. This observation may be related to an experience-induced increase in auditory attentional capacity. PMID:27729884

Olfactory identification deficit and its relationship with hedonic traits in patients with first-episode schizophrenia and individuals with schizotypy.

PubMed

Zou, Lai-Quan; Zhou, Han-Yu; Lui, Simon S Y; Wang, Yi; Wang, Ya; Gan, Jun; Zhu, Xiong-Zhao; Cheung, Eric F C; Chan, Raymond C K

2018-04-20

Olfactory identification impairments have been consistently found in schizophrenia patients. However, few previous studies have investigated this in first-episode patients. There are also inconsistent findings regarding olfactory identification ability in psychometrically-defined schizotypy individuals. In this study, we directly compared the olfactory identification ability of first-episode schizophrenia patients with schizotypy individuals. The relationship between olfactory identification impairments and hedonic traits was also examined. Thirty-five first-episode schizophrenia patients, 40 schizotypy individuals as defined by the Chapman's Anhedonia Scales and 40 demographically matched controls were recruited. The University of Pennsylvania Smell Identification Test was administered. Hedonic capacity was assessed using the Temporal Experience of Pleasure Scale (TEPS). The results showed that both the schizophrenia and schizotypy groups showed poorer olfactory identification ability than controls, and the impairment was significantly correlated with reduced pleasure experiences. Our findings support olfactory identification impairment as a trait marker for schizophrenia. Copyright © 2018 Elsevier Inc. All rights reserved.

LDPC-based iterative joint source-channel decoding for JPEG2000.

PubMed

Pu, Lingling; Wu, Zhenyu; Bilgin, Ali; Marcellin, Michael W; Vasic, Bane

2007-02-01

A framework is proposed for iterative joint source-channel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error-resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. Decoding is carried out jointly in an iterative fashion. Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance.

Economic grand rounds: financing first-episode psychosis services in the United States.

PubMed

Goldman, Howard H; Karakus, Mustafa; Frey, William; Beronio, Kirsten

2013-06-01

Adequate financing is essential to implementing services for individuals experiencing a first episode of a psychotic illness. Recovery After an Initial Schizophrenia Episode (RAISE), a project sponsored by the National Institute of Mental Health, is providing a practical test of the implementation and effectiveness of first-episode services in real-world settings. This column describes approaches to financing early intervention services that are being used at five of 18 U.S. sites participating in a clinical trial of a team-based, multielement RAISE intervention. The authors also describe new options for financing that will become available as the Affordable Care Act (ACA) is implemented more fully. The ACA will rationalize coverage of first-episode services, but the all-important Medicaid provisions will also require individual state action to implement services optimally.

Drinking Level, Drinking Pattern, and Twenty-Year Total Mortality Among Late-Life Drinkers.

PubMed

Holahan, Charles J; Schutte, Kathleen K; Brennan, Penny L; Holahan, Carole K; Moos, Rudolf H

2015-07-01

Research on moderate drinking has focused on the average level of drinking. Recently, however, investigators have begun to consider the role of the pattern of drinking, particularly heavy episodic drinking, in mortality. The present study examined the combined roles of average drinking level (moderate vs. high) and drinking pattern (regular vs. heavy episodic) in 20-year total mortality among late-life drinkers. The sample comprised 1,121 adults ages 55-65 years. Alcohol consumption was assessed at baseline, and total mortality was indexed across 20 years. We used multiple logistic regression analyses controlling for a broad set of sociodemographic, behavioral, and health status covariates. Among individuals whose high level of drinking placed them at risk, a heavy episodic drinking pattern did not increase mortality odds compared with a regular drinking pattern. Conversely, among individuals who engage in a moderate level of drinking, prior findings showed that a heavy episodic drinking pattern did increase mortality risk compared with a regular drinking pattern. Correspondingly, a high compared with a moderate drinking level increased mortality risk among individuals maintaining a regular drinking pattern, but not among individuals engaging in a heavy episodic drinking pattern, whose pattern of consumption had already placed them at risk. Findings highlight that low-risk drinking requires that older adults drink low to moderate average levels of alcohol and avoid heavy episodic drinking. Heavy episodic drinking is frequent among late-middle-aged and older adults and needs to be addressed along with average consumption in understanding the health risks of late-life drinkers.

Optimizing psychosocial interventions in first-episode psychosis: current perspectives and future directions.

PubMed

Breitborde, Nicholas Jk; Moe, Aubrey M; Ered, Arielle; Ellman, Lauren M; Bell, Emily K

2017-01-01

Psychotic-spectrum disorders such as schizophrenia, schizoaffective disorder, and bipolar disorder with psychotic features are devastating illnesses accompanied by high levels of morbidity and mortality. Growing evidence suggests that outcomes for individuals with psychotic-spectrum disorders can be meaningfully improved by increasing the quality of mental health care provided to these individuals and reducing the delay between the first onset of psychotic symptoms and the receipt of adequate psychiatric care. More specifically, multicomponent treatment packages that 1) simultaneously target multiple symptomatic and functional needs and 2) are provided as soon as possible following the initial onset of psychotic symptoms appear to have disproportionately positive effects on the course of psychotic-spectrum disorders. Yet, despite the benefit of multicomponent care for first-episode psychosis, clinical and functional outcomes among individuals with first-episode psychosis participating in such services are still suboptimal. Thus, the goal of this review is to highlight putative strategies to improve care for individuals with first-episode psychosis with specific attention to optimizing psychosocial interventions. To address this goal, we highlight four burgeoning areas of research with regard to optimization of psychosocial interventions for first-episode psychosis: 1) reducing the delay in receipt of evidence-based psychosocial treatments; 2) synergistic pairing of psychosocial interventions; 3) personalized delivery of psychosocial interventions; and 4) technological enhancement of psychosocial interventions. Future research on these topics has the potential to optimize the treatment response to evidence-based psychosocial interventions and to enhance the improved (but still suboptimal) treatment outcomes commonly experienced by individuals with first-episode psychosis.

Belief propagation decoding of quantum channels by passing quantum messages

NASA Astrophysics Data System (ADS)

Renes, Joseph M.

2017-07-01

The belief propagation (BP) algorithm is a powerful tool in a wide range of disciplines from statistical physics to machine learning to computational biology, and is ubiquitous in decoding classical error-correcting codes. The algorithm works by passing messages between nodes of the factor graph associated with the code and enables efficient decoding of the channel, in some cases even up to the Shannon capacity. Here we construct the first BP algorithm which passes quantum messages on the factor graph and is capable of decoding the classical-quantum channel with pure state outputs. This gives explicit decoding circuits whose number of gates is quadratic in the code length. We also show that this decoder can be modified to work with polar codes for the pure state channel and as part of a decoder for transmitting quantum information over the amplitude damping channel. These represent the first explicit capacity-achieving decoders for non-Pauli channels.

Low Power LDPC Code Decoder Architecture Based on Intermediate Message Compression Technique

NASA Astrophysics Data System (ADS)

Shimizu, Kazunori; Togawa, Nozomu; Ikenaga, Takeshi; Goto, Satoshi

Reducing the power dissipation for LDPC code decoder is a major challenging task to apply it to the practical digital communication systems. In this paper, we propose a low power LDPC code decoder architecture based on an intermediate message-compression technique which features as follows: (i) An intermediate message compression technique enables the decoder to reduce the required memory capacity and write power dissipation. (ii) A clock gated shift register based intermediate message memory architecture enables the decoder to decompress the compressed messages in a single clock cycle while reducing the read power dissipation. The combination of the above two techniques enables the decoder to reduce the power dissipation while keeping the decoding throughput. The simulation results show that the proposed architecture improves the power efficiency up to 52% and 18% compared to that of the decoder based on the overlapped schedule and the rapid convergence schedule without the proposed techniques respectively.

Episodic Memory and Episodic Foresight in 3- and 5-Year-Old Children

ERIC Educational Resources Information Center

Hayne, Harlene; Gross, Julien; McNamee, Stephanie; Fitzgibbon, Olivia; Tustin, Karen

2011-01-01

In the present study, we examined the development of episodic memory and episodic foresight. Three- and 5-year-olds were interviewed individually using a personalised timeline that included photographs of them at different points in their life. After constructing the timeline with the experimenter, each child was asked to discuss a number of…

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1998-01-01

A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and sectionalization of trellises. Chapter 7 discusses trellis decomposition and subtrellises for low-weight codewords. Chapter 8 first presents well known methods for constructing long powerful codes from short component codes or component codes of smaller dimensions, and then provides methods for constructing their trellises which include Shannon and Cartesian product techniques. Chapter 9 deals with convolutional codes, puncturing, zero-tail termination and tail-biting.Chapters 10 through 13 present various trellis-based decoding algorithms, old and new. Chapter 10 first discusses the application of the well known Viterbi decoding algorithm to linear block codes, optimum sectionalization of a code trellis to minimize computation complexity, and design issues for IC (integrated circuit) implementation of a Viterbi decoder. Then it presents a new decoding algorithm for convolutional codes, named Differential Trellis Decoding (DTD) algorithm. Chapter 12 presents a suboptimum reliability-based iterative decoding algorithm with a low-weight trellis search for the most likely codeword. This decoding algorithm provides a good trade-off between error performance and decoding complexity. All the decoding algorithms presented in Chapters 10 through 12 are devised to minimize word error probability. Chapter 13 presents decoding algorithms that minimize bit error probability and provide the corresponding soft (reliability) information at the output of the decoder. Decoding algorithms presented are the MAP (maximum a posteriori probability) decoding algorithm and the Soft-Output Viterbi Algorithm (SOVA) algorithm. Finally, the minimization of bit error probability in trellis-based MLD is discussed.

Temporal Context Memory in High-Functioning Autism

ERIC Educational Resources Information Center

Gras-Vincendon, Agnes; Mottron, Laurent; Salame, Pierre; Bursztejn, Claude; Danion, Jean-Marie

2007-01-01

Episodic memory, i.e. memory for specific episodes situated in space and time, seems impaired in individuals with autism. According to weak central coherence theory, individuals with autism have general difficulty connecting contextual and item information which then impairs their capacity to memorize information in context. This study…

Buffer management for sequential decoding. [block erasure probability reduction

NASA Technical Reports Server (NTRS)

Layland, J. W.

1974-01-01

Sequential decoding has been found to be an efficient means of communicating at low undetected error rates from deep space probes, but erasure or computational overflow remains a significant problem. Erasure of a block occurs when the decoder has not finished decoding that block at the time that it must be output. By drawing upon analogies in computer time sharing, this paper develops a buffer-management strategy which reduces the decoder idle time to a negligible level, and therefore improves the erasure probability of a sequential decoder. For a decoder with a speed advantage of ten and a buffer size of ten blocks, operating at an erasure rate of .01, use of this buffer-management strategy reduces the erasure rate to less than .0001.

Application of source biasing technique for energy efficient DECODER circuit design: memory array application

NASA Astrophysics Data System (ADS)

Gupta, Neha; Parihar, Priyanka; Neema, Vaibhav

2018-04-01

Researchers have proposed many circuit techniques to reduce leakage power dissipation in memory cells. If we want to reduce the overall power in the memory system, we have to work on the input circuitry of memory architecture i.e. row and column decoder. In this research work, low leakage power with a high speed row and column decoder for memory array application is designed and four new techniques are proposed. In this work, the comparison of cluster DECODER, body bias DECODER, source bias DECODER, and source coupling DECODER are designed and analyzed for memory array application. Simulation is performed for the comparative analysis of different DECODER design parameters at 180 nm GPDK technology file using the CADENCE tool. Simulation results show that the proposed source bias DECODER circuit technique decreases the leakage current by 99.92% and static energy by 99.92% at a supply voltage of 1.2 V. The proposed circuit also improves dynamic power dissipation by 5.69%, dynamic PDP/EDP 65.03% and delay 57.25% at 1.2 V supply voltage.

Prediction of episodic acidification in North-eastern USA: An empirical/mechanistic approach

USGS Publications Warehouse

Davies, T.D.; Tranter, M.; Wigington, P.J.; Eshleman, K.N.; Peters, N.E.; Van Sickle, J.; DeWalle, David R.; Murdoch, Peter S.

1999-01-01

Observations from the US Environmental Protection Agency's Episodic Response Project (ERP) in the North-eastern United States are used to develop an empirical/mechanistic scheme for prediction of the minimum values of acid neutralizing capacity (ANC) during episodes. An acidification episode is defined as a hydrological event during which ANC decreases. The pre-episode ANC is used to index the antecedent condition, and the stream flow increase reflects how much the relative contributions of sources of waters change during the episode. As much as 92% of the total variation in the minimum ANC in individual catchments can be explained (with levels of explanation >70% for nine of the 13 streams) by a multiple linear regression model that includes pre-episode ANC and change in discharge as independent variable. The predictive scheme is demonstrated to be regionally robust, with the regional variance explained ranging from 77 to 83%. The scheme is not successful for each ERP stream, and reasons are suggested for the individual failures. The potential for applying the predictive scheme to other watersheds is demonstrated by testing the model with data from the Panola Mountain Research Watershed in the South-eastern United States, where the variance explained by the model was 74%. The model can also be utilized to assess 'chemically new' and 'chemically old' water sources during acidification episodes.Observations from the US Environmental Protection Agency's Episodic Response Project (ERP) in the Northeastern United States are used to develop an empirical/mechanistic scheme for prediction of the minimum values of acid neutralizing capacity (ANC) during episodes. An acidification episode is defined as a hydrological event during which ANC decreases. The pre-episode ANC is used to index the antecedent condition, and the stream flow increase reflects how much the relative contributions of sources of waters change during the episode. As much as 92% of the total variation in the minimum ANC in individual catchments can be explained (with levels of explanation >70% for nine of the 13 streams) by a multiple linear regression model that includes pre-episode ANC and change in discharge as independent variables. The predictive scheme is demonstrated to be regionally robust, with the regional variance explained ranging from 77 to 83%. The scheme is not successful for each ERP stream, and reasons are suggested for the individual failures. The potential for applying the predictive scheme to other watersheds is demonstrated by testing the model with data from the Panola Mountain Research Watershed in the South-eastern United States, where the variance explained by the model was 74%. The model can also be utilized to assess `chemically new' and `chemically old' water sources during acidification episodes.

You never think about my feelings: interpersonal dominance as a predictor of emotion decoding accuracy.

PubMed

Moeller, Sara K; Lee, Elizabeth A Ewing; Robinson, Michael D

2011-08-01

Dominance and submission constitute fundamentally different social interaction strategies that may be enacted most effectively to the extent that the emotions of others are relatively ignored (dominance) versus noticed (submission). On the basis of such considerations, we hypothesized a systematic relationship between chronic tendencies toward high versus low levels of interpersonal dominance and emotion decoding accuracy in objective tasks. In two studies (total N = 232), interpersonally dominant individuals exhibited poorer levels of emotion recognition in response to audio and video clips (Study 1) and facial expressions of emotion (Study 2). The results provide a novel perspective on interpersonal dominance, suggest its strategic nature (Study 2), and are discussed in relation to Fiske's (1993) social-cognitive theory of power. 2011 APA, all rights reserved

Efficiency turns the table on neural encoding, decoding and noise.

PubMed

Deneve, Sophie; Chalk, Matthew

2016-04-01

Sensory neurons are usually described with an encoding model, for example, a function that predicts their response from the sensory stimulus using a receptive field (RF) or a tuning curve. However, central to theories of sensory processing is the notion of 'efficient coding'. We argue here that efficient coding implies a completely different neural coding strategy. Instead of a fixed encoding model, neural populations would be described by a fixed decoding model (i.e. a model reconstructing the stimulus from the neural responses). Because the population solves a global optimization problem, individual neurons are variable, but not noisy, and have no truly invariant tuning curve or receptive field. We review recent experimental evidence and implications for neural noise correlations, robustness and adaptation. Copyright © 2016. Published by Elsevier Ltd.

Decoding Spontaneous Emotional States in the Human Brain

PubMed Central

Kragel, Philip A.; Knodt, Annchen R.; Hariri, Ahmad R.; LaBar, Kevin S.

2016-01-01

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems. PMID:27627738

Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network.

PubMed

Zafar, Raheel; Kamel, Nidal; Naufal, Mohamad; Malik, Aamir Saeed; Dass, Sarat C; Ahmad, Rana Fayyaz; Abdullah, Jafri M; Reza, Faruque

2017-01-01

Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. Selection of significant features is an important part of fMRI data analysis, since it reduces the computational burden and improves the prediction performance; significant features are selected using t-test. MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. The proposed method showed better overall accuracy (68.6%) compared to ROI (61.88%) and estimation values (64.17%).

Decoding rule search domain in the left inferior frontal gyrus

PubMed Central

Babcock, Laura; Vallesi, Antonino

2018-01-01

Traditionally, the left hemisphere has been thought to extract mainly verbal patterns of information, but recent evidence has shown that the left Inferior Frontal Gyrus (IFG) is active during inductive reasoning in both the verbal and spatial domains. We aimed to understand whether the left IFG supports inductive reasoning in a domain-specific or domain-general fashion. To do this we used Multi-Voxel Pattern Analysis to decode the representation of domain during a rule search task. Thirteen participants were asked to extract the rule underlying streams of letters presented in different spatial locations. Each rule was either verbal (letters forming words) or spatial (positions forming geometric figures). Our results show that domain was decodable in the left prefrontal cortex, suggesting that this region represents domain-specific information, rather than processes common to the two domains. A replication study with the same participants tested two years later confirmed these findings, though the individual representations changed, providing evidence for the flexible nature of representations. This study extends our knowledge on the neural basis of goal-directed behaviors and on how information relevant for rule extraction is flexibly mapped in the prefrontal cortex. PMID:29547623

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons.

PubMed

Oddo, Calogero M; Mazzoni, Alberto; Spanne, Anton; Enander, Jonas M D; Mogensen, Hannes; Bengtsson, Fredrik; Camboni, Domenico; Micera, Silvestro; Jörntell, Henrik

2017-04-04

Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models.

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons

PubMed Central

Oddo, Calogero M.; Mazzoni, Alberto; Spanne, Anton; Enander, Jonas M. D.; Mogensen, Hannes; Bengtsson, Fredrik; Camboni, Domenico; Micera, Silvestro; Jörntell, Henrik

2017-01-01

Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models. PMID:28374841

A Scalable Architecture of a Structured LDPC Decoder

NASA Technical Reports Server (NTRS)

Lee, Jason Kwok-San; Lee, Benjamin; Thorpe, Jeremy; Andrews, Kenneth; Dolinar, Sam; Hamkins, Jon

2004-01-01

We present a scalable decoding architecture for a certain class of structured LDPC codes. The codes are designed using a small (n,r) protograph that is replicated Z times to produce a decoding graph for a (Z x n, Z x r) code. Using this architecture, we have implemented a decoder for a (4096,2048) LDPC code on a Xilinx Virtex-II 2000 FPGA, and achieved decoding speeds of 31 Mbps with 10 fixed iterations. The implemented message-passing algorithm uses an optimized 3-bit non-uniform quantizer that operates with 0.2dB implementation loss relative to a floating point decoder.

Multiuser signal detection using sequential decoding

NASA Astrophysics Data System (ADS)

Xie, Zhenhua; Rushforth, Craig K.; Short, Robert T.

1990-05-01

The application of sequential decoding to the detection of data transmitted over the additive white Gaussian noise channel by K asynchronous transmitters using direct-sequence spread-spectrum multiple access is considered. A modification of Fano's (1963) sequential-decoding metric, allowing the messages from a given user to be safely decoded if its Eb/N0 exceeds -1.6 dB, is presented. Computer simulation is used to evaluate the performance of a sequential decoder that uses this metric in conjunction with the stack algorithm. In many circumstances, the sequential decoder achieves results comparable to those obtained using the much more complicated optimal receiver.

Complementary Reliability-Based Decodings of Binary Linear Block Codes

NASA Technical Reports Server (NTRS)

Fossorier, Marc P. C.; Lin, Shu

1997-01-01

This correspondence presents a hybrid reliability-based decoding algorithm which combines the reprocessing method based on the most reliable basis and a generalized Chase-type algebraic decoder based on the least reliable positions. It is shown that reprocessing with a simple additional algebraic decoding effort achieves significant coding gain. For long codes, the order of reprocessing required to achieve asymptotic optimum error performance is reduced by approximately 1/3. This significantly reduces the computational complexity, especially for long codes. Also, a more efficient criterion for stopping the decoding process is derived based on the knowledge of the algebraic decoding solution.

Visual perception as retrospective Bayesian decoding from high- to low-level features

PubMed Central

Ding, Stephanie; Cueva, Christopher J.; Tsodyks, Misha; Qian, Ning

2017-01-01

When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. PMID:29073108

Single trial discrimination of individual finger movements on one hand: A combined MEG and EEG study☆

PubMed Central

Quandt, F.; Reichert, C.; Hinrichs, H.; Heinze, H.J.; Knight, R.T.; Rieger, J.W.

2012-01-01

It is crucial to understand what brain signals can be decoded from single trials with different recording techniques for the development of Brain-Machine Interfaces. A specific challenge for non-invasive recording methods are activations confined to small spatial areas on the cortex such as the finger representation of one hand. Here we study the information content of single trial brain activity in non-invasive MEG and EEG recordings elicited by finger movements of one hand. We investigate the feasibility of decoding which of four fingers of one hand performed a slight button press. With MEG we demonstrate reliable discrimination of single button presses performed with the thumb, the index, the middle or the little finger (average over all subjects and fingers 57%, best subject 70%, empirical guessing level: 25.1%). EEG decoding performance was less robust (average over all subjects and fingers 43%, best subject 54%, empirical guessing level 25.1%). Spatiotemporal patterns of amplitude variations in the time series provided best information for discriminating finger movements. Non-phase-locked changes of mu and beta oscillations were less predictive. Movement related high gamma oscillations were observed in average induced oscillation amplitudes in the MEG but did not provide sufficient information about the finger's identity in single trials. Importantly, pre-movement neuronal activity provided information about the preparation of the movement of a specific finger. Our study demonstrates the potential of non-invasive MEG to provide informative features for individual finger control in a Brain-Machine Interface neuroprosthesis. PMID:22155040

Emotional Intelligence and Mismatching Expressive and Verbal Messages: A Contribution to Detection of Deception

PubMed Central

Wojciechowski, Jerzy; Stolarski, Maciej; Matthews, Gerald

2014-01-01

Processing facial emotion, especially mismatches between facial and verbal messages, is believed to be important in the detection of deception. For example, emotional leakage may accompany lying. Individuals with superior emotion perception abilities may then be more adept in detecting deception by identifying mismatch between facial and verbal messages. Two personal factors that may predict such abilities are female gender and high emotional intelligence (EI). However, evidence on the role of gender and EI in detection of deception is mixed. A key issue is that the facial processing skills required to detect deception may not be the same as those required to identify facial emotion. To test this possibility, we developed a novel facial processing task, the FDT (Face Decoding Test) that requires detection of inconsistencies between facial and verbal cues to emotion. We hypothesized that gender and ability EI would be related to performance when cues were inconsistent. We also hypothesized that gender effects would be mediated by EI, because women tend to score as more emotionally intelligent on ability tests. Data were collected from 210 participants. Analyses of the FDT suggested that EI was correlated with superior face decoding in all conditions. We also confirmed the expected gender difference, the superiority of high EI individuals, and the mediation hypothesis. Also, EI was more strongly associated with facial decoding performance in women than in men, implying there may be gender differences in strategies for processing affective cues. It is concluded that integration of emotional and cognitive cues may be a core attribute of EI that contributes to the detection of deception. PMID:24658500

Test Review: Torgesen, J. K., Wagner, R. K., and Rashotte, C. A. (2012), "Test of Word Reading Efficiency-Second Edition" (TOWRE-2). Austin, TX: Pro-Ed

ERIC Educational Resources Information Center

Tarar, Jessica M.; Meisinger, Elizabeth B.; Dickens, Rachel H.

2015-01-01

The TOWRE-2 was developed to provide an efficient measure of two essential wordlevel reading skills, sight word reading and phonetic decoding skills. The Sight Word Efficiency (SWE) subtest assesses the number of real words that an individual can read from a vertical list within 45 s. This subtest is designed to measure the size of an individual's…

Personal Characteristics Associated with Episodes of Injury in a Residential Facility.

ERIC Educational Resources Information Center

Konarski, Edward A., Jr.; Sutton, Kelly; Huffman, Alice

1997-01-01

Investigation of episodes of injury and personal characteristics among 412 individuals with mental retardation living in Intermediate Care Facilities found that 16% of the group experienced 67% of injuries. Individuals taking antipsychotics, having higher maladaptive behavior scores, and having relatively higher levels of adaptive behavior were…

Clinical correlates of distorted auditory perception in first-episode psychosis.

PubMed

Morenz, Rachel; Woolverton, Cindy; Frost, R Brock; Kiewel, Nicole A; Breitborde, Nicholas J K

2015-06-01

Auditory hallucinations are hypothesized to be based in distorted sensory perceptions, with increasingly distorted perceptions of reality possibly prompting the first psychotic phase of schizophrenia spectrum disorders. Our goal was to examine the association between distorted auditory perceptions and psychotic symptomatology, social functioning and quality of life among individuals with first-episode psychosis. Forty individuals with first-episode psychosis completed assessments of distorted auditory perception, psychotic symptomatology, social functioning and quality of life. Both negative (greater symptomatology) and positive clinical correlates (better quality of life) were associated with greater distorted auditory perceptions. Our findings suggest that distorted auditory perceptions are associated with both positive and negative clinical correlates among individuals with first-episode psychosis. These results highlight the potential clinical importance of balancing the goal of symptomatic reduction with the need to maintain healthy coping strategies that may be biologically and psychologically entwined with the symptoms of psychosis, themselves. © 2014 Wiley Publishing Asia Pty Ltd.

Closed-Loop Control of a Neuroprosthetic Hand by Magnetoencephalographic Signals.

PubMed

Fukuma, Ryohei; Yanagisawa, Takufumi; Yorifuji, Shiro; Kato, Ryu; Yokoi, Hiroshi; Hirata, Masayuki; Saitoh, Youichi; Kishima, Haruhiko; Kamitani, Yukiyasu; Yoshimine, Toshiki

2015-01-01

A neuroprosthesis using a brain-machine interface (BMI) is a promising therapeutic option for severely paralyzed patients, but the ability to control it may vary among individual patients and needs to be evaluated before any invasive procedure is undertaken. We have developed a neuroprosthetic hand that can be controlled by magnetoencephalographic (MEG) signals to noninvasively evaluate subjects' ability to control a neuroprosthesis. Six nonparalyzed subjects performed grasping or opening movements of their right hand while the slow components of the MEG signals (SMFs) were recorded in an open-loop condition. The SMFs were used to train two decoders to infer the timing and types of movement by support vector machine and Gaussian process regression. The SMFs were also used to calculate estimated slow cortical potentials (eSCPs) to identify the origin of motor information. Finally, using the trained decoders, the subjects controlled a neuroprosthetic hand in a closed-loop condition. The SMFs in the open-loop condition revealed movement-related cortical field characteristics and successfully inferred the movement type with an accuracy of 75.0 ± 12.9% (mean ± SD). In particular, the eSCPs in the sensorimotor cortex contralateral to the moved hand varied significantly enough among the movement types to be decoded with an accuracy of 76.5 ± 10.6%, which was significantly higher than the accuracy associated with eSCPs in the ipsilateral sensorimotor cortex (58.1 ± 13.7%; p = 0.0072, paired two-tailed Student's t-test). Moreover, another decoder using SMFs successfully inferred when the accuracy was the greatest. Combining these two decoders allowed the neuroprosthetic hand to be controlled in a closed-loop condition. Use of real-time MEG signals was shown to successfully control the neuroprosthetic hand. The developed system may be useful for evaluating movement-related slow cortical potentials of severely paralyzed patients to predict the efficacy of invasive BMI.

Closed-Loop Control of a Neuroprosthetic Hand by Magnetoencephalographic Signals

PubMed Central

Fukuma, Ryohei; Yanagisawa, Takufumi; Yorifuji, Shiro; Kato, Ryu; Yokoi, Hiroshi; Hirata, Masayuki; Saitoh, Youichi; Kishima, Haruhiko; Kamitani, Yukiyasu; Yoshimine, Toshiki

2015-01-01

Objective A neuroprosthesis using a brain–machine interface (BMI) is a promising therapeutic option for severely paralyzed patients, but the ability to control it may vary among individual patients and needs to be evaluated before any invasive procedure is undertaken. We have developed a neuroprosthetic hand that can be controlled by magnetoencephalographic (MEG) signals to noninvasively evaluate subjects’ ability to control a neuroprosthesis. Method Six nonparalyzed subjects performed grasping or opening movements of their right hand while the slow components of the MEG signals (SMFs) were recorded in an open-loop condition. The SMFs were used to train two decoders to infer the timing and types of movement by support vector machine and Gaussian process regression. The SMFs were also used to calculate estimated slow cortical potentials (eSCPs) to identify the origin of motor information. Finally, using the trained decoders, the subjects controlled a neuroprosthetic hand in a closed-loop condition. Results The SMFs in the open-loop condition revealed movement-related cortical field characteristics and successfully inferred the movement type with an accuracy of 75.0 ± 12.9% (mean ± SD). In particular, the eSCPs in the sensorimotor cortex contralateral to the moved hand varied significantly enough among the movement types to be decoded with an accuracy of 76.5 ± 10.6%, which was significantly higher than the accuracy associated with eSCPs in the ipsilateral sensorimotor cortex (58.1 ± 13.7%; p = 0.0072, paired two-tailed Student’s t-test). Moreover, another decoder using SMFs successfully inferred when the accuracy was the greatest. Combining these two decoders allowed the neuroprosthetic hand to be controlled in a closed-loop condition. Conclusions Use of real-time MEG signals was shown to successfully control the neuroprosthetic hand. The developed system may be useful for evaluating movement-related slow cortical potentials of severely paralyzed patients to predict the efficacy of invasive BMI. PMID:26134845

A Comparative Case Study of Learning Strategies and Recommendations of Five Professional Musicians with Dyslexia

ERIC Educational Resources Information Center

Nelson, Kent Peter; Hourigan, Ryan M.

2016-01-01

Many of the characteristics of dyslexia--such as difficulties with decoding written symbols, phonemic awareness, physical coordination, and readable handwriting--may adversely affect music learning. Despite challenges, individuals with dyslexia can succeed in music. The purpose of this study was to examine the perceptions of five professional…

Meaningful Reading Gains by Adult Literacy Learners

ERIC Educational Resources Information Center

Scarborough, Hollis S.; Sabatini, John P.; Shore, Jane; Cutting, Laurie E.; Pugh, Kenneth; Katz, Leonard

2013-01-01

To obtain a fuller picture of the efficacy of reading instruction programs for adult literacy learners, gains by individual students were examined in a sample (n = 148) in which weak to moderate gains at the group level had been obtained in response to tutoring interventions that focused on strengthening basic decoding and fluency skills of low…

Multimodal Alexia: Neuropsychological Mechanisms and Implications for Treatment

ERIC Educational Resources Information Center

Kim, Esther S.; Rapcsak, Steven Z.; Andersen, Sarah; Beeson, Pelagie M.

2011-01-01

Letter-by-letter (LBL) reading is the phenomenon whereby individuals with acquired alexia decode words by sequential identification of component letters. In cases where letter recognition or letter naming is impaired, however, a LBL reading approach is obviated, resulting in a nearly complete inability to read, or global alexia. In some such…

The Teacher as Communicator: An Aspect of Teacher Effectiveness.

ERIC Educational Resources Information Center

Olson, David R.; And Others

Experiments were devised to determine teacher effectiveness on the basis of ability to communicate, on the assumption that no relevant learning will occur if communication is faulty. A series of communication games involved an encoder (teacher) and decoder (student) to provide tentative answers to the questions: 1) Are there individual differences…

Decoding Success: A Middle-Class Logic of Individual Advancement in a U.S. Suburb and High School

ERIC Educational Resources Information Center

Demerath, Peter; Lynch, Jill; Milner, H. Richard, IV; Peters, April; Davidson, Mario

2010-01-01

Background: Researchers have largely attributed achievement gaps between different groups of students in the United States to differences in resources, parent education, socioeconomic status (SES), and school quality. They have also shown how, through their "cultural productions," certain students may disadvantage themselves. Focus: This article…

The Impact of New Technologies on the Literacy Attainment of Deaf Children

ERIC Educational Resources Information Center

Harris, Margaret

2015-01-01

To become successful readers, hearing children require competence in both decoding--the ability to read individual words, underpinned by phonological skills and letter-sound knowledge--and linguistic comprehension--the ability to understand what they read--underpinned by language skills, including vocabulary knowledge. Children who are born with a…

Temperament and character profiles of Japanese university students with depressive episodes and ideas of suicide or self-harm: a PHQ-9 screening study.

PubMed

Mitsui, Nobuyuki; Asakura, Satoshi; Shimizu, Yusuke; Fujii, Yutaka; Kako, Yuki; Tanaka, Teruaki; Oba, Koji; Inoue, Takeshi; Kusumi, Ichiro

2013-11-01

The aim of our study was to reveal the personality traits of individuals with major and other depressive episodes among the young adult population. Furthermore, character traits of individuals with ideas of suicide or self-harm were also investigated in this study. The subjects of this study were 1421 university students who completed the Patient Health Questionnaire (PHQ-9) and the Temperament and Character Inventory (TCI). The subjects were divided into three separate groups: the major depressive episode group (N = 41), the other depressive episode group (N = 97), and the non-depressive controls (N = 1283). This separation was achieved using the PHQ-9 algorithm diagnosis. We compared the TCI scores using an analysis of variance. Moreover, the Cochran-Armitage trend test was used to determine the diagnosis, ideas of suicide or self-harm, and analysis of character profiles. The major depressive episode group had significantly higher HA (P < 0.001), lower RD (P < 0.001), lower SD (P < 0.001), and lower C (P < 0.001) scores than non-depressive controls. The other depressive episode group had significantly higher HA scores (P < 0.001) and lower SD scores (P < 0.001) than non-depressive controls. The Cochran-Armitage trend test revealed that the prevalence of depressive episodes decreased as the character profiles matured (χ(2)(trend) = 57.2, P < 0.0001). The same tendency was observed in individuals who had ideas of suicide or self-harm (χ(2)(trend) = 49.3, P < 0.0001). High HA and low SD scores were common personality traits among young adults with major depressive episodes. Furthermore, the immaturity of character profiles was clearly associated with depressive episodes and ideas of suicide or self-harm. Copyright © 2013 Elsevier Inc. All rights reserved.

Characters and clues: Factors affecting children’s extension of knowledge through integration of separate episodes

PubMed Central

Bauer, Patricia J.; King, Jessica E.; Larkina, Marina; Varga, Nicole L.; White, Elizabeth A.

2012-01-01

Children build up knowledge about the world and also remember individual episodes. How individual episodes during which children learn new things become integrated with one another to form general knowledge is only beginning to be explored. Integration between separate episodes is called on in educational contexts and in everyday life as a major means of extending knowledge and organizing information. Bauer and San Souci (2010) provided an initial demonstration that 6-year-olds extend their knowledge by integrating between separate but related episodes; the episodes shared a high level of surface similarity. Experiments 1A and 1B of the current research were tests of integration under low and high levels of surface similarity, respectively. In Experiment 1A, when surface similarity of the episodes was low, 6-year-olds integrated between passages of text, yet their performance was not as robust as observed previously. In Experiment 1B, when surface similarity of the episodes was high, a replication of Bauer and San Souci’s results was observed. In Experiment 2, we tested whether a “hint” to consult the information learned in the passages improved performance even when surface level similarity was low. The hint had a strong facilitating effect. Possible mechanisms of integration between separate yet related episodes are discussed. PMID:22153911

Hawaiian fissure fountains 1: decoding deposits-episode 1 of the 1969-1974 Mauna Ulu eruption

USGS Publications Warehouse

Parcheta, C.E.; Houghton, Bruce F.; Swanson, D.A.

2012-01-01

Deposits from episode 1 of the 1969–1974 Mauna Ulu eruption of Kīlauea provide an exceptional opportunity to study processes of low intensity Hawaiian fissure fountains. Episode 1 lava flows passed through dense forest that had little impact on flow dynamics; in contrast, the pattern of spatter preservation was strongly influenced by the forest (through the formation of tree molds) and the preexisting topography. A low, near-continuous spatter rampart is present upwind and upslope, on the north side of the fissure. Most of the pyroclastic products, however, fell downwind to the south of the fissure, but little was preserved due to two processes: (1) incorporation of proximal spatter in rheomorphic lava flows 10–20 m from the vents, and (2) the downslope transport of cooler spatter falling on top of these flows beyond 20 m from vent. The lava flow field itself shows a complex history. Initially, discharge from the fissure exceeded the transport capacity of the southern drainage pathways, and lava ponded dynamically to a maximum height of 4 m for 40–120 min, until fountains began to decline. During declining discharge, lava flowed both southward away from the fissure and increasingly back into the vents. There is a clear “lava-shed” or delineation between where lava drained northwards back into the fissure, and where it continued flowing to the south. The 1969 deposits suggest that care is needed when products of less well-documented eruptions are analyzed, as postdepositional transport of spatter may preclude the formation of classic paired (symmetrical) ramparts.

Simultaneous real-time monitoring of multiple cortical systems.

PubMed

Gupta, Disha; Jeremy Hill, N; Brunner, Peter; Gunduz, Aysegul; Ritaccio, Anthony L; Schalk, Gerwin

2014-10-01

Real-time monitoring of the brain is potentially valuable for performance monitoring, communication, training or rehabilitation. In natural situations, the brain performs a complex mix of various sensory, motor or cognitive functions. Thus, real-time brain monitoring would be most valuable if (a) it could decode information from multiple brain systems simultaneously, and (b) this decoding of each brain system were robust to variations in the activity of other (unrelated) brain systems. Previous studies showed that it is possible to decode some information from different brain systems in retrospect and/or in isolation. In our study, we set out to determine whether it is possible to simultaneously decode important information about a user from different brain systems in real time, and to evaluate the impact of concurrent activity in different brain systems on decoding performance. We study these questions using electrocorticographic signals recorded in humans. We first document procedures for generating stable decoding models given little training data, and then report their use for offline and for real-time decoding from 12 subjects (six for offline parameter optimization, six for online experimentation). The subjects engage in tasks that involve movement intention, movement execution and auditory functions, separately, and then simultaneously. Main Results: Our real-time results demonstrate that our system can identify intention and movement periods in single trials with an accuracy of 80.4% and 86.8%, respectively (where 50% would be expected by chance). Simultaneously, the decoding of the power envelope of an auditory stimulus resulted in an average correlation coefficient of 0.37 between the actual and decoded power envelopes. These decoders were trained separately and executed simultaneously in real time. This study yielded the first demonstration that it is possible to decode simultaneously the functional activity of multiple independent brain systems. Our comparison of univariate and multivariate decoding strategies, and our analysis of the influence of their decoding parameters, provides benchmarks and guidelines for future research on this topic.

Simultaneous Real-Time Monitoring of Multiple Cortical Systems

PubMed Central

Gupta, Disha; Hill, N. Jeremy; Brunner, Peter; Gunduz, Aysegul; Ritaccio, Anthony L.; Schalk, Gerwin

2014-01-01

Objective Real-time monitoring of the brain is potentially valuable for performance monitoring, communication, training or rehabilitation. In natural situations, the brain performs a complex mix of various sensory, motor, or cognitive functions. Thus, real-time brain monitoring would be most valuable if (a) it could decode information from multiple brain systems simultaneously, and (b) this decoding of each brain system were robust to variations in the activity of other (unrelated) brain systems. Previous studies showed that it is possible to decode some information from different brain systems in retrospect and/or in isolation. In our study, we set out to determine whether it is possible to simultaneously decode important information about a user from different brain systems in real time, and to evaluate the impact of concurrent activity in different brain systems on decoding performance. Approach We study these questions using electrocorticographic (ECoG) signals recorded in humans. We first document procedures for generating stable decoding models given little training data, and then report their use for offline and for real-time decoding from 12 subjects (6 for offline parameter optimization, 6 for online experimentation). The subjects engage in tasks that involve movement intention, movement execution and auditory functions, separately, and then simultaneously. Main results Our real-time results demonstrate that our system can identify intention and movement periods in single trials with an accuracy of 80.4% and 86.8%, respectively (where 50% would be expected by chance). Simultaneously, the decoding of the power envelope of an auditory stimulus resulted in an average correlation coefficient of 0.37 between the actual and decoded power envelope. These decoders were trained separately and executed simultaneously in real time. Significance This study yielded the first demonstration that it is possible to decode simultaneously the functional activity of multiple independent brain systems. Our comparison of univariate and multivariate decoding strategies, and our analysis of the influence of their decoding parameters, provides benchmarks and guidelines for future research on this topic. PMID:25080161

The ribosome as an optimal decoder: a lesson in molecular recognition.

PubMed

Savir, Yonatan; Tlusty, Tsvi

2013-04-11

The ribosome is a complex molecular machine that, in order to synthesize proteins, has to decode mRNAs by pairing their codons with matching tRNAs. Decoding is a major determinant of fitness and requires accurate and fast selection of correct tRNAs among many similar competitors. However, it is unclear whether the modern ribosome, and in particular its large conformational changes during decoding, are the outcome of adaptation to its task as a decoder or the result of other constraints. Here, we derive the energy landscape that provides optimal discrimination between competing substrates and thereby optimal tRNA decoding. We show that the measured landscape of the prokaryotic ribosome is sculpted in this way. This model suggests that conformational changes of the ribosome and tRNA during decoding are means to obtain an optimal decoder. Our analysis puts forward a generic mechanism that may be utilized broadly by molecular recognition systems. Copyright © 2013 Elsevier Inc. All rights reserved.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; An Iterative Decoding Algorithm for Linear Block Codes Based on a Low-Weight Trellis Search

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc

1998-01-01

For long linear block codes, maximum likelihood decoding based on full code trellises would be very hard to implement if not impossible. In this case, we may wish to trade error performance for the reduction in decoding complexity. Sub-optimum soft-decision decoding of a linear block code based on a low-weight sub-trellis can be devised to provide an effective trade-off between error performance and decoding complexity. This chapter presents such a suboptimal decoding algorithm for linear block codes. This decoding algorithm is iterative in nature and based on an optimality test. It has the following important features: (1) a simple method to generate a sequence of candidate code-words, one at a time, for test; (2) a sufficient condition for testing a candidate code-word for optimality; and (3) a low-weight sub-trellis search for finding the most likely (ML) code-word.

Enhanced decoding for the Galileo S-band mission

NASA Technical Reports Server (NTRS)

Dolinar, S.; Belongie, M.

1993-01-01

A coding system under consideration for the Galileo S-band low-gain antenna mission is a concatenated system using a variable redundancy Reed-Solomon outer code and a (14,1/4) convolutional inner code. The 8-bit Reed-Solomon symbols are interleaved to depth 8, and the eight 255-symbol codewords in each interleaved block have redundancies 64, 20, 20, 20, 64, 20, 20, and 20, respectively (or equivalently, the codewords have 191, 235, 235, 235, 191, 235, 235, and 235 8-bit information symbols, respectively). This concatenated code is to be decoded by an enhanced decoder that utilizes a maximum likelihood (Viterbi) convolutional decoder; a Reed Solomon decoder capable of processing erasures; an algorithm for declaring erasures in undecoded codewords based on known erroneous symbols in neighboring decodable words; a second Viterbi decoding operation (redecoding) constrained to follow only paths consistent with the known symbols from previously decodable Reed-Solomon codewords; and a second Reed-Solomon decoding operation using the output from the Viterbi redecoder and additional erasure declarations to the extent possible. It is estimated that this code and decoder can achieve a decoded bit error rate of 1 x 10(exp 7) at a concatenated code signal-to-noise ratio of 0.76 dB. By comparison, a threshold of 1.17 dB is required for a baseline coding system consisting of the same (14,1/4) convolutional code, a (255,223) Reed-Solomon code with constant redundancy 32 also interleaved to depth 8, a one-pass Viterbi decoder, and a Reed Solomon decoder incapable of declaring or utilizing erasures. The relative gain of the enhanced system is thus 0.41 dB. It is predicted from analysis based on an assumption of infinite interleaving that the coding gain could be further improved by approximately 0.2 dB if four stages of Viterbi decoding and four levels of Reed-Solomon redundancy are permitted. Confirmation of this effect and specification of the optimum four-level redundancy profile for depth-8 interleaving is currently being done.

Multi-stage decoding of multi-level modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data.

PubMed

Grootswagers, Tijl; Wardle, Susan G; Carlson, Thomas A

2017-04-01

Multivariate pattern analysis (MVPA) or brain decoding methods have become standard practice in analyzing fMRI data. Although decoding methods have been extensively applied in brain-computer interfaces, these methods have only recently been applied to time series neuroimaging data such as MEG and EEG to address experimental questions in cognitive neuroscience. In a tutorial style review, we describe a broad set of options to inform future time series decoding studies from a cognitive neuroscience perspective. Using example MEG data, we illustrate the effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to "decode" different perceptual stimuli or cognitive states over time from dynamic brain activation patterns. We show that decisions made at both preprocessing (e.g., dimensionality reduction, subsampling, trial averaging) and decoding (e.g., classifier selection, cross-validation design) stages of the analysis can significantly affect the results. In addition to standard decoding, we describe extensions to MVPA for time-varying neuroimaging data including representational similarity analysis, temporal generalization, and the interpretation of classifier weight maps. Finally, we outline important caveats in the design and interpretation of time series decoding experiments.

A Parallel Decoding Algorithm for Short Polar Codes Based on Error Checking and Correcting

PubMed Central

Pan, Xiaofei; Pan, Kegang; Ye, Zhan; Gong, Chao

2014-01-01

We propose a parallel decoding algorithm based on error checking and correcting to improve the performance of the short polar codes. In order to enhance the error-correcting capacity of the decoding algorithm, we first derive the error-checking equations generated on the basis of the frozen nodes, and then we introduce the method to check the errors in the input nodes of the decoder by the solutions of these equations. In order to further correct those checked errors, we adopt the method of modifying the probability messages of the error nodes with constant values according to the maximization principle. Due to the existence of multiple solutions of the error-checking equations, we formulate a CRC-aided optimization problem of finding the optimal solution with three different target functions, so as to improve the accuracy of error checking. Besides, in order to increase the throughput of decoding, we use a parallel method based on the decoding tree to calculate probability messages of all the nodes in the decoder. Numerical results show that the proposed decoding algorithm achieves better performance than that of some existing decoding algorithms with the same code length. PMID:25540813

Meta-cognitive skills training enhances computerized cognitive remediation outcomes among individuals with first-episode psychosis.

PubMed

Breitborde, Nicholas J K; Woolverton, Cindy; Dawson, Spencer C; Bismark, Andrew; Bell, Emily K; Bathgate, Christina J; Norman, Kaila

2017-06-01

Meta-cognitive skills training (MST) is a frequent component of cognitive remediation programmes for individuals with psychosis. However, no study has investigated whether incorporating such activities produces increased clinical benefits compared with computerized cognitive remediation alone. Individuals with first-episode psychosis who completed computerized cognitive remediation with concurrent meta-cognitive skills training (CCR + MST) were compared with a historical control group who received computerized cognitive remediation alone (CCR) and did not differ from the CCR + MST group with regard to pre-intervention cognition, diagnosis, age, duration of psychotic illness or sex. Participants completed assessments of cognition and real-world functioning before and after 6 months of treatment. Individual receiving CCR + MST experience greater gains in cognition and real-world functioning than individuals who received CCR. MST may be an important component within cognitive remediation programmes for first-episode psychosis. © 2015 Wiley Publishing Asia Pty Ltd.

Decoding Facial Expressions: A New Test with Decoding Norms.

ERIC Educational Resources Information Center

Leathers, Dale G.; Emigh, Ted H.

1980-01-01

Describes the development and testing of a new facial meaning sensitivity test designed to determine how specialized are the meanings that can be decoded from facial expressions. Demonstrates the use of the test to measure a receiver's current level of skill in decoding facial expressions. (JMF)

Edge-Related Activity Is Not Necessary to Explain Orientation Decoding in Human Visual Cortex.

PubMed

Wardle, Susan G; Ritchie, J Brendan; Seymour, Kiley; Carlson, Thomas A

2017-02-01

Multivariate pattern analysis is a powerful technique; however, a significant theoretical limitation in neuroscience is the ambiguity in interpreting the source of decodable information used by classifiers. This is exemplified by the continued controversy over the source of orientation decoding from fMRI responses in human V1. Recently Carlson (2014) identified a potential source of decodable information by modeling voxel responses based on the Hubel and Wiesel (1972) ice-cube model of visual cortex. The model revealed that activity associated with the edges of gratings covaries with orientation and could potentially be used to discriminate orientation. Here we empirically evaluate whether "edge-related activity" underlies orientation decoding from patterns of BOLD response in human V1. First, we systematically mapped classifier performance as a function of stimulus location using population receptive field modeling to isolate each voxel's overlap with a large annular grating stimulus. Orientation was decodable across the stimulus; however, peak decoding performance occurred for voxels with receptive fields closer to the fovea and overlapping with the inner edge. Critically, we did not observe the expected second peak in decoding performance at the outer stimulus edge as predicted by the edge account. Second, we evaluated whether voxels that contribute most to classifier performance have receptive fields that cluster in cortical regions corresponding to the retinotopic location of the stimulus edge. Instead, we find the distribution of highly weighted voxels to be approximately random, with a modest bias toward more foveal voxels. Our results demonstrate that edge-related activity is likely not necessary for orientation decoding. A significant theoretical limitation of multivariate pattern analysis in neuroscience is the ambiguity in interpreting the source of decodable information used by classifiers. For example, orientation can be decoded from BOLD activation patterns in human V1, even though orientation columns are at a finer spatial scale than 3T fMRI. Consequently, the source of decodable information remains controversial. Here we test the proposal that information related to the stimulus edges underlies orientation decoding. We map voxel population receptive fields in V1 and evaluate orientation decoding performance as a function of stimulus location in retinotopic cortex. We find orientation is decodable from voxels whose receptive fields do not overlap with the stimulus edges, suggesting edge-related activity does not substantially drive orientation decoding. Copyright © 2017 the authors 0270-6474/17/371187-10$15.00/0.

Tail Biting Trellis Representation of Codes: Decoding and Construction

NASA Technical Reports Server (NTRS)

Shao. Rose Y.; Lin, Shu; Fossorier, Marc

1999-01-01

This paper presents two new iterative algorithms for decoding linear codes based on their tail biting trellises, one is unidirectional and the other is bidirectional. Both algorithms are computationally efficient and achieves virtually optimum error performance with a small number of decoding iterations. They outperform all the previous suboptimal decoding algorithms. The bidirectional algorithm also reduces decoding delay. Also presented in the paper is a method for constructing tail biting trellises for linear block codes.

Visual perception as retrospective Bayesian decoding from high- to low-level features.

PubMed

Ding, Stephanie; Cueva, Christopher J; Tsodyks, Misha; Qian, Ning

2017-10-24

When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. Published under the PNAS license.

A subject-independent pattern-based Brain-Computer Interface

PubMed Central

Ray, Andreas M.; Sitaram, Ranganatha; Rana, Mohit; Pasqualotto, Emanuele; Buyukturkoglu, Korhan; Guan, Cuntai; Ang, Kai-Keng; Tejos, Cristián; Zamorano, Francisco; Aboitiz, Francisco; Birbaumer, Niels; Ruiz, Sergio

2015-01-01

While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG) signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs) from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e., happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to “match” their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders. PMID:26539089

Playing charades in the fMRI: are mirror and/or mentalizing areas involved in gestural communication?

PubMed

Schippers, Marleen B; Gazzola, Valeria; Goebel, Rainer; Keysers, Christian

2009-08-27

Communication is an important aspect of human life, allowing us to powerfully coordinate our behaviour with that of others. Boiled down to its mere essentials, communication entails transferring a mental content from one brain to another. Spoken language obviously plays an important role in communication between human individuals. Manual gestures however often aid the semantic interpretation of the spoken message, and gestures may have played a central role in the earlier evolution of communication. Here we used the social game of charades to investigate the neural basis of gestural communication by having participants produce and interpret meaningful gestures while their brain activity was measured using functional magnetic resonance imaging. While participants decoded observed gestures, the putative mirror neuron system (pMNS: premotor, parietal and posterior mid-temporal cortex), associated with motor simulation, and the temporo-parietal junction (TPJ), associated with mentalizing and agency attribution, were significantly recruited. Of these areas only the pMNS was recruited during the production of gestures. This suggests that gestural communication relies on a combination of simulation and, during decoding, mentalizing/agency attribution brain areas. Comparing the decoding of gestures with a condition in which participants viewed the same gestures with an instruction not to interpret the gestures showed that although parts of the pMNS responded more strongly during active decoding, most of the pMNS and the TPJ did not show such significant task effects. This suggests that the mere observation of gestures recruits most of the system involved in voluntary interpretation.

Decoding and Encoding Facial Expressions in Preschool-Age Children.

ERIC Educational Resources Information Center

Zuckerman, Miron; Przewuzman, Sylvia J.

1979-01-01

Preschool-age children drew, decoded, and encoded facial expressions depicting five different emotions. Accuracy of drawing, decoding and encoding each of the five emotions was consistent across the three tasks; decoding ability was correlated with drawing ability among female subjects, but neither of these abilities was correlated with encoding…

Multichannel error correction code decoder

NASA Technical Reports Server (NTRS)

Wagner, Paul K.; Ivancic, William D.

1993-01-01

A brief overview of a processing satellite for a mesh very-small-aperture (VSAT) communications network is provided. The multichannel error correction code (ECC) decoder system, the uplink signal generation and link simulation equipment, and the time-shared decoder are described. The testing is discussed. Applications of the time-shared decoder are recommended.

Gender identity better than sex explains individual differences in episodic and semantic components of autobiographical memory and future thinking.

PubMed

Compère, Laurie; Rari, Eirini; Gallarda, Thierry; Assens, Adèle; Nys, Marion; Coussinoux, Sandrine; Machefaux, Sébastien; Piolino, Pascale

2018-01-01

A recently tested hypothesis suggests that inter-individual differences in episodic autobiographical memory (EAM) are better explained by individual identification of typical features of a gender identity than by sex. This study aimed to test this hypothesis by investigating sex and gender related differences not only in EAM but also during retrieval of more abstract self-knowledge (i.e., semantic autobiographical memory, SAM, and conceptual self, CS), and considering past and future perspectives. No sex-related differences were identified, but regardless of the sex, feminine gender identity was associated with clear differences in emotional aspects that were expressed in both episodic and more abstract forms of AM, and in the past and future perspectives, while masculine gender identity was associated with limited effects. In conclusion, our results support the hypothesis that inter-individual differences in AM are better explained by gender identity than by sex, extending this assumption to both episodic and semantic forms of AM and future thinking. Copyright © 2017 Elsevier Inc. All rights reserved.

A software simulation study of a (255,223) Reed-Solomon encoder-decoder

NASA Technical Reports Server (NTRS)

Pollara, F.

1985-01-01

A set of software programs which simulates a (255,223) Reed-Solomon encoder/decoder pair is described. The transform decoder algorithm uses a modified Euclid algorithm, and closely follows the pipeline architecture proposed for the hardware decoder. Uncorrectable error patterns are detected by a simple test, and the inverse transform is computed by a finite field FFT. Numerical examples of the decoder operation are given for some test codewords, with and without errors. The use of the software package is briefly described.

First-episode psychosis in the criminal justice system: identifying a critical intercept for early intervention.

PubMed

Ford, Elizabeth

2015-01-01

After participating in this activity, learners should be better able to:Evaluate emerging concepts of identification, treatment and discharge planning for individuals who are experiencing a first psychotic episode while detained in the criminal justice system. The United States incarcerates more people than any other nation in the world. The system of jails and prisons that holds those individuals has become the largest provider of mental health care in the country, with rates of psychotic illness many times higher than in the community. A subset of this population includes individuals experiencing their first episode of psychosis who are untreated and are new to the rules of institutional settings. Retrospective and anecdotal reports indicate that many individuals in the criminal justice system have first-episode psychosis, yet no published information is available about the actual rates. For these patients, behavior associated with psychotic symptoms may have led to their arrest, but correctional facilities are poorly equipped to identify their needs and to provide the type of comprehensive treatment needed to improve functional status, quality of life, and illness recovery. Even as first-episode programs are flourishing in community settings, we know little about how to identify, engage, possibly divert, and treat these patients in settings designed as punishment. Efforts should be made both to reduce the number of these individuals inappropriately prosecuted within the criminal justice system and to begin in-jail efforts to engage them in treatment, in anticipation of their eventual return to the community.

Error-trellis syndrome decoding techniques for convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1985-01-01

An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decordig is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

Medial temporal lobe structure and cognition in individuals with schizophrenia and in their non-psychotic siblings.

PubMed

Karnik-Henry, Meghana S; Wang, Lei; Barch, Deanna M; Harms, Michael P; Campanella, Carolina; Csernansky, John G

2012-07-01

Medial temporal lobe (MTL) structures play a central role in episodic memory. Prior studies suggest that individuals with schizophrenia have deficits in episodic memory as well as structural abnormalities of the medial temporal lobe (MTL). While correlations have been reported between MTL volume loss and episodic memory deficits in such individuals, it is not clear whether such correlations reflect the influence of the disease state or of underlying genetic influences that might contribute to risk. We used high resolution magnetic resonance imaging and probabilistic algorithms for image analysis to determine whether MTL structure, episodic memory performance and the relationship between the two differed among groups of 47 healthy control subjects, 50 control siblings, 39 schizophrenia subjects, and 33 siblings of schizophrenia subjects. High-dimensional large deformation brain mapping was used to obtain volume measures of the hippocampus. Cortical distance mapping was used to obtain volume and thickness measures of the parahippocampal gyrus (PHG) and its substructures: the entorhinal cortex (ERC), the perirhinal cortex (PRC), and the parahippocampal cortex (PHC). Neuropsychological data was used to establish an episodic memory domain score for each subject. Both schizophrenia subjects and their siblings displayed abnormalities in episodic memory performance. Siblings of individuals with schizophrenia, and to a lesser extent, individuals with schizophrenia themselves, displayed abnormalities in measures of MTL structure (volume loss or cortical thinning) as compared to control groups. Further, we observed correlations between structural measures and memory performance in both schizophrenia subjects and their siblings, but not in their respective control groups. These findings suggest that disease-specific genetic factors present in both patients and their relatives may be responsible for correlated abnormalities of MTL structure and memory impairment. The observed attenuated effect of such factors on MTL structure in individuals with schizophrenia may be due to non-genetic influences related to the development and progression of the disease on global brain structure and cognitive processing. Copyright © 2012 Elsevier B.V. All rights reserved.

Heavy episodic drinking is a trait-state: a cautionary note.

PubMed

Mushquash, Aislin R; Sherry, Simon B; Mackinnon, Sean P; Mushquash, Christopher J; Stewart, Sherry H

2014-01-01

Heavy episodic (binge) drinking is common in and problematic for undergraduates. Researchers often assume that an individual's heavy episodic drinking is stable and trait-like. However, this fails to consider fluctuating, state-like variation in heavy episodic drinking. This study proposes and tests a novel conceptualization of heavy episodic drinking as a trait-state wherein the contribution of both trait-like stability and state-like fluctuations are quantified. It was hypothesized that heavy episodic drinking is a trait-state such that individuals have trait-like tendencies to engage in heavy episodic drinking, and state-like differences in the expression of this tendency over time. A sample of 114 first-year undergraduates from a Canadian university completed self-report measures of heavy episodic drinking at 3 time points across 130 days. Hypotheses were tested with repeated-measures analysis of variance (ANOVA), test-retest correlations, and generalizability theory analyses. A substantial proportion of the variance in heavy episodic drinking is attributable to trait-like stability, with a smaller proportion attributable to state-like fluctuations. The heavy episodic drinker seems characterized by a stable, trait-like tendency to drink in a risky manner, and this trait-like tendency seems to fluctuate in degree of expression over time. Findings complement research suggesting that people have trait-like predispositions that increase their risk for heavy episodic drinking. However, despite this stable tendency to drink heavily, the frequency of heavy episodic drinking appears to be at least partly sporadic or situation dependent. These findings serve as a caution to alcohol researchers and clinicians who often assume that a single assessment of heavy episodic drinking captures a person's usual drinking behavior.

High data rate Reed-Solomon encoding and decoding using VLSI technology

NASA Technical Reports Server (NTRS)

Miller, Warner; Morakis, James

1987-01-01

Presented as an implementation of a Reed-Solomon encode and decoder, which is 16-symbol error correcting, each symbol is 8 bits. This Reed-Solomon (RS) code is an efficient error correcting code that the National Aeronautics and Space Administration (NASA) will use in future space communications missions. A Very Large Scale Integration (VLSI) implementation of the encoder and decoder accepts data rates up 80 Mbps. A total of seven chips are needed for the decoder (four of the seven decoding chips are customized using 3-micron Complementary Metal Oxide Semiconduction (CMOS) technology) and one chip is required for the encoder. The decoder operates with the symbol clock being the system clock for the chip set. Approximately 1.65 billion Galois Field (GF) operations per second are achieved with the decoder chip set and 640 MOPS are achieved with the encoder chip.

The basis of orientation decoding in human primary visual cortex: fine- or coarse-scale biases?

PubMed

Maloney, Ryan T

2015-01-01

Orientation signals in human primary visual cortex (V1) can be reliably decoded from the multivariate pattern of activity as measured with functional magnetic resonance imaging (fMRI). The precise underlying source of these decoded signals (whether by orientation biases at a fine or coarse scale in cortex) remains a matter of some controversy, however. Freeman and colleagues (J Neurosci 33: 19695-19703, 2013) recently showed that the accuracy of decoding of spiral patterns in V1 can be predicted by a voxel's preferred spatial position (the population receptive field) and its coarse orientation preference, suggesting that coarse-scale biases are sufficient for orientation decoding. Whether they are also necessary for decoding remains an open question, and one with implications for the broader interpretation of multivariate decoding results in fMRI studies. Copyright © 2015 the American Physiological Society.

Emotion Decoding and Incidental Processing Fluency as Antecedents of Attitude Certainty.

PubMed

Petrocelli, John V; Whitmire, Melanie B

2017-07-01

Previous research demonstrates that attitude certainty influences the degree to which an attitude changes in response to persuasive appeals. In the current research, decoding emotions from facial expressions and incidental processing fluency, during attitude formation, are examined as antecedents of both attitude certainty and attitude change. In Experiment 1, participants who decoded anger or happiness during attitude formation expressed their greater attitude certainty, and showed more resistance to persuasion than participants who decoded sadness. By manipulating the emotion decoded, the diagnosticity of processing fluency experienced during emotion decoding, and the gaze direction of the social targets, Experiment 2 suggests that the link between emotion decoding and attitude certainty results from incidental processing fluency. Experiment 3 demonstrated that fluency in processing irrelevant stimuli influences attitude certainty, which in turn influences resistance to persuasion. Implications for appraisal-based accounts of attitude formation and attitude change are discussed.

Deep Learning Methods for Improved Decoding of Linear Codes

NASA Astrophysics Data System (ADS)

Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair

2018-02-01

The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.

Decoding Children's Expressions of Affect.

ERIC Educational Resources Information Center

Feinman, Joel A.; Feldman, Robert S.

Mothers' ability to decode the emotional expressions of their male and female children was compared to the decoding ability of non-mothers. Happiness, sadness, fear and anger were induced in children in situations that varied in terms of spontaneous and role-played encoding modes. It was hypothesized that mothers would be more accurate decoders of…

Decoding Area Studies and Interdisciplinary Majors: Building a Framework for Entry-Level Students

ERIC Educational Resources Information Center

MacPherson, Kristina Ruth

2015-01-01

Decoding disciplinary expertise for novices is increasingly part of the undergraduate curriculum. But how might area studies and other interdisciplinary programs, which require integration of courses from multiple disciplines, decode expertise in a similar fashion? Additionally, as a part of decoding area studies and interdisciplines, how might a…

47 CFR 11.12 - Two-tone Attention Signal encoder and decoder.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 1 2011-10-01 2011-10-01 false Two-tone Attention Signal encoder and decoder... SYSTEM (EAS) General § 11.12 Two-tone Attention Signal encoder and decoder. Existing two-tone Attention Signal encoder and decoder equipment type accepted for use as Emergency Broadcast System equipment under...

47 CFR 11.12 - Two-tone Attention Signal encoder and decoder.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 1 2010-10-01 2010-10-01 false Two-tone Attention Signal encoder and decoder... SYSTEM (EAS) General § 11.12 Two-tone Attention Signal encoder and decoder. Existing two-tone Attention Signal encoder and decoder equipment type accepted for use as Emergency Broadcast System equipment under...

Sequential Syndrome Decoding of Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1984-01-01

The algebraic structure of convolutional codes are reviewed and sequential syndrome decoding is applied to those codes. These concepts are then used to realize by example actual sequential decoding, using the stack algorithm. The Fano metric for use in sequential decoding is modified so that it can be utilized to sequentially find the minimum weight error sequence.

On decoding of multi-level MPSK modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Gupta, Alok Kumar

1990-01-01

The decoding problem of multi-level block modulation codes is investigated. The hardware design of soft-decision Viterbi decoder for some short length 8-PSK block modulation codes is presented. An effective way to reduce the hardware complexity of the decoder by reducing the branch metric and path metric, using a non-uniform floating-point to integer mapping scheme, is proposed and discussed. The simulation results of the design are presented. The multi-stage decoding (MSD) of multi-level modulation codes is also investigated. The cases of soft-decision and hard-decision MSD are considered and their performance are evaluated for several codes of different lengths and different minimum squared Euclidean distances. It is shown that the soft-decision MSD reduces the decoding complexity drastically and it is suboptimum. The hard-decision MSD further simplifies the decoding while still maintaining a reasonable coding gain over the uncoded system, if the component codes are chosen properly. Finally, some basic 3-level 8-PSK modulation codes using BCH codes as component codes are constructed and their coding gains are found for hard decision multistage decoding.

Contributions of phonological awareness, phonological short-term memory, and rapid automated naming, toward decoding ability in students with mild intellectual disability.

PubMed

Soltani, Amanallah; Roslan, Samsilah

2013-03-01

Reading decoding ability is a fundamental skill to acquire word-specific orthographic information necessary for skilled reading. Decoding ability and its underlying phonological processing skills have been heavily investigated typically among developing students. However, the issue has rarely been noticed among students with intellectual disability who commonly suffer from reading decoding problems. This study is aimed at determining the contributions of phonological awareness, phonological short-term memory, and rapid automated naming, as three well known phonological processing skills, to decoding ability among 60 participants with mild intellectual disability of unspecified origin ranging from 15 to 23 years old. The results of the correlation analysis revealed that all three aspects of phonological processing are significantly correlated with decoding ability. Furthermore, a series of hierarchical regression analysis indicated that after controlling the effect of IQ, phonological awareness, and rapid automated naming are two distinct sources of decoding ability, but phonological short-term memory significantly contributes to decoding ability under the realm of phonological awareness. Copyright © 2013 Elsevier Ltd. All rights reserved.

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics.

PubMed

Prins, Noeline W; Sanchez, Justin C; Prasad, Abhishek

2017-06-01

For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-term goal is to create autonomous BMIs that can utilize an evaluative feedback from the brain to update the decoding algorithm and use it intelligently in order to adapt the decoder. In this study, we show how to extract the necessary evaluative feedback from a biologically realistic (synthetic) source, use both the quantity and the quality of the feedback, and how that feedback information can be incorporated into a reinforcement learning (RL) controller architecture to maximize its performance. Motivated by the perception-action-reward cycle (PARC) in the brain which links reward for cognitive decision making and goal-directed behavior, we used a reward-based RL architecture named Actor-Critic RL as the model. Instead of using an error signal towards building an autonomous BMI, we envision to use a reward signal from the nucleus accumbens (NAcc) which plays a key role in the linking of reward to motor behaviors. To deal with the complexity and non-stationarity of biological reward signals, we used a confidence metric which was used to indicate the degree of feedback accuracy. This confidence was added to the Actor's weight update equation in the RL controller architecture. If the confidence was high (>0.2), the BMI decoder used this feedback to update its parameters. However, when the confidence was low, the BMI decoder ignored the feedback and did not update its parameters. The range between high confidence and low confidence was termed as the 'ambiguous' region. When the feedback was within this region, the BMI decoder updated its weight at a lower rate than when fully confident, which was decided by the confidence. We used two biologically realistic models to generate synthetic data for MI (Izhikevich model) and NAcc (Humphries model) to validate proposed controller architecture. In this work, we show how the overall performance of the BMI was improved by using a threshold close to the decision boundary to reject erroneous feedback. Additionally, we show the stability of the system improved when the feedback was used with a threshold. The result of this study is a step towards making BMIs autonomous. While our method is not fully autonomous, the results demonstrate that extensive training times necessary at the beginning of each BMI session can be significantly decreased. In our approach, decoder training time was only limited to 10 trials in the first BMI session. Subsequent sessions used previous session weights to initialize the decoder. We also present a method where the use of a threshold can be applied to any decoder with a feedback signal that is less than perfect so that erroneous feedback can be avoided and the stability of the system can be increased.

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics

NASA Astrophysics Data System (ADS)

Prins, Noeline W.; Sanchez, Justin C.; Prasad, Abhishek

2017-06-01

Objective. For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-term goal is to create autonomous BMIs that can utilize an evaluative feedback from the brain to update the decoding algorithm and use it intelligently in order to adapt the decoder. In this study, we show how to extract the necessary evaluative feedback from a biologically realistic (synthetic) source, use both the quantity and the quality of the feedback, and how that feedback information can be incorporated into a reinforcement learning (RL) controller architecture to maximize its performance. Approach. Motivated by the perception-action-reward cycle (PARC) in the brain which links reward for cognitive decision making and goal-directed behavior, we used a reward-based RL architecture named Actor-Critic RL as the model. Instead of using an error signal towards building an autonomous BMI, we envision to use a reward signal from the nucleus accumbens (NAcc) which plays a key role in the linking of reward to motor behaviors. To deal with the complexity and non-stationarity of biological reward signals, we used a confidence metric which was used to indicate the degree of feedback accuracy. This confidence was added to the Actor’s weight update equation in the RL controller architecture. If the confidence was high (>0.2), the BMI decoder used this feedback to update its parameters. However, when the confidence was low, the BMI decoder ignored the feedback and did not update its parameters. The range between high confidence and low confidence was termed as the ‘ambiguous’ region. When the feedback was within this region, the BMI decoder updated its weight at a lower rate than when fully confident, which was decided by the confidence. We used two biologically realistic models to generate synthetic data for MI (Izhikevich model) and NAcc (Humphries model) to validate proposed controller architecture. Main results. In this work, we show how the overall performance of the BMI was improved by using a threshold close to the decision boundary to reject erroneous feedback. Additionally, we show the stability of the system improved when the feedback was used with a threshold. Significance: The result of this study is a step towards making BMIs autonomous. While our method is not fully autonomous, the results demonstrate that extensive training times necessary at the beginning of each BMI session can be significantly decreased. In our approach, decoder training time was only limited to 10 trials in the first BMI session. Subsequent sessions used previous session weights to initialize the decoder. We also present a method where the use of a threshold can be applied to any decoder with a feedback signal that is less than perfect so that erroneous feedback can be avoided and the stability of the system can be increased.

Grasp movement decoding from premotor and parietal cortex.

PubMed

Townsend, Benjamin R; Subasi, Erk; Scherberger, Hansjörg

2011-10-05

Despite recent advances in harnessing cortical motor-related activity to control computer cursors and robotic devices, the ability to decode and execute different grasping patterns remains a major obstacle. Here we demonstrate a simple Bayesian decoder for real-time classification of grip type and wrist orientation in macaque monkeys that uses higher-order planning signals from anterior intraparietal cortex (AIP) and ventral premotor cortex (area F5). Real-time decoding was based on multiunit signals, which had similar tuning properties to cells in previous single-unit recording studies. Maximum decoding accuracy for two grasp types (power and precision grip) and five wrist orientations was 63% (chance level, 10%). Analysis of decoder performance showed that grip type decoding was highly accurate (90.6%), with most errors occurring during orientation classification. In a subsequent off-line analysis, we found small but significant performance improvements (mean, 6.25 percentage points) when using an optimized spike-sorting method (superparamagnetic clustering). Furthermore, we observed significant differences in the contributions of F5 and AIP for grasp decoding, with F5 being better suited for classification of the grip type and AIP contributing more toward decoding of object orientation. However, optimum decoding performance was maximal when using neural activity simultaneously from both areas. Overall, these results highlight quantitative differences in the functional representation of grasp movements in AIP and F5 and represent a first step toward using these signals for developing functional neural interfaces for hand grasping.

An Improved Unscented Kalman Filter Based Decoder for Cortical Brain-Machine Interfaces.

PubMed

Li, Simin; Li, Jie; Li, Zheng

2016-01-01

Brain-machine interfaces (BMIs) seek to connect brains with machines or computers directly, for application in areas such as prosthesis control. For this application, the accuracy of the decoding of movement intentions is crucial. We aim to improve accuracy by designing a better encoding model of primary motor cortical activity during hand movements and combining this with decoder engineering refinements, resulting in a new unscented Kalman filter based decoder, UKF2, which improves upon our previous unscented Kalman filter decoder, UKF1. The new encoding model includes novel acceleration magnitude, position-velocity interaction, and target-cursor-distance features (the decoder does not require target position as input, it is decoded). We add a novel probabilistic velocity threshold to better determine the user's intent to move. We combine these improvements with several other refinements suggested by others in the field. Data from two Rhesus monkeys indicate that the UKF2 generates offline reconstructions of hand movements (mean CC 0.851) significantly more accurately than the UKF1 (0.833) and the popular position-velocity Kalman filter (0.812). The encoding model of the UKF2 could predict the instantaneous firing rate of neurons (mean CC 0.210), given kinematic variables and past spiking, better than the encoding models of these two decoders (UKF1: 0.138, p-v Kalman: 0.098). In closed-loop experiments where each monkey controlled a computer cursor with each decoder in turn, the UKF2 facilitated faster task completion (mean 1.56 s vs. 2.05 s) and higher Fitts's Law bit rate (mean 0.738 bit/s vs. 0.584 bit/s) than the UKF1. These results suggest that the modeling and decoder engineering refinements of the UKF2 improve decoding performance. We believe they can be used to enhance other decoders as well.

An Improved Unscented Kalman Filter Based Decoder for Cortical Brain-Machine Interfaces

PubMed Central

Li, Simin; Li, Jie; Li, Zheng

2016-01-01

Brain-machine interfaces (BMIs) seek to connect brains with machines or computers directly, for application in areas such as prosthesis control. For this application, the accuracy of the decoding of movement intentions is crucial. We aim to improve accuracy by designing a better encoding model of primary motor cortical activity during hand movements and combining this with decoder engineering refinements, resulting in a new unscented Kalman filter based decoder, UKF2, which improves upon our previous unscented Kalman filter decoder, UKF1. The new encoding model includes novel acceleration magnitude, position-velocity interaction, and target-cursor-distance features (the decoder does not require target position as input, it is decoded). We add a novel probabilistic velocity threshold to better determine the user's intent to move. We combine these improvements with several other refinements suggested by others in the field. Data from two Rhesus monkeys indicate that the UKF2 generates offline reconstructions of hand movements (mean CC 0.851) significantly more accurately than the UKF1 (0.833) and the popular position-velocity Kalman filter (0.812). The encoding model of the UKF2 could predict the instantaneous firing rate of neurons (mean CC 0.210), given kinematic variables and past spiking, better than the encoding models of these two decoders (UKF1: 0.138, p-v Kalman: 0.098). In closed-loop experiments where each monkey controlled a computer cursor with each decoder in turn, the UKF2 facilitated faster task completion (mean 1.56 s vs. 2.05 s) and higher Fitts's Law bit rate (mean 0.738 bit/s vs. 0.584 bit/s) than the UKF1. These results suggest that the modeling and decoder engineering refinements of the UKF2 improve decoding performance. We believe they can be used to enhance other decoders as well. PMID:28066170

The association of ADHD symptoms and reading acquisition during elementary school years.

PubMed

Ehm, Jan-Henning; Kerner Auch Koerner, Julia; Gawrilow, Caterina; Hasselhorn, Marcus; Schmiedek, Florian

2016-09-01

The present longitudinal study aimed to investigate the influence of ADHD symptoms on reading development in elementary schoolchildren. To this end, repeated assessments of ADHD symptoms (teacher ratings of inattention, hyperactivity, and impulsivity) and reading achievement (standardized tests of decoding speed and text comprehension) were examined in a sample comprising 2,014 elementary schoolchildren at the end of Grades 1, 2, 3, respectively, and in the middle of Grade 4. Latent change score models revealed that the level of ADHD symptoms was associated with lower levels and less growth in decoding speed and text comprehension. Furthermore, individual differences in changes in ADHD symptoms and reading performance were negatively associated. Together, these results indicate commonalities in the development of ADHD symptomatology and reading achievement throughout elementary school. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Decoding DNA, RNA and peptides with quantum tunnelling

NASA Astrophysics Data System (ADS)

di Ventra, Massimiliano; Taniguchi, Masateru

2016-02-01

Drugs and treatments could be precisely tailored to an individual patient by extracting their cellular- and molecular-level information. For this approach to be feasible on a global scale, however, information on complete genomes (DNA), transcriptomes (RNA) and proteomes (all proteins) needs to be obtained quickly and at low cost. Quantum mechanical phenomena could potentially be of value here, because the biological information needs to be decoded at an atomic level and quantum tunnelling has recently been shown to be able to differentiate single nucleobases and amino acids in short sequences. Here, we review the different approaches to using quantum tunnelling for sequencing, highlighting the theoretical background to the method and the experimental capabilities demonstrated to date. We also explore the potential advantages of the approach and the technical challenges that must be addressed to deliver practical quantum sequencing devices.

Barcoded microchips for biomolecular assays.

PubMed

Zhang, Yi; Sun, Jiashu; Zou, Yu; Chen, Wenwen; Zhang, Wei; Xi, Jianzhong Jeff; Jiang, Xingyu

2015-01-20

Multiplexed assay of analytes is of great importance for clinical diagnostics and other analytical applications. Barcode-based bioassays with the ability to encode and decode may realize this goal in a straightforward and consistent manner. We present here a microfluidic barcoded chip containing several sets of microchannels with different widths, imitating the commonly used barcode. A single barcoded microchip can carry out tens of individual protein/nucleic acid assays (encode) and immediately yield all assay results by a portable barcode reader or a smartphone (decode). The applicability of a barcoded microchip is demonstrated by human immunodeficiency virus (HIV) immunoassays for simultaneous detection of three targets (anti-gp41 antibody, anti-gp120 antibody, and anti-gp36 antibody) from six human serum samples. We can also determine seven pathogen-specific oligonucleotides by a single chip containing both positive and negative controls.

Phonics Teaching and Learning in Whole Language Classrooms: New Evidence from Research.

ERIC Educational Resources Information Center

Dahl, Karin L.; Scharer, Patricia L.

2000-01-01

Investigates eight first-grade whole language classrooms in terms of what phonics skills and concepts were taught, where phonics instruction occurred, and how it was conducted. Shows gains in ability to decode and encode words for all students. Finds that teachers responded to individual needs of learners, and that skills were taught within the…

Anomalous Gray Matter Patterns in Specific Reading Comprehension Deficit Are Independent of Dyslexia

ERIC Educational Resources Information Center

Bailey, Stephen; Hoeft, Fumiko; Aboud, Katherine; Cutting, Laurie

2016-01-01

Specific reading comprehension deficit (SRCD) affects up to 10 % of all children. SRCD is distinct from dyslexia (DYS) in that individuals with SRCD show poor comprehension despite adequate decoding skills. Despite its prevalence and considerable behavioral research, there is not yet a unified cognitive profile of SRCD. While its neuroanatomical…

Relationship between daily affect and overeating-only, loss of control eating-only, and binge eating episodes in obese adults

PubMed Central

Berg, Kelly C.; Peterson, Carol B.; Crosby, Ross D.; Cao, Li; Crow, Scott J.; Engel, Scott G.; Wonderlich, Stephen A.

2013-01-01

The two objectives of the current study were: (1) to identify daily patterns of negative affect (NA) in obese individuals; and (2) to determine whether daily affect patterns were related to overeating without loss of control (OE-only), loss of control eating without overeating (LOC-only), and binge eating (BE) episodes. Fifty obese (BMI=40.3±08.5) adults (84.0% female) completed a two-week ecological momentary assessment protocol during which they completed assessments of NA and indicated whether their eating episodes were characterized by OE and/or LOC. Latent growth mixture modeling (LGMM) was used to identify daily trajectories of NA. GEE analysis was used to determine whether daily affect trajectories were differentially related to the frequency of OE-only, LOC-only, and BE episodes. The LGMM analyses identified nine unique trajectories of NA. Significantly higher frequencies of OE-only and BE episodes occurred on days characterized by high or increasing levels of NA. There were no significant differences between classes for the frequency of LOC-only episodes. These data suggest that NA may act as an antecedent to OE-only and BE episodes and that targeting “problematic affect days” may reduce the occurrence of OE-only and BE episodes among obese individuals. PMID:24200217

Regional Gray Matter Volume Deficits in Adolescents with First-Episode Psychosis

ERIC Educational Resources Information Center

Janssen, Joost; Parellada, Mara; Moreno, Dolores; Graell, Montserrat; Fraguas, David; Zabala, Arantzazu; Vazquez, Veronica Garcia; Desco, Manuel; Arango, Celso

2008-01-01

The regional gray matter volumes of adolescents with first-episode psychosis are compared with those of a control group. Magnetic resonance imaging was conducted on 70 patients with early onset FEP and on 51 individuals without FEP. Findings revealed that volume deficits in the left medial frontal gray matter were common in individuals with…

Reed-Solomon decoder

NASA Technical Reports Server (NTRS)

Lahmeyer, Charles R. (Inventor)

1987-01-01

A Reed-Solomon decoder with dedicated hardware for five sequential algorithms was designed with overall pipelining by memory swapping between input, processing and output memories, and internal pipelining through the five algorithms. The code definition used in decoding is specified by a keyword received with each block of data so that a number of different code formats may be decoded by the same hardware.

A study of digital holographic filters generation. Phase 2: Digital data communication system, volume 1

NASA Technical Reports Server (NTRS)

Ingels, F. M.; Mo, C. D.

1978-01-01

An empirical study of the performance of the Viterbi decoders in bursty channels was carried out and an improved algebraic decoder for nonsystematic codes was developed. The hybrid algorithm was simulated for the (2,1), k = 7 code on a computer using 20 channels having various error statistics, ranging from pure random error to pure bursty channels. The hybrid system outperformed both the algebraic and the Viterbi decoders in every case, except the 1% random error channel where the Viterbi decoder had one bit less decoding error.

Large-Constraint-Length, Fast Viterbi Decoder

NASA Technical Reports Server (NTRS)

Collins, O.; Dolinar, S.; Hsu, In-Shek; Pollara, F.; Olson, E.; Statman, J.; Zimmerman, G.

1990-01-01

Scheme for efficient interconnection makes VLSI design feasible. Concept for fast Viterbi decoder provides for processing of convolutional codes of constraint length K up to 15 and rates of 1/2 to 1/6. Fully parallel (but bit-serial) architecture developed for decoder of K = 7 implemented in single dedicated VLSI circuit chip. Contains six major functional blocks. VLSI circuits perform branch metric computations, add-compare-select operations, and then store decisions in traceback memory. Traceback processor reads appropriate memory locations and puts out decoded bits. Used as building block for decoders of larger K.

Locating and decoding barcodes in fuzzy images captured by smart phones

NASA Astrophysics Data System (ADS)

Deng, Wupeng; Hu, Jiwei; Liu, Quan; Lou, Ping

2017-07-01

With the development of barcodes for commercial use, people's requirements for detecting barcodes by smart phone become increasingly pressing. The low quality of barcode image captured by mobile phone always affects the decoding and recognition rates. This paper focuses on locating and decoding EAN-13 barcodes in fuzzy images. We present a more accurate locating algorithm based on segment length and high fault-tolerant rate algorithm for decoding barcodes. Unlike existing approaches, location algorithm is based on the edge segment length of EAN -13 barcodes, while our decoding algorithm allows the appearance of fuzzy region in barcode image. Experimental results are performed on damaged, contaminated and scratched digital images, and provide a quite promising result for EAN -13 barcode location and decoding.

Direct and Indirect Costs of Chronic and Episodic Migraine in the United States: A Web-Based Survey.

PubMed

Messali, Andrew; Sanderson, Joanna C; Blumenfeld, Andrew M; Goadsby, Peter J; Buse, Dawn C; Varon, Sepideh F; Stokes, Michael; Lipton, Richard B

2016-02-01

The objective of this study was to compare the societal direct and indirect costs of chronic and episodic migraine in the United States. Episodic and chronic migraine are distinguished by the frequency of headache-days. Chronic migraine has a greater overall impact on quality of life than does episodic migraine. Individuals with chronic migraine also use more healthcare resources (resulting in higher direct costs) and experience greater decreases in productivity (resulting in higher indirect costs) than those with episodic migraine as shown in the American Migraine Prevalence and Prevention (AMPP) Study. The International Burden of Migraine Study utilized a web-based questionnaire to elicit data on several topics related to the burden of migraine illness, including health resource utilization and productivity losses. Potential survey participants were identified by Synovate Healthcare (Chicago, IL, USA) from a pool of registered panelists from various countries. The panelists were screened online to determine eligibility and to identify individuals with migraine (episodic or chronic), based on reported symptoms. Participants from the United States were divided into episodic and chronic migraine groups, based on reported headache-day per month frequency. Direct and indirect costs were estimated by applying estimated unit costs to reported headache-related productivity losses and resource use. Costs were compared between participants with episodic and chronic migraine. Mean [standard deviation] total annual cost of headache among people with chronic migraine ($8243 [$10,646]) was over three times that of episodic migraine ($2649 [$4634], P < .001). Participants with chronic migraine had significantly greater direct medical costs ($4943 [$6382]) and indirect (lost productivity) costs ($3300 [$6907]) than did participants with episodic migraine (direct, $1705 [$3591]; indirect, $943 [$2084]) (P < .001 for each). Unlike previous findings, direct medical costs constituted the majority of total headache-related costs for both chronic migraine (60.0%, $4943 of $8243) and episodic migraine (64.3%, $1705 of $2649) participants. A large portion of direct medical costs are attributable to pharmaceutical utilization among both chronic migraine (80%, $3925 of 4943) and episodic migraine (70%, $1196 of $1705) participants. The results of this study build on previous results of the AMPP Study, demonstrating that headache-related direct, indirect, and total costs are significantly greater among individuals with chronic migraine than with episodic migraine in the United States. © 2016 American Headache Society.

Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning

PubMed Central

Turk-Browne, Nicholas B.; Botvinick, Matthew M.; Norman, Kenneth A.

2017-01-01

A growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippocampus specializes in memorizing individual episodes. In particular, the Complementary Learning Systems theory argues that there is a computational trade-off between learning the specifics of individual experiences and regularities that hold across those experiences. We asked whether it is possible for the hippocampus to handle both statistical learning and memorization of individual episodes. We exposed a neural network model that instantiates known properties of hippocampal projections and subfields to sequences of items with temporal regularities. We found that the monosynaptic pathway—the pathway connecting entorhinal cortex directly to region CA1—was able to support statistical learning, while the trisynaptic pathway—connecting entorhinal cortex to CA1 through dentate gyrus and CA3—learned individual episodes, with apparent representations of regularities resulting from associative reactivation through recurrence. Thus, in paradigms involving rapid learning, the computational trade-off between learning episodes and regularities may be handled by separate anatomical pathways within the hippocampus itself. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872368

Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning.

PubMed

Schapiro, Anna C; Turk-Browne, Nicholas B; Botvinick, Matthew M; Norman, Kenneth A

2017-01-05

A growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippocampus specializes in memorizing individual episodes. In particular, the Complementary Learning Systems theory argues that there is a computational trade-off between learning the specifics of individual experiences and regularities that hold across those experiences. We asked whether it is possible for the hippocampus to handle both statistical learning and memorization of individual episodes. We exposed a neural network model that instantiates known properties of hippocampal projections and subfields to sequences of items with temporal regularities. We found that the monosynaptic pathway-the pathway connecting entorhinal cortex directly to region CA1-was able to support statistical learning, while the trisynaptic pathway-connecting entorhinal cortex to CA1 through dentate gyrus and CA3-learned individual episodes, with apparent representations of regularities resulting from associative reactivation through recurrence. Thus, in paradigms involving rapid learning, the computational trade-off between learning episodes and regularities may be handled by separate anatomical pathways within the hippocampus itself.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

An uncontrolled trial of multi-component care for first-episode psychosis: Effects on social cognition.

PubMed

Breitborde, Nicholas J K; Moe, Aubrey M; Woolverton, Cindy; Harrison-Monroe, Patricia; Bell, Emily K

2018-06-01

Growing evidence suggests that specialized, multi-component treatment programmes produce improvements in numerous outcomes among individuals with first-episode psychosis. However, these programmes often lack interventions specifically designed to address deficits in social cognition. This raises questions about the effectiveness of such programmes in addressing deficits in social cognition that accompany psychotic disorders. We investigated the effect of participation in a multi-component treatment programme on social cognition among 71 individuals with first-episode psychosis. Participants experienced gains in emotion processing, social knowledge, social perception and theory of mind. However, after controlling for multiple comparisons, these improvements were limited to theory of mind and recognition of social cues in low emotion interactions. Although our findings should be interpreted cautiously, they raise the possibility that individuals participating in multi-component treatment programmes for first-episode psychosis without interventions specifically targeting social cognition may still experience gains in social cognition. © 2017 John Wiley & Sons Australia, Ltd.

Detecting and interpreting conscious experiences in behaviorally non-responsive patients.

PubMed

Naci, Lorina; Sinai, Leah; Owen, Adrian M

2017-01-15

Decoding the contents of consciousness from brain activity is one of the most challenging frontiers of cognitive neuroscience. The ability to interpret mental content without recourse to behavior is most relevant for understanding patients who may be demonstrably conscious, but entirely unable to speak or move willfully in any way, precluding any systematic investigation of their conscious experience. The lack of consistent behavioral responsivity engenders unique challenges to decoding any conscious experiences these patients may have solely based on their brain activity. For this reason, paradigms that have been successful in healthy individuals cannot serve to interpret conscious mental states in this patient group. Until recently, patient studies have used structured instructions to elicit willful modulation of brain activity according to command, in order to decode the presence of willful brain-based responses in this patient group. In recent work, we have used naturalistic paradigms, such as watching a movie or listening to an audio-story, to demonstrate that a common neural code supports conscious experiences in different individuals. Moreover, we have demonstrated that this code can be used to interpret the conscious experiences of a patient who had remained non-responsive for several years. This approach is easy to administer, brief, and does not require compliance with task instructions. Rather, it engages attention naturally through meaningful stimuli that are similar to the real-world sensory information in a patient's environment. Therefore, it may be particularly suited to probing consciousness and revealing residual brain function in highly impaired, acute, patients in a comatose state, thus helping to improve diagnostication and prognostication for this vulnerable patient group from the critical early stages of severe brain-injury. Copyright © 2015 Elsevier Inc. All rights reserved.

Single-trial decoding of auditory novelty responses facilitates the detection of residual consciousness

PubMed Central

King, J.R.; Faugeras, F.; Gramfort, A.; Schurger, A.; El Karoui, I.; Sitt, J.D.; Rohaut, B.; Wacongne, C.; Labyt, E.; Bekinschtein, T.; Cohen, L.; Naccache, L.; Dehaene, S.

2017-01-01

Detecting residual consciousness in unresponsive patients is a major clinical concern and a challenge for theoretical neuroscience. To tackle this issue, we recently designed a paradigm that dissociates two electro-encephalographic (EEG) responses to auditory novelty. Whereas a local change in pitch automatically elicits a mismatch negativity (MMN), a change in global sound sequence leads to a late P300b response. The latter component is thought to be present only when subjects consciously perceive the global novelty. Unfortunately, it can be difficult to detect because individual variability is high, especially in clinical recordings. Here, we show that multivariate pattern classifiers can extract subject-specific EEG patterns and predict single-trial local or global novelty responses. We first validate our method with 38 high-density EEG, MEG and intracranial EEG recordings. We empirically demonstrate that our approach circumvents the issues associated with multiple comparisons and individual variability while improving the statistics. Moreover, we confirm in control subjects that local responses are robust to distraction whereas global responses depend on attention. We then investigate 104 vegetative state (VS), minimally conscious state (MCS) and conscious state (CS) patients recorded with high-density EEG. For the local response, the proportion of significant decoding scores (M = 60%) does not vary with the state of consciousness. By contrast, for the global response, only 14% of the VS patients' EEG recordings presented a significant effect, compared to 31% in MCS patients' and 52% in CS patients'. In conclusion, single-trial multivariate decoding of novelty responses provides valuable information in non-communicating patients and paves the way towards real-time monitoring of the state of consciousness. PMID:23859924

Within-person Changes in Individual Symptoms of Depression Predict Subsequent Depressive Episodes in Adolescents: A Prospective Study

PubMed Central

Kouros, Chrystyna D.; Morris, Matthew C.; Garber, Judy

2015-01-01

The current longitudinal study examined which individual symptoms of depression uniquely predicted a subsequent Major Depressive Episode (MDE) in adolescents, and whether these relations differed by sex. Adolescents (N=240) were first interviewed in grade 6 (M=11.86 years old; SD = 0.56; 54% female; 81.5% Caucasian) and then annually through grade 12 regarding their individual symptoms of depression as well as the occurrence of MDEs. Individual symptoms of depression were assessed with the Children’s Depression Rating Scale-Revised (CDRS-R) and depressive episodes were assessed with the Longitudinal Interval Follow-up Evaluation (LIFE). Results showed that within-person changes in sleep problems and low self-esteem/excessive guilt positively predicted an increased likelihood of an MDE for both boys and girls. Significant sex differences also were found. Within-person changes in anhedonia predicted an increased likelihood of a subsequent MDE among boys, whereas irritability predicted a decreased likelihood of a future MDE among boys, and concentration difficulties predicted a decreased likelihood of an MDE in girls. These results identified individual depressive symptoms that predicted subsequent depressive episodes in male and female adolescents, and may be used to guide the early detection, treatment, and prevention of depressive disorders in youth. PMID:26105209

Bimanual coordination positively predicts episodic memory: A combined behavioral and MRI investigation.

PubMed

Lyle, Keith B; Dombroski, Brynn A; Faul, Leonard; Hopkins, Robin F; Naaz, Farah; Switala, Andrew E; Depue, Brendan E

2017-11-01

Some people remember events more completely and accurately than other people, but the origins of individual differences in episodic memory are poorly understood. One way to advance understanding is by identifying characteristics of individuals that reliably covary with memory performance. Recent research suggests motor behavior is related to memory performance, with individuals who consistently use a single preferred hand for unimanual actions performing worse than individuals who make greater use of both hands. This research has relied on self-reports of behavior. It is unknown whether objective measures of motor behavior also predict memory performance. Here, we tested the predictive power of bimanual coordination, an important form of manual dexterity. Bimanual coordination, as measured objectively on the Purdue Pegboard Test, was positively related to correct recall on the California Verbal Learning Test-II and negatively related to false recall. Furthermore, MRI data revealed that cortical surface area in right lateral prefrontal regions was positively related to correct recall. In one of these regions, cortical thickness was negatively related to bimanual coordination. These results suggest that individual differences in episodic memory may partially reflect morphological variation in right lateral prefrontal cortex and suggest a relationship between neural correlates of episodic memory and motor behavior. Copyright © 2017 Elsevier Inc. All rights reserved.

Validity of the two-level model for Viterbi decoder gap-cycle performance

NASA Technical Reports Server (NTRS)

Dolinar, S.; Arnold, S.

1990-01-01

A two-level model has previously been proposed for approximating the performance of a Viterbi decoder which encounters data received with periodically varying signal-to-noise ratio. Such cyclically gapped data is obtained from the Very Large Array (VLA), either operating as a stand-alone system or arrayed with Goldstone. This approximate model predicts that the decoder error rate will vary periodically between two discrete levels with the same period as the gap cycle. It further predicts that the length of the gapped portion of the decoder error cycle for a constraint length K decoder will be about K-1 bits shorter than the actual duration of the gap. The two-level model for Viterbi decoder performance with gapped data is subjected to detailed validation tests. Curves showing the cyclical behavior of the decoder error burst statistics are compared with the simple square-wave cycles predicted by the model. The validity of the model depends on a parameter often considered irrelevant in the analysis of Viterbi decoder performance, the overall scaling of the received signal or the decoder's branch-metrics. Three scaling alternatives are examined: optimum branch-metric scaling and constant branch-metric scaling combined with either constant noise-level scaling or constant signal-level scaling. The simulated decoder error cycle curves roughly verify the accuracy of the two-level model for both the case of optimum branch-metric scaling and the case of constant branch-metric scaling combined with constant noise-level scaling. However, the model is not accurate for the case of constant branch-metric scaling combined with constant signal-level scaling.

Adaptive Distributed Video Coding with Correlation Estimation using Expectation Propagation

PubMed Central

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2013-01-01

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method. PMID:23750314

Decoding continuous three-dimensional hand trajectories from epidural electrocorticographic signals in Japanese macaques

NASA Astrophysics Data System (ADS)

Shimoda, Kentaro; Nagasaka, Yasuo; Chao, Zenas C.; Fujii, Naotaka

2012-06-01

Brain-machine interface (BMI) technology captures brain signals to enable control of prosthetic or communication devices with the goal of assisting patients who have limited or no ability to perform voluntary movements. Decoding of inherent information in brain signals to interpret the user's intention is one of main approaches for developing BMI technology. Subdural electrocorticography (sECoG)-based decoding provides good accuracy, but surgical complications are one of the major concerns for this approach to be applied in BMIs. In contrast, epidural electrocorticography (eECoG) is less invasive, thus it is theoretically more suitable for long-term implementation, although it is unclear whether eECoG signals carry sufficient information for decoding natural movements. We successfully decoded continuous three-dimensional hand trajectories from eECoG signals in Japanese macaques. A steady quantity of information of continuous hand movements could be acquired from the decoding system for at least several months, and a decoding model could be used for ˜10 days without significant degradation in accuracy or recalibration. The correlation coefficients between observed and predicted trajectories were lower than those for sECoG-based decoding experiments we previously reported, owing to a greater degree of chewing artifacts in eECoG-based decoding than is found in sECoG-based decoding. As one of the safest invasive recording methods available, eECoG provides an acceptable level of performance. With the ease of replacement and upgrades, eECoG systems could become the first-choice interface for real-life BMI applications.

Adaptive distributed video coding with correlation estimation using expectation propagation

NASA Astrophysics Data System (ADS)

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-01

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Adaptive Distributed Video Coding with Correlation Estimation using Expectation Propagation.

PubMed

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-15

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Episodic and Semantic Memory Influences on Picture Naming in Alzheimer's Disease

ERIC Educational Resources Information Center

Small, Jeff A.; Sandhu, Nirmaljeet

2008-01-01

This study investigated the relationship between semantic and episodic memory as they support lexical access by healthy younger and older adults and individuals with Alzheimer's disease (AD). In particular, we were interested in examining the pattern of semantic and episodic memory declines in AD (i.e., word-finding difficulty and impaired recent…

Remembering the past and imagining the future: attachment effects on production of episodic details in close relationships.

PubMed

Cao, Xiancai; Madore, Kevin P; Wang, Dahua; Schacter, Daniel L

2018-09-01

Attachment theories and studies have shown that Internal Working Models (IWMs) can impact autobiographical memory and future-oriented information processing relevant to close relationships. According to the constructive episodic simulation hypothesis (CESH), both remembering the past and imagining the future rely on episodic memory. We hypothesised that one way IWMs may bridge past experiences and future adaptations is via episodic memory. The present study investigated the association between attachment and episodic specificity in attachment-relevant and attachment-irrelevant memory and imagination among young and older adults. We measured the attachment style of 37 young adults and 40 older adults, and then asked them to remember or imagine attachment-relevant and attachment-irrelevant events. Participants' narratives were coded for internal details (i.e., episodic) and external details (e.g., semantic, repetitions). The results showed that across age group, secure individuals generated more internal details and fewer external details in attachment-relevant tasks compared to attachment-irrelevant tasks; these differences were not observed in insecure individuals. These findings support the CESH and provide a new perspective to understand the function of IWMs.

Cracking the code: a decode strategy for the international business machines punch cards of Korean war soldiers.

PubMed

Mitsunaga, Erin M

2006-05-01

During the Korean War, International Business Machines (IBM) punch cards were created for every individual involved in military combat. Each card contained all pertinent personal information about the individual and was utilized to keep track of all soldiers involved. However, at present, all of the information known about these punch cards reveals only their format and their significance; there is little to no information on how these cards were created or how to interpret the information contained without the aid of the computer system used during the war. Today, it is believed there is no one available to explain this computerized system, nor do the original computers exist. This decode strategy is the result of an attempt to decipher the information on these cards through the use of all available medical and dental records for each individual examined. By cross-referencing the relevant personal information with the known format of the cards, a basic guess-and-check method was utilized. After examining hundreds of IBM punch cards, however, it has become clear that the punch card method of recording information was not infallible. In some cases, there are gaps of information on cards where there are data recorded on personal records; in others, information is punched incorrectly onto the cards, perhaps as the result of a transcription error. Taken all together, it is clear that the information contained on each individual's card should be taken solely as another form of personal documentation.

Older adults who persistently present to the emergency department with severe, non-severe, and indeterminate episode patterns.

PubMed

Kaskie, Brian; Obrizan, Maksym; Jones, Michael P; Bentler, Suzanne; Weigel, Paula; Hockenberry, Jason; Wallace, Robert B; Ohsfeldt, Robert L; Rosenthal, Gary E; Wolinsky, Fredric D

2011-10-21

It is well known that older adults figure prominently in the use of emergency departments (ED) across the United States. Previous research has differentiated ED visits by levels of clinical severity and found health status and other individual characteristics distinguished severe from non-severe visits. In this research, we classified older adults into population groups that persistently present with severe, non-severe, or indeterminate patterns of ED episodes. We then contrasted the three groups using a comprehensive set of covariates. Using a unique dataset linking individual characteristics with Medicare claims for calendar years 1991-2007, we identified patterns of ED use among the large, nationally representative AHEAD sample consisting of 5,510 older adults. We then classified one group of older adults who persistently presented to the ED with clinically severe episodes and another group who persistently presented to the ED with non-severe episodes. These two groups were contrasted using logistic regression, and then contrasted against a third group with a persistent pattern of ED episodes with indeterminate levels of severity using multinomial logistic regression. Variable selection was based on Andersen's behavioral model of health services use and featured clinical status, demographic and socioeconomic characteristics, health behaviors, health service use patterns, local health care supply, and other contextual effects. We identified 948 individuals (17.2% of the entire sample) who presented a pattern in which their ED episodes were typically defined as severe and 1,076 individuals (19.5%) who typically presented with non-severe episodes. Individuals who persistently presented to the ED with severe episodes were more likely to be older (AOR 1.52), men (AOR 1.28), current smokers (AOR 1.60), experience diabetes (AOR (AOR 1.80), heart disease (AOR 1.70), hypertension (AOR 1.32) and have a greater amount of morbidity (AOR 1.48) than those who persistently presented to the ED with non-severe episodes. When contrasted with 1,177 individuals with a persistent pattern of indeterminate severity ED use, persons with severe patterns were older (AOR 1.36), more likely to be obese (AOR 1.36), and experience heart disease (AOR 1.49) and hypertension (AOR 1.36) while persons with non-severe patterns were less likely to smoke (AOR 0.63) and have diabetes (AOR 0.67) or lung disease (AOR 0.58). We distinguished three large, readily identifiable groups of older adults which figure prominently in the use of EDs across the United States. Our results suggest that one group affects the general capacity of the ED to provide care as they persistently present with severe episodes requiring urgent staff attention and greater resource allocation. Another group persistently presents with non-severe episodes and creates a considerable share of the excess demand for ED care. Future research should determine how chronic disease management programs and varied co-payment obligations might impact the use of the ED by these two large and distinct groups of older adults with consistent ED use patterns.

Recent advances in coding theory for near error-free communications

NASA Technical Reports Server (NTRS)

Cheung, K.-M.; Deutsch, L. J.; Dolinar, S. J.; Mceliece, R. J.; Pollara, F.; Shahshahani, M.; Swanson, L.

1991-01-01

Channel and source coding theories are discussed. The following subject areas are covered: large constraint length convolutional codes (the Galileo code); decoder design (the big Viterbi decoder); Voyager's and Galileo's data compression scheme; current research in data compression for images; neural networks for soft decoding; neural networks for source decoding; finite-state codes; and fractals for data compression.

Fast transform decoding of nonsystematic Reed-Solomon codes

NASA Technical Reports Server (NTRS)

Truong, T. K.; Cheung, K.-M.; Reed, I. S.; Shiozaki, A.

1989-01-01

A Reed-Solomon (RS) code is considered to be a special case of a redundant residue polynomial (RRP) code, and a fast transform decoding algorithm to correct both errors and erasures is presented. This decoding scheme is an improvement of the decoding algorithm for the RRP code suggested by Shiozaki and Nishida, and can be realized readily on very large scale integration chips.

The Differential Contributions of Auditory-Verbal and Visuospatial Working Memory on Decoding Skills in Children Who Are Poor Decoders

ERIC Educational Resources Information Center

Squires, Katie Ellen

2013-01-01

This study investigated the differential contribution of auditory-verbal and visuospatial working memory (WM) on decoding skills in second- and fifth-grade children identified with poor decoding. Thirty-two second-grade students and 22 fifth-grade students completed measures that assessed simple and complex auditory-verbal and visuospatial memory,…

Polar Coding with CRC-Aided List Decoding

DTIC Science & Technology

2015-08-01

TECHNICAL REPORT 2087 August 2015 Polar Coding with CRC-Aided List Decoding David Wasserman Approved...list decoding . RESULTS Our simulation results show that polar coding can produce results very similar to the FEC used in the Digital Video...standard. RECOMMENDATIONS In any application for which the DVB-S2 FEC is considered, polar coding with CRC-aided list decod - ing with N = 65536

Decoding position, velocity, or goal: does it matter for brain-machine interfaces?

PubMed

Marathe, A R; Taylor, D M

2011-04-01

Arm end-point position, end-point velocity, and the intended final location or 'goal' of a reach have all been decoded from cortical signals for use in brain-machine interface (BMI) applications. These different aspects of arm movement can be decoded from the brain and used directly to control the position, velocity, or movement goal of a device. However, these decoded parameters can also be remapped to control different aspects of movement, such as using the decoded position of the hand to control the velocity of a device. People easily learn to use the position of a joystick to control the velocity of an object in a videogame. Similarly, in BMI systems, the position, velocity, or goal of a movement could be decoded from the brain and remapped to control some other aspect of device movement. This study evaluates how easily people make transformations between position, velocity, and reach goal in BMI systems. It also evaluates how different amounts of decoding error impact on device control with and without these transformations. Results suggest some remapping options can significantly improve BMI control. This study provides guidance on what remapping options to use when various amounts of decoding error are present.

Encoder-Decoder Optimization for Brain-Computer Interfaces

PubMed Central

Merel, Josh; Pianto, Donald M.; Cunningham, John P.; Paninski, Liam

2015-01-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages. PMID:26029919

Encoder-decoder optimization for brain-computer interfaces.

PubMed

Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam

2015-06-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Decoding position, velocity, or goal: Does it matter for brain-machine interfaces?

NASA Astrophysics Data System (ADS)

Marathe, A. R.; Taylor, D. M.

2011-04-01

Arm end-point position, end-point velocity, and the intended final location or 'goal' of a reach have all been decoded from cortical signals for use in brain-machine interface (BMI) applications. These different aspects of arm movement can be decoded from the brain and used directly to control the position, velocity, or movement goal of a device. However, these decoded parameters can also be remapped to control different aspects of movement, such as using the decoded position of the hand to control the velocity of a device. People easily learn to use the position of a joystick to control the velocity of an object in a videogame. Similarly, in BMI systems, the position, velocity, or goal of a movement could be decoded from the brain and remapped to control some other aspect of device movement. This study evaluates how easily people make transformations between position, velocity, and reach goal in BMI systems. It also evaluates how different amounts of decoding error impact on device control with and without these transformations. Results suggest some remapping options can significantly improve BMI control. This study provides guidance on what remapping options to use when various amounts of decoding error are present.

Improved HDRG decoders for qudit and non-Abelian quantum error correction

NASA Astrophysics Data System (ADS)

Hutter, Adrian; Loss, Daniel; Wootton, James R.

2015-03-01

Hard-decision renormalization group (HDRG) decoders are an important class of decoding algorithms for topological quantum error correction. Due to their versatility, they have been used to decode systems with fractal logical operators, color codes, qudit topological codes, and non-Abelian systems. In this work, we develop a method of performing HDRG decoding which combines strengths of existing decoders and further improves upon them. In particular, we increase the minimal number of errors necessary for a logical error in a system of linear size L from \\Theta ({{L}2/3}) to Ω ({{L}1-ε }) for any ε \\gt 0. We apply our algorithm to decoding D({{{Z}}d}) quantum double models and a non-Abelian anyon model with Fibonacci-like fusion rules, and show that it indeed significantly outperforms previous HDRG decoders. Furthermore, we provide the first study of continuous error correction with imperfect syndrome measurements for the D({{{Z}}d}) quantum double models. The parallelized runtime of our algorithm is poly(log L) for the perfect measurement case. In the continuous case with imperfect syndrome measurements, the averaged runtime is O(1) for Abelian systems, while continuous error correction for non-Abelian anyons stays an open problem.

An architecture of entropy decoder, inverse quantiser and predictor for multi-standard video decoding

NASA Astrophysics Data System (ADS)

Liu, Leibo; Chen, Yingjie; Yin, Shouyi; Lei, Hao; He, Guanghui; Wei, Shaojun

2014-07-01

A VLSI architecture for entropy decoder, inverse quantiser and predictor is proposed in this article. This architecture is used for decoding video streams of three standards on a single chip, i.e. H.264/AVC, AVS (China National Audio Video coding Standard) and MPEG2. The proposed scheme is called MPMP (Macro-block-Parallel based Multilevel Pipeline), which is intended to improve the decoding performance to satisfy the real-time requirements while maintaining a reasonable area and power consumption. Several techniques, such as slice level pipeline, MB (Macro-Block) level pipeline, MB level parallel, etc., are adopted. Input and output buffers for the inverse quantiser and predictor are shared by the decoding engines for H.264, AVS and MPEG2, therefore effectively reducing the implementation overhead. Simulation shows that decoding process consumes 512, 435 and 438 clock cycles per MB in H.264, AVS and MPEG2, respectively. Owing to the proposed techniques, the video decoder can support H.264 HP (High Profile) 1920 × 1088@30fps (frame per second) streams, AVS JP (Jizhun Profile) 1920 × 1088@41fps streams and MPEG2 MP (Main Profile) 1920 × 1088@39fps streams when exploiting a 200 MHz working frequency.

Brain-to-text: decoding spoken phrases from phone representations in the brain.

PubMed

Herff, Christian; Heger, Dominic; de Pesters, Adriana; Telaar, Dominic; Brunner, Peter; Schalk, Gerwin; Schultz, Tanja

2015-01-01

It has long been speculated whether communication between humans and machines based on natural speech related cortical activity is possible. Over the past decade, studies have suggested that it is feasible to recognize isolated aspects of speech from neural signals, such as auditory features, phones or one of a few isolated words. However, until now it remained an unsolved challenge to decode continuously spoken speech from the neural substrate associated with speech and language processing. Here, we show for the first time that continuously spoken speech can be decoded into the expressed words from intracranial electrocorticographic (ECoG) recordings.Specifically, we implemented a system, which we call Brain-To-Text that models single phones, employs techniques from automatic speech recognition (ASR), and thereby transforms brain activity while speaking into the corresponding textual representation. Our results demonstrate that our system can achieve word error rates as low as 25% and phone error rates below 50%. Additionally, our approach contributes to the current understanding of the neural basis of continuous speech production by identifying those cortical regions that hold substantial information about individual phones. In conclusion, the Brain-To-Text system described in this paper represents an important step toward human-machine communication based on imagined speech.

Brain-to-text: decoding spoken phrases from phone representations in the brain

PubMed Central

Herff, Christian; Heger, Dominic; de Pesters, Adriana; Telaar, Dominic; Brunner, Peter; Schalk, Gerwin; Schultz, Tanja

2015-01-01

It has long been speculated whether communication between humans and machines based on natural speech related cortical activity is possible. Over the past decade, studies have suggested that it is feasible to recognize isolated aspects of speech from neural signals, such as auditory features, phones or one of a few isolated words. However, until now it remained an unsolved challenge to decode continuously spoken speech from the neural substrate associated with speech and language processing. Here, we show for the first time that continuously spoken speech can be decoded into the expressed words from intracranial electrocorticographic (ECoG) recordings.Specifically, we implemented a system, which we call Brain-To-Text that models single phones, employs techniques from automatic speech recognition (ASR), and thereby transforms brain activity while speaking into the corresponding textual representation. Our results demonstrate that our system can achieve word error rates as low as 25% and phone error rates below 50%. Additionally, our approach contributes to the current understanding of the neural basis of continuous speech production by identifying those cortical regions that hold substantial information about individual phones. In conclusion, the Brain-To-Text system described in this paper represents an important step toward human-machine communication based on imagined speech. PMID:26124702

Attentional Selection in a Cocktail Party Environment Can Be Decoded from Single-Trial EEG

PubMed Central

O'Sullivan, James A.; Power, Alan J.; Mesgarani, Nima; Rajaram, Siddharth; Foxe, John J.; Shinn-Cunningham, Barbara G.; Slaney, Malcolm; Shamma, Shihab A.; Lalor, Edmund C.

2015-01-01

How humans solve the cocktail party problem remains unknown. However, progress has been made recently thanks to the realization that cortical activity tracks the amplitude envelope of speech. This has led to the development of regression methods for studying the neurophysiology of continuous speech. One such method, known as stimulus-reconstruction, has been successfully utilized with cortical surface recordings and magnetoencephalography (MEG). However, the former is invasive and gives a relatively restricted view of processing along the auditory hierarchy, whereas the latter is expensive and rare. Thus it would be extremely useful for research in many populations if stimulus-reconstruction was effective using electroencephalography (EEG), a widely available and inexpensive technology. Here we show that single-trial (≈60 s) unaveraged EEG data can be decoded to determine attentional selection in a naturalistic multispeaker environment. Furthermore, we show a significant correlation between our EEG-based measure of attention and performance on a high-level attention task. In addition, by attempting to decode attention at individual latencies, we identify neural processing at ∼200 ms as being critical for solving the cocktail party problem. These findings open up new avenues for studying the ongoing dynamics of cognition using EEG and for developing effective and natural brain–computer interfaces. PMID:24429136

Examining the Predictive Validity of a Dynamic Assessment of Decoding to Forecast Response Tier 2 to Intervention

PubMed Central

Cho, Eunsoo; Compton, Donald L.; Fuchs, Doug; Fuchs, Lynn S.; Bouton, Bobette

2013-01-01

The purpose of this study was to examine the role of a dynamic assessment (DA) of decoding in predicting responsiveness to Tier 2 small group tutoring in a response-to-intervention model. First-grade students (n=134) who did not show adequate progress in Tier 1 based on 6 weeks of progress monitoring received Tier 2 small-group tutoring in reading for 14 weeks. Student responsiveness to Tier 2 was assessed weekly with word identification fluency (WIF). A series of conditional individual growth curve analyses were completed that modeled the correlates of WIF growth (final level of performance and growth). Its purpose was to examine the predictive validity of DA in the presence of 3 sets of variables: static decoding measures, Tier 1 responsiveness indicators, and pre-reading variables (phonemic awareness, rapid letter naming, oral vocabulary, and IQ). DA was a significant predictor of final level and growth, uniquely explaining 3% – 13% of the variance in Tier 2 responsiveness depending on the competing predictors in the model and WIF outcome (final level of performance or growth). Although the additional variances explained uniquely by DA were relatively small, results indicate the potential of DA in identifying Tier 2 nonresponders. PMID:23213050

Examining the predictive validity of a dynamic assessment of decoding to forecast response to tier 2 intervention.

PubMed

Cho, Eunsoo; Compton, Donald L; Fuchs, Douglas; Fuchs, Lynn S; Bouton, Bobette

2014-01-01

The purpose of this study was to examine the role of a dynamic assessment (DA) of decoding in predicting responsiveness to Tier 2 small-group tutoring in a response-to-intervention model. First grade students (n = 134) who did not show adequate progress in Tier 1 based on 6 weeks of progress monitoring received Tier 2 small-group tutoring in reading for 14 weeks. Student responsiveness to Tier 2 was assessed weekly with word identification fluency (WIF). A series of conditional individual growth curve analyses were completed that modeled the correlates of WIF growth (final level of performance and growth). Its purpose was to examine the predictive validity of DA in the presence of three sets of variables: static decoding measures, Tier 1 responsiveness indicators, and prereading variables (phonemic awareness, rapid letter naming, oral vocabulary, and IQ). DA was a significant predictor of final level and growth, uniquely explaining 3% to 13% of the variance in Tier 2 responsiveness depending on the competing predictors in the model and WIF outcome (final level of performance or growth). Although the additional variances explained uniquely by DA were relatively small, results indicate the potential of DA in identifying Tier 2 nonresponders. © Hammill Institute on Disabilities 2012.

Motion Direction Biases and Decoding in Human Visual Cortex

PubMed Central

Wang, Helena X.; Merriam, Elisha P.; Freeman, Jeremy

2014-01-01

Functional magnetic resonance imaging (fMRI) studies have relied on multivariate analysis methods to decode visual motion direction from measurements of cortical activity. Above-chance decoding has been commonly used to infer the motion-selective response properties of the underlying neural populations. Moreover, patterns of reliable response biases across voxels that underlie decoding have been interpreted to reflect maps of functional architecture. Using fMRI, we identified a direction-selective response bias in human visual cortex that: (1) predicted motion-decoding accuracy; (2) depended on the shape of the stimulus aperture rather than the absolute direction of motion, such that response amplitudes gradually decreased with distance from the stimulus aperture edge corresponding to motion origin; and 3) was present in V1, V2, V3, but not evident in MT+, explaining the higher motion-decoding accuracies reported previously in early visual cortex. These results demonstrate that fMRI-based motion decoding has little or no dependence on the underlying functional organization of motion selectivity. PMID:25209297

Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

PubMed Central

Jones, Michael N.

2017-01-01

A central goal of cognitive neuroscience is to decode human brain activity—that is, to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive—that is, capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a probabilistic decoding framework based on a novel topic model—Generalized Correspondence Latent Dirichlet Allocation—that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text—enabling researchers, for the first time, to generate quantitative, context-sensitive interpretations of whole-brain patterns of brain activity. PMID:29059185

Altered cognitive development in the siblings of individuals with schizophrenia

PubMed Central

Barch, Deanna M.; Cohen, Rachel; Csernansky, John

2014-01-01

The goal of the current study was to further investigate the late neurodevelopmental hypothesis of schizophrenia by examining cross-sectional, age-related changes in cognitive function among young adult: 1) siblings of individuals with schizophrenia (N = 66); (2) healthy control participants (N = 77); and (3) the siblings of healthy controls (N = 77). All subjects participated in a battery of tasks in four domains: 1) IQ; 2) working memory; 3) episodic memory; and 4) executive function. We found significant group differences in the relationships between age and performance in working memory and episodic memory, with similar patterns for executive function and verbal IQ. The siblings of individuals with schizophrenia showed impaired performance in working memory, episodic memory, and executive function. In addition, healthy controls and/or their siblings showed age-related improvements in all four cognitive domains, while the siblings of individuals with schizophrenia only showed this for verbal IQ. PMID:25485180

Altered cognitive development in the siblings of individuals with schizophrenia.

PubMed

Barch, Deanna M; Cohen, Rachel; Csernansky, John

2014-03-01

The goal of the current study was to further investigate the late neurodevelopmental hypothesis of schizophrenia by examining cross-sectional, age-related changes in cognitive function among young adult: 1) siblings of individuals with schizophrenia (N = 66); (2) healthy control participants (N = 77); and (3) the siblings of healthy controls (N = 77). All subjects participated in a battery of tasks in four domains: 1) IQ; 2) working memory; 3) episodic memory; and 4) executive function. We found significant group differences in the relationships between age and performance in working memory and episodic memory, with similar patterns for executive function and verbal IQ. The siblings of individuals with schizophrenia showed impaired performance in working memory, episodic memory, and executive function. In addition, healthy controls and/or their siblings showed age-related improvements in all four cognitive domains, while the siblings of individuals with schizophrenia only showed this for verbal IQ.

Latent change models of adult cognition: are changes in processing speed and working memory associated with changes in episodic memory?

PubMed

Hertzog, Christopher; Dixon, Roger A; Hultsch, David F; MacDonald, Stuart W S

2003-12-01

The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations.

Individuals with episodic amnesia are not stuck in time.

PubMed

Craver, Carl F; Kwan, Donna; Steindam, Chloe; Rosenbaum, R Shayna

2014-05-01

The metaphor that individuals with episodic amnesia due to hippocampal damage are "stuck in time" persists in science, philosophy, and everyday life despite mounting evidence that episodic amnesia can spare many central aspects of temporal consciousness. Here we describe some of this evidence, focusing specifically on KC, one of the most thoroughly documented and severe cases of episodic amnesia on record. KC understands the concept of time, knows that it passes, and can orient himself with respect to his personal past and future. He expresses typical attitudes toward his past and future, and he is able to make future-regarding decisions. Theories claiming that the hippocampus plays an essential role in temporal consciousness need to be revised in light of these findings. Copyright © 2014 Elsevier Ltd. All rights reserved.

Soft-output decoding algorithms in iterative decoding of turbo codes

NASA Technical Reports Server (NTRS)

Benedetto, S.; Montorsi, G.; Divsalar, D.; Pollara, F.

1996-01-01

In this article, we present two versions of a simplified maximum a posteriori decoding algorithm. The algorithms work in a sliding window form, like the Viterbi algorithm, and can thus be used to decode continuously transmitted sequences obtained by parallel concatenated codes, without requiring code trellis termination. A heuristic explanation is also given of how to embed the maximum a posteriori algorithms into the iterative decoding of parallel concatenated codes (turbo codes). The performances of the two algorithms are compared on the basis of a powerful rate 1/3 parallel concatenated code. Basic circuits to implement the simplified a posteriori decoding algorithm using lookup tables, and two further approximations (linear and threshold), with a very small penalty, to eliminate the need for lookup tables are proposed.

The Limits of Coding with Joint Constraints on Detected and Undetected Error Rates

NASA Technical Reports Server (NTRS)

Dolinar, Sam; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush

2008-01-01

We develop a remarkably tight upper bound on the performance of a parameterized family of bounded angle maximum-likelihood (BA-ML) incomplete decoders. The new bound for this class of incomplete decoders is calculated from the code's weight enumerator, and is an extension of Poltyrev-type bounds developed for complete ML decoders. This bound can also be applied to bound the average performance of random code ensembles in terms of an ensemble average weight enumerator. We also formulate conditions defining a parameterized family of optimal incomplete decoders, defined to minimize both the total codeword error probability and the undetected error probability for any fixed capability of the decoder to detect errors. We illustrate the gap between optimal and BA-ML incomplete decoding via simulation of a small code.

Direct migration motion estimation and mode decision to decoder for a low-complexity decoder Wyner-Ziv video coding

NASA Astrophysics Data System (ADS)

Lei, Ted Chih-Wei; Tseng, Fan-Shuo

2017-07-01

This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.

Mechanisms of Memory Retrieval in Slow-Wave Sleep

PubMed Central

Cairney, Scott A; Sobczak, Justyna M; Lindsay, Shane

2017-01-01

Abstract Study Objectives Memories are strengthened during sleep. The benefits of sleep for memory can be enhanced by re-exposing the sleeping brain to auditory cues; a technique known as targeted memory reactivation (TMR). Prior studies have not assessed the nature of the retrieval mechanisms underpinning TMR: the matching process between auditory stimuli encountered during sleep and previously encoded memories. We carried out two experiments to address this issue. Methods In Experiment 1, participants associated words with verbal and nonverbal auditory stimuli before an overnight interval in which subsets of these stimuli were replayed in slow-wave sleep. We repeated this paradigm in Experiment 2 with the single difference that the gender of the verbal auditory stimuli was switched between learning and sleep. Results In Experiment 1, forgetting of cued (vs. noncued) associations was reduced by TMR with verbal and nonverbal cues to similar extents. In Experiment 2, TMR with identical nonverbal cues reduced forgetting of cued (vs. noncued) associations, replicating Experiment 1. However, TMR with nonidentical verbal cues reduced forgetting of both cued and noncued associations. Conclusions These experiments suggest that the memory effects of TMR are influenced by the acoustic overlap between stimuli delivered at training and sleep. Our findings hint at the existence of two processing routes for memory retrieval during sleep. Whereas TMR with acoustically identical cues may reactivate individual associations via simple episodic matching, TMR with nonidentical verbal cues may utilize linguistic decoding mechanisms, resulting in widespread reactivation across a broad category of memories. PMID:28934526

Numerical and analytical bounds on threshold error rates for hypergraph-product codes

NASA Astrophysics Data System (ADS)

Kovalev, Alexey A.; Prabhakar, Sanjay; Dumer, Ilya; Pryadko, Leonid P.

2018-06-01

We study analytically and numerically decoding properties of finite-rate hypergraph-product quantum low density parity-check codes obtained from random (3,4)-regular Gallager codes, with a simple model of independent X and Z errors. Several nontrivial lower and upper bounds for the decodable region are constructed analytically by analyzing the properties of the homological difference, equal minus the logarithm of the maximum-likelihood decoding probability for a given syndrome. Numerical results include an upper bound for the decodable region from specific heat calculations in associated Ising models and a minimum-weight decoding threshold of approximately 7 % .

A new LDPC decoding scheme for PDM-8QAM BICM coherent optical communication system

NASA Astrophysics Data System (ADS)

Liu, Yi; Zhang, Wen-bo; Xi, Li-xia; Tang, Xian-feng; Zhang, Xiao-guang

2015-11-01

A new log-likelihood ratio (LLR) message estimation method is proposed for polarization-division multiplexing eight quadrature amplitude modulation (PDM-8QAM) bit-interleaved coded modulation (BICM) optical communication system. The formulation of the posterior probability is theoretically analyzed, and the way to reduce the pre-decoding bit error rate ( BER) of the low density parity check (LDPC) decoder for PDM-8QAM constellations is presented. Simulation results show that it outperforms the traditional scheme, i.e., the new post-decoding BER is decreased down to 50% of that of the traditional post-decoding algorithm.

Optical signal processing for a smart vehicle lighting system using a-SiCH technology

NASA Astrophysics Data System (ADS)

Vieira, M. A.; Vieira, M.; Vieira, P.; Louro, P.

2017-05-01

We propose the use of Visible Light Communication (VLC) for vehicle safety applications, creating a smart vehicle lighting system that combines the functions of illumination and signaling, communications, and positioning. The feasibility of VLC is demonstrated by employing trichromatic Red-Green-Blue (RGB) LEDs as transmitters, since they offer the possibility of Wavelength Division Multiplexing (WDM), which can greatly increase the transmission data rate, when using SiC double p-i-n receivers to encode/decode the information. Trichromatic RGB Light Emitting Diodes (LED)s (RGB-LED) are used together for illumination proposes (headlamps) and individually, each chip, to transmit the driving range distance and data information. An on-off code is used to transmit the data. Free space is the transmission medium. The receivers consist of two stacked amorphous a-H:SiC cells. They combine the simultaneous demultiplexing operation with the photodetection and self-amplification. The proposed coding is based on SiC technology. Multiple Input Multi Output (MIMO) architecture is used. For data transmission, we propose the use of two headlights based on commercially available modulated white RGB-LEDs. For data receiving and decoding we use three a-SiC:H double pin/pin optical processors symmetrically distributed at the vehicle tail Moreover, we present a way to achieve vehicular communication using the parity bits. A representation with a 4 bit original string color message and the transmitted 7 bit string, the encoding and decoding accurate positional information processes and the design of SiC navigation system are discussed and tested. A visible multilateration method estimates the drive distance range by using the decoded information received from several non-collinear transmitters.

A Systolic VLSI Design of a Pipeline Reed-solomon Decoder

NASA Technical Reports Server (NTRS)

Shao, H. M.; Truong, T. K.; Deutsch, L. J.; Yuen, J. H.; Reed, I. S.

1984-01-01

A pipeline structure of a transform decoder similar to a systolic array was developed to decode Reed-Solomon (RS) codes. An important ingredient of this design is a modified Euclidean algorithm for computing the error locator polynomial. The computation of inverse field elements is completely avoided in this modification of Euclid's algorithm. The new decoder is regular and simple, and naturally suitable for VLSI implementation.

A VLSI design of a pipeline Reed-Solomon decoder

NASA Technical Reports Server (NTRS)

Shao, H. M.; Truong, T. K.; Deutsch, L. J.; Yuen, J. H.; Reed, I. S.

1985-01-01

A pipeline structure of a transform decoder similar to a systolic array was developed to decode Reed-Solomon (RS) codes. An important ingredient of this design is a modified Euclidean algorithm for computing the error locator polynomial. The computation of inverse field elements is completely avoided in this modification of Euclid's algorithm. The new decoder is regular and simple, and naturally suitable for VLSI implementation.

Coding/decoding two-dimensional images with orbital angular momentum of light.

PubMed

Chu, Jiaqi; Li, Xuefeng; Smithwick, Quinn; Chu, Daping

2016-04-01

We investigate encoding and decoding of two-dimensional information using the orbital angular momentum (OAM) of light. Spiral phase plates and phase-only spatial light modulators are used in encoding and decoding of OAM states, respectively. We show that off-axis points and spatial variables encoded with a given OAM state can be recovered through decoding with the corresponding complimentary OAM state.

To sort or not to sort: the impact of spike-sorting on neural decoding performance.

PubMed

Todorova, Sonia; Sadtler, Patrick; Batista, Aaron; Chase, Steven; Ventura, Valérie

2014-10-01

Brain-computer interfaces (BCIs) are a promising technology for restoring motor ability to paralyzed patients. Spiking-based BCIs have successfully been used in clinical trials to control multi-degree-of-freedom robotic devices. Current implementations of these devices require a lengthy spike-sorting step, which is an obstacle to moving this technology from the lab to the clinic. A viable alternative is to avoid spike-sorting, treating all threshold crossings of the voltage waveform on an electrode as coming from one putative neuron. It is not known, however, how much decoding information might be lost by ignoring spike identity. We present a full analysis of the effects of spike-sorting schemes on decoding performance. Specifically, we compare how well two common decoders, the optimal linear estimator and the Kalman filter, reconstruct the arm movements of non-human primates performing reaching tasks, when receiving input from various sorting schemes. The schemes we tested included: using threshold crossings without spike-sorting; expert-sorting discarding the noise; expert-sorting, including the noise as if it were another neuron; and automatic spike-sorting using waveform features. We also decoded from a joint statistical model for the waveforms and tuning curves, which does not involve an explicit spike-sorting step. Discarding the threshold crossings that cannot be assigned to neurons degrades decoding: no spikes should be discarded. Decoding based on spike-sorted units outperforms decoding based on electrodes voltage crossings: spike-sorting is useful. The four waveform based spike-sorting methods tested here yield similar decoding efficiencies: a fast and simple method is competitive. Decoding using the joint waveform and tuning model shows promise but is not consistently superior. Our results indicate that simple automated spike-sorting performs as well as the more computationally or manually intensive methods used here. Even basic spike-sorting adds value to the low-threshold waveform-crossing methods often employed in BCI decoding.

To sort or not to sort: the impact of spike-sorting on neural decoding performance

NASA Astrophysics Data System (ADS)

Todorova, Sonia; Sadtler, Patrick; Batista, Aaron; Chase, Steven; Ventura, Valérie

2014-10-01

Objective. Brain-computer interfaces (BCIs) are a promising technology for restoring motor ability to paralyzed patients. Spiking-based BCIs have successfully been used in clinical trials to control multi-degree-of-freedom robotic devices. Current implementations of these devices require a lengthy spike-sorting step, which is an obstacle to moving this technology from the lab to the clinic. A viable alternative is to avoid spike-sorting, treating all threshold crossings of the voltage waveform on an electrode as coming from one putative neuron. It is not known, however, how much decoding information might be lost by ignoring spike identity. Approach. We present a full analysis of the effects of spike-sorting schemes on decoding performance. Specifically, we compare how well two common decoders, the optimal linear estimator and the Kalman filter, reconstruct the arm movements of non-human primates performing reaching tasks, when receiving input from various sorting schemes. The schemes we tested included: using threshold crossings without spike-sorting; expert-sorting discarding the noise; expert-sorting, including the noise as if it were another neuron; and automatic spike-sorting using waveform features. We also decoded from a joint statistical model for the waveforms and tuning curves, which does not involve an explicit spike-sorting step. Main results. Discarding the threshold crossings that cannot be assigned to neurons degrades decoding: no spikes should be discarded. Decoding based on spike-sorted units outperforms decoding based on electrodes voltage crossings: spike-sorting is useful. The four waveform based spike-sorting methods tested here yield similar decoding efficiencies: a fast and simple method is competitive. Decoding using the joint waveform and tuning model shows promise but is not consistently superior. Significance. Our results indicate that simple automated spike-sorting performs as well as the more computationally or manually intensive methods used here. Even basic spike-sorting adds value to the low-threshold waveform-crossing methods often employed in BCI decoding.

47 CFR 11.33 - EAS Decoder.

Code of Federal Regulations, 2011 CFR

2011-10-01

... time periods expire. (4) Display and logging. A visual message shall be developed from any valid header... input. (8) Decoder Programming. Access to decoder programming shall be protected by a lock or other...

PATTERNS OF SYMPTOM ONSET AND REMISSION IN EPISODES OF HOPELESSNESS DEPRESSION

PubMed Central

Iacoviello, Brian M.; Alloy, Lauren B.; Abramson, Lyn Y.; Choi, Jimmy Y.; Morgan, Julia E.

2014-01-01

Background Hopelessness depression (HD) is a subtype of depression postulated by the Hopelessness Theory of Depression to present as a constellation of symptoms occurring when an individual with a specific cognitive vulnerability (negative inferential style) experiences negative life events. In the current study, the course of HD episodes was evaluated prospectively and analyzed to explore patterns of symptom onset and remission. Methods In 169 HD episodes reported by 65 participants, survival analyses were conducted on the time to onset or remission for 29 individual symptoms. Survival analyses yielded probability density graphs for risk of onset and risk of offset that indicated whether the symptom tended to appear or remit early, late, or unpredictably during the episode. Results The symptom of hopelessness often appeared earliest in HD episodes, followed by self-blame, brooding/worry, decreased self-esteem, dependency, and decreased appetite. Hopelessness, decreased self-esteem, self-blame, brooding/worry, dependency, and increased appetite were typically the latest symptoms to remit. Conclusions The current study provided evidence for patterns of symptom onset and remission in HD episodes. Hopelessness and other symptoms predicted to appear according to the Hopelessness Theory were generally the earliest to appear, latest to remit, and appeared to form the core syndrome of these HD episodes. Identifying patterns of symptom onset and remission may provide a tool for subtyping depression episodes. Clinically, these results point to the utility of attending to patterns of symptom onset and remission in patients presenting with HD episodes, particularly for treatment planning and monitoring. PMID:23495016

Relationships among L1 Print Exposure and Early L1 Literacy Skills, L2 Aptitude, and L2 Proficiency

ERIC Educational Resources Information Center

Sparks, Richard L.; Patton, Jon; Ganschow, Leonore; Humbach, Nancy

2012-01-01

Authors examined the relationship between individual differences in L1 print exposure and differences in early L1 skills and later L2 aptitude, L2 proficiency, and L2 classroom achievement. Participants were administered measures of L1 word decoding, spelling, phonemic awareness, reading comprehension, receptive vocabulary, and listening…

Do L1 Reading Achievement and L1 Print Exposure Contribute to the Prediction of L2 Proficiency?

ERIC Educational Resources Information Center

Sparks, Richard L.; Patton, Jon; Ganschow, Leonore; Humbach, Nancy

2012-01-01

The study examined whether individual differences in high school first language (L1) reading achievement and print exposure would account for unique variance in second language (L2) written (word decoding, spelling, writing, reading comprehension) and oral (listening/speaking) proficiency after adjusting for the effects of early L1 literacy and…

The Effectiveness of One-to-One Tutoring by Community Tutors for At-Risk Beginning Readers.

ERIC Educational Resources Information Center

Vadasy, Patricia F.; Jenkins, Joseph R.; Antil, Lawrence R.; Wayne, Susan K.; O'Connor, Rollanda E.

1997-01-01

Twenty at-risk first graders received 30 minutes of individual instruction from community tutors four days a week for up to 23 weeks. Subjects outperformed the control group on all reading, decoding, spelling and segmenting, and writing measures. Tutors who implemented the program with a high degree of fidelity achieved significant effect sizes in…

The Roles of Cognitive and Language Abilities in Predicting Decoding and Reading Comprehension: Comparisons of Dyslexia and Specific Language Impairment

ERIC Educational Resources Information Center

Lauterbach, Alexandra A.; Park, Yujeong; Lombardino, Linda J.

2017-01-01

This study aimed to (a) explore the roles of cognitive and language variables in predicting reading abilities of two groups of individuals with reading disabilities (i.e., dyslexia and specific language impairment) and (b) examine which variable(s) is the most predictive in differentiating two groups. Inclusion/exclusion criteria applied to…

The inadequacy of Individual Educational Program (IEP) goals for high school students with word-level reading difficulties.

PubMed

Catone, William V; Brady, Susan A

2005-06-01

This investigation analyzed goals from the Individual Educational Programs (IEPs) of 54 high school students with diagnosed reading disabilities in basic skills (decoding and/or word identification). Results showed that for 73% of the students, the IEPs written when they were in high school failed to specify any objectives regarding their acute difficulties with basic skills. IEPs from earlier points in the students' educations were also reviewed, as available. For 23 of the students, IEPs were present in the students' files for three time points: elementary school (ES), middle school (MS), and high school (HS). Another 20 students from the sample of 54 had IEPs available for two time points (HS and either MS or ES). Comparisons with the IEPs from younger years showed a pattern of decline from ES to MS to HS in the percentage of IEPs that commented on or set goals pertaining to weaknesses in decoding. These findings suggest that basic skills deficits that persist into the upper grade levels are not being sufficiently targeted for remediation, and help explain why older students frequently fail to resolve their reading problems.

Relationship between daily affect and overeating-only, loss of control eating-only, and binge eating episodes in obese adults.

PubMed

Berg, Kelly C; Peterson, Carol B; Crosby, Ross D; Cao, Li; Crow, Scott J; Engel, Scott G; Wonderlich, Stephen A

2014-01-30

The two objectives of the current study were: (1) to identify daily patterns of negative affect (NA) in obese individuals; and (2) to determine whether daily affect patterns were related to overeating without loss of control (OE-only), loss of control eating without overeating (LOC-only), and binge eating (BE) episodes. Fifty obese (BMI=40.3 ± 08.5) adults (84.0% female) completed a two-week ecological momentary assessment protocol during which they completed assessments of NA and indicated whether their eating episodes were characterized by OE and/or LOC. Latent growth mixture modeling (LGMM) was used to identify daily trajectories of NA. GEE analysis was used to determine whether daily affect trajectories were differentially related to the frequency of OE-only, LOC-only, and BE episodes. The LGMM analyses identified nine unique trajectories of NA. Significantly higher frequencies of OE-only and BE episodes occurred on days characterized by high or increasing levels of NA. There were no significant differences between classes for the frequency of LOC-only episodes. These data suggest that NA may act as an antecedent to OE-only and BE episodes and that targeting "problematic affect days" may reduce the occurrence of OE-only and BE episodes among obese individuals. © 2013 Elsevier Ireland Ltd. All rights reserved.

The Neurocognitive Development of Episodic Prospection and Its Implications for Academic Achievement

ERIC Educational Resources Information Center

Prabhakar, Janani; Coughlin, Christine; Ghetti, Simona

2016-01-01

Episodic prospection is the ability to mentally simulate personal future events that are rich in contextual detail and plausible for the individual. It therefore incorporates episodic information (who, what, where, and when of a particular event), as well as details about one's self (e.g., knowledge, goals, motivations and desires). The ability to…

Atypical Neurophysiology Underlying Episodic and Semantic Memory in Adults with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Massand, Esha; Bowler, Dermot M.

2015-01-01

Individuals with autism spectrum disorder (ASD) show atypicalities in episodic memory (Boucher et al. in Psychological Bulletin, 138 (3), 458-496, 2012). We asked participants to recall the colours of a set of studied line drawings (episodic judgement), or to recognize line drawings alone (semantic judgement). Cycowicz et al. ("Journal of…

On the error probability of general tree and trellis codes with applications to sequential decoding

NASA Technical Reports Server (NTRS)

Johannesson, R.

1973-01-01

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.

Viterbi decoding for satellite and space communication.

NASA Technical Reports Server (NTRS)

Heller, J. A.; Jacobs, I. M.

1971-01-01

Convolutional coding and Viterbi decoding, along with binary phase-shift keyed modulation, is presented as an efficient system for reliable communication on power limited satellite and space channels. Performance results, obtained theoretically and through computer simulation, are given for optimum short constraint length codes for a range of code constraint lengths and code rates. System efficiency is compared for hard receiver quantization and 4 and 8 level soft quantization. The effects on performance of varying of certain parameters relevant to decoder complexity and cost are examined. Quantitative performance degradation due to imperfect carrier phase coherence is evaluated and compared to that of an uncoded system. As an example of decoder performance versus complexity, a recently implemented 2-Mbit/sec constraint length 7 Viterbi decoder is discussed. Finally a comparison is made between Viterbi and sequential decoding in terms of suitability to various system requirements.

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights

PubMed Central

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks. PMID:26973503

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights.

PubMed

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks.

Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features.

PubMed

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-01-01

Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed objects can be predicted from brain activity during sleep using statistical decoders trained with stimulus-induced brain activity. However, it remains unclear whether and how visual image features associated with dreamed objects are represented in the brain. In this study, we used a deep neural network (DNN) model for object recognition as a proxy for hierarchical visual feature representation, and DNN features for dreamed objects were analyzed with brain decoding of fMRI data collected during dreaming. The decoders were first trained with stimulus-induced brain activity labeled with the feature values of the stimulus image from multiple DNN layers. The decoders were then used to decode DNN features from the dream fMRI data, and the decoded features were compared with the averaged features of each object category calculated from a large-scale image database. We found that the feature values decoded from the dream fMRI data positively correlated with those associated with dreamed object categories at mid- to high-level DNN layers. Using the decoded features, the dreamed object category could be identified at above-chance levels by matching them to the averaged features for candidate categories. The results suggest that dreaming recruits hierarchical visual feature representations associated with objects, which may support phenomenal aspects of dream experience.

Visual coding with a population of direction-selective neurons.

PubMed

Fiscella, Michele; Franke, Felix; Farrow, Karl; Müller, Jan; Roska, Botond; da Silveira, Rava Azeredo; Hierlemann, Andreas

2015-10-01

The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions. Copyright © 2015 the American Physiological Society.

Visual coding with a population of direction-selective neurons

PubMed Central

Farrow, Karl; Müller, Jan; Roska, Botond; Azeredo da Silveira, Rava; Hierlemann, Andreas

2015-01-01

The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions. PMID:26289471

Quantum cryptographic system with reduced data loss

DOEpatents

Lo, H.K.; Chau, H.F.

1998-03-24

A secure method for distributing a random cryptographic key with reduced data loss is disclosed. Traditional quantum key distribution systems employ similar probabilities for the different communication modes and thus reject at least half of the transmitted data. The invention substantially reduces the amount of discarded data (those that are encoded and decoded in different communication modes e.g. using different operators) in quantum key distribution without compromising security by using significantly different probabilities for the different communication modes. Data is separated into various sets according to the actual operators used in the encoding and decoding process and the error rate for each set is determined individually. The invention increases the key distribution rate of the BB84 key distribution scheme proposed by Bennett and Brassard in 1984. Using the invention, the key distribution rate increases with the number of quantum signals transmitted and can be doubled asymptotically. 23 figs.

Advanced Interrogation of Fiber-Optic Bragg Grating and Fabry-Perot Sensors with KLT Analysis

PubMed Central

Tosi, Daniele

2015-01-01

The Karhunen-Loeve Transform (KLT) is applied to accurate detection of optical fiber sensors in the spectral domain. By processing an optical spectrum, although coarsely sampled, through the KLT, and subsequently processing the obtained eigenvalues, it is possible to decode a plurality of optical sensor results. The KLT returns higher accuracy than other demodulation techniques, despite coarse sampling, and exhibits higher resilience to noise. Three case studies of KLT-based processing are presented, representing most of the current challenges in optical fiber sensing: (1) demodulation of individual sensors, such as Fiber Bragg Gratings (FBGs) and Fabry-Perot Interferometers (FPIs); (2) demodulation of dual (FBG/FPI) sensors; (3) application of reverse KLT to isolate different sensors operating on the same spectrum. A simulative outline is provided to demonstrate the KLT operation and estimate performance; a brief experimental section is also provided to validate accurate FBG and FPI decoding. PMID:26528975

Advanced Interrogation of Fiber-Optic Bragg Grating and Fabry-Perot Sensors with KLT Analysis.

PubMed

Tosi, Daniele

2015-10-29

The Karhunen-Loeve Transform (KLT) is applied to accurate detection of optical fiber sensors in the spectral domain. By processing an optical spectrum, although coarsely sampled, through the KLT, and subsequently processing the obtained eigenvalues, it is possible to decode a plurality of optical sensor results. The KLT returns higher accuracy than other demodulation techniques, despite coarse sampling, and exhibits higher resilience to noise. Three case studies of KLT-based processing are presented, representing most of the current challenges in optical fiber sensing: (1) demodulation of individual sensors, such as Fiber Bragg Gratings (FBGs) and Fabry-Perot Interferometers (FPIs); (2) demodulation of dual (FBG/FPI) sensors; (3) application of reverse KLT to isolate different sensors operating on the same spectrum. A simulative outline is provided to demonstrate the KLT operation and estimate performance; a brief experimental section is also provided to validate accurate FBG and FPI decoding.

Differences in the emergent coding properties of cortical and striatal ensembles

PubMed Central

Ma, L.; Hyman, J.M.; Lindsay, A.J.; Phillips, A.G.; Seamans, J.K.

2016-01-01

The function of a given brain region is often defined by the coding properties of its individual neurons, yet how this information is combined at the ensemble level is an equally important consideration. In the present study, multiple neurons from the anterior cingulate cortex (ACC) and the dorsal striatum (DS) were recorded simultaneously as rats performed different sequences of the same three actions. Sequence and lever decoding was remarkably similar on a per-neuron basis in the two regions. At the ensemble level, sequence-specific representations in the DS appeared synchronously but transiently along with the representation of lever location, while these two streams of information appeared independently and asynchronously in the ACC. As a result the ACC achieved superior ensemble decoding accuracy overall. Thus, the manner in which information was combined across neurons in an ensemble determined the functional separation of the ACC and DS on this task. PMID:24974796

An online BCI game based on the decoding of users' attention to color stimulus.

PubMed

Yang, Lingling; Leung, Howard

2013-01-01

Studies have shown that statistically there are differences in theta, alpha and beta band powers when people look at blue and red colors. In this paper, a game has been developed to test whether these statistical differences are good enough for online Brain Computer Interface (BCI) application. We implemented a two-choice BCI game in which the subject makes the choice by looking at a color option and our system decodes the subject's intention by analyzing the EEG signal. In our system, band power features of the EEG data were used to train a support vector machine (SVM) classification model. An online mechanism was adopted to update the classification model during the training stage to account for individual differences. Our results showed that an accuracy of 70%-80% could be achieved and it provided evidence for the possibility in applying color stimuli to BCI applications.

Quantum cryptographic system with reduced data loss

DOEpatents

Lo, Hoi-Kwong; Chau, Hoi Fung

1998-01-01

A secure method for distributing a random cryptographic key with reduced data loss. Traditional quantum key distribution systems employ similar probabilities for the different communication modes and thus reject at least half of the transmitted data. The invention substantially reduces the amount of discarded data (those that are encoded and decoded in different communication modes e.g. using different operators) in quantum key distribution without compromising security by using significantly different probabilities for the different communication modes. Data is separated into various sets according to the actual operators used in the encoding and decoding process and the error rate for each set is determined individually. The invention increases the key distribution rate of the BB84 key distribution scheme proposed by Bennett and Brassard in 1984. Using the invention, the key distribution rate increases with the number of quantum signals transmitted and can be doubled asymptotically.

All-in-one visual and computer decoding of multiple secrets: translated-flip VC with polynomial-style sharing

NASA Astrophysics Data System (ADS)

Wu, Chia-Hua; Lee, Suiang-Shyan; Lin, Ja-Chen

2017-06-01

This all-in-one hiding method creates two transparencies that have several decoding options: visual decoding with or without translation flipping and computer decoding. In visual decoding, two less-important (or fake) binary secret images S1 and S2 can be revealed. S1 is viewed by the direct stacking of two transparencies. S2 is viewed by flipping one transparency and translating the other to a specified coordinate before stacking. Finally, important/true secret files can be decrypted by a computer using the information extracted from transparencies. The encoding process to hide this information includes the translated-flip visual cryptography, block types, the ways to use polynomial-style sharing, and linear congruential generator. If a thief obtained both transparencies, which are stored in distinct places, he still needs to find the values of keys used in computer decoding to break through after viewing S1 and/or S2 by stacking. However, the thief might just try every other kind of stacking and finally quit finding more secrets; for computer decoding is totally different from stacking decoding. Unlike traditional image hiding that uses images as host media, our method hides fine gray-level images in binary transparencies. Thus, our host media are transparencies. Comparisons and analysis are provided.

Multiscale decoding for reliable brain-machine interface performance over time.

PubMed

Han-Lin Hsieh; Wong, Yan T; Pesaran, Bijan; Shanechi, Maryam M

2017-07-01

Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously use spikes and other recording modalities such as local field potentials (LFP), which are more robust to signal degradation over time. We have developed a multiscale decoder that can simultaneously model the different statistical profiles of multi-scale spike/LFP activity (discrete spikes vs. continuous LFP). This decoder can also run at multiple time-scales (millisecond for spikes vs. tens of milliseconds for LFP). Here, we validate the multiscale decoder for estimating the movement of 7 major upper-arm joint angles in a non-human primate (NHP) during a 3D reach-to-grasp task. The multiscale decoder uses motor cortical spike/LFP recordings as its input. We show that the multiscale decoder can improve decoding accuracy by adding information from LFP to spikes, while running at the fast millisecond time-scale of the spiking activity. Moreover, this improvement is achieved using relatively few LFP channels, demonstrating the robustness of the approach. These results suggest that using multiscale decoders has the potential to improve the reliability and longevity of BMIs.

Decoding the Semantic Content of Natural Movies from Human Brain Activity

PubMed Central

Huth, Alexander G.; Lee, Tyler; Nishimoto, Shinji; Bilenko, Natalia Y.; Vu, An T.; Gallant, Jack L.

2016-01-01

One crucial test for any quantitative model of the brain is to show that the model can be used to accurately decode information from evoked brain activity. Several recent neuroimaging studies have decoded the structure or semantic content of static visual images from human brain activity. Here we present a decoding algorithm that makes it possible to decode detailed information about the object and action categories present in natural movies from human brain activity signals measured by functional MRI. Decoding is accomplished using a hierarchical logistic regression (HLR) model that is based on labels that were manually assigned from the WordNet semantic taxonomy. This model makes it possible to simultaneously decode information about both specific and general categories, while respecting the relationships between them. Our results show that we can decode the presence of many object and action categories from averaged blood-oxygen level-dependent (BOLD) responses with a high degree of accuracy (area under the ROC curve > 0.9). Furthermore, we used this framework to test whether semantic relationships defined in the WordNet taxonomy are represented the same way in the human brain. This analysis showed that hierarchical relationships between general categories and atypical examples, such as organism and plant, did not seem to be reflected in representations measured by BOLD fMRI. PMID:27781035

On the decoding process in ternary error-correcting output codes.

PubMed

Escalera, Sergio; Pujol, Oriol; Radeva, Petia

2010-01-01

A common way to model multiclass classification problems is to design a set of binary classifiers and to combine them. Error-Correcting Output Codes (ECOC) represent a successful framework to deal with these type of problems. Recent works in the ECOC framework showed significant performance improvements by means of new problem-dependent designs based on the ternary ECOC framework. The ternary framework contains a larger set of binary problems because of the use of a "do not care" symbol that allows us to ignore some classes by a given classifier. However, there are no proper studies that analyze the effect of the new symbol at the decoding step. In this paper, we present a taxonomy that embeds all binary and ternary ECOC decoding strategies into four groups. We show that the zero symbol introduces two kinds of biases that require redefinition of the decoding design. A new type of decoding measure is proposed, and two novel decoding strategies are defined. We evaluate the state-of-the-art coding and decoding strategies over a set of UCI Machine Learning Repository data sets and into a real traffic sign categorization problem. The experimental results show that, following the new decoding strategies, the performance of the ECOC design is significantly improved.

Multisession, noninvasive closed-loop neuroprosthetic control of grasping by upper limb amputees.

PubMed

Agashe, H A; Paek, A Y; Contreras-Vidal, J L

2016-01-01

Upper limb amputation results in a severe reduction in the quality of life of affected individuals due to their inability to easily perform activities of daily living. Brain-machine interfaces (BMIs) that translate grasping intent from the brain's neural activity into prosthetic control may increase the level of natural control currently available in myoelectric prostheses. Current BMI techniques demonstrate accurate arm position and single degree-of-freedom grasp control but are invasive and require daily recalibration. In this study we tested if transradial amputees (A1 and A2) could control grasp preshaping in a prosthetic device using a noninvasive electroencephalography (EEG)-based closed-loop BMI system. Participants attempted to grasp presented objects by controlling two grasping synergies, in 12 sessions performed over 5 weeks. Prior to closed-loop control, the first six sessions included a decoder calibration phase using action observation by the participants; thereafter, the decoder was fixed to examine neuroprosthetic performance in the absence of decoder recalibration. Ability of participants to control the prosthetic was measured by the success rate of grasping; ie, the percentage of trials within a session in which presented objects were successfully grasped. Participant A1 maintained a steady success rate (63±3%) across sessions (significantly above chance [41±5%] for 11 sessions). Participant A2, who was under the influence of pharmacological treatment for depression, hormone imbalance, pain management (for phantom pain as well as shoulder joint inflammation), and drug dependence, achieved a success rate of 32±2% across sessions (significantly above chance [27±5%] in only two sessions). EEG signal quality was stable across sessions, but the decoders created during the first six sessions showed variation, indicating EEG features relevant to decoding at a smaller timescale (100ms) may not be stable. Overall, our results show that (a) an EEG-based BMI for grasping is a feasible strategy for further investigation of prosthetic control by amputees, and (b) factors that may affect brain activity such as medication need further examination to improve accuracy and stability of BMI performance. © 2016 Elsevier B.V. All rights reserved.

Characterizing Durations of Heroin Abstinence in the California Civil Addict Program: Results From a 33-Year Observational Cohort Study

PubMed Central

Nosyk, Bohdan; Anglin, M. Douglas; Brecht, Mary-Lynn; Lima, Viviane Dias; Hser, Yih-Ing

2013-01-01

In accordance with the chronic disease model of opioid dependence, cessation is often observed as a longitudinal process rather than a discrete endpoint. We aimed to characterize and identify predictors of periods of heroin abstinence in the natural history of recovery from opioid dependence. Data were collected on participants from California who were enrolled in the Civil Addict Program from 1962 onward by use of a natural history interview. Multivariate regression using proportional hazards frailty models was applied to identify independent predictors and correlates of repeated abstinence episode durations. Among 471 heroin-dependent males, 387 (82.2%) reported 932 abstinence episodes, 60.3% of which lasted at least 1 year. Multivariate analysis revealed several important findings. First, demographic factors such as age and ethnicity did not explain variation in durations of abstinence episodes. However, employment and lower drug use severity predicted longer episodes. Second, abstinence durations were longer following sustained treatment versus incarceration. Third, individuals with multiple abstinence episodes remained abstinent for longer durations in successive episodes. Finally, abstinence episodes initiated >10 and ≤20 years after first use lasted longer than others. Public policy facilitating engagement of opioid-dependent individuals in maintenance-oriented drug treatment and employment is recommended to achieve and sustain opioid abstinence. PMID:23445901

Impaired Social and Role Function in Ultra-High Risk for Psychosis and First-Episode Schizophrenia: Its Relations with Negative Symptoms.

PubMed

Lee, So Jung; Kim, Kyung Ran; Lee, Su Young; An, Suk Kyoon

2017-03-01

Psychosocial dysfunction was a nettlesome of schizophrenia even in their prodromal phase as well as first episode and its relations with psychopathology were not determined. The aim of the present study was to examine whether the social and role function impairment was found in ultra-high risk for psychosis (UHR) individuals as well as first-episode schizophrenia patients and to explore its relations with psychopathology. Thirty-seven normal controls, 63 UHR participants and 28 young, first-episode schizophrenia patients were recruited. Psychosocial functioning was examined by using Global function: Social and Role scale. Psychopathologies of positive, negative and depressive symptom were also measured. Social and role functioning in UHR were compromised at the equivalent level of those of first-episode schizophrenia patients. Multiple linear regression analysis revealed that social and role dysfunction was associated with negative symptoms in each UHR and first-episode schizophrenia group. These findings suggest that the significant impairment of social and role function may be appeared before the active psychosis onset at the level of extent to those of first-episode schizophrenia patients. The psychosocial intervention strategy especially targeting the negative symptoms should be developed and provided to individuals from their prepsychotic stage of schizophrenia.

Impaired Social and Role Function in Ultra-High Risk for Psychosis and First-Episode Schizophrenia: Its Relations with Negative Symptoms.

PubMed

Lee, So Jung; Kim, Kyung Ran; Lee, Su Young; An, Suk Kyoon

2017-09-01

Psychosocial dysfunction was a nettlesome problem of schizophrenia even in their prodromal phase as well as in their first-episode. In addition, its relations with psychopathology were not determined. The aim of the present study was to examine whether the social and role function impairment was found in ultra-high risk for psychosis (UHR) individuals as well as first-episode schizophrenia patients and to explore its relations with psychopathology. Thirty-seven normal controls, 63 UHR participants and 28 young, first-episode schizophrenia patients were recruited. Psychosocial functioning was examined by using Global function: Social and Role scale. Psychopathologies of positive, negative and depressive symptom were also measured. Social and role functioning in UHR were compromised at the equivalent level of those of first-episode schizophrenia patients. Multiple linear regression analysis revealed that social and role dysfunction was associated with negative symptoms in each UHR and first-episode schizophrenia group. These findings suggest that the significant impairment of social and role function may be appeared before the active psychosis onset at the level of extent to those of first-episode schizophrenia patients. The psychosocial intervention strategy especially targeting the negative symptoms should be developed and provided to individuals from their prepsychotic stage of schizophrenia.

A model for sequential decoding overflow due to a noisy carrier reference. [communication performance prediction

NASA Technical Reports Server (NTRS)

Layland, J. W.

1974-01-01

An approximate analysis of the effect of a noisy carrier reference on the performance of sequential decoding is presented. The analysis uses previously developed techniques for evaluating noisy reference performance for medium-rate uncoded communications adapted to sequential decoding for data rates of 8 to 2048 bits/s. In estimating the ten to the minus fourth power deletion probability thresholds for Helios, the model agrees with experimental data to within the experimental tolerances. The computational problem involved in sequential decoding, carrier loop effects, the main characteristics of the medium-rate model, modeled decoding performance, and perspectives on future work are discussed.

State-space decoding of primary afferent neuron firing rates

NASA Astrophysics Data System (ADS)

Wagenaar, J. B.; Ventura, V.; Weber, D. J.

2011-02-01

Kinematic state feedback is important for neuroprostheses to generate stable and adaptive movements of an extremity. State information, represented in the firing rates of populations of primary afferent (PA) neurons, can be recorded at the level of the dorsal root ganglia (DRG). Previous work in cats showed the feasibility of using DRG recordings to predict the kinematic state of the hind limb using reverse regression. Although accurate decoding results were attained, reverse regression does not make efficient use of the information embedded in the firing rates of the neural population. In this paper, we present decoding results based on state-space modeling, and show that it is a more principled and more efficient method for decoding the firing rates in an ensemble of PA neurons. In particular, we show that we can extract confounded information from neurons that respond to multiple kinematic parameters, and that including velocity components in the firing rate models significantly increases the accuracy of the decoded trajectory. We show that, on average, state-space decoding is twice as efficient as reverse regression for decoding joint and endpoint kinematics.

Utilizing sensory prediction errors for movement intention decoding: A new methodology

PubMed Central

Nakamura, Keigo; Ando, Hideyuki

2018-01-01

We propose a new methodology for decoding movement intentions of humans. This methodology is motivated by the well-documented ability of the brain to predict sensory outcomes of self-generated and imagined actions using so-called forward models. We propose to subliminally stimulate the sensory modality corresponding to a user’s intended movement, and decode a user’s movement intention from his electroencephalography (EEG), by decoding for prediction errors—whether the sensory prediction corresponding to a user’s intended movement matches the subliminal sensory stimulation we induce. We tested our proposal in a binary wheelchair turning task in which users thought of turning their wheelchair either left or right. We stimulated their vestibular system subliminally, toward either the left or the right direction, using a galvanic vestibular stimulator and show that the decoding for prediction errors from the EEG can radically improve movement intention decoding performance. We observed an 87.2% median single-trial decoding accuracy across tested participants, with zero user training, within 96 ms of the stimulation, and with no additional cognitive load on the users because the stimulation was subliminal. PMID:29750195

Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions.

PubMed

Contini, Erika W; Wardle, Susan G; Carlson, Thomas A

2017-10-01

Visual object recognition is a complex, dynamic process. Multivariate pattern analysis methods, such as decoding, have begun to reveal how the brain processes complex visual information. Recently, temporal decoding methods for EEG and MEG have offered the potential to evaluate the temporal dynamics of object recognition. Here we review the contribution of M/EEG time-series decoding methods to understanding visual object recognition in the human brain. Consistent with the current understanding of the visual processing hierarchy, low-level visual features dominate decodable object representations early in the time-course, with more abstract representations related to object category emerging later. A key finding is that the time-course of object processing is highly dynamic and rapidly evolving, with limited temporal generalisation of decodable information. Several studies have examined the emergence of object category structure, and we consider to what degree category decoding can be explained by sensitivity to low-level visual features. Finally, we evaluate recent work attempting to link human behaviour to the neural time-course of object processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploring Differential Effects across Two Decoding Treatments on Item-Level Transfer in Children with Significant Word Reading Difficulties: A New Approach for Testing Intervention Elements

ERIC Educational Resources Information Center

Steacy, Laura M.; Elleman, Amy M.; Lovett, Maureen W.; Compton, Donald L.

2016-01-01

In English, gains in decoding skill do not map directly onto increases in word reading. However, beyond the Self-Teaching Hypothesis, little is known about the transfer of decoding skills to word reading. In this study, we offer a new approach to testing specific decoding elements on transfer to word reading. To illustrate, we modeled word-reading…

Comparison of memory thresholds for planar qudit geometries

NASA Astrophysics Data System (ADS)

Marks, Jacob; Jochym-O'Connor, Tomas; Gheorghiu, Vlad

2017-11-01

We introduce and analyze a new type of decoding algorithm called general color clustering, based on renormalization group methods, to be used in qudit color codes. The performance of this decoder is analyzed under a generalized bit-flip error model, and is used to obtain the first memory threshold estimates for qudit 6-6-6 color codes. The proposed decoder is compared with similar decoding schemes for qudit surface codes as well as the current leading qubit decoders for both sets of codes. We find that, as with surface codes, clustering performs sub-optimally for qubit color codes, giving a threshold of 5.6 % compared to the 8.0 % obtained through surface projection decoding methods. However, the threshold rate increases by up to 112% for large qudit dimensions, plateauing around 11.9 % . All the analysis is performed using QTop, a new open-source software for simulating and visualizing topological quantum error correcting codes.

A high data rate universal lattice decoder on FPGA

NASA Astrophysics Data System (ADS)

Ma, Jing; Huang, Xinming; Kura, Swapna

2005-06-01

This paper presents the architecture design of a high data rate universal lattice decoder for MIMO channels on FPGA platform. A phost strategy based lattice decoding algorithm is modified in this paper to reduce the complexity of the closest lattice point search. The data dependency of the improved algorithm is examined and a parallel and pipeline architecture is developed with the iterative decoding function on FPGA and the division intensive channel matrix preprocessing on DSP. Simulation results demonstrate that the improved lattice decoding algorithm provides better bit error rate and less iteration number compared with the original algorithm. The system prototype of the decoder shows that it supports data rate up to 7Mbit/s on a Virtex2-1000 FPGA, which is about 8 times faster than the original algorithm on FPGA platform and two-orders of magnitude better than its implementation on a DSP platform.

Non-tables look-up search algorithm for efficient H.264/AVC context-based adaptive variable length coding decoding

NASA Astrophysics Data System (ADS)

Han, Yishi; Luo, Zhixiao; Wang, Jianhua; Min, Zhixuan; Qin, Xinyu; Sun, Yunlong

2014-09-01

In general, context-based adaptive variable length coding (CAVLC) decoding in H.264/AVC standard requires frequent access to the unstructured variable length coding tables (VLCTs) and significant memory accesses are consumed. Heavy memory accesses will cause high power consumption and time delays, which are serious problems for applications in portable multimedia devices. We propose a method for high-efficiency CAVLC decoding by using a program instead of all the VLCTs. The decoded codeword from VLCTs can be obtained without any table look-up and memory access. The experimental results show that the proposed algorithm achieves 100% memory access saving and 40% decoding time saving without degrading video quality. Additionally, the proposed algorithm shows a better performance compared with conventional CAVLC decoding, such as table look-up by sequential search, table look-up by binary search, Moon's method, and Kim's method.

Error-correction coding for digital communications

NASA Astrophysics Data System (ADS)

Clark, G. C., Jr.; Cain, J. B.

This book is written for the design engineer who must build the coding and decoding equipment and for the communication system engineer who must incorporate this equipment into a system. It is also suitable as a senior-level or first-year graduate text for an introductory one-semester course in coding theory. Fundamental concepts of coding are discussed along with group codes, taking into account basic principles, practical constraints, performance computations, coding bounds, generalized parity check codes, polynomial codes, and important classes of group codes. Other topics explored are related to simple nonalgebraic decoding techniques for group codes, soft decision decoding of block codes, algebraic techniques for multiple error correction, the convolutional code structure and Viterbi decoding, syndrome decoding techniques, and sequential decoding techniques. System applications are also considered, giving attention to concatenated codes, coding for the white Gaussian noise channel, interleaver structures for coded systems, and coding for burst noise channels.

Functioning before and after a major depressive episode: pre-existing vulnerability or scar? A prospective three-wave population-based study.

PubMed

Bos, E H; Ten Have, M; van Dorsselaer, S; Jeronimus, B F; de Graaf, R; de Jonge, P

2018-01-14

The vulnerability hypothesis suggests that impairments after remission of depressive episodes reflect a pre-existing vulnerability, while the scar hypothesis proposes that depression leaves residual impairments that confer risk of subsequent episodes. We prospectively examined vulnerability and scar effects in mental and physical functioning in a representative Dutch population sample. Three waves were used from the Netherlands Mental Health Survey and Incidence Study-2, a population-based study with a 6-years follow-up. Mental and physical functioning were assessed with the Medical Outcomes Study Short Form (SF-36). Major depressive disorder (MDD) was assessed with the Composite International Diagnostic Interview 3.0. Vulnerability effects were examined by comparing healthy controls (n = 2826) with individuals who developed a first-onset depressive episode during first follow-up but did not have a lifetime diagnosis of MDD at baseline (n = 181). Scarring effects were examined by comparing pre- and post-morbid functioning in individuals who developed a depressive episode after baseline that was remitted at the third wave (n = 108). Both mental (B = -5.4, s.e. = 0.9, p < 0.001) and physical functioning (B = -8.2, s.e. = 1.1, p < 0.001) at baseline were lower in individuals who developed a first depressive episode after baseline compared with healthy controls. This effect was most pronounced in people who developed a severe episode. No firm evidence of scarring in mental or physical functioning was found. In unadjusted analyses, physical functioning was still lowered post-morbidly (B = -5.1, s.e. = 2.1, p = 0.014), but this effect disappeared in adjusted analyses. Functional impairments after remission of depression seem to reflect a pre-existing vulnerability rather than a scar.

Soft-Decision Decoding of Binary Linear Block Codes Based on an Iterative Search Algorithm

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Moorthy, H. T.

1997-01-01

This correspondence presents a suboptimum soft-decision decoding scheme for binary linear block codes based on an iterative search algorithm. The scheme uses an algebraic decoder to iteratively generate a sequence of candidate codewords one at a time using a set of test error patterns that are constructed based on the reliability information of the received symbols. When a candidate codeword is generated, it is tested based on an optimality condition. If it satisfies the optimality condition, then it is the most likely (ML) codeword and the decoding stops. If it fails the optimality test, a search for the ML codeword is conducted in a region which contains the ML codeword. The search region is determined by the current candidate codeword and the reliability of the received symbols. The search is conducted through a purged trellis diagram for the given code using the Viterbi algorithm. If the search fails to find the ML codeword, a new candidate is generated using a new test error pattern, and the optimality test and search are renewed. The process of testing and search continues until either the MEL codeword is found or all the test error patterns are exhausted and the decoding process is terminated. Numerical results show that the proposed decoding scheme achieves either practically optimal performance or a performance only a fraction of a decibel away from the optimal maximum-likelihood decoding with a significant reduction in decoding complexity compared with the Viterbi decoding based on the full trellis diagram of the codes.

From classic motor imagery to complex movement intention decoding: The noninvasive Graz-BCI approach.

PubMed

Müller-Putz, G R; Schwarz, A; Pereira, J; Ofner, P

2016-01-01

In this chapter, we give an overview of the Graz-BCI research, from the classic motor imagery detection to complex movement intentions decoding. We start by describing the classic motor imagery approach, its application in tetraplegic end users, and the significant improvements achieved using coadaptive brain-computer interfaces (BCIs). These strategies have the drawback of not mirroring the way one plans a movement. To achieve a more natural control-and to reduce the training time-the movements decoded by the BCI need to be closely related to the user's intention. Within this natural control, we focus on the kinematic level, where movement direction and hand position or velocity can be decoded from noninvasive recordings. First, we review movement execution decoding studies, where we describe the decoding algorithms, their performance, and associated features. Second, we describe the major findings in movement imagination decoding, where we emphasize the importance of estimating the sources of the discriminative features. Third, we introduce movement target decoding, which could allow the determination of the target without knowing the exact movement-by-movement details. Aside from the kinematic level, we also address the goal level, which contains relevant information on the upcoming action. Focusing on hand-object interaction and action context dependency, we discuss the possible impact of some recent neurophysiological findings in the future of BCI control. Ideally, the goal and the kinematic decoding would allow an appropriate matching of the BCI to the end users' needs, overcoming the limitations of the classic motor imagery approach. © 2016 Elsevier B.V. All rights reserved.

Using low-frequency earthquake families on the San Andreas fault as deep creepmeters

NASA Astrophysics Data System (ADS)

Thomas, A.; Beeler, N. M.; Bletery, Q.; Burgmann, R.; Shelly, D. R.

2017-12-01

The San Andreas fault hosts tectonic tremor and low-frequency earthquakes (LFEs) similar to those in subduction zone environments. These LFEs are grouped into families based on waveform similarity and locate between 16 and 29 km depth along a 150-km-long section of the fault centered on Parkfield, CA. ­Within individual LFE families event occurrence is not steady. In some families, bursts of a few events recur on timescales of days while in other families there are nearly quiescent periods that often last for months followed by episodes where hundreds of events occur over the course of a few days. These two different styles of LFE occurrence are called continuous and episodic respectively. LFEs are often assumed to reflect persistent regions that periodically fail during the aseismic shear of the surrounding fault allowing them to be used as creepmeters. We test this idea by formalizing the definition of a creepmeter (the LFE occurrence rate is proportional to the local fault slip rate), determining whether this definition is consistent with the observations, and over what timescale. We use the recurrence intervals of LFEs within individual families to create a catalog of LFE bursts. For the episodic families, we consider both longer duration (multiday) inferred creep episodes (dubbed long-timescale episodic) as well as the frequent short-term bursts of events that occur many times during inferred creep episodes (dubbed short-timescale episodic). We then use the recurrence intervals of LFE bursts to estimate the timing, duration, recurrence interval, slip, and slip rate associated with inferred slow slip events. We find that continuous families and the short-timescale episodic families appear to be inconsistent with our definition of a creepmeter (defined on the recurrence interval timescale) because their estimated durations are not physically meaningful. A straight-forward interpretation of the frequent short-term bursts of the continuous and short-timescale episodic families is that they do not represent individual creep events but rather are persistent asperities that are driven to failure by quasi-continuous creep on the surrounding fault. In contrast, episodic families likely define sections of the fault where slip is distinctly episodic in well-defined SSEs that slip at 15 times the long-term rate.

Similar patterns of neural activity predict memory function during encoding and retrieval.

PubMed

Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

Multiformat decoder for a DSP-based IP set-top box

NASA Astrophysics Data System (ADS)

Pescador, F.; Garrido, M. J.; Sanz, C.; Juárez, E.; Samper, D.; Antoniello, R.

2007-05-01

Internet Protocol Set-Top Boxes (IP STBs) based on single-processor architectures have been recently introduced in the market. In this paper, the implementation of an MPEG-4 SP/ASP video decoder for a multi-format IP STB based on a TMS320DM641 DSP is presented. An initial decoder for PC platform was fully tested and ported to the DSP. Using this code an optimization process was started achieving a 90% speedup. This process allows real-time MPEG-4 SP/ASP decoding. The MPEG-4 decoder has been integrated in an IP STB and tested in a real environment using DVD movies and TV channels with excellent results.

HEVC real-time decoding

NASA Astrophysics Data System (ADS)

Bross, Benjamin; Alvarez-Mesa, Mauricio; George, Valeri; Chi, Chi Ching; Mayer, Tobias; Juurlink, Ben; Schierl, Thomas

2013-09-01

The new High Efficiency Video Coding Standard (HEVC) was finalized in January 2013. Compared to its predecessor H.264 / MPEG4-AVC, this new international standard is able to reduce the bitrate by 50% for the same subjective video quality. This paper investigates decoder optimizations that are needed to achieve HEVC real-time software decoding on a mobile processor. It is shown that HEVC real-time decoding up to high definition video is feasible using instruction extensions of the processor while decoding 4K ultra high definition video in real-time requires additional parallel processing. For parallel processing, a picture-level parallel approach has been chosen because it is generic and does not require bitstreams with special indication.

Approximate maximum likelihood decoding of block codes

NASA Technical Reports Server (NTRS)

Greenberger, H. J.

1979-01-01

Approximate maximum likelihood decoding algorithms, based upon selecting a small set of candidate code words with the aid of the estimated probability of error of each received symbol, can give performance close to optimum with a reasonable amount of computation. By combining the best features of various algorithms and taking care to perform each step as efficiently as possible, a decoding scheme was developed which can decode codes which have better performance than those presently in use and yet not require an unreasonable amount of computation. The discussion of the details and tradeoffs of presently known efficient optimum and near optimum decoding algorithms leads, naturally, to the one which embodies the best features of all of them.

Spatial Navigation Impairments Among Intellectually High-Functioning Adults With Autism Spectrum Disorder: Exploring Relations With Theory of Mind, Episodic Memory, and Episodic Future Thinking

PubMed Central

2013-01-01

Research suggests that spatial navigation relies on the same neural network as episodic memory, episodic future thinking, and theory of mind (ToM). Such findings have stimulated theories (e.g., the scene construction and self-projection hypotheses) concerning possible common underlying cognitive capacities. Consistent with such theories, autism spectrum disorder (ASD) is characterized by concurrent impairments in episodic memory, episodic future thinking, and ToM. However, it is currently unclear whether spatial navigation is also impaired. Hence, ASD provides a test case for the scene construction and self-projection theories. The study of spatial navigation in ASD also provides a test of the extreme male brain theory of ASD, which predicts intact or superior navigation (purportedly a systemizing skill) performance among individuals with ASD. Thus, the aim of the current study was to establish whether spatial navigation in ASD is impaired, intact, or superior. Twenty-seven intellectually high-functioning adults with ASD and 28 sex-, age-, and IQ-matched neurotypical comparison adults completed the memory island virtual navigation task. Tests of episodic memory, episodic future thinking, and ToM were also completed. Participants with ASD showed significantly diminished performance on the memory island task, and performance was positively related to ToM and episodic memory, but not episodic future thinking. These results suggest that (contra the extreme male brain theory) individuals with ASD have impaired survey-based navigation skills—that is, difficulties generating cognitive maps of the environment—and adds weight to the idea that scene construction/self-projection are impaired in ASD. The theoretical and clinical implications of these results are discussed. PMID:24364620

Detectable signals of episodic risk effects on acute HIV transmission: Strategies for analyzing transmission systems using genetic data

PubMed Central

Alam, Shah Jamal; Zhang, Xinyu; Romero-Severson, Ethan Obie; Henry, Christopher; Zhong, Lin; Volz, Erik M.; Brenner, Bluma G.; Koopman, James S.

2013-01-01

Episodic high-risk sexual behavior is common and can have a profound effect on HIV transmission. In a model of HIV transmission among men who have sex with men (MSM), changing the frequency, duration and contact rates of high-risk episodes can take endemic prevalence from zero to 50% and more than double transmissions during acute HIV infection (AHI). Undirected test and treat could be inefficient in the presence of strong episodic risk effects. Partner services approaches that use a variety of control options will be likely to have better effects under these conditions, but the question remains: What data will reveal if a population is experiencing episodic risk effects? HIV sequence data from Montreal reveals genetic clusters whose size distribution stabilizes over time and reflects the size distribution of acute infection outbreaks (AIOs). Surveillance provides complementary behavioral data. In order to use both types of data efficiently, it is essential to examine aspects of models that affect both the episodic risk effects and the shape of transmission trees. As a demonstration, we use a deterministic compartmental model of episodic risk to explore the determinants of the fraction of transmissions during acute HIV infection (AHI) at the endemic equilibrium. We use a corresponding individual-based model to observe AIO size distributions and patterns of transmission within AIO. Episodic risk parameters determining whether AHI transmission trees had longer chains, more clustered transmissions from single individuals, or different mixes of these were explored. Encouragingly for parameter estimation, AIO size distributions reflected the frequency of transmissions from acute infection across divergent parameter sets. Our results show that episodic risk dynamics influence both the size and duration of acute infection outbreaks, thus providing a possible link between genetic cluster size distributions and episodic risk dynamics. PMID:23438430

Episodic and working memory deficits in alcoholic Korsakoff patients: the continuity theory revisited.

PubMed

Pitel, Anne Lise; Beaunieux, Hélène; Witkowski, Thomas; Vabret, François; de la Sayette, Vincent; Viader, Fausto; Desgranges, Béatrice; Eustache, Francis

2008-07-01

The exact nature of episodic and working memory impairments in alcoholic Korsakoff patients (KS) remains unclear, as does the specificity of these neuropsychological deficits compared with those of non-Korsakoff alcoholics (AL). The goals of the present study were therefore to (1) specify the nature of episodic and working memory impairments in KS, (2) determine the specificity of the KS neuropsychological profile compared with the AL profile, and (3) observe the distribution of individual performances within the 2 patient groups. We investigated episodic memory (encoding and retrieval abilities, contextual memory and state of consciousness associated with memories), the slave systems of working memory (phonological loop, visuospatial sketchpad and episodic buffer) and executive functions (inhibition, flexibility, updating and integration abilities) in 14 strictly selected KS, 40 AL and 55 control subjects (CS). Compared with CS, KS displayed impairments of episodic memory encoding and retrieval, contextual memory, recollection, the slave systems of working memory and executive functions. Although episodic memory was more severely impaired in KS than in AL, the single specificity of the KS profile was a disproportionately large encoding deficit. Apart from organizational and updating abilities, the slave systems of working memory and inhibition, flexibility and integration abilities were impaired to the same extent in both alcoholic groups. However, some KS were unable to complete the most difficult executive tasks. There was only a partial overlap of individual performances by KS and AL for episodic memory and a total mixture of the 2 groups for working memory. Korsakoff's syndrome encompasses impairments of the different episodic and working memory components. AL and KS displayed similar profiles of episodic and working memory deficits, in accordance with neuroimaging investigations showing similar patterns of brain damage in both alcoholic groups.

Memory of occasional events in rats: individual episodic memory profiles, flexibility, and neural substrate.

PubMed

Veyrac, Alexandra; Allerborn, Marina; Gros, Alexandra; Michon, Frederic; Raguet, Louise; Kenney, Jana; Godinot, Florette; Thevenet, Marc; Garcia, Samuel; Messaoudi, Belkacem; Laroche, Serge; Ravel, Nadine

2015-05-13

In search for the mechanisms underlying complex forms of human memory, such as episodic recollection, a primary challenge is to develop adequate animal models amenable to neurobiological investigation. Here, we proposed a novel framework and paradigm that provides means to quantitatively evaluate the ability of rats to form and recollect a combined knowledge of what happened, where it happened, and when or in which context it happened (referred to as episodic-like memory) after a few specific episodes in situations as close as possible to a paradigm we recently developed to study episodic memory in humans. In this task, rats have to remember two odor-drink associations (what happened) encountered in distinct locations (where it happened) within two different multisensory enriched environments (in which context/occasion it happened), each characterized by a particular combination of odors and places. By analyzing licking behavior on each drinking port, we characterized quantitatively individual recollection profiles and showed that rats are able to incidentally form and recollect an accurate, long-term integrated episodic-like memory that can last ≥ 24 d after limited exposure to the episodes. Placing rats in a contextually challenging recollection situation at recall reveals the ability for flexible use of episodic memory as described in humans. We further report that reversible inactivation of the dorsal hippocampus during recall disrupts the animal's capacity to recollect the complete episodic memory. Cellular imaging of c-Fos and Zif268 brain activation reveals that episodic memory recollection recruits a specific, distributed network of hippocampal-prefrontal cortex structures that correlates with the accuracy of the integrated recollection performance. Copyright © 2015 the authors 0270-6474/15/337575-12$15.00/0.

Miniaturization of flight deflection measurement system

NASA Technical Reports Server (NTRS)

Fodale, Robert (Inventor); Hampton, Herbert R. (Inventor)

1990-01-01

A flight deflection measurement system is disclosed including a hybrid microchip of a receiver/decoder. The hybrid microchip decoder is mounted piggy back on the miniaturized receiver and forms an integral unit therewith. The flight deflection measurement system employing the miniaturized receiver/decoder can be used in a wind tunnel. In particular, the miniaturized receiver/decoder can be employed in a spin measurement system due to its small size and can retain already established control surface actuation functions.

Fast and Flexible Successive-Cancellation List Decoders for Polar Codes

NASA Astrophysics Data System (ADS)

Hashemi, Seyyed Ali; Condo, Carlo; Gross, Warren J.

2017-11-01

Polar codes have gained significant amount of attention during the past few years and have been selected as a coding scheme for the next generation of mobile broadband standard. Among decoding schemes, successive-cancellation list (SCL) decoding provides a reasonable trade-off between the error-correction performance and hardware implementation complexity when used to decode polar codes, at the cost of limited throughput. The simplified SCL (SSCL) and its extension SSCL-SPC increase the speed of decoding by removing redundant calculations when encountering particular information and frozen bit patterns (rate one and single parity check codes), while keeping the error-correction performance unaltered. In this paper, we improve SSCL and SSCL-SPC by proving that the list size imposes a specific number of bit estimations required to decode rate one and single parity check codes. Thus, the number of estimations can be limited while guaranteeing exactly the same error-correction performance as if all bits of the code were estimated. We call the new decoding algorithms Fast-SSCL and Fast-SSCL-SPC. Moreover, we show that the number of bit estimations in a practical application can be tuned to achieve desirable speed, while keeping the error-correction performance almost unchanged. Hardware architectures implementing both algorithms are then described and implemented: it is shown that our design can achieve 1.86 Gb/s throughput, higher than the best state-of-the-art decoders.

Plasma steroid profiles in nesting loggerhead turtles (Caretta caretta) in Queensland, Australia: relationship to nesting episode and season.

PubMed

Whittier, J M; Corrie, F; Limpus, C

1997-04-01

Plasma levels of four hormones-progesterone (P), testosterone (T), estradiol 17-beta (E2), and corticosterone (B)-were measured in samples taken from nesting female loggerhead turtles (Caretta caretta) by using specific radioimmunoassays. Samples were taken in an early, middle, or late period during the summer nesting season from females at first, second, third, or > fourth nesting episodes, defined as successive within-season nesting events, at Mon Repos Beach, Queensland, Australia. Data on individual patterns of nesting, collected over the past 20 years by the Queensland Turtle Research Project, and the seasonal nesting data, were analyzed with respect to influences on hormonal profiles. Circulating levels of E2 were mostly undetectable, suggesting either that this estrogen is not produced at this time of nesting, or that, perhaps, another estrogen may be present that is not detected by the specific radioimmunoassay. P, T, and B profiles in the nesting females were associated with the individual turtles' progression through successive nesting episodes, with a marked decline in all three hormones by the last (> 4) nesting episode of the season. Nesting episode accounted for significant changes that were related to season, in that nesting episode and season were significantly correlated. These patterns were observed in the population, when singly sampled at each time period or nesting episode, and in individual females sampled repeatedly over time. Moreover, T and B were highly and significantly correlated in females at all nesting episodes and time periods, and in the singly and repeatedly sampled females. The magnitude of change in T and B over time was also highly and significantly correlated in repeatedly sampled females. Together these results suggest the hypothesis that T and B interact over the period of successive nesting and may be involved in reproductive functions such as the mobilization of reserves for egg production in C. caretta.

Overview of Decoding across the Disciplines

ERIC Educational Resources Information Center

Boman, Jennifer; Currie, Genevieve; MacDonald, Ron; Miller-Young, Janice; Yeo, Michelle; Zettel, Stephanie

2017-01-01

In this chapter we describe the Decoding the Disciplines Faculty Learning Community at Mount Royal University and how Decoding has been used in new and multidisciplinary ways in the various teaching, curriculum, and research projects that are presented in detail in subsequent chapters.

Maximum likelihood decoding analysis of accumulate-repeat-accumulate codes

NASA Technical Reports Server (NTRS)

Abbasfar, A.; Divsalar, D.; Yao, K.

2004-01-01

In this paper, the performance of the repeat-accumulate codes with (ML) decoding are analyzed and compared to random codes by very tight bounds. Some simple codes are shown that perform very close to Shannon limit with maximum likelihood decoding.

Improved prediction of bimanual movements by a two-staged (effector-then-trajectory) decoder with epidural ECoG in nonhuman primates

NASA Astrophysics Data System (ADS)

Choi, Hoseok; Lee, Jeyeon; Park, Jinsick; Lee, Seho; Ahn, Kyoung-ha; Kim, In Young; Lee, Kyoung-Min; Jang, Dong Pyo

2018-02-01

Objective. In arm movement BCIs (brain-computer interfaces), unimanual research has been much more extensively studied than its bimanual counterpart. However, it is well known that the bimanual brain state is different from the unimanual one. Conventional methodology used in unimanual studies does not take the brain stage into consideration, and therefore appears to be insufficient for decoding bimanual movements. In this paper, we propose the use of a two-staged (effector-then-trajectory) decoder, which combines the classification of movement conditions and uses a hand trajectory predicting algorithm for unimanual and bimanual movements, for application in real-world BCIs. Approach. Two micro-electrode patches (32 channels) were inserted over the dura mater of the left and right hemispheres of two rhesus monkeys, covering the motor related cortex for epidural electrocorticograph (ECoG). Six motion sensors (inertial measurement unit) were used to record the movement signals. The monkeys performed three types of arm movement tasks: left unimanual, right unimanual, bimanual. To decode these movements, we used a two-staged decoder, which combines the effector classifier for four states (left unimanual, right unimanual, bimanual movements, and stationary state) and movement predictor using regression. Main results. Using this approach, we successfully decoded both arm positions using the proposed decoder. The results showed that decoding performance for bimanual movements were improved compared to the conventional method, which does not consider the effector, and the decoding performance was significant and stable over a period of four months. In addition, we also demonstrated the feasibility of epidural ECoG signals, which provided an adequate level of decoding accuracy. Significance. These results provide evidence that brain signals are different depending on the movement conditions or effectors. Thus, the two-staged method could be useful if BCIs are used to generalize for both unimanual and bimanual operations in human applications and in various neuro-prosthetics fields.

Individual Finger Control of the Modular Prosthetic Limb using High-Density Electrocorticography in a Human Subject

PubMed Central

Fifer, Matthew S.; Johannes, Matthew S.; Katyal, Kapil D.; Para, Matthew P.; Armiger, Robert; Anderson, William S.; Thakor, Nitish V.; Wester, Brock A.; Crone, Nathan E.

2016-01-01

Objective We used native sensorimotor representations of fingers in a brain-machine interface to achieve immediate online control of individual prosthetic fingers. Approach Using high gamma responses recorded with a high-density ECoG array, we rapidly mapped the functional anatomy of cued finger movements. We used these cortical maps to select ECoG electrodes for a hierarchical linear discriminant analysis classification scheme to predict: 1) if any finger was moving, and, if so, 2) which digit was moving. To account for sensory feedback, we also mapped the spatiotemporal activation elicited by vibrotactile stimulation. Finally, we used this prediction framework to provide immediate online control over individual fingers of the Johns Hopkins University Applied Physics Laboratory (JHU/APL) Modular Prosthetic Limb (MPL). Main Results The balanced classification accuracy for detection of movements during the online control session was 92% (chance: 50%). At the onset of movement, finger classification was 76% (chance: 20%), and 88% (chance: 25%) if the pinky and ring finger movements were coupled. Balanced accuracy of fully flexing the cued finger was 64%, and 77% had we combined pinky and ring commands. Offline decoding yielded a peak finger decoding accuracy of 96.5% (chance: 20%) when using an optimized selection of electrodes. Offline analysis demonstrated significant finger-specific activations throughout sensorimotor cortex. Activations either prior to movement onset or during sensory feedback led to discriminable finger control. Significance Our results demonstrate the ability of ECoG-based BMIs to leverage the native functional anatomy of sensorimotor cortical populations to immediately control individual finger movements in real time. PMID:26863276

Individual finger control of a modular prosthetic limb using high-density electrocorticography in a human subject

NASA Astrophysics Data System (ADS)

Hotson, Guy; McMullen, David P.; Fifer, Matthew S.; Johannes, Matthew S.; Katyal, Kapil D.; Para, Matthew P.; Armiger, Robert; Anderson, William S.; Thakor, Nitish V.; Wester, Brock A.; Crone, Nathan E.

2016-04-01

Objective. We used native sensorimotor representations of fingers in a brain-machine interface (BMI) to achieve immediate online control of individual prosthetic fingers. Approach. Using high gamma responses recorded with a high-density electrocorticography (ECoG) array, we rapidly mapped the functional anatomy of cued finger movements. We used these cortical maps to select ECoG electrodes for a hierarchical linear discriminant analysis classification scheme to predict: (1) if any finger was moving, and, if so, (2) which digit was moving. To account for sensory feedback, we also mapped the spatiotemporal activation elicited by vibrotactile stimulation. Finally, we used this prediction framework to provide immediate online control over individual fingers of the Johns Hopkins University Applied Physics Laboratory modular prosthetic limb. Main results. The balanced classification accuracy for detection of movements during the online control session was 92% (chance: 50%). At the onset of movement, finger classification was 76% (chance: 20%), and 88% (chance: 25%) if the pinky and ring finger movements were coupled. Balanced accuracy of fully flexing the cued finger was 64%, and 77% had we combined pinky and ring commands. Offline decoding yielded a peak finger decoding accuracy of 96.5% (chance: 20%) when using an optimized selection of electrodes. Offline analysis demonstrated significant finger-specific activations throughout sensorimotor cortex. Activations either prior to movement onset or during sensory feedback led to discriminable finger control. Significance. Our results demonstrate the ability of ECoG-based BMIs to leverage the native functional anatomy of sensorimotor cortical populations to immediately control individual finger movements in real time.

Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities

NASA Astrophysics Data System (ADS)

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.

Influence of incident angle on the decoding in laser polarization encoding guidance

NASA Astrophysics Data System (ADS)

Zhou, Muchun; Chen, Yanru; Zhao, Qi; Xin, Yu; Wen, Hongyuan

2009-07-01

Dynamic detection of polarization states is very important for laser polarization coding guidance systems. In this paper, a set of dynamic polarization decoding and detection system used in laser polarization coding guidance was designed. Detection process of the normal incident polarized light is analyzed with Jones Matrix; the system can effectively detect changes in polarization. Influence of non-normal incident light on performance of polarization decoding and detection system is studied; analysis showed that changes in incident angle will have a negative impact on measure results, the non-normal incident influence is mainly caused by second-order birefringence and polarization sensitivity effect generated in the phase delay and beam splitter prism. Combined with Fresnel formula, decoding errors of linearly polarized light, elliptically polarized light and circularly polarized light with different incident angles into the detector are calculated respectively, the results show that the decoding errors increase with increase of incident angle. Decoding errors have relations with geometry parameters, material refractive index of wave plate, polarization beam splitting prism. Decoding error can be reduced by using thin low-order wave-plate. Simulation of detection of polarized light with different incident angle confirmed the corresponding conclusions.

Online decoding of object-based attention using real-time fMRI.

PubMed

Niazi, Adnan M; van den Broek, Philip L C; Klanke, Stefan; Barth, Markus; Poel, Mannes; Desain, Peter; van Gerven, Marcel A J

2014-01-01

Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Extracting duration information in a picture category decoding task using hidden Markov Models

NASA Astrophysics Data System (ADS)

Pfeiffer, Tim; Heinze, Nicolai; Frysch, Robert; Deouell, Leon Y.; Schoenfeld, Mircea A.; Knight, Robert T.; Rose, Georg

2016-04-01

Objective. Adapting classifiers for the purpose of brain signal decoding is a major challenge in brain-computer-interface (BCI) research. In a previous study we showed in principle that hidden Markov models (HMM) are a suitable alternative to the well-studied static classifiers. However, since we investigated a rather straightforward task, advantages from modeling of the signal could not be assessed. Approach. Here, we investigate a more complex data set in order to find out to what extent HMMs, as a dynamic classifier, can provide useful additional information. We show for a visual decoding problem that besides category information, HMMs can simultaneously decode picture duration without an additional training required. This decoding is based on a strong correlation that we found between picture duration and the behavior of the Viterbi paths. Main results. Decoding accuracies of up to 80% could be obtained for category and duration decoding with a single classifier trained on category information only. Significance. The extraction of multiple types of information using a single classifier enables the processing of more complex problems, while preserving good training results even on small databases. Therefore, it provides a convenient framework for online real-life BCI utilizations.

Building Bridges from the Decoding Interview to Teaching Practice

ERIC Educational Resources Information Center

Pettit, Jennifer; Rathburn, Melanie; Calvert, Victoria; Lexier, Roberta; Underwood, Margot; Gleeson, Judy; Dean, Yasmin

2017-01-01

This chapter describes a multidisciplinary faculty self-study about reciprocity in service-learning. The study began with each coauthor participating in a Decoding interview. We describe how Decoding combined with collaborative self-study had a positive impact on our teaching practice.

An extended Reed Solomon decoder design

NASA Technical Reports Server (NTRS)

Chen, J.; Owsley, P.; Purviance, J.

1991-01-01

It has previously been shown that the Reed-Solomon (RS) codes can correct errors beyond the Singleton and Rieger Bounds with an arbitrarily small probability of a miscorrect. That is, an (n,k) RS code can correct more than (n-k)/2 errors. An implementation of such an RS decoder is presented in this paper. An existing RS decoder, the AHA4010, is utilized in this work. This decoder is especially useful for errors which are patterned with a long burst plus some random errors.

A high speed sequential decoder

NASA Technical Reports Server (NTRS)

Lum, H., Jr.

1972-01-01

The performance and theory of operation for the High Speed Hard Decision Sequential Decoder are delineated. The decoder is a forward error correction system which is capable of accepting data from binary-phase-shift-keyed and quadriphase-shift-keyed modems at input data rates up to 30 megabits per second. Test results show that the decoder is capable of maintaining a composite error rate of 0.00001 at an input E sub b/N sub o of 5.6 db. This performance has been obtained with minimum circuit complexity.

Neural Decoder for Topological Codes

NASA Astrophysics Data System (ADS)

Torlai, Giacomo; Melko, Roger G.

2017-07-01

We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning. We provide a general prescription for the training of the network and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization. We demonstrate the neural decoder numerically on the well-known two-dimensional toric code with phase-flip errors.

Within-Category Decoding of Information in Different Attentional States in Short-Term Memory.

PubMed

LaRocque, Joshua J; Riggall, Adam C; Emrich, Stephen M; Postle, Bradley R

2017-10-01

A long-standing assumption of cognitive neuroscience has been that working memory (WM) is accomplished by sustained, elevated neural activity. More recently, theories of WM have expanded this view by describing different attentional states in WM with differing activation levels. Several studies have used multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data to study neural activity corresponding to these WM states. Intriguingly, no evidence was found for active neural representations for information held in WM outside the focus of attention ("unattended memory items," UMIs), suggesting that only attended memory items (AMIs) are accompanied by an active trace. However, these results depended on category-level decoding, which lacks sensitivity to neural representations of individual items. Therefore, we employed a WM task in which subjects remembered the directions of motion of two dot arrays, with a retrocue indicating which was relevant for an imminent memory probe (the AMI). This design allowed MVPA decoding of delay-period fMRI signal at the stimulus-item level, affording a more sensitive test of the neural representation of UMIs. Whereas evidence for the AMI was reliably high, evidence for the UMI dropped to baseline, consistent with the notion that different WM attentional states may have qualitatively different mechanisms of retention. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Applying a Multiple Group Causal Indicator Modeling Framework to the Reading Comprehension Skills of Third, Seventh, and Tenth Grade Students

PubMed Central

Tighe, Elizabeth L.; Wagner, Richard K.; Schatschneider, Christopher

2015-01-01

This study demonstrates the utility of applying a causal indicator modeling framework to investigate important predictors of reading comprehension in third, seventh, and tenth grade students. The results indicated that a 4-factor multiple indicator multiple indicator cause (MIMIC) model of reading comprehension provided adequate fit at each grade level. This model included latent predictor constructs of decoding, verbal reasoning, nonverbal reasoning, and working memory and accounted for a large portion of the reading comprehension variance (73% to 87%) across grade levels. Verbal reasoning contributed the most unique variance to reading comprehension at all grade levels. In addition, we fit a multiple group 4-factor MIMIC model to investigate the relative stability (or variability) of the predictor contributions to reading comprehension across development (i.e., grade levels). The results revealed that the contributions of verbal reasoning, nonverbal reasoning, and working memory to reading comprehension were stable across the three grade levels. Decoding was the only predictor that could not be constrained to be equal across grade levels. The contribution of decoding skills to reading comprehension was higher in third grade and then remained relatively stable between seventh and tenth grade. These findings illustrate the feasibility of using MIMIC models to explain individual differences in reading comprehension across the development of reading skills. PMID:25821346

Decoding the direction of imagined visual motion using 7 T ultra-high field fMRI

PubMed Central

Emmerling, Thomas C.; Zimmermann, Jan; Sorger, Bettina; Frost, Martin A.; Goebel, Rainer

2016-01-01

There is a long-standing debate about the neurocognitive implementation of mental imagery. One form of mental imagery is the imagery of visual motion, which is of interest due to its naturalistic and dynamic character. However, so far only the mere occurrence rather than the specific content of motion imagery was shown to be detectable. In the current study, the application of multi-voxel pattern analysis to high-resolution functional data of 12 subjects acquired with ultra-high field 7 T functional magnetic resonance imaging allowed us to show that imagery of visual motion can indeed activate the earliest levels of the visual hierarchy, but the extent thereof varies highly between subjects. Our approach enabled classification not only of complex imagery, but also of its actual contents, in that the direction of imagined motion out of four options was successfully identified in two thirds of the subjects and with accuracies of up to 91.3% in individual subjects. A searchlight analysis confirmed the local origin of decodable information in striate and extra-striate cortex. These high-accuracy findings not only shed new light on a central question in vision science on the constituents of mental imagery, but also show for the first time that the specific sub-categorical content of visual motion imagery is reliably decodable from brain imaging data on a single-subject level. PMID:26481673

A Reduction in Delay Discounting by Using Episodic Future Imagination and the Association with Episodic Memory Capacity

PubMed Central

Hu, Xiaochen; Kleinschmidt, Helena; Martin, Jason A.; Han, Ying; Thelen, Manuela; Meiberth, Dix; Jessen, Frank; Weber, Bernd

2017-01-01

Delay discounting (DD) refers to the phenomenon that individuals discount future consequences. Previous studies showed that future imagination reduces DD, which was mediated by functional connectivity between medial prefrontal valuation areas and a key region for episodic memory (hippocampus). Future imagination involves an initial period of construction and a later period of elaboration, with the more elaborative latter period recruiting more cortical regions. This study examined whether elaborative future imagination modulated DD, and if so, what are the underlying neural substrates. It was assumed that cortical areas contribute to the modulation effect during the later period of imagination. Since future imagination is supported by episodic memory capacity, we additionally hypothesize that the neural network underlying the modulation effect is related to individual episodic memory capacity. Twenty-two subjects received an extensive interview on personal future events, followed by an fMRI DD experiment with and without the need to perform elaborative future imagination simultaneously. Subjects' episodic memory capacity was also assessed. Behavioral results replicate previous findings of a reduced discount rate in the DD plus imagination condition compared to the DD only condition. The behavioral effect positively correlated with: (i) subjective value signal changes in midline brain structures during the initial imagination period; and (ii) signal changes in left prefrontoparietal areas during the later imagination period. Generalized psychophysiological interaction (gPPI) analyses reveal positive correlations between the behavioral effect and functional connectivity among the following areas: right anterior cingulate cortex (ACC) and left hippocampus; left inferior parietal cortex (IPC) and left hippocampus; and left IPC and bilateral occipital cortices. These changes in functional connectivity are also associated with episodic memory capacity. A hierarchical multiple regression indicates that the model with both the valuation related signal changes in the right ACC and the imagination related signal changes in the left IPC best predicts the reduction in DD. This study illustrates interactions between the left hippocampus and multiple cortical regions underlying the modulation effect of elaborative episodic future imagination, demonstrating, for the first time, empirical support for a relation to individual episodic memory capacity. PMID:28105009

A Reduction in Delay Discounting by Using Episodic Future Imagination and the Association with Episodic Memory Capacity.

PubMed

Hu, Xiaochen; Kleinschmidt, Helena; Martin, Jason A; Han, Ying; Thelen, Manuela; Meiberth, Dix; Jessen, Frank; Weber, Bernd

2016-01-01

Delay discounting (DD) refers to the phenomenon that individuals discount future consequences. Previous studies showed that future imagination reduces DD, which was mediated by functional connectivity between medial prefrontal valuation areas and a key region for episodic memory (hippocampus). Future imagination involves an initial period of construction and a later period of elaboration, with the more elaborative latter period recruiting more cortical regions. This study examined whether elaborative future imagination modulated DD, and if so, what are the underlying neural substrates. It was assumed that cortical areas contribute to the modulation effect during the later period of imagination. Since future imagination is supported by episodic memory capacity, we additionally hypothesize that the neural network underlying the modulation effect is related to individual episodic memory capacity. Twenty-two subjects received an extensive interview on personal future events, followed by an fMRI DD experiment with and without the need to perform elaborative future imagination simultaneously. Subjects' episodic memory capacity was also assessed. Behavioral results replicate previous findings of a reduced discount rate in the DD plus imagination condition compared to the DD only condition. The behavioral effect positively correlated with: (i) subjective value signal changes in midline brain structures during the initial imagination period; and (ii) signal changes in left prefrontoparietal areas during the later imagination period. Generalized psychophysiological interaction (gPPI) analyses reveal positive correlations between the behavioral effect and functional connectivity among the following areas: right anterior cingulate cortex (ACC) and left hippocampus; left inferior parietal cortex (IPC) and left hippocampus; and left IPC and bilateral occipital cortices. These changes in functional connectivity are also associated with episodic memory capacity. A hierarchical multiple regression indicates that the model with both the valuation related signal changes in the right ACC and the imagination related signal changes in the left IPC best predicts the reduction in DD. This study illustrates interactions between the left hippocampus and multiple cortical regions underlying the modulation effect of elaborative episodic future imagination, demonstrating, for the first time, empirical support for a relation to individual episodic memory capacity.

Altered prefrontal brain activity in persons at risk for Alzheimer's disease: an fMRI study.

PubMed

Elgh, Eva; Larsson, Anne; Eriksson, Sture; Nyberg, Lars

2003-06-01

Early diagnosis of Alzheimer's disease (AD) is critical for adequate treatment and care. Recently it has been shown that functional magnetic resonance imaging (fMRI) can be important in preclinical detection of AD. The purpose of this study was to examine possible differences in memory-related brain activation between persons with high versus low risk for AD. This was achieved by combining a validated neurocognitive screening battery (the 7-minutes test) with memory assessment and fMRI. One hundred two healthy community-living persons with subjective memory complaints were recruited through advertisement and tested with the 7-minutes test. Based on their test performance they were classified as having either high (n = 8) or low risk (n = 94) for AD. Six high-risk individuals and six age-, sex-, and education-matched low-risk individuals were investigated with fMRI while engaged in episodic memory tasks. The high-risk individuals performed worse than low-risk individuals on tests of episodic memory. Patterns of brain activity during episodic encoding and retrieval showed significant group differences (p < .05 corrected). During both encoding and retrieval, the low-risk persons showed increased activity relative to a baseline condition in prefrontal brain regions that previously have been implicated in episodic memory. By contrast, the high-risk persons did not significantly activate any prefrontal regions, but instead showed increased activity in visual occipito-temporal regions. Patterns of prefrontal brain activity related to episodic memory differ between persons with high versus low risk for AD, and lowered prefrontal activity may predict subsequent disease.

Decoding Face Information in Time, Frequency and Space from Direct Intracranial Recordings of the Human Brain

PubMed Central

Oya, Hiroyuki; Howard, Matthew A.; Adolphs, Ralph

2008-01-01

Faces are processed by a neural system with distributed anatomical components, but the roles of these components remain unclear. A dominant theory of face perception postulates independent representations of invariant aspects of faces (e.g., identity) in ventral temporal cortex including the fusiform gyrus, and changeable aspects of faces (e.g., emotion) in lateral temporal cortex including the superior temporal sulcus. Here we recorded neuronal activity directly from the cortical surface in 9 neurosurgical subjects undergoing epilepsy monitoring while they viewed static and dynamic facial expressions. Applying novel decoding analyses to the power spectrogram of electrocorticograms (ECoG) from over 100 contacts in ventral and lateral temporal cortex, we found better representation of both invariant and changeable aspects of faces in ventral than lateral temporal cortex. Critical information for discriminating faces from geometric patterns was carried by power modulations between 50 to 150 Hz. For both static and dynamic face stimuli, we obtained a higher decoding performance in ventral than lateral temporal cortex. For discriminating fearful from happy expressions, critical information was carried by power modulation between 60–150 Hz and below 30 Hz, and again better decoded in ventral than lateral temporal cortex. Task-relevant attention improved decoding accuracy more than10% across a wide frequency range in ventral but not at all in lateral temporal cortex. Spatial searchlight decoding showed that decoding performance was highest around the middle fusiform gyrus. Finally, we found that the right hemisphere, in general, showed superior decoding to the left hemisphere. Taken together, our results challenge the dominant model for independent face representation of invariant and changeable aspects: information about both face attributes was better decoded from a single region in the middle fusiform gyrus. PMID:19065268

Older adults' decoding of emotions: age-related differences in interpreting dynamic emotional displays and the well-preserved ability to recognize happiness.

PubMed

Moraitou, Despina; Papantoniou, Georgia; Gkinopoulos, Theofilos; Nigritinou, Magdalini

2013-09-01

Although the ability to recognize emotions through bodily and facial muscular movements is vital to everyday life, numerous studies have found that older adults are less adept at identifying emotions than younger adults. The message gleaned from research has been one of greater decline in abilities to recognize specific negative emotions than positive ones. At the same time, these results raise methodological issues with regard to different modalities in which emotion decoding is measured. The main aim of the present study is to identify the pattern of age differences in the ability to decode basic emotions from naturalistic visual emotional displays. The sample comprised a total of 208 adults from Greece, aged from 18 to 86 years. Participants were examined using the Emotion Evaluation Test, which is the first part of a broader audiovisual tool, The Awareness of Social Inference Test. The Emotion Evaluation Test was designed to examine a person's ability to identify six emotions and discriminate these from neutral expressions, as portrayed dynamically by professional actors. The findings indicate that decoding of basic emotions occurs along the broad affective dimension of uncertainty, and a basic step in emotion decoding involves recognizing whether information presented is emotional or not. Age was found to negatively affect the ability to decode basic negatively valenced emotions as well as pleasant surprise. Happiness decoding is the only ability that was found well-preserved with advancing age. The main conclusion drawn from the study is that the pattern in which emotion decoding from visual cues is affected by normal ageing depends on the rate of uncertainty, which either is related to decoding difficulties or is inherent to a specific emotion. © 2013 The Authors. Psychogeriatrics © 2013 Japanese Psychogeriatric Society.

Multivariate pattern analysis for MEG: A comparison of dissimilarity measures.

PubMed

Guggenmos, Matthias; Sterzer, Philipp; Cichy, Radoslaw Martin

2018-06-01

Multivariate pattern analysis (MVPA) methods such as decoding and representational similarity analysis (RSA) are growing rapidly in popularity for the analysis of magnetoencephalography (MEG) data. However, little is known about the relative performance and characteristics of the specific dissimilarity measures used to describe differences between evoked activation patterns. Here we used a multisession MEG data set to qualitatively characterize a range of dissimilarity measures and to quantitatively compare them with respect to decoding accuracy (for decoding) and between-session reliability of representational dissimilarity matrices (for RSA). We tested dissimilarity measures from a range of classifiers (Linear Discriminant Analysis - LDA, Support Vector Machine - SVM, Weighted Robust Distance - WeiRD, Gaussian Naïve Bayes - GNB) and distances (Euclidean distance, Pearson correlation). In addition, we evaluated three key processing choices: 1) preprocessing (noise normalisation, removal of the pattern mean), 2) weighting decoding accuracies by decision values, and 3) computing distances in three different partitioning schemes (non-cross-validated, cross-validated, within-class-corrected). Four main conclusions emerged from our results. First, appropriate multivariate noise normalization substantially improved decoding accuracies and the reliability of dissimilarity measures. Second, LDA, SVM and WeiRD yielded high peak decoding accuracies and nearly identical time courses. Third, while using decoding accuracies for RSA was markedly less reliable than continuous distances, this disadvantage was ameliorated by decision-value-weighting of decoding accuracies. Fourth, the cross-validated Euclidean distance provided unbiased distance estimates and highly replicable representational dissimilarity matrices. Overall, we strongly advise the use of multivariate noise normalisation as a general preprocessing step, recommend LDA, SVM and WeiRD as classifiers for decoding and highlight the cross-validated Euclidean distance as a reliable and unbiased default choice for RSA. Copyright © 2018 Elsevier Inc. All rights reserved.

A low-complexity Reed-Solomon decoder using new key equation solver

NASA Astrophysics Data System (ADS)

Xie, Jun; Yuan, Songxin; Tu, Xiaodong; Zhang, Chongfu

2006-09-01

This paper presents a low-complexity parallel Reed-Solomon (RS) (255,239) decoder architecture using a novel pipelined variable stages recursive Modified Euclidean (ME) algorithm for optical communication. The pipelined four-parallel syndrome generator is proposed. The time multiplexing and resource sharing schemes are used in the novel recursive ME algorithm to reduce the logic gate count. The new key equation solver can be shared by two decoder macro. A new Chien search cell which doesn't need initialization is proposed in the paper. The proposed decoder can be used for 2.5Gb/s data rates device. The decoder is implemented in Altera' Stratixll device. The resource utilization is reduced about 40% comparing to the conventional method.

Episodic and semantic components of autobiographical memories and imagined future events in post-traumatic stress disorder.

PubMed

Brown, Adam D; Addis, Donna Rose; Romano, Tracy A; Marmar, Charles R; Bryant, Richard A; Hirst, William; Schacter, Daniel L

2014-01-01

Individuals with post-traumatic stress disorder (PTSD) tend to retrieve autobiographical memories with less episodic specificity, referred to as overgeneralised autobiographical memory. In line with evidence that autobiographical memory overlaps with one's capacity to imagine the future, recent work has also shown that individuals with PTSD also imagine themselves in the future with less episodic specificity. To date most studies quantify episodic specificity by the presence of a distinct event. However, this method does not distinguish between the numbers of internal (episodic) and external (semantic) details, which can provide additional insights into remembering the past and imagining the future. This study employed the Autobiographical Interview (AI) coding scheme to the autobiographical memory and imagined future event narratives generated by combat veterans with and without PTSD. Responses were coded for the number of internal and external details. Compared to combat veterans without PTSD, those with PTSD generated more external than internal details when recalling past or imagining future events, and fewer internal details were associated with greater symptom severity. The potential mechanisms underlying these bidirectional deficits and clinical implications are discussed.

47 CFR 79.103 - Closed caption decoder requirements for apparatus.

Code of Federal Regulations, 2014 CFR

2014-10-01

... RADIO SERVICES ACCESSIBILITY OF VIDEO PROGRAMMING Apparatus § 79.103 Closed caption decoder requirements... video programming transmitted simultaneously with sound, if such apparatus is manufactured in the United... with built-in closed caption decoder circuitry or capability designed to display closed-captioned video...

High-speed architecture for the decoding of trellis-coded modulation

NASA Technical Reports Server (NTRS)

Osborne, William P.

1992-01-01

Since 1971, when the Viterbi Algorithm was introduced as the optimal method of decoding convolutional codes, improvements in circuit technology, especially VLSI, have steadily increased its speed and practicality. Trellis-Coded Modulation (TCM) combines convolutional coding with higher level modulation (non-binary source alphabet) to provide forward error correction and spectral efficiency. For binary codes, the current stare-of-the-art is a 64-state Viterbi decoder on a single CMOS chip, operating at a data rate of 25 Mbps. Recently, there has been an interest in increasing the speed of the Viterbi Algorithm by improving the decoder architecture, or by reducing the algorithm itself. Designs employing new architectural techniques are now in existence, however these techniques are currently applied to simpler binary codes, not to TCM. The purpose of this report is to discuss TCM architectural considerations in general, and to present the design, at the logic gate level, or a specific TCM decoder which applies these considerations to achieve high-speed decoding.

Modified Dynamic Decode-and-Forward Relaying Protocol for Type II Relay in LTE-Advanced and Beyond

PubMed Central

Nam, Sung Sik; Alouini, Mohamed-Slim; Choi, Seyeong

2016-01-01

In this paper, we propose a modified dynamic decode-and-forward (MoDDF) relaying protocol to meet the critical requirements for user equipment (UE) relays in next-generation cellular systems (e.g., LTE-Advanced and beyond). The proposed MoDDF realizes the fast jump-in relaying and the sequential decoding with an application of random codeset to encoding and re-encoding process at the source and the multiple UE relays, respectively. A subframe-by-subframe decoding based on the accumulated (or buffered) messages is employed to achieve energy, information, or mixed combining. Finally, possible early termination of decoding at the end user can lead to the higher spectral efficiency and more energy saving by reducing the frequency of redundant subframe transmission and decoding. These attractive features eliminate the need of directly exchanging control messages between multiple UE relays and the end user, which is an important prerequisite for the practical UE relay deployment. PMID:27898712

Modified Dynamic Decode-and-Forward Relaying Protocol for Type II Relay in LTE-Advanced and Beyond.

PubMed

Nam, Sung Sik; Alouini, Mohamed-Slim; Choi, Seyeong

2016-01-01

In this paper, we propose a modified dynamic decode-and-forward (MoDDF) relaying protocol to meet the critical requirements for user equipment (UE) relays in next-generation cellular systems (e.g., LTE-Advanced and beyond). The proposed MoDDF realizes the fast jump-in relaying and the sequential decoding with an application of random codeset to encoding and re-encoding process at the source and the multiple UE relays, respectively. A subframe-by-subframe decoding based on the accumulated (or buffered) messages is employed to achieve energy, information, or mixed combining. Finally, possible early termination of decoding at the end user can lead to the higher spectral efficiency and more energy saving by reducing the frequency of redundant subframe transmission and decoding. These attractive features eliminate the need of directly exchanging control messages between multiple UE relays and the end user, which is an important prerequisite for the practical UE relay deployment.

EEG-based auditory attention decoding using unprocessed binaural signals in reverberant and noisy conditions?

PubMed

Aroudi, Ali; Doclo, Simon

2017-07-01

To decode auditory attention from single-trial EEG recordings in an acoustic scenario with two competing speakers, a least-squares method has been recently proposed. This method however requires the clean speech signals of both the attended and the unattended speaker to be available as reference signals. Since in practice only the binaural signals consisting of a reverberant mixture of both speakers and background noise are available, in this paper we explore the potential of using these (unprocessed) signals as reference signals for decoding auditory attention in different acoustic conditions (anechoic, reverberant, noisy, and reverberant-noisy). In addition, we investigate whether it is possible to use these signals instead of the clean attended speech signal for filter training. The experimental results show that using the unprocessed binaural signals for filter training and for decoding auditory attention is feasible with a relatively large decoding performance, although for most acoustic conditions the decoding performance is significantly lower than when using the clean speech signals.

An Optimized Three-Level Design of Decoder Based on Nanoscale Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Seyedi, Saeid; Navimipour, Nima Jafari

2018-03-01

Quantum-dot Cellular Automata (QCA) has been potentially considered as a supersede to Complementary Metal-Oxide-Semiconductor (CMOS) because of its inherent advantages. Many QCA-based logic circuits with smaller feature size, improved operating frequency, and lower power consumption than CMOS have been offered. This technology works based on electron relations inside quantum-dots. Due to the importance of designing an optimized decoder in any digital circuit, in this paper, we design, implement and simulate a new 2-to-4 decoder based on QCA with low delay, area, and complexity. The logic functionality of the 2-to-4 decoder is verified using the QCADesigner tool. The results have shown that the proposed QCA-based decoder has high performance in terms of a number of cells, covered area, and time delay. Due to the lower clock pulse frequency, the proposed 2-to-4 decoder is helpful for building QCA-based sequential digital circuits with high performance.

Effects on incidental memory of affective tone in associated past and future episodes: influence of emotional intelligence.

PubMed

Toyota, Hiroshi

2011-02-01

The present study examined the effects of emotion elicited by episodes (past events or expected future events) and the relationship between individual differences in emotional intelligence and memory. Participants' emotional intelligence was assessed on the Japanese version of Emotional Skills and Competence Questionnaire. They rated the pleasantness of episodes they associated with targets, and then performed unexpected free recall tests. When the targets were associated with episodes that were past events, all participants recalled more of the targets associated with pleasant and unpleasant episodes than those associated with neutral episodes. However, when the targets were associated with episodes expected to occur in the future, only participants with higher emotional intelligence scores recalled more of the targets associated with pleasant and unpleasant episodes. The participants with lower emotional intelligence scores recalled the three target types with similar accuracy. These results were interpreted as showing that emotional intelligence is associated with the processing of targets associated with future episodes as retrieval cues.

An Investigation of Individual Variability in Brain Activity During Episodic Encoding and Retrieval

DTIC Science & Technology

2008-12-01

variability in mnemonic strategy use is, at least in part, related to the extensive variability observed in brain activity patterns. While a number of...1 AN INVESTIGATION OF INDIVIDUAL VARIABILITY IN BRAIN ACTIVITY DURING EPISODIC ENCODING AND RETRIEVAL C.L. Donovan*, and M.B. Miller Department of...strategy measures for predicting differences in brain activity patterns during a learning and memory task and to compare their predictive value to other

Hard decoding algorithm for optimizing thresholds under general Markovian noise

NASA Astrophysics Data System (ADS)

Chamberland, Christopher; Wallman, Joel; Beale, Stefanie; Laflamme, Raymond

2017-04-01

Quantum error correction is instrumental in protecting quantum systems from noise in quantum computing and communication settings. Pauli channels can be efficiently simulated and threshold values for Pauli error rates under a variety of error-correcting codes have been obtained. However, realistic quantum systems can undergo noise processes that differ significantly from Pauli noise. In this paper, we present an efficient hard decoding algorithm for optimizing thresholds and lowering failure rates of an error-correcting code under general completely positive and trace-preserving (i.e., Markovian) noise. We use our hard decoding algorithm to study the performance of several error-correcting codes under various non-Pauli noise models by computing threshold values and failure rates for these codes. We compare the performance of our hard decoding algorithm to decoders optimized for depolarizing noise and show improvements in thresholds and reductions in failure rates by several orders of magnitude. Our hard decoding algorithm can also be adapted to take advantage of a code's non-Pauli transversal gates to further suppress noise. For example, we show that using the transversal gates of the 5-qubit code allows arbitrary rotations around certain axes to be perfectly corrected. Furthermore, we show that Pauli twirling can increase or decrease the threshold depending upon the code properties. Lastly, we show that even if the physical noise model differs slightly from the hypothesized noise model used to determine an optimized decoder, failure rates can still be reduced by applying our hard decoding algorithm.

Elegant Grapheme-Phoneme Correspondence: A Periodic Chart and Singularity Generalization Unify Decoding

ERIC Educational Resources Information Center

Gates, Louis

2018-01-01

The accompanying article introduces highly transparent grapheme-phoneme relationships embodied within a Periodic table of decoding cells, which arguably presents the quintessential transparent decoding elements. The study then folds these cells into one highly transparent but simply stated singularity generalization--this generalization unifies…

Oppositional Decoding as an Act of Resistance.

ERIC Educational Resources Information Center

Steiner, Linda

1988-01-01

Argues that contributors to the "No Comment" feature of "Ms." magazine are engaging in oppositional decoding and speculates on why this is a satisfying group process. Also notes such decoding presents another challenge to the idea that mass media has the same effect on all audiences. (SD)

Future-directed thinking in first-episode psychosis.

PubMed

Goodby, Emmeline; MacLeod, Andrew K

2016-06-01

This study employed the Future Thinking Task (MacLeod et al., 2005, Br. J. Clin. Psychol., 44, 495) to investigate whether future-directed thinking in first-episode psychosis is significantly different from that of matched controls, and to identify its correlates in this patient group. Cross-sectional, mixed-model, case-control design. Participants were 30 patients with first-episode psychosis and 27 matched controls. The Future Thinking Task was used to assess future-directed thinking in both groups. Anxiety and depression were also measured as well as self-report measures of hopelessness, suicide ideation and a measure of negative symptoms. Individuals with psychosis were impaired in future-directed thinking in both positive and negative domains, particularly with respect to the coming year. Increased self-reported hopelessness was associated with reduced positive future thinking and increased negative future thinking. Increased positive future thinking was also associated with reduced severity of negative symptoms, whilst negative future thinking was associated with suicide ideation. Individuals with first-episode psychosis show a reduction in positive future thinking in line with that seen in other clinical groups, but this is accompanied by an unexpected reduction in negative future thinking. The findings suggest a general disengagement with the future in this group that may affect recovery and functioning. Individuals with first-episode psychosis may benefit from interventions to help them engage with their future, in particular in the mid-range, up to 1 year. The Future Thinking Task may be a helpful addition to the assessment of suicide risk in those with first-episode psychosis. Decreased positive future thinking was associated with increased severity of negative symptoms, indicating a potential new treatment angle for this resistant aspect of psychosis. The cross-sectional design of this study does not allow for conclusions about the causal relationship between psychosis and future-directed thinking. This study investigated future-directed thinking in individuals with a range of psychotic illnesses employing a trans-diagnostic approach; therefore, conclusions cannot be drawn about the nature of future-directed thinking in individual psychotic disorders. © 2015 The British Psychological Society.

Encoding of Spatial Attention by Primate Prefrontal Cortex Neuronal Ensembles

PubMed Central

Treue, Stefan

2018-01-01

Abstract Single neurons in the primate lateral prefrontal cortex (LPFC) encode information about the allocation of visual attention and the features of visual stimuli. However, how this compares to the performance of neuronal ensembles at encoding the same information is poorly understood. Here, we recorded the responses of neuronal ensembles in the LPFC of two macaque monkeys while they performed a task that required attending to one of two moving random dot patterns positioned in different hemifields and ignoring the other pattern. We found single units selective for the location of the attended stimulus as well as for its motion direction. To determine the coding of both variables in the population of recorded units, we used a linear classifier and progressively built neuronal ensembles by iteratively adding units according to their individual performance (best single units), or by iteratively adding units based on their contribution to the ensemble performance (best ensemble). For both methods, ensembles of relatively small sizes (n < 60) yielded substantially higher decoding performance relative to individual single units. However, the decoder reached similar performance using fewer neurons with the best ensemble building method compared with the best single units method. Our results indicate that neuronal ensembles within the LPFC encode more information about the attended spatial and nonspatial features of visual stimuli than individual neurons. They further suggest that efficient coding of attention can be achieved by relatively small neuronal ensembles characterized by a certain relationship between signal and noise correlation structures. PMID:29568798

Early visual responses predict conscious face perception within and between subjects during binocular rivalry

PubMed Central

Sandberg, Kristian; Bahrami, Bahador; Kanai, Ryota; Barnes, Gareth Robert; Overgaard, Morten; Rees, Geraint

2014-01-01

Previous studies indicate that conscious face perception may be related to neural activity in a large time window around 170-800ms after stimulus presentation, yet in the majority of these studies changes in conscious experience are confounded with changes in physical stimulation. Using multivariate classification on MEG data recorded when participants reported changes in conscious perception evoked by binocular rivalry between a face and a grating, we showed that only MEG signals in the 120-320ms time range, peaking at the M170 around 180ms and the P2m at around 260ms, reliably predicted conscious experience. Conscious perception could not only be decoded significantly better than chance from the sensors that showed the largest average difference, as previous studies suggest, but also from patterns of activity across groups of occipital sensors that individually were unable to predict perception better than chance. Additionally, source space analyses showed that sources in the early and late visual system predicted conscious perception more accurately than frontal and parietal sites, although conscious perception could also be decoded there. Finally, the patterns of neural activity associated with conscious face perception generalized from one participant to another around the times of maximum prediction accuracy. Our work thus demonstrates that the neural correlates of particular conscious contents (here, faces) are highly consistent in time and space within individuals and that these correlates are shared to some extent between individuals. PMID:23281780

The effects of marital status on episodic and semantic memory in healthy middle-aged and old individuals.

PubMed

Mousavi-Nasab, S-M-Hossein; Kormi-Nouri, Reza; Sundström, Anna; Nilsson, Lars-Göran

2012-02-01

The present study examined the influences of marital status on different episodic and semantic memory tasks. A total of 1882 adult men and women participated in a longitudinal project (Betula) on memory, health and aging. The participants were grouped into two age cohorts, 35-60 and 65-85, and studied over a period of 5 years. Episodic memory tasks concerned recognition and recall, whereas semantic memory tasks concerned knowledge and fluency. The results showed, after controlling for education, some diseases, chronological age and leisure activity as covariates, that there were significant differences between married and single individuals in episodic memory, but not in semantic memory. Married people showed significantly better memory performances than singles in both subsystems of episodic memory, that is, recall and recognition. Also, the rate of decline in episodic memory was significantly larger for singles and widowed than other groups over the 5-year time period in both age groups. The findings demonstrate that the positive relation found between marriage and health can be extended to the relation between marriage and cognitive performance. This effect might be explained by the role played by cognitive stimulation in memory and cognition. © 2011 The Authors. Scandinavian Journal of Psychology © 2011 The Scandinavian Psychological Associations.

47 CFR 11.33 - EAS Decoder.

Code of Federal Regulations, 2014 CFR

2014-10-01

...: (1) Inputs. Decoders must have the capability to receive at least two audio inputs from EAS... externally, at least two minutes of audio or text messages. A decoder manufactured without an internal means to record and store audio or text must be equipped with a means (such as an audio or digital jack...

47 CFR 11.33 - EAS Decoder.

Code of Federal Regulations, 2013 CFR

2013-10-01

...: (1) Inputs. Decoders must have the capability to receive at least two audio inputs from EAS... externally, at least two minutes of audio or text messages. A decoder manufactured without an internal means to record and store audio or text must be equipped with a means (such as an audio or digital jack...

47 CFR 11.33 - EAS Decoder.

Code of Federal Regulations, 2012 CFR

2012-10-01

...: (1) Inputs. Decoders must have the capability to receive at least two audio inputs from EAS... externally, at least two minutes of audio or text messages. A decoder manufactured without an internal means to record and store audio or text must be equipped with a means (such as an audio or digital jack...

Hands-On Decoding: Guidelines for Using Manipulative Letters

ERIC Educational Resources Information Center

Pullen, Paige Cullen; Lane, Holly B.

2016-01-01

Manipulative objects have long been an essential tool in the development of mathematics knowledge and skills. A growing body of evidence suggests using manipulative letters for decoding practice is an also an effective method for teaching reading, particularly in improving the phonological and decoding skills of students at risk for reading…

The Contribution of Attentional Control and Working Memory to Reading Comprehension and Decoding

ERIC Educational Resources Information Center

Arrington, C. Nikki; Kulesz, Paulina A.; Francis, David J.; Fletcher, Jack M.; Barnes, Marcia A.

2014-01-01

Little is known about how specific components of working memory, namely, attentional processes including response inhibition, sustained attention, and cognitive inhibition, are related to reading decoding and comprehension. The current study evaluated the relations of reading comprehension, decoding, working memory, and attentional control in…

Decoding and Spelling Accommodations for Postsecondary Students Demonstrating Dyslexia--It's More than Processing Speed

ERIC Educational Resources Information Center

Gregg, Noel; Hoy, Cheri; Flaherty, Donna Ann; Norris, Peggy; Coleman, Christopher; Davis, Mark; Jordan, Michael

2005-01-01

The vast majority of students with learning disabilities at the postsecondary level demonstrate reading decoding, reading fluency, and writing deficits. Identification of valid and reliable psychometric measures for documenting decoding and spelling disabilities at the postsecondary level is critical for determining appropriate accommodations. The…

Coding for reliable satellite communications

NASA Technical Reports Server (NTRS)

Lin, S.

1984-01-01

Several error control coding techniques for reliable satellite communications were investigated to find algorithms for fast decoding of Reed-Solomon codes in terms of dual basis. The decoding of the (255,223) Reed-Solomon code, which is used as the outer code in the concatenated TDRSS decoder, was of particular concern.

A /31,15/ Reed-Solomon Code for large memory systems

NASA Technical Reports Server (NTRS)

Lim, R. S.

1979-01-01

This paper describes the encoding and the decoding of a (31,15) Reed-Solomon Code for multiple-burst error correction for large memory systems. The decoding procedure consists of four steps: (1) syndrome calculation, (2) error-location polynomial calculation, (3) error-location numbers calculation, and (4) error values calculation. The principal features of the design are the use of a hardware shift register for both high-speed encoding and syndrome calculation, and the use of a commercially available (31,15) decoder for decoding Steps 2, 3 and 4.

Information encoder/decoder using chaotic systems

DOEpatents

Miller, Samuel Lee; Miller, William Michael; McWhorter, Paul Jackson

1997-01-01

The present invention discloses a chaotic system-based information encoder and decoder that operates according to a relationship defining a chaotic system. Encoder input signals modify the dynamics of the chaotic system comprising the encoder. The modifications result in chaotic, encoder output signals that contain the encoder input signals encoded within them. The encoder output signals are then capable of secure transmissions using conventional transmission techniques. A decoder receives the encoder output signals (i.e., decoder input signals) and inverts the dynamics of the encoding system to directly reconstruct the original encoder input signals.

Information encoder/decoder using chaotic systems

DOEpatents

Miller, S.L.; Miller, W.M.; McWhorter, P.J.

1997-10-21

The present invention discloses a chaotic system-based information encoder and decoder that operates according to a relationship defining a chaotic system. Encoder input signals modify the dynamics of the chaotic system comprising the encoder. The modifications result in chaotic, encoder output signals that contain the encoder input signals encoded within them. The encoder output signals are then capable of secure transmissions using conventional transmission techniques. A decoder receives the encoder output signals (i.e., decoder input signals) and inverts the dynamics of the encoding system to directly reconstruct the original encoder input signals. 32 figs.

Node synchronization schemes for the Big Viterbi Decoder

NASA Technical Reports Server (NTRS)

Cheung, K.-M.; Swanson, L.; Arnold, S.

1992-01-01

The Big Viterbi Decoder (BVD), currently under development for the DSN, includes three separate algorithms to acquire and maintain node and frame synchronization. The first measures the number of decoded bits between two consecutive renormalization operations (renorm rate), the second detects the presence of the frame marker in the decoded bit stream (bit correlation), while the third searches for an encoded version of the frame marker in the encoded input stream (symbol correlation). A detailed account of the operation is given, as well as performance comparison, of the three methods.

Error Control Coding Techniques for Space and Satellite Communications

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.; Cabral, Hermano A.; He, Jiali

1997-01-01

Bootstrap Hybrid Decoding (BHD) (Jelinek and Cocke, 1971) is a coding/decoding scheme that adds extra redundancy to a set of convolutionally encoded codewords and uses this redundancy to provide reliability information to a sequential decoder. Theoretical results indicate that bit error probability performance (BER) of BHD is close to that of Turbo-codes, without some of their drawbacks. In this report we study the use of the Multiple Stack Algorithm (MSA) (Chevillat and Costello, Jr., 1977) as the underlying sequential decoding algorithm in BHD, which makes possible an iterative version of BHD.

A comparison of VLSI architectures for time and transform domain decoding of Reed-Solomon codes

NASA Technical Reports Server (NTRS)

Hsu, I. S.; Truong, T. K.; Deutsch, L. J.; Satorius, E. H.; Reed, I. S.

1988-01-01

It is well known that the Euclidean algorithm or its equivalent, continued fractions, can be used to find the error locator polynomial needed to decode a Reed-Solomon (RS) code. It is shown that this algorithm can be used for both time and transform domain decoding by replacing its initial conditions with the Forney syndromes and the erasure locator polynomial. By this means both the errata locator polynomial and the errate evaluator polynomial can be obtained with the Euclidean algorithm. With these ideas, both time and transform domain Reed-Solomon decoders for correcting errors and erasures are simplified and compared. As a consequence, the architectures of Reed-Solomon decoders for correcting both errors and erasures can be made more modular, regular, simple, and naturally suitable for VLSI implementation.

Dynamic configuration management of a multi-standard and multi-mode reconfigurable multi-ASIP architecture for turbo decoding

NASA Astrophysics Data System (ADS)

Lapotre, Vianney; Gogniat, Guy; Baghdadi, Amer; Diguet, Jean-Philippe

2017-12-01

The multiplication of connected devices goes along with a large variety of applications and traffic types needing diverse requirements. Accompanying this connectivity evolution, the last years have seen considerable evolutions of wireless communication standards in the domain of mobile telephone networks, local/wide wireless area networks, and Digital Video Broadcasting (DVB). In this context, intensive research has been conducted to provide flexible turbo decoder targeting high throughput, multi-mode, multi-standard, and power consumption efficiency. However, flexible turbo decoder implementations have not often considered dynamic reconfiguration issues in this context that requires high speed configuration switching. Starting from this assessment, this paper proposes the first solution that allows frame-by-frame run-time configuration management of a multi-processor turbo decoder without compromising the decoding performances.

Convolutional coding at 50 Mbps for the Shuttle Ku-band return link

NASA Technical Reports Server (NTRS)

Batson, B. H.; Huth, G. K.

1976-01-01

Error correcting coding is required for 50 Mbps data link from the Shuttle Orbiter through the Tracking and Data Relay Satellite System (TDRSS) to the ground because of severe power limitations. Convolutional coding has been chosen because the decoding algorithms (sequential and Viterbi) provide significant coding gains at the required bit error probability of one in 10 to the sixth power and can be implemented at 50 Mbps with moderate hardware. While a 50 Mbps sequential decoder has been built, the highest data rate achieved for a Viterbi decoder is 10 Mbps. Thus, five multiplexed 10 Mbps Viterbi decoders must be used to provide a 50 Mbps data rate. This paper discusses the tradeoffs which were considered when selecting the multiplexed Viterbi decoder approach for this application.

A concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Kasami, T.; Fujiwara, T.; Lin, S.

1986-01-01

In this paper, a concatenated coding scheme for error control in data communications is presented and analyzed. In this scheme, the inner code is used for both error correction and detection; however, the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error (or decoding error) of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughput efficiency of the proposed error control scheme incorporated with a selective-repeat ARQ retransmission strategy is also analyzed. Three specific examples are presented. One of the examples is proposed for error control in the NASA Telecommand System.

Continuous Force Decoding from Local Field Potentials of the Primary Motor Cortex in Freely Moving Rats.

PubMed

Khorasani, Abed; Heydari Beni, Nargess; Shalchyan, Vahid; Daliri, Mohammad Reza

2016-10-21

Local field potential (LFP) signals recorded by intracortical microelectrodes implanted in primary motor cortex can be used as a high informative input for decoding of motor functions. Recent studies show that different kinematic parameters such as position and velocity can be inferred from multiple LFP signals as precisely as spiking activities, however, continuous decoding of the force magnitude from the LFP signals in freely moving animals has remained an open problem. Here, we trained three rats to press a force sensor for getting a drop of water as a reward. A 16-channel micro-wire array was implanted in the primary motor cortex of each trained rat, and obtained LFP signals were used for decoding of the continuous values recorded by the force sensor. Average coefficient of correlation and the coefficient of determination between decoded and actual force signals were r = 0.66 and R 2  = 0.42, respectively. We found that LFP signal on gamma frequency bands (30-120 Hz) had the most contribution in the trained decoding model. This study suggests the feasibility of using low number of LFP channels for the continuous force decoding in freely moving animals resembling BMI systems in real life applications.

Electrophysiological difference between mental state decoding and mental state reasoning.

PubMed

Cao, Bihua; Li, Yiyuan; Li, Fuhong; Li, Hong

2012-06-29

Previous studies have explored the neural mechanism of Theory of Mind (ToM), but the neural correlates of its two components, mental state decoding and mental state reasoning, remain unclear. In the present study, participants were presented with various photographs, showing an actor looking at 1 of 2 objects, either with a happy or an unhappy expression. They were asked to either decode the emotion of the actor (mental state decoding task), predict which object would be chosen by the actor (mental state reasoning task), or judge at which object the actor was gazing (physical task), while scalp potentials were recorded. Results showed that (1) the reasoning task elicited an earlier N2 peak than the decoding task did over the prefrontal scalp sites; and (2) during the late positive component (240-440 ms), the reasoning task elicited a more positive deflection than the other two tasks did at the prefrontal scalp sites. In addition, neither the decoding task nor the reasoning task has no left/right hemisphere difference. These findings imply that mental state reasoning differs from mental state decoding early (210 ms) after stimulus onset, and that the prefrontal lobe is the neural basis of mental state reasoning. Copyright © 2012 Elsevier B.V. All rights reserved.

Reading skills of students with speech sound disorders at three stages of literacy development.

PubMed

Skebo, Crysten M; Lewis, Barbara A; Freebairn, Lisa A; Tag, Jessica; Avrich Ciesla, Allison; Stein, Catherine M

2013-10-01

The relationship between phonological awareness, overall language, vocabulary, and nonlinguistic cognitive skills to decoding and reading comprehension was examined for students at 3 stages of literacy development (i.e., early elementary school, middle school, and high school). Students with histories of speech sound disorders (SSD) with and without language impairment (LI) were compared to students without histories of SSD or LI (typical language; TL). In a cross-sectional design, students ages 7;0 (years;months) to 17;9 completed tests that measured reading, language, and nonlinguistic cognitive skills. For the TL group, phonological awareness predicted decoding at early elementary school, and overall language predicted reading comprehension at early elementary school and both decoding and reading comprehension at middle school and high school. For the SSD-only group, vocabulary predicted both decoding and reading comprehension at early elementary school, and overall language predicted both decoding and reading comprehension at middle school and decoding at high school. For the SSD and LI group, overall language predicted decoding at all 3 literacy stages and reading comprehension at early elementary school and middle school, and vocabulary predicted reading comprehension at high school. Although similar skills contribute to reading across the age span, the relative importance of these skills changes with children's literacy stages.

Reading Skills of Students With Speech Sound Disorders at Three Stages of Literacy Development

PubMed Central

Skebo, Crysten M.; Lewis, Barbara A.; Freebairn, Lisa A.; Tag, Jessica; Ciesla, Allison Avrich; Stein, Catherine M.

2015-01-01

Purpose The relationship between phonological awareness, overall language, vocabulary, and nonlinguistic cognitive skills to decoding and reading comprehension was examined for students at 3 stages of literacy development (i.e., early elementary school, middle school, and high school). Students with histories of speech sound disorders (SSD) with and without language impairment (LI) were compared to students without histories of SSD or LI (typical language; TL). Method In a cross-sectional design, students ages 7;0 (years; months) to 17;9 completed tests that measured reading, language, and nonlinguistic cognitive skills. Results For the TL group, phonological awareness predicted decoding at early elementary school, and overall language predicted reading comprehension at early elementary school and both decoding and reading comprehension at middle school and high school. For the SSD-only group, vocabulary predicted both decoding and reading comprehension at early elementary school, and overall language predicted both decoding and reading comprehension at middle school and decoding at high school. For the SSD and LI group, overall language predicted decoding at all 3 literacy stages and reading comprehension at early elementary school and middle school, and vocabulary predicted reading comprehension at high school. Conclusion Although similar skills contribute to reading across the age span, the relative importance of these skills changes with children’s literacy stages. PMID:23833280

Optimizations of a Hardware Decoder for Deep-Space Optical Communications

NASA Technical Reports Server (NTRS)

Cheng, Michael K.; Nakashima, Michael A.; Moision, Bruce E.; Hamkins, Jon

2007-01-01

The National Aeronautics and Space Administration has developed a capacity approaching modulation and coding scheme that comprises a serial concatenation of an inner accumulate pulse-position modulation (PPM) and an outer convolutional code [or serially concatenated PPM (SCPPM)] for deep-space optical communications. Decoding of this code uses the turbo principle. However, due to the nonbinary property of SCPPM, a straightforward application of classical turbo decoding is very inefficient. Here, we present various optimizations applicable in hardware implementation of the SCPPM decoder. More specifically, we feature a Super Gamma computation to efficiently handle parallel trellis edges, a pipeline-friendly 'maxstar top-2' circuit that reduces the max-only approximation penalty, a low-latency cyclic redundancy check circuit for window-based decoders, and a high-speed algorithmic polynomial interleaver that leads to memory savings. Using the featured optimizations, we implement a 6.72 megabits-per-second (Mbps) SCPPM decoder on a single field-programmable gate array (FPGA). Compared to the current data rate of 256 kilobits per second from Mars, the SCPPM coded scheme represents a throughput increase of more than twenty-six fold. Extension to a 50-Mbps decoder on a board with multiple FPGAs follows naturally. We show through hardware simulations that the SCPPM coded system can operate within 1 dB of the Shannon capacity at nominal operating conditions.

Word Decoding Development during Phonics Instruction in Children at Risk for Dyslexia.

PubMed

Schaars, Moniek M H; Segers, Eliane; Verhoeven, Ludo

2017-05-01

In the present study, we examined the early word decoding development of 73 children at genetic risk of dyslexia and 73 matched controls. We conducted monthly curriculum-embedded word decoding measures during the first 5 months of phonics-based reading instruction followed by standardized word decoding measures halfway and by the end of first grade. In kindergarten, vocabulary, phonological awareness, lexical retrieval, and verbal and visual short-term memory were assessed. The results showed that the children at risk were less skilled in phonemic awareness in kindergarten. During the first 5 months of reading instruction, children at risk were less efficient in word decoding and the discrepancy increased over the months. In subsequent months, the discrepancy prevailed for simple words but increased for more complex words. Phonemic awareness and lexical retrieval predicted the reading development in children at risk and controls to the same extent. It is concluded that children at risk are behind their typical peers in word decoding development starting from the very beginning. Furthermore, it is concluded that the disadvantage increased during phonics instruction and that the same predictors underlie the development of word decoding in the two groups of children. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Error control techniques for satellite and space communications

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.

1986-01-01

High rate concatenated coding systems with trellis inner codes and Reed-Solomon (RS) outer codes for application in satellite communication systems are considered. Two types of inner codes are studied: high rate punctured binary convolutional codes which result in overall effective information rates between 1/2 and 1 bit per channel use; and bandwidth efficient signal space trellis codes which can achieve overall effective information rates greater than 1 bit per channel use. Channel capacity calculations with and without side information performed for the concatenated coding system. Concatenated coding schemes are investigated. In Scheme 1, the inner code is decoded with the Viterbi algorithm and the outer RS code performs error-correction only (decoding without side information). In scheme 2, the inner code is decoded with a modified Viterbi algorithm which produces reliability information along with the decoded output. In this algorithm, path metrics are used to estimate the entire information sequence, while branch metrics are used to provide the reliability information on the decoded sequence. This information is used to erase unreliable bits in the decoded output. An errors-and-erasures RS decoder is then used for the outer code. These two schemes are proposed for use on NASA satellite channels. Results indicate that high system reliability can be achieved with little or no bandwidth expansion.

Sleep loss as a trigger of mood episodes in bipolar disorder: individual differences based on diagnostic subtype and gender.

PubMed

Lewis, Katie Swaden; Gordon-Smith, Katherine; Forty, Liz; Di Florio, Arianna; Craddock, Nick; Jones, Lisa; Jones, Ian

2017-09-01

Background Sleep loss may trigger mood episodes in people with bipolar disorder but individual differences could influence vulnerability to this trigger. Aims To determine whether bipolar subtype (bipolar disorder type I (BP-I) or II (BD-II)) and gender were associated with vulnerability to the sleep loss trigger. Method During a semi-structured interview, 3140 individuals (68% women) with bipolar disorder (66% BD-I) reported whether sleep loss had triggered episodes of high or low mood. DSM-IV diagnosis of bipolar subtype was derived from case notes and interview data. Results Sleep loss triggering episodes of high mood was associated with female gender (odds ratio (OR) = 1.43, 95% CI 1.17-1.75, P < 0.001) and BD-I subtype (OR = 2.81, 95% CI 2.26-3.50, P < 0.001). Analyses on sleep loss triggering low mood were not significant following adjustment for confounders. Conclusions Gender and bipolar subtype may increase vulnerability to high mood following sleep deprivation. This should be considered in situations where patients encounter sleep disruption, such as shift work and international travel. © The Royal College of Psychiatrists 2017.

Sleep loss as a trigger of mood episodes in bipolar disorder: individual differences based on diagnostic subtype and gender

PubMed Central

Lewis, Katie Swaden; Gordon-Smith, Katherine; Forty, Liz; Di Florio, Arianna; Craddock, Nick; Jones, Lisa; Jones, Ian

2017-01-01

Background Sleep loss may trigger mood episodes in people with bipolar disorder but individual differences could influence vulnerability to this trigger. Aims To determine whether bipolar subtype (bipolar disorder type I (BP-I) or II (BD-II)) and gender were associated with vulnerability to the sleep loss trigger. Method During a semi-structured interview, 3140 individuals (68% women) with bipolar disorder (66% BD-I) reported whether sleep loss had triggered episodes of high or low mood. DSM-IV diagnosis of bipolar subtype was derived from case notes and interview data. Results Sleep loss triggering episodes of high mood was associated with female gender (odds ratio (OR) = 1.43, 95% CI 1.17–1.75, P < 0.001) and BD-I subtype (OR = 2.81, 95% CI 2.26–3.50, P < 0.001). Analyses on sleep loss triggering low mood were not significant following adjustment for confounders. Conclusions Gender and bipolar subtype may increase vulnerability to high mood following sleep deprivation. This should be considered in situations where patients encounter sleep disruption, such as shift work and international travel. PMID:28684405

Word pair classification during imagined speech using direct brain recordings

NASA Astrophysics Data System (ADS)

Martin, Stephanie; Brunner, Peter; Iturrate, Iñaki; Millán, José Del R.; Schalk, Gerwin; Knight, Robert T.; Pasley, Brian N.

2016-05-01

People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used high gamma (70-150 Hz) time features with a support vector machine model to classify individual words from a pair of words. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the SVM kernel. Classification accuracy reached 88% in a two-class classification framework (50% chance level), and average classification accuracy across fifteen word-pairs was significant across five subjects (mean = 58% p < 0.05). We also compared classification accuracy between imagined speech, overt speech and listening. As predicted, higher classification accuracy was obtained in the listening and overt speech conditions (mean = 89% and 86%, respectively; p < 0.0001), where speech stimuli were directly presented. The results provide evidence for a neural representation for imagined words in the temporal lobe, frontal lobe and sensorimotor cortex, consistent with previous findings in speech perception and production. These data represent a proof of concept study for basic decoding of speech imagery, and delineate a number of key challenges to usage of speech imagery neural representations for clinical applications.

Word pair classification during imagined speech using direct brain recordings

PubMed Central

Martin, Stephanie; Brunner, Peter; Iturrate, Iñaki; Millán, José del R.; Schalk, Gerwin; Knight, Robert T.; Pasley, Brian N.

2016-01-01

People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used high gamma (70–150 Hz) time features with a support vector machine model to classify individual words from a pair of words. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the SVM kernel. Classification accuracy reached 88% in a two-class classification framework (50% chance level), and average classification accuracy across fifteen word-pairs was significant across five subjects (mean = 58%; p < 0.05). We also compared classification accuracy between imagined speech, overt speech and listening. As predicted, higher classification accuracy was obtained in the listening and overt speech conditions (mean = 89% and 86%, respectively; p < 0.0001), where speech stimuli were directly presented. The results provide evidence for a neural representation for imagined words in the temporal lobe, frontal lobe and sensorimotor cortex, consistent with previous findings in speech perception and production. These data represent a proof of concept study for basic decoding of speech imagery, and delineate a number of key challenges to usage of speech imagery neural representations for clinical applications. PMID:27165452

Individual Differences in Adult Reading Are Associated with Left Temporo-parietal to Dorsal Striatal Functional Connectivity

PubMed Central

Achal, Sanjay; Hoeft, Fumiko; Bray, Signe

2016-01-01

Reading skills vary widely in both children and adults, with a number of factors contributing to this variability. The most prominent factor may be related to efficiency of storage, representation, or retrieval of speech sounds. This phonological hypothesis is supported by findings of reduced activation in poor readers in left hemisphere ventro-lateral prefrontal and temporo-parietal phonological processing regions. Less well explained by phonological theories are reported hyperactivation in prefrontal, striatal, and insular regions. This study investigated functional connectivity of a core phonological processing region, the temporo-parietal junction (TPJ), in relation to reading skill in an adult community sample. We hypothesized that connectivity between TPJ and regions implicated in meta-analyses of reading disorder would correlate with individual differences in reading. Forty-four adults aged 30–54, ranging in reading ability, underwent resting fMRI scans. Data-driven connectivity clustering was used to identify TPJ subregions for seed-based connectivity analyses. Correlations were assessed between TPJ connectivity and timed-pseudoword reading (decoding) ability. We found a significant correlation wherein greater left supramarginal gyrus to anterior caudate connectivity was associated with weaker decoding. This suggests that hyperactivation of the dorsal striatum, reported in poor readers during reading tasks, may reflect compensatory or inefficient overintegration into attention networks. PMID:26400921

Single-Cell in Situ RNA Analysis With Switchable Fluorescent Oligonucleotides.

PubMed

Xiao, Lu; Guo, Jia

2018-01-01

Comprehensive RNA analyses in individual cells in their native spatial contexts promise to transform our understanding of normal physiology and disease pathogenesis. Here we report a single-cell in situ RNA analysis approach using switchable fluorescent oligonucleotides (SFO). In this method, transcripts are first hybridized by pre-decoding oligonucleotides. These oligonucleotides subsequently recruit SFO to stain their corresponding RNA targets. After fluorescence imaging, all the SFO in the whole specimen are simultaneously removed by DNA strand displacement reactions. Through continuous cycles of target staining, fluorescence imaging, and SFO removal, a large number of different transcripts can be identified by unique fluorophore sequences and visualized at the optical resolution. To demonstrate the feasibility of this approach, we show that the hybridized SFO can be efficiently stripped by strand displacement reactions within 30 min. We also demonstrate that this SFO removal process maintains the integrity of the RNA targets and the pre-decoding oligonucleotides, and keeps them hybridized. Applying this approach, we show that transcripts can be restained in at least eight hybridization cycles with high analysis accuracy, which theoretically would enable the whole transcriptome to be quantified at the single molecule sensitivity in individual cells. This in situ RNA analysis technology will have wide applications in systems biology, molecular diagnosis, and targeted therapies.

Functional brain imaging of episodic memory decline in ageing.

PubMed

Nyberg, L

2017-01-01

The episodic long-term memory system supports remembering of events. It is considered to be the most age-sensitive system, with an average onset of decline around 60 years of age. However, there is marked interindividual variability, such that some individuals show faster than average change and others show no or very little change. This variability may be related to the risk of developing dementia, with elevated risk for individuals with accelerated episodic memory decline. Brain imaging with functional magnetic resonance imaging (MRI) of blood oxygen level-dependent (BOLD) signalling or positron emission tomography (PET) has been used to reveal the brain bases of declining episodic memory in ageing. Several studies have demonstrated a link between age-related episodic memory decline and the hippocampus during active mnemonic processing, which is further supported by studies of hippocampal functional connectivity in the resting state. The hippocampus interacts with anterior and posterior neocortical regions to support episodic memory, and alterations in hippocampus-neocortex connectivity have been shown to contribute to impaired episodic memory. Multimodal MRI studies and more recently hybrid MRI/PET studies allow consideration of various factors that can influence the association between the hippocampal BOLD signal and memory performance. These include neurovascular factors, grey and white matter structural alterations, dopaminergic neurotransmission, amyloid-Β and glucose metabolism. Knowledge about the brain bases of episodic memory decline can guide interventions to strengthen memory in older adults, particularly in those with an elevated risk of developing dementia, with promising results for combinations of cognitive and physical stimulation. © 2016 The Association for the Publication of the Journal of Internal Medicine.

Robust tactile sensory responses in finger area of primate motor cortex relevant to prosthetic control

NASA Astrophysics Data System (ADS)

Schroeder, Karen E.; Irwin, Zachary T.; Bullard, Autumn J.; Thompson, David E.; Bentley, J. Nicole; Stacey, William C.; Patil, Parag G.; Chestek, Cynthia A.

2017-08-01

Objective. Challenges in improving the performance of dexterous upper-limb brain-machine interfaces (BMIs) have prompted renewed interest in quantifying the amount and type of sensory information naturally encoded in the primary motor cortex (M1). Previous single unit studies in monkeys showed M1 is responsive to tactile stimulation, as well as passive and active movement of the limbs. However, recent work in this area has focused primarily on proprioception. Here we examined instead how tactile somatosensation of the hand and fingers is represented in M1. Approach. We recorded multi- and single units and thresholded neural activity from macaque M1 while gently brushing individual finger pads at 2 Hz. We also recorded broadband neural activity from electrocorticogram (ECoG) grids placed on human motor cortex, while applying the same tactile stimulus. Main results. Units displaying significant differences in firing rates between individual fingers (p  <  0.05) represented up to 76.7% of sorted multiunits across four monkeys. After normalizing by the number of channels with significant motor finger responses, the percentage of electrodes with significant tactile responses was 74.9%  ±  24.7%. No somatotopic organization of finger preference was obvious across cortex, but many units exhibited cosine-like tuning across multiple digits. Sufficient sensory information was present in M1 to correctly decode stimulus position from multiunit activity above chance levels in all monkeys, and also from ECoG gamma power in two human subjects. Significance. These results provide some explanation for difficulties experienced by motor decoders in clinical trials of cortically controlled prosthetic hands, as well as the general problem of disentangling motor and sensory signals in primate motor cortex during dextrous tasks. Additionally, examination of unit tuning during tactile and proprioceptive inputs indicates cells are often tuned differently in different contexts, reinforcing the need for continued refinement of BMI training and decoding approaches to closed-loop BMI systems for dexterous grasping.

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance.

PubMed

Astrand, Elaine

2018-06-01

Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, [Formula: see text]. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  <  0.05). It is furthermore shown that this measure allows to predict task performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain-machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for individuals with degraded WM capacity.

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance

NASA Astrophysics Data System (ADS)

Astrand, Elaine

2018-06-01

Objective. Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Approach. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, n\\in [1,2] . Main results. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  <  0.05). It is furthermore shown that this measure allows to predict task performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. Significance. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain–machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for individuals with degraded WM capacity.

Linear methods for reducing EMG contamination in peripheral nerve motor decodes.

PubMed

Kagan, Zachary B; Wendelken, Suzanne; Page, David M; Davis, Tyler; Hutchinson, Douglas T; Clark, Gregory A; Warren, David J

2016-08-01

Signals recorded from the peripheral nervous system (PNS) with high channel count penetrating microelectrode arrays, such as the Utah Slanted Electrode Array (USEA), often have electromyographic (EMG) signals contaminating the neural signal. This common-mode signal source may prevent single neural units from successfully being detected, thus hindering motor decode algorithms. Reducing this EMG contamination may lead to more accurate motor decode performance. A virtual reference (VR), created by a weighted linear combination of signals from a subset of all available channels, can be used to reduce this EMG contamination. Four methods of determining individual channel weights and six different methods of selecting subsets of channels were investigated (24 different VR types in total). The methods of determining individual channel weights were equal weighting, regression-based weighting, and two different proximity-based weightings. The subsets of channels were selected by a radius-based criteria, such that a channel was included if it was within a particular radius of inclusion from the target channel. These six radii of inclusion were 1.5, 2.9, 3.2, 5, 8.4, and 12.8 electrode-distances; the 12.8 electrode radius includes all USEA electrodes. We found that application of a VR improves the detectability of neural events via increasing the SNR, but we found no statistically meaningful difference amongst the VR types we examined. The computational complexity of implementation varies with respect to the method of determining channel weights and the number of channels in a subset, but does not correlate with VR performance. Hence, we examined the computational costs of calculating and applying the VR and based on these criteria, we recommend an equal weighting method of assigning weights with a 3.2 electrode-distance radius of inclusion. Further, we found empirically that application of the recommended VR will require less than 1 ms for 33.3 ms of data from one USEA.

Mechanisms of Memory Retrieval in Slow-Wave Sleep.

PubMed

Cairney, Scott A; Sobczak, Justyna M; Lindsay, Shane; Gaskell, M Gareth

2017-09-01

Memories are strengthened during sleep. The benefits of sleep for memory can be enhanced by re-exposing the sleeping brain to auditory cues; a technique known as targeted memory reactivation (TMR). Prior studies have not assessed the nature of the retrieval mechanisms underpinning TMR: the matching process between auditory stimuli encountered during sleep and previously encoded memories. We carried out two experiments to address this issue. In Experiment 1, participants associated words with verbal and nonverbal auditory stimuli before an overnight interval in which subsets of these stimuli were replayed in slow-wave sleep. We repeated this paradigm in Experiment 2 with the single difference that the gender of the verbal auditory stimuli was switched between learning and sleep. In Experiment 1, forgetting of cued (vs. noncued) associations was reduced by TMR with verbal and nonverbal cues to similar extents. In Experiment 2, TMR with identical nonverbal cues reduced forgetting of cued (vs. noncued) associations, replicating Experiment 1. However, TMR with nonidentical verbal cues reduced forgetting of both cued and noncued associations. These experiments suggest that the memory effects of TMR are influenced by the acoustic overlap between stimuli delivered at training and sleep. Our findings hint at the existence of two processing routes for memory retrieval during sleep. Whereas TMR with acoustically identical cues may reactivate individual associations via simple episodic matching, TMR with nonidentical verbal cues may utilize linguistic decoding mechanisms, resulting in widespread reactivation across a broad category of memories. © Sleep Research Society 2017. Published by Oxford University Press [on behalf of the Sleep Research Society].

Method and apparatus for data decoding and processing

DOEpatents

Hunter, Timothy M.; Levy, Arthur J.

1992-01-01

A system and technique is disclosed for automatically controlling the decoding and digitizaiton of an analog tape. The system includes the use of a tape data format which includes a plurality of digital codes recorded on the analog tape in a predetermined proximity to a period of recorded analog data. The codes associated with each period of analog data include digital identification codes prior to the analog data, a start of data code coincident with the analog data recording, and an end of data code subsequent to the associated period of recorded analog data. The formatted tape is decoded in a processing and digitization system which includes an analog tape player coupled to a digitizer to transmit analog information from the recorded tape over at least one channel to the digitizer. At the same time, the tape player is coupled to a decoder and interface system which detects and decodes the digital codes on the tape corresponding to each period of recorded analog data and controls tape movement and digitizer initiation in response to preprogramed modes. A host computer is also coupled to the decoder and interface system and the digitizer and programmed to initiate specific modes of data decoding through the decoder and interface system including the automatic compilation and storage of digital identification information and digitized data for the period of recorded analog data corresponding to the digital identification data, compilation and storage of selected digitized data representing periods of recorded analog data, and compilation of digital identification information related to each of the periods of recorded analog data.

A High-Performance Neural Prosthesis Incorporating Discrete State Selection With Hidden Markov Models.

PubMed

Kao, Jonathan C; Nuyujukian, Paul; Ryu, Stephen I; Shenoy, Krishna V

2017-04-01

Communication neural prostheses aim to restore efficient communication to people with motor neurological injury or disease by decoding neural activity into control signals. These control signals are both analog (e.g., the velocity of a computer mouse) and discrete (e.g., clicking an icon with a computer mouse) in nature. Effective, high-performing, and intuitive-to-use communication prostheses should be capable of decoding both analog and discrete state variables seamlessly. However, to date, the highest-performing autonomous communication prostheses rely on precise analog decoding and typically do not incorporate high-performance discrete decoding. In this report, we incorporated a hidden Markov model (HMM) into an intracortical communication prosthesis to enable accurate and fast discrete state decoding in parallel with analog decoding. In closed-loop experiments with nonhuman primates implanted with multielectrode arrays, we demonstrate that incorporating an HMM into a neural prosthesis can increase state-of-the-art achieved bitrate by 13.9% and 4.2% in two monkeys ( ). We found that the transition model of the HMM is critical to achieving this performance increase. Further, we found that using an HMM resulted in the highest achieved peak performance we have ever observed for these monkeys, achieving peak bitrates of 6.5, 5.7, and 4.7 bps in Monkeys J, R, and L, respectively. Finally, we found that this neural prosthesis was robustly controllable for the duration of entire experimental sessions. These results demonstrate that high-performance discrete decoding can be beneficially combined with analog decoding to achieve new state-of-the-art levels of performance.

Risk factors for episodic neck pain in workers: a 5-year prospective study of a general working population.

PubMed

Petit, Audrey; Bodin, Julie; Delarue, Angélique; D'Escatha, Alexis; Fouquet, Natacha; Roquelaure, Yves

2018-04-01

Development of neck pain (NP) in workers has a multifactorial etiology and depends on both individual and workplace factors. The aim of this study was to investigate risk factors for episodic NP in a large diverse sample of active workers. A prospective study based on the surveillance program implemented by the French Public Health Agency in the Loire Valley region. Between 2002 and 2005, 3710 workers were included. Between 2007 and 2010, 2332 workers responded to a follow-up questionnaire which assessed: (1) musculoskeletal symptoms (Nordic questionnaire) and (2) individual and work-related risk factors. Associations between episodic NP in 2007 (i.e., free subjects at baseline and who suffered at least 8 days during the preceding 12 months) and individual and work-related risk factors at baseline were studied using logistic regression modeling, stratified by sex. Among the 1510 workers (914 men, 596 women) still active at follow-up, 10.4% (8.4-12.4) of men and 14.6% (11.8-17.4) of women declared episodic NP. Among men, work pace dependence of guests or permanent hierarchical controls were risk factors of NP [OR = 1.8 (1.1-2.8) and OR = 2.1 (1.3-3.3), respectively]. Among women, the combination of sustained/repeated arm abduction with high physical perceived exertion was the strongest risk factor for NP [OR = 3.5 (1.7-7.2)]; age and paced work were also predictors for NP in women. NP results from complex relationships between individual and work-related variables. High physical workload, awkward postures, and poor organizational environment together with age differently predicted episodic NP according to the sex.

Diarrhoea episodes and treatment-seeking behaviour in a slum area of North Jakarta, Indonesia.

PubMed

Simanjuntak, Cyrus H; Punjabi, Narain H; Wangsasaputra, Ferry; Nurdin, Dazwir; Pulungsih, Sri Pandam; Rofiq, Ainur; Santoso, Hari; Pujarwoto, H; Sjahrurachman, Agus; Sudarmono, Pratiwi; von Seidlein, Lorenz; Acosta, Camilo; Robertson, Susan E; Ali, Mohammad; Lee, Hyejon; Park, JinKyung; Deen, Jacqueline L; Agtini, Magdarina D; Clemens, John D

2004-06-01

Visits to household during a census in an impoverished area of north Jakarta were used for exploring the four-week prevalence of diarrhoea, factors associated with episodes of diarrhoea, and the patterns of healthcare use. For 160,261 urban slum-dwellers, information was collected on the socioeconomic status of the household and on diarrhoea episodes of individual household residents in the preceding four weeks. In households with a reported case of diarrhoea, the household head was asked which form of healthcare was used first. In total, 8,074 individuals (5%)--13% of children aged less than five years and 4% of adults--had a diarrhoea episode in the preceding four weeks. The two strongest factors associated with a history of diarrhoea were a diarrhoea episode in another household member in the four weeks preceding the interview (adjusted odds ratio [OR] 11.1; 95% confidence interval [CI] 10.4-11.8) and age less than five years (adjusted OR 3.4; 95% CI 3.2-3.5). Of the 8,074 diarrhoea cases, 1,969 (25%) treated themselves, 1,822 (23%) visited a public-health centre (PHC), 1,462 (18%) visited a private practitioner or a private clinic, 1,318 (16%) presented at a hospital, 753 (9%) bought drugs from a drug vendor, and 750 (9%) used other healthcare providers, such as belian (traditional healers). Children with diarrhoea were most often brought to a PHC, a private clinic, or a hospital for treatment. Compared to children, adults with diarrhoea were more likely to treat themselves. Individuals from households in the lowest-income group were significantly more likely to attend a PHC for treatment of diarrhoea compared to individuals from households in the middle- and higher-income groups.

VLSI chip-set for data compression using the Rice algorithm

NASA Technical Reports Server (NTRS)

Venbrux, J.; Liu, N.

1990-01-01

A full custom VLSI implementation of a data compression encoder and decoder which implements the lossless Rice data compression algorithm is discussed in this paper. The encoder and decoder reside on single chips. The data rates are to be 5 and 10 Mega-samples-per-second for the decoder and encoder respectively.

Training Students to Decode Verbal and Nonverbal Cues: Effects on Confidence and Performance.

ERIC Educational Resources Information Center

Costanzo, Mark

1992-01-01

A study conducted with 105 university students investigated the effectiveness of using previous research findings as a means of teaching students how to interpret verbal and nonverbal behavior (decoding). Practice may be the critical feature for training in decoding. Research findings were successfully converted into educational techniques. (SLD)

Communication Encoding and Decoding in Children from Different Socioeconomic and Racial Groups.

ERIC Educational Resources Information Center

Quay, Lorene C.; And Others

Although lower socioeconomic status (SES) black children have been shown to be inferior to middle-SES white children in communication accuracy, whether the problem is in encoding (production), decoding (comprehension), or both is not clear. To evaluate encoding and decoding separately, tape recordings of picture descriptions were obtained from…

The Impact of Nonverbal Communication in Organizations: A Survey of Perceptions.

ERIC Educational Resources Information Center

Graham, Gerald H.; And Others

1991-01-01

Discusses a survey of 505 respondents from business organizations. Reports that self-described good decoders of nonverbal communication consider nonverbal communication more important than do other decoders. Notes that both men and women perceive women as both better decoders and encoders of nonverbal cues. Recommends paying more attention to…

Does Linguistic Comprehension Support the Decoding Skills of Struggling Readers?

ERIC Educational Resources Information Center

Blick, Michele; Nicholson, Tom; Chapman, James; Berman, Jeanette

2017-01-01

This study investigated the contribution of linguistic comprehension to the decoding skills of struggling readers. Participants were 36 children aged between eight and 12 years, all below average in decoding but differing in linguistic comprehension. The children read passages from the Neale Analysis of Reading Ability and their first 25 miscues…

Role of Gender and Linguistic Diversity in Word Decoding Development

ERIC Educational Resources Information Center

Verhoeven, Ludo; van Leeuwe, Jan

2011-01-01

The purpose of the present study was to investigate the role of gender and linguistic diversity in the growth of Dutch word decoding skills throughout elementary school for a representative sample of children living in the Netherlands. Following a longitudinal design, the children's decoding abilities for (1) regular CVC words, (2) complex…

The Relationship between Reading Comprehension, Decoding, and Fluency in Greek: A Cross-Sectional Study

ERIC Educational Resources Information Center

Padeliadu, Susana; Antoniou, Faye

2014-01-01

Experts widely consider decoding and fluency as the basis of reading comprehension, while at the same time consistently documenting problems in these areas as major characteristics of students with learning disabilities. However, scholars have developed most of the relevant research within phonologically deep languages, wherein decoding problems…

Cognitive Training and Reading Remediation

ERIC Educational Resources Information Center

Mahapatra, Shamita

2015-01-01

Reading difficulties are experienced by children either because they fail to decode the words and thus are unable to comprehend the text or simply fail to comprehend the text even if they are able to decode the words and read them out. Failure in word decoding results from a failure in phonological coding of written information, whereas, reading…

Validation of the Informal Decoding Inventory

ERIC Educational Resources Information Center

McKenna, Michael C.; Walpole, Sharon; Jang, Bong Gee

2017-01-01

This study investigated the reliability and validity of Part 1 of the Informal Decoding Inventory (IDI), a free diagnostic assessment used to plan Tier 2 intervention for first graders with decoding deficits. Part 1 addresses single-syllable words and consists of five subtests that progress in difficulty and that contain real word and pseudoword…

Applying the Decoding the Disciplines Process to Teaching Structural Mechanics: An Autoethnographic Case Study

ERIC Educational Resources Information Center

Tingerthal, John Steven

2013-01-01

Using case study methodology and autoethnographic methods, this study examines a process of curricular development known as "Decoding the Disciplines" (Decoding) by documenting the experience of its application in a construction engineering mechanics course. Motivated by the call to integrate what is known about teaching and learning…

Error Control Coding Techniques for Space and Satellite Communications

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.; Takeshita, Oscar Y.; Cabral, Hermano A.; He, Jiali; White, Gregory S.

1997-01-01

Turbo coding using iterative SOVA decoding and M-ary differentially coherent or non-coherent modulation can provide an effective coding modulation solution: (1) Energy efficient with relatively simple SOVA decoding and small packet lengths, depending on BEP required; (2) Low number of decoding iterations required; and (3) Robustness in fading with channel interleaving.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; A Recursive Maximum Likelihood Decoding

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc

1998-01-01

The Viterbi algorithm is indeed a very simple and efficient method of implementing the maximum likelihood decoding. However, if we take advantage of the structural properties in a trellis section, other efficient trellis-based decoding algorithms can be devised. Recently, an efficient trellis-based recursive maximum likelihood decoding (RMLD) algorithm for linear block codes has been proposed. This algorithm is more efficient than the conventional Viterbi algorithm in both computation and hardware requirements. Most importantly, the implementation of this algorithm does not require the construction of the entire code trellis, only some special one-section trellises of relatively small state and branch complexities are needed for constructing path (or branch) metric tables recursively. At the end, there is only one table which contains only the most likely code-word and its metric for a given received sequence r = (r(sub 1), r(sub 2),...,r(sub n)). This algorithm basically uses the divide and conquer strategy. Furthermore, it allows parallel/pipeline processing of received sequences to speed up decoding.

Multidimensional biochemical information processing of dynamical patterns

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Comparison of incoming dental school patients with and without disabilities.

PubMed

Stiefel, D J; Truelove, E L; Martin, M D; Mandel, L S

1997-01-01

A survey of incoming dental school patients compared 64 adult patients (DECOD) and 73 patients without disability (ND), regarding past dental experience, current needs, and basis for selecting the school's clinics. The responses indicated that, for DECOD patients, clinic selection was based largely on Medicaid acceptance, staff experience, and inability of other dentists to manage their disability; for ND patients, selection was based on lower fee structure. Both groups expressed high treatment need, but the rate was lower for DECOD than for ND patients. More DECOD patients reported severe dental anxiety and adverse effects of dental problems on general health. Chart records revealed that clinical findings exceeded perceived need for both DECOD and ND patients. While both groups had high periodontal disease rates (91%), DECOD patients had significantly poorer oral hygiene and less restorative need than ND patients. The findings suggest differences between persons with disabilities and other patient groups in difficulty of access to dental services in the community, reasons for entering the dental school system, and in presenting treatment need and/or treatment planning.

Word and Person Effects on Decoding Accuracy: A New Look at an Old Question

PubMed Central

Gilbert, Jennifer K.; Compton, Donald L.; Kearns, Devin M.

2011-01-01

The purpose of this study was to extend the literature on decoding by bringing together two lines of research, namely person and word factors that affect decoding, using a crossed random-effects model. The sample was comprised of 196 English-speaking grade 1 students. A researcher-developed pseudoword list was used as the primary outcome measure. Because grapheme-phoneme correspondence (GPC) knowledge was treated as person and word specific, we are able to conclude that it is neither necessary nor sufficient for a student to know all GPCs in a word before accurately decoding the word. And controlling for word-specific GPC knowledge, students with lower phonemic awareness and slower rapid naming skill have lower predicted probabilities of correct decoding than counterparts with superior skills. By assessing a person-by-word interaction, we found that students with lower phonemic awareness have more difficulty applying knowledge of complex vowel graphemes compared to complex consonant graphemes when decoding unfamiliar words. Implications of the methodology and results are discussed in light of future research. PMID:21743750

Longitudinal Stability and Predictors of Poor Oral Comprehenders and Poor Decoders

PubMed Central

Elwér, Åsa; Keenan, Janice M.; Olson, Richard K.; Byrne, Brian; Samuelsson, Stefan

2012-01-01

Two groups of 4th grade children were selected from a population sample (N= 926) to either be Poor Oral Comprehenders (poor oral comprehension but normal word decoding), or Poor Decoders (poor decoding but normal oral comprehension). By examining both groups in the same study with varied cognitive and literacy predictors, and examining them both retrospectively and prospectively, we could assess how distinctive and stable the predictors of each deficit are. Predictors were assessed retrospectively at preschool, at the end of kindergarten, 1st, and 2nd grades. Group effects were significant at all test occasions, including those for preschool vocabulary (worse in poor oral comprehenders) and rapid naming (RAN) (worse in poor decoders). Preschool RAN and Vocabulary prospectively predicted grade 4 group membership (77–79% correct classification) within the selected samples. Reselection in preschool of at-risk poor decoder and poor oral comprehender subgroups based on these variables led to significant but relatively weak prediction of subtype membership at grade 4. Implications of the predictive stability of our results for identification and intervention of these important subgroups are discussed. PMID:23528975

Multidimensional biochemical information processing of dynamical patterns.

PubMed

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Robust pattern decoding in shape-coded structured light

NASA Astrophysics Data System (ADS)

Tang, Suming; Zhang, Xu; Song, Zhan; Song, Lifang; Zeng, Hai

2017-09-01

Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.

Encoding and decoding of digital spiral imaging based on bidirectional transformation of light's spatial eigenmodes.

PubMed

Zhang, Wuhong; Chen, Lixiang

2016-06-15

Digital spiral imaging has been demonstrated as an effective optical tool to encode optical information and retrieve topographic information of an object. Here we develop a conceptually new and concise scheme for optical image encoding and decoding toward free-space digital spiral imaging. We experimentally demonstrate that the optical lattices with ℓ=±50 orbital angular momentum superpositions and a clover image with nearly 200 Laguerre-Gaussian (LG) modes can be well encoded and successfully decoded. It is found that an image encoded/decoded with a two-index LG spectrum (considering both azimuthal and radial indices, ℓ and p) possesses much higher fidelity than that with a one-index LG spectrum (only considering the ℓ index). Our work provides an alternative tool for the image encoding/decoding scheme toward free-space optical communications.

Orientation decoding depends on maps, not columns

PubMed Central

Freeman, Jeremy; Brouwer, Gijs Joost; Heeger, David J.; Merriam, Elisha P.

2011-01-01

The representation of orientation in primary visual cortex (V1) has been examined at a fine spatial scale corresponding to the columnar architecture. We present functional magnetic resonance imaging (fMRI) measurements providing evidence for a topographic map of orientation preference in human V1 at a much coarser scale, in register with the angular-position component of the retinotopic map of V1. This coarse-scale orientation map provides a parsimonious explanation for why multivariate pattern analysis methods succeed in decoding stimulus orientation from fMRI measurements, challenging the widely-held assumption that decoding results reflect sampling of spatial irregularities in the fine-scale columnar architecture. Decoding stimulus attributes and cognitive states from fMRI measurements has proven useful for a number of applications, but our results demonstrate that the interpretation cannot assume decoding reflects or exploits columnar organization. PMID:21451017

Factor-Analysis Methods for Higher-Performance Neural Prostheses

PubMed Central

Santhanam, Gopal; Yu, Byron M.; Gilja, Vikash; Ryu, Stephen I.; Afshar, Afsheen; Sahani, Maneesh; Shenoy, Krishna V.

2009-01-01

Neural prostheses aim to provide treatment options for individuals with nervous-system disease or injury. It is necessary, however, to increase the performance of such systems before they can be clinically viable for patients with motor dysfunction. One performance limitation is the presence of correlated trial-to-trial variability that can cause neural responses to wax and wane in concert as the subject is, for example, more attentive or more fatigued. If a system does not properly account for this variability, it may mistakenly interpret such variability as an entirely different intention by the subject. We report here the design and characterization of factor-analysis (FA)–based decoding algorithms that can contend with this confound. We characterize the decoders (classifiers) on experimental data where monkeys performed both a real reach task and a prosthetic cursor task while we recorded from 96 electrodes implanted in dorsal premotor cortex. The decoder attempts to infer the underlying factors that comodulate the neurons' responses and can use this information to substantially lower error rates (one of eight reach endpoint predictions) by ≲75% (e.g., ∼20% total prediction error using traditional independent Poisson models reduced to ∼5%). We also examine additional key aspects of these new algorithms: the effect of neural integration window length on performance, an extension of the algorithms to use Poisson statistics, and the effect of training set size on the decoding accuracy of test data. We found that FA-based methods are most effective for integration windows >150 ms, although still advantageous at shorter timescales, that Gaussian-based algorithms performed better than the analogous Poisson-based algorithms and that the FA algorithm is robust even with a limited amount of training data. We propose that FA-based methods are effective in modeling correlated trial-to-trial neural variability and can be used to substantially increase overall prosthetic system performance. PMID:19297518

Vacillation, indecision and hesitation in moment-by-moment decoding of monkey motor cortex

PubMed Central

Kaufman, Matthew T; Churchland, Mark M; Ryu, Stephen I; Shenoy, Krishna V

2015-01-01

When choosing actions, we can act decisively, vacillate, or suffer momentary indecision. Studying how individual decisions unfold requires moment-by-moment readouts of brain state. Here we provide such a view from dorsal premotor and primary motor cortex. Two monkeys performed a novel decision task while we recorded from many neurons simultaneously. We found that a decoder trained using ‘forced choices’ (one target viable) was highly reliable when applied to ‘free choices’. However, during free choices internal events formed three categories. Typically, neural activity was consistent with rapid, unwavering choices. Sometimes, though, we observed presumed ‘changes of mind’: the neural state initially reflected one choice before changing to reflect the final choice. Finally, we observed momentary ‘indecision’: delay forming any clear motor plan. Further, moments of neural indecision accompanied moments of behavioral indecision. Together, these results reveal the rich and diverse set of internal events long suspected to occur during free choice. DOI: http://dx.doi.org/10.7554/eLife.04677.001 PMID:25942352

Coding and decoding libraries of sequence-defined functional copolymers synthesized via photoligation

PubMed Central

Zydziak, Nicolas; Konrad, Waldemar; Feist, Florian; Afonin, Sergii; Weidner, Steffen; Barner-Kowollik, Christopher

2016-01-01

Designing artificial macromolecules with absolute sequence order represents a considerable challenge. Here we report an advanced light-induced avenue to monodisperse sequence-defined functional linear macromolecules up to decamers via a unique photochemical approach. The versatility of the synthetic strategy—combining sequential and modular concepts—enables the synthesis of perfect macromolecules varying in chemical constitution and topology. Specific functions are placed at arbitrary positions along the chain via the successive addition of monomer units and blocks, leading to a library of functional homopolymers, alternating copolymers and block copolymers. The in-depth characterization of each sequence-defined chain confirms the precision nature of the macromolecules. Decoding of the functional information contained in the molecular structure is achieved via tandem mass spectrometry without recourse to their synthetic history, showing that the sequence information can be read. We submit that the presented photochemical strategy is a viable and advanced concept for coding individual monomer units along a macromolecular chain. PMID:27901024

Coding and decoding libraries of sequence-defined functional copolymers synthesized via photoligation.

PubMed

Zydziak, Nicolas; Konrad, Waldemar; Feist, Florian; Afonin, Sergii; Weidner, Steffen; Barner-Kowollik, Christopher

2016-11-30

Designing artificial macromolecules with absolute sequence order represents a considerable challenge. Here we report an advanced light-induced avenue to monodisperse sequence-defined functional linear macromolecules up to decamers via a unique photochemical approach. The versatility of the synthetic strategy-combining sequential and modular concepts-enables the synthesis of perfect macromolecules varying in chemical constitution and topology. Specific functions are placed at arbitrary positions along the chain via the successive addition of monomer units and blocks, leading to a library of functional homopolymers, alternating copolymers and block copolymers. The in-depth characterization of each sequence-defined chain confirms the precision nature of the macromolecules. Decoding of the functional information contained in the molecular structure is achieved via tandem mass spectrometry without recourse to their synthetic history, showing that the sequence information can be read. We submit that the presented photochemical strategy is a viable and advanced concept for coding individual monomer units along a macromolecular chain.

Emotion recognition in body dysmorphic disorder: application of the Reading the Mind in the Eyes Task.

PubMed

Buhlmann, Ulrike; Winter, Anna; Kathmann, Norbert

2013-03-01

Body dysmorphic disorder (BDD) is characterized by perceived appearance-related defects, often tied to aspects of the face or head (e.g., acne). Deficits in decoding emotional expressions have been examined in several psychological disorders including BDD. Previous research indicates that BDD is associated with impaired facial emotion recognition, particularly in situations that involve the BDD sufferer him/herself. The purpose of this study was to further evaluate the ability to read other people's emotions among 31 individuals with BDD, and 31 mentally healthy controls. We applied the Reading the Mind in the Eyes task, in which participants are presented with a series of pairs of eyes, one at a time, and are asked to identify the emotion that describes the stimulus best. The groups did not differ with respect to decoding other people's emotions by looking into their eyes. Findings are discussed in light of previous research examining emotion recognition in BDD. Copyright © 2013. Published by Elsevier Ltd.

Decoder calibration with ultra small current sample set for intracortical brain-machine interface

NASA Astrophysics Data System (ADS)

Zhang, Peng; Ma, Xuan; Chen, Luyao; Zhou, Jin; Wang, Changyong; Li, Wei; He, Jiping

2018-04-01

Objective. Intracortical brain-machine interfaces (iBMIs) aim to restore efficient communication and movement ability for paralyzed patients. However, frequent recalibration is required for consistency and reliability, and every recalibration will require relatively large most current sample set. The aim in this study is to develop an effective decoder calibration method that can achieve good performance while minimizing recalibration time. Approach. Two rhesus macaques implanted with intracortical microelectrode arrays were trained separately on movement and sensory paradigm. Neural signals were recorded to decode reaching positions or grasping postures. A novel principal component analysis-based domain adaptation (PDA) method was proposed to recalibrate the decoder with only ultra small current sample set by taking advantage of large historical data, and the decoding performance was compared with other three calibration methods for evaluation. Main results. The PDA method closed the gap between historical and current data effectively, and made it possible to take advantage of large historical data for decoder recalibration in current data decoding. Using only ultra small current sample set (five trials of each category), the decoder calibrated using the PDA method could achieve much better and more robust performance in all sessions than using other three calibration methods in both monkeys. Significance. (1) By this study, transfer learning theory was brought into iBMIs decoder calibration for the first time. (2) Different from most transfer learning studies, the target data in this study were ultra small sample set and were transferred to the source data. (3) By taking advantage of historical data, the PDA method was demonstrated to be effective in reducing recalibration time for both movement paradigm and sensory paradigm, indicating a viable generalization. By reducing the demand for large current training data, this new method may facilitate the application of intracortical brain-machine interfaces in clinical practice.

Predictive Ensemble Decoding of Acoustical Features Explains Context-Dependent Receptive Fields.

PubMed

Yildiz, Izzet B; Mesgarani, Nima; Deneve, Sophie

2016-12-07

A primary goal of auditory neuroscience is to identify the sound features extracted and represented by auditory neurons. Linear encoding models, which describe neural responses as a function of the stimulus, have been primarily used for this purpose. Here, we provide theoretical arguments and experimental evidence in support of an alternative approach, based on decoding the stimulus from the neural response. We used a Bayesian normative approach to predict the responses of neurons detecting relevant auditory features, despite ambiguities and noise. We compared the model predictions to recordings from the primary auditory cortex of ferrets and found that: (1) the decoding filters of auditory neurons resemble the filters learned from the statistics of speech sounds; (2) the decoding model captures the dynamics of responses better than a linear encoding model of similar complexity; and (3) the decoding model accounts for the accuracy with which the stimulus is represented in neural activity, whereas linear encoding model performs very poorly. Most importantly, our model predicts that neuronal responses are fundamentally shaped by "explaining away," a divisive competition between alternative interpretations of the auditory scene. Neural responses in the auditory cortex are dynamic, nonlinear, and hard to predict. Traditionally, encoding models have been used to describe neural responses as a function of the stimulus. However, in addition to external stimulation, neural activity is strongly modulated by the responses of other neurons in the network. We hypothesized that auditory neurons aim to collectively decode their stimulus. In particular, a stimulus feature that is decoded (or explained away) by one neuron is not explained by another. We demonstrated that this novel Bayesian decoding model is better at capturing the dynamic responses of cortical neurons in ferrets. Whereas the linear encoding model poorly reflects selectivity of neurons, the decoding model can account for the strong nonlinearities observed in neural data. Copyright © 2016 Yildiz et al.

Hypophosphatemia is a common complication in severely disabled individuals with neurological disorders and is caused by infection, refeeding and Fanconi syndrome.

PubMed

Saito, Yoshiaki; Aoki, Yusuke; Takeshita, Eri; Saito, Takashi; Sugai, Kenji; Komaki, Hirofumi; Nakagawa, Eiji; Ishiyama, Akihiko; Takanoha, Satoko; Wada, Satoru; Sasaki, Masayuki

2014-11-01

To describe the characteristics of hypophosphatemia in severely disabled individuals with neurological disorders and to identify its causative factors. We retrospectively reviewed clinical data from 82 individuals with motor skills classified as sitting, rollover or bedridden. Age, gender and body mass index were compared in individuals with (n=19) and without (n=63) a history of hypophosphatemia (serum phosphate levels <2.0 mg/dl). The clinical course of each patient with hypophosphatemia was reviewed and the cause identified. Laboratory data during hypophosphatemia was compared with that after recovery. The age, gender and body mass index did not differ significantly between the individuals with and without hypophosphatemia. Nineteen patients experienced 25 episodes of hypophosphatemia. The causes included febrile illnesses (n=17), refeeding syndrome (n=4) and Fanconi syndrome (n=3), but was unidentifiable in one episode. Significant elevations in C-reactive protein levels and reductions in sodium levels were observed during hypophosphatemia episodes. Hypophosphatemia is a common complication in severely disabled individuals with frequent bacterial infections, refeeding following malnutrition and valproate administration for epilepsy treatment. Because severe hypophosphatemia is life threatening, serum phosphate levels should be closely monitored in this population. Copyright © 2013 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Neural network decoder for quantum error correcting codes

NASA Astrophysics Data System (ADS)

Krastanov, Stefan; Jiang, Liang

Artificial neural networks form a family of extremely powerful - albeit still poorly understood - tools used in anything from image and sound recognition through text generation to, in our case, decoding. We present a straightforward Recurrent Neural Network architecture capable of deducing the correcting procedure for a quantum error-correcting code from a set of repeated stabilizer measurements. We discuss the fault-tolerance of our scheme and the cost of training the neural network for a system of a realistic size. Such decoders are especially interesting when applied to codes, like the quantum LDPC codes, that lack known efficient decoding schemes.

New Syndrome Decoding Techniques for the (n, K) Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

This paper presents a new syndrome decoding algorithm for the (n,k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3,1)CC.

Simplified Syndrome Decoding of (n, 1) Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

A new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck is presented. The new algorithm uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). This set of Diophantine solutions is a coset of the CC space. A recursive or Viterbi-like algorithm is developed to find the minimum weight error vector cirumflex E(D) in this error coset. An example illustrating the new decoding algorithm is given for the binary nonsymmetric (2,1)CC.

An embedded controller for a 7-degree of freedom prosthetic arm.

PubMed

Tenore, Francesco; Armiger, Robert S; Vogelstein, R Jacob; Wenstrand, Douglas S; Harshbarger, Stuart D; Englehart, Kevin

2008-01-01

We present results from an embedded real-time hardware system capable of decoding surface myoelectric signals (sMES) to control a seven degree of freedom upper limb prosthesis. This is one of the first hardware implementations of sMES decoding algorithms and the most advanced controller to-date. We compare decoding results from the device to simulation results from a real-time PC-based operating system. Performance of both systems is shown to be similar, with decoding accuracy greater than 90% for the floating point software simulation and 80% for fixed point hardware and software implementations.

A concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Lin, S.

1985-01-01

A concatenated coding scheme for error contol in data communications was analyzed. The inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughout efficiency of the proposed error control scheme incorporated with a selective repeat ARQ retransmission strategy is analyzed.

Trajectories of higher- and lower-order dimensions of negative and positive affect relative to restrictive eating in anorexia nervosa.

PubMed

Haynos, Ann F; Berg, Kelly C; Cao, Li; Crosby, Ross D; Lavender, Jason M; Utzinger, Linsey M; Wonderlich, Stephen A; Engel, Scott G; Mitchell, James E; Le Grange, Daniel; Peterson, Carol B; Crow, Scott J

2017-07-01

Despite robust support for the role of affect in the maintenance of binge eating and purging, the relationship between affect and restrictive eating remains poorly understood. To investigate the relationship between restrictive eating and affect, ecological momentary assessment data from 118 women with anorexia nervosa (AN) were used to examine trajectories of higher-order dimensions of negative affect (NA) and positive affect (PA), as well as lower-order dimensions of NA (Fear, Guilt) and PA (Joviality, Self-Assurance) relative to restrictive eating. Affect trajectories were modeled before and after restrictive eating episodes and AN subtype was examined as a moderator of these trajectories. Across the sample, Guilt significantly increased before and decreased after restrictive eating episodes. Global NA, Global PA, Fear, Joviality, and Self-Assurance did not vary relative to restrictive eating episodes across the sample. However, significant subtype by trajectory interactions were detected for PA indices. Among individuals with AN restricting subtype, Global PA, Joviality, and Self-Assurance decreased prior to and Self-Assurance increased following restrictive eating episodes. In contrast, Global PA and Self-Assurance increased prior to, but did not change following, restrictive eating episodes among individuals with AN binge eating/purging subtype. Results suggest that dietary restriction may function to mitigate guilt across AN subtypes and to enhance self-assurance among individuals with AN restricting subtype. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

IDENTIFYING A SUSCEPTIBLE SUBGROUP: EFFECTS OF THE PITTSBURGH AIR POLLUTION EPISODE UPON SCHOOL CHILDREN

EPA Science Inventory

Pulmonary function test results on 224 parochial schoolchildren collected during and after the Pittsburgh air pollution episode of November 1975 were reanalyzed to determine whether a small subgroup of susceptible children could be defined. Individual regressions of three-quarter...

42 CFR § 512.110 - Access to records and retention.

Code of Federal Regulations, 2010 CFR

2017-10-01

... SERVICES (CONTINUED) HEALTH CARE INFRASTRUCTURE AND MODEL PROGRAMS EPISODE PAYMENT MODEL Episode Payment Model Participants § 512.110 Access to records and retention. EPM participants, EPM collaborators... requirements and, if applicable, the individual's or entity's compliance with CR incentive payment model...

Re-reading after mind wandering.

PubMed

Varao-Sousa, Trish L; Solman, Grayden J F; Kingstone, Alan

2017-09-01

Though much research has been conducted on the causes and processes underlying mind wandering, relatively little has addressed what happens after an episode of mind wandering. We explore this issue in the context of reading. Specifically, by examining re-reading behaviours following mind wandering episodes. Results from 2 studies reveal that after mind wandering, participants re-read nearly half the time. This re-reading occurs whether mind wandering is self-caught or probe-caught, and it typically involves retracing a line or 2 of text. Based on subjective reports, it appears that individuals re-read when they feel that clarification of the text is needed, suggesting that a key concept of the text is missed during a mind wandering episode. Future work aimed at understanding how individuals refocus their attention following mind wandering in different settings should provide additional insights into the fluctuation of attentional focus and the immediate impact of a mind wandering episode. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Prediction of the period of psychotic episode in individual schizophrenics by simulation-data construction approach.

PubMed

Huang, Chun-Jung; Wang, Hsiao-Fan; Chiu, Hsien-Jane; Lan, Tsuo-Hung; Hu, Tsung-Ming; Loh, El-Wui

2010-10-01

Although schizophrenia can be treated, most patients still experience inevitable psychotic episodes from time to time. Precautious actions can be taken if the next onset can be predicted. However, sufficient information is always lacking in the clinical scenario. A possible solution is to use the virtual data generated from limited of original data. Data construction method (DCM) has been shown to generate the virtual felt earthquake data effectively and used in the prediction of further events. Here we investigated the performance of DCM in deriving the membership functions and discrete-event simulations (DES) in predicting the period embracing the initiation and termination time-points of the next psychotic episode of 35 individual schizophrenic patients. The results showed that 21 subjects had a success of simulations (RSS) ≥70%. Further analysis demonstrated that the co-morbidity of coronary heart diseases (CHD), risks of CHD, and the frequency of previous psychotic episodes increased the RSS.

State-Dependent Decoding Algorithms Improve the Performance of a Bidirectional BMI in Anesthetized Rats.

PubMed

De Feo, Vito; Boi, Fabio; Safaai, Houman; Onken, Arno; Panzeri, Stefano; Vato, Alessandro

2017-01-01

Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.

Intra-dance variation among waggle runs and the design of efficient protocols for honey bee dance decoding.

PubMed

Couvillon, Margaret J; Riddell Pearce, Fiona C; Harris-Jones, Elisabeth L; Kuepfer, Amanda M; Mackenzie-Smith, Samantha J; Rozario, Laura A; Schürch, Roger; Ratnieks, Francis L W

2012-05-15

Noise is universal in information transfer. In animal communication, this presents a challenge not only for intended signal receivers, but also to biologists studying the system. In honey bees, a forager communicates to nestmates the location of an important resource via the waggle dance. This vibrational signal is composed of repeating units (waggle runs) that are then averaged by nestmates to derive a single vector. Manual dance decoding is a powerful tool for studying bee foraging ecology, although the process is time-consuming: a forager may repeat the waggle run 1- >100 times within a dance. It is impractical to decode all of these to obtain the vector; however, intra-dance waggle runs vary, so it is important to decode enough to obtain a good average. Here we examine the variation among waggle runs made by foraging bees to devise a method of dance decoding. The first and last waggle runs within a dance are significantly more variable than the middle run. There was no trend in variation for the middle waggle runs. We recommend that any four consecutive waggle runs, not including the first and last runs, may be decoded, and we show that this methodology is suitable by demonstrating the goodness-of-fit between the decoded vectors from our subsamples with the vectors from the entire dances.

Intra-dance variation among waggle runs and the design of efficient protocols for honey bee dance decoding

PubMed Central

Couvillon, Margaret J.; Riddell Pearce, Fiona C.; Harris-Jones, Elisabeth L.; Kuepfer, Amanda M.; Mackenzie-Smith, Samantha J.; Rozario, Laura A.; Schürch, Roger; Ratnieks, Francis L. W.

2012-01-01

Summary Noise is universal in information transfer. In animal communication, this presents a challenge not only for intended signal receivers, but also to biologists studying the system. In honey bees, a forager communicates to nestmates the location of an important resource via the waggle dance. This vibrational signal is composed of repeating units (waggle runs) that are then averaged by nestmates to derive a single vector. Manual dance decoding is a powerful tool for studying bee foraging ecology, although the process is time-consuming: a forager may repeat the waggle run 1- >100 times within a dance. It is impractical to decode all of these to obtain the vector; however, intra-dance waggle runs vary, so it is important to decode enough to obtain a good average. Here we examine the variation among waggle runs made by foraging bees to devise a method of dance decoding. The first and last waggle runs within a dance are significantly more variable than the middle run. There was no trend in variation for the middle waggle runs. We recommend that any four consecutive waggle runs, not including the first and last runs, may be decoded, and we show that this methodology is suitable by demonstrating the goodness-of-fit between the decoded vectors from our subsamples with the vectors from the entire dances. PMID:23213438

Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems

PubMed Central

Malik, Wasim Q.; Truccolo, Wilson; Brown, Emery N.; Hochberg, Leigh R.

2011-01-01

The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5 ± 0.5 s (mean ± s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25 ± 3 single units by a factor of 7.0 ± 0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems. PMID:21078582

Extracting Behaviorally Relevant Traits from Natural Stimuli: Benefits of Combinatorial Representations at the Accessory Olfactory Bulb

PubMed Central

Kahan, Anat; Ben-Shaul, Yoram

2016-01-01

For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouse’s strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB) in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a female’s receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons. PMID:26938460

Extracting Behaviorally Relevant Traits from Natural Stimuli: Benefits of Combinatorial Representations at the Accessory Olfactory Bulb.

PubMed

Kahan, Anat; Ben-Shaul, Yoram

2016-03-01

For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouse's strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB) in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a female's receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons.