Visual and auditory socio-cognitive perception in unilateral temporal lobe epilepsy in children and adolescents: a prospective controlled study.

PubMed

Laurent, Agathe; Arzimanoglou, Alexis; Panagiotakaki, Eleni; Sfaello, Ignacio; Kahane, Philippe; Ryvlin, Philippe; Hirsch, Edouard; de Schonen, Scania

2014-12-01

A high rate of abnormal social behavioural traits or perceptual deficits is observed in children with unilateral temporal lobe epilepsy. In the present study, perception of auditory and visual social signals, carried by faces and voices, was evaluated in children or adolescents with temporal lobe epilepsy. We prospectively investigated a sample of 62 children with focal non-idiopathic epilepsy early in the course of the disorder. The present analysis included 39 children with a confirmed diagnosis of temporal lobe epilepsy. Control participants (72), distributed across 10 age groups, served as a control group. Our socio-perceptual evaluation protocol comprised three socio-visual tasks (face identity, facial emotion and gaze direction recognition), two socio-auditory tasks (voice identity and emotional prosody recognition), and three control tasks (lip reading, geometrical pattern and linguistic intonation recognition). All 39 patients also benefited from a neuropsychological examination. As a group, children with temporal lobe epilepsy performed at a significantly lower level compared to the control group with regards to recognition of facial identity, direction of eye gaze, and emotional facial expressions. We found no relationship between the type of visual deficit and age at first seizure, duration of epilepsy, or the epilepsy-affected cerebral hemisphere. Deficits in socio-perceptual tasks could be found independently of the presence of deficits in visual or auditory episodic memory, visual non-facial pattern processing (control tasks), or speech perception. A normal FSIQ did not exempt some of the patients from an underlying deficit in some of the socio-perceptual tasks. Temporal lobe epilepsy not only impairs development of emotion recognition, but can also impair development of perception of other socio-perceptual signals in children with or without intellectual deficiency. Prospective studies need to be designed to evaluate the results of appropriate re-education programs in children presenting with deficits in social cue processing.

Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns.

PubMed

Viswanathan, Jayalakshmi; Rémy, Florence; Bacon-Macé, Nadège; Thorpe, Simon J

2016-01-01

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10- and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities. Significance Statement Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities.

Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns

PubMed Central

Viswanathan, Jayalakshmi; Rémy, Florence; Bacon-Macé, Nadège; Thorpe, Simon J.

2016-01-01

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10− and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities. Significance Statement Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities. PMID:27932941

Learning and recognition of tactile temporal sequences by mice and humans

PubMed Central

Bale, Michael R; Bitzidou, Malamati; Pitas, Anna; Brebner, Leonie S; Khazim, Lina; Anagnou, Stavros T; Stevenson, Caitlin D; Maravall, Miguel

2017-01-01

The world around us is replete with stimuli that unfold over time. When we hear an auditory stream like music or speech or scan a texture with our fingertip, physical features in the stimulus are concatenated in a particular order. This temporal patterning is critical to interpreting the stimulus. To explore the capacity of mice and humans to learn tactile sequences, we developed a task in which subjects had to recognise a continuous modulated noise sequence delivered to whiskers or fingertips, defined by its temporal patterning over hundreds of milliseconds. GO and NO-GO sequences differed only in that the order of their constituent noise modulation segments was temporally scrambled. Both mice and humans efficiently learned tactile sequences. Mouse sequence recognition depended on detecting transitions in noise amplitude; animals could base their decision on the earliest information available. Humans appeared to use additional cues, including the duration of noise modulation segments. DOI: http://dx.doi.org/10.7554/eLife.27333.001 PMID:28812976

Fundamental remote sensing science research program. Part 1: Status report of the mathematical pattern recognition and image analysis project

NASA Technical Reports Server (NTRS)

Heydorn, R. D.

1984-01-01

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of the Earth from remotely sensed measurement of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inference about the Earth.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

PubMed

Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

2015-09-30

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. Copyright © 2015 the authors 0270-6474/15/3513402-17$15.00/0.

Visual pattern recognition based on spatio-temporal patterns of retinal ganglion cells’ activities

PubMed Central

Jing, Wei; Liu, Wen-Zhong; Gong, Xin-Wei; Gong, Hai-Qing

2010-01-01

Neural information is processed based on integrated activities of relevant neurons. Concerted population activity is one of the important ways for retinal ganglion cells to efficiently organize and process visual information. In the present study, the spike activities of bullfrog retinal ganglion cells in response to three different visual patterns (checker-board, vertical gratings and horizontal gratings) were recorded using multi-electrode arrays. A measurement of subsequence distribution discrepancy (MSDD) was applied to identify the spatio-temporal patterns of retinal ganglion cells’ activities in response to different stimulation patterns. The results show that the population activity patterns were different in response to different stimulation patterns, such difference in activity pattern was consistently detectable even when visual adaptation occurred during repeated experimental trials. Therefore, the stimulus pattern can be reliably discriminated according to the spatio-temporal pattern of the neuronal activities calculated using the MSDD algorithm. PMID:21886670

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm

PubMed Central

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-01-01

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen’s temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home. PMID:26007738

A dynamical pattern recognition model of gamma activity in auditory cortex

PubMed Central

Zavaglia, M.; Canolty, R.T.; Schofield, T.M.; Leff, A.P.; Ursino, M.; Knight, R.T.; Penny, W.D.

2012-01-01

This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75–150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain. PMID:22327049

Successful Decoding of Famous Faces in the Fusiform Face Area

PubMed Central

Axelrod, Vadim; Yovel, Galit

2015-01-01

What are the neural mechanisms of face recognition? It is believed that the network of face-selective areas, which spans the occipital, temporal, and frontal cortices, is important in face recognition. A number of previous studies indeed reported that face identity could be discriminated based on patterns of multivoxel activity in the fusiform face area and the anterior temporal lobe. However, given the difficulty in localizing the face-selective area in the anterior temporal lobe, its role in face recognition is still unknown. Furthermore, previous studies limited their analysis to occipito-temporal regions without testing identity decoding in more anterior face-selective regions, such as the amygdala and prefrontal cortex. In the current high-resolution functional Magnetic Resonance Imaging study, we systematically examined the decoding of the identity of famous faces in the temporo-frontal network of face-selective and adjacent non-face-selective regions. A special focus has been put on the face-area in the anterior temporal lobe, which was reliably localized using an optimized scanning protocol. We found that face-identity could be discriminated above chance level only in the fusiform face area. Our results corroborate the role of the fusiform face area in face recognition. Future studies are needed to further explore the role of the more recently discovered anterior face-selective areas in face recognition. PMID:25714434

Neural correlates of own- and other-race face perception: spatial and temporal response differences.

PubMed

Natu, Vaidehi; Raboy, David; O'Toole, Alice J

2011-02-01

Humans show an "other-race effect" for face recognition, with more accurate recognition of own- versus other-race faces. We compared the neural representations of own- and other-race faces using functional magnetic resonance imaging (fMRI) data in combination with a multi-voxel pattern classifier. Neural activity was recorded while Asians and Caucasians viewed Asian and Caucasian faces. A pattern classifier, applied to voxels across a broad range of ventral temporal areas, discriminated the brain activity maps elicited in response to Asian versus Caucasian faces in the brains of both Asians and Caucasians. Classification was most accurate in the first few time points of the block and required the use of own-race faces in the localizer scan to select voxels for classifier input. Next, we examined differences in the time-course of neural responses to own- and other-race faces and found evidence for a temporal "other-race effect." Own-race faces elicited a larger neural response initially that attenuated rapidly. The response to other-race faces was weaker at first, but increased over time, ultimately surpassing the magnitude of the own-race response in the fusiform "face" area (FFA). A similar temporal response pattern held across a broad range of ventral temporal areas. The pattern-classification results indicate the early availability of categorical information about own- versus other-race face status in the spatial pattern of neural activity. The slower, more sustained, brain response to other-race faces may indicate the need to recruit additional neural resources to process other-race faces for identification. Copyright © 2010 Elsevier Inc. All rights reserved.

Improving activity recognition using temporal coherence.

PubMed

Ataya, Abbas; Jallon, Pierre; Bianchi, Pascal; Doron, Maeva

2013-01-01

Assessment of daily physical activity using data from wearable sensors has recently become a prominent research area in the biomedical engineering field and a substantial application for pattern recognition. In this paper, we present an accelerometer-based activity recognition scheme on the basis of a hierarchical structured classifier. A first step consists of distinguishing static activities from dynamic ones in order to extract relevant features for each activity type. Next, a separate classifier is applied to detect more specific activities of the same type. On top of our activity recognition system, we introduce a novel approach to take into account the temporal coherence of activities. Inter-activity transition information is modeled by a directed graph Markov chain. Confidence measures in activity classes are then evaluated from conventional classifier's outputs and coupled with the graph to reinforce activity estimation. Accurate results and significant improvement of activity detection are obtained when applying our system for the recognition of 9 activities for 48 subjects.

It Takes Two–Skilled Recognition of Objects Engages Lateral Areas in Both Hemispheres

PubMed Central

Bilalić, Merim; Kiesel, Andrea; Pohl, Carsten; Erb, Michael; Grodd, Wolfgang

2011-01-01

Our object recognition abilities, a direct product of our experience with objects, are fine-tuned to perfection. Left temporal and lateral areas along the dorsal, action related stream, as well as left infero-temporal areas along the ventral, object related stream are engaged in object recognition. Here we show that expertise modulates the activity of dorsal areas in the recognition of man-made objects with clearly specified functions. Expert chess players were faster than chess novices in identifying chess objects and their functional relations. Experts' advantage was domain-specific as there were no differences between groups in a control task featuring geometrical shapes. The pattern of eye movements supported the notion that experts' extensive knowledge about domain objects and their functions enabled superior recognition even when experts were not directly fixating the objects of interest. Functional magnetic resonance imaging (fMRI) related exclusively the areas along the dorsal stream to chess specific object recognition. Besides the commonly involved left temporal and parietal lateral brain areas, we found that only in experts homologous areas on the right hemisphere were also engaged in chess specific object recognition. Based on these results, we discuss whether skilled object recognition does not only involve a more efficient version of the processes found in non-skilled recognition, but also qualitatively different cognitive processes which engage additional brain areas. PMID:21283683

A Spiking Neural Network System for Robust Sequence Recognition.

PubMed

Yu, Qiang; Yan, Rui; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2016-03-01

This paper proposes a biologically plausible network architecture with spiking neurons for sequence recognition. This architecture is a unified and consistent system with functional parts of sensory encoding, learning, and decoding. This is the first systematic model attempting to reveal the neural mechanisms considering both the upstream and the downstream neurons together. The whole system is a consistent temporal framework, where the precise timing of spikes is employed for information processing and cognitive computing. Experimental results show that the system is competent to perform the sequence recognition, being robust to noisy sensory inputs and invariant to changes in the intervals between input stimuli within a certain range. The classification ability of the temporal learning rule used in the system is investigated through two benchmark tasks that outperform the other two widely used learning rules for classification. The results also demonstrate the computational power of spiking neurons over perceptrons for processing spatiotemporal patterns. In summary, the system provides a general way with spiking neurons to encode external stimuli into spatiotemporal spikes, to learn the encoded spike patterns with temporal learning rules, and to decode the sequence order with downstream neurons. The system structure would be beneficial for developments in both hardware and software.

Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.

PubMed

Syed Abdul Mutalib, Sharifah Norsukhairin; Juahir, Hafizan; Azid, Azman; Mohd Sharif, Sharifah; Latif, Mohd Talib; Aris, Ahmad Zaharin; Zain, Sharifuddin M; Dominick, Doreena

2013-09-01

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.

Functional specialization and convergence in the occipito-temporal cortex supporting haptic and visual identification of human faces and body parts: an fMRI study.

PubMed

Kitada, Ryo; Johnsrude, Ingrid S; Kochiyama, Takanori; Lederman, Susan J

2009-10-01

Humans can recognize common objects by touch extremely well whenever vision is unavailable. Despite its importance to a thorough understanding of human object recognition, the neuroscientific study of this topic has been relatively neglected. To date, the few published studies have addressed the haptic recognition of nonbiological objects. We now focus on haptic recognition of the human body, a particularly salient object category for touch. Neuroimaging studies demonstrate that regions of the occipito-temporal cortex are specialized for visual perception of faces (fusiform face area, FFA) and other body parts (extrastriate body area, EBA). Are the same category-sensitive regions activated when these components of the body are recognized haptically? Here, we use fMRI to compare brain organization for haptic and visual recognition of human body parts. Sixteen subjects identified exemplars of faces, hands, feet, and nonbiological control objects using vision and haptics separately. We identified two discrete regions within the fusiform gyrus (FFA and the haptic face region) that were each sensitive to both haptically and visually presented faces; however, these two regions differed significantly in their response patterns. Similarly, two regions within the lateral occipito-temporal area (EBA and the haptic body region) were each sensitive to body parts in both modalities, although the response patterns differed. Thus, although the fusiform gyrus and the lateral occipito-temporal cortex appear to exhibit modality-independent, category-sensitive activity, our results also indicate a degree of functional specialization related to sensory modality within these structures.

Compensation for Blur Requires Increase in Field of View and Viewing Time

PubMed Central

Kwon, MiYoung; Liu, Rong; Chien, Lillian

2016-01-01

Spatial resolution is an important factor for human pattern recognition. In particular, low resolution (blur) is a defining characteristic of low vision. Here, we examined spatial (field of view) and temporal (stimulus duration) requirements for blurry object recognition. The spatial resolution of an image such as letter or face, was manipulated with a low-pass filter. In experiment 1, studying spatial requirement, observers viewed a fixed-size object through a window of varying sizes, which was repositioned until object identification (moving window paradigm). Field of view requirement, quantified as the number of “views” (window repositions) for correct recognition, was obtained for three blur levels, including no blur. In experiment 2, studying temporal requirement, we determined threshold viewing time, the stimulus duration yielding criterion recognition accuracy, at six blur levels, including no blur. For letter and face recognition, we found blur significantly increased the number of views, suggesting a larger field of view is required to recognize blurry objects. We also found blur significantly increased threshold viewing time, suggesting longer temporal integration is necessary to recognize blurry objects. The temporal integration reflects the tradeoff between stimulus intensity and time. While humans excel at recognizing blurry objects, our findings suggest compensating for blur requires increased field of view and viewing time. The need for larger spatial and longer temporal integration for recognizing blurry objects may further challenge object recognition in low vision. Thus, interactions between blur and field of view should be considered for developing low vision rehabilitation or assistive aids. PMID:27622710

Selective verbal recognition memory impairments are associated with atrophy of the language network in non-semantic variants of primary progressive aphasia.

PubMed

Nilakantan, Aneesha S; Voss, Joel L; Weintraub, Sandra; Mesulam, M-Marsel; Rogalski, Emily J

2017-06-01

Primary progressive aphasia (PPA) is clinically defined by an initial loss of language function and preservation of other cognitive abilities, including episodic memory. While PPA primarily affects the left-lateralized perisylvian language network, some clinical neuropsychological tests suggest concurrent initial memory loss. The goal of this study was to test recognition memory of objects and words in the visual and auditory modality to separate language-processing impairments from retentive memory in PPA. Individuals with non-semantic PPA had longer reaction times and higher false alarms for auditory word stimuli compared to visual object stimuli. Moreover, false alarms for auditory word recognition memory were related to cortical thickness within the left inferior frontal gyrus and left temporal pole, while false alarms for visual object recognition memory was related to cortical thickness within the right-temporal pole. This pattern of results suggests that specific vulnerability in processing verbal stimuli can hinder episodic memory in PPA, and provides evidence for differential contributions of the left and right temporal poles in word and object recognition memory. Copyright © 2017 Elsevier Ltd. All rights reserved.

Speaker normalization for chinese vowel recognition in cochlear implants.

PubMed

Luo, Xin; Fu, Qian-Jie

2005-07-01

Because of the limited spectra-temporal resolution associated with cochlear implants, implant patients often have greater difficulty with multitalker speech recognition. The present study investigated whether multitalker speech recognition can be improved by applying speaker normalization techniques to cochlear implant speech processing. Multitalker Chinese vowel recognition was tested with normal-hearing Chinese-speaking subjects listening to a 4-channel cochlear implant simulation, with and without speaker normalization. For each subject, speaker normalization was referenced to the speaker that produced the best recognition performance under conditions without speaker normalization. To match the remaining speakers to this "optimal" output pattern, the overall frequency range of the analysis filter bank was adjusted for each speaker according to the ratio of the mean third formant frequency values between the specific speaker and the reference speaker. Results showed that speaker normalization provided a small but significant improvement in subjects' overall recognition performance. After speaker normalization, subjects' patterns of recognition performance across speakers changed, demonstrating the potential for speaker-dependent effects with the proposed normalization technique.

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.

Tracking speech comprehension in space and time.

PubMed

Pulvermüller, Friedemann; Shtyrov, Yury; Ilmoniemi, Risto J; Marslen-Wilson, William D

2006-07-01

A fundamental challenge for the cognitive neuroscience of language is to capture the spatio-temporal patterns of brain activity that underlie critical functional components of the language comprehension process. We combine here psycholinguistic analysis, whole-head magnetoencephalography (MEG), the Mismatch Negativity (MMN) paradigm, and state-of-the-art source localization techniques (Equivalent Current Dipole and L1 Minimum-Norm Current Estimates) to locate the process of spoken word recognition at a specific moment in space and time. The magnetic MMN to words presented as rare "deviant stimuli" in an oddball paradigm among repetitive "standard" speech stimuli, peaked 100-150 ms after the information in the acoustic input, was sufficient for word recognition. The latency with which words were recognized corresponded to that of an MMN source in the left superior temporal cortex. There was a significant correlation (r = 0.7) of latency measures of word recognition in individual study participants with the latency of the activity peak of the superior temporal source. These results demonstrate a correspondence between the behaviorally determined recognition point for spoken words and the cortical activation in left posterior superior temporal areas. Both the MMN calculated in the classic manner, obtained by subtracting standard from deviant stimulus response recorded in the same experiment, and the identity MMN (iMMN), defined as the difference between the neuromagnetic responses to the same stimulus presented as standard and deviant stimulus, showed the same significant correlation with word recognition processes.

Fluidity of HIV-1-Specific T-Cell Responses during Acute and Early Subtype C HIV-1 Infection and Associations with Early Disease Progression ▿

PubMed Central

Mlotshwa, Mandla; Riou, Catherine; Chopera, Denis; de Assis Rosa, Debra; Ntale, Roman; Treunicht, Florette; Woodman, Zenda; Werner, Lise; van Loggerenberg, Francois; Mlisana, Koleka; Abdool Karim, Salim; Williamson, Carolyn; Gray, Clive M.

2010-01-01

Deciphering immune events during early stages of human immunodeficiency virus type 1 (HIV-1) infection is critical for understanding the course of disease. We characterized the hierarchy of HIV-1-specific T-cell gamma interferon (IFN-γ) enzyme-linked immunospot (ELISPOT) assay responses during acute subtype C infection in 53 individuals and associated temporal patterns of responses with disease progression in the first 12 months. There was a diverse pattern of T-cell recognition across the proteome, with the recognition of Nef being immunodominant as early as 3 weeks postinfection. Over the first 6 months, we found that there was a 23% chance of an increased response to Nef for every week postinfection (P = 0.0024), followed by a nonsignificant increase to Pol (4.6%) and Gag (3.2%). Responses to Env and regulatory proteins appeared to remain stable. Three temporal patterns of HIV-specific T-cell responses could be distinguished: persistent, lost, or new. The proportion of persistent T-cell responses was significantly lower (P = 0.0037) in individuals defined as rapid progressors than in those progressing slowly and who controlled viremia. Almost 90% of lost T-cell responses were coincidental with autologous viral epitope escape. Regression analysis between the time to fixed viral escape and lost T-cell responses (r = 0.61; P = 0.019) showed a mean delay of 14 weeks after viral escape. Collectively, T-cell epitope recognition is not a static event, and temporal patterns of IFN-γ-based responses exist. This is due partly to viral sequence variation but also to the recognition of invariant viral epitopes that leads to waves of persistent T-cell immunity, which appears to associate with slower disease progression in the first year of infection. PMID:20826686

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems.

PubMed

Jácome, Gabriel; Valarezo, Carla; Yoo, Changkyoo

2018-03-30

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.

Human action recognition based on spatial-temporal descriptors using key poses

NASA Astrophysics Data System (ADS)

Hu, Shuo; Chen, Yuxin; Wang, Huaibao; Zuo, Yaqing

2014-11-01

Human action recognition is an important area of pattern recognition today due to its direct application and need in various occasions like surveillance and virtual reality. In this paper, a simple and effective human action recognition method is presented based on the key poses of human silhouette and the spatio-temporal feature. Firstly, the contour points of human silhouette have been gotten, and the key poses are learned by means of K-means clustering based on the Euclidean distance between each contour point and the centre point of the human silhouette, and then the type of each action is labeled for further match. Secondly, we obtain the trajectories of centre point of each frame, and create a spatio-temporal feature value represented by W to describe the motion direction and speed of each action. The value W contains the information of location and temporal order of each point on the trajectories. Finally, the matching stage is performed by comparing the key poses and W between training sequences and test sequences, the nearest neighbor sequences is found and its label supplied the final result. Experiments on the public available Weizmann datasets show the proposed method can improve accuracy by distinguishing amphibious poses and increase suitability for real-time applications by reducing the computational cost.

Right Limbic FDG-PET Hypometabolism Correlates with Emotion Recognition and Attribution in Probable Behavioral Variant of Frontotemporal Dementia Patients

PubMed Central

Cerami, Chiara; Dodich, Alessandra; Iannaccone, Sandro; Marcone, Alessandra; Lettieri, Giada; Crespi, Chiara; Gianolli, Luigi; Cappa, Stefano F.; Perani, Daniela

2015-01-01

The behavioural variant of frontotemporal dementia (bvFTD) is a rare disease mainly affecting the social brain. FDG-PET fronto-temporal hypometabolism is a supportive feature for the diagnosis. It may also provide specific functional metabolic signatures for altered socio-emotional processing. In this study, we evaluated the emotion recognition and attribution deficits and FDG-PET cerebral metabolic patterns at the group and individual levels in a sample of sporadic bvFTD patients, exploring the cognitive-functional correlations. Seventeen probable mild bvFTD patients (10 male and 7 female; age 67.8±9.9) were administered standardized and validated version of social cognition tasks assessing the recognition of basic emotions and the attribution of emotions and intentions (i.e., Ekman 60-Faces test-Ek60F and Story-based Empathy task-SET). FDG-PET was analysed using an optimized voxel-based SPM method at the single-subject and group levels. Severe deficits of emotion recognition and processing characterized the bvFTD condition. At the group level, metabolic dysfunction in the right amygdala, temporal pole, and middle cingulate cortex was highly correlated to the emotional recognition and attribution performances. At the single-subject level, however, heterogeneous impairments of social cognition tasks emerged, and different metabolic patterns, involving limbic structures and prefrontal cortices, were also observed. The derangement of a right limbic network is associated with altered socio-emotional processing in bvFTD patients, but different hypometabolic FDG-PET patterns and heterogeneous performances on social tasks at an individual level exist. PMID:26513651

Relationship between slow visual processing and reading speed in people with macular degeneration

PubMed Central

Cheong, Allen MY; Legge, Gordon E; Lawrence, Mary G; Cheung, Sing-Hang; Ruff, Mary A

2007-01-01

Purpose People with macular degeneration (MD) often read slowly even with adequate magnification to compensate for acuity loss. Oculomotor deficits may affect reading in MD, but cannot fully explain the substantial reduction in reading speed. Central-field loss (CFL) is often a consequence of macular degeneration, necessitating the use of peripheral vision for reading. We hypothesized that slower temporal processing of visual patterns in peripheral vision is a factor contributing to slow reading performance in MD patients. Methods Fifteen subjects with MD, including 12 with CFL, and five age-matched control subjects were recruited. Maximum reading speed and critical print size were measured with RSVP (Rapid Serial Visual Presentation). Temporal processing speed was studied by measuring letter-recognition accuracy for strings of three randomly selected letters centered at fixation for a range of exposure times. Temporal threshold was defined as the exposure time yielding 80% recognition accuracy for the central letter. Results Temporal thresholds for the MD subjects ranged from 159 to 5881 ms, much longer than values for age-matched controls in central vision (13 ms, p<0.01). The mean temporal threshold for the 11 MD subjects who used eccentric fixation (1555.8 ± 1708.4 ms) was much longer than the mean temporal threshold (97.0 ms ± 34.2 ms, p<0.01) for the age-matched controls at 10° in the lower visual field. Individual temporal thresholds accounted for 30% of the variance in reading speed (p<0.05). Conclusion The significant association between increased temporal threshold for letter recognition and reduced reading speed is consistent with the hypothesis that slower visual processing of letter recognition is one of the factors limiting reading speed in MD subjects. PMID:17881032

Complex auditory behaviour emerges from simple reactive steering

NASA Astrophysics Data System (ADS)

Hedwig, Berthold; Poulet, James F. A.

2004-08-01

The recognition and localization of sound signals is fundamental to acoustic communication. Complex neural mechanisms are thought to underlie the processing of species-specific sound patterns even in animals with simple auditory pathways. In female crickets, which orient towards the male's calling song, current models propose pattern recognition mechanisms based on the temporal structure of the song. Furthermore, it is thought that localization is achieved by comparing the output of the left and right recognition networks, which then directs the female to the pattern that most closely resembles the species-specific song. Here we show, using a highly sensitive method for measuring the movements of female crickets, that when walking and flying each sound pulse of the communication signal releases a rapid steering response. Thus auditory orientation emerges from reactive motor responses to individual sound pulses. Although the reactive motor responses are not based on the song structure, a pattern recognition process may modulate the gain of the responses on a longer timescale. These findings are relevant to concepts of insect auditory behaviour and to the development of biologically inspired robots performing cricket-like auditory orientation.

Temporal-pattern recognition by single neurons in a sensory pathway devoted to social communication behavior

PubMed Central

Carlson, Bruce A.

2010-01-01

Sensory systems often encode stimulus information into the temporal pattern of action potential activity. However, little is known about how the information contained within these patterns is extracted by postsynaptic neurons. Similar to temporal coding by sensory neurons, social information in mormyrid fish is encoded into the temporal patterning of an electric organ discharge (EOD). In the current study, sensitivity to temporal patterns of electrosensory stimuli was found to arise within the midbrain posterior exterolateral nucleus (ELp). Whole-cell patch recordings from ELp neurons in vivo revealed three patterns of interpulse interval (IPI) tuning: low-pass neurons tuned to long intervals, high-pass neurons tuned to short intervals and band-pass neurons tuned to intermediate intervals. Many neurons within each class also responded preferentially to either increasing or decreasing IPIs. Playback of electric signaling patterns recorded from freely behaving fish revealed that the IPI and direction tuning of ELp neurons resulted in selective responses to particular social communication displays characterized by distinct IPI patterns. The postsynaptic potential responses of many neurons indicated a combination of excitatory and inhibitory synaptic input, and the IPI tuning of ELp neurons was directly related to rate-dependent changes in the direction and amplitude of postsynaptic potentials. These results suggest that differences in the dynamics of short-term synaptic plasticity in excitatory and inhibitory pathways may tune central sensory neurons to particular temporal patterns of presynaptic activity. This may represent a general mechanism for the processing of behaviorally-relevant stimulus information encoded into temporal patterns of activity by sensory neurons. PMID:19641105

Temporal-pattern recognition by single neurons in a sensory pathway devoted to social communication behavior.

PubMed

Carlson, Bruce A

2009-07-29

Sensory systems often encode stimulus information into the temporal pattern of action potential activity. However, little is known about how the information contained within these patterns is extracted by postsynaptic neurons. Similar to temporal coding by sensory neurons, social information in mormyrid fish is encoded into the temporal patterning of an electric organ discharge. In the current study, sensitivity to temporal patterns of electrosensory stimuli was found to arise within the midbrain posterior exterolateral nucleus (ELp). Whole-cell patch recordings from ELp neurons in vivo revealed three patterns of interpulse interval (IPI) tuning: low-pass neurons tuned to long intervals, high-pass neurons tuned to short intervals, and bandpass neurons tuned to intermediate intervals. Many neurons within each class also responded preferentially to either increasing or decreasing IPIs. Playback of electric signaling patterns recorded from freely behaving fish revealed that the IPI and direction tuning of ELp neurons resulted in selective responses to particular social communication displays characterized by distinct IPI patterns. The postsynaptic potential responses of many neurons indicated a combination of excitatory and inhibitory synaptic input, and the IPI tuning of ELp neurons was directly related to rate-dependent changes in the direction and amplitude of postsynaptic potentials. These results suggest that differences in the dynamics of short-term synaptic plasticity in excitatory and inhibitory pathways may tune central sensory neurons to particular temporal patterns of presynaptic activity. This may represent a general mechanism for the processing of behaviorally relevant stimulus information encoded into temporal patterns of activity by sensory neurons.

Role of temporal processing stages by inferior temporal neurons in facial recognition.

PubMed

Sugase-Miyamoto, Yasuko; Matsumoto, Narihisa; Kawano, Kenji

2011-01-01

In this review, we focus on the role of temporal stages of encoded facial information in the visual system, which might enable the efficient determination of species, identity, and expression. Facial recognition is an important function of our brain and is known to be processed in the ventral visual pathway, where visual signals are processed through areas V1, V2, V4, and the inferior temporal (IT) cortex. In the IT cortex, neurons show selective responses to complex visual images such as faces, and at each stage along the pathway the stimulus selectivity of the neural responses becomes sharper, particularly in the later portion of the responses. In the IT cortex of the monkey, facial information is represented by different temporal stages of neural responses, as shown in our previous study: the initial transient response of face-responsive neurons represents information about global categories, i.e., human vs. monkey vs. simple shapes, whilst the later portion of these responses represents information about detailed facial categories, i.e., expression and/or identity. This suggests that the temporal stages of the neuronal firing pattern play an important role in the coding of visual stimuli, including faces. This type of coding may be a plausible mechanism underlying the temporal dynamics of recognition, including the process of detection/categorization followed by the identification of objects. Recent single-unit studies in monkeys have also provided evidence consistent with the important role of the temporal stages of encoded facial information. For example, view-invariant facial identity information is represented in the response at a later period within a region of face-selective neurons. Consistent with these findings, temporally modulated neural activity has also been observed in human studies. These results suggest a close correlation between the temporal processing stages of facial information by IT neurons and the temporal dynamics of face recognition.

Role of Temporal Processing Stages by Inferior Temporal Neurons in Facial Recognition

PubMed Central

Sugase-Miyamoto, Yasuko; Matsumoto, Narihisa; Kawano, Kenji

2011-01-01

In this review, we focus on the role of temporal stages of encoded facial information in the visual system, which might enable the efficient determination of species, identity, and expression. Facial recognition is an important function of our brain and is known to be processed in the ventral visual pathway, where visual signals are processed through areas V1, V2, V4, and the inferior temporal (IT) cortex. In the IT cortex, neurons show selective responses to complex visual images such as faces, and at each stage along the pathway the stimulus selectivity of the neural responses becomes sharper, particularly in the later portion of the responses. In the IT cortex of the monkey, facial information is represented by different temporal stages of neural responses, as shown in our previous study: the initial transient response of face-responsive neurons represents information about global categories, i.e., human vs. monkey vs. simple shapes, whilst the later portion of these responses represents information about detailed facial categories, i.e., expression and/or identity. This suggests that the temporal stages of the neuronal firing pattern play an important role in the coding of visual stimuli, including faces. This type of coding may be a plausible mechanism underlying the temporal dynamics of recognition, including the process of detection/categorization followed by the identification of objects. Recent single-unit studies in monkeys have also provided evidence consistent with the important role of the temporal stages of encoded facial information. For example, view-invariant facial identity information is represented in the response at a later period within a region of face-selective neurons. Consistent with these findings, temporally modulated neural activity has also been observed in human studies. These results suggest a close correlation between the temporal processing stages of facial information by IT neurons and the temporal dynamics of face recognition. PMID:21734904

Modularity of music: evidence from a case of pure amusia.

PubMed

Piccirilli, M; Sciarma, T; Luzzi, S

2000-10-01

A case of pure amusia in a 20 year old left handed non-professional musician is reported. The patient showed an impairment of music abilities in the presence of normal processing of speech and environmental sounds. Furthermore, whereas recognition and production of melodic sequences were grossly disturbed, both the recognition and production of rhythm patterns were preserved. This selective breakdown pattern was produced by a focal lesion in the left superior temporal gyrus. This case thus suggests that not only linguistic and musical skills, but also melodic and rhythmic processing are independent of each other. This functional dissociation in the musical domain supports the hypothesis that music components have a modular organisation. Furthermore, there is the suggestion that amusia may be produced by a lesion located strictly in one hemisphere and that the superior temporal gyrus plays a crucial part in melodic processing.

Creative-Dynamics Approach To Neural Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

Fundamental remote science research program. Part 2: Status report of the mathematical pattern recognition and image analysis project

NASA Technical Reports Server (NTRS)

Heydorn, R. P.

1984-01-01

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of he Earth from remotely sensed measurements of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inferences about the Earth. This report summarizes the progress that has been made toward this program goal by each of the principal investigators in the MPRIA Program.

Characterizing the spatio-temporal dynamics of the neural events occurring prior to and up to overt recognition of famous faces.

PubMed

Jemel, Boutheina; Schuller, Anne-Marie; Goffaux, Valérie

2010-10-01

Although it is generally acknowledged that familiar face recognition is fast, mandatory, and proceeds outside conscious control, it is still unclear whether processes leading to familiar face recognition occur in a linear (i.e., gradual) or a nonlinear (i.e., all-or-none) manner. To test these two alternative accounts, we recorded scalp ERPs while participants indicated whether they recognize as familiar the faces of famous and unfamiliar persons gradually revealed in a descending sequence of frames, from the noisier to the least noisy. This presentation procedure allowed us to characterize the changes in scalp ERP responses occurring prior to and up to overt recognition. Our main finding is that gradual and all-or-none processes are possibly involved during overt recognition of familiar faces. Although the N170 and the N250 face-sensitive responses displayed an abrupt activity change at the moment of overt recognition of famous faces, later ERPs encompassing the N400 and late positive component exhibited an incremental increase in amplitude as the point of recognition approached. In addition, famous faces that were not overtly recognized at one trial before recognition elicited larger ERP potentials than unfamiliar faces, probably reflecting a covert recognition process. Overall, these findings present evidence that recognition of familiar faces implicates spatio-temporally complex neural processes exhibiting differential pattern activity changes as a function of recognition state.

Long-term modifications of synaptic efficacy in the human inferior and middle temporal cortex

NASA Technical Reports Server (NTRS)

Chen, W. R.; Lee, S.; Kato, K.; Spencer, D. D.; Shepherd, G. M.; Williamson, A.

1996-01-01

The primate temporal cortex has been demonstrated to play an important role in visual memory and pattern recognition. It is of particular interest to investigate whether activity-dependent modification of synaptic efficacy, a presumptive mechanism for learning and memory, is present in this cortical region. Here we address this issue by examining the induction of synaptic plasticity in surgically resected human inferior and middle temporal cortex. The results show that synaptic strength in the human temporal cortex could undergo bidirectional modifications, depending on the pattern of conditioning stimulation. High frequency stimulation (100 or 40 Hz) in layer IV induced long-term potentiation (LTP) of both intracellular excitatory postsynaptic potentials and evoked field potentials in layers II/III. The LTP induced by 100 Hz tetanus was blocked by 50-100 microM DL-2-amino-5-phosphonovaleric acid, suggesting that N-methyl-D-aspartate receptors were responsible for its induction. Long-term depression (LTD) was elicited by prolonged low frequency stimulation (1 Hz, 15 min). It was reduced, but not completely blocked, by DL-2-amino-5-phosphonovaleric acid, implying that some other mechanisms in addition to N-methyl-DL-aspartate receptors were involved in LTD induction. LTD was input-specific, i.e., low frequency stimulation of one pathway produced LTD of synaptic transmission in that pathway only. Finally, the LTP and LTD could reverse each other, suggesting that they can act cooperatively to modify the functional state of cortical network. These results suggest that LTP and LTD are possible mechanisms for the visual memory and pattern recognition functions performed in the human temporal cortex.

Listening for Recollection: A Multi-Voxel Pattern Analysis of Recognition Memory Retrieval Strategies

PubMed Central

Quamme, Joel R.; Weiss, David J.; Norman, Kenneth A.

2010-01-01

Recent studies of recognition memory indicate that subjects can strategically vary how much they rely on recollection of specific details vs. feelings of familiarity when making recognition judgments. One possible explanation of these results is that subjects can establish an internally directed attentional state (“listening for recollection”) that enhances retrieval of studied details; fluctuations in this attentional state over time should be associated with fluctuations in subjects’ recognition behavior. In this study, we used multi-voxel pattern analysis of fMRI data to identify brain regions that are involved in listening for recollection. We looked for brain regions that met the following criteria: (1) Distinct neural patterns should be present when subjects are instructed to rely on recollection vs. familiarity, and (2) fluctuations in these neural patterns should be related to recognition behavior in the manner predicted by dual-process theories of recognition: Specifically, the presence of the recollection pattern during the pre-stimulus interval (indicating that subjects are “listening for recollection” at that moment) should be associated with a selective decrease in false alarms to related lures. We found that pre-stimulus activity in the right supramarginal gyrus met all of these criteria, suggesting that this region proactively establishes an internally directed attentional state that fosters recollection. We also found other regions (e.g., left middle temporal gyrus) where the pattern of neural activity was related to subjects’ responding to related lures after stimulus onset (but not before), suggesting that these regions implement processes that are engaged in a reactive fashion to boost recollection. PMID:20740073

Famous faces and voices: Differential profiles in early right and left semantic dementia and in Alzheimer's disease.

PubMed

Luzzi, Simona; Baldinelli, Sara; Ranaldi, Valentina; Fabi, Katia; Cafazzo, Viviana; Fringuelli, Fabio; Silvestrini, Mauro; Provinciali, Leandro; Reverberi, Carlo; Gainotti, Guido

2017-01-08

Famous face and voice recognition is reported to be impaired both in semantic dementia (SD) and in Alzheimer's Disease (AD), although more severely in the former. In AD a coexistence of perceptual impairment in face and voice processing has also been reported and this could contribute to the altered performance in complex semantic tasks. On the other hand, in SD both face and voice recognition disorders could be related to the prevalence of atrophy in the right temporal lobe (RTL). The aim of the present study was twofold: (1) to investigate famous faces and voices recognition in SD and AD to verify if the two diseases show a differential pattern of impairment, resulting from disruption of different cognitive mechanisms; (2) to check if face and voice recognition disorders prevail in patients with atrophy mainly affecting the RTL. To avoid the potential influence of primary perceptual problems in face and voice recognition, a pool of patients suffering from early SD and AD were administered a detailed set of tests exploring face and voice perception. Thirteen SD (8 with prevalence of right and 5 with prevalence of left temporal atrophy) and 25 CE patients, who did not show visual and auditory perceptual impairment, were finally selected and were administered an experimental battery exploring famous face and voice recognition and naming. Twelve SD patients underwent cerebral PET imaging and were classified in right and left SD according to the onset modality and to the prevalent decrease in FDG uptake in right or left temporal lobe respectively. Correlation of PET imaging and famous face and voice recognition was performed. Results showed a differential performance profile in the two diseases, because AD patients were significantly impaired in the naming tests, but showed preserved recognition, whereas SD patients were profoundly impaired both in naming and in recognition of famous faces and voices. Furthermore, face and voice recognition disorders prevailed in SD patients with RTL atrophy, who also showed a conceptual impairment on the Pyramids and Palm Trees test more important in the pictorial than in the verbal modality. Finally, in 12SD patients in whom PET was available, a strong correlation between FDG uptake and face-to-name and voice-to-name matching data was found in the right but not in the left temporal lobe. The data support the hypothesis of a different cognitive basis for impairment of face and voice recognition in the two dementias and suggest that the pattern of impairment in SD may be due to a loss of semantic representations, while a defect of semantic control, with impaired naming and preserved recognition might be hypothesized in AD. Furthermore, the correlation between face and voice recognition disorders and RTL damage are consistent with the hypothesis assuming that in the RTL person-specific knowledge may be mainly based upon non-verbal representations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Beyond sensory images: Object-based representation in the human ventral pathway

PubMed Central

Pietrini, Pietro; Furey, Maura L.; Ricciardi, Emiliano; Gobbini, M. Ida; Wu, W.-H. Carolyn; Cohen, Leonardo; Guazzelli, Mario; Haxby, James V.

2004-01-01

We investigated whether the topographically organized, category-related patterns of neural response in the ventral visual pathway are a representation of sensory images or a more abstract representation of object form that is not dependent on sensory modality. We used functional MRI to measure patterns of response evoked during visual and tactile recognition of faces and manmade objects in sighted subjects and during tactile recognition in blind subjects. Results showed that visual and tactile recognition evoked category-related patterns of response in a ventral extrastriate visual area in the inferior temporal gyrus that were correlated across modality for manmade objects. Blind subjects also demonstrated category-related patterns of response in this “visual” area, and in more ventral cortical regions in the fusiform gyrus, indicating that these patterns are not due to visual imagery and, furthermore, that visual experience is not necessary for category-related representations to develop in these cortices. These results demonstrate that the representation of objects in the ventral visual pathway is not simply a representation of visual images but, rather, is a representation of more abstract features of object form. PMID:15064396

Déjà vu in unilateral temporal-lobe epilepsy is associated with selective familiarity impairments on experimental tasks of recognition memory.

PubMed

Martin, Chris B; Mirsattari, Seyed M; Pruessner, Jens C; Pietrantonio, Sandra; Burneo, Jorge G; Hayman-Abello, Brent; Köhler, Stefan

2012-11-01

In déjà vu, a phenomenological impression of familiarity for the current visual environment is experienced with a sense that it should in fact not feel familiar. The fleeting nature of this phenomenon in daily life, and the difficulty in developing experimental paradigms to elicit it, has hindered progress in understanding déjà vu. Some neurological patients with temporal-lobe epilepsy (TLE) consistently experience déjà vu at the onset of their seizures. An investigation of such patients offers a unique opportunity to shed light on its possible underlying mechanisms. In the present study, we sought to determine whether unilateral TLE patients with déjà vu (TLE+) show a unique pattern of interictal memory deficits that selectively affect familiarity assessment. In Experiment 1, we employed a Remember-Know paradigm for categorized visual scenes and found evidence for impairments that were limited to familiarity-based responses. In Experiment 2, we administered an exclusion task for highly similar categorized visual scenes that placed both recognition processes in opposition. TLE+ patients again displayed recognition impairments, and these impairments spared their ability to engage recollective processes so as to counteract familiarity. The selective deficits we observed in TLE+ patients contrasted with the broader pattern of recognition-memory impairments that was present in a control group of unilateral patients without déjà vu (TLE-). MRI volumetry revealed that ipsilateral medial temporal structures were less broadly affected in TLE+ than in TLE- patients, with a trend for more focal volume reductions in the rhinal cortices of the TLE+ group. The current findings establish a first empirical link between déjà vu in TLE and processes of familiarity assessment, as defined and measured in current cognitive models. They also reveal a pattern of selectivity in recognition impairments that is rarely observed and, thus, of significant theoretical interest to the memory literature at large. Copyright © 2012 Elsevier Ltd. All rights reserved.

Temporal lobe structures and facial emotion recognition in schizophrenia patients and nonpsychotic relatives.

PubMed

Goghari, Vina M; Macdonald, Angus W; Sponheim, Scott R

2011-11-01

Temporal lobe abnormalities and emotion recognition deficits are prominent features of schizophrenia and appear related to the diathesis of the disorder. This study investigated whether temporal lobe structural abnormalities were associated with facial emotion recognition deficits in schizophrenia and related to genetic liability for the disorder. Twenty-seven schizophrenia patients, 23 biological family members, and 36 controls participated. Several temporal lobe regions (fusiform, superior temporal, middle temporal, amygdala, and hippocampus) previously associated with face recognition in normative samples and found to be abnormal in schizophrenia were evaluated using volumetric analyses. Participants completed a facial emotion recognition task and an age recognition control task under time-limited and self-paced conditions. Temporal lobe volumes were tested for associations with task performance. Group status explained 23% of the variance in temporal lobe volume. Left fusiform gray matter volume was decreased by 11% in patients and 7% in relatives compared with controls. Schizophrenia patients additionally exhibited smaller hippocampal and middle temporal volumes. Patients were unable to improve facial emotion recognition performance with unlimited time to make a judgment but were able to improve age recognition performance. Patients additionally showed a relationship between reduced temporal lobe gray matter and poor facial emotion recognition. For the middle temporal lobe region, the relationship between greater volume and better task performance was specific to facial emotion recognition and not age recognition. Because schizophrenia patients exhibited a specific deficit in emotion recognition not attributable to a generalized impairment in face perception, impaired emotion recognition may serve as a target for interventions.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

PubMed

Zhuang, Ning; Zeng, Ying; Yang, Kai; Zhang, Chi; Tong, Li; Yan, Bin

2018-03-12

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

PubMed Central

Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

2018-01-01

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

Hierarchical singleton-type recurrent neural fuzzy networks for noisy speech recognition.

PubMed

Juang, Chia-Feng; Chiou, Chyi-Tian; Lai, Chun-Lung

2007-05-01

This paper proposes noisy speech recognition using hierarchical singleton-type recurrent neural fuzzy networks (HSRNFNs). The proposed HSRNFN is a hierarchical connection of two singleton-type recurrent neural fuzzy networks (SRNFNs), where one is used for noise filtering and the other for recognition. The SRNFN is constructed by recurrent fuzzy if-then rules with fuzzy singletons in the consequences, and their recurrent properties make them suitable for processing speech patterns with temporal characteristics. In n words recognition, n SRNFNs are created for modeling n words, where each SRNFN receives the current frame feature and predicts the next one of its modeling word. The prediction error of each SRNFN is used as recognition criterion. In filtering, one SRNFN is created, and each SRNFN recognizer is connected to the same SRNFN filter, which filters noisy speech patterns in the feature domain before feeding them to the SRNFN recognizer. Experiments with Mandarin word recognition under different types of noise are performed. Other recognizers, including multilayer perceptron (MLP), time-delay neural networks (TDNNs), and hidden Markov models (HMMs), are also tested and compared. These experiments and comparisons demonstrate good results with HSRNFN for noisy speech recognition tasks.

Biologically inspired emotion recognition from speech

NASA Astrophysics Data System (ADS)

Caponetti, Laura; Buscicchio, Cosimo Alessandro; Castellano, Giovanna

2011-12-01

Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM) recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC) and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

Use of Co-occurrences for Temporal Expressions Annotation

NASA Astrophysics Data System (ADS)

Craveiro, Olga; Macedo, Joaquim; Madeira, Henrique

The annotation or extraction of temporal information from text documents is becoming increasingly important in many natural language processing applications such as text summarization, information retrieval, question answering, etc.. This paper presents an original method for easy recognition of temporal expressions in text documents. The method creates semantically classified temporal patterns, using word co-occurrences obtained from training corpora and a pre-defined seed keywords set, derived from the used language temporal references. A participation on a Portuguese named entity evaluation contest showed promising effectiveness and efficiency results. This approach can be adapted to recognize other type of expressions or languages, within other contexts, by defining the suitable word sets and training corpora.

Temporal abstraction and inductive logic programming for arrhythmia recognition from electrocardiograms.

PubMed

Carrault, G; Cordier, M-O; Quiniou, R; Wang, F

2003-07-01

This paper proposes a novel approach to cardiac arrhythmia recognition from electrocardiograms (ECGs). ECGs record the electrical activity of the heart and are used to diagnose many heart disorders. The numerical ECG is first temporally abstracted into series of time-stamped events. Temporal abstraction makes use of artificial neural networks to extract interesting waves and their features from the input signals. A temporal reasoner called a chronicle recogniser processes such series in order to discover temporal patterns called chronicles which can be related to cardiac arrhythmias. Generally, it is difficult to elicit an accurate set of chronicles from a doctor. Thus, we propose to learn automatically from symbolic ECG examples the chronicles discriminating the arrhythmias belonging to some specific subset. Since temporal relationships are of major importance, inductive logic programming (ILP) is the tool of choice as it enables first-order relational learning. The approach has been evaluated on real ECGs taken from the MIT-BIH database. The performance of the different modules as well as the efficiency of the whole system is presented. The results are rather good and demonstrate that integrating numerical techniques for low level perception and symbolic techniques for high level classification is very valuable.

Employing wavelet-based texture features in ammunition classification

NASA Astrophysics Data System (ADS)

Borzino, Ángelo M. C. R.; Maher, Robert C.; Apolinário, José A.; de Campos, Marcello L. R.

2017-05-01

Pattern recognition, a branch of machine learning, involves classification of information in images, sounds, and other digital representations. This paper uses pattern recognition to identify which kind of ammunition was used when a bullet was fired based on a carefully constructed set of gunshot sound recordings. To do this task, we show that texture features obtained from the wavelet transform of a component of the gunshot signal, treated as an image, and quantized in gray levels, are good ammunition discriminators. We test the technique with eight different calibers and achieve a classification rate better than 95%. We also compare the performance of the proposed method with results obtained by standard temporal and spectrographic techniques

Perceiving patterns of play in dynamic sport tasks: investigating the essential information underlying skilled performance.

PubMed

Willams, A Mark; Hodges, Nicola J; North, Jamie S; Barton, Gabor

2006-01-01

The perceptual-cognitive information used to support pattern-recognition skill in soccer was examined. In experiment 1, skilled players were quicker and more accurate than less-skilled players at recognising familiar and unfamiliar soccer action sequences presented on film. In experiment 2, these action sequences were converted into point-light displays, with superficial display features removed and the positions of players and the relational information between them made more salient. Skilled players were more accurate than less-skilled players in recognising sequences presented in point-light form, implying that each pattern of play can be defined by the unique relations between players. In experiment 3, various offensive and defensive players were occluded for the duration of each trial in an attempt to identify the most important sources of information underpinning successful performance. A decrease in response accuracy was observed under occluded compared with non-occluded conditions and the expertise effect was no longer observed. The relational information between certain key players, team-mates and their defensive counterparts may provide the essential information for effective pattern-recognition skill in soccer. Structural feature analysis, temporal phase relations, and knowledge-based information are effectively integrated to facilitate pattern recognition in dynamic sport tasks.

Effects of age and hearing loss on recognition of unaccented and accented multisyllabic words.

PubMed

Gordon-Salant, Sandra; Yeni-Komshian, Grace H; Fitzgibbons, Peter J; Cohen, Julie I

2015-02-01

The effects of age and hearing loss on recognition of unaccented and accented words of varying syllable length were investigated. It was hypothesized that with increments in length of syllables, there would be atypical alterations in syllable stress in accented compared to native English, and that these altered stress patterns would be sensitive to auditory temporal processing deficits with aging. Sets of one-, two-, three-, and four-syllable words with the same initial syllable were recorded by one native English and two Spanish-accented talkers. Lists of these words were presented in isolation and in sentence contexts to younger and older normal-hearing listeners and to older hearing-impaired listeners. Hearing loss effects were apparent for unaccented and accented monosyllabic words, whereas age effects were observed for recognition of accented multisyllabic words, consistent with the notion that altered syllable stress patterns with accent are sensitive for revealing effects of age. Older listeners also exhibited lower recognition scores for moderately accented words in sentence contexts than in isolation, suggesting that the added demands on working memory for words in sentence contexts impact recognition of accented speech. The general pattern of results suggests that hearing loss, age, and cognitive factors limit the ability to recognize Spanish-accented speech.

Effects of age and hearing loss on recognition of unaccented and accented multisyllabic words

PubMed Central

Gordon-Salant, Sandra; Yeni-Komshian, Grace H.; Fitzgibbons, Peter J.; Cohen, Julie I.

2015-01-01

The effects of age and hearing loss on recognition of unaccented and accented words of varying syllable length were investigated. It was hypothesized that with increments in length of syllables, there would be atypical alterations in syllable stress in accented compared to native English, and that these altered stress patterns would be sensitive to auditory temporal processing deficits with aging. Sets of one-, two-, three-, and four-syllable words with the same initial syllable were recorded by one native English and two Spanish-accented talkers. Lists of these words were presented in isolation and in sentence contexts to younger and older normal-hearing listeners and to older hearing-impaired listeners. Hearing loss effects were apparent for unaccented and accented monosyllabic words, whereas age effects were observed for recognition of accented multisyllabic words, consistent with the notion that altered syllable stress patterns with accent are sensitive for revealing effects of age. Older listeners also exhibited lower recognition scores for moderately accented words in sentence contexts than in isolation, suggesting that the added demands on working memory for words in sentence contexts impact recognition of accented speech. The general pattern of results suggests that hearing loss, age, and cognitive factors limit the ability to recognize Spanish-accented speech. PMID:25698021

What can neuromorphic event-driven precise timing add to spike-based pattern recognition?

PubMed

Akolkar, Himanshu; Meyer, Cedric; Clady, Zavier; Marre, Olivier; Bartolozzi, Chiara; Panzeri, Stefano; Benosman, Ryad

2015-03-01

This letter introduces a study to precisely measure what an increase in spike timing precision can add to spike-driven pattern recognition algorithms. The concept of generating spikes from images by converting gray levels into spike timings is currently at the basis of almost every spike-based modeling of biological visual systems. The use of images naturally leads to generating incorrect artificial and redundant spike timings and, more important, also contradicts biological findings indicating that visual processing is massively parallel, asynchronous with high temporal resolution. A new concept for acquiring visual information through pixel-individual asynchronous level-crossing sampling has been proposed in a recent generation of asynchronous neuromorphic visual sensors. Unlike conventional cameras, these sensors acquire data not at fixed points in time for the entire array but at fixed amplitude changes of their input, resulting optimally sparse in space and time-pixel individually and precisely timed only if new, (previously unknown) information is available (event based). This letter uses the high temporal resolution spiking output of neuromorphic event-based visual sensors to show that lowering time precision degrades performance on several recognition tasks specifically when reaching the conventional range of machine vision acquisition frequencies (30-60 Hz). The use of information theory to characterize separability between classes for each temporal resolution shows that high temporal acquisition provides up to 70% more information that conventional spikes generated from frame-based acquisition as used in standard artificial vision, thus drastically increasing the separability between classes of objects. Experiments on real data show that the amount of information loss is correlated with temporal precision. Our information-theoretic study highlights the potentials of neuromorphic asynchronous visual sensors for both practical applications and theoretical investigations. Moreover, it suggests that representing visual information as a precise sequence of spike times as reported in the retina offers considerable advantages for neuro-inspired visual computations.

Dysfunctional role of parietal lobe during self-face recognition in schizophrenia.

PubMed

Yun, Je-Yeon; Hur, Ji-Won; Jung, Wi Hoon; Jang, Joon Hwan; Youn, Tak; Kang, Do-Hyung; Park, Sohee; Kwon, Jun Soo

2014-01-01

Anomalous sense of self is central to schizophrenia yet difficult to demonstrate empirically. The present study examined the effective neural network connectivity underlying self-face recognition in patients with schizophrenia (SZ) using [15O]H2O Positron Emission Tomography (PET) and Structural Equation Modeling. Eight SZ and eight age-matched healthy controls (CO) underwent six consecutive [15O]H2O PET scans during self-face (SF) and famous face (FF) recognition blocks, each of which was repeated three times. There were no behavioral performance differences between the SF and FF blocks in SZ. Moreover, voxel-based analyses of data from SZ revealed no significant differences in the regional cerebral blood flow (rCBF) levels between the SF and FF recognition conditions. Further effective connectivity analyses for SZ also showed a similar pattern of effective connectivity network across the SF and FF recognition. On the other hand, comparison of SF recognition effective connectivity network between SZ and CO demonstrated significantly attenuated effective connectivity strength not only between the right supramarginal gyrus and left inferior temporal gyrus, but also between the cuneus and right medial prefrontal cortex in SZ. These findings support a conceptual model that posits a causal relationship between disrupted self-other discrimination and attenuated effective connectivity among the right supramarginal gyrus, cuneus, and prefronto-temporal brain areas involved in the SF recognition network of SZ. © 2013.

Behavioral and Single-Neuron Sensitivity to Millisecond Variations in Temporally Patterned Communication Signals

PubMed Central

Baker, Christa A.; Ma, Lisa; Casareale, Chelsea R.

2016-01-01

In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8–12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. SIGNIFICANCE STATEMENT The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. PMID:27559179

Behavioral and Single-Neuron Sensitivity to Millisecond Variations in Temporally Patterned Communication Signals.

PubMed

Baker, Christa A; Ma, Lisa; Casareale, Chelsea R; Carlson, Bruce A

2016-08-24

In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8-12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. Copyright © 2016 the authors 0270-6474/16/368985-16$15.00/0.

Advanced brain aging: relationship with epidemiologic and genetic risk factors, and overlap with Alzheimer disease atrophy patterns.

PubMed

Habes, M; Janowitz, D; Erus, G; Toledo, J B; Resnick, S M; Doshi, J; Van der Auwera, S; Wittfeld, K; Hegenscheid, K; Hosten, N; Biffar, R; Homuth, G; Völzke, H; Grabe, H J; Hoffmann, W; Davatzikos, C

2016-04-05

We systematically compared structural imaging patterns of advanced brain aging (ABA) in the general-population, herein defined as significant deviation from typical BA to those found in Alzheimer disease (AD). The hypothesis that ABA would show different patterns of structural change compared with those found in AD was tested via advanced pattern analysis methods. In particular, magnetic resonance images of 2705 participants from the Study of Health in Pomerania (aged 20-90 years) were analyzed using an index that captures aging atrophy patterns (Spatial Pattern of Atrophy for Recognition of BA (SPARE-BA)), and an index previously shown to capture atrophy patterns found in clinical AD (Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease (SPARE-AD)). We studied the association between these indices and risk factors, including an AD polygenic risk score. Finally, we compared the ABA-associated atrophy with typical AD-like patterns. We observed that SPARE-BA had significant association with: smoking (P<0.05), anti-hypertensive (P<0.05), anti-diabetic drug use (men P<0.05, women P=0.06) and waist circumference for the male cohort (P<0.05), after adjusting for age. Subjects with ABA had spatially extensive gray matter loss in the frontal, parietal and temporal lobes (false-discovery-rate-corrected q<0.001). ABA patterns of atrophy were partially overlapping with, but notably deviating from those typically found in AD. Subjects with ABA had higher SPARE-AD values; largely due to the partial spatial overlap of associated patterns in temporal regions. The AD polygenic risk score was significantly associated with SPARE-AD but not with SPARE-BA. Our findings suggest that ABA is likely characterized by pathophysiologic mechanisms that are distinct from, or only partially overlapping with those of AD.

Improved perception of music with a harmonic based algorithm for cochlear implants.

PubMed

Li, Xing; Nie, Kaibao; Imennov, Nikita S; Rubinstein, Jay T; Atlas, Les E

2013-07-01

The lack of fine structure information in conventional cochlear implant (CI) encoding strategies presumably contributes to the generally poor music perception with CIs. To improve CI users' music perception, a harmonic-single-sideband-encoder (HSSE) strategy was developed , which explicitly tracks the harmonics of a single musical source and transforms them into modulators conveying both amplitude and temporal fine structure cues to electrodes. To investigate its effectiveness, vocoder simulations of HSSE and the conventional continuous-interleaved-sampling (CIS) strategy were implemented. Using these vocoders, five normal-hearing subjects' melody and timbre recognition performance were evaluated: a significant benefit of HSSE to both melody (p < 0.002) and timbre (p < 0.026) recognition was found. Additionally, HSSE was acutely tested in eight CI subjects. On timbre recognition, a significant advantage of HSSE over the subjects' clinical strategy was demonstrated: the largest improvement was 35% and the mean 17% (p < 0.013). On melody recognition, two subjects showed 20% improvement with HSSE; however, the mean improvement of 7% across subjects was not significant (p > 0.090). To quantify the temporal cues delivered to the auditory nerve, the neural spike patterns evoked by HSSE and CIS for one melody stimulus were simulated using an auditory nerve model. Quantitative analysis demonstrated that HSSE can convey temporal pitch cues better than CIS. The results suggest that HSSE is a promising strategy to enhance music perception with CIs.

Temporal and speech processing skills in normal hearing individuals exposed to occupational noise.

PubMed

Kumar, U Ajith; Ameenudin, Syed; Sangamanatha, A V

2012-01-01

Prolonged exposure to high levels of occupational noise can cause damage to hair cells in the cochlea and result in permanent noise-induced cochlear hearing loss. Consequences of cochlear hearing loss on speech perception and psychophysical abilities have been well documented. Primary goal of this research was to explore temporal processing and speech perception Skills in individuals who are exposed to occupational noise of more than 80 dBA and not yet incurred clinically significant threshold shifts. Contribution of temporal processing skills to speech perception in adverse listening situation was also evaluated. A total of 118 participants took part in this research. Participants comprised three groups of train drivers in the age range of 30-40 (n= 13), 41 50 ( = 13), 41-50 (n = 9), and 51-60 (n = 6) years and their non-noise-exposed counterparts (n = 30 in each age group). Participants of all the groups including the train drivers had hearing sensitivity within 25 dB HL in the octave frequencies between 250 and 8 kHz. Temporal processing was evaluated using gap detection, modulation detection, and duration pattern tests. Speech recognition was tested in presence multi-talker babble at -5dB SNR. Differences between experimental and control groups were analyzed using ANOVA and independent sample t-tests. Results showed a trend of reduced temporal processing skills in individuals with noise exposure. These deficits were observed despite normal peripheral hearing sensitivity. Speech recognition scores in the presence of noise were also significantly poor in noise-exposed group. Furthermore, poor temporal processing skills partially accounted for the speech recognition difficulties exhibited by the noise-exposed individuals. These results suggest that noise can cause significant distortions in the processing of suprathreshold temporal cues which may add to difficulties in hearing in adverse listening conditions.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

Neural correlates of auditory recognition memory in the primate dorsal temporal pole

PubMed Central

Ng, Chi-Wing; Plakke, Bethany

2013-01-01

Temporal pole (TP) cortex is associated with higher-order sensory perception and/or recognition memory, as human patients with damage in this region show impaired performance during some tasks requiring recognition memory (Olson et al. 2007). The underlying mechanisms of TP processing are largely based on examination of the visual nervous system in humans and monkeys, while little is known about neuronal activity patterns in the auditory portion of this region, dorsal TP (dTP; Poremba et al. 2003). The present study examines single-unit activity of dTP in rhesus monkeys performing a delayed matching-to-sample task utilizing auditory stimuli, wherein two sounds are determined to be the same or different. Neurons of dTP encode several task-relevant events during the delayed matching-to-sample task, and encoding of auditory cues in this region is associated with accurate recognition performance. Population activity in dTP shows a match suppression mechanism to identical, repeated sound stimuli similar to that observed in the visual object identification pathway located ventral to dTP (Desimone 1996; Nakamura and Kubota 1996). However, in contrast to sustained visual delay-related activity in nearby analogous regions, auditory delay-related activity in dTP is transient and limited. Neurons in dTP respond selectively to different sound stimuli and often change their sound response preferences between experimental contexts. Current findings suggest a significant role for dTP in auditory recognition memory similar in many respects to the visual nervous system, while delay memory firing patterns are not prominent, which may relate to monkeys' shorter forgetting thresholds for auditory vs. visual objects. PMID:24198324

Time course of brain activation elicited by basic emotions.

PubMed

Hot, Pascal; Sequeira, Henrique

2013-11-13

Whereas facial emotion recognition protocols have shown that each discrete emotion has a specific time course of brain activation, there is no electrophysiological evidence to support these findings for emotional induction by complex pictures. Our objective was to specify the differences between the time courses of brain activation elicited by feelings of happiness and, with unpleasant pictures, by feelings of disgust and sadness. We compared event-related potentials (ERPs) elicited by the watching of high-arousing pictures from the International Affective Picture System, selected to induce specific emotions. In addition to a classical arousal effect on late positive components, we found specific ERP patterns for each emotion in early temporal windows (<200 ms). Disgust was the first emotion to be associated with different brain processing after 140 ms, whereas happiness and sadness differed in ERPs elicited at the frontal and central sites after 160 ms. Our findings highlight the limits of the classical averaging of ERPs elicited by different emotions inside the same valence and suggest that each emotion could elicit a specific temporal pattern of brain activation, similar to those observed with emotional face recognition.

Studies in automatic speech recognition and its application in aerospace

NASA Astrophysics Data System (ADS)

Taylor, Michael Robinson

Human communication is characterized in terms of the spectral and temporal dimensions of speech waveforms. Electronic speech recognition strategies based on Dynamic Time Warping and Markov Model algorithms are described and typical digit recognition error rates are tabulated. The application of Direct Voice Input (DVI) as an interface between man and machine is explored within the context of civil and military aerospace programmes. Sources of physical and emotional stress affecting speech production within military high performance aircraft are identified. Experimental results are reported which quantify fundamental frequency and coarse temporal dimensions of male speech as a function of the vibration, linear acceleration and noise levels typical of aerospace environments; preliminary indications of acoustic phonetic variability reported by other researchers are summarized. Connected whole-word pattern recognition error rates are presented for digits spoken under controlled Gz sinusoidal whole-body vibration. Correlations are made between significant increases in recognition error rate and resonance of the abdomen-thorax and head subsystems of the body. The phenomenon of vibrato style speech produced under low frequency whole-body Gz vibration is also examined. Interactive DVI system architectures and avionic data bus integration concepts are outlined together with design procedures for the efficient development of pilot-vehicle command and control protocols.

The effects of age on the neural correlates of episodic encoding.

PubMed

Grady, C L; McIntosh, A R; Rajah, M N; Beig, S; Craik, F I

1999-12-01

Young and old adults underwent positron emission tomographic scans while encoding pictures of objects and words using three encoding strategies: deep processing (a semantic living/nonliving judgement), shallow processing (size judgement) and intentional learning. Picture memory exceeded word memory in both young and old groups, and there was an age-related decrement only in word recognition. During the encoding tasks three brain activity patterns were found that differentiated stimulus type and the different encoding strategies. The stimulus-specific pattern was characterized by greater activity in extrastriate and medial temporal cortices during picture encoding, and greater activity in left prefrontal and temporal cortices during encoding of words. The older adults showed this pattern to a significantly lesser degree. A pattern distinguishing deep processing from intentional learning of words and pictures was identified, characterized mainly by differences in prefrontal cortex, and this pattern also was of significantly lesser magnitude in the old group. A final pattern identified areas with increased activity during deep processing and intentional learning of pictures, including left prefrontal and bilateral medial temporal regions. There was no group difference in this pattern. These results indicate age-related dysfunction in several encoding networks, with sparing of one specifically involved in more elaborate encoding of pictures. These age-related changes appear to affect verbal memory more than picture memory.

Pen-chant: Acoustic emissions of handwriting and drawing

NASA Astrophysics Data System (ADS)

Seniuk, Andrew G.

The sounds generated by a writing instrument ('pen-chant') provide a rich and underutilized source of information for pattern recognition. We examine the feasibility of recognition of handwritten cursive text, exclusively through an analysis of acoustic emissions. We design and implement a family of recognizers using a template matching approach, with templates and similarity measures derived variously from: smoothed amplitude signal with fixed resolution, discrete sequence of magnitudes obtained from peaks in the smoothed amplitude signal, and ordered tree obtained from a scale space signal representation. Test results are presented for recognition of isolated lowercase cursive characters and for whole words. We also present qualitative results for recognizing gestures such as circling, scratch-out, check-marks, and hatching. Our first set of results, using samples provided by the author, yield recognition rates of over 70% (alphabet) and 90% (26 words), with a confidence of +/-8%, based solely on acoustic emissions. Our second set of results uses data gathered from nine writers. These results demonstrate that acoustic emissions are a rich source of information, usable---on their own or in conjunction with image-based features---to solve pattern recognition problems. In future work, this approach can be applied to writer identification, handwriting and gesture-based computer input technology, emotion recognition, and temporal analysis of sketches.

Across-site patterns of modulation detection: Relation to speech recognitiona)

PubMed Central

Garadat, Soha N.; Zwolan, Teresa A.; Pfingst, Bryan E.

2012-01-01

The aim of this study was to identify across-site patterns of modulation detection thresholds (MDTs) in subjects with cochlear implants and to determine if removal of sites with the poorest MDTs from speech processor programs would result in improved speech recognition. Five hundred millisecond trains of symmetric-biphasic pulses were modulated sinusoidally at 10 Hz and presented at a rate of 900 pps using monopolar stimulation. Subjects were asked to discriminate a modulated pulse train from an unmodulated pulse train for all electrodes in quiet and in the presence of an interleaved unmodulated masker presented on the adjacent site. Across-site patterns of masked MDTs were then used to construct two 10-channel MAPs such that one MAP consisted of sites with the best masked MDTs and the other MAP consisted of sites with the worst masked MDTs. Subjects’ speech recognition skills were compared when they used these two different MAPs. Results showed that MDTs were variable across sites and were elevated in the presence of a masker by various amounts across sites. Better speech recognition was observed when the processor MAP consisted of sites with best masked MDTs, suggesting that temporal modulation sensitivity has important contributions to speech recognition with a cochlear implant. PMID:22559376

Research of Daily Conversation Transmitting System Based on Mouth Part Pattern Recognition

NASA Astrophysics Data System (ADS)

Watanabe, Mutsumi; Nishi, Natsuko

The authors are developing a vision-based intension transfer technique by recognizing user’s face expressions and movements, to help free and convenient communications with aged or disabled persons who find difficulties in talking, discriminating small character prints and operating keyboards by hands and fingers. In this paper we report a prototype system, where layered daily conversations are successively selected by recognizing the transition in shape of user’s mouth parts using camera image sequences settled in front of the user. Four mouth part patterns are used in the system. A method that automatically recognizes these patterns by analyzing the intensity histogram data around the mouth region is newly developed. The confirmation of a selection on the way is executed by detecting the open and shut movements of mouth through the temporal change in intensity histogram data. The method has been installed in a desktop PC by VC++ programs. Experimental results of mouth shape pattern recognition by twenty-five persons have shown the effectiveness of the method.

Familiarity and Recollection Produce Distinct Eye Movement, Pupil and Medial Temporal Lobe Responses when Memory Strength Is Matched

ERIC Educational Resources Information Center

Kafkas, Alexandros; Montaldi, Daniela

2012-01-01

Two experiments explored eye measures (fixations and pupil response patterns) and brain responses (BOLD) accompanying the recognition of visual object stimuli based on familiarity and recollection. In both experiments, the use of a modified remember/know procedure led to high confidence and matched accuracy levels characterising strong familiarity…

Machine processing for remotely acquired data. [using multivariate statistical analysis

NASA Technical Reports Server (NTRS)

Landgrebe, D. A.

1974-01-01

This paper is a general discussion of earth resources information systems which utilize airborne and spaceborne sensors. It points out that information may be derived by sensing and analyzing the spectral, spatial and temporal variations of electromagnetic fields emanating from the earth surface. After giving an overview system organization, the two broad categories of system types are discussed. These are systems in which high quality imagery is essential and those more numerically oriented. Sensors are also discussed with this categorization of systems in mind. The multispectral approach and pattern recognition are described as an example data analysis procedure for numerically-oriented systems. The steps necessary in using a pattern recognition scheme are described and illustrated with data obtained from aircraft and the Earth Resources Technology Satellite (ERTS-1).

A shared representation of order between encoding and recognition in visual short-term memory.

PubMed

Kalm, Kristjan; Norris, Dennis

2017-07-15

Many complex tasks require people to bind individual events into a sequence that can be held in short term memory (STM). For this purpose information about the order of the individual events in the sequence needs to be maintained in an active and accessible form in STM over a period of few seconds. Here we investigated how the temporal order information is shared between the presentation and response phases of an STM task. We trained a classification algorithm on the fMRI activity patterns from the presentation phase of the STM task to predict the order of the items during the subsequent recognition phase. While voxels in a number of brain regions represented positional information during either presentation and recognition phases, only voxels in the lateral prefrontal cortex (PFC) and the anterior temporal lobe (ATL) represented position consistently across task phases. A shared positional code in the ATL might reflect verbal recoding of visual sequences to facilitate the maintenance of order information over several seconds. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Voice Recognition in Face-Blind Patients

PubMed Central

Liu, Ran R.; Pancaroglu, Raika; Hills, Charlotte S.; Duchaine, Brad; Barton, Jason J. S.

2016-01-01

Right or bilateral anterior temporal damage can impair face recognition, but whether this is an associative variant of prosopagnosia or part of a multimodal disorder of person recognition is an unsettled question, with implications for cognitive and neuroanatomic models of person recognition. We assessed voice perception and short-term recognition of recently heard voices in 10 subjects with impaired face recognition acquired after cerebral lesions. All 4 subjects with apperceptive prosopagnosia due to lesions limited to fusiform cortex had intact voice discrimination and recognition. One subject with bilateral fusiform and anterior temporal lesions had a combined apperceptive prosopagnosia and apperceptive phonagnosia, the first such described case. Deficits indicating a multimodal syndrome of person recognition were found only in 2 subjects with bilateral anterior temporal lesions. All 3 subjects with right anterior temporal lesions had normal voice perception and recognition, 2 of whom performed normally on perceptual discrimination of faces. This confirms that such lesions can cause a modality-specific associative prosopagnosia. PMID:25349193

Interrupted Monosyllabic Words: The Effects of Ten Interruption Locations on Recognition Performance by Older Listeners with Sensorineural Hearing Loss.

PubMed

Wilson, Richard H; Sharrett, Kadie C

2017-01-01

Two previous experiments from our laboratory with 70 interrupted monosyllabic words demonstrated that recognition performance was influenced by the temporal location of the interruption pattern. The interruption pattern (10 interruptions/sec, 50% duty cycle) was always the same and referenced word onset; the only difference between the patterns was the temporal location of the on- and off-segments of the interruption cycle. In the first study, both young and older listeners obtained better recognition performances when the initial on-segment coincided with word onset than when the initial on-segment was delayed by 50 msec. The second experiment with 24 young listeners detailed recognition performance as the interruption pattern was incremented in 10-msec steps through the 0- to 90-msec onset range. Across the onset conditions, 95% of the functions were either flat or U-shaped. To define the effects that interruption pattern locations had on word recognition by older listeners with sensorineural hearing loss as the interruption pattern incremented, re: word onset, from 0 to 90 msec in 10-msec steps. A repeated-measures design with ten interruption patterns (onset conditions) and one uninterruption condition. Twenty-four older males (mean = 69.6 yr) with sensorineural hearing loss participated in two 1-hour sessions. The three-frequency pure-tone average was 24.0 dB HL and word recognition was ≥80% correct. Seventy consonant-vowel nucleus-consonant words formed the corpus of materials with 25 additional words used for practice. For each participant, the 700 interrupted stimuli (70 words by 10 onset conditions), the 70 words uninterrupted, and two practice lists each were randomized and recorded on compact disc in 33 tracks of 25 words each. The data were analyzed at the participant and word levels and compared to the results obtained earlier on 24 young listeners with normal hearing. The mean recognition performance on the 70 words uninterrupted was 91.0% with an overall mean performance on the ten interruption conditions of 63.2% (range: 57.9-69.3%), compared to 80.4% (range: 73.0-87.7%) obtained earlier on the young adults. The best performances were at the extremes of the onset conditions. Standard deviations ranged from 22.1% to 28.1% (24 participants) and from 9.2% to 12.8% (70 words). An arithmetic algorithm categorized the shapes of the psychometric functions across the ten onset conditions. With the older participants in the current study, 40% of the functions were flat, 41.4% were U-shaped, and 18.6% were inverted U-shaped, which compared favorably to the function shapes by the young listeners in the earlier study of 50.0%, 41.4%, and 8.6%, respectively. There were two words on which the older listeners had 40% better performances. Collectively, the data are orderly, but at the individual word or participant level, the data are somewhat volatile, which may reflect auditory processing differences between the participant groups. The diversity of recognition performances by the older listeners on the ten interruption conditions with each of the 70 words supports the notion that the term hearing loss is inclusive of processes well beyond the filtering produced by end-organ sensitivity deficits. American Academy of Audiology

Altered topology of neural circuits in congenital prosopagnosia.

PubMed

Rosenthal, Gideon; Tanzer, Michal; Simony, Erez; Hasson, Uri; Behrmann, Marlene; Avidan, Galia

2017-08-21

Using a novel, fMRI-based inter-subject functional correlation (ISFC) approach, which isolates stimulus-locked inter-regional correlation patterns, we compared the cortical topology of the neural circuit for face processing in participants with an impairment in face recognition, congenital prosopagnosia (CP), and matched controls. Whereas the anterior temporal lobe served as the major network hub for face processing in controls, this was not the case for the CPs. Instead, this group evinced hyper-connectivity in posterior regions of the visual cortex, mostly associated with the lateral occipital and the inferior temporal cortices. Moreover, the extent of this hyper-connectivity was correlated with the face recognition deficit. These results offer new insights into the perturbed cortical topology in CP, which may serve as the underlying neural basis of the behavioral deficits typical of this disorder. The approach adopted here has the potential to uncover altered topologies in other neurodevelopmental disorders, as well.

Evaluation of Anomaly Detection Method Based on Pattern Recognition

NASA Astrophysics Data System (ADS)

Fontugne, Romain; Himura, Yosuke; Fukuda, Kensuke

The number of threats on the Internet is rapidly increasing, and anomaly detection has become of increasing importance. High-speed backbone traffic is particularly degraded, but their analysis is a complicated task due to the amount of data, the lack of payload data, the asymmetric routing and the use of sampling techniques. Most anomaly detection schemes focus on the statistical properties of network traffic and highlight anomalous traffic through their singularities. In this paper, we concentrate on unusual traffic distributions, which are easily identifiable in temporal-spatial space (e.g., time/address or port). We present an anomaly detection method that uses a pattern recognition technique to identify anomalies in pictures representing traffic. The main advantage of this method is its ability to detect attacks involving mice flows. We evaluate the parameter set and the effectiveness of this approach by analyzing six years of Internet traffic collected from a trans-Pacific link. We show several examples of detected anomalies and compare our results with those of two other methods. The comparison indicates that the only anomalies detected by the pattern-recognition-based method are mainly malicious traffic with a few packets.

Role of fusiform and anterior temporal cortical areas in facial recognition.

PubMed

Nasr, Shahin; Tootell, Roger B H

2012-11-15

Recent fMRI studies suggest that cortical face processing extends well beyond the fusiform face area (FFA), including unspecified portions of the anterior temporal lobe. However, the exact location of such anterior temporal region(s), and their role during active face recognition, remain unclear. Here we demonstrate that (in addition to FFA) a small bilateral site in the anterior tip of the collateral sulcus ('AT'; the anterior temporal face patch) is selectively activated during recognition of faces but not houses (a non-face object). In contrast to the psychophysical prediction that inverted and contrast reversed faces are processed like other non-face objects, both FFA and AT (but not other visual areas) were also activated during recognition of inverted and contrast reversed faces. However, response accuracy was better correlated to recognition-driven activity in AT, compared to FFA. These data support a segregated, hierarchical model of face recognition processing, extending to the anterior temporal cortex. Copyright © 2012 Elsevier Inc. All rights reserved.

Role of Fusiform and Anterior Temporal Cortical Areas in Facial Recognition

PubMed Central

Nasr, Shahin; Tootell, Roger BH

2012-01-01

Recent FMRI studies suggest that cortical face processing extends well beyond the fusiform face area (FFA), including unspecified portions of the anterior temporal lobe. However, the exact location of such anterior temporal region(s), and their role during active face recognition, remain unclear. Here we demonstrate that (in addition to FFA) a small bilateral site in the anterior tip of the collateral sulcus (‘AT’; the anterior temporal face patch) is selectively activated during recognition of faces but not houses (a non-face object). In contrast to the psychophysical prediction that inverted and contrast reversed faces are processed like other non-face objects, both FFA and AT (but not other visual areas) were also activated during recognition of inverted and contrast reversed faces. However, response accuracy was better correlated to recognition-driven activity in AT, compared to FFA. These data support a segregated, hierarchical model of face recognition processing, extending to the anterior temporal cortex. PMID:23034518

Tracking down the path of memory: eye scanpaths facilitate retrieval of visuospatial information.

PubMed

Bochynska, Agata; Laeng, Bruno

2015-09-01

Recent research points to a crucial role of eye fixations on the same spatial locations where an item appeared when learned, for the successful retrieval of stored information (e.g., Laeng et al. in Cognition 131:263-283, 2014. doi: 10.1016/j.cognition.2014.01.003 ). However, evidence about whether the specific temporal sequence (i.e., scanpath) of these eye fixations is also relevant for the accuracy of memory remains unclear. In the current study, eye fixations were recorded while looking at a checkerboard-like pattern. In a recognition session (48 h later), animations were shown where each square that formed the pattern was presented one by one, either according to the same, idiosyncratic, temporal sequence in which they were originally viewed by each participant or in a shuffled sequence although the squares were, in both conditions, always in their correct positions. Afterward, participants judged whether they had seen the same pattern before or not. Showing the elements serially according to the original scanpath's sequence yielded a significantly better recognition performance than the shuffled condition. In a forced fixation condition, where the gaze was maintained on the center of the screen, the advantage of memory accuracy for same versus shuffled scanpaths disappeared. Concluding, gaze scanpaths (i.e., the order of fixations and not simply their positions) are functional to visual memory and physical reenacting of the original, embodied, perception can facilitate retrieval.

Quantitative estimation of time-variable earthquake hazard by using fuzzy set theory

NASA Astrophysics Data System (ADS)

Deyi, Feng; Ichikawa, M.

1989-11-01

In this paper, the various methods of fuzzy set theory, called fuzzy mathematics, have been applied to the quantitative estimation of the time-variable earthquake hazard. The results obtained consist of the following. (1) Quantitative estimation of the earthquake hazard on the basis of seismicity data. By using some methods of fuzzy mathematics, seismicity patterns before large earthquakes can be studied more clearly and more quantitatively, highly active periods in a given region and quiet periods of seismic activity before large earthquakes can be recognized, similarities in temporal variation of seismic activity and seismic gaps can be examined and, on the other hand, the time-variable earthquake hazard can be assessed directly on the basis of a series of statistical indices of seismicity. Two methods of fuzzy clustering analysis, the method of fuzzy similarity, and the direct method of fuzzy pattern recognition, have been studied is particular. One method of fuzzy clustering analysis is based on fuzzy netting, and another is based on the fuzzy equivalent relation. (2) Quantitative estimation of the earthquake hazard on the basis of observational data for different precursors. The direct method of fuzzy pattern recognition has been applied to research on earthquake precursors of different kinds. On the basis of the temporal and spatial characteristics of recognized precursors, earthquake hazards in different terms can be estimated. This paper mainly deals with medium-short-term precursors observed in Japan and China.

Correction of Microplate Data from High-Throughput Screening.

PubMed

Wang, Yuhong; Huang, Ruili

2016-01-01

High-throughput screening (HTS) makes it possible to collect cellular response data from a large number of cell lines and small molecules in a timely and cost-effective manner. The errors and noises in the microplate-formatted data from HTS have unique characteristics, and they can be generally grouped into three categories: run-wise (temporal, multiple plates), plate-wise (background pattern, single plate), and well-wise (single well). In this chapter, we describe a systematic solution for identifying and correcting such errors and noises, mainly basing on pattern recognition and digital signal processing technologies.

Maintenance of youth-like processing protects against false memory in later adulthood.

PubMed

Fandakova, Yana; Lindenberger, Ulman; Shing, Yee Lee

2015-02-01

Normal cognitive aging compromises the ability to form and retrieve associations among features of a memory episode. One indicator of this age-related deficit is older adults' difficulty in detecting and correctly rejecting new associations of familiar items. Comparing 28 younger and 30 older adults on a continuous recognition task with word pairs, we found that older adults whose activation patterns deviate less from the average pattern of younger adults while detecting repaired associations show the following: (1) higher overall memory and fewer false recognitions; (2) stronger functional connectivity of prefrontal regions with middle temporal and parahippocampal gyrus; and (3) higher recall and strategic categorical clustering in an independently assessed free recall task. Deviations from the average young-adult network reflected underactivation of frontoparietal regions instead of overactivation of regions not activated by younger adults. We conclude that maintenance of youth-like task-relevant activation patterns is critical for preserving memory functions in later adulthood. Copyright © 2015 Elsevier Inc. All rights reserved.

Spatio-Temporal Pattern Recognition Using Hidden Markov Models

DTIC Science & Technology

1994-06-01

Jersey, 1982. 5. H. B . Barlow and W. R. Levick . The mechanism of directionally selective units in rabbit’s retina. Journal of Physiology (London), 178:477...108 A.2.2 Re-estimate of .. .. ................... .110 A.2.3 Re-estimate of B ...... ................... 110 A.3 Logarithmic Form of the Baum-Welch...19 a0 Transition Probability from State i to State j ................ 19 B Observation Probability Matrix

Impaired extraction of speech rhythm from temporal modulation patterns in speech in developmental dyslexia

PubMed Central

Leong, Victoria; Goswami, Usha

2014-01-01

Dyslexia is associated with impaired neural representation of the sound structure of words (phonology). The “phonological deficit” in dyslexia may arise in part from impaired speech rhythm perception, thought to depend on neural oscillatory phase-locking to slow amplitude modulation (AM) patterns in the speech envelope. Speech contains AM patterns at multiple temporal rates, and these different AM rates are associated with phonological units of different grain sizes, e.g., related to stress, syllables or phonemes. Here, we assess the ability of adults with dyslexia to use speech AMs to identify rhythm patterns (RPs). We study 3 important temporal rates: “Stress” (~2 Hz), “Syllable” (~4 Hz) and “Sub-beat” (reduced syllables, ~14 Hz). 21 dyslexics and 21 controls listened to nursery rhyme sentences that had been tone-vocoded using either single AM rates from the speech envelope (Stress only, Syllable only, Sub-beat only) or pairs of AM rates (Stress + Syllable, Syllable + Sub-beat). They were asked to use the acoustic rhythm of the stimulus to identity the original nursery rhyme sentence. The data showed that dyslexics were significantly poorer at detecting rhythm compared to controls when they had to utilize multi-rate temporal information from pairs of AMs (Stress + Syllable or Syllable + Sub-beat). These data suggest that dyslexia is associated with a reduced ability to utilize AMs <20 Hz for rhythm recognition. This perceptual deficit in utilizing AM patterns in speech could be underpinned by less efficient neuronal phase alignment and cross-frequency neuronal oscillatory synchronization in dyslexia. Dyslexics' perceptual difficulties in capturing the full spectro-temporal complexity of speech over multiple timescales could contribute to the development of impaired phonological representations for words, the cognitive hallmark of dyslexia across languages. PMID:24605099

Temporal association tracts and the breakdown of episodic memory in mild cognitive impairment

PubMed Central

Metzler-Baddeley, Claudia; Hunt, Sarah; Jones, Derek K.; Leemans, Alexander; Aggleton, John P.

2012-01-01

Objective: To examine the pattern of association between microstructure of temporal lobe connections and the breakdown of episodic memory that is a core feature of mild cognitive impairment (MCI). Methods: Twenty-five individuals with MCI and 20 matched controls underwent diffusion MRI and cognitive assessment. Three temporal pathways were reconstructed by tractography: fornix, parahippocampal cingulum (PHC), and uncinate fasciculus. Tissue volume fraction—a tract-specific measure of atrophy—and microstructural measures were derived for each tract. To test specificity of associations, a comparison tract (corticospinal tract) and control cognitive domains were also examined. Results: In MCI, tissue volume fraction was reduced in the fornix. Axial and radial diffusivity were increased in uncinate and PHC implying more subtle microstructural change. In controls, tissue volume fraction in the fornix was the predominant correlate of free recall. In contrast, in MCI, the strongest relationship was with left PHC. Microstructure of uncinate and PHC also correlated with recognition memory, and recognition confidence, in MCI. Conclusions: Episodic memory in MCI is related to the structure of multiple temporal association pathways. These associations are not confined to the fornix, as they are in healthy young and older adults. In MCI, because of a compromised fornix, alternative pathways may contribute disproportionally to episodic memory performance. PMID:23175726

[The role of temporal fine structure in tone recognition and music perception].

PubMed

Zhou, Q; Gu, X; Liu, B

2017-11-07

The sound signal can be decomposed into temporal envelope and temporal fine structure information. The temporal envelope information is crucial for speech perception in quiet environment, and the temporal fine structure information plays an important role in speech perception in noise, Mandarin tone recognition and music perception, especially the pitch and melody perception.

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise.

PubMed

Shen, Jing; Souza, Pamela E

2017-09-18

This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for speech recognition in noise. Last, we explored the individual factors that predict the amount of dynamic-pitch benefit for speech recognition in noise. Younger listeners with normal hearing and older listeners with varying levels of hearing sensitivity participated in the study, in which speech reception thresholds were measured with sentences in nonspeech noise. The younger listeners benefited more from dynamic pitch for speech recognition in temporally modulated noise than unmodulated noise. Older listeners were able to benefit from the dynamic-pitch cues but received less benefit from noise modulation than the younger listeners. For those older listeners with hearing loss, the amount of hearing loss strongly predicted the dynamic-pitch benefit for speech recognition in noise. Dynamic-pitch cues aid speech recognition in noise, particularly when noise has temporal modulation. Hearing loss negatively affects the dynamic-pitch benefit to older listeners with significant hearing loss.

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

PubMed Central

Souza, Pamela E.

2017-01-01

Purpose This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for speech recognition in noise. Last, we explored the individual factors that predict the amount of dynamic-pitch benefit for speech recognition in noise. Method Younger listeners with normal hearing and older listeners with varying levels of hearing sensitivity participated in the study, in which speech reception thresholds were measured with sentences in nonspeech noise. Results The younger listeners benefited more from dynamic pitch for speech recognition in temporally modulated noise than unmodulated noise. Older listeners were able to benefit from the dynamic-pitch cues but received less benefit from noise modulation than the younger listeners. For those older listeners with hearing loss, the amount of hearing loss strongly predicted the dynamic-pitch benefit for speech recognition in noise. Conclusions Dynamic-pitch cues aid speech recognition in noise, particularly when noise has temporal modulation. Hearing loss negatively affects the dynamic-pitch benefit to older listeners with significant hearing loss. PMID:28800370

Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem

PubMed Central

Liu, Xunying; Zhang, Chao; Woodland, Phil; Fonteneau, Elisabeth

2017-01-01

There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR) systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental ‘machine states’, generated as the ASR analysis progresses over time, to the incremental ‘brain states’, measured using combined electro- and magneto-encephalography (EMEG), generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain. PMID:28945744

Efficient Spatio-Temporal Local Binary Patterns for Spontaneous Facial Micro-Expression Recognition

PubMed Central

Wang, Yandan; See, John; Phan, Raphael C.-W.; Oh, Yee-Hui

2015-01-01

Micro-expression recognition is still in the preliminary stage, owing much to the numerous difficulties faced in the development of datasets. Since micro-expression is an important affective clue for clinical diagnosis and deceit analysis, much effort has gone into the creation of these datasets for research purposes. There are currently two publicly available spontaneous micro-expression datasets—SMIC and CASME II, both with baseline results released using the widely used dynamic texture descriptor LBP-TOP for feature extraction. Although LBP-TOP is popular and widely used, it is still not compact enough. In this paper, we draw further inspiration from the concept of LBP-TOP that considers three orthogonal planes by proposing two efficient approaches for feature extraction. The compact robust form described by the proposed LBP-Six Intersection Points (SIP) and a super-compact LBP-Three Mean Orthogonal Planes (MOP) not only preserves the essential patterns, but also reduces the redundancy that affects the discriminality of the encoded features. Through a comprehensive set of experiments, we demonstrate the strengths of our approaches in terms of recognition accuracy and efficiency. PMID:25993498

Age-related individual variability in memory performance is associated with amygdala-hippocampal circuit function and emotional pattern separation.

PubMed

Leal, Stephanie L; Noche, Jessica A; Murray, Elizabeth A; Yassa, Michael A

2017-01-01

While aging is generally associated with episodic memory decline, not all older adults exhibit memory loss. Furthermore, emotional memories are not subject to the same extent of forgetting and appear preserved in aging. We conducted high-resolution fMRI during a task involving pattern separation of emotional information in older adults with and without age-related memory impairment (characterized by performance on a word-list learning task: low performers: LP vs. high performers: HP). We found signals consistent with emotional pattern separation in hippocampal dentate (DG)/CA3 in HP but not in LP individuals, suggesting a deficit in emotional pattern separation. During false recognition, we found increased DG/CA3 activity in LP individuals, suggesting that hyperactivity may be associated with overgeneralization. We additionally observed a selective deficit in basolateral amygdala-lateral entorhinal cortex-DG/CA3 functional connectivity in LP individuals during pattern separation of negative information. During negative false recognition, LP individuals showed increased medial temporal lobe functional connectivity, consistent with overgeneralization. Overall, these results suggest a novel mechanistic account of individual differences in emotional memory alterations exhibited in aging. Copyright © 2016 Elsevier Inc. All rights reserved.

Age-related individual variability in memory performance is associated with amygdala-hippocampal circuit function and emotional pattern separation

PubMed Central

Leal, Stephanie L.; Noche, Jessica A.; Murray, Elizabeth A.; Yassa, Michael A.

2018-01-01

While aging is generally associated with episodic memory decline, not all older adults exhibit memory loss. Furthermore, emotional memories are not subject to the same extent of forgetting and appear preserved in aging. We conducted high-resolution fMRI during a task involving pattern separation of emotional information in older adults with and without age-related memory impairment (characterized by performance on a word-list learning task: low performers: LP vs. high performers: HP). We found signals consistent with emotional pattern separation in hippocampal dentate (DG)/CA3 in HP but not in LP individuals, suggesting a deficit in emotional pattern separation. During false recognition, we found increased DG/CA3 activity in LP individuals, suggesting that hyperactivity may be associated with overgeneralization. We additionally observed a selective deficit in basolateral amygdala—lateral entorhinal cortex—DG/CA3 functional connectivity in LP individuals during pattern separation of negative information. During negative false recognition, LP individuals showed increased medial temporal lobe functional connectivity, consistent with overgeneralization. Overall, these results suggest a novel mechanistic account of individual differences in emotional memory alterations exhibited in aging. PMID:27723500

Face shape and face identity processing in behavioral variant fronto-temporal dementia: A specific deficit for familiarity and name recognition of famous faces.

PubMed

De Winter, François-Laurent; Timmers, Dorien; de Gelder, Beatrice; Van Orshoven, Marc; Vieren, Marleen; Bouckaert, Miriam; Cypers, Gert; Caekebeke, Jo; Van de Vliet, Laura; Goffin, Karolien; Van Laere, Koen; Sunaert, Stefan; Vandenberghe, Rik; Vandenbulcke, Mathieu; Van den Stock, Jan

2016-01-01

Deficits in face processing have been described in the behavioral variant of fronto-temporal dementia (bvFTD), primarily regarding the recognition of facial expressions. Less is known about face shape and face identity processing. Here we used a hierarchical strategy targeting face shape and face identity recognition in bvFTD and matched healthy controls. Participants performed 3 psychophysical experiments targeting face shape detection (Experiment 1), unfamiliar face identity matching (Experiment 2), familiarity categorization and famous face-name matching (Experiment 3). The results revealed group differences only in Experiment 3, with a deficit in the bvFTD group for both familiarity categorization and famous face-name matching. Voxel-based morphometry regression analyses in the bvFTD group revealed an association between grey matter volume of the left ventral anterior temporal lobe and familiarity recognition, while face-name matching correlated with grey matter volume of the bilateral ventral anterior temporal lobes. Subsequently, we quantified familiarity-specific and name-specific recognition deficits as the sum of the celebrities of which respectively only the name or only the familiarity was accurately recognized. Both indices were associated with grey matter volume of the bilateral anterior temporal cortices. These findings extent previous results by documenting the involvement of the left anterior temporal lobe (ATL) in familiarity detection and the right ATL in name recognition deficits in fronto-temporal lobar degeneration.

Proteome and Secretome Analysis Reveals Differential Post-transcriptional Regulation of Toll-like Receptor Responses*

PubMed Central

Koppenol-Raab, Marijke; Sjoelund, Virginie; Manes, Nathan P.; Gottschalk, Rachel A.; Dutta, Bhaskar; Benet, Zachary L.; Fraser, Iain D. C.

2017-01-01

The innate immune system is the organism's first line of defense against pathogens. Pattern recognition receptors (PRRs) are responsible for sensing the presence of pathogen-associated molecules. The prototypic PRRs, the membrane-bound receptors of the Toll-like receptor (TLR) family, recognize pathogen-associated molecular patterns (PAMPs) and initiate an innate immune response through signaling pathways that depend on the adaptor molecules MyD88 and TRIF. Deciphering the differences in the complex signaling events that lead to pathogen recognition and initiation of the correct response remains challenging. Here we report the discovery of temporal changes in the protein signaling components involved in innate immunity. Using an integrated strategy combining unbiased proteomics, transcriptomics and macrophage stimulations with three different PAMPs, we identified differences in signaling between individual TLRs and revealed specifics of pathway regulation at the protein level. PMID:28235783

Retrograde amnesia in patients with diencephalic, temporal lobe or frontal lesions.

PubMed

Kopelman, M D; Stanhope, N; Kingsley, D

1999-07-01

Patients with focal diencephalic, temporal lobe, or frontal lobe lesions were examined on various measures of remote memory. Korsakoff patients showed a severe impairment with a characteristic 'temporal gradient', whereas two patients with focal diencephalic damage (and anterograde amnesia) were virtually unimpaired on remote memory measures. Patients with frontal lobe pathology were severely impaired in the recall of autobiographical incidents and famous news events. Patients with temporal lobe pathology showed severe impairment but a relatively 'flat' temporal gradient, largely attributable to herpes encephalitis patients. From recognition and cued recall tasks, it is argued that there is an important retrieval component to the remote memory deficit across all the lesion groups. In general, the pattern of performance by the frontal lobe and temporal lobe groups was closely similar, and there was no evidence of any major access/storage difference between them. However, laterality comparisons across these groups indicated that the right temporal and frontal lobe regions may make a greater contribution to the retrieval of past episodic (incident and event) memories, whereas the left temporal region is more closely involved in the lexical-semantic labelling of remote memories.

Statistical methods for investigating quiescence and other temporal seismicity patterns

USGS Publications Warehouse

Matthews, M.V.; Reasenberg, P.A.

1988-01-01

We propose a statistical model and a technique for objective recognition of one of the most commonly cited seismicity patterns:microearthquake quiescence. We use a Poisson process model for seismicity and define a process with quiescence as one with a particular type of piece-wise constant intensity function. From this model, we derive a statistic for testing stationarity against a 'quiescence' alternative. The large-sample null distribution of this statistic is approximated from simulated distributions of appropriate functionals applied to Brownian bridge processes. We point out the restrictiveness of the particular model we propose and of the quiescence idea in general. The fact that there are many point processes which have neither constant nor quiescent rate functions underscores the need to test for and describe nonuniformity thoroughly. We advocate the use of the quiescence test in conjunction with various other tests for nonuniformity and with graphical methods such as density estimation. ideally these methods may promote accurate description of temporal seismicity distributions and useful characterizations of interesting patterns. ?? 1988 Birkha??user Verlag.

Good, bad and ugly word stress--fMRI evidence for foot structure driven processing of prosodic violations.

PubMed

Domahs, Ulrike; Klein, Elise; Huber, Walter; Domahs, Frank

2013-06-01

Using a stress violation paradigm, we investigated whether metrical feet constrain the way prosodic patterns are processed and evaluated. Processing of correctly versus incorrectly stressed words was associated with activation in left posterior angular and retrosplenial cortex, indicating the recognition of an expected and familiar pattern, whereas the inverse contrast yielded enhanced bilateral activation in the superior temporal gyrus, reflecting higher costs in auditory (re-)analysis. More fine-grained analyses of severe versus mild stress violations revealed activations of the left superior temporal and left anterior angular gyrus whereas the opposite contrast led to frontal activations including Broca's area and its right-hemisphere homologue, suggesting that detection of mild violations lead to increased effort in working memory and deeper phonological processing. Our results provide first evidence that different incorrect stress patterns are processed in a qualitatively different way and that the underlying foot structure seems to determine potential stress positions in German words. Copyright © 2013 Elsevier Inc. All rights reserved.

Real-time Mainshock Forecast by Statistical Discrimination of Foreshock Clusters

NASA Astrophysics Data System (ADS)

Nomura, S.; Ogata, Y.

2016-12-01

Foreshock discremination is one of the most effective ways for short-time forecast of large main shocks. Though many large earthquakes accompany their foreshocks, discreminating them from enormous small earthquakes is difficult and only probabilistic evaluation from their spatio-temporal features and magnitude evolution may be available. Logistic regression is the statistical learning method best suited to such binary pattern recognition problems where estimates of a-posteriori probability of class membership are required. Statistical learning methods can keep learning discreminating features from updating catalog and give probabilistic recognition of forecast in real time. We estimated a non-linear function of foreshock proportion by smooth spline bases and evaluate the possibility of foreshocks by the logit function. In this study, we classified foreshocks from earthquake catalog by the Japan Meteorological Agency by single-link clustering methods and learned spatial and temporal features of foreshocks by the probability density ratio estimation. We use the epicentral locations, time spans and difference in magnitudes for learning and forecasting. Magnitudes of main shocks are also predicted our method by incorporating b-values into our method. We discuss the spatial pattern of foreshocks from the classifier composed by our model. We also implement a back test to validate predictive performance of the model by this catalog.

Information Theoretic Extraction of EEG Features for Monitoring Subject Attention

NASA Technical Reports Server (NTRS)

Principe, Jose C.

2000-01-01

The goal of this project was to test the applicability of information theoretic learning (feasibility study) to develop new brain computer interfaces (BCI). The difficulty to BCI comes from several aspects: (1) the effective data collection of signals related to cognition; (2) the preprocessing of these signals to extract the relevant information; (3) the pattern recognition methodology to detect reliably the signals related to cognitive states. We only addressed the two last aspects in this research. We started by evaluating an information theoretic measure of distance (Bhattacharyya distance) for BCI performance with good predictive results. We also compared several features to detect the presence of event related desynchronization (ERD) and synchronization (ERS), and concluded that at least for now the bandpass filtering is the best compromise between simplicity and performance. Finally, we implemented several classifiers for temporal - pattern recognition. We found out that the performance of temporal classifiers is superior to static classifiers but not by much. We conclude by stating that the future of BCI should be found in alternate approaches to sense, collect and process the signals created by populations of neurons. Towards this goal, cross-disciplinary teams of neuroscientists and engineers should be funded to approach BCIs from a much more principled view point.

Impaired Facial Expression Recognition in Children with Temporal Lobe Epilepsy: Impact of Early Seizure Onset on Fear Recognition

ERIC Educational Resources Information Center

Golouboff, Nathalie; Fiori, Nicole; Delalande, Olivier; Fohlen, Martine; Dellatolas, Georges; Jambaque, Isabelle

2008-01-01

The amygdala has been implicated in the recognition of facial emotions, especially fearful expressions, in adults with early-onset right temporal lobe epilepsy (TLE). The present study investigates the recognition of facial emotions in children and adolescents, 8-16 years old, with epilepsy. Twenty-nine subjects had TLE (13 right, 16 left) and…

[Q:] When would you prefer a SOSSAGE to a SAUSAGE? [A:] At about 100 msec. ERP correlates of orthographic typicality and lexicality in written word recognition.

PubMed

Hauk, O; Patterson, K; Woollams, A; Watling, L; Pulvermüller, F; Rogers, T T

2006-05-01

Using a speeded lexical decision task, event-related potentials (ERPs), and minimum norm current source estimates, we investigated early spatiotemporal aspects of cortical activation elicited by words and pseudo-words that varied in their orthographic typicality, that is, in the frequency of their component letter pairs (bi-grams) and triplets (tri-grams). At around 100 msec after stimulus onset, the ERP pattern revealed a significant typicality effect, where words and pseudo-words with atypical orthography (e.g., yacht, cacht) elicited stronger brain activation than items characterized by typical spelling patterns (cart, yart). At approximately 200 msec, the ERP pattern revealed a significant lexicality effect, with pseudo-words eliciting stronger brain activity than words. The two main factors interacted significantly at around 160 msec, where words showed a typicality effect but pseudo-words did not. The principal cortical sources of the effects of both typicality and lexicality were localized in the inferior temporal cortex. Around 160 msec, atypical words elicited the stronger source currents in the left anterior inferior temporal cortex, whereas the left perisylvian cortex was the site of greater activation to typical words. Our data support distinct but interactive processing stages in word recognition, with surface features of the stimulus being processed before the word as a meaningful lexical entry. The interaction of typicality and lexicality can be explained by integration of information from the early form-based system and lexicosemantic processes.

Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition.

PubMed

Wirsich, Jonathan; Bénar, Christian; Ranjeva, Jean-Philippe; Descoins, Médéric; Soulier, Elisabeth; Le Troter, Arnaud; Confort-Gouny, Sylviane; Liégeois-Chauvel, Catherine; Guye, Maxime

2014-10-15

Simultaneous EEG-fMRI has opened up new avenues for improving the spatio-temporal resolution of functional brain studies. However, this method usually suffers from poor EEG quality, especially for evoked potentials (ERPs), due to specific artifacts. As such, the use of EEG-informed fMRI analysis in the context of cognitive studies has particularly focused on optimizing narrow ERP time windows of interest, which ignores the rich diverse temporal information of the EEG signal. Here, we propose to use simultaneous EEG-fMRI to investigate the neural cascade occurring during face recognition in 14 healthy volunteers by using the successive ERP peaks recorded during the cognitive part of this process. N170, N400 and P600 peaks, commonly associated with face recognition, were successfully and reproducibly identified for each trial and each subject by using a group independent component analysis (ICA). For the first time we use this group ICA to extract several independent components (IC) corresponding to the sequence of activation and used single-trial peaks as modulation parameters in a general linear model (GLM) of fMRI data. We obtained an occipital-temporal-frontal stream of BOLD signal modulation, in accordance with the three successive IC-ERPs providing an unprecedented spatio-temporal characterization of the whole cognitive process as defined by BOLD signal modulation. By using this approach, the pattern of EEG-informed BOLD modulation provided improved characterization of the network involved than the fMRI-only analysis or the source reconstruction of the three ERPs; the latter techniques showing only two regions in common localized in the occipital lobe. Copyright © 2014 Elsevier Inc. All rights reserved.

Modeling Geometric-Temporal Context With Directional Pyramid Co-Occurrence for Action Recognition.

PubMed

Yuan, Chunfeng; Li, Xi; Hu, Weiming; Ling, Haibin; Maybank, Stephen J

2014-02-01

In this paper, we present a new geometric-temporal representation for visual action recognition based on local spatio-temporal features. First, we propose a modified covariance descriptor under the log-Euclidean Riemannian metric to represent the spatio-temporal cuboids detected in the video sequences. Compared with previously proposed covariance descriptors, our descriptor can be measured and clustered in Euclidian space. Second, to capture the geometric-temporal contextual information, we construct a directional pyramid co-occurrence matrix (DPCM) to describe the spatio-temporal distribution of the vector-quantized local feature descriptors extracted from a video. DPCM characterizes the co-occurrence statistics of local features as well as the spatio-temporal positional relationships among the concurrent features. These statistics provide strong descriptive power for action recognition. To use DPCM for action recognition, we propose a directional pyramid co-occurrence matching kernel to measure the similarity of videos. The proposed method achieves the state-of-the-art performance and improves on the recognition performance of the bag-of-visual-words (BOVWs) models by a large margin on six public data sets. For example, on the KTH data set, it achieves 98.78% accuracy while the BOVW approach only achieves 88.06%. On both Weizmann and UCF CIL data sets, the highest possible accuracy of 100% is achieved.

The effect of encoding strategy on the neural correlates of memory for faces.

PubMed

Bernstein, Lori J; Beig, Sania; Siegenthaler, Amy L; Grady, Cheryl L

2002-01-01

Encoding and recognition of unfamiliar faces in young adults were examined using positron emission tomography to determine whether different encoding strategies would lead to encoding/retrieval differences in brain activity. Three types of encoding were compared: a 'deep' task (judging pleasantness/unpleasantness), a 'shallow' task (judging right/left orientation), and an intentional learning task in which subjects were instructed to learn the faces for a subsequent memory test but were not provided with a specific strategy. Memory for all faces was tested with an old/new recognition test. A modest behavioral effect was obtained, with deeply-encoded faces being recognized more accurately than shallowly-encoded or intentionally-learned faces. Regardless of encoding strategy, encoding activated a primarily ventral system including bilateral temporal and fusiform regions and left prefrontal cortices, whereas recognition activated a primarily dorsal set of regions including right prefrontal and parietal areas. Within encoding, the type of strategy produced different brain activity patterns, with deep encoding being characterized by left amygdala and left anterior cingulate activation. There was no effect of encoding strategy on brain activity during the recognition conditions. Posterior fusiform gyrus activation was related to better recognition accuracy in those conditions encouraging perceptual strategies, whereas activity in left frontal and temporal areas correlated with better performance during the 'deep' condition. Results highlight three important aspects of face memory: (1) the effect of encoding strategy was seen only at encoding and not at recognition; (2) left inferior prefrontal cortex was engaged during encoding of faces regardless of strategy; and (3) differential activity in fusiform gyrus was found, suggesting that activity in this area is not only a result of automatic face processing but is modulated by controlled processes.

Combining feature extraction and classification for fNIRS BCIs by regularized least squares optimization.

PubMed

Heger, Dominic; Herff, Christian; Schultz, Tanja

2014-01-01

In this paper, we show that multiple operations of the typical pattern recognition chain of an fNIRS-based BCI, including feature extraction and classification, can be unified by solving a convex optimization problem. We formulate a regularized least squares problem that learns a single affine transformation of raw HbO(2) and HbR signals. We show that this transformation can achieve competitive results in an fNIRS BCI classification task, as it significantly improves recognition of different levels of workload over previously published results on a publicly available n-back data set. Furthermore, we visualize the learned models and analyze their spatio-temporal characteristics.

Algorithm for real-time detection of signal patterns using phase synchrony: an application to an electrode array

NASA Astrophysics Data System (ADS)

Sadeghi, Saman; MacKay, William A.; van Dam, R. Michael; Thompson, Michael

2011-02-01

Real-time analysis of multi-channel spatio-temporal sensor data presents a considerable technical challenge for a number of applications. For example, in brain-computer interfaces, signal patterns originating on a time-dependent basis from an array of electrodes on the scalp (i.e. electroencephalography) must be analyzed in real time to recognize mental states and translate these to commands which control operations in a machine. In this paper we describe a new technique for recognition of spatio-temporal patterns based on performing online discrimination of time-resolved events through the use of correlation of phase dynamics between various channels in a multi-channel system. The algorithm extracts unique sensor signature patterns associated with each event during a training period and ranks importance of sensor pairs in order to distinguish between time-resolved stimuli to which the system may be exposed during real-time operation. We apply the algorithm to electroencephalographic signals obtained from subjects tested in the neurophysiology laboratories at the University of Toronto. The extension of this algorithm for rapid detection of patterns in other sensing applications, including chemical identification via chemical or bio-chemical sensor arrays, is also discussed.

Neural correlates of incidental memory in mild cognitive impairment: an fMRI study.

PubMed

Mandzia, Jennifer L; McAndrews, Mary Pat; Grady, Cheryl L; Graham, Simon J; Black, Sandra E

2009-05-01

Behaviour and fMRI brain activation patterns were compared during encoding and recognition tasks in mild cognitive impairment (MCI) (n=14) and normal controls (NC) (n=14). Deep (natural vs. man-made) and shallow (color vs. black and white) decisions were made at encoding and pictures from each condition were presented for yes/no recognition 20 min later. MCI showed less inferior frontal activation during deep (left only) and superficial encoding (bilaterally) and in both medial temporal lobes (MTL). When performance was equivalent (recognition of words encoded superficially), MTL activation was similar for the two groups, but during recognition testing of deeply encoded items NC showed more activation in both prefrontal and left MTL region. In a region of interest analysis, the extent of activation during deep encoding in the parahippocampi bilaterally and in left hippocampus correlated with subsequent recognition accuracy for those items in controls but not in MCI, which may reflect the heterogeneity of activation responses in conjunction with different degrees of pathology burden and progression status in the MCI group.

Continuous Chinese sign language recognition with CNN-LSTM

NASA Astrophysics Data System (ADS)

Yang, Su; Zhu, Qing

2017-07-01

The goal of sign language recognition (SLR) is to translate the sign language into text, and provide a convenient tool for the communication between the deaf-mute and the ordinary. In this paper, we formulate an appropriate model based on convolutional neural network (CNN) combined with Long Short-Term Memory (LSTM) network, in order to accomplish the continuous recognition work. With the strong ability of CNN, the information of pictures captured from Chinese sign language (CSL) videos can be learned and transformed into vector. Since the video can be regarded as an ordered sequence of frames, LSTM model is employed to connect with the fully-connected layer of CNN. As a recurrent neural network (RNN), it is suitable for sequence learning tasks with the capability of recognizing patterns defined by temporal distance. Compared with traditional RNN, LSTM has performed better on storing and accessing information. We evaluate this method on our self-built dataset including 40 daily vocabularies. The experimental results show that the recognition method with CNN-LSTM can achieve a high recognition rate with small training sets, which will meet the needs of real-time SLR system.

The role of temporal call structure in species recognition of male Allobates talamancae (Cope, 1875): (Anura: Dendrobatidae).

PubMed

Kollarits, Dennis; Wappl, Christian; Ringler, Max

2017-01-30

Acoustic species recognition in anurans depends on spectral and temporal characteristics of the advertisement call. The recognition space of a species is shaped by the likelihood of heterospecific acoustic interference. The dendrobatid frogs Allobates talamancae (Cope, 1875) and Silverstoneia flotator (Dunn, 1931) occur syntopically in south-west Costa Rica. A previous study showed that these two species avoid acoustic interference by spectral stratification. In this study, the role of the temporal call structure in the advertisement call of A. talamancae was analyzed, in particular the internote-interval duration in providing species specific temporal cues. In playback trials, artificial advertisement calls with internote-intervals deviating up to ± 90 % from the population mean internote-interval were broadcast to vocally active territorial males. The phonotactic reactions of the males indicated that, unlike in closely related species, internote-interval duration is not a call property essential for species recognition in A. talamancae . However, temporal call structure may be used for species recognition when the likelihood of heterospecific interference is high. Also, the close-encounter courtship call of male A. talamancae is described.

Neuronal correlate of visual associative long-term memory in the primate temporal cortex

NASA Astrophysics Data System (ADS)

Miyashita, Yasushi

1988-10-01

In human long-term memory, ideas and concepts become associated in the learning process1. No neuronal correlate for this cognitive function has so far been described, except that memory traces are thought to be localized in the cerebral cortex; the temporal lobe has been assigned as the site for visual experience because electric stimulation of this area results in imagery recall,2 and lesions produce deficits in visual recognition of objects3-9. We previously reported that in the anterior ventral temporal cortex of monkeys, individual neurons have a sustained activity that is highly selective for a few of the 100 coloured fractal patterns used in a visual working-memory task10. Here I report the development of this selectivity through repeated trials involving the working memory. The few patterns for which a neuron was conjointly selective were frequently related to each other through stimulus-stimulus association imposed during training. The results indicate that the selectivity acquired by these cells represents a neuronal correlate of the associative long-term memory of pictures.

Recognition Memory for Words and Faces Before and After Temporal Lobectomy.

ERIC Educational Resources Information Center

Naugle, Richard I.; And Others

1994-01-01

To assess the sensitivity of Warrington's Recognition Memory Test "words" and "faces" subtests to lateralized temporal lobe seizure foci and effects of epilepsy surgery, 27 left- and 39 right-temporal lobectomy patients were tested before and after surgery. Conditions under which misclassification is most likely are discussed.…

Support for an auto-associative model of spoken cued recall: evidence from fMRI.

PubMed

de Zubicaray, Greig; McMahon, Katie; Eastburn, Mathew; Pringle, Alan J; Lorenz, Lina; Humphreys, Michael S

2007-03-02

Cued recall and item recognition are considered the standard episodic memory retrieval tasks. However, only the neural correlates of the latter have been studied in detail with fMRI. Using an event-related fMRI experimental design that permits spoken responses, we tested hypotheses from an auto-associative model of cued recall and item recognition [Chappell, M., & Humphreys, M. S. (1994). An auto-associative neural network for sparse representations: Analysis and application to models of recognition and cued recall. Psychological Review, 101, 103-128]. In brief, the model assumes that cues elicit a network of phonological short term memory (STM) and semantic long term memory (LTM) representations distributed throughout the neocortex as patterns of sparse activations. This information is transferred to the hippocampus which converges upon the item closest to a stored pattern and outputs a response. Word pairs were learned from a study list, with one member of the pair serving as the cue at test. Unstudied words were also intermingled at test in order to provide an analogue of yes/no recognition tasks. Compared to incorrectly rejected studied items (misses) and correctly rejected (CR) unstudied items, correctly recalled items (hits) elicited increased responses in the left hippocampus and neocortical regions including the left inferior prefrontal cortex (LIPC), left mid lateral temporal cortex and inferior parietal cortex, consistent with predictions from the model. This network was very similar to that observed in yes/no recognition studies, supporting proposals that cued recall and item recognition involve common rather than separate mechanisms.

Automated classification of neurological disorders of gait using spatio-temporal gait parameters.

PubMed

Pradhan, Cauchy; Wuehr, Max; Akrami, Farhoud; Neuhaeusser, Maximilian; Huth, Sabrina; Brandt, Thomas; Jahn, Klaus; Schniepp, Roman

2015-04-01

Automated pattern recognition systems have been used for accurate identification of neurological conditions as well as the evaluation of the treatment outcomes. This study aims to determine the accuracy of diagnoses of (oto-)neurological gait disorders using different types of automated pattern recognition techniques. Clinically confirmed cases of phobic postural vertigo (N = 30), cerebellar ataxia (N = 30), progressive supranuclear palsy (N = 30), bilateral vestibulopathy (N = 30), as well as healthy subjects (N = 30) were recruited for the study. 8 measurements with 136 variables using a GAITRite(®) sensor carpet were obtained from each subject. Subjects were randomly divided into two groups (training cases and validation cases). Sensitivity and specificity of k-nearest neighbor (KNN), naive-bayes classifier (NB), artificial neural network (ANN), and support vector machine (SVM) in classifying the validation cases were calculated. ANN and SVM had the highest overall sensitivity with 90.6% and 92.0% respectively, followed by NB (76.0%) and KNN (73.3%). SVM and ANN showed high false negative rates for bilateral vestibulopathy cases (20.0% and 26.0%); while KNN and NB had high false negative rates for progressive supranuclear palsy cases (76.7% and 40.0%). Automated pattern recognition systems are able to identify pathological gait patterns and establish clinical diagnosis with good accuracy. SVM and ANN in particular differentiate gait patterns of several distinct oto-neurological disorders of gait with high sensitivity and specificity compared to KNN and NB. Both SVM and ANN appear to be a reliable diagnostic and management tool for disorders of gait. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Consolidation of Object and Context Recognition Memory Involve Different Regions of the Temporal Lobe

ERIC Educational Resources Information Center

Balderas, Israela; Rodriguez-Ortiz, Carlos J.; Salgado-Tonda, Paloma; Chavez-Hurtado, Julio; McGaugh, James L.; Bermudez-Rattoni, Federico

2008-01-01

These experiments investigated the involvement of several temporal lobe regions in consolidation of recognition memory. Anisomycin, a protein synthesis inhibitor, was infused into the hippocampus, perirhinal cortex, insular cortex, or basolateral amygdala of rats immediately after the sample phase of object or object-in-context recognition memory…

Complementary Hemispheric Asymmetries in Object Naming and Recognition: A Voxel-Based Correlational Study

ERIC Educational Resources Information Center

Acres, K.; Taylor, K. I.; Moss, H. E.; Stamatakis, E. A.; Tyler, L. K.

2009-01-01

Cognitive neuroscientific research proposes complementary hemispheric asymmetries in naming and recognising visual objects, with a left temporal lobe advantage for object naming and a right temporal lobe advantage for object recognition. Specifically, it has been proposed that the left inferior temporal lobe plays a mediational role linking…

Speaker recognition with temporal cues in acoustic and electric hearing

NASA Astrophysics Data System (ADS)

Vongphoe, Michael; Zeng, Fan-Gang

2005-08-01

Natural spoken language processing includes not only speech recognition but also identification of the speaker's gender, age, emotional, and social status. Our purpose in this study is to evaluate whether temporal cues are sufficient to support both speech and speaker recognition. Ten cochlear-implant and six normal-hearing subjects were presented with vowel tokens spoken by three men, three women, two boys, and two girls. In one condition, the subject was asked to recognize the vowel. In the other condition, the subject was asked to identify the speaker. Extensive training was provided for the speaker recognition task. Normal-hearing subjects achieved nearly perfect performance in both tasks. Cochlear-implant subjects achieved good performance in vowel recognition but poor performance in speaker recognition. The level of the cochlear implant performance was functionally equivalent to normal performance with eight spectral bands for vowel recognition but only to one band for speaker recognition. These results show a disassociation between speech and speaker recognition with primarily temporal cues, highlighting the limitation of current speech processing strategies in cochlear implants. Several methods, including explicit encoding of fundamental frequency and frequency modulation, are proposed to improve speaker recognition for current cochlear implant users.

Visual Object Detection, Categorization, and Identification Tasks Are Associated with Different Time Courses and Sensitivities

ERIC Educational Resources Information Center

de la Rosa, Stephan; Choudhery, Rabia N.; Chatziastros, Astros

2011-01-01

Recent evidence suggests that the recognition of an object's presence and its explicit recognition are temporally closely related. Here we re-examined the time course (using a fine and a coarse temporal resolution) and the sensitivity of three possible component processes of visual object recognition. In particular, participants saw briefly…

A Kinect based sign language recognition system using spatio-temporal features

NASA Astrophysics Data System (ADS)

Memiş, Abbas; Albayrak, Songül

2013-12-01

This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

A design philosophy for multi-layer neural networks with applications to robot control

NASA Technical Reports Server (NTRS)

Vadiee, Nader; Jamshidi, MO

1989-01-01

A system is proposed which receives input information from many sensors that may have diverse scaling, dimension, and data representations. The proposed system tolerates sensory information with faults. The proposed self-adaptive processing technique has great promise in integrating the techniques of artificial intelligence and neural networks in an attempt to build a more intelligent computing environment. The proposed architecture can provide a detailed decision tree based on the input information, information stored in a long-term memory, and the adapted rule-based knowledge. A mathematical model for analysis will be obtained to validate the cited hypotheses. An extensive software program will be developed to simulate a typical example of pattern recognition problem. It is shown that the proposed model displays attention, expectation, spatio-temporal, and predictory behavior which are specific to the human brain. The anticipated results of this research project are: (1) creation of a new dynamic neural network structure, and (2) applications to and comparison with conventional multi-layer neural network structures. The anticipated benefits from this research are vast. The model can be used in a neuro-computer architecture as a building block which can perform complicated, nonlinear, time-varying mapping from a multitude of input excitory classes to an output or decision environment. It can be used for coordinating different sensory inputs and past experience of a dynamic system and actuating signals. The commercial applications of this project can be the creation of a special-purpose neuro-computer hardware which can be used in spatio-temporal pattern recognitions in such areas as air defense systems, e.g., target tracking, and recognition. Potential robotics-related applications are trajectory planning, inverse dynamics computations, hierarchical control, task-oriented control, and collision avoidance.

Action recognition using mined hierarchical compound features.

PubMed

Gilbert, Andrew; Illingworth, John; Bowden, Richard

2011-05-01

The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single-frame object recognition and adapting them for temporal-based action recognition. Inspired by the success of interest points in the 2D spatial domain, their 3D (space-time) counterparts typically form the basic components used to describe actions, and in action recognition the features used are often engineered to fire sparsely. This is to ensure that the problem is tractable; however, this can sacrifice recognition accuracy as it cannot be assumed that the optimum features in terms of class discrimination are obtained from this approach. In contrast, we propose to initially use an overcomplete set of simple 2D corners in both space and time. These are grouped spatially and temporally using a hierarchical process, with an increasing search area. At each stage of the hierarchy, the most distinctive and descriptive features are learned efficiently through data mining. This allows large amounts of data to be searched for frequently reoccurring patterns of features. At each level of the hierarchy, the mined compound features become more complex, discriminative, and sparse. This results in fast, accurate recognition with real-time performance on high-resolution video. As the compound features are constructed and selected based upon their ability to discriminate, their speed and accuracy increase at each level of the hierarchy. The approach is tested on four state-of-the-art data sets, the popular KTH data set to provide a comparison with other state-of-the-art approaches, the Multi-KTH data set to illustrate performance at simultaneous multiaction classification, despite no explicit localization information provided during training. Finally, the recent Hollywood and Hollywood2 data sets provide challenging complex actions taken from commercial movie sequences. For all four data sets, the proposed hierarchical approach outperforms all other methods reported thus far in the literature and can achieve real-time operation.

Multiple brain networks for visual self-recognition with different sensitivity for motion and body part.

PubMed

Sugiura, Motoaki; Sassa, Yuko; Jeong, Hyeonjeong; Miura, Naoki; Akitsuki, Yuko; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

2006-10-01

Multiple brain networks may support visual self-recognition. It has been hypothesized that the left ventral occipito-temporal cortex processes one's own face as a symbol, and the right parieto-frontal network processes self-image in association with motion-action contingency. Using functional magnetic resonance imaging, we first tested these hypotheses based on the prediction that these networks preferentially respond to a static self-face and to moving one's whole body, respectively. Brain activation specifically related to self-image during familiarity judgment was compared across four stimulus conditions comprising a two factorial design: factor Motion contrasted picture (Picture) and movie (Movie), and factor Body part a face (Face) and whole body (Body). Second, we attempted to segregate self-specific networks using a principal component analysis (PCA), assuming an independent pattern of inter-subject variability in activation over the four stimulus conditions in each network. The bilateral ventral occipito-temporal and the right parietal and frontal cortices exhibited self-specific activation. The left ventral occipito-temporal cortex exhibited greater self-specific activation for Face than for Body, in Picture, consistent with the prediction for this region. The activation profiles of the right parietal and frontal cortices did not show preference for Movie Body predicted by the assumed roles of these regions. The PCA extracted two cortical networks, one with its peaks in the right posterior, and another in frontal cortices; their possible roles in visuo-spatial and conceptual self-representations, respectively, were suggested by previous findings. The results thus supported and provided evidence of multiple brain networks for visual self-recognition.

Computation by symmetry operations in a structured model of the brain: Recognition of rotational invariance and time reversal

NASA Astrophysics Data System (ADS)

McGrann, John V.; Shaw, Gordon L.; Shenoy, Krishna V.; Leng, Xiaodan; Mathews, Robert B.

1994-06-01

Symmetries have long been recognized as a vital component of physical and biological systems. What we propose here is that symmetry operations are an important feature of higher brain function and result from the spatial and temporal modularity of the cortex. These symmetry operations arise naturally in the trion model of the cortex. The trion model is a highly structured mathematical realization of the Mountcastle organizational principle [Mountcastle, in The Mindful Brain (MIT, Cambridge, 1978)] in which the cortical column is the basic neural network of the cortex and is comprised of subunit minicolumns, which are idealized as trions with three levels of firing. A columnar network of a small number of trions has a large repertoire of quasistable, periodic spatial-temporal firing magic patterns (MP's), which can be excited. The MP's are related by specific symmetries: Spatial rotation, parity, ``spin'' reversal, and time reversal as well as other ``global'' symmetry operations in this abstract internal language of the brain. These MP's can be readily enhanced (as well as inherent categories of MP's) by only a small change in connection strengths via a Hebb learning rule. Learning introduces small breaking of the symmetries in the connectivities which enables a symmetry in the patterns to be recognized in the Monte Carlo evolution of the MP's. Examples of the recognition of rotational invariance and of a time-reversed pattern are presented. We propose the possibility of building a logic device from the hardware implementation of a higher level architecture of trion cortical columns.

Music Perception in Dementia.

PubMed

Golden, Hannah L; Clark, Camilla N; Nicholas, Jennifer M; Cohen, Miriam H; Slattery, Catherine F; Paterson, Ross W; Foulkes, Alexander J M; Schott, Jonathan M; Mummery, Catherine J; Crutch, Sebastian J; Warren, Jason D

2017-01-01

Despite much recent interest in music and dementia, music perception has not been widely studied across dementia syndromes using an information processing approach. Here we addressed this issue in a cohort of 30 patients representing major dementia syndromes of typical Alzheimer's disease (AD, n = 16), logopenic aphasia (LPA, an Alzheimer variant syndrome; n = 5), and progressive nonfluent aphasia (PNFA; n = 9) in relation to 19 healthy age-matched individuals. We designed a novel neuropsychological battery to assess perception of musical patterns in the dimensions of pitch and temporal information (requiring detection of notes that deviated from the established pattern based on local or global sequence features) and musical scene analysis (requiring detection of a familiar tune within polyphonic harmony). Performance on these tests was referenced to generic auditory (timbral) deviance detection and recognition of familiar tunes and adjusted for general auditory working memory performance. Relative to healthy controls, patients with AD and LPA had group-level deficits of global pitch (melody contour) processing while patients with PNFA as a group had deficits of local (interval) as well as global pitch processing. There was substantial individual variation within syndromic groups. Taking working memory performance into account, no specific deficits of musical temporal processing, timbre processing, musical scene analysis, or tune recognition were identified. The findings suggest that particular aspects of music perception such as pitch pattern analysis may open a window on the processing of information streams in major dementia syndromes. The potential selectivity of musical deficits for particular dementia syndromes and particular dimensions of processing warrants further systematic investigation.

Basic research planning in mathematical pattern recognition and image analysis

NASA Technical Reports Server (NTRS)

Bryant, J.; Guseman, L. F., Jr.

1981-01-01

Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.

Optical Pattern Recognition

NASA Astrophysics Data System (ADS)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

ERIC Educational Resources Information Center

Shen, Jung; Souza, Pamela E.

2017-01-01

Purpose: This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for…

Auditory temporal processing in patients with temporal lobe epilepsy.

PubMed

Lavasani, Azam Navaei; Mohammadkhani, Ghassem; Motamedi, Mahmoud; Karimi, Leyla Jalilvand; Jalaei, Shohreh; Shojaei, Fereshteh Sadat; Danesh, Ali; Azimi, Hadi

2016-07-01

Auditory temporal processing is the main feature of speech processing ability. Patients with temporal lobe epilepsy, despite their normal hearing sensitivity, may present speech recognition disorders. The present study was carried out to evaluate the auditory temporal processing in patients with unilateral TLE. The present study was carried out on 25 patients with epilepsy: 11 patients with right temporal lobe epilepsy and 14 with left temporal lobe epilepsy with a mean age of 31.1years and 18 control participants with a mean age of 29.4years. The two experimental and control groups were evaluated via gap-in-noise and duration pattern sequence tests. One-way ANOVA was run to analyze the data. The mean of the threshold of the GIN test in the control group was observed to be better than that in participants with LTLE and RTLE. Also, it was observed that the percentage of correct responses on the DPS test in the control group and in participants with RTLE was better than that in participants with LTLE. Patients with TLE have difficulties in temporal processing. Difficulties are more significant in patients with LTLE, likely because the left temporal lobe is specialized for the processing of temporal information. Copyright © 2016 Elsevier Inc. All rights reserved.

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

PubMed Central

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

2016-01-01

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.

PubMed

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

2016-06-10

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.

Naming and recognizing famous faces in temporal lobe epilepsy.

PubMed

Glosser, G; Salvucci, A E; Chiaravalloti, N D

2003-07-08

To assess naming and recognition of faces of familiar famous people in patients with epilepsy before and after anterior temporal lobectomy (ATL). Color photographs of famous people were presented for naming and description to 63 patients with temporal lobe epilepsy (TLE) either before or after ATL and to 10 healthy age- and education-matched controls. Spontaneous naming of photographed famous people was impaired in all patient groups, but was most abnormal in patients who had undergone left ATL. When allowed to demonstrate knowledge of the famous faces through verbal descriptions, rather than naming, patients with left TLE, left ATL, and right TLE improved to normal levels, but patients with right ATL were still impaired, suggesting a new deficit in identifying famous faces. Naming of famous people was related to naming of other common objects, verbal memory, and perceptual discrimination of faces. Recognition of the identity of pictured famous people was more related to visuospatial perception and memory. Lesions in anterior regions of the right temporal lobe impair recognition of the identities of familiar faces, as well as the learning of new faces. Lesions in the left temporal lobe, especially in anterior regions, disrupt access to the names of known people, but do not affect recognition of the identities of famous faces. Results are consistent with the hypothesized role of lateralized anterior temporal lobe structures in facial recognition and naming of unique entities.

Short temporal asynchrony disrupts visual object recognition

PubMed Central

Singer, Jedediah M.; Kreiman, Gabriel

2014-01-01

Humans can recognize objects and scenes in a small fraction of a second. The cascade of signals underlying rapid recognition might be disrupted by temporally jittering different parts of complex objects. Here we investigated the time course over which shape information can be integrated to allow for recognition of complex objects. We presented fragments of object images in an asynchronous fashion and behaviorally evaluated categorization performance. We observed that visual recognition was significantly disrupted by asynchronies of approximately 30 ms, suggesting that spatiotemporal integration begins to break down with even small deviations from simultaneity. However, moderate temporal asynchrony did not completely obliterate recognition; in fact, integration of visual shape information persisted even with an asynchrony of 100 ms. We describe the data with a concise model based on the dynamic reduction of uncertainty about what image was presented. These results emphasize the importance of timing in visual processing and provide strong constraints for the development of dynamical models of visual shape recognition. PMID:24819738

Obligatory and facultative brain regions for voice-identity recognition

PubMed Central

Roswandowitz, Claudia; Kappes, Claudia; Obrig, Hellmuth; von Kriegstein, Katharina

2018-01-01

Abstract Recognizing the identity of others by their voice is an important skill for social interactions. To date, it remains controversial which parts of the brain are critical structures for this skill. Based on neuroimaging findings, standard models of person-identity recognition suggest that the right temporal lobe is the hub for voice-identity recognition. Neuropsychological case studies, however, reported selective deficits of voice-identity recognition in patients predominantly with right inferior parietal lobe lesions. Here, our aim was to work towards resolving the discrepancy between neuroimaging studies and neuropsychological case studies to find out which brain structures are critical for voice-identity recognition in humans. We performed a voxel-based lesion-behaviour mapping study in a cohort of patients (n = 58) with unilateral focal brain lesions. The study included a comprehensive behavioural test battery on voice-identity recognition of newly learned (voice-name, voice-face association learning) and familiar voices (famous voice recognition) as well as visual (face-identity recognition) and acoustic control tests (vocal-pitch and vocal-timbre discrimination). The study also comprised clinically established tests (neuropsychological assessment, audiometry) and high-resolution structural brain images. The three key findings were: (i) a strong association between voice-identity recognition performance and right posterior/mid temporal and right inferior parietal lobe lesions; (ii) a selective association between right posterior/mid temporal lobe lesions and voice-identity recognition performance when face-identity recognition performance was factored out; and (iii) an association of right inferior parietal lobe lesions with tasks requiring the association between voices and faces but not voices and names. The results imply that the right posterior/mid temporal lobe is an obligatory structure for voice-identity recognition, while the inferior parietal lobe is only a facultative component of voice-identity recognition in situations where additional face-identity processing is required. PMID:29228111

Obligatory and facultative brain regions for voice-identity recognition.

PubMed

Roswandowitz, Claudia; Kappes, Claudia; Obrig, Hellmuth; von Kriegstein, Katharina

2018-01-01

Recognizing the identity of others by their voice is an important skill for social interactions. To date, it remains controversial which parts of the brain are critical structures for this skill. Based on neuroimaging findings, standard models of person-identity recognition suggest that the right temporal lobe is the hub for voice-identity recognition. Neuropsychological case studies, however, reported selective deficits of voice-identity recognition in patients predominantly with right inferior parietal lobe lesions. Here, our aim was to work towards resolving the discrepancy between neuroimaging studies and neuropsychological case studies to find out which brain structures are critical for voice-identity recognition in humans. We performed a voxel-based lesion-behaviour mapping study in a cohort of patients (n = 58) with unilateral focal brain lesions. The study included a comprehensive behavioural test battery on voice-identity recognition of newly learned (voice-name, voice-face association learning) and familiar voices (famous voice recognition) as well as visual (face-identity recognition) and acoustic control tests (vocal-pitch and vocal-timbre discrimination). The study also comprised clinically established tests (neuropsychological assessment, audiometry) and high-resolution structural brain images. The three key findings were: (i) a strong association between voice-identity recognition performance and right posterior/mid temporal and right inferior parietal lobe lesions; (ii) a selective association between right posterior/mid temporal lobe lesions and voice-identity recognition performance when face-identity recognition performance was factored out; and (iii) an association of right inferior parietal lobe lesions with tasks requiring the association between voices and faces but not voices and names. The results imply that the right posterior/mid temporal lobe is an obligatory structure for voice-identity recognition, while the inferior parietal lobe is only a facultative component of voice-identity recognition in situations where additional face-identity processing is required. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

A computerized recognition system for the home-based physiotherapy exercises using an RGBD camera.

PubMed

Ar, Ilktan; Akgul, Yusuf Sinan

2014-11-01

Computerized recognition of the home based physiotherapy exercises has many benefits and it has attracted considerable interest among the computer vision community. However, most methods in the literature view this task as a special case of motion recognition. In contrast, we propose to employ the three main components of a physiotherapy exercise (the motion patterns, the stance knowledge, and the exercise object) as different recognition tasks and embed them separately into the recognition system. The low level information about each component is gathered using machine learning methods. Then, we use a generative Bayesian network to recognize the exercise types by combining the information from these sources at an abstract level, which takes the advantage of domain knowledge for a more robust system. Finally, a novel postprocessing step is employed to estimate the exercise repetitions counts. The performance evaluation of the system is conducted with a new dataset which contains RGB (red, green, and blue) and depth videos of home-based exercise sessions for commonly applied shoulder and knee exercises. The proposed system works without any body-part segmentation, bodypart tracking, joint detection, and temporal segmentation methods. In the end, favorable exercise recognition rates and encouraging results on the estimation of repetition counts are obtained.

Visual paired-associate learning: in search of material-specific effects in adult patients who have undergone temporal lobectomy.

PubMed

Smith, Mary Lou; Bigel, Marla; Miller, Laurie A

2011-02-01

The mesial temporal lobes are important for learning arbitrary associations. It has previously been demonstrated that left mesial temporal structures are involved in learning word pairs, but it is not yet known whether comparable lesions in the right temporal lobe impair visually mediated associative learning. Patients who had undergone left (n=16) or right (n=18) temporal lobectomy for relief of intractable epilepsy and healthy controls (n=13) were administered two paired-associate learning tasks assessing their learning and memory of pairs of abstract designs or pairs of symbols in unique locations. Both patient groups had deficits in learning the designs, but only the right temporal group was impaired in recognition. For the symbol location task, differences were not found in learning, but again a recognition deficit was found for the right temporal group. The findings implicate the mesial temporal structures in relational learning. They support a material-specific effect for recognition but not for learning and recall of arbitrary visual and visual-spatial associative information. Copyright © 2010 Elsevier Inc. All rights reserved.

Temporal Sensitivity Measured Shortly After Cochlear Implantation Predicts 6-Month Speech Recognition Outcome.

PubMed

Erb, Julia; Ludwig, Alexandra Annemarie; Kunke, Dunja; Fuchs, Michael; Obleser, Jonas

2018-04-24

Psychoacoustic tests assessed shortly after cochlear implantation are useful predictors of the rehabilitative speech outcome. While largely independent, both spectral and temporal resolution tests are important to provide an accurate prediction of speech recognition. However, rapid tests of temporal sensitivity are currently lacking. Here, we propose a simple amplitude modulation rate discrimination (AMRD) paradigm that is validated by predicting future speech recognition in adult cochlear implant (CI) patients. In 34 newly implanted patients, we used an adaptive AMRD paradigm, where broadband noise was modulated at the speech-relevant rate of ~4 Hz. In a longitudinal study, speech recognition in quiet was assessed using the closed-set Freiburger number test shortly after cochlear implantation (t0) as well as the open-set Freiburger monosyllabic word test 6 months later (t6). Both AMRD thresholds at t0 (r = -0.51) and speech recognition scores at t0 (r = 0.56) predicted speech recognition scores at t6. However, AMRD and speech recognition at t0 were uncorrelated, suggesting that those measures capture partially distinct perceptual abilities. A multiple regression model predicting 6-month speech recognition outcome with deafness duration and speech recognition at t0 improved from adjusted R = 0.30 to adjusted R = 0.44 when AMRD threshold was added as a predictor. These findings identify AMRD thresholds as a reliable, nonredundant predictor above and beyond established speech tests for CI outcome. This AMRD test could potentially be developed into a rapid clinical temporal-resolution test to be integrated into the postoperative test battery to improve the reliability of speech outcome prognosis.

Dynamic texture recognition using local binary patterns with an application to facial expressions.

PubMed

Zhao, Guoying; Pietikäinen, Matti

2007-06-01

Dynamic texture (DT) is an extension of texture to the temporal domain. Description and recognition of DTs have attracted growing attention. In this paper, a novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered. First, the textures are modeled with volume local binary patterns (VLBP), which are an extension of the LBP operator widely used in ordinary texture analysis, combining motion and appearance. To make the approach computationally simple and easy to extend, only the co-occurrences of the local binary patterns on three orthogonal planes (LBP-TOP) are then considered. A block-based method is also proposed to deal with specific dynamic events such as facial expressions in which local information and its spatial locations should also be taken into account. In experiments with two DT databases, DynTex and Massachusetts Institute of Technology (MIT), both the VLBP and LBP-TOP clearly outperformed the earlier approaches. The proposed block-based method was evaluated with the Cohn-Kanade facial expression database with excellent results. The advantages of our approach include local processing, robustness to monotonic gray-scale changes, and simple computation.

Use of Biometrics within Sub-Saharan Refugee Communities

DTIC Science & Technology

2013-12-01

fingerprint patterns, iris pattern recognition, and facial recognition as a means of establishing an individual’s identity. Biometrics creates and...Biometrics typically comprises fingerprint patterns, iris pattern recognition, and facial recognition as a means of establishing an individual’s identity...authentication because it identifies an individual based on mathematical analysis of the random pattern visible within the iris. Facial recognition is

Componential Network for the Recognition of Tool-Associated Actions: Evidence from Voxel-based Lesion-Symptom Mapping in Acute Stroke Patients.

PubMed

Martin, Markus; Dressing, Andrea; Bormann, Tobias; Schmidt, Charlotte S M; Kümmerer, Dorothee; Beume, Lena; Saur, Dorothee; Mader, Irina; Rijntjes, Michel; Kaller, Christoph P; Weiller, Cornelius

2017-08-01

The study aimed to elucidate areas involved in recognizing tool-associated actions, and to characterize the relationship between recognition and active performance of tool use.We performed voxel-based lesion-symptom mapping in a prospective cohort of 98 acute left-hemisphere ischemic stroke patients (68 male, age mean ± standard deviation, 65 ± 13 years; examination 4.4 ± 2 days post-stroke). In a video-based test, patients distinguished correct tool-related actions from actions with spatio-temporal (incorrect grip, kinematics, or tool orientation) or conceptual errors (incorrect tool-recipient matching, e.g., spreading jam on toast with a paintbrush). Moreover, spatio-temporal and conceptual errors were determined during actual tool use.Deficient spatio-temporal error discrimination followed lesions within a dorsal network in which the inferior parietal lobule (IPL) and the lateral temporal cortex (sLTC) were specifically relevant for assessing functional hand postures and kinematics, respectively. Conversely, impaired recognition of conceptual errors resulted from damage to ventral stream regions including anterior temporal lobe. Furthermore, LTC and IPL lesions impacted differently on action recognition and active tool use, respectively.In summary, recognition of tool-associated actions relies on a componential network. Our study particularly highlights the dissociable roles of LTC and IPL for the recognition of action kinematics and functional hand postures, respectively. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Aberrant activity and connectivity of the posterior superior temporal sulcus during social cognition in schizophrenia.

PubMed

Mier, Daniela; Eisenacher, Sarah; Rausch, Franziska; Englisch, Susanne; Gerchen, Martin Fungisai; Zamoscik, Vera; Meyer-Lindenberg, Andreas; Zink, Mathias; Kirsch, Peter

2017-10-01

Schizophrenia is associated with significant impairments in social cognition. These impairments have been shown to go along with altered activation of the posterior superior temporal sulcus (pSTS). However, studies that investigate connectivity of pSTS during social cognition in schizophrenia are sparse. Twenty-two patients with schizophrenia and 22 matched healthy controls completed a social-cognitive task for functional magnetic resonance imaging that allows the investigation of affective Theory of Mind (ToM), emotion recognition and the processing of neutral facial expressions. Moreover, a resting-state measurement was taken. Patients with schizophrenia performed worse in the social-cognitive task (main effect of group). In addition, a group by social-cognitive processing interaction was revealed for activity, as well as for connectivity during the social-cognitive task, i.e., patients with schizophrenia showed hyperactivity of right pSTS during neutral face processing, but hypoactivity during emotion recognition and affective ToM. In addition, hypoconnectivity between right and left pSTS was revealed for affective ToM, but not for neutral face processing or emotion recognition. No group differences in connectivity from right to left pSTS occurred during resting state. This pattern of aberrant activity and connectivity of the right pSTS during social cognition might form the basis of false-positive perceptions of emotions and intentions and could contribute to the emergence and sustainment of delusions.

Early Visual Word Processing Is Flexible: Evidence from Spatiotemporal Brain Dynamics.

PubMed

Chen, Yuanyuan; Davis, Matthew H; Pulvermüller, Friedemann; Hauk, Olaf

2015-09-01

Visual word recognition is often described as automatic, but the functional locus of top-down effects is still a matter of debate. Do task demands modulate how information is retrieved, or only how it is used? We used EEG/MEG recordings to assess whether, when, and how task contexts modify early retrieval of specific psycholinguistic information in occipitotemporal cortex, an area likely to contribute to early stages of visual word processing. Using a parametric approach, we analyzed the spatiotemporal response patterns of occipitotemporal cortex for orthographic, lexical, and semantic variables in three psycholinguistic tasks: silent reading, lexical decision, and semantic decision. Task modulation of word frequency and imageability effects occurred simultaneously in ventral occipitotemporal regions-in the vicinity of the putative visual word form area-around 160 msec, following task effects on orthographic typicality around 100 msec. Frequency and typicality also produced task-independent effects in anterior temporal lobe regions after 200 msec. The early task modulation for several specific psycholinguistic variables indicates that occipitotemporal areas integrate perceptual input with prior knowledge in a task-dependent manner. Still, later task-independent effects in anterior temporal lobes suggest that word recognition eventually leads to retrieval of semantic information irrespective of task demands. We conclude that even a highly overlearned visual task like word recognition should be described as flexible rather than automatic.

Self-face recognition in social context.

PubMed

Sugiura, Motoaki; Sassa, Yuko; Jeong, Hyeonjeong; Wakusawa, Keisuke; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

2012-06-01

The concept of "social self" is often described as a representation of the self-reflected in the eyes or minds of others. Although the appearance of one's own face has substantial social significance for humans, neuroimaging studies have failed to link self-face recognition and the likely neural substrate of the social self, the medial prefrontal cortex (MPFC). We assumed that the social self is recruited during self-face recognition under a rich social context where multiple other faces are available for comparison of social values. Using functional magnetic resonance imaging (fMRI), we examined the modulation of neural responses to the faces of the self and of a close friend in a social context. We identified an enhanced response in the ventral MPFC and right occipitoparietal sulcus in the social context specifically for the self-face. Neural response in the right lateral parietal and inferior temporal cortices, previously claimed as self-face-specific, was unaffected for the self-face but unexpectedly enhanced for the friend's face in the social context. Self-face-specific activation in the pars triangularis of the inferior frontal gyrus, and self-face-specific reduction of activation in the left middle temporal gyrus and the right supramarginal gyrus, replicating a previous finding, were not subject to such modulation. Our results thus demonstrated the recruitment of a social self during self-face recognition in the social context. At least three brain networks for self-face-specific activation may be dissociated by different patterns of response-modulation in the social context, suggesting multiple dynamic self-other representations in the human brain. Copyright © 2011 Wiley-Liss, Inc.

Category-Specific Naming and Recognition Deficits in Temporal Lobe Epilepsy Surgical Patients

PubMed Central

Drane, Daniel L.; Ojemann, George A.; Aylward, Elizabeth; Ojemann, Jeffrey G.; Johnson, L. Clark; Silbergeld, Daniel L.; Miller, John W.; Tranel, Daniel

2008-01-01

Objective Based upon Damasio's “Convergence Zone” model of semantic memory, we predicted that epilepsy surgical patients with anterior temporal lobe (TL) seizure onset would exhibit a pattern of category-specific naming and recognition deficits not observed in patients with seizures arising elsewhere. Methods We assessed epilepsy patients with unilateral seizure onset of anterior TL or other origin (n = 22), pre- or postoperatively, using a set of category-specific items and a conventional measure of visual naming (Boston Naming Test: BNT). Results Category-specific naming deficits were exhibited by patients with dominant anterior TL seizure onset/resection for famous faces and animals, while category-specific recognition deficits for these same categories were exhibited by patients with nondominant anterior TL onset/resection. Patients with other seizure onset did not exhibit category-specific deficits. Naming and recognition deficits were frequently not detected by the BNT, which samples only a limited range of stimuli. Interpretation Consistent with the “convergence zone” framework, results suggest that the nondominant anterior TL plays a major role in binding sensory information into conceptual percepts for certain stimuli, while dominant TL regions function to provide a link to verbal labels for these percepts. Although observed category-specific deficits were striking, they were often missed by the BNT, suggesting that they are more prevalent than recognized in both pre- and postsurgical epilepsy patients. Systematic investigation of these deficits could lead to more refined models of semantic memory, aid in the localization of seizures, and contribute to modifications in surgical technique and patient selection in epilepsy surgery to improve neurocognitive outcome. PMID:18206185

Rotation-invariant neural pattern recognition system with application to coin recognition.

PubMed

Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

1992-01-01

In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

Wavelet-Based Signal and Image Processing for Target Recognition

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.

2002-11-01

The PI visited NSWC Dahlgren, VA, for six weeks in May-June 2002 and collaborated with scientists in the G33 TEAMS facility, and with Marilyn Rudzinsky of T44 Technology and Photonic Systems Branch. During this visit the PI also presented six educational seminars to NSWC scientists on various aspects of signal processing. Several items from the grant proposal were completed, including (1) wavelet-based algorithms for interpolation of 1-d signals and 2-d images; (2) Discrete Wavelet Transform domain based algorithms for filtering of image data; (3) wavelet-based smoothing of image sequence data originally obtained for the CRITTIR (Clutter Rejection Involving Temporal Techniques in the Infra-Red) project. The PI visited the University of Stellenbosch, South Africa to collaborate with colleagues Prof. B.M. Herbst and Prof. J. du Preez on the use of wavelet image processing in conjunction with pattern recognition techniques. The University of Stellenbosch has offered the PI partial funding to support a sabbatical visit in Fall 2003, the primary purpose of which is to enable the PI to develop and enhance his expertise in Pattern Recognition. During the first year, the grant supported publication of 3 referred papers, presentation of 9 seminars and an intensive two-day course on wavelet theory. The grant supported the work of two students who functioned as research assistants.

Autocorrelation factors and intelligibility of Japanese monosyllables in individuals with sensorineural hearing loss.

PubMed

Shimokura, Ryota; Akasaka, Sakie; Nishimura, Tadashi; Hosoi, Hiroshi; Matsui, Toshie

2017-02-01

Some Japanese monosyllables contain consonants that are not easily discernible for individuals with sensorineural hearing loss. However, the acoustic features that make these monosyllables difficult to discern have not been clearly identified. Here, this study used the autocorrelation function (ACF), which can capture temporal features of signals, to clarify the factors influencing speech intelligibility. For each monosyllable, five factors extracted from the ACF [Φ(0): total energy; τ 1 and ϕ 1 : delay time and amplitude of the maximum peak; τ e : effective duration; W ϕ (0) : spectral centroid], voice onset time, speech intelligibility index, and loudness level were compared with the percentage of correctly perceived articulations (144 ears) obtained by 50 Japanese vowel and consonant-vowel monosyllables produced by one female speaker. Results showed that median effective duration [(τ e ) med ] was strongly correlated with the percentage of correctly perceived articulations of the consonants (r = 0.87, p < 0.01). (τ e ) med values were computed by running ACFs with the time lag at which the magnitude of the logarithmic-ACF envelope had decayed to -10 dB. Effective duration is a measure of temporal pattern persistence, i.e., the duration over which the waveform maintains a stable pattern. The authors postulate that low recognition ability is related to degraded perception of temporal fluctuation patterns.

The medial temporal lobes distinguish between within-item and item-context relations during autobiographical memory retrieval.

PubMed

Sheldon, Signy; Levine, Brian

2015-12-01

During autobiographical memory retrieval, the medial temporal lobes (MTL) relate together multiple event elements, including object (within-item relations) and context (item-context relations) information, to create a cohesive memory. There is consistent support for a functional specialization within the MTL according to these relational processes, much of which comes from recognition memory experiments. In this study, we compared brain activation patterns associated with retrieving within-item relations (i.e., associating conceptual and sensory-perceptual object features) and item-context relations (i.e., spatial relations among objects) with respect to naturalistic autobiographical retrieval. We developed a novel paradigm that cued participants to retrieve information about past autobiographical events, non-episodic within-item relations, and non-episodic item-context relations with the perceptuomotor aspects of retrieval equated across these conditions. We used multivariate analysis techniques to extract common and distinct patterns of activity among these conditions within the MTL and across the whole brain, both in terms of spatial and temporal patterns of activity. The anterior MTL (perirhinal cortex and anterior hippocampus) was preferentially recruited for generating within-item relations later in retrieval whereas the posterior MTL (posterior parahippocampal cortex and posterior hippocampus) was preferentially recruited for generating item-context relations across the retrieval phase. These findings provide novel evidence for functional specialization within the MTL with respect to naturalistic memory retrieval. © 2015 Wiley Periodicals, Inc.

Neural microgenesis of personally familiar face recognition

PubMed Central

Ramon, Meike; Vizioli, Luca; Liu-Shuang, Joan; Rossion, Bruno

2015-01-01

Despite a wealth of information provided by neuroimaging research, the neural basis of familiar face recognition in humans remains largely unknown. Here, we isolated the discriminative neural responses to unfamiliar and familiar faces by slowly increasing visual information (i.e., high-spatial frequencies) to progressively reveal faces of unfamiliar or personally familiar individuals. Activation in ventral occipitotemporal face-preferential regions increased with visual information, independently of long-term face familiarity. In contrast, medial temporal lobe structures (perirhinal cortex, amygdala, hippocampus) and anterior inferior temporal cortex responded abruptly when sufficient information for familiar face recognition was accumulated. These observations suggest that following detailed analysis of individual faces in core posterior areas of the face-processing network, familiar face recognition emerges categorically in medial temporal and anterior regions of the extended cortical face network. PMID:26283361

Neural microgenesis of personally familiar face recognition.

PubMed

Ramon, Meike; Vizioli, Luca; Liu-Shuang, Joan; Rossion, Bruno

2015-09-01

Despite a wealth of information provided by neuroimaging research, the neural basis of familiar face recognition in humans remains largely unknown. Here, we isolated the discriminative neural responses to unfamiliar and familiar faces by slowly increasing visual information (i.e., high-spatial frequencies) to progressively reveal faces of unfamiliar or personally familiar individuals. Activation in ventral occipitotemporal face-preferential regions increased with visual information, independently of long-term face familiarity. In contrast, medial temporal lobe structures (perirhinal cortex, amygdala, hippocampus) and anterior inferior temporal cortex responded abruptly when sufficient information for familiar face recognition was accumulated. These observations suggest that following detailed analysis of individual faces in core posterior areas of the face-processing network, familiar face recognition emerges categorically in medial temporal and anterior regions of the extended cortical face network.

Segregation of anterior temporal regions critical for retrieving names of unique and nonunique entities reflects underlying long-range connectivity

PubMed Central

Mehta, Sonya; Inoue, Kayo; Rudrauf, David; Damasio, Hanna; Tranel, Daniel; Grabowski, Thomas

2015-01-01

Lesion-deficit studies support the hypothesis that the left anterior temporal lobe (ATL) plays a critical role in retrieving names of concrete entities. They further suggest that different regions of the left ATL process different conceptual categories. Here we test the specificity of these relationships and whether the anatomical segregation is related to the underlying organization of white matter connections. We reanalyzed data from a previous lesion study of naming and recognition across five categories of concrete entities. In voxelwise logistic regressions of lesion-deficit associations, we formally incorporated measures of disconnection of long-range association fiber tracts (FTs) and covaried for recognition and non-category specific naming deficits. We also performed fiber tractwise analyses to assess whether damage to specific FTs was preferentially associated with category-selective naming deficits. Damage to the basolateral ATL was associated with naming deficits for both unique (famous faces) and non-unique entities, whereas the damage to the temporal pole was associated with naming deficits for unique entities only. This segregation pattern remained after accounting for comorbid recognition deficits or naming deficits in other categories. The tractwise analyses showed that damage to the uncinate fasciculus was associated with naming impairments for unique entities, while damage to the inferior longitudinal fasciculus was associated with naming impairments for non-unique entities. Covarying for FT transection in voxelwise analyses rendered the cortical association for unique entities more focal. These results are consistent with the partial segregation of brain system support for name retrieval of unique and non-unique entities at both the level of cortical components and underlying white matter fiber bundles. Our study reconciles theoretic accounts of the functional organization of the left ATL by revealing both category-related processing and semantic hub sectors. PMID:26707082

The functional neuroanatomy of verbal memory in Alzheimer's disease: [18F]-Fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) correlates of recency and recognition memory.

PubMed

Staffaroni, Adam M; Melrose, Rebecca J; Leskin, Lorraine P; Riskin-Jones, Hannah; Harwood, Dylan; Mandelkern, Mark; Sultzer, David L

2017-09-01

The objective of this study was to distinguish the functional neuroanatomy of verbal learning and recognition in Alzheimer's disease (AD) using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word Learning task. In 81 Veterans diagnosed with dementia due to AD, we conducted a cluster-based correlation analysis to assess the relationships between recency and recognition memory scores from the CERAD Word Learning Task and cortical metabolic activity measured using [ 18 F]-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET). AD patients (Mini-Mental State Examination, MMSE mean = 20.2) performed significantly better on the recall of recency items during learning trials than of primacy and middle items. Recency memory was associated with cerebral metabolism in the left middle and inferior temporal gyri and left fusiform gyrus (p < .05 at the corrected cluster level). In contrast, recognition memory was correlated with metabolic activity in two clusters: (a) a large cluster that included the left hippocampus, parahippocampal gyrus, entorhinal cortex, anterior temporal lobe, and inferior and middle temporal gyri; (b) the bilateral orbitofrontal cortices (OFC). The present study further informs our understanding of the disparate functional neuroanatomy of recency memory and recognition memory in AD. We anticipated that the recency effect would be relatively preserved and associated with temporoparietal brain regions implicated in short-term verbal memory, while recognition memory would be associated with the medial temporal lobe and possibly the OFC. Consistent with our a priori hypotheses, list learning in our AD sample was characterized by a reduced primacy effect and a relatively spared recency effect; however, recency memory was associated with cerebral metabolism in inferior and lateral temporal regions associated with the semantic memory network, rather than regions associated with short-term verbal memory. The correlates of recognition memory included the medial temporal lobe and OFC, replicating prior studies.

Emotional memory and perception in temporal lobectomy patients with amygdala damage.

PubMed

Brierley, B; Medford, N; Shaw, P; David, A S

2004-04-01

The human amygdala is implicated in the formation of emotional memories and the perception of emotional stimuli--particularly fear--across various modalities. To discern the extent to which these functions are related. 28 patients who had anterior temporal lobectomy (13 left and 15 right) for intractable epilepsy were recruited. Structural magnetic resonance imaging showed that three of them had atrophy of their remaining amygdala. All participants were given tests of affect perception from facial and vocal expressions and of emotional memory, using a standard narrative test and a novel test of word recognition. The results were standardised against matched healthy controls. Performance on all emotion tasks in patients with unilateral lobectomy ranged from unimpaired to moderately impaired. Perception of emotions in faces and voices was (with exceptions) significantly positively correlated, indicating multimodal emotional processing. However, there was no correlation between the subjects' performance on tests of emotional memory and perception. Several subjects showed strong emotional memory enhancement but poor fear perception. Patients with bilateral amygdala damage had greater impairment, particularly on the narrative test of emotional memory, one showing superior fear recognition but absent memory enhancement. Bilateral amygdala damage is particularly disruptive of emotional memory processes in comparison with unilateral temporal lobectomy. On a cognitive level, the pattern of results implies that perception of emotional expressions and emotional memory are supported by separate processing systems or streams.

Exogenous temporal cues enhance recognition memory in an object-based manner.

PubMed

Ohyama, Junji; Watanabe, Katsumi

2010-11-01

Exogenous attention enhances the perception of attended items in both a space-based and an object-based manner. Exogenous attention also improves recognition memory for attended items in the space-based mode. However, it has not been examined whether object-based exogenous attention enhances recognition memory. To address this issue, we examined whether a sudden visual change in a task-irrelevant stimulus (an exogenous cue) would affect participants' recognition memory for items that were serially presented around a cued time. The results showed that recognition accuracy for an item was strongly enhanced when the visual cue occurred at the same location and time as the item (Experiments 1 and 2). The memory enhancement effect occurred when the exogenous visual cue and an item belonged to the same object (Experiments 3 and 4) and even when the cue was counterpredictive of the timing of an item to be asked about (Experiment 5). The present study suggests that an exogenous temporal cue automatically enhances the recognition accuracy for an item that is presented at close temporal proximity to the cue and that recognition memory enhancement occurs in an object-based manner.

Implications of Animal Object Memory Research for Human Amnesia

ERIC Educational Resources Information Center

Winters, Boyer D.; Saksida, Lisa M.; Bussey, Timothy J.

2010-01-01

Damage to structures in the human medial temporal lobe causes severe memory impairment. Animal object recognition tests gained prominence from attempts to model "global" human medial temporal lobe amnesia, such as that observed in patient HM. These tasks, such as delayed nonmatching-to-sample and spontaneous object recognition, for assessing…

Multichannel Compression, Temporal Cues, and Audibility.

ERIC Educational Resources Information Center

Souza, Pamela E.; Turner, Christopher W.

1998-01-01

The effect of the reduction of the temporal envelope produced by multichannel compression on recognition was examined in 16 listeners with hearing loss, with particular focus on audibility of the speech signal. Multichannel compression improved speech recognition when superior audibility was provided by a two-channel compression system over linear…

Efficient visual object and word recognition relies on high spatial frequency coding in the left posterior fusiform gyrus: evidence from a case-series of patients with ventral occipito-temporal cortex damage.

PubMed

Roberts, Daniel J; Woollams, Anna M; Kim, Esther; Beeson, Pelagie M; Rapcsak, Steven Z; Lambon Ralph, Matthew A

2013-11-01

Recent visual neuroscience investigations suggest that ventral occipito-temporal cortex is retinotopically organized, with high acuity foveal input projecting primarily to the posterior fusiform gyrus (pFG), making this region crucial for coding high spatial frequency information. Because high spatial frequencies are critical for fine-grained visual discrimination, we hypothesized that damage to the left pFG should have an adverse effect not only on efficient reading, as observed in pure alexia, but also on the processing of complex non-orthographic visual stimuli. Consistent with this hypothesis, we obtained evidence that a large case series (n = 20) of patients with lesions centered on left pFG: 1) Exhibited reduced sensitivity to high spatial frequencies; 2) demonstrated prolonged response latencies both in reading (pure alexia) and object naming; and 3) were especially sensitive to visual complexity and similarity when discriminating between novel visual patterns. These results suggest that the patients' dual reading and non-orthographic recognition impairments have a common underlying mechanism and reflect the loss of high spatial frequency visual information normally coded in the left pFG.

An early illness recognition framework using a temporal Smith Waterman algorithm and NLP.

PubMed

Hajihashemi, Zahra; Popescu, Mihail

2013-01-01

In this paper we propose a framework for detecting health patterns based on non-wearable sensor sequence similarity and natural language processing (NLP). In TigerPlace, an aging in place facility from Columbia, MO, we deployed 47 sensor networks together with a nursing electronic health record (EHR) system to provide early illness recognition. The proposed framework utilizes sensor sequence similarity and NLP on EHR nursing comments to automatically notify the physician when health problems are detected. The reported methodology is inspired by genomic sequence annotation using similarity algorithms such as Smith Waterman (SW). Similarly, for each sensor sequence, we associate health concepts extracted from the nursing notes using Metamap, a NLP tool provided by Unified Medical Language System (UMLS). Since sensor sequences, unlike genomics ones, have an associated time dimension we propose a temporal variant of SW (TSW) to account for time. The main challenges presented by our framework are finding the most suitable time sequence similarity and aggregation of the retrieved UMLS concepts. On a pilot dataset from three Tiger Place residents, with a total of 1685 sensor days and 626 nursing records, we obtained an average precision of 0.64 and a recall of 0.37.

Separable spectro-temporal Gabor filter bank features: Reducing the complexity of robust features for automatic speech recognition.

PubMed

Schädler, Marc René; Kollmeier, Birger

2015-04-01

To test if simultaneous spectral and temporal processing is required to extract robust features for automatic speech recognition (ASR), the robust spectro-temporal two-dimensional-Gabor filter bank (GBFB) front-end from Schädler, Meyer, and Kollmeier [J. Acoust. Soc. Am. 131, 4134-4151 (2012)] was de-composed into a spectral one-dimensional-Gabor filter bank and a temporal one-dimensional-Gabor filter bank. A feature set that is extracted with these separate spectral and temporal modulation filter banks was introduced, the separate Gabor filter bank (SGBFB) features, and evaluated on the CHiME (Computational Hearing in Multisource Environments) keywords-in-noise recognition task. From the perspective of robust ASR, the results showed that spectral and temporal processing can be performed independently and are not required to interact with each other. Using SGBFB features permitted the signal-to-noise ratio (SNR) to be lowered by 1.2 dB while still performing as well as the GBFB-based reference system, which corresponds to a relative improvement of the word error rate by 12.8%. Additionally, the real time factor of the spectro-temporal processing could be reduced by more than an order of magnitude. Compared to human listeners, the SNR needed to be 13 dB higher when using Mel-frequency cepstral coefficient features, 11 dB higher when using GBFB features, and 9 dB higher when using SGBFB features to achieve the same recognition performance.

Assessment of Spectral and Temporal Resolution in Cochlear Implant Users Using Psychoacoustic Discrimination and Speech Cue Categorization.

PubMed

Winn, Matthew B; Won, Jong Ho; Moon, Il Joon

This study was conducted to measure auditory perception by cochlear implant users in the spectral and temporal domains, using tests of either categorization (using speech-based cues) or discrimination (using conventional psychoacoustic tests). The authors hypothesized that traditional nonlinguistic tests assessing spectral and temporal auditory resolution would correspond to speech-based measures assessing specific aspects of phonetic categorization assumed to depend on spectral and temporal auditory resolution. The authors further hypothesized that speech-based categorization performance would ultimately be a superior predictor of speech recognition performance, because of the fundamental nature of speech recognition as categorization. Nineteen cochlear implant listeners and 10 listeners with normal hearing participated in a suite of tasks that included spectral ripple discrimination, temporal modulation detection, and syllable categorization, which was split into a spectral cue-based task (targeting the /ba/-/da/ contrast) and a timing cue-based task (targeting the /b/-/p/ and /d/-/t/ contrasts). Speech sounds were manipulated to contain specific spectral or temporal modulations (formant transitions or voice onset time, respectively) that could be categorized. Categorization responses were quantified using logistic regression to assess perceptual sensitivity to acoustic phonetic cues. Word recognition testing was also conducted for cochlear implant listeners. Cochlear implant users were generally less successful at utilizing both spectral and temporal cues for categorization compared with listeners with normal hearing. For the cochlear implant listener group, spectral ripple discrimination was significantly correlated with the categorization of formant transitions; both were correlated with better word recognition. Temporal modulation detection using 100- and 10-Hz-modulated noise was not correlated either with the cochlear implant subjects' categorization of voice onset time or with word recognition. Word recognition was correlated more closely with categorization of the controlled speech cues than with performance on the psychophysical discrimination tasks. When evaluating people with cochlear implants, controlled speech-based stimuli are feasible to use in tests of auditory cue categorization, to complement traditional measures of auditory discrimination. Stimuli based on specific speech cues correspond to counterpart nonlinguistic measures of discrimination, but potentially show better correspondence with speech perception more generally. The ubiquity of the spectral (formant transition) and temporal (voice onset time) stimulus dimensions across languages highlights the potential to use this testing approach even in cases where English is not the native language.

A unified framework for the functional organization of the medial temporal lobes and the phenomenology of episodic memory.

PubMed

Ranganath, Charan

2010-11-01

There is currently an intense debate about the nature of recognition memory and about the roles of medial temporal lobe subregions in recognition memory processes. At a larger level, this debate has been about whether it is appropriate to propose unified theories to explain memory at neural, functional, and phenomenological levels of analysis. Here, I review findings from physiology, functional imaging, and lesion studies in humans, monkeys, and rodents relevant to the roles of medial temporal lobe subregions in recognition memory, as well as in short-term memory and perception. The results from these studies are consistent with the idea that there is functional heterogeneity in the medial temporal lobes, although the differences among medial temporal lobe subregions do not precisely correspond to different types of memory tasks, cognitive processes, or states of awareness. Instead, the evidence is consistent with the idea that medial temporal lobe subregions differ in terms of the kind of information they process and represent, and that these regions collectively support episodic memory by binding item and context information. © 2010 Wiley-Liss, Inc.

The role of spectral and temporal cues in voice gender discrimination by normal-hearing listeners and cochlear implant users.

PubMed

Fu, Qian-Jie; Chinchilla, Sherol; Galvin, John J

2004-09-01

The present study investigated the relative importance of temporal and spectral cues in voice gender discrimination and vowel recognition by normal-hearing subjects listening to an acoustic simulation of cochlear implant speech processing and by cochlear implant users. In the simulation, the number of speech processing channels ranged from 4 to 32, thereby varying the spectral resolution; the cutoff frequencies of the channels' envelope filters ranged from 20 to 320 Hz, thereby manipulating the available temporal cues. For normal-hearing subjects, results showed that both voice gender discrimination and vowel recognition scores improved as the number of spectral channels was increased. When only 4 spectral channels were available, voice gender discrimination significantly improved as the envelope filter cutoff frequency was increased from 20 to 320 Hz. For all spectral conditions, increasing the amount of temporal information had no significant effect on vowel recognition. Both voice gender discrimination and vowel recognition scores were highly variable among implant users. The performance of cochlear implant listeners was similar to that of normal-hearing subjects listening to comparable speech processing (4-8 spectral channels). The results suggest that both spectral and temporal cues contribute to voice gender discrimination and that temporal cues are especially important for cochlear implant users to identify the voice gender when there is reduced spectral resolution.

The Temporal Dynamics of Spoken Word Recognition in Adverse Listening Conditions

ERIC Educational Resources Information Center

Brouwer, Susanne; Bradlow, Ann R.

2016-01-01

This study examined the temporal dynamics of spoken word recognition in noise and background speech. In two visual-world experiments, English participants listened to target words while looking at four pictures on the screen: a target (e.g. "candle"), an onset competitor (e.g. "candy"), a rhyme competitor (e.g.…

Hemispheric asymmetries of a motor memory in a recognition test after learning a movement sequence.

PubMed

Leinen, Peter; Panzer, Stefan; Shea, Charles H

2016-11-01

Two experiments utilizing a spatial-temporal movement sequence were designed to determine if the memory of the sequence is lateralized in the left or right hemisphere. In Experiment 1, dominant right-handers were randomly assigned to one of two acquisition groups: a left-hand starter and a right-hand starter group. After an acquisition phase, reaction time (RT) was measured in a recognition test by providing the learned sequential pattern in the left or right visual half-field for 150ms. In a retention test and two transfer tests the dominant coordinate system for sequence production was evaluated. In Experiment 2 dominant left-handers and dominant right-handers had to acquire the sequence with their dominant limb. The results of Experiment 1 indicated that RT was significantly shorter when the acquired sequence was provided in the right visual field during the recognition test. The same results occurred in Experiment 2 for dominant right-handers and left-handers. These results indicated a right visual field left hemisphere advantage in the recognition test for the practiced stimulus for dominant left and right-handers, when the task was practiced with the dominant limb. Copyright © 2016 Elsevier B.V. All rights reserved.

An fMRI comparison of neural activity associated with recognition of familiar melodies in younger and older adults

PubMed Central

Sikka, Ritu; Cuddy, Lola L.; Johnsrude, Ingrid S.; Vanstone, Ashley D.

2015-01-01

Several studies of semantic memory in non-musical domains involving recognition of items from long-term memory have shown an age-related shift from the medial temporal lobe structures to the frontal lobe. However, the effects of aging on musical semantic memory remain unexamined. We compared activation associated with recognition of familiar melodies in younger and older adults. Recognition follows successful retrieval from the musical lexicon that comprises a lifetime of learned musical phrases. We used the sparse-sampling technique in fMRI to determine the neural correlates of melody recognition by comparing activation when listening to familiar vs. unfamiliar melodies, and to identify age differences. Recognition-related cortical activation was detected in the right superior temporal, bilateral inferior and superior frontal, left middle orbitofrontal, bilateral precentral, and left supramarginal gyri. Region-of-interest analysis showed greater activation for younger adults in the left superior temporal gyrus and for older adults in the left superior frontal, left angular, and bilateral superior parietal regions. Our study provides powerful evidence for these musical memory networks due to a large sample (N = 40) that includes older adults. This study is the first to investigate the neural basis of melody recognition in older adults and to compare the findings to younger adults. PMID:26500480

Reference frames for spatial frequency in face representation differ in the temporal visual cortex and amygdala.

PubMed

Inagaki, Mikio; Fujita, Ichiro

2011-07-13

Social communication in nonhuman primates and humans is strongly affected by facial information from other individuals. Many cortical and subcortical brain areas are known to be involved in processing facial information. However, how the neural representation of faces differs across different brain areas remains unclear. Here, we demonstrate that the reference frame for spatial frequency (SF) tuning of face-responsive neurons differs in the temporal visual cortex and amygdala in monkeys. Consistent with psychophysical properties for face recognition, temporal cortex neurons were tuned to image-based SFs (cycles/image) and showed viewing distance-invariant representation of face patterns. On the other hand, many amygdala neurons were influenced by retina-based SFs (cycles/degree), a characteristic that is useful for social distance computation. The two brain areas also differed in the luminance contrast sensitivity of face-responsive neurons; amygdala neurons sharply reduced their responses to low luminance contrast images, while temporal cortex neurons maintained the level of their responses. From these results, we conclude that different types of visual processing in the temporal visual cortex and the amygdala contribute to the construction of the neural representations of faces.

Discrimination of acoustic communication signals by grasshoppers (Chorthippus biguttulus): temporal resolution, temporal integration, and the impact of intrinsic noise.

PubMed

Ronacher, Bernhard; Wohlgemuth, Sandra; Vogel, Astrid; Krahe, Rüdiger

2008-08-01

A characteristic feature of hearing systems is their ability to resolve both fast and subtle amplitude modulations of acoustic signals. This applies also to grasshoppers, which for mate identification rely mainly on the characteristic temporal patterns of their communication signals. Usually the signals arriving at a receiver are contaminated by various kinds of noise. In addition to extrinsic noise, intrinsic noise caused by stochastic processes within the nervous system contributes to making signal recognition a difficult task. The authors asked to what degree intrinsic noise affects temporal resolution and, particularly, the discrimination of similar acoustic signals. This study aims at exploring the neuronal basis for sexual selection, which depends on exploiting subtle differences between basically similar signals. Applying a metric, by which the similarities of spike trains can be assessed, the authors investigated how well the communication signals of different individuals of the same species could be discriminated and correctly classified based on the responses of auditory neurons. This spike train metric yields clues to the optimal temporal resolution with which spike trains should be evaluated. (c) 2008 APA, all rights reserved

Self-recognition of avatar motion: how do I know it's me?

PubMed

Cook, Richard; Johnston, Alan; Heyes, Cecilia

2012-02-22

When motion is isolated from form cues and viewed from third-person perspectives, individuals are able to recognize their own whole body movements better than those of friends. Because we rarely see our own bodies in motion from third-person viewpoints, this self-recognition advantage may indicate a contribution to perception from the motor system. Our first experiment provides evidence that recognition of self-produced and friends' motion dissociate, with only the latter showing sensitivity to orientation. Through the use of selectively disrupted avatar motion, our second experiment shows that self-recognition of facial motion is mediated by knowledge of the local temporal characteristics of one's own actions. Specifically, inverted self-recognition was unaffected by disruption of feature configurations and trajectories, but eliminated by temporal distortion. While actors lack third-person visual experience of their actions, they have a lifetime of proprioceptive, somatosensory, vestibular and first-person-visual experience. These sources of contingent feedback may provide actors with knowledge about the temporal properties of their actions, potentially supporting recognition of characteristic rhythmic variation when viewing self-produced motion. In contrast, the ability to recognize the motion signatures of familiar others may be dependent on configural topographic cues.

An ultra-sparse code underliesthe generation of neural sequences in a songbird

NASA Astrophysics Data System (ADS)

Hahnloser, Richard H. R.; Kozhevnikov, Alexay A.; Fee, Michale S.

2002-09-01

Sequences of motor activity are encoded in many vertebrate brains by complex spatio-temporal patterns of neural activity; however, the neural circuit mechanisms underlying the generation of these pre-motor patterns are poorly understood. In songbirds, one prominent site of pre-motor activity is the forebrain robust nucleus of the archistriatum (RA), which generates stereotyped sequences of spike bursts during song and recapitulates these sequences during sleep. We show that the stereotyped sequences in RA are driven from nucleus HVC (high vocal centre), the principal pre-motor input to RA. Recordings of identified HVC neurons in sleeping and singing birds show that individual HVC neurons projecting onto RA neurons produce bursts sparsely, at a single, precise time during the RA sequence. These HVC neurons burst sequentially with respect to one another. We suggest that at each time in the RA sequence, the ensemble of active RA neurons is driven by a subpopulation of RA-projecting HVC neurons that is active only at that time. As a population, these HVC neurons may form an explicit representation of time in the sequence. Such a sparse representation, a temporal analogue of the `grandmother cell' concept for object recognition, eliminates the problem of temporal interference during sequence generation and learning attributed to more distributed representations.

Learning and disrupting invariance in visual recognition with a temporal association rule

PubMed Central

Isik, Leyla; Leibo, Joel Z.; Poggio, Tomaso

2012-01-01

Learning by temporal association rules such as Foldiak's trace rule is an attractive hypothesis that explains the development of invariance in visual recognition. Consistent with these rules, several recent experiments have shown that invariance can be broken at both the psychophysical and single cell levels. We show (1) that temporal association learning provides appropriate invariance in models of object recognition inspired by the visual cortex, (2) that we can replicate the “invariance disruption” experiments using these models with a temporal association learning rule to develop and maintain invariance, and (3) that despite dramatic single cell effects, a population of cells is very robust to these disruptions. We argue that these models account for the stability of perceptual invariance despite the underlying plasticity of the system, the variability of the visual world and expected noise in the biological mechanisms. PMID:22754523

Repetition Suppression and Reactivation in Auditory–Verbal Short-Term Recognition Memory

PubMed Central

D'Esposito, Mark

2009-01-01

The neural response to stimulus repetition is not uniform across brain regions, stimulus modalities, or task contexts. For instance, it has been observed in many functional magnetic resonance imaging (fMRI) studies that sometimes stimulus repetition leads to a relative reduction in neural activity (repetition suppression), whereas in other cases repetition results in a relative increase in activity (repetition enhancement). In the present study, we hypothesized that in the context of a verbal short-term recognition memory task, repetition-related “increases” should be observed in the same posterior temporal regions that have been previously associated with “persistent activity” in working memory rehearsal paradigms. We used fMRI and a continuous recognition memory paradigm with short lags to examine repetition effects in the posterior and anterior regions of the superior temporal cortex. Results showed that, consistent with our hypothesis, the 2 posterior temporal regions consistently associated with working memory maintenance, also show repetition increases during short-term recognition memory. In contrast, a region in the anterior superior temporal lobe showed repetition suppression effects, consistent with previous research work on perceptual adaptation in the auditory–verbal domain. We interpret these results in light of recent theories of the functional specialization along the anterior and posterior axes of the superior temporal lobe. PMID:18987393

Repetition suppression and reactivation in auditory-verbal short-term recognition memory.

PubMed

Buchsbaum, Bradley R; D'Esposito, Mark

2009-06-01

The neural response to stimulus repetition is not uniform across brain regions, stimulus modalities, or task contexts. For instance, it has been observed in many functional magnetic resonance imaging (fMRI) studies that sometimes stimulus repetition leads to a relative reduction in neural activity (repetition suppression), whereas in other cases repetition results in a relative increase in activity (repetition enhancement). In the present study, we hypothesized that in the context of a verbal short-term recognition memory task, repetition-related "increases" should be observed in the same posterior temporal regions that have been previously associated with "persistent activity" in working memory rehearsal paradigms. We used fMRI and a continuous recognition memory paradigm with short lags to examine repetition effects in the posterior and anterior regions of the superior temporal cortex. Results showed that, consistent with our hypothesis, the 2 posterior temporal regions consistently associated with working memory maintenance, also show repetition increases during short-term recognition memory. In contrast, a region in the anterior superior temporal lobe showed repetition suppression effects, consistent with previous research work on perceptual adaptation in the auditory-verbal domain. We interpret these results in light of recent theories of the functional specialization along the anterior and posterior axes of the superior temporal lobe.

Orientation Encoding and Viewpoint Invariance in Face Recognition: Inferring Neural Properties from Large-Scale Signals.

PubMed

Ramírez, Fernando M

2018-05-01

Viewpoint-invariant face recognition is thought to be subserved by a distributed network of occipitotemporal face-selective areas that, except for the human anterior temporal lobe, have been shown to also contain face-orientation information. This review begins by highlighting the importance of bilateral symmetry for viewpoint-invariant recognition and face-orientation perception. Then, monkey electrophysiological evidence is surveyed describing key tuning properties of face-selective neurons-including neurons bimodally tuned to mirror-symmetric face-views-followed by studies combining functional magnetic resonance imaging (fMRI) and multivariate pattern analyses to probe the representation of face-orientation and identity information in humans. Altogether, neuroimaging studies suggest that face-identity is gradually disentangled from face-orientation information along the ventral visual processing stream. The evidence seems to diverge, however, regarding the prevalent form of tuning of neural populations in human face-selective areas. In this context, caveats possibly leading to erroneous inferences regarding mirror-symmetric coding are exposed, including the need to distinguish angular from Euclidean distances when interpreting multivariate pattern analyses. On this basis, this review argues that evidence from the fusiform face area is best explained by a view-sensitive code reflecting head angular disparity, consistent with a role of this area in face-orientation perception. Finally, the importance is stressed of explicit models relating neural properties to large-scale signals.

Patterns of False Memory in Patients with Huntington's Disease.

PubMed

Chen, I-Wen; Chen, Chiung-Mei; Wu, Yih-Ru; Hua, Mau-Sun

2017-06-01

Increased false memory recognition in patients with Huntington's disease (HD) has been widely reported; however, the underlying memory constructive processes remain unclear. The present study explored gist memory, item-specific memory, and monitoring ability in patients with HD. Twenty-five patients (including 13 patients with mild HD and 12 patients with moderate-to-severe HD) and 30 healthy comparison participants (HC) were recruited. We used the Deese-Roediger-McDermott (DRM) paradigm to investigate participants' false recognition patterns, along with neuropsychological tests to assess general cognitive function. Both mild and moderate-to-severe patients with HD showed significant executive functioning and episodic memory impairment. On the DRM tasks, both HD patient groups showed significantly impaired performance in tasks assessing unrelated false recognition and item-specific memory as compared to the HC group; moderate-to-severe patients performed more poorly than mild patients did. Only moderate-severe patients exhibited significantly poorer related false recognition index scores than HCs in the verbal DRM task; performance of HD patient groups was comparable to the HC group on the pictorial DRM task. It appears that diminished verbatim memory and monitoring ability are early signs of cognitive decline during the HD course. Conversely, gist memory is relatively robust, with only partial decline during advanced-stage HD. Our findings suggest that medial temporal lobe function is relatively preserved compared to that of frontal-related structures in early HD. Thus, gist-based memory rehabilitation programs might be beneficial for patients with HD. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Dual Coding of Frequency Modulation in the Ventral Cochlear Nucleus.

PubMed

Paraouty, Nihaad; Stasiak, Arkadiusz; Lorenzi, Christian; Varnet, Léo; Winter, Ian M

2018-04-25

Frequency modulation (FM) is a common acoustic feature of natural sounds and is known to play a role in robust sound source recognition. Auditory neurons show precise stimulus-synchronized discharge patterns that may be used for the representation of low-rate FM. However, it remains unclear whether this representation is based on synchronization to slow temporal envelope (ENV) cues resulting from cochlear filtering or phase locking to faster temporal fine structure (TFS) cues. To investigate the plausibility of those encoding schemes, single units of the ventral cochlear nucleus of guinea pigs of either sex were recorded in response to sine FM tones centered at the unit's best frequency (BF). The results show that, in contrast to high-BF units, for modulation depths within the receptive field, low-BF units (<4 kHz) demonstrate good phase locking to TFS. For modulation depths extending beyond the receptive field, the discharge patterns follow the ENV and fluctuate at the modulation rate. The receptive field proved to be a good predictor of the ENV responses for most primary-like and chopper units. The current in vivo data also reveal a high level of diversity in responses across unit types. TFS cues are mainly conveyed by low-frequency and primary-like units and ENV cues by chopper and onset units. The diversity of responses exhibited by cochlear nucleus neurons provides a neural basis for a dual-coding scheme of FM in the brainstem based on both ENV and TFS cues. SIGNIFICANCE STATEMENT Natural sounds, including speech, convey informative temporal modulations in frequency. Understanding how the auditory system represents those frequency modulations (FM) has important implications as robust sound source recognition depends crucially on the reception of low-rate FM cues. Here, we recorded 115 single-unit responses from the ventral cochlear nucleus in response to FM and provide the first physiological evidence of a dual-coding mechanism of FM via synchronization to temporal envelope cues and phase locking to temporal fine structure cues. We also demonstrate a diversity of neural responses with different coding specializations. These results support the dual-coding scheme proposed by psychophysicists to account for FM sensitivity in humans and provide new insights on how this might be implemented in the early stages of the auditory pathway. Copyright © 2018 the authors 0270-6474/18/384123-15$15.00/0.

Auditory Temporal Order Discrimination and Backward Recognition Masking in Adults with Dyslexia

ERIC Educational Resources Information Center

Griffiths, Yvonne M.; Hill, Nicholas I.; Bailey, Peter J.; Snowling, Margaret J.

2003-01-01

The ability of 20 adult dyslexic readers to extract frequency information from successive tone pairs was compared with that of IQ-matched controls using temporal order discrimination and auditory backward recognition masking (ABRM) tasks. In both paradigms, the interstimulus interval (ISI) between tones in a pair was either short (20 ms) or long…

Assessment of spectral and temporal resolution in cochlear implant users using psychoacoustic discrimination and speech cue categorization

PubMed Central

Winn, Matthew B.; Won, Jong Ho; Moon, Il Joon

2016-01-01

Objectives This study was conducted to measure auditory perception by cochlear implant users in the spectral and temporal domains, using tests of either categorization (using speech-based cues) or discrimination (using conventional psychoacoustic tests). We hypothesized that traditional nonlinguistic tests assessing spectral and temporal auditory resolution would correspond to speech-based measures assessing specific aspects of phonetic categorization assumed to depend on spectral and temporal auditory resolution. We further hypothesized that speech-based categorization performance would ultimately be a superior predictor of speech recognition performance, because of the fundamental nature of speech recognition as categorization. Design Nineteen CI listeners and 10 listeners with normal hearing (NH) participated in a suite of tasks that included spectral ripple discrimination (SRD), temporal modulation detection (TMD), and syllable categorization, which was split into a spectral-cue-based task (targeting the /ba/-/da/ contrast) and a timing-cue-based task (targeting the /b/-/p/ and /d/-/t/ contrasts). Speech sounds were manipulated in order to contain specific spectral or temporal modulations (formant transitions or voice onset time, respectively) that could be categorized. Categorization responses were quantified using logistic regression in order to assess perceptual sensitivity to acoustic phonetic cues. Word recognition testing was also conducted for CI listeners. Results CI users were generally less successful at utilizing both spectral and temporal cues for categorization compared to listeners with normal hearing. For the CI listener group, SRD was significantly correlated with the categorization of formant transitions; both were correlated with better word recognition. TMD using 100 Hz and 10 Hz modulated noise was not correlated with the CI subjects’ categorization of VOT, nor with word recognition. Word recognition was correlated more closely with categorization of the controlled speech cues than with performance on the psychophysical discrimination tasks. Conclusions When evaluating people with cochlear implants, controlled speech-based stimuli are feasible to use in tests of auditory cue categorization, to complement traditional measures of auditory discrimination. Stimuli based on specific speech cues correspond to counterpart non-linguistic measures of discrimination, but potentially show better correspondence with speech perception more generally. The ubiquity of the spectral (formant transition) and temporal (VOT) stimulus dimensions across languages highlights the potential to use this testing approach even in cases where English is not the native language. PMID:27438871

An fMRI study of semantic processing in men with schizophrenia

PubMed Central

Kubicki, M.; McCarley, R.W.; Nestor, P.G.; Huh, T.; Kikinis, R.; Shenton, M.E.; Wible, C.G.

2009-01-01

As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditions. Under the deep, semantic encoding condition, subjects made semantic judgments as to whether the words were abstract or concrete. Under the shallow, nonsemantic encoding condition, subjects made perceptual judgments of the font size (uppercase/lowercase) of the presented words. After performance of the behavioral task, a recognition test was used to assess the depth of processing effect, defined as better performance for semantically encoded words than for perceptually encoded words. For the scanned version only, the words for both conditions were repeated in order to assess repetition-priming effects. Reaction times were assessed in both testing scenarios. Both groups showed the expected depth of processing effect for recognition, and control subjects showed the expected increased activation of the left inferior prefrontal cortex (LIPC) under semantic encoding relative to perceptual encoding conditions as well as repetition priming for semantic conditions only. In contrast, schizophrenics showed similar patterns of fMRI activation regardless of condition. Most striking in relation to controls, patients showed decreased LIFC activation concurrent with increased left superior temporal gyrus activation for semantic encoding versus shallow encoding. Furthermore, schizophrenia subjects did not show the repetition priming effect, either behaviorally or as a decrease in LIPC activity. In patients with schizophrenia, LIFC underactivation and left superior temporal gyrus overactivation for semantically encoded words may reflect a disease-related disruption of a distributed frontal temporal network that is engaged in the representation and processing of meaning of words, text, and discourse and which may underlie schizophrenic thought disturbance. PMID:14683698

An fMRI study of semantic processing in men with schizophrenia.

PubMed

Kubicki, M; McCarley, R W; Nestor, P G; Huh, T; Kikinis, R; Shenton, M E; Wible, C G

2003-12-01

As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditions. Under the deep, semantic encoding condition, subjects made semantic judgments as to whether the words were abstract or concrete. Under the shallow, nonsemantic encoding condition, subjects made perceptual judgments of the font size (uppercase/lowercase) of the presented words. After performance of the behavioral task, a recognition test was used to assess the depth of processing effect, defined as better performance for semantically encoded words than for perceptually encoded words. For the scanned version only, the words for both conditions were repeated in order to assess repetition-priming effects. Reaction times were assessed in both testing scenarios. Both groups showed the expected depth of processing effect for recognition, and control subjects showed the expected increased activation of the left inferior prefrontal cortex (LIPC) under semantic encoding relative to perceptual encoding conditions as well as repetition priming for semantic conditions only. In contrast, schizophrenics showed similar patterns of fMRI activation regardless of condition. Most striking in relation to controls, patients showed decreased LIFC activation concurrent with increased left superior temporal gyrus activation for semantic encoding versus shallow encoding. Furthermore, schizophrenia subjects did not show the repetition priming effect, either behaviorally or as a decrease in LIPC activity. In patients with schizophrenia, LIFC underactivation and left superior temporal gyrus overactivation for semantically encoded words may reflect a disease-related disruption of a distributed frontal temporal network that is engaged in the representation and processing of meaning of words, text, and discourse and which may underlie schizophrenic thought disturbance.

Pattern recognition approach to the subsequent event of damaging earthquakes in Italy

NASA Astrophysics Data System (ADS)

Gentili, S.; Di Giovambattista, R.

2017-05-01

In this study, we investigate the occurrence of large aftershocks following the most significant earthquakes that occurred in Italy after 1980. In accordance with previous studies (Vorobieva and Panza, 1993; Vorobieva, 1999), we group clusters associated with mainshocks into two categories: ;type A; if, given a main shock of magnitude M, the subsequent strongest earthquake in the cluster has magnitude ≥M - 1 or type B otherwise. In this paper, we apply a pattern recognition approach using statistical features to foresee the class of the analysed clusters. The classification of the two categories is based on some features of the time, space, and magnitude distribution of the aftershocks. Specifically, we analyse the temporal evolution of the radiated energy at different elapsed times after the mainshock, the spatio-temporal evolution of the aftershocks occurring within a few days, and the probability of a strong earthquake. An attempt is made to classify the studied region into smaller seismic zones with a prevalence of type A and B clusters. We demonstrate that the two types of clusters have distinct preferred geographic locations inside the Italian territory that likely reflected key properties of the deforming regions, different crustal domains and faulting style. We use decision trees as classifiers of single features to characterize the features depending on the cluster type. The performance of the classification is tested by the Leave-One-Out method. The analysis is performed on different time-spans after the mainshock to simulate the dependence of the accuracy on the information available as data increased over a longer period with increasing time after the mainshock.

Profiles of cognitive dysfunction in chronic amphetamine and heroin abusers.

PubMed

Ornstein, T J; Iddon, J L; Baldacchino, A M; Sahakian, B J; London, M; Everitt, B J; Robbins, T W

2000-08-01

Groups of subjects whose primary drug of abuse was amphetamine or heroin were compared, together with age- and IQ-matched control subjects. The study consisted of a neuropsychological test battery which included both conventional tests and also computerised tests of recognition memory, spatial working memory, planning, sequence generation, visual discrimination learning, and attentional set-shifting. Many of these tests have previously been shown to be sensitive to cortical damage (including selective lesions of the temporal or frontal lobes) and to cognitive deficits in dementia, basal ganglia disease, and neuropsychiatric disorder. Qualitative differences, as well as some commonalities, were found in the profile of cognitive impairment between the two groups. The chronic amphetamine abusers were significantly impaired in performance on the extra-dimensional shift task (a core component of the Wisconsin Card Sort Test) whereas in contrast, the heroin abusers were impaired in learning the normally easier intra-dimensional shift component. Both groups were impaired in some of tests of spatial working memory. However, the amphetamine group, unlike the heroin group, were not deficient in an index of strategic performance on this test. The heroin group failed to show significant improvement between two blocks of a sequence generation task after training and additionally exhibited more perseverative behavior on this task. The two groups were profoundly, but equivalently impaired on a test of pattern recognition memory sensitive to temporal lobe dysfunction. These results indicate that chronic drug use may lead to distinct patterns of cognitive impairment that may be associated with dysfunction of different components of cortico-striatal circuitry.

HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition.

PubMed

James, Alex Pappachen; Fedorova, Irina; Ibrayev, Timur; Kudithipudi, Dhireesha

2017-06-01

Hierarchical Temporal Memory (HTM) is an online machine learning algorithm that emulates the neo-cortex. The development of a scalable on-chip HTM architecture is an open research area. The two core substructures of HTM are spatial pooler and temporal memory. In this work, we propose a new Spatial Pooler circuit design with parallel memristive crossbar arrays for the 2D columns. The proposed design was validated on two different benchmark datasets, face recognition, and speech recognition. The circuits are simulated and analyzed using a practical memristor device model and 0.18 μm IBM CMOS technology model. The databases AR, YALE, ORL, and UFI, are used to test the performance of the design in face recognition. TIMIT dataset is used for the speech recognition.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

PubMed

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

The involvement of emotion recognition in affective theory of mind.

PubMed

Mier, Daniela; Lis, Stefanie; Neuthe, Kerstin; Sauer, Carina; Esslinger, Christine; Gallhofer, Bernd; Kirsch, Peter

2010-11-01

This study was conducted to explore the relationship between emotion recognition and affective Theory of Mind (ToM). Forty subjects performed a facial emotion recognition and an emotional intention recognition task (affective ToM) in an event-related fMRI study. Conjunction analysis revealed overlapping activation during both tasks. Activation in some of these conjunctly activated regions was even stronger during affective ToM than during emotion recognition, namely in the inferior frontal gyrus, the superior temporal sulcus, the temporal pole, and the amygdala. In contrast to previous studies investigating ToM, we found no activation in the anterior cingulate, commonly assumed as the key region for ToM. The results point to a close relationship of emotion recognition and affective ToM and can be interpreted as evidence for the assumption that at least basal forms of ToM occur by an embodied, non-cognitive process. Copyright © 2010 Society for Psychophysiological Research.

Recognition of emotion with temporal lobe epilepsy and asymmetrical amygdala damage.

PubMed

Fowler, Helen L; Baker, Gus A; Tipples, Jason; Hare, Dougal J; Keller, Simon; Chadwick, David W; Young, Andrew W

2006-08-01

Impairments in emotion recognition occur when there is bilateral damage to the amygdala. In this study, ability to recognize auditory and visual expressions of emotion was investigated in people with asymmetrical amygdala damage (AAD) and temporal lobe epilepsy (TLE). Recognition of five emotions was tested across three participant groups: those with right AAD and TLE, those with left AAD and TLE, and a comparison group. Four tasks were administered: recognition of emotion from facial expressions, sentences describing emotion-laden situations, nonverbal sounds, and prosody. Accuracy scores for each task and emotion were analysed, and no consistent overall effect of AAD on emotion recognition was found. However, some individual participants with AAD were significantly impaired at recognizing emotions, in both auditory and visual domains. The findings indicate that a minority of individuals with AAD have impairments in emotion recognition, but no evidence of specific impairments (e.g., visual or auditory) was found.

Shapes displayed with durations in the microsecond range do not obey Bloch's law of temporal summation

PubMed Central

Greene, Ernest; Ogden, R. Todd

2013-01-01

Shape patterns were displayed with simultaneous brief flashes from a light-emitting diode array. Flash durations in the microsecond range and luminous intensities were adjusted to vary the degree of successful shape recognition. Four experiments were conducted to test whether Bloch's law would apply in this task. Bloch's law holds that for very brief flashes the perceptual threshold is determined by the total number of photons being delivered, i.e., there is reciprocity of intensity and duration. The present results did not find that effectiveness of flashes was based on the total quantity of photons, as predicted by Bloch's law. Additionally, the evidence points to a visual mechanism that has ultra-high temporal precision that either registers the rate of photon flux or the duration of flashes. PMID:24349700

Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model

PubMed Central

Dou, Fei; Jia, Limin; Wang, Li; Xu, Jie; Huang, Yakun

2014-01-01

Passenger flow forecast is of essential importance to the organization of railway transportation and is one of the most important basics for the decision-making on transportation pattern and train operation planning. Passenger flow of high-speed railway features the quasi-periodic variations in a short time and complex nonlinear fluctuation because of existence of many influencing factors. In this study, a fuzzy temporal logic based passenger flow forecast model (FTLPFFM) is presented based on fuzzy logic relationship recognition techniques that predicts the short-term passenger flow for high-speed railway, and the forecast accuracy is also significantly improved. An applied case that uses the real-world data illustrates the precision and accuracy of FTLPFFM. For this applied case, the proposed model performs better than the k-nearest neighbor (KNN) and autoregressive integrated moving average (ARIMA) models. PMID:25431586

A bio-inspired system for spatio-temporal recognition in static and video imagery

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

2007-04-01

This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

Face recognition system and method using face pattern words and face pattern bytes

DOEpatents

Zheng, Yufeng

2014-12-23

The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

Is it about the self or the significance? An fMRI study of self-name recognition.

PubMed

Tacikowski, P; Brechmann, A; Marchewka, A; Jednoróg, K; Dobrowolny, M; Nowicka, A

2011-01-01

Our own name, due to its high social relevance, is supposed to have a unique status in our information processing. However, demonstrating this phenomenon empirically proves difficult as famous and unknown names, to which self-name is often compared in the studies, may differ from self-name not only in terms of the 'me vs. not-me' distinction, but also as regards their emotional content and frequency of occurrence in everyday life. In this fMRI study, apart from famous and unknown names we used the names of the most important persons in our subjects' lives. When compared to famous or unknown names recognition, self-name recognition was associated with robust activations in widely distributed bilateral network including fronto-temporal, limbic and subcortical structures, however, when compared to significant other's name, the activations were present specifically in the right inferior frontal gyrus. In addition, the significant other's name produced a similar pattern of activations to the one activated by self-name. These results suggest that the differences between own and other's name processing may rather be quantitative than qualitative in nature.

Using Temporal Modulation Sensitivity to Select Stimulation Sites for Processor MAPs in Cochlear Implant Listeners

PubMed Central

Garadat, Soha N.; Zwolan, Teresa A.; Pfingst, Bryan E.

2013-01-01

Previous studies in our laboratory showed that temporal acuity as assessed by modulation detection thresholds (MDTs) varied across activation sites and that this site-to-site variability was subject specific. Using two 10-channel MAPs, the previous experiments showed that processor MAPs that had better across-site mean (ASM) MDTs yielded better speech recognition than MAPs with poorer ASM MDTs tested in the same subject. The current study extends our earlier work on developing more optimal fitting strategies to test the feasibility of using a site-selection approach in the clinical domain. This study examined the hypothesis that revising the clinical speech processor MAP for cochlear implant (CI) recipients by turning off selected sites that have poorer temporal acuity and reallocating frequencies to the remaining electrodes would lead to improved speech recognition. Twelve CI recipients participated in the experiments. We found that site selection procedure based on MDTs in the presence of a masker resulted in improved performance on consonant recognition and recognition of sentences in noise. In contrast, vowel recognition was poorer with the experimental MAP than with the clinical MAP, possibly due to reduced spectral resolution when sites were removed from the experimental MAP. Overall, these results suggest a promising path for improving recipient outcomes using personalized processor-fitting strategies based on a psychophysical measure of temporal acuity. PMID:23881208

Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.

Classifying Lower Extremity Muscle Fatigue during Walking using Machine Learning and Inertial Sensors

PubMed Central

Zhang, Jian; Lockhart, Thurmon E.; Soangra, Rahul

2013-01-01

Fatigue in lower extremity musculature is associated with decline in postural stability, motor performance and alters normal walking patterns in human subjects. Automated recognition of lower extremity muscle fatigue condition may be advantageous in early detection of fall and injury risks. Supervised machine learning methods such as Support Vector Machines (SVM) have been previously used for classifying healthy and pathological gait patterns and also for separating old and young gait patterns. In this study we explore the classification potential of SVM in recognition of gait patterns utilizing an inertial measurement unit associated with lower extremity muscular fatigue. Both kinematic and kinetic gait patterns of 17 participants (29±11 years) were recorded and analyzed in normal and fatigued state of walking. Lower extremities were fatigued by performance of a squatting exercise until the participants reached 60% of their baseline maximal voluntary exertion level. Feature selection methods were used to classify fatigue and no-fatigue conditions based on temporal and frequency information of the signals. Additionally, influences of three different kernel schemes (i.e., linear, polynomial, and radial basis function) were investigated for SVM classification. The results indicated that lower extremity muscle fatigue condition influenced gait and loading responses. In terms of the SVM classification results, an accuracy of 96% was reached in distinguishing the two gait patterns (fatigue and no-fatigue) within the same subject using the kinematic, time and frequency domain features. It is also found that linear kernel and RBF kernel were equally good to identify intra-individual fatigue characteristics. These results suggest that intra-subject fatigue classification using gait patterns from an inertial sensor holds considerable potential in identifying “at-risk” gait due to muscle fatigue. PMID:24081829

Macro-Scale Patterns in Upwelling/Downwelling Activity at North American West Coast

PubMed Central

Saldívar-Lucio, Romeo; Di Lorenzo, Emanuele; Nakamura, Miguel; Villalobos, Héctor; Lluch-Cota, Daniel; Del Monte-Luna, Pablo

2016-01-01

The seasonal and interannual variability of vertical transport (upwelling/downwelling) has been relatively well studied, mainly for the California Current System, including low-frequency changes and latitudinal heterogeneity. The aim of this work was to identify potentially predictable patterns in upwelling/downwelling activity along the North American west coast and discuss their plausible mechanisms. To this purpose we applied the min/max Autocorrelation Factor technique and time series analysis. We found that spatial co-variation of seawater vertical movements present three dominant low-frequency signals in the range of 33, 19 and 11 years, resembling periodicities of: atmospheric circulation, nodal moon tides and solar activity. Those periodicities might be related to the variability of vertical transport through their influence on dominant wind patterns, the position/intensity of pressure centers and the strength of atmospheric circulation cells (wind stress). The low-frequency signals identified in upwelling/downwelling are coherent with temporal patterns previously reported at the study region: sea surface temperature along the Pacific coast of North America, catch fluctuations of anchovy Engraulis mordax and sardine Sardinops sagax, the Pacific Decadal Oscillation, changes in abundance and distribution of salmon populations, and variations in the position and intensity of the Aleutian low. Since the vertical transport is an oceanographic process with strong biological relevance, the recognition of their spatio-temporal patterns might allow for some reasonable forecasting capacity, potentially useful for marine resources management of the region. PMID:27893826

Temporal Dynamics of Host Molecular Responses Differentiate Symptomatic and Asymptomatic Influenza A Infection

PubMed Central

Huang, Yongsheng; Zaas, Aimee K.; Rao, Arvind; Dobigeon, Nicolas; Woolf, Peter J.; Veldman, Timothy; Øien, N. Christine; McClain, Micah T.; Varkey, Jay B.; Nicholson, Bradley; Carin, Lawrence; Kingsmore, Stephen; Woods, Christopher W.; Ginsburg, Geoffrey S.; Hero, Alfred O.

2011-01-01

Exposure to influenza viruses is necessary, but not sufficient, for healthy human hosts to develop symptomatic illness. The host response is an important determinant of disease progression. In order to delineate host molecular responses that differentiate symptomatic and asymptomatic Influenza A infection, we inoculated 17 healthy adults with live influenza (H3N2/Wisconsin) and examined changes in host peripheral blood gene expression at 16 timepoints over 132 hours. Here we present distinct transcriptional dynamics of host responses unique to asymptomatic and symptomatic infections. We show that symptomatic hosts invoke, simultaneously, multiple pattern recognition receptors-mediated antiviral and inflammatory responses that may relate to virus-induced oxidative stress. In contrast, asymptomatic subjects tightly regulate these responses and exhibit elevated expression of genes that function in antioxidant responses and cell-mediated responses. We reveal an ab initio molecular signature that strongly correlates to symptomatic clinical disease and biomarkers whose expression patterns best discriminate early from late phases of infection. Our results establish a temporal pattern of host molecular responses that differentiates symptomatic from asymptomatic infections and reveals an asymptomatic host-unique non-passive response signature, suggesting novel putative molecular targets for both prognostic assessment and ameliorative therapeutic intervention in seasonal and pandemic influenza. PMID:21901105

Cerebral blood flow relationships associated with a difficult tone recognition task in trained normal volunteers.

PubMed

Holcomb, H H; Medoff, D R; Caudill, P J; Zhao, Z; Lahti, A C; Dannals, R F; Tamminga, C A

1998-09-01

Tone recognition is partially subserved by neural activity in the right frontal and primary auditory cortices. First we determined the brain areas associated with tone perception and recognition. This study then examined how regional cerebral blood flow (rCBF) in these and other brain regions correlates with the behavioral characteristics of a difficult tone recognition task. rCBF changes were assessed using H2(15)O positron emission tomography. Subtraction procedures were used to localize significant change regions and correlational analyses were applied to determine how response times (RT) predicted rCBF patterns. Twelve trained normal volunteers were studied in three conditions: REST, sensory motor control (SMC) and decision (DEC). The SMC-REST contrast revealed bilateral activation of primary auditory cortices, cerebellum and bilateral inferior frontal gyri. DEC-SMC produced significant clusters in the right middle and inferior frontal gyri, insula and claustrum; the anterior cingulate gyrus and supplementary motor area; the left insula/claustrum; and the left cerebellum. Correlational analyses, RT versus rCBF from DEC scans, showed a positive correlation in right inferior and middle frontal cortex; rCBF in bilateral auditory cortices and cerebellum exhibited significant negative correlations with RT These changes suggest that neural activity in the right frontal, superior temporal and cerebellar regions shifts back and forth in magnitude depending on whether tone recognition RT is relatively fast or slow, during a difficult, accurate assessment.

Pattern Recognition Using Artificial Neural Network: A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, artificial neural network techniques theory have been receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection of training and test samples, and performance evaluation. In spite of almost 50 years of research and development in this field, the general problem of recognizing complex patterns with arbitrary orientation, location, and scale remains unsolved. New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system using ANN and identify research topics and applications which are at the forefront of this exciting and challenging field.

Auditory Pattern Recognition and Brief Tone Discrimination of Children with Reading Disorders

ERIC Educational Resources Information Center

Walker, Marianna M.; Givens, Gregg D.; Cranford, Jerry L.; Holbert, Don; Walker, Letitia

2006-01-01

Auditory pattern recognition skills in children with reading disorders were investigated using perceptual tests involving discrimination of frequency and duration tonal patterns. A behavioral test battery involving recognition of the pattern of presentation of tone triads was used in which individual components differed in either frequency or…

Image pattern recognition supporting interactive analysis and graphical visualization

NASA Technical Reports Server (NTRS)

Coggins, James M.

1992-01-01

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

Understanding eye movements in face recognition using hidden Markov models.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2014-09-16

We use a hidden Markov model (HMM) based approach to analyze eye movement data in face recognition. HMMs are statistical models that are specialized in handling time-series data. We conducted a face recognition task with Asian participants, and model each participant's eye movement pattern with an HMM, which summarized the participant's scan paths in face recognition with both regions of interest and the transition probabilities among them. By clustering these HMMs, we showed that participants' eye movements could be categorized into holistic or analytic patterns, demonstrating significant individual differences even within the same culture. Participants with the analytic pattern had longer response times, but did not differ significantly in recognition accuracy from those with the holistic pattern. We also found that correct and wrong recognitions were associated with distinctive eye movement patterns; the difference between the two patterns lies in the transitions rather than locations of the fixations alone. © 2014 ARVO.

Segregation of anterior temporal regions critical for retrieving names of unique and non-unique entities reflects underlying long-range connectivity.

PubMed

Mehta, Sonya; Inoue, Kayo; Rudrauf, David; Damasio, Hanna; Tranel, Daniel; Grabowski, Thomas

2016-02-01

Lesion-deficit studies support the hypothesis that the left anterior temporal lobe (ATL) plays a critical role in retrieving names of concrete entities. They further suggest that different regions of the left ATL process different conceptual categories. Here we test the specificity of these relationships and whether the anatomical segregation is related to the underlying organization of white matter connections. We reanalyzed data from a previous lesion study of naming and recognition across five categories of concrete entities. In voxelwise logistic regressions of lesion-deficit associations, we formally incorporated measures of disconnection of long-range association fiber tracts (FTs) and covaried for recognition and non-category-specific naming deficits. We also performed fiber tractwise analyses to assess whether damage to specific FTs was preferentially associated with category-selective naming deficits. Damage to the basolateral ATL was associated with naming deficits for both unique (famous faces) and non-unique entities, whereas the damage to the temporal pole was associated with naming deficits for unique entities only. This segregation pattern remained after accounting for comorbid recognition deficits or naming deficits in other categories. The tractwise analyses showed that damage to the uncinate fasciculus (UNC) was associated with naming impairments for unique entities, while damage to the inferior longitudinal fasciculus (ILF) was associated with naming impairments for non-unique entities. Covarying for FT transection in voxelwise analyses rendered the cortical association for unique entities more focal. These results are consistent with the partial segregation of brain system support for name retrieval of unique and non-unique entities at both the level of cortical components and underlying white matter fiber bundles. Our study reconciles theoretic accounts of the functional organization of the left ATL by revealing both category-related processing and semantic hub sectors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Famous face identification in temporal lobe epilepsy: Support for a multimodal integration model of semantic memory

PubMed Central

Drane, Daniel L.; Ojemann, Jeffrey G.; Phatak, Vaishali; Loring, David W.; Gross, Robert E.; Hebb, Adam O.; Silbergeld, Daniel L.; Miller, John W.; Voets, Natalie L.; Saindane, Amit M.; Barsalou, Lawrence; Meador, Kimford J.; Ojemann, George A.; Tranel, Daniel

2012-01-01

This study aims to demonstrate that the left and right anterior temporal lobes (ATLs) perform critical but unique roles in famous face identification, with damage to either leading to differing deficit patterns reflecting decreased access to lexical or semantic concepts but not their degradation. Famous face identification was studied in 22 presurgical and 14 postsurgical temporal lobe epilepsy (TLE) patients and 20 healthy comparison subjects using free recall and multiple choice (MC) paradigms. Right TLE patients exhibited presurgical deficits in famous face recognition, and postsurgical deficits in both famous face recognition and familiarity judgments. However, they did not exhibit any problems with naming before or after surgery. In contrast, left TLE patients demonstrated both pre-and postsurgical deficits in famous face naming but no significant deficits in recognition or familiarity. Double dissociations in performance between groups were alleviated by altering task demands. Postsurgical right TLE patients provided with MC options correctly identified greater than 70% of famous faces they initially rated as unfamiliar. Left TLE patients accurately chose the name for nearly all famous faces they recognized (based on their verbal description) but initially failed to name, although they tended to rapidly lose access to this name. We believe alterations in task demands activate alternative routes to semantic and lexical networks, demonstrating that unique pathways to such stored information exist, and suggesting a different role for each ATL in identifying visually presented famous faces. The right ATL appears to play a fundamental role in accessing semantic information from a visual route, with the left ATL serving to link semantic information to the language system to produce a specific name. These findings challenge several assumptions underlying amodal models of semantic memory, and provide support for the integrated multimodal theories of semantic memory and a distributed representation of concepts. PMID:23040175

Famous face identification in temporal lobe epilepsy: support for a multimodal integration model of semantic memory.

PubMed

Drane, Daniel L; Ojemann, Jeffrey G; Phatak, Vaishali; Loring, David W; Gross, Robert E; Hebb, Adam O; Silbergeld, Daniel L; Miller, John W; Voets, Natalie L; Saindane, Amit M; Barsalou, Lawrence; Meador, Kimford J; Ojemann, George A; Tranel, Daniel

2013-06-01

This study aims to demonstrate that the left and right anterior temporal lobes (ATLs) perform critical but unique roles in famous face identification, with damage to either leading to differing deficit patterns reflecting decreased access to lexical or semantic concepts but not their degradation. Famous face identification was studied in 22 presurgical and 14 postsurgical temporal lobe epilepsy (TLE) patients and 20 healthy comparison subjects using free recall and multiple choice (MC) paradigms. Right TLE patients exhibited presurgical deficits in famous face recognition, and postsurgical deficits in both famous face recognition and familiarity judgments. However, they did not exhibit any problems with naming before or after surgery. In contrast, left TLE patients demonstrated both pre- and postsurgical deficits in famous face naming but no significant deficits in recognition or familiarity. Double dissociations in performance between groups were alleviated by altering task demands. Postsurgical right TLE patients provided with MC options correctly identified greater than 70% of famous faces they initially rated as unfamiliar. Left TLE patients accurately chose the name for nearly all famous faces they recognized (based on their verbal description) but initially failed to name, although they tended to rapidly lose access to this name. We believe alterations in task demands activate alternative routes to semantic and lexical networks, demonstrating that unique pathways to such stored information exist, and suggesting a different role for each ATL in identifying visually presented famous faces. The right ATL appears to play a fundamental role in accessing semantic information from a visual route, with the left ATL serving to link semantic information to the language system to produce a specific name. These findings challenge several assumptions underlying amodal models of semantic memory, and provide support for the integrated multimodal theories of semantic memory and a distributed representation of concepts. Copyright © 2012 Elsevier Ltd. All rights reserved.

On the Processing of Semantic Aspects of Experience in the Anterior Medial Temporal Lobe: An Event-Related fMRI Study

ERIC Educational Resources Information Center

Meyer, Patric; Mecklinger, Axel; Friederici, Angela D.

2010-01-01

Recognition memory based on familiarity judgments is a form of declarative memory that has been repeatedly associated with the anterior medial temporal lobe. It has been argued that this region sustains familiarity-based recognition not only by retrieving item-specific information but also by coding for those semantic aspects of an event that…

Global Neural Pattern Similarity as a Common Basis for Categorization and Recognition Memory

PubMed Central

Xue, Gui; Love, Bradley C.; Preston, Alison R.; Poldrack, Russell A.

2014-01-01

Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. PMID:24872552

Relating the Content and Confidence of Recognition Judgments

PubMed Central

Selmeczy, Diana; Dobbins, Ian G.

2014-01-01

The Remember/Know procedure, developed by Tulving (1985) to capture the distinction between the conscious correlates of episodic and semantic retrieval, has spurned considerable research and debate. However, only a handful of reports have examined the recognition content beyond this dichotomous simplification. To address this, we collected participants’ written justifications in support of ordinary old/new recognition decisions accompanied by confidence ratings using a 3-point scale (high/medium/low). Unlike prior research, we did not provide the participants with any descriptions of Remembering or Knowing and thus, if the justifications mapped well onto theory, they would do so spontaneously. Word frequency analysis (unigrams, bigrams, and trigrams), independent ratings, and machine learning techniques (Support Vector Machine - SVM) converged in demonstrating that the linguistic content of high and medium confidence recognition differs in a manner consistent with dual process theories of recognition. For example, the use of ‘I remember’, particularly when combined with temporal or perceptual information (e.g., ‘when’, ‘saw’, ‘distinctly’), was heavily associated with high confidence recognition. Conversely, participants also used the absence of remembering for personally distinctive materials as support for high confidence new reports (‘would have remembered’). Thus, participants afford a special status to the presence or absence of remembering and use this actively as a basis for high confidence during recognition judgments. Additionally, the pattern of classification successes and failures of a SVM was well anticipated by the Dual Process Signal Detection model of recognition and inconsistent with a single process, strictly unidimensional approach. “One might think that memory should have something to do with remembering, and remembering is a conscious experience.”(Tulving, 1985, p. 1) PMID:23957366

Music Recognition in Frontotemporal Lobar Degeneration and Alzheimer Disease

PubMed Central

Johnson, Julene K; Chang, Chiung-Chih; Brambati, Simona M; Migliaccio, Raffaella; Gorno-Tempini, Maria Luisa; Miller, Bruce L; Janata, Petr

2013-01-01

Objective To compare music recognition in patients with frontotemporal dementia, semantic dementia, Alzheimer disease, and controls and to evaluate the relationship between music recognition and brain volume. Background Recognition of familiar music depends on several levels of processing. There are few studies about how patients with dementia recognize familiar music. Methods Subjects were administered tasks that assess pitch and melody discrimination, detection of pitch errors in familiar melodies, and naming of familiar melodies. Results There were no group differences on pitch and melody discrimination tasks. However, patients with semantic dementia had considerable difficulty naming familiar melodies and also scored the lowest when asked to identify pitch errors in the same melodies. Naming familiar melodies, but not other music tasks, was strongly related to measures of semantic memory. Voxel-based morphometry analysis of brain MRI showed that difficulty in naming songs was associated with the bilateral temporal lobes and inferior frontal gyrus, whereas difficulty in identifying pitch errors in familiar melodies correlated with primarily the right temporal lobe. Conclusions The results support a view that the anterior temporal lobes play a role in familiar melody recognition, and that musical functions are affected differentially across forms of dementia. PMID:21617528

Déjà-vu in temporal lobe epilepsy: metabolic pattern of cortical involvement in patients with normal brain MRI.

PubMed

Guedj, Eric; Aubert, Sandrine; McGonigal, Aileen; Mundler, Olivier; Bartolomei, Fabrice

2010-06-01

To contribute to the identification of brain regions involved in déjà-vu, we studied the metabolic pattern of cortical involvement in patients with seizures of temporal lobe origin presenting with or without déjà-vu. Using voxel-based analysis of 18FDG-PET brain scans, we compared glucose metabolic rate of 8 patients with déjà-vu, 8 patients without déjà-vu, and 20 age-matched healthy subjects. Patients were selected after comprehensive non-invasive presurgical evaluation, including normal brain MRI and surface electroclinical features compatible with unilateral temporal lobe epilepsy (TLE). Patients with and without déjà-vu did not differ in terms of age, gender, epilepsy lateralization, epilepsy onset, epilepsy duration, and other subjective ictal manifestations. TLE patients with déjà-vu exhibited ipsilateral hypometabolism of superior temporal gyrus and of parahippocampal region, in the vicinity of perirhinal/entorhinal cortex, in comparison either to healthy subjects or to TLE patients without déjà-vu (p<0.05 FDR-corrected). By contrast, no difference was found between patient subgroups for hypometabolism of hippocampus and amygdala. At an individual-level, in comparison to healthy subjects, hypometabolism of both parahippocampal region and superior temporal gyrus was present in 7/8 patients with déjà-vu. Hippocampal metabolism was spared in 3 of these 7 patients. These findings argue for metabolic dysfunction of a medial-lateral temporal network in patients with déjà-vu and normal brain MRI. Within the medial temporal lobe, specific involvement of the parahippocampal region, often in the absence of hippocampal impairment, suggests that the feeling of familiarity during seizures greatly depends on alteration of the recognition memory system. Copyright 2010 Elsevier Ltd. All rights reserved.

Implicit phonological priming during visual word recognition.

PubMed

Wilson, Lisa B; Tregellas, Jason R; Slason, Erin; Pasko, Bryce E; Rojas, Donald C

2011-03-15

Phonology is a lower-level structural aspect of language involving the sounds of a language and their organization in that language. Numerous behavioral studies utilizing priming, which refers to an increased sensitivity to a stimulus following prior experience with that or a related stimulus, have provided evidence for the role of phonology in visual word recognition. However, most language studies utilizing priming in conjunction with functional magnetic resonance imaging (fMRI) have focused on lexical-semantic aspects of language processing. The aim of the present study was to investigate the neurobiological substrates of the automatic, implicit stages of phonological processing. While undergoing fMRI, eighteen individuals performed a lexical decision task (LDT) on prime-target pairs including word-word homophone and pseudoword-word pseudohomophone pairs with a prime presentation below perceptual threshold. Whole-brain analyses revealed several cortical regions exhibiting hemodynamic response suppression due to phonological priming including bilateral superior temporal gyri (STG), middle temporal gyri (MTG), and angular gyri (AG) with additional region of interest (ROI) analyses revealing response suppression in the left lateralized supramarginal gyrus (SMG). Homophone and pseudohomophone priming also resulted in different patterns of hemodynamic responses relative to one another. These results suggest that phonological processing plays a key role in visual word recognition. Furthermore, enhanced hemodynamic responses for unrelated stimuli relative to primed stimuli were observed in midline cortical regions corresponding to the default-mode network (DMN) suggesting that DMN activity can be modulated by task requirements within the context of an implicit task. Copyright © 2010 Elsevier Inc. All rights reserved.

Dissociating neural markers of stimulus memorability and subjective recognition during episodic retrieval.

PubMed

Bainbridge, Wilma A; Rissman, Jesse

2018-06-06

While much of memory research takes an observer-centric focus looking at participant performance, recent work has pinpointed important item-centric effects on memory, or how intrinsically memorable a given stimulus is. However, little is known about the neural correlates of memorability during memory retrieval, or how such correlates relate to subjective memory behavior. Here, stimuli and blood-oxygen-level dependent data from a prior functional magnetic resonance imaging (fMRI) study were reanalyzed using a memorability-based framework. In that study, sixteen participants studied 200 novel face images and were scanned while making recognition memory judgments on those faces, interspersed with 200 unstudied faces. In the current investigation, memorability scores for those stimuli were obtained through an online crowd-sourced (N = 740) continuous recognition test that measured each image's corrected recognition rate. Representational similarity analyses were conducted across the brain to identify regions wherein neural pattern similarity tracked item-specific effects (stimulus memorability) versus observer-specific effects (individual memory performance). We find two non-overlapping sets of regions, with memorability-related information predominantly represented within ventral and medial temporal regions and memory retrieval outcome-related information within fronto-parietal regions. These memorability-based effects persist regardless of image history, implying that coding of stimulus memorability may be a continuous and automatic perceptual process.

[False recognition of faces associated with fronto-temporal dementia with prosopagnosia].

PubMed

Verstichel, P

2005-09-01

The association of prosopagnosia and false recognition of faces is unusual and contributes to our understanding of the generation of facial familiarity. A 67-year-old man with a left prefrontal traumatic lesion, developed a temporal variety of fronto-temporal dementia (semantic dementia) with amyotrophic lateral sclerosis. Cerebral imagery demonstrated a bilateral, temporal anterior atrophy predominating in the right hemisphere. The main cognitive signs consisted in severe difficulties to recognize faces of familiar people (prosopagnosia), associated with systematic false recognition of unfamiliar people. Neuropsychological testing indicated that the prosopagnosia probably resulted from the association of an associative/mnemonic mechanism (inability to activate the Face Recognition Units (FRU) from the visual input) and a semantic mechanism (degradation of semantic/biographical information or deconnexion between FRU and this information). At the early stage of the disease, the patient could activate residual semantic information about individuals from their names, but after a 4-year course, he failed to do so. This worsening could be attributed to the extension of the degenerative lesions to the left temporal lobe. Familiar and unfamiliar faces triggered a marked feeling of knowing. False recognition concerned all the unfamiliar faces, and the patient claimed spontaneously that they corresponded to actors, but he could not provide any additional information about their specific identities. The coexistence of prosopagnosia and false recognition suggests the existence of different interconnected systems processing face recognition, one intended to identification of individuals, and the other producing the sense of familiarity. Dysfunctions at different stages of one or the other of these two processes could result in distortions in the feeling of knowing. From this case and others reported in literature, we propose to complete the classical model of face processing by adding a pathway linked to limbic system and frontal structures. This later pathway could normally emit signals for familiarity, essentially autonomic, in response to the familiar faces. These signals, primitively unconscious, secondly reach consciousness and are then integrated by a central supervisor system which evaluates and verifies identity-specific biographical information in order to make a decision about the sense of familiarity.

Auditory properties in the parabelt regions of the superior temporal gyrus in the awake macaque monkey: an initial survey.

PubMed

Kajikawa, Yoshinao; Frey, Stephen; Ross, Deborah; Falchier, Arnaud; Hackett, Troy A; Schroeder, Charles E

2015-03-11

The superior temporal gyrus (STG) is on the inferior-lateral brain surface near the external ear. In macaques, 2/3 of the STG is occupied by an auditory cortical region, the "parabelt," which is part of a network of inferior temporal areas subserving communication and social cognition as well as object recognition and other functions. However, due to its location beneath the squamous temporal bone and temporalis muscle, the STG, like other inferior temporal regions, has been a challenging target for physiological studies in awake-behaving macaques. We designed a new procedure for implanting recording chambers to provide direct access to the STG, allowing us to evaluate neuronal properties and their topography across the full extent of the STG in awake-behaving macaques. Initial surveys of the STG have yielded several new findings. Unexpectedly, STG sites in monkeys that were listening passively responded to tones with magnitudes comparable to those of responses to 1/3 octave band-pass noise. Mapping results showed longer response latencies in more rostral sites and possible tonotopic patterns parallel to core and belt areas, suggesting the reversal of gradients between caudal and rostral parabelt areas. These results will help further exploration of parabelt areas. Copyright © 2015 the authors 0270-6474/15/354140-11$15.00/0.

[Prosopagnosia and facial expression recognition].

PubMed

Koyama, Shinichi

2014-04-01

This paper reviews clinical neuropsychological studies that have indicated that the recognition of a person's identity and the recognition of facial expressions are processed by different cortical and subcortical areas of the brain. The fusiform gyrus, especially the right fusiform gyrus, plays an important role in the recognition of identity. The superior temporal sulcus, amygdala, and medial frontal cortex play important roles in facial-expression recognition. Both facial recognition and facial-expression recognition are highly intellectual processes that involve several regions of the brain.

Behavioral Performance and Neural Areas Associated with Memory Processes Contribute to Math and Reading Achievement in 6-year-old Children.

PubMed

Blankenship, Tashauna L; Keith, Kayla; Calkins, Susan D; Bell, Martha Ann

2018-01-01

Associations between working memory and academic achievement (math and reading) are well documented. Surprisingly, little is known of the contributions of episodic memory, segmented into temporal memory (recollection proxy) and item recognition (familiarity proxy), to academic achievement. This is the first study to observe these associations in typically developing 6-year old children. Overlap in neural correlates exists between working memory, episodic memory, and math and reading achievement. We attempted to tease apart the neural contributions of working memory, temporal memory, and item recognition to math and reading achievement. Results suggest that working memory and temporal memory, but not item recognition, are important contributors to both math and reading achievement, and that EEG power during a working memory task contributes to performance on tests of academic achievement.

Primitive Auditory Memory Is Correlated with Spatial Unmasking That Is Based on Direct-Reflection Integration

PubMed Central

Li, Huahui; Kong, Lingzhi; Wu, Xihong; Li, Liang

2013-01-01

In reverberant rooms with multiple-people talking, spatial separation between speech sources improves recognition of attended speech, even though both the head-shadowing and interaural-interaction unmasking cues are limited by numerous reflections. It is the perceptual integration between the direct wave and its reflections that bridges the direct-reflection temporal gaps and results in the spatial unmasking under reverberant conditions. This study further investigated (1) the temporal dynamic of the direct-reflection-integration-based spatial unmasking as a function of the reflection delay, and (2) whether this temporal dynamic is correlated with the listeners’ auditory ability to temporally retain raw acoustic signals (i.e., the fast decaying primitive auditory memory, PAM). The results showed that recognition of the target speech against the speech-masker background is a descending exponential function of the delay of the simulated target reflection. In addition, the temporal extent of PAM is frequency dependent and markedly longer than that for perceptual fusion. More importantly, the temporal dynamic of the speech-recognition function is significantly correlated with the temporal extent of the PAM of low-frequency raw signals. Thus, we propose that a chain process, which links the earlier-stage PAM with the later-stage correlation computation, perceptual integration, and attention facilitation, plays a role in spatially unmasking target speech under reverberant conditions. PMID:23658664

Differentiating between self and others: an ALE meta-analysis of fMRI studies of self-recognition and theory of mind.

PubMed

van Veluw, Susanne J; Chance, Steven A

2014-03-01

The perception of self and others is a key aspect of social cognition. In order to investigate the neurobiological basis of this distinction we reviewed two classes of task that study self-awareness and awareness of others (theory of mind, ToM). A reliable task to measure self-awareness is the recognition of one's own face in contrast to the recognition of others' faces. False-belief tasks are widely used to identify neural correlates of ToM as a measure of awareness of others. We performed an activation likelihood estimation meta-analysis, using the fMRI literature on self-face recognition and false-belief tasks. The brain areas involved in performing false-belief tasks were the medial prefrontal cortex (MPFC), bilateral temporo-parietal junction, precuneus, and the bilateral middle temporal gyrus. Distinct self-face recognition regions were the right superior temporal gyrus, the right parahippocampal gyrus, the right inferior frontal gyrus/anterior cingulate cortex, and the left inferior parietal lobe. Overlapping brain areas were the superior temporal gyrus, and the more ventral parts of the MPFC. We confirmed that self-recognition in contrast to recognition of others' faces, and awareness of others involves a network that consists of separate, distinct neural pathways, but also includes overlapping regions of higher order prefrontal cortex where these processes may be combined. Insights derived from the neurobiology of disorders such as autism and schizophrenia are consistent with this notion.

Pattern activation/recognition theory of mind

PubMed Central

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

Pattern activation/recognition theory of mind.

PubMed

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

Transdiagnostic deviant facial recognition for implicit negative emotion in autism and schizophrenia.

PubMed

Ciaramidaro, Angela; Bölte, Sven; Schlitt, Sabine; Hainz, Daniela; Poustka, Fritz; Weber, Bernhard; Freitag, Christine; Walter, Henrik

2018-02-01

Impaired facial affect recognition (FAR) is observed in schizophrenia and autism spectrum disorder (ASD) and has been linked to amygdala and fusiform gyrus dysfunction. ASD patient's impairments seem to be more pronounced during implicit rather than explicit FAR, whereas for schizophrenia data are inconsistent. However, there are no studies comparing both patient groups in an identical design. The aim of this three-group study was to identify (i) whether FAR alterations are equally present in both groups, (ii) whether they are present rather during implicit or explicit FAR, (iii) and whether they are conveyed by similar or disorder-specific neural mechanisms. Using fMRI, we investigated neural activation during explicit and implicit negative and neutral FAR in 33 young-adult individuals with ASD, 20 subjects with paranoid-schizophrenia and 25 IQ- and gender-matched controls individuals. Differences in activation patterns between each clinical group and controls, respectively were found exclusively for implicit FAR in amygdala and fusiform gyrus. In addition, the ASD group additionally showed reduced activations in medial prefrontal cortex (PFC), bilateral dorso-lateral PFC, ventro-lateral PFC, posterior-superior temporal sulcus and left temporo-parietal junction. Although subjects with ASD showed more widespread altered activation patterns, a direct comparison between both patient groups did not show disorder-specific deficits in neither patient group. In summary, our findings are consistent with a common neural deficit during implicit negative facial affect recognition in schizophrenia and autism spectrum disorders. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Longitudinal study of fingerprint recognition.

PubMed

Yoon, Soweon; Jain, Anil K

2015-07-14

Human identification by fingerprints is based on the fundamental premise that ridge patterns from distinct fingers are different (uniqueness) and a fingerprint pattern does not change over time (persistence). Although the uniqueness of fingerprints has been investigated by developing statistical models to estimate the probability of error in comparing two random samples of fingerprints, the persistence of fingerprints has remained a general belief based on only a few case studies. In this study, fingerprint match (similarity) scores are analyzed by multilevel statistical models with covariates such as time interval between two fingerprints in comparison, subject's age, and fingerprint image quality. Longitudinal fingerprint records of 15,597 subjects are sampled from an operational fingerprint database such that each individual has at least five 10-print records over a minimum time span of 5 y. In regard to the persistence of fingerprints, the longitudinal analysis on a single (right index) finger demonstrates that (i) genuine match scores tend to significantly decrease when time interval between two fingerprints in comparison increases, whereas the change in impostor match scores is negligible; and (ii) fingerprint recognition accuracy at operational settings, nevertheless, tends to be stable as the time interval increases up to 12 y, the maximum time span in the dataset. However, the uncertainty of temporal stability of fingerprint recognition accuracy becomes substantially large if either of the two fingerprints being compared is of poor quality. The conclusions drawn from 10-finger fusion analysis coincide with the conclusions from single-finger analysis.

Neuropsychological and FDG-PET profiles in VGKC autoimmune limbic encephalitis.

PubMed

Dodich, Alessandra; Cerami, Chiara; Iannaccone, Sandro; Marcone, Alessandra; Alongi, Pierpaolo; Crespi, Chiara; Canessa, Nicola; Andreetta, Francesca; Falini, Andrea; Cappa, Stefano F; Perani, Daniela

2016-10-01

Limbic encephalitis (LE) is characterized by an acute or subacute onset with memory impairments, confusional state, behavioral disorders, variably associated with seizures and dystonic movements. It is due to inflammatory processes that selectively affect the medial temporal lobe structures. Voltage-gate potassium channel (VGKC) autoantibodies are frequently observed. In this study, we assessed at the individual level FDG-PET brain metabolic dysfunctions and neuropsychological profiles in three autoimmune LE cases seropositive for neuronal VGKC-complex autoantibodies. LGI1 and CASPR2 potassium channel complex autoantibody subtyping was performed. Cognitive abilities were evaluated with an in-depth neuropsychological battery focused on episodic memory and affective recognition/processing skills. FDG-PET data were analyzed at single-subject level according to a standardized and validated voxel-based Statistical Parametric Mapping (SPM) method. Patients showed severe episodic memory and fear recognition deficits at the neuropsychological assessment. No disorder of mentalizing processing was present. Variable patterns of increases and decreases of brain glucose metabolism emerged in the limbic structures, highlighting the pathology-driven selective vulnerability of this system. Additional involvement of cortical and subcortical regions, particularly in the sensorimotor system and basal ganglia, was found. Episodic memory and fear recognition deficits characterize the cognitive profile of LE. Commonalities and differences may occur in the brain metabolic patterns. Single-subject voxel-based analysis of FDG-PET imaging could be useful in the early detection of the metabolic correlates of cognitive and non-cognitive deficits characterizing LE condition. Copyright © 2016 Elsevier Inc. All rights reserved.

Longitudinal study of fingerprint recognition

PubMed Central

Yoon, Soweon; Jain, Anil K.

2015-01-01

Human identification by fingerprints is based on the fundamental premise that ridge patterns from distinct fingers are different (uniqueness) and a fingerprint pattern does not change over time (persistence). Although the uniqueness of fingerprints has been investigated by developing statistical models to estimate the probability of error in comparing two random samples of fingerprints, the persistence of fingerprints has remained a general belief based on only a few case studies. In this study, fingerprint match (similarity) scores are analyzed by multilevel statistical models with covariates such as time interval between two fingerprints in comparison, subject’s age, and fingerprint image quality. Longitudinal fingerprint records of 15,597 subjects are sampled from an operational fingerprint database such that each individual has at least five 10-print records over a minimum time span of 5 y. In regard to the persistence of fingerprints, the longitudinal analysis on a single (right index) finger demonstrates that (i) genuine match scores tend to significantly decrease when time interval between two fingerprints in comparison increases, whereas the change in impostor match scores is negligible; and (ii) fingerprint recognition accuracy at operational settings, nevertheless, tends to be stable as the time interval increases up to 12 y, the maximum time span in the dataset. However, the uncertainty of temporal stability of fingerprint recognition accuracy becomes substantially large if either of the two fingerprints being compared is of poor quality. The conclusions drawn from 10-finger fusion analysis coincide with the conclusions from single-finger analysis. PMID:26124106

Resolving human object recognition in space and time

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2014-01-01

A comprehensive picture of object processing in the human brain requires combining both spatial and temporal information about brain activity. Here, we acquired human magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) responses to 92 object images. Multivariate pattern classification applied to MEG revealed the time course of object processing: whereas individual images were discriminated by visual representations early, ordinate and superordinate category levels emerged relatively later. Using representational similarity analysis, we combine human fMRI and MEG to show content-specific correspondence between early MEG responses and primary visual cortex (V1), and later MEG responses and inferior temporal (IT) cortex. We identified transient and persistent neural activities during object processing, with sources in V1 and IT., Finally, human MEG signals were correlated to single-unit responses in monkey IT. Together, our findings provide an integrated space- and time-resolved view of human object categorization during the first few hundred milliseconds of vision. PMID:24464044

Potential implementation of reservoir computing models based on magnetic skyrmions

NASA Astrophysics Data System (ADS)

Bourianoff, George; Pinna, Daniele; Sitte, Matthias; Everschor-Sitte, Karin

2018-05-01

Reservoir Computing is a type of recursive neural network commonly used for recognizing and predicting spatio-temporal events relying on a complex hierarchy of nested feedback loops to generate a memory functionality. The Reservoir Computing paradigm does not require any knowledge of the reservoir topology or node weights for training purposes and can therefore utilize naturally existing networks formed by a wide variety of physical processes. Most efforts to implement reservoir computing prior to this have focused on utilizing memristor techniques to implement recursive neural networks. This paper examines the potential of magnetic skyrmion fabrics and the complex current patterns which form in them as an attractive physical instantiation for Reservoir Computing. We argue that their nonlinear dynamical interplay resulting from anisotropic magnetoresistance and spin-torque effects allows for an effective and energy efficient nonlinear processing of spatial temporal events with the aim of event recognition and prediction.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition.

PubMed

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Towards limb position invariant myoelectric pattern recognition using time-dependent spectral features.

PubMed

Khushaba, Rami N; Takruri, Maen; Miro, Jaime Valls; Kodagoda, Sarath

2014-07-01

Recent studies in Electromyogram (EMG) pattern recognition reveal a gap between research findings and a viable clinical implementation of myoelectric control strategies. One of the important factors contributing to the limited performance of such controllers in practice is the variation in the limb position associated with normal use as it results in different EMG patterns for the same movements when carried out at different positions. However, the end goal of the myoelectric control scheme is to allow amputees to control their prosthetics in an intuitive and accurate manner regardless of the limb position at which the movement is initiated. In an attempt to reduce the impact of limb position on EMG pattern recognition, this paper proposes a new feature extraction method that extracts a set of power spectrum characteristics directly from the time-domain. The end goal is to form a set of features invariant to limb position. Specifically, the proposed method estimates the spectral moments, spectral sparsity, spectral flux, irregularity factor, and signals power spectrum correlation. This is achieved through using Fourier transform properties to form invariants to amplification, translation and signal scaling, providing an efficient and accurate representation of the underlying EMG activity. Additionally, due to the inherent temporal structure of the EMG signal, the proposed method is applied on the global segments of EMG data as well as the sliced segments using multiple overlapped windows. The performance of the proposed features is tested on EMG data collected from eleven subjects, while implementing eight classes of movements, each at five different limb positions. Practical results indicate that the proposed feature set can achieve significant reduction in classification error rates, in comparison to other methods, with ≈8% error on average across all subjects and limb positions. A real-time implementation and demonstration is also provided and made available as a video supplement (see Appendix A). Copyright © 2014 Elsevier Ltd. All rights reserved.

Impaired facial emotion recognition in patients with mesial temporal lobe epilepsy associated with hippocampal sclerosis (MTLE-HS): Side and age at onset matters.

PubMed

Hlobil, Ulf; Rathore, Chaturbhuj; Alexander, Aley; Sarma, Sankara; Radhakrishnan, Kurupath

2008-08-01

To define the determinants of impaired facial emotion recognition (FER) in patients with mesial temporal lobe epilepsy associated with hippocampal sclerosis (MTLE-HS), we examined 76 patients with unilateral MTLE-HS, 36 prior to antero-mesial temporal lobectomy (AMTL) and 40 after AMTL, and 28 healthy control subjects with a FER test consisting of 60 items (20 each for anger, fear, and happiness). Mean percentages of the accurate responses were calculated for different subgroups: right vs. left MTLE-HS, early (age at onset <6 years) vs. late-onset, and before vs. after AMTL. After controlling for years of education, duration of epilepsy and number of antiepileptic drugs (AEDs) taken, on multivariate analysis, fear recognition was profoundly impaired in early-onset right MTLE-HS patients compared to other MTLE patients and control subjects. Happiness recognition was significantly better in post-AMTL MTLE-HS patients compared to pre-AMTL patients while anger and fear recognition did not differ. We conclude that patients with right MTLE-HS with age at seizure onset <6 years are maximally predisposed to impaired fear recognition. In them, right AMTL does not further worsen FER abilities. Longitudinal studies comparing FER in the same patients before and after AMTL will be required to refine and confirm our cross-sectional observations.

Impaired recognition of scary music following unilateral temporal lobe excision.

PubMed

Gosselin, Nathalie; Peretz, Isabelle; Noulhiane, Marion; Hasboun, Dominique; Beckett, Christine; Baulac, Michel; Samson, Séverine

2005-03-01

Music constitutes an ideal means to create a sense of suspense in films. However, there has been minimal investigation into the underlying cerebral organization for perceiving danger created by music. In comparison, the amygdala's role in recognition of fear in non-musical contexts has been well established. The present study sought to fill this gap in exploring how patients with amygdala resection recognize emotional expression in music. To this aim, we tested 16 patients with left (LTR; n = 8) or right (RTR; n = 8) medial temporal resection (including amygdala) for the relief of medically intractable seizures and 16 matched controls in an emotion recognition task involving instrumental music. The musical selections were purposely created to induce fear, peacefulness, happiness and sadness. Participants were asked to rate to what extent each musical passage expressed these four emotions on 10-point scales. In order to check for the presence of a perceptual problem, the same musical selections were presented to the participants in an error detection task. None of the patients was found to perform below controls in the perceptual task. In contrast, both LTR and RTR patients were found to be impaired in the recognition of scary music. Recognition of happy and sad music was normal. These findings suggest that the anteromedial temporal lobe (including the amygdala) plays a role in the recognition of danger in a musical context.

Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition

PubMed Central

Tian, Moqian; Grill-Spector, Kalanit

2015-01-01

Recognizing objects is difficult because it requires both linking views of an object that can be different and distinguishing objects with similar appearance. Interestingly, people can learn to recognize objects across views in an unsupervised way, without feedback, just from the natural viewing statistics. However, there is intense debate regarding what information during unsupervised learning is used to link among object views. Specifically, researchers argue whether temporal proximity, motion, or spatiotemporal continuity among object views during unsupervised learning is beneficial. Here, we untangled the role of each of these factors in unsupervised learning of novel three-dimensional (3-D) objects. We found that after unsupervised training with 24 object views spanning a 180° view space, participants showed significant improvement in their ability to recognize 3-D objects across rotation. Surprisingly, there was no advantage to unsupervised learning with spatiotemporal continuity or motion information than training with temporal proximity. However, we discovered that when participants were trained with just a third of the views spanning the same view space, unsupervised learning via spatiotemporal continuity yielded significantly better recognition performance on novel views than learning via temporal proximity. These results suggest that while it is possible to obtain view-invariant recognition just from observing many views of an object presented in temporal proximity, spatiotemporal information enhances performance by producing representations with broader view tuning than learning via temporal association. Our findings have important implications for theories of object recognition and for the development of computational algorithms that learn from examples. PMID:26024454

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

PubMed Central

Swartz, R. Andrew

2013-01-01

This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136

The signer and the sign: cortical correlates of person identity and language processing from point-light displays.

PubMed

Campbell, Ruth; Capek, Cheryl M; Gazarian, Karine; MacSweeney, Mairéad; Woll, Bencie; David, Anthony S; McGuire, Philip K; Brammer, Michael J

2011-09-01

In this study, the first to explore the cortical correlates of signed language (SL) processing under point-light display conditions, the observer identified either a signer or a lexical sign from a display in which different signers were seen producing a number of different individual signs. Many of the regions activated by point-light under these conditions replicated those previously reported for full-image displays, including regions within the inferior temporal cortex that are specialised for face and body-part identification, although such body parts were invisible in the display. Right frontal regions were also recruited - a pattern not usually seen in full-image SL processing. This activation may reflect the recruitment of information about person identity from the reduced display. A direct comparison of identify-signer and identify-sign conditions showed these tasks relied to a different extent on the posterior inferior regions. Signer identification elicited greater activation than sign identification in (bilateral) inferior temporal gyri (BA 37/19), fusiform gyri (BA 37), middle and posterior portions of the middle temporal gyri (BAs 37 and 19), and superior temporal gyri (BA 22 and 42). Right inferior frontal cortex was a further focus of differential activation (signer>sign). These findings suggest that the neural systems supporting point-light displays for the processing of SL rely on a cortical network including areas of the inferior temporal cortex specialized for face and body identification. While this might be predicted from other studies of whole body point-light actions (Vaina, Solomon, Chowdhury, Sinha, & Belliveau, 2001) it is not predicted from the perspective of spoken language processing, where voice characteristics and speech content recruit distinct cortical regions (Stevens, 2004) in addition to a common network. In this respect, our findings contrast with studies of voice/speech recognition (Von Kriegstein, Kleinschmidt, Sterzer, & Giraud, 2005). Inferior temporal regions associated with the visual recognition of a person appear to be required during SL processing, for both carrier and content information. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Advanced optical correlation and digital methods for pattern matching—50th anniversary of Vander Lugt matched filter

NASA Astrophysics Data System (ADS)

Millán, María S.

2012-10-01

On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical-digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption-decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical-digital solutions.

Temporally flexible feedback signal to foveal cortex for peripheral object recognition

PubMed Central

Fan, Xiaoxu; Wang, Lan; Shao, Hanyu; Kersten, Daniel; He, Sheng

2016-01-01

Recent studies have shown that information from peripherally presented images is present in the human foveal retinotopic cortex, presumably because of feedback signals. We investigated this potential feedback signal by presenting noise in fovea at different object–noise stimulus onset asynchronies (SOAs), whereas subjects performed a discrimination task on peripheral objects. Results revealed a selective impairment of performance when foveal noise was presented at 250-ms SOA, but only for tasks that required comparing objects’ spatial details, suggesting a task- and stimulus-dependent foveal processing mechanism. Critically, the temporal window of foveal processing was shifted when mental rotation was required for the peripheral objects, indicating that the foveal retinotopic processing is not automatically engaged at a fixed time following peripheral stimulation; rather, it occurs at a stage when detailed information is required. Moreover, fMRI measurements using multivoxel pattern analysis showed that both image and object category-relevant information of peripheral objects was represented in the foveal cortex. Taken together, our results support the hypothesis of a temporally flexible feedback signal to the foveal retinotopic cortex when discriminating objects in the visual periphery. PMID:27671651

Decoding semantic information from human electrocorticographic (ECoG) signals.

PubMed

Wang, Wei; Degenhart, Alan D; Sudre, Gustavo P; Pomerleau, Dean A; Tyler-Kabara, Elizabeth C

2011-01-01

This study examined the feasibility of decoding semantic information from human cortical activity. Four human subjects undergoing presurgical brain mapping and seizure foci localization participated in this study. Electrocorticographic (ECoG) signals were recorded while the subjects performed simple language tasks involving semantic information processing, such as a picture naming task where subjects named pictures of objects belonging to different semantic categories. Robust high-gamma band (60-120 Hz) activation was observed at the left inferior frontal gyrus (LIFG) and the posterior portion of the superior temporal gyrus (pSTG) with a temporal sequence corresponding to speech production and perception. Furthermore, Gaussian Naïve Bayes and Support Vector Machine classifiers, two commonly used machine learning algorithms for pattern recognition, were able to predict the semantic category of an object using cortical activity captured by ECoG electrodes covering the frontal, temporal and parietal cortices. These findings have implications for both basic neuroscience research and development of semantic-based brain-computer interface systems (BCI) that can help individuals with severe motor or communication disorders to express their intention and thoughts.

Flow-Signature Analysis of Water Consumption in Nonresidential Building Water Networks Using High-Resolution and Medium-Resolution Smart Meter Data: Two Case Studies

NASA Astrophysics Data System (ADS)

Clifford, Eoghan; Mulligan, Sean; Comer, Joanne; Hannon, Louise

2018-01-01

Real-time monitoring of water consumption activities can be an effective mechanism to achieve efficient water network management. This approach, largely enabled by the advent of smart metering technologies, is gradually being practiced in domestic and industrial contexts. In particular, identifying water consumption habits from flow-signatures, i.e., the specific end-usage patterns, is being investigated as a means for conservation in both the residential and nonresidential context. However, the quality of meter data is bivariate (dependent on number of meters and data temporal resolution) and as a result, planning a smart metering scheme is relatively difficult with no generic design approach available. In this study, a comprehensive medium-resolution to high-resolution smart metering program was implemented at two nonresidential trial sites to evaluate the effect of spatial and temporal data aggregation. It was found that medium-resolution water meter data were capable of exposing regular, continuous, peak use, and diurnal patterns which reflect group wide end-usage characteristics. The high-resolution meter data permitted flow-signature at a personal end-use level. Through this unique opportunity to observe water usage characteristics via flow-signature patterns, newly defined hydraulic-based design coefficients determined from Poisson rectangular pulse were developed to intuitively aid in the process of pattern discovery with implications for automated activity recognition applications. A smart meter classification and siting index was introduced which categorizes meter resolution in terms of their suitable application.

Mapping parahippocampal systems for recognition and recency memory in the absence of the rat hippocampus

PubMed Central

Kinnavane, L; Amin, E; Horne, M; Aggleton, J P

2014-01-01

The present study examined immediate-early gene expression in the perirhinal cortex of rats with hippocampal lesions. The goal was to test those models of recognition memory which assume that the perirhinal cortex can function independently of the hippocampus. The c-fos gene was targeted, as its expression in the perirhinal cortex is strongly associated with recognition memory. Four groups of rats were examined. Rats with hippocampal lesions and their surgical controls were given either a recognition memory task (novel vs. familiar objects) or a relative recency task (objects with differing degrees of familiarity). Perirhinal Fos expression in the hippocampal-lesioned groups correlated with both recognition and recency performance. The hippocampal lesions, however, had no apparent effect on overall levels of perirhinal or entorhinal cortex c-fos expression in response to novel objects, with only restricted effects being seen in the recency condition. Network analyses showed that whereas the patterns of parahippocampal interactions were differentially affected by novel or familiar objects, these correlated networks were not altered by hippocampal lesions. Additional analyses in control rats revealed two modes of correlated medial temporal activation. Novel stimuli recruited the pathway from the lateral entorhinal cortex (cortical layer II or III) to hippocampal field CA3, and thence to CA1. Familiar stimuli recruited the direct pathway from the lateral entorhinal cortex (principally layer III) to CA1. The present findings not only reveal the independence from the hippocampus of some perirhinal systems associated with recognition memory, but also show how novel stimuli engage hippocampal subfields in qualitatively different ways from familiar stimuli. PMID:25264133

Testing a Neurocomputational Model of Recollection, Familiarity, and Source Recognition

ERIC Educational Resources Information Center

Elfman, Kane W.; Parks, Colleen M.; Yonelinas, Andrew P.

2008-01-01

The authors assess whether the complementary learning systems model of the medial temporal lobes (Norman & O'Reilly, 2003) is able to account for source recognition receiver operating characteristics (ROCs). The model assumes that recognition reflects the contribution of a hippocampally mediated recollection process and a cortically mediated…

Robust autoassociative memory with coupled networks of Kuramoto-type oscillators

NASA Astrophysics Data System (ADS)

Heger, Daniel; Krischer, Katharina

2016-08-01

Uncertain recognition success, unfavorable scaling of connection complexity, or dependence on complex external input impair the usefulness of current oscillatory neural networks for pattern recognition or restrict technical realizations to small networks. We propose a network architecture of coupled oscillators for pattern recognition which shows none of the mentioned flaws. Furthermore we illustrate the recognition process with simulation results and analyze the dynamics analytically: Possible output patterns are isolated attractors of the system. Additionally, simple criteria for recognition success are derived from a lower bound on the basins of attraction.

Distinct spatio-temporal profiles of beta-oscillations within visual and sensorimotor areas during action recognition as revealed by MEG.

PubMed

Pavlidou, Anastasia; Schnitzler, Alfons; Lange, Joachim

2014-05-01

The neural correlates of action recognition have been widely studied in visual and sensorimotor areas of the human brain. However, the role of neuronal oscillations involved during the process of action recognition remains unclear. Here, we were interested in how the plausibility of an action modulates neuronal oscillations in visual and sensorimotor areas. Subjects viewed point-light displays (PLDs) of biomechanically plausible and implausible versions of the same actions. Using magnetoencephalography (MEG), we examined dynamic changes of oscillatory activity during these action recognition processes. While both actions elicited oscillatory activity in visual and sensorimotor areas in several frequency bands, a significant difference was confined to the beta-band (∼20 Hz). An increase of power for plausible actions was observed in left temporal, parieto-occipital and sensorimotor areas of the brain, in the beta-band in successive order between 1650 and 2650 msec. These distinct spatio-temporal beta-band profiles suggest that the action recognition process is modulated by the degree of biomechanical plausibility of the action, and that spectral power in the beta-band may provide a functional interaction between visual and sensorimotor areas in humans. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hidden Markov models for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J. (Inventor)

1995-01-01

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Hidden Markov models for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J. (Inventor)

1993-01-01

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) perpendicular to x), 1 less than or equal to i is less than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Live-cell Video Microscopy of Fungal Pathogen Phagocytosis

PubMed Central

Lewis, Leanne E.; Bain, Judith M.; Okai, Blessing; Gow, Neil A.R.; Erwig, Lars Peter

2013-01-01

Phagocytic clearance of fungal pathogens, and microorganisms more generally, may be considered to consist of four distinct stages: (i) migration of phagocytes to the site where pathogens are located; (ii) recognition of pathogen-associated molecular patterns (PAMPs) through pattern recognition receptors (PRRs); (iii) engulfment of microorganisms bound to the phagocyte cell membrane, and (iv) processing of engulfed cells within maturing phagosomes and digestion of the ingested particle. Studies that assess phagocytosis in its entirety are informative1, 2, 3, 4, 5 but are limited in that they do not normally break the process down into migration, engulfment and phagosome maturation, which may be affected differentially. Furthermore, such studies assess uptake as a single event, rather than as a continuous dynamic process. We have recently developed advanced live-cell imaging technologies, and have combined these with genetic functional analysis of both pathogen and host cells to create a cross-disciplinary platform for the analysis of innate immune cell function and fungal pathogenesis. These studies have revealed novel aspects of phagocytosis that could only be observed using systematic temporal analysis of the molecular and cellular interactions between human phagocytes and fungal pathogens and infectious microorganisms more generally. For example, we have begun to define the following: (a) the components of the cell surface required for each stage of the process of recognition, engulfment and killing of fungal cells1, 6, 7, 8; (b) how surface geometry influences the efficiency of macrophage uptake and killing of yeast and hyphal cells7; and (c) how engulfment leads to alteration of the cell cycle and behavior of macrophages 9, 10. In contrast to single time point snapshots, live-cell video microscopy enables a wide variety of host cells and pathogens to be studied as continuous sequences over lengthy time periods, providing spatial and temporal information on a broad range of dynamic processes, including cell migration, replication and vesicular trafficking. Here we describe in detail how to prepare host and fungal cells, and to conduct the video microscopy experiments. These methods can provide a user-guide for future studies with other phagocytes and microorganisms. PMID:23329139

Cognitive and Neural Effects of Semantic Encoding Strategy Training in Older Adults

PubMed Central

Anderson, B. A.; Barch, D. M.; Jacoby, L. L.

2012-01-01

Prior research suggests that older adults are less likely than young adults to use effective learning strategies during intentional encoding. This functional magnetic resonance imaging (fMRI) study investigated whether training older adults to use semantic encoding strategies can increase their self-initiated use of these strategies and improve their recognition memory. The effects of training on older adults' brain activity during intentional encoding were also examined. Training increased older adults' self-initiated semantic encoding strategy use and eliminated pretraining age differences in recognition memory following intentional encoding. Training also increased older adults' brain activity in the medial superior frontal gyrus, right precentral gyrus, and left caudate during intentional encoding. In addition, older adults' training-related changes in recognition memory were strongly correlated with training-related changes in brain activity in prefrontal and left lateral temporal regions associated with semantic processing and self-initiated verbal encoding strategy use in young adults. These neuroimaging results demonstrate that semantic encoding strategy training can alter older adults' brain activity patterns during intentional encoding and suggest that young and older adults may use the same network of brain regions to support self-initiated use of verbal encoding strategies. PMID:21709173

Human brain distinctiveness based on EEG spectral coherence connectivity.

PubMed

Rocca, D La; Campisi, P; Vegso, B; Cserti, P; Kozmann, G; Babiloni, F; Fallani, F De Vico

2014-09-01

The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years. Most of the current analyses rely on the extraction of features characterizing the activity of single brain regions, like power spectrum estimation, thus neglecting possible temporal dependencies between the generated EEG signals. However, important physiological information can be extracted from the way different brain regions are functionally coupled. In this study, we propose a novel approach that fuses spectral coherence-based connectivity between different brain regions as a possibly viable biometric feature. The proposed approach is tested on a large dataset of subjects (N = 108) during eyes-closed (EC) and eyes-open (EO) resting state conditions. The obtained recognition performance shows that using brain connectivity leads to higher distinctiveness with respect to power-spectrum measurements, in both the experimental conditions. Notably, a 100% recognition accuracy is obtained in EC and EO when integrating functional connectivity between regions in the frontal lobe, while a lower 97.5% is obtained in EC (96.26% in EO) when fusing power spectrum information from parieto-occipital (centro-parietal in EO) regions. Taken together, these results suggest that the functional connectivity patterns represent effective features for improving EEG-based biometric systems.

New generation of human machine interfaces for controlling UAV through depth-based gesture recognition

NASA Astrophysics Data System (ADS)

Mantecón, Tomás.; del Blanco, Carlos Roberto; Jaureguizar, Fernando; García, Narciso

2014-06-01

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

Perceptual Integration Deficits in Autism Spectrum Disorders Are Associated with Reduced Interhemispheric Gamma-Band Coherence.

PubMed

Peiker, Ina; David, Nicole; Schneider, Till R; Nolte, Guido; Schöttle, Daniel; Engel, Andreas K

2015-12-16

The integration of visual details into a holistic percept is essential for object recognition. This integration has been reported as a key deficit in patients with autism spectrum disorders (ASDs). The weak central coherence account posits an altered disposition to integrate features into a coherent whole in ASD. Here, we test the hypothesis that such weak perceptual coherence may be reflected in weak neural coherence across different cortical sites. We recorded magnetoencephalography from 20 adult human participants with ASD and 20 matched controls, who performed a slit-viewing paradigm, in which objects gradually passed behind a vertical or horizontal slit so that only fragments of the object were visible at any given moment. Object recognition thus required perceptual integration over time and, in case of the horizontal slit, also across visual hemifields. ASD participants were selectively impaired in the horizontal slit condition, indicating specific difficulties in long-range synchronization between the hemispheres. Specifically, the ASD group failed to show condition-related enhancement of imaginary coherence between the posterior superior temporal sulci in both hemispheres during horizontal slit-viewing in contrast to controls. Moreover, local synchronization reflected in occipitocerebellar beta-band power was selectively reduced for horizontal compared with vertical slit-viewing in ASD. Furthermore, we found disturbed connectivity between right posterior superior temporal sulcus and left cerebellum. Together, our results suggest that perceptual integration deficits co-occur with specific patterns of abnormal global and local synchronization in ASD. The weak central coherence account proposes a tendency of individuals with autism spectrum disorders (ASDs) to focus on details at the cost of an integrated coherent whole. Here, we provide evidence, at the behavioral and the neural level, that visual integration in object recognition is impaired in ASD, when details had to be integrated across both visual hemifields. We found enhanced interhemispheric gamma-band coherence in typically developed participants when communication between cortical hemispheres was required by the task. Importantly, participants with ASD failed to show this enhanced coherence between bilateral posterior superior temporal sulci. The findings suggest that visual integration is disturbed at the local and global synchronization scale, which might bear implications for object recognition in ASD. Copyright © 2015 the authors 0270-6474/15/3516352-10$15.00/0.

Critical Song Features for Auditory Pattern Recognition in Crickets

PubMed Central

Meckenhäuser, Gundula; Hennig, R. Matthias; Nawrot, Martin P.

2013-01-01

Many different invertebrate and vertebrate species use acoustic communication for pair formation. In the cricket Gryllus bimaculatus, females recognize their species-specific calling song and localize singing males by positive phonotaxis. The song pattern of males has a clear structure consisting of brief and regular pulses that are grouped into repetitive chirps. Information is thus present on a short and a long time scale. Here, we ask which structural features of the song critically determine the phonotactic performance. To this end we employed artificial neural networks to analyze a large body of behavioral data that measured females’ phonotactic behavior under systematic variation of artificially generated song patterns. In a first step we used four non-redundant descriptive temporal features to predict the female response. The model prediction showed a high correlation with the experimental results. We used this behavioral model to explore the integration of the two different time scales. Our result suggested that only an attractive pulse structure in combination with an attractive chirp structure reliably induced phonotactic behavior to signals. In a further step we investigated all feature sets, each one consisting of a different combination of eight proposed temporal features. We identified feature sets of size two, three, and four that achieve highest prediction power by using the pulse period from the short time scale plus additional information from the long time scale. PMID:23437054

State Identification for Planetary Rovers: Learning and Recognition

NASA Technical Reports Server (NTRS)

Aycard, Olivier; Washington, Richard

1999-01-01

A planetary rover must be able to identify states where it should stop or change its plan. With limited and infrequent communication from ground, the rover must recognize states accurately. However, the sensor data is inherently noisy, so identifying the temporal patterns of data that correspond to interesting or important states becomes a complex problem. In this paper, we present an approach to state identification using second-order Hidden Markov Models. Models are trained automatically on a set of labeled training data; the rover uses those models to identify its state from the observed data. The approach is demonstrated on data from a planetary rover platform.

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

NASA Astrophysics Data System (ADS)

Acciarri, R.; Adams, C.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; Jan de Vries, J.; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Rudolf von Rohr, C.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

2018-01-01

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.

Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.

PubMed

de Melo, Silas Nogueira; Pereira, Débora V S; Andresen, Martin A; Matias, Lindon Fonseca

2018-05-01

Temporal and spatial patterns of crime in Campinas, Brazil, are analyzed considering the relevance of routine activity theory in a Latin American context. We use geo-referenced criminal event data, 2010-2013, analyzing spatial patterns using census tracts and temporal patterns considering seasons, months, days, and hours. Our analyses include difference in means tests, count-based regression models, and Kulldorff's scan test. We find that crime in Campinas, Brazil, exhibits both temporal and spatial-temporal patterns. However, the presence of these patterns at the different temporal scales varies by crime type. Specifically, not all crime types have statistically significant temporal patterns at all scales of analysis. As such, routine activity theory works well to explain temporal and spatial-temporal patterns of crime in Campinas, Brazil. However, local knowledge of Brazilian culture is necessary for understanding a portion of these crime patterns.

The Pandora multi-algorithm approach to automated pattern recognition in LAr TPC detectors

NASA Astrophysics Data System (ADS)

Marshall, J. S.; Blake, A. S. T.; Thomson, M. A.; Escudero, L.; de Vries, J.; Weston, J.; MicroBooNE Collaboration

2017-09-01

The development and operation of Liquid Argon Time Projection Chambers (LAr TPCs) for neutrino physics has created a need for new approaches to pattern recognition, in order to fully exploit the superb imaging capabilities offered by this technology. The Pandora Software Development Kit provides functionality to aid the process of designing, implementing and running pattern recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition: individual algorithms each address a specific task in a particular topology; a series of many tens of algorithms then carefully builds-up a picture of the event. The input to the Pandora pattern recognition is a list of 2D Hits. The output from the chain of over 70 algorithms is a hierarchy of reconstructed 3D Particles, each with an identified particle type, vertex and direction.

Online recognition of the multiphase flow regime and study of slug flow in pipeline

NASA Astrophysics Data System (ADS)

Liejin, Guo; Bofeng, Bai; Liang, Zhao; Xin, Wang; Hanyang, Gu

2009-02-01

Multiphase flow is the phenomenon existing widely in nature, daily life, as well as petroleum and chemical engineering industrial fields. The interface structure among multiphase and their movement are complicated, which distribute random and heterogeneously in the spatial and temporal scales and have multivalue of the flow structure and state[1]. Flow regime is defined as the macro feature about the multiphase interface structure and its distribution, which is an important feature to describe multiphase flow. The energy and mass transport mechanism differ much for each flow regimes. It is necessary to solve the flow regime recognition to get a clear understanding of the physical phenomena and their mechanism of multiphase flow. And the flow regime is one of the main factors affecting the online measurement accuracy of phase fraction, flow rate and other phase parameters. Therefore, it is of great scientific and technological importance to develop new principles and methods of multiphase flow regime online recognition, and of great industrial background. In this paper, the key reasons that the present method cannot be used to solve the industrial multiphase flow pattern recognition are clarified firstly. Then the prerequisite to realize the online recognition of multiphase flow regime is analyzed, and the recognition rules for partial flow pattern are obtained based on the massive experimental data. The standard templates for every flow regime feature are calculated with self-organization cluster algorithm. The multi-sensor data fusion method is proposed to realize the online recognition of multiphase flow regime with the pressure and differential pressure signals, which overcomes the severe influence of fluid flow velocity and the oil fraction on the recognition. The online recognition method is tested in the practice, which has less than 10 percent measurement error. The method takes advantages of high confidence, good fault tolerance and less requirement of single sensor performance. Among various flow patterns of gas-liquid flow, slug flow occurs frequently in the petroleum, chemical, civil and nuclear industries. In the offshore oil and gas field, the maximum slug length and its statistical distribution are very important for the design of separator and downstream processing facility at steady state operations. However transient conditions may be encountered in the production, such as operational upsets, start-up, shut-down, pigging and blowdown, which are key operational and safety issues related to oil field development. So it is necessary to have an understanding the flow parameters under transient conditions. In this paper, the evolution of slug length along a horizontal pipe in gas-liquid flow is also studied in details and then an experimental study of flowrate transients in slug flow is provided. Also, the special gas-liquid flow phenomena easily encountered in the life span of offshore oil fields, called severe slugging, is studied experimentally and some results are presented.

Real Time Large Memory Optical Pattern Recognition.

DTIC Science & Technology

1984-06-01

AD-Ri58 023 REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION(U) - h ARMY MISSILE COMMAND REDSTONE ARSENAL AL RESEARCH DIRECTORATE D A GREGORY JUN...TECHNICAL REPORT RR-84-9 Ln REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION Don A. Gregory Research Directorate US Army Missile Laboratory JUNE 1984 L...RR-84-9 , ___/_ _ __ _ __ _ __ _ __"__ _ 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED Real Time Large Memory Optical Pattern Technical

Classification and machine recognition of severe weather patterns

NASA Technical Reports Server (NTRS)

Wang, P. P.; Burns, R. C.

1976-01-01

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.

Fuzzy Logic-Based Audio Pattern Recognition

NASA Astrophysics Data System (ADS)

Malcangi, M.

2008-11-01

Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

New Optical Transforms For Statistical Image Recognition

NASA Astrophysics Data System (ADS)

Lee, Sing H.

1983-12-01

In optical implementation of statistical image recognition, new optical transforms on large images for real-time recognition are of special interest. Several important linear transformations frequently used in statistical pattern recognition have now been optically implemented, including the Karhunen-Loeve transform (KLT), the Fukunaga-Koontz transform (FKT) and the least-squares linear mapping technique (LSLMT).1-3 The KLT performs principle components analysis on one class of patterns for feature extraction. The FKT performs feature extraction for separating two classes of patterns. The LSLMT separates multiple classes of patterns by maximizing the interclass differences and minimizing the intraclass variations.

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

The Eyes Know Time: A Novel Paradigm to Reveal the Development of Temporal Memory

ERIC Educational Resources Information Center

Pathman, Thanujeni; Ghetti, Simona

2014-01-01

Temporal memory in 7-year-olds, 10-year-olds, and young adults (N = 78) was examined introducing a novel eye-movement paradigm. Participants learned object sequences and were tested under three conditions: temporal order, temporal context, and recognition. Age-related improvements in accuracy were found across conditions; accuracy in the temporal…

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

PubMed Central

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve. PMID:29081753

Two areas for familiar face recognition in the primate brain.

PubMed

Landi, Sofia M; Freiwald, Winrich A

2017-08-11

Familiarity alters face recognition: Familiar faces are recognized more accurately than unfamiliar ones and under difficult viewing conditions when unfamiliar face recognition fails. The neural basis for this fundamental difference remains unknown. Using whole-brain functional magnetic resonance imaging, we found that personally familiar faces engage the macaque face-processing network more than unfamiliar faces. Familiar faces also recruited two hitherto unknown face areas at anatomically conserved locations within the perirhinal cortex and the temporal pole. These two areas, but not the core face-processing network, responded to familiar faces emerging from a blur with a characteristic nonlinear surge, akin to the abruptness of familiar face recognition. In contrast, responses to unfamiliar faces and objects remained linear. Thus, two temporal lobe areas extend the core face-processing network into a familiar face-recognition system. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Influence of motion on face recognition.

PubMed

Bonfiglio, Natale S; Manfredi, Valentina; Pessa, Eliano

2012-02-01

The influence of motion information and temporal associations on recognition of non-familiar faces was investigated using two groups which performed a face recognition task. One group was presented with regular temporal sequences of face views designed to produce the impression of motion of the face rotating in depth, the other group with random sequences of the same views. In one condition, participants viewed the sequences of the views in rapid succession with a negligible interstimulus interval (ISI). This condition was characterized by three different presentation times. In another condition, participants were presented a sequence with a 1-sec. ISI among the views. That regular sequences of views with a negligible ISI and a shorter presentation time were hypothesized to give rise to better recognition, related to a stronger impression of face rotation. Analysis of data from 45 participants showed a shorter presentation time was associated with significantly better accuracy on the recognition task; however, differences between performances associated with regular and random sequences were not significant.

The Need for Careful Data Collection for Pattern Recognition in Digital Pathology.

PubMed

Marée, Raphaël

2017-01-01

Effective pattern recognition requires carefully designed ground-truth datasets. In this technical note, we first summarize potential data collection issues in digital pathology and then propose guidelines to build more realistic ground-truth datasets and to control their quality. We hope our comments will foster the effective application of pattern recognition approaches in digital pathology.

Pattern recognition: A basis for remote sensing data analysis

NASA Technical Reports Server (NTRS)

Swain, P. H.

1973-01-01

The theoretical basis for the pattern-recognition-oriented algorithms used in the multispectral data analysis software system is discussed. A model of a general pattern recognition system is presented. The receptor or sensor is usually a multispectral scanner. For each ground resolution element the receptor produces n numbers or measurements corresponding to the n channels of the scanner.

Optical Pattern Recognition With Self-Amplification

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1994-01-01

In optical pattern recognition system with self-amplification, no reference beam used in addressing mode. Polarization of laser beam and orientation of photorefractive crystal chosen to maximize photorefractive effect. Intensity of recognition signal is orders of magnitude greater than other optical correlators. Apparatus regarded as real-time or quasi-real-time optical pattern recognizer with memory and reprogrammability.

[Neural mechanisms of facial recognition].

PubMed

Nagai, Chiyoko

2007-01-01

We review recent researches in neural mechanisms of facial recognition in the light of three aspects: facial discrimination and identification, recognition of facial expressions, and face perception in itself. First, it has been demonstrated that the fusiform gyrus has a main role of facial discrimination and identification. However, whether the FFA (fusiform face area) is really a special area for facial processing or not is controversial; some researchers insist that the FFA is related to 'becoming an expert' for some kinds of visual objects, including faces. Neural mechanisms of prosopagnosia would be deeply concerned to this issue. Second, the amygdala seems to be very concerned to recognition of facial expressions, especially fear. The amygdala, connected with the superior temporal sulcus and the orbitofrontal cortex, appears to operate the cortical function. The amygdala and the superior temporal sulcus are related to gaze recognition, which explains why a patient with bilateral amygdala damage could not recognize only a fear expression; the information from eyes is necessary for fear recognition. Finally, even a newborn infant can recognize a face as a face, which is congruent with the innate hypothesis of facial recognition. Some researchers speculate that the neural basis of such face perception is the subcortical network, comprised of the amygdala, the superior colliculus, and the pulvinar. This network would relate to covert recognition that prosopagnosic patients have.

The bag-of-frames approach to audio pattern recognition: a sufficient model for urban soundscapes but not for polyphonic music.

PubMed

Aucouturier, Jean-Julien; Defreville, Boris; Pachet, François

2007-08-01

The "bag-of-frames" approach (BOF) to audio pattern recognition represents signals as the long-term statistical distribution of their local spectral features. This approach has proved nearly optimal for simulating the auditory perception of natural and human environments (or soundscapes), and is also the most predominent paradigm to extract high-level descriptions from music signals. However, recent studies show that, contrary to its application to soundscape signals, BOF only provides limited performance when applied to polyphonic music signals. This paper proposes to explicitly examine the difference between urban soundscapes and polyphonic music with respect to their modeling with the BOF approach. First, the application of the same measure of acoustic similarity on both soundscape and music data sets confirms that the BOF approach can model soundscapes to near-perfect precision, and exhibits none of the limitations observed in the music data set. Second, the modification of this measure by two custom homogeneity transforms reveals critical differences in the temporal and statistical structure of the typical frame distribution of each type of signal. Such differences may explain the uneven performance of BOF algorithms on soundscapes and music signals, and suggest that their human perception rely on cognitive processes of a different nature.

Global neural pattern similarity as a common basis for categorization and recognition memory.

PubMed

Davis, Tyler; Xue, Gui; Love, Bradley C; Preston, Alison R; Poldrack, Russell A

2014-05-28

Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. Copyright © 2014 the authors 0270-6474/14/347472-13$15.00/0.

Receptive amusia: evidence for cross-hemispheric neural networks underlying music processing strategies.

PubMed

Schuppert, M; Münte, T F; Wieringa, B M; Altenmüller, E

2000-03-01

Perceptual musical functions were investigated in patients suffering from unilateral cerebrovascular cortical lesions. Using MIDI (Musical Instrument Digital Interface) technique, a standardized short test battery was established that covers local (analytical) as well as global perceptual mechanisms. These represent the principal cognitive strategies in melodic and temporal musical information processing (local, interval and rhythm; global, contour and metre). Of the participating brain-damaged patients, a total of 69% presented with post-lesional impairments in music perception. Left-hemisphere-damaged patients showed significant deficits in the discrimination of local as well as global structures in both melodic and temporal information processing. Right-hemisphere-damaged patients also revealed an overall impairment of music perception, reaching significance in the temporal conditions. Detailed analysis outlined a hierarchical organization, with an initial right-hemisphere recognition of contour and metre followed by identification of interval and rhythm via left-hemisphere subsystems. Patterns of dissociated and associated melodic and temporal deficits indicate autonomous, yet partially integrated neural subsystems underlying the processing of melodic and temporal stimuli. In conclusion, these data contradict a strong hemispheric specificity for music perception, but indicate cross-hemisphere, fragmented neural substrates underlying local and global musical information processing in the melodic and temporal dimensions. Due to the diverse profiles of neuropsychological deficits revealed in earlier investigations as well as in this study, individual aspects of musicality and musical behaviour very likely contribute to the definite formation of these widely distributed neural networks.

Familiarity and recollection produce distinct eye movement, pupil and medial temporal lobe responses when memory strength is matched.

PubMed

Kafkas, Alexandros; Montaldi, Daniela

2012-11-01

Two experiments explored eye measures (fixations and pupil response patterns) and brain responses (BOLD) accompanying the recognition of visual object stimuli based on familiarity and recollection. In both experiments, the use of a modified remember/know procedure led to high confidence and matched accuracy levels characterising strong familiarity (F3) and recollection (R) responses. In Experiment 1, visual scanning behaviour at retrieval distinguished familiarity-based from recollection-based recognition. Recollection, relative to strength-matched familiarity, involved significantly larger pupil dilations and more dispersed fixation patterns. In Experiment 2, the hippocampus was selectively activated for recollected stimuli, while no evidence of activation was observed in the hippocampus for strong familiarity of matched accuracy. Recollection also activated the parahippocampal cortex (PHC), while the adjacent perirhinal cortex (PRC) was actively engaged in response to strong familiarity (than to recollection). Activity in prefrontal and parietal areas differentiated familiarity and recollection in both the extent and the magnitude of activity they exhibited, while the dorsomedial thalamus showed selective familiarity-related activity, and the ventrolateral and anterior thalamus selective recollection-related activity. These findings are consistent with the view that the hippocampus and PRC play contrasting roles in supporting recollection and familiarity and that these differences are not a result of differences in memory strength. Overall, the combined pupil dilation, eye movement and fMRI data suggest the operation of recognition mechanisms drawing differentially on familiarity and recollection, whose neural bases are distinct within the MTL. Copyright © 2012 Elsevier Ltd. All rights reserved.

Sonar Recognition Training: An Investigation of Whole VS. Part and Analytic VS. Synthetic Procedures.

ERIC Educational Resources Information Center

Annett, John

An experienced person, in such tasks as sonar detection and recognition, has a considerable superiority over a machine recognition system in auditory pattern recognition. However, people require extensive exposure to auditory patterns before achieving a high level of performance. In an attempt to discover a method of training people to recognize…

Degraded character recognition based on gradient pattern

NASA Astrophysics Data System (ADS)

Babu, D. R. Ramesh; Ravishankar, M.; Kumar, Manish; Wadera, Kevin; Raj, Aakash

2010-02-01

Degraded character recognition is a challenging problem in the field of Optical Character Recognition (OCR). The performance of an optical character recognition depends upon printed quality of the input documents. Many OCRs have been designed which correctly identifies the fine printed documents. But, very few reported work has been found on the recognition of the degraded documents. The efficiency of the OCRs system decreases if the input image is degraded. In this paper, a novel approach based on gradient pattern for recognizing degraded printed character is proposed. The approach makes use of gradient pattern of an individual character for recognition. Experiments were conducted on character image that is either digitally written or a degraded character extracted from historical documents and the results are found to be satisfactory.

It doesn't matter what you say: FMRI correlates of voice learning and recognition independent of speech content.

PubMed

Zäske, Romi; Awwad Shiekh Hasan, Bashar; Belin, Pascal

2017-09-01

Listeners can recognize newly learned voices from previously unheard utterances, suggesting the acquisition of high-level speech-invariant voice representations during learning. Using functional magnetic resonance imaging (fMRI) we investigated the anatomical basis underlying the acquisition of voice representations for unfamiliar speakers independent of speech, and their subsequent recognition among novel voices. Specifically, listeners studied voices of unfamiliar speakers uttering short sentences and subsequently classified studied and novel voices as "old" or "new" in a recognition test. To investigate "pure" voice learning, i.e., independent of sentence meaning, we presented German sentence stimuli to non-German speaking listeners. To disentangle stimulus-invariant and stimulus-dependent learning, during the test phase we contrasted a "same sentence" condition in which listeners heard speakers repeating the sentences from the preceding study phase, with a "different sentence" condition. Voice recognition performance was above chance in both conditions although, as expected, performance was higher for same than for different sentences. During study phases activity in the left inferior frontal gyrus (IFG) was related to subsequent voice recognition performance and same versus different sentence condition, suggesting an involvement of the left IFG in the interactive processing of speaker and speech information during learning. Importantly, at test reduced activation for voices correctly classified as "old" compared to "new" emerged in a network of brain areas including temporal voice areas (TVAs) of the right posterior superior temporal gyrus (pSTG), as well as the right inferior/middle frontal gyrus (IFG/MFG), the right medial frontal gyrus, and the left caudate. This effect of voice novelty did not interact with sentence condition, suggesting a role of temporal voice-selective areas and extra-temporal areas in the explicit recognition of learned voice identity, independent of speech content. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic Target Recognition Based on Cross-Plot

PubMed Central

Wong, Kelvin Kian Loong; Abbott, Derek

2011-01-01

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository. PMID:21980508

Right anterior superior temporal activation predicts auditory sentence comprehension following aphasic stroke.

PubMed

Crinion, Jenny; Price, Cathy J

2005-12-01

Previous studies have suggested that recovery of speech comprehension after left hemisphere infarction may depend on a mechanism in the right hemisphere. However, the role that distinct right hemisphere regions play in speech comprehension following left hemisphere stroke has not been established. Here, we used functional magnetic resonance imaging (fMRI) to investigate narrative speech activation in 18 neurologically normal subjects and 17 patients with left hemisphere stroke and a history of aphasia. Activation for listening to meaningful stories relative to meaningless reversed speech was identified in the normal subjects and in each patient. Second level analyses were then used to investigate how story activation changed with the patients' auditory sentence comprehension skills and surprise story recognition memory tests post-scanning. Irrespective of lesion site, performance on tests of auditory sentence comprehension was positively correlated with activation in the right lateral superior temporal region, anterior to primary auditory cortex. In addition, when the stroke spared the left temporal cortex, good performance on tests of auditory sentence comprehension was also correlated with the left posterior superior temporal cortex (Wernicke's area). In distinct contrast to this, good story recognition memory predicted left inferior frontal and right cerebellar activation. The implication of this double dissociation in the effects of auditory sentence comprehension and story recognition memory is that left frontal and left temporal activations are dissociable. Our findings strongly support the role of the right temporal lobe in processing narrative speech and, in particular, auditory sentence comprehension following left hemisphere aphasic stroke. In addition, they highlight the importance of the right anterior superior temporal cortex where the response was dissociated from that in the left posterior temporal lobe.

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

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

Acciarri, R.; Adams, C.; An, R.

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

DOE PAGES

Acciarri, R.; Adams, C.; An, R.; ...

2018-01-29

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

A critical ethnographic study of encounters between midwives and breast-feeding women in postnatal wards in England.

PubMed

Dykes, Fiona

2005-09-01

To explore the nature of interactions between midwives and breast-feeding women within postnatal wards. A critical ethnographic study using participant observation and focused interviews. Two maternity units in Northern England, UK. 61 postnatal women and 39 midwives. The interactions between midwives and women were encompassed by the global theme of 'taking time and touching base'. However, most encounters were characterised by an absence of 'taking time' or 'touching base'. This related to midwives' experiences of temporal pressure and inability to establish relationality with women due to their working patterns. The global theme was underpinned by five organising themes: 'communicating temporal pressure'; 'routines and procedures'; 'disconnected encounters'; 'managing breast feeding'; and 'rationing information'. The organisational culture within the postnatal wards contributed to midwives experiencing profound temporal pressures and an inability to establish relationality with women. Within this context, the needs of breast-feeding women for emotional, esteem, informational and practical support were largely unmet. Transformative action is required to dramatically reorganise the provision of hospital-based, postnatal ward midwifery care in parts of the UK. This should include a re-conceptualisation of caring time, with recognition that midwives need sufficient time in order to give time to others. This, in turn, requires recognition that caring time is cyclical and rhythmical, allowing for relationality, sociability, mutuality and reciprocity. The midwifery staffing structure in postnatal wards needs to be reviewed, as it is unacceptable to midwives and service users for staff to be rapidly relocated according to other demands within the institution. Most radically, it is argued that now is the time to reconsider the suitability of the hospital as the place and space within which women commence their breast-feeding journey.

Mechanisms and neural basis of object and pattern recognition: a study with chess experts.

PubMed

Bilalić, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-11-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and novices performing chess-related and -unrelated (visual) search tasks. As expected, the superiority of experts was limited to the chess-specific task, as there were no differences in a control task that used the same chess stimuli but did not require chess-specific recognition. The analysis of eye movements showed that experts immediately and exclusively focused on the relevant aspects in the chess task, whereas novices also examined irrelevant aspects. With random chess positions, when pattern knowledge could not be used to guide perception, experts nevertheless maintained an advantage. Experts' superior domain-specific parafoveal vision, a consequence of their knowledge about individual domain-specific symbols, enabled improved object recognition. Functional magnetic resonance imaging corroborated this differentiation between object and pattern recognition and showed that chess-specific object recognition was accompanied by bilateral activation of the occipitotemporal junction, whereas chess-specific pattern recognition was related to bilateral activations in the middle part of the collateral sulci. Using the expertise approach together with carefully chosen controls and multiple dependent measures, we identified object and pattern recognition as two essential cognitive processes in expert visual cognition, which may also help to explain the mechanisms of everyday perception.

Finger Vein Recognition Based on Local Directional Code

PubMed Central

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-01-01

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP. PMID:23202194

Finger vein recognition based on local directional code.

PubMed

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-11-05

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP.

Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition.

PubMed

Ming, Yue; Wang, Guangchao; Fan, Chunxiao

2015-01-01

With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition.

Implicit and Explicit Contributions to Object Recognition: Evidence from Rapid Perceptual Learning

PubMed Central

Hassler, Uwe; Friese, Uwe; Gruber, Thomas

2012-01-01

The present study investigated implicit and explicit recognition processes of rapidly perceptually learned objects by means of steady-state visual evoked potentials (SSVEP). Participants were initially exposed to object pictures within an incidental learning task (living/non-living categorization). Subsequently, degraded versions of some of these learned pictures were presented together with degraded versions of unlearned pictures and participants had to judge, whether they recognized an object or not. During this test phase, stimuli were presented at 15 Hz eliciting an SSVEP at the same frequency. Source localizations of SSVEP effects revealed for implicit and explicit processes overlapping activations in orbito-frontal and temporal regions. Correlates of explicit object recognition were additionally found in the superior parietal lobe. These findings are discussed to reflect facilitation of object-specific processing areas within the temporal lobe by an orbito-frontal top-down signal as proposed by bi-directional accounts of object recognition. PMID:23056558

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Influence of Blurred Ways on Pattern Recognition of a Scale-Free Hopfield Neural Network

NASA Astrophysics Data System (ADS)

Chang, Wen-Li

2010-01-01

We investigate the influence of blurred ways on pattern recognition of a Barabási-Albert scale-free Hopfield neural network (SFHN) with a small amount of errors. Pattern recognition is an important function of information processing in brain. Due to heterogeneous degree of scale-free network, different blurred ways have different influences on pattern recognition with same errors. Simulation shows that among partial recognition, the larger loading ratio (the number of patterns to average degree P/langlekrangle) is, the smaller the overlap of SFHN is. The influence of directed (large) way is largest and the directed (small) way is smallest while random way is intermediate between them. Under the ratio of the numbers of stored patterns to the size of the network P/N is less than 0. 1 conditions, there are three families curves of the overlap corresponding to directed (small), random and directed (large) blurred ways of patterns and these curves are not associated with the size of network and the number of patterns. This phenomenon only occurs in the SFHN. These conclusions are benefit for understanding the relation between neural network structure and brain function.

The recognition of graphical patterns invariant to geometrical transformation of the models

NASA Astrophysics Data System (ADS)

Ileană, Ioan; Rotar, Corina; Muntean, Maria; Ceuca, Emilian

2010-11-01

In case that a pattern recognition system is used for images recognition (in robot vision, handwritten recognition etc.), the system must have the capacity to identify an object indifferently of its size or position in the image. The problem of the invariance of recognition can be approached in some fundamental modes. One may apply the similarity criterion used in associative recall. The original pattern is replaced by a mathematical transform that assures some invariance (e.g. the value of two-dimensional Fourier transformation is translation invariant, the value of Mellin transformation is scale invariant). In a different approach the original pattern is represented through a set of features, each of them being coded indifferently of the position, orientation or position of the pattern. Generally speaking, it is easy to obtain invariance in relation with one transformation group, but is difficult to obtain simultaneous invariance at rotation, translation and scale. In this paper we analyze some methods to achieve invariant recognition of images, particularly for digit images. A great number of experiments are due and the conclusions are underplayed in the paper.

Engaging and disengaging recurrent inhibition coincides with sensing and unsensing of a sensory stimulus

PubMed Central

Saha, Debajit; Sun, Wensheng; Li, Chao; Nizampatnam, Srinath; Padovano, William; Chen, Zhengdao; Chen, Alex; Altan, Ege; Lo, Ray; Barbour, Dennis L.; Raman, Baranidharan

2017-01-01

Even simple sensory stimuli evoke neural responses that are dynamic and complex. Are the temporally patterned neural activities important for controlling the behavioral output? Here, we investigated this issue. Our results reveal that in the insect antennal lobe, due to circuit interactions, distinct neural ensembles are activated during and immediately following the termination of every odorant. Such non-overlapping response patterns are not observed even when the stimulus intensity or identities were changed. In addition, we find that ON and OFF ensemble neural activities differ in their ability to recruit recurrent inhibition, entrain field-potential oscillations and more importantly in their relevance to behaviour (initiate versus reset conditioned responses). Notably, we find that a strikingly similar strategy is also used for encoding sound onsets and offsets in the marmoset auditory cortex. In sum, our results suggest a general approach where recurrent inhibition is associated with stimulus ‘recognition' and ‘derecognition'. PMID:28534502

The evolution of meaning: spatio-temporal dynamics of visual object recognition.

PubMed

Clarke, Alex; Taylor, Kirsten I; Tyler, Lorraine K

2011-08-01

Research on the spatio-temporal dynamics of visual object recognition suggests a recurrent, interactive model whereby an initial feedforward sweep through the ventral stream to prefrontal cortex is followed by recurrent interactions. However, critical questions remain regarding the factors that mediate the degree of recurrent interactions necessary for meaningful object recognition. The novel prediction we test here is that recurrent interactivity is driven by increasing semantic integration demands as defined by the complexity of semantic information required by the task and driven by the stimuli. To test this prediction, we recorded magnetoencephalography data while participants named living and nonliving objects during two naming tasks. We found that the spatio-temporal dynamics of neural activity were modulated by the level of semantic integration required. Specifically, source reconstructed time courses and phase synchronization measures showed increased recurrent interactions as a function of semantic integration demands. These findings demonstrate that the cortical dynamics of object processing are modulated by the complexity of semantic information required from the visual input.

Pattern recognition technique

NASA Technical Reports Server (NTRS)

Hong, J. P.

1971-01-01

Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

NASA Astrophysics Data System (ADS)

Khoshahval, S.; Farnaghi, M.; Taleai, M.

2017-09-01

Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user's visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users' behaviour in a system and can be utilized in various location-based applications.

Selective amygdalohippocampectomy versus standard temporal lobectomy in patients with mesiotemporal lobe epilepsy and unilateral hippocampal sclerosis: post-operative facial emotion recognition abilities.

PubMed

Wendling, Anne-Sophie; Steinhoff, Bernhard J; Bodin, Frédéric; Staack, Anke M; Zentner, Josef; Scholly, Julia; Valenti, Maria-Paula; Schulze-Bonhage, Andreas; Hirsch, Edouard

2015-03-01

Surgical treatment of mesial temporal lobe epilepsy (mTLE) patients involves the removal either of the left or the right hippocampus. Since the mesial temporal lobe is responsible for emotion recognition abilities, we aimed to assess facial emotion recognition (FER) in two homogeneous patient cohorts that differed only in the administered surgery design since anterior temporal lobectomy (ATL) or selective amygdalohippocampectomy (SAH) were performed independently of the underlying electroclinical conditions. The patient selection for the two respective surgical procedures was carried out retrospectively between 2000 and 2009 by two independent epilepsy centres, the Kork Epilepsy Centre, Germany and the University Hospital of Strasbourg, France. All included patients had presented with unilateral hippocampus sclerosis (HS) without associated dysplasia or white matter blurring and had become seizure-free postoperatively. Psychometric evaluation was carried out with the Ekman 60 Faces Test and screened for depression and psychosomatic symptoms with the SCL-90 R and the BDI. Thirty healthy volunteers participated as control subjects. Sixty patients were included, 27 had undergone SAH and 33 ATL. Patients and controls obtained comparable scores in FER for surprise, happiness, anger and sadness. Concerning fear and disgust the patient group scored significantly worse. Left-sided operations led to the the most pronounced impairment. The ATL group scored significantly worse for recognition of fear compared with SAH patients. Inversely, after SAH scores for disgust were significantly lower than after ATL, independently of the side of resection. Unilateral temporal damage impairs FER. Different neurosurgical procedures may affect FER differently. Copyright © 2015 Elsevier B.V. All rights reserved.

A comparison of the real-time controllability of pattern recognition to conventional myoelectric control for discrete and simultaneous movements

PubMed Central

2014-01-01

Myoelectric control has been used for decades to control powered upper limb prostheses. Conventional, amplitude-based control has been employed to control a single prosthesis degree of freedom (DOF) such as closing and opening of the hand. Within the last decade, new and advanced arm and hand prostheses have been constructed that are capable of actuating numerous DOFs. Pattern recognition control has been proposed to control a greater number of DOFs than conventional control, but has traditionally been limited to sequentially controlling DOFs one at a time. However, able-bodied individuals use multiple DOFs simultaneously, and it may be beneficial to provide amputees the ability to perform simultaneous movements. In this study, four amputees who had undergone targeted motor reinnervation (TMR) surgery with previous training using myoelectric prostheses were configured to use three control strategies: 1) conventional amplitude-based myoelectric control, 2) sequential (one-DOF) pattern recognition control, 3) simultaneous pattern recognition control. Simultaneous pattern recognition was enabled by having amputees train each simultaneous movement as a separate motion class. For tasks that required control over just one DOF, sequential pattern recognition based control performed the best with the lowest average completion times, completion rates and length error. For tasks that required control over 2 DOFs, the simultaneous pattern recognition controller performed the best with the lowest average completion times, completion rates and length error compared to the other control strategies. In the two strategies in which users could employ simultaneous movements (conventional and simultaneous pattern recognition), amputees chose to use simultaneous movements 78% of the time with simultaneous pattern recognition and 64% of the time with conventional control for tasks that required two DOF motions to reach the target. These results suggest that when amputees are given the ability to control multiple DOFs simultaneously, they choose to perform tasks that utilize multiple DOFs with simultaneous movements. Additionally, they were able to perform these tasks with higher performance (faster speed, lower length error and higher completion rates) without losing substantial performance in 1 DOF tasks. PMID:24410948

ARCH: Adaptive recurrent-convolutional hybrid networks for long-term action recognition

PubMed Central

Xin, Miao; Zhang, Hong; Wang, Helong; Sun, Mingui; Yuan, Ding

2017-01-01

Recognition of human actions from digital video is a challenging task due to complex interfering factors in uncontrolled realistic environments. In this paper, we propose a learning framework using static, dynamic and sequential mixed features to solve three fundamental problems: spatial domain variation, temporal domain polytrope, and intra- and inter-class diversities. Utilizing a cognitive-based data reduction method and a hybrid “network upon networks” architecture, we extract human action representations which are robust against spatial and temporal interferences and adaptive to variations in both action speed and duration. We evaluated our method on the UCF101 and other three challenging datasets. Our results demonstrated a superior performance of the proposed algorithm in human action recognition. PMID:29290647

Video-based convolutional neural networks for activity recognition from robot-centric videos

NASA Astrophysics Data System (ADS)

Ryoo, M. S.; Matthies, Larry

2016-05-01

In this evaluation paper, we discuss convolutional neural network (CNN)-based approaches for human activity recognition. In particular, we investigate CNN architectures designed to capture temporal information in videos and their applications to the human activity recognition problem. There have been multiple previous works to use CNN-features for videos. These include CNNs using 3-D XYT convolutional filters, CNNs using pooling operations on top of per-frame image-based CNN descriptors, and recurrent neural networks to learn temporal changes in per-frame CNN descriptors. We experimentally compare some of these different representatives CNNs while using first-person human activity videos. We especially focus on videos from a robots viewpoint, captured during its operations and human-robot interactions.

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

NASA Astrophysics Data System (ADS)

Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

Basics of identification measurement technology

NASA Astrophysics Data System (ADS)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

Effect of speech-intrinsic variations on human and automatic recognition of spoken phonemes.

PubMed

Meyer, Bernd T; Brand, Thomas; Kollmeier, Birger

2011-01-01

The aim of this study is to quantify the gap between the recognition performance of human listeners and an automatic speech recognition (ASR) system with special focus on intrinsic variations of speech, such as speaking rate and effort, altered pitch, and the presence of dialect and accent. Second, it is investigated if the most common ASR features contain all information required to recognize speech in noisy environments by using resynthesized ASR features in listening experiments. For the phoneme recognition task, the ASR system achieved the human performance level only when the signal-to-noise ratio (SNR) was increased by 15 dB, which is an estimate for the human-machine gap in terms of the SNR. The major part of this gap is attributed to the feature extraction stage, since human listeners achieve comparable recognition scores when the SNR difference between unaltered and resynthesized utterances is 10 dB. Intrinsic variabilities result in strong increases of error rates, both in human speech recognition (HSR) and ASR (with a relative increase of up to 120%). An analysis of phoneme duration and recognition rates indicates that human listeners are better able to identify temporal cues than the machine at low SNRs, which suggests incorporating information about the temporal dynamics of speech into ASR systems.

Domain-specific impairment of source memory following a right posterior medial temporal lobe lesion.

PubMed

Peters, Jan; Koch, Benno; Schwarz, Michael; Daum, Irene

2007-01-01

This single case analysis of memory performance in a patient with an ischemic lesion affecting posterior but not anterior right medial temporal lobe (MTL) indicates that source memory can be disrupted in a domain-specific manner. The patient showed normal recognition memory for gray-scale photos of objects (visual condition) and spoken words (auditory condition). While memory for visual source (texture/color of the background against which pictures appeared) was within the normal range, auditory source memory (male/female speaker voice) was at chance level, a performance pattern significantly different from the control group. This dissociation is consistent with recent fMRI evidence of anterior/posterior MTL dissociations depending upon the nature of source information (visual texture/color vs. auditory speaker voice). The findings are in good agreement with the view of dissociable memory processing by the perirhinal cortex (anterior MTL) and parahippocampal cortex (posterior MTL), depending upon the neocortical input that these regions receive. (c) 2007 Wiley-Liss, Inc.

Classic and recent advances in understanding amnesia.

PubMed

Allen, Richard J

2018-01-01

Neurological amnesia has been and remains the focus of intense study, motivated by the drive to understand typical and atypical memory function and the underlying brain basis that is involved. There is now a consensus that amnesia associated with hippocampal (and, in many cases, broader medial temporal lobe) damage results in deficits in episodic memory, delayed recall, and recollective experience. However, debate continues regarding the patterns of preservation and impairment across a range of abilities, including semantic memory and learning, delayed recognition, working memory, and imagination. This brief review highlights some of the influential and recent advances in these debates and what they may tell us about the amnesic condition and hippocampal function.

A spatiotemporal profile of visual system activation revealed by current source density analysis in the awake macaque.

PubMed

Schroeder, C E; Mehta, A D; Givre, S J

1998-01-01

We investigated the spatiotemporal activation pattern, produced by one visual stimulus, across cerebral cortical regions in awake monkeys. Laminar profiles of postsynaptic potentials and action potentials were indexed with current source density (CSD) and multiunit activity profiles respectively. Locally, we found contrasting activation profiles in dorsal and ventral stream areas. The former, like V1 and V2, exhibit a 'feedforward' profile, with excitation beginning at the depth of Lamina 4, followed by activation of the extragranular laminae. The latter often displayed a multilaminar/columnar profile, with initial responses distributed across the laminae and reflecting modulation rather than excitation; CSD components were accompanied by either no changes or by suppression of action potentials. System-wide, response latencies indicated a large dorsal/ventral stream latency advantage, which generalizes across a wide range of methods. This predicts a specific temporal ordering of dorsal and ventral stream components of visual analysis, as well as specific patterns of dorsal-ventral stream interaction. Our findings support a hierarchical model of cortical organization that combines serial and parallel elements. Critical in such a model is the recognition that processing within a location typically entails multiple temporal components or 'waves' of activity, driven by input conveyed over heterogeneous pathways from the retina.

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

Physical Exercise During Adolescence Versus Adulthood: Differential Effects on Object Recognition Memory and BDNF Levels

PubMed Central

Hopkins, Michael E.; Nitecki, Roni; Bucci, David J.

2011-01-01

It is well established that physical exercise can enhance hippocampal-dependent forms of learning and memory in laboratory animals, commensurate with increases in hippocampal neural plasticity (BDNF mRNA/protein, neurogenesis, LTP). However, very little is known about the effects of exercise on other, non-spatial forms of learning and memory. In addition, there has been little investigation of the duration of the effects of exercise on behavior or plasticity. Likewise, few studies have compared the effects of exercising during adulthood versus adolescence. This is particularly important since exercise may capitalize on the peak of neural plasticity observed during adolescence, resulting in a different pattern of behavioral and neurobiological effects. The present study addressed these gaps in the literature by comparing the effects of 4 weeks of voluntary exercise (wheel running) during adulthood or adolescence on novel object recognition and BDNF levels in the perirhinal cortex (PER) and hippocampus (HP). Exercising during adulthood improved object recognition memory when rats were tested immediately after 4 weeks of exercise, an effect that was accompanied by increased BDNF levels in PER and HP. When rats were tested again 2 weeks after exercise ended, the effects of exercise on recognition memory and BDNF levels were no longer present. Exercising during adolescence had a very different pattern of effects. First, both exercising and non-exercising rats could discriminate between novel and familiar objects immediately after the exercise regimen ended; furthermore there was no group difference in BDNF levels. Two or four weeks later, however, rats that had previously exercised as adolescents could still discriminate between novel and familiar objects, while non-exercising rats could not. Moreover, the formerly exercising rats exhibited higher levels of BDNF in PER compared to HP, while the reverse was true in the non-exercising rats. These findings reveal a novel interaction between exercise, development, and medial temporal lobe memory systems. PMID:21839807

33 CFR 106.215 - Company or OCS facility personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

... appropriate: (a) Knowledge of current and anticipated security threats and patterns. (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Recognition of techniques used to circumvent security...

33 CFR 106.215 - Company or OCS facility personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

... appropriate: (a) Knowledge of current and anticipated security threats and patterns. (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Recognition of techniques used to circumvent security...

Facial expression recognition based on improved local ternary pattern and stacked auto-encoder

NASA Astrophysics Data System (ADS)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to enhance the robustness of facial expression recognition, we propose a method of facial expression recognition based on improved Local Ternary Pattern (LTP) combined with Stacked Auto-Encoder (SAE). This method uses the improved LTP extraction feature, and then uses the improved depth belief network as the detector and classifier to extract the LTP feature. The combination of LTP and improved deep belief network is realized in facial expression recognition. The recognition rate on CK+ databases has improved significantly.

Multi-modal imaging predicts memory performance in normal aging and cognitive decline.

PubMed

Walhovd, K B; Fjell, A M; Dale, A M; McEvoy, L K; Brewer, J; Karow, D S; Salmon, D P; Fennema-Notestine, C

2010-07-01

This study (n=161) related morphometric MR imaging, FDG-PET and APOE genotype to memory scores in normal controls (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD). Stepwise regression analyses focused on morphometric and metabolic characteristics of the episodic memory network: hippocampus, entorhinal, parahippocampal, retrosplenial, posterior cingulate, precuneus, inferior parietal, and lateral orbitofrontal cortices. In NC, hippocampal metabolism predicted learning; entorhinal metabolism predicted recognition; and hippocampal metabolism predicted recall. In MCI, thickness of the entorhinal and precuneus cortices predicted learning, while parahippocampal metabolism predicted recognition. In AD, posterior cingulate cortical thickness predicted learning, while APOE genotype predicted recognition. In the total sample, hippocampal volume and metabolism, cortical thickness of the precuneus, and inferior parietal metabolism predicted learning; hippocampal volume and metabolism, parahippocampal thickness and APOE genotype predicted recognition. Imaging methods appear complementary and differentially sensitive to memory in health and disease. Medial temporal and parietal metabolism and morphometry best explained memory variance. Medial temporal characteristics were related to learning, recall and recognition, while parietal structures only predicted learning. Copyright 2008. Published by Elsevier Inc.

The pupillary response discriminates between subjective and objective familiarity and novelty.

PubMed

Kafkas, Alexandros; Montaldi, Daniela

2015-10-01

The pupil response discriminates between old and new stimuli, with old stimuli characterized by larger pupil dilation patterns than new stimuli. We sought to explore the cause of the pupil old/new effect and discount the effect of targetness, effort, recollection retrieval, and complexity of the recognition decision. Two experiments are reported in which the pupil response and the eye fixation patterns were measured, while participants identified novel and familiar object stimuli, in two separate tasks, emphasizing either novelty or familiarity detection. In Experiment 1, familiarity and novelty decisions were taken using a rating scale, while in Experiment 2 a simpler yes/no decision was used. In both experiments, we found that detection of target familiar stimuli resulted in greater pupil dilation than the detection of target novel stimuli, while the duration of the first fixation discriminated between familiar and novel stimuli as early as within 320 ms after stimulus onset. Importantly, the pupil response distinguished between the objective (during an earlier temporal component) and the subjective (during a later temporal component) status of the stimulus for misses and false alarms. In the light of previous findings, we suggest that the pupil and fixation old/new effects reflect the distinct neural and cognitive mechanisms involved in the familiarity and novelty decisions. The findings also have important implications for the use of pupil dilation and eye movement patterns to explore explicit and implicit memory processes. © 2015 The Authors. Psychophysiology published by Wiley Periodicals, Inc. on behalf of Society for Psychophysiological Research.

Deficits in temporal order memory induced by interferon-alpha (IFN-α) treatment are rescued by aerobic exercise.

PubMed

Barlow, Sally; Fahey, Briana; Smith, Kimberley J; Passecker, Johannes; Della-Chiesa, Andrea; Hok, Vincent; Day, Jennifer S; Callaghan, Charlotte K; O'Mara, Shane M

2018-05-18

Patients receiving cytokine immunotherapy with IFN-α frequently present with neuropsychiatric consequences and cognitive impairments, including a profound depressive-like symptomatology. While the neurobiological substrates of the dysfunction that leads to adverse events in IFN-α-treated patients remains ill-defined, dysfunctions of the hippocampus and prefrontal cortex (PFC) are strong possibilities. To date, hippocampal deficits have been well-characterised; there does however remain a lack of insight into the nature of prefrontal participation. Here, we used a PFC-supported temporal order memory paradigm to examine if IFN-α treatment induced deficits in performance; additionally, we used an object recognition task to assess the integrity of the perirhinal cortex (PRH). Finally, the utility of exercise as an ameliorative strategy to recover temporal order deficits in rats was also explored. We found that IFN-α-treatment impaired temporal order memory discriminations, whereas recognition memory remained intact, reflecting a possible dissociation between recognition and temporal order memory processing. Further characterisation of temporal order memory impairments using a longitudinal design revealed that deficits persisted for 10 weeks following cessation of IFN-α-treatment. Finally, a 6 week forced exercise regime reversed IFN-α-induced deficits in temporal order memory. These data provide further insight into the circuitry involved in cognitive impairments arising from IFN-α-treatment. Here we suggest that PFC (or the hippocampo-prefrontal pathway) may be compromised whilst the function of the PRH is preserved. Deficits may persist after cessation of IFN-α-treatment which suggests that extended patient monitoring is required. Aerobic exercise may be restorative and could prove beneficial for patients treated with IFN-α. Copyright © 2018 Elsevier Inc. All rights reserved.

Neural correlates of impaired emotion processing in manifest Huntington's disease.

PubMed

Dogan, Imis; Saß, Christian; Mirzazade, Shahram; Kleiman, Alexandra; Werner, Cornelius J; Pohl, Anna; Schiefer, Johannes; Binkofski, Ferdinand; Schulz, Jörg B; Shah, N Jon; Reetz, Kathrin

2014-05-01

The complex phenotype of Huntington's disease (HD) encompasses motor, psychiatric and cognitive dysfunctions, including early impairments in emotion recognition. In this first functional magnetic resonance imaging study, we investigated emotion-processing deficits in 14 manifest HD patients and matched controls. An emotion recognition task comprised short video clips displaying one of six basic facial expressions (sadness, happiness, disgust, fear, anger and neutral). Structural changes between patients and controls were assessed by means of voxel-based morphometry. Along with deficient recognition of negative emotions, patients exhibited predominantly lower neural response to stimuli of negative valences in the amygdala, hippocampus, striatum, insula, cingulate and prefrontal cortices, as well as in sensorimotor, temporal and visual areas. Most of the observed reduced activity patterns could not be explained merely by regional volume loss. Reduced activity in the thalamus during fear correlated with lower thalamic volumes. During the processing of sadness, patients exhibited enhanced amygdala and hippocampal activity along with reduced recruitment of the medial prefrontal cortex. Higher amygdala activity was related to more pronounced amygdala atrophy and disease burden. Overall, the observed emotion-related dysfunctions in the context of structural neurodegeneration suggest both disruptions of striatal-thalamo-cortical loops and potential compensation mechanism with greater disease severity in manifest HD.

A steady state visually evoked potential investigation of memory and ageing.

PubMed

Macpherson, Helen; Pipingas, Andrew; Silberstein, Richard

2009-04-01

Old age is generally accompanied by a decline in memory performance. Specifically, neuroimaging and electrophysiological studies have revealed that there are age-related changes in the neural correlates of episodic and working memory. This study investigated age-associated changes in the steady state visually evoked potential (SSVEP) amplitude and latency associated with memory performance. Participants were 15 older (59-67 years) and 14 younger (20-30 years) adults who performed an object working memory (OWM) task and a contextual recognition memory (CRM) task, whilst the SSVEP was recorded from 64 electrode sites. Retention of a single object in the low demand OWM task was characterised by smaller frontal SSVEP amplitude and latency differences in older adults than in younger adults, indicative of an age-associated reduction in neural processes. Recognition of visual images in the more difficult CRM task was accompanied by larger, more sustained SSVEP amplitude and latency decreases over temporal parietal regions in older adults. In contrast, the more transient, frontally mediated pattern of activity demonstrated by younger adults suggests that younger and older adults utilize different neural resources to perform recognition judgements. The results provide support for compensatory processes in the aging brain; at lower task demands, older adults demonstrate reduced neural activity, whereas at greater task demands neural activity is increased.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Theoretical Aspects of the Patterns Recognition Statistical Theory Used for Developing the Diagnosis Algorithms for Complicated Technical Systems

NASA Astrophysics Data System (ADS)

Obozov, A. A.; Serpik, I. N.; Mihalchenko, G. S.; Fedyaeva, G. A.

2017-01-01

In the article, the problem of application of the pattern recognition (a relatively young area of engineering cybernetics) for analysis of complicated technical systems is examined. It is shown that the application of a statistical approach for hard distinguishable situations could be the most effective. The different recognition algorithms are based on Bayes approach, which estimates posteriori probabilities of a certain event and an assumed error. Application of the statistical approach to pattern recognition is possible for solving the problem of technical diagnosis complicated systems and particularly big powered marine diesel engines.

Parietal lobe critically supports successful paired immediate and single-item delayed memory for targets.

PubMed

Krumm, Sabine; Kivisaari, Sasa L; Monsch, Andreas U; Reinhardt, Julia; Ulmer, Stephan; Stippich, Christoph; Kressig, Reto W; Taylor, Kirsten I

2017-05-01

The parietal lobe is important for successful recognition memory, but its role is not yet fully understood. We investigated the parietal lobes' contribution to immediate paired-associate memory and delayed item-recognition memory separately for hits (targets) and correct rejections (distractors). We compared the behavioral performance of 56 patients with known parietal and medial temporal lobe dysfunction (i.e. early Alzheimer's Disease) to 56 healthy control participants in an immediate paired and delayed single item object memory task. Additionally, we performed voxel-based morphometry analyses to investigate the functional-neuroanatomic relationships between performance and voxel-based estimates of atrophy in whole-brain analyses. Behaviorally, all participants performed better identifying targets than rejecting distractors. The voxel-based morphometry analyses associated atrophy in the right ventral parietal cortex with fewer correct responses to familiar items (i.e. hits) in the immediate and delayed conditions. Additionally, medial temporal lobe integrity correlated with better performance in rejecting distractors, but not in identifying targets, in the immediate paired-associate task. Our findings suggest that the parietal lobe critically supports successful immediate and delayed target recognition memory, and that the ventral aspect of the parietal cortex and the medial temporal lobe may have complementary preferences for identifying targets and rejecting distractors, respectively, during recognition memory. Copyright © 2017. Published by Elsevier Inc.

ICPR-2016 - International Conference on Pattern Recognition

Science.gov Websites

Learning for Scene Understanding" Speakers ICPR2016 PAPER AWARDS Best Piero Zamperoni Student Paper -Paced Dictionary Learning for Cross-Domain Retrieval and Recognition Xu, Dan; Song, Jingkuan; Alameda discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and

The Spatial Vision Tree: A Generic Pattern Recognition Engine- Scientific Foundations, Design Principles, and Preliminary Tree Design

NASA Technical Reports Server (NTRS)

Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2010-01-01

New foundational ideas are used to define a novel approach to generic visual pattern recognition. These ideas proceed from the starting point of the intrinsic equivalence of noise reduction and pattern recognition when noise reduction is taken to its theoretical limit of explicit matched filtering. This led us to think of the logical extension of sparse coding using basis function transforms for both de-noising and pattern recognition to the full pattern specificity of a lexicon of matched filter pattern templates. A key hypothesis is that such a lexicon can be constructed and is, in fact, a generic visual alphabet of spatial vision. Hence it provides a tractable solution for the design of a generic pattern recognition engine. Here we present the key scientific ideas, the basic design principles which emerge from these ideas, and a preliminary design of the Spatial Vision Tree (SVT). The latter is based upon a cryptographic approach whereby we measure a large aggregate estimate of the frequency of occurrence (FOO) for each pattern. These distributions are employed together with Hamming distance criteria to design a two-tier tree. Then using information theory, these same FOO distributions are used to define a precise method for pattern representation. Finally the experimental performance of the preliminary SVT on computer generated test images and complex natural images is assessed.

Modeling Interval Temporal Dependencies for Complex Activities Understanding

DTIC Science & Technology

2013-10-11

ORGANIZATION NAMES AND ADDRESSES U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS Human activity modeling...computer vision applications: human activity recognition and facial activity recognition. The results demonstrate the superior performance of the

Hopfield's Model of Patterns Recognition and Laws of Artistic Perception

NASA Astrophysics Data System (ADS)

Yevin, Igor; Koblyakov, Alexander

The model of patterns recognition or attractor network model of associative memory, offered by J.Hopfield 1982, is the most known model in theoretical neuroscience. This paper aims to show, that such well-known laws of art perception as the Wundt curve, perception of visual ambiguity in art, and also the model perception of musical tonalities are nothing else than special cases of the Hopfield’s model of patterns recognition.

Computer discrimination procedures applicable to aerial and ERTS multispectral data

NASA Technical Reports Server (NTRS)

Richardson, A. J.; Torline, R. J.; Allen, W. A.

1970-01-01

Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

Integration of nonthematic details in pictures and passages.

PubMed

Viera, C L; Homa, D L

1991-01-01

Nonthematic details in naturalistic scenes were manipulated to produce four stimulus versions: color photos, black-white copies, and elaborated and unelaborated line drawings (Experiment 1); analogous verbal descriptions of each visual version were produced for Experiment 2. In Experiment 1, two or three different versions of a scene were presented in the mixed condition; the same version of the scene was repeated either two or three times in the same condition, and a 1-presentation control condition was also included. In Experiment 2, the same presentation conditions were used across different groups of subjects who either viewed the pictures or heard the descriptions. An old/new recognition test was given in which the nonstudied versions of the studied items were used as foils. Higher false recognition performances for the mixed condition were found for the visual materials in both experiments, and in the second experiment the verbal materials produced equivalently high levels of false recognition for both same and mixed conditions. Additionally, in Experiment 2 the patterns of performances across material conditions were differentially affected by the manipulation of detail in the four stimulus versions. These differences across materials suggest that the integration of semantically consistent details across temporally separable presentations is facilitated when the stimuli do not provide visual/physical attributes to enhance discrimination of different presentations. Further, the evidence derived from the visual scenes in both experiments indicates that the semantic schema abstracted from a picture is not the sole mediator of recognition performance.

Recognition of Famous Names Predicts Episodic Memory Decline in Cognitively Intact Elders

PubMed Central

Seidenberg, Michael; Kay, Christina; Woodard, John L.; Nielson, Kristy A.; Smith, J. Carson; Kandah, Cassandra; Guidotti Breting, Leslie M.; Novitski, Julia; Lancaster, Melissa; Matthews, Monica; Hantke, Nathan; Butts, Alissa; Rao, Stephen M.

2013-01-01

Objective: Semantic memory impairment is common in both Mild Cognitive Impairment (MCI) and early Alzheimer’s disease (AD), and the ability to recognize familiar people is particularly vulnerable. A time-limited temporal gradient (TG) in which well known people from decades earlier are better recalled than those learned recently is also reported in both AD and MCI. In this study, we hypothesized that the TG pattern on a famous name recognition task (FNRT) administered to cognitively intact elders would predict future episodic memory decline, and would also show a significant correlation with hippocampal volume. Methods: 78 healthy elders (ages 65-90) with normal cognition and episodic memory at baseline were administered a FNRT. Follow-up episodic memory testing 18 months later produced two groups: Declining (≥ 1 SD reduction in episodic memory) and Stable (< 1 SD). Results: The Declining group (N=27) recognized fewer recent famous names than the Stable group (N=51), while recognition for remote names was comparable. Baseline MRI volumes for both the left and right hippocampus was significantly smaller in the Declining group than the Stable group. Smaller baseline hippocampal volume was also significantly correlated with poorer performance for recent, but not remote famous names. Logistic regression analyses indicated that baseline TG performance was a significant predictor of group status (Declining versus Stable) independent of chronological age and APOE ε4 inheritance. Conclusions: Famous name recognition may serve as an early pre-clinical cognitive marker of episodic memory decline in older individuals. PMID:23688215

Temporal distance and person memory: thinking about the future changes memory for the past.

PubMed

Wyer, Natalie A; Perfect, Timothy J; Pahl, Sabine

2010-06-01

Psychological distance has been shown to influence how people construe an event such that greater distance produces high-level construal (characterized by global or holistic processing) and lesser distance produces low-level construal (characterized by detailed or feature-based processing). The present research tested the hypothesis that construal level has carryover effects on how information about an event is retrieved from memory. Two experiments manipulated temporal distance and found that greater distance (high-level construal) improves face recognition and increases retrieval of the abstract features of an event, whereas lesser distance (low-level construal) impairs face recognition and increases retrieval of the concrete details of an event. The findings have implications for transfer-inappropriate processing accounts of face recognition and event memory, and suggest potential applications in forensic settings.

Working and strategic memory deficits in schizophrenia

NASA Technical Reports Server (NTRS)

Stone, M.; Gabrieli, J. D.; Stebbins, G. T.; Sullivan, E. V.

1998-01-01

Working memory and its contribution to performance on strategic memory tests in schizophrenia were studied. Patients (n = 18) and control participants (n = 15), all men, received tests of immediate memory (forward digit span), working memory (listening, computation, and backward digit span), and long-term strategic (free recall, temporal order, and self-ordered pointing) and nonstrategic (recognition) memory. Schizophrenia patients performed worse on all tests. Education, verbal intelligence, and immediate memory capacity did not account for deficits in working memory in schizophrenia patients. Reduced working memory capacity accounted for group differences in strategic memory but not in recognition memory. Working memory impairment may be central to the profile of impaired cognitive performance in schizophrenia and is consistent with hypothesized frontal lobe dysfunction associated with this disease. Additional medial-temporal dysfunction may account for the recognition memory deficit.

Human single-neuron responses at the threshold of conscious recognition

PubMed Central

Quiroga, R. Quian; Mukamel, R.; Isham, E. A.; Malach, R.; Fried, I.

2008-01-01

We studied the responses of single neurons in the human medial temporal lobe while subjects viewed familiar faces, animals, and landmarks. By progressively shortening the duration of stimulus presentation, coupled with backward masking, we show two striking properties of these neurons. (i) Their responses are not statistically different for the 33-ms, 66-ms, and 132-ms stimulus durations, and only for the 264-ms presentations there is a significantly higher firing. (ii) These responses follow conscious perception, as indicated by the subjects' recognition report. Remarkably, when recognized, a single snapshot as brief as 33 ms was sufficient to trigger strong single-unit responses far outlasting stimulus presentation. These results suggest that neurons in the medial temporal lobe can reflect conscious recognition by “all-or-none” responses. PMID:18299568

Research on the feature extraction and pattern recognition of the distributed optical fiber sensing signal

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Sun, Qi; Pi, Shaohua; Wu, Hongyan

2014-09-01

In this paper, feature extraction and pattern recognition of the distributed optical fiber sensing signal have been studied. We adopt Mel-Frequency Cepstral Coefficient (MFCC) feature extraction, wavelet packet energy feature extraction and wavelet packet Shannon entropy feature extraction methods to obtain sensing signals (such as speak, wind, thunder and rain signals, etc.) characteristic vectors respectively, and then perform pattern recognition via RBF neural network. Performances of these three feature extraction methods are compared according to the results. We choose MFCC characteristic vector to be 12-dimensional. For wavelet packet feature extraction, signals are decomposed into six layers by Daubechies wavelet packet transform, in which 64 frequency constituents as characteristic vector are respectively extracted. In the process of pattern recognition, the value of diffusion coefficient is introduced to increase the recognition accuracy, while keeping the samples for testing algorithm the same. Recognition results show that wavelet packet Shannon entropy feature extraction method yields the best recognition accuracy which is up to 97%; the performance of 12-dimensional MFCC feature extraction method is less satisfactory; the performance of wavelet packet energy feature extraction method is the worst.

A Temporal Pattern Mining Approach for Classifying Electronic Health Record Data

PubMed Central

Batal, Iyad; Valizadegan, Hamed; Cooper, Gregory F.; Hauskrecht, Milos

2013-01-01

We study the problem of learning classification models from complex multivariate temporal data encountered in electronic health record systems. The challenge is to define a good set of features that are able to represent well the temporal aspect of the data. Our method relies on temporal abstractions and temporal pattern mining to extract the classification features. Temporal pattern mining usually returns a large number of temporal patterns, most of which may be irrelevant to the classification task. To address this problem, we present the Minimal Predictive Temporal Patterns framework to generate a small set of predictive and non-spurious patterns. We apply our approach to the real-world clinical task of predicting patients who are at risk of developing heparin induced thrombocytopenia. The results demonstrate the benefit of our approach in efficiently learning accurate classifiers, which is a key step for developing intelligent clinical monitoring systems. PMID:25309815

Brain regions and functional interactions supporting early word recognition in the face of input variability.

PubMed

Benavides-Varela, Silvia; Siugzdaite, Roma; Gómez, David Maximiliano; Macagno, Francesco; Cattarossi, Luigi; Mehler, Jacques

2017-07-18

Perception and cognition in infants have been traditionally investigated using habituation paradigms, assuming that babies' memories in laboratory contexts are best constructed after numerous repetitions of the very same stimulus in the absence of interference. A crucial, yet open, question regards how babies deal with stimuli experienced in a fashion similar to everyday learning situations-namely, in the presence of interfering stimuli. To address this question, we used functional near-infrared spectroscopy to test 40 healthy newborns on their ability to encode words presented in concomitance with other words. The results evidenced a habituation-like hemodynamic response during encoding in the left-frontal region, which was associated with a progressive decrement of the functional connections between this region and the left-temporal, right-temporal, and right-parietal regions. In a recognition test phase, a characteristic neural signature of recognition recruited first the right-frontal region and subsequently the right-parietal ones. Connections originating from the right-temporal regions to these areas emerged when newborns listened to the familiar word in the test phase. These findings suggest a neural specialization at birth characterized by the lateralization of memory functions: the interplay between temporal and left-frontal regions during encoding and between temporo-parietal and right-frontal regions during recognition of speech sounds. Most critically, the results show that newborns are capable of retaining the sound of specific words despite hearing other stimuli during encoding. Thus, habituation designs that include various items may be as effective for studying early memory as repeated presentation of a single word.

Emotion recognition and social cognition in temporal lobe epilepsy and the effect of epilepsy surgery.

PubMed

Amlerova, Jana; Cavanna, Andrea E; Bradac, Ondrej; Javurkova, Alena; Raudenska, Jaroslava; Marusic, Petr

2014-07-01

The abilities to identify facial expression from another person's face and to attribute mental states to others refer to preserved function of the temporal lobes. In the present study, we set out to evaluate emotion recognition and social cognition in presurgical and postsurgical patients with unilateral refractory temporal lobe epilepsy (TLE). The aim of our study was to investigate the effects of TLE surgery and to identify the main risk factors for impairment in these functions. We recruited 30 patients with TLE for longitudinal data analysis (14 with right-sided and 16 with left-sided TLE) and 74 patients for cross-sectional data analysis (37 with right-sided and 37 with left-sided TLE) plus 20 healthy controls. Besides standard neuropsychological assessment, we administered an analog of the Ekman and Friesen test and the Faux Pas Test to assess emotion recognition and social cognition, respectively. Both emotion recognition and social cognition were impaired in the group of patients with TLE, irrespective of the focus side, compared with healthy controls. The performance in both tests was strongly dependent on the intelligence level. Beyond intelligence level, earlier age at epilepsy onset, longer disease duration, and history of early childhood brain injury predicted social cognition problems in patients with TLE. Epilepsy surgery within the temporal lobe seems to have neutral effect on patients' performances in both domains. However, there are a few individual patients who appear to be at risk of postoperative decline, even when seizure freedom is achieved following epilepsy surgery. Copyright © 2014 Elsevier Inc. All rights reserved.

Pattern association--a key to recognition of shark attacks.

PubMed

Cirillo, G; James, H

2004-12-01

Investigation of a number of shark attacks in South Australian waters has lead to recognition of pattern similarities on equipment recovered from the scene of such attacks. Six cases are presented in which a common pattern of striations has been noted.

Adaptive Changes in Grain-Size in Morphological Processing

ERIC Educational Resources Information Center

Lee, Chang H.

2008-01-01

Substantial neurobiological data indicate that the dominant cortical region for printed-word recognition shifts from a temporo-parietal (dorsal) to an occipito-temporal (ventral) locus with increasing recognition experience. The circuits also have different characteristic speeds of response and word preferences. Previous evidence suggested that…

Dissecting out conscious and unconscious memory (sub)processes within the human medial temporal lobe.

PubMed

Grunwald, T; Pezer, N; Münte, T F; Kurthen, M; Lehnertz, K; Van Roost, D; Fernández, G; Kutas, M; Elger, C E

2003-11-01

The human medial temporal lobe (MTL) system mediates memories that can be consciously recollected. However, the specific natures of the individual contributions of its various subregions to conscious memory processes remain equivocal. Here we show a functional dissociation between the hippocampus proper and the parahippocampal region in conscious and unconscious memory as revealed by invasive recordings of limbic event-related brain potentials recorded during explicit and implicit word recognition: Only hippocampal and not parahippocampal neural activity exhibits a sensitivity to the implicit versus explicit nature of the recognition memory task. Moreover, only within the hippocampus proper do the neural responses to repeated words differ not only from those to new words but also from each other as a function of recognition success. By contrast parahippocampal (rhinal) responses are sensitive to repetition independent of conscious recognition. These findings thus demonstrate that it is the hippocampus proper among the MTL structures that is specifically engaged during conscious memory processes.

Recognition vs Reverse Engineering in Boolean Concepts Learning

ERIC Educational Resources Information Center

Shafat, Gabriel; Levin, Ilya

2012-01-01

This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

Finger vein recognition based on personalized weight maps.

PubMed

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-09-10

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition.

Finger Vein Recognition Based on Personalized Weight Maps

PubMed Central

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-01-01

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition. PMID:24025556

Classifying adolescent attention-deficit/hyperactivity disorder (ADHD) based on functional and structural imaging.

PubMed

Iannaccone, Reto; Hauser, Tobias U; Ball, Juliane; Brandeis, Daniel; Walitza, Susanne; Brem, Silvia

2015-10-01

Attention-deficit/hyperactivity disorder (ADHD) is a common disabling psychiatric disorder associated with consistent deficits in error processing, inhibition and regionally decreased grey matter volumes. The diagnosis is based on clinical presentation, interviews and questionnaires, which are to some degree subjective and would benefit from verification through biomarkers. Here, pattern recognition of multiple discriminative functional and structural brain patterns was applied to classify adolescents with ADHD and controls. Functional activation features in a Flanker/NoGo task probing error processing and inhibition along with structural magnetic resonance imaging data served to predict group membership using support vector machines (SVMs). The SVM pattern recognition algorithm correctly classified 77.78% of the subjects with a sensitivity and specificity of 77.78% based on error processing. Predictive regions for controls were mainly detected in core areas for error processing and attention such as the medial and dorsolateral frontal areas reflecting deficient processing in ADHD (Hart et al., in Hum Brain Mapp 35:3083-3094, 2014), and overlapped with decreased activations in patients in conventional group comparisons. Regions more predictive for ADHD patients were identified in the posterior cingulate, temporal and occipital cortex. Interestingly despite pronounced univariate group differences in inhibition-related activation and grey matter volumes the corresponding classifiers failed or only yielded a poor discrimination. The present study corroborates the potential of task-related brain activation for classification shown in previous studies. It remains to be clarified whether error processing, which performed best here, also contributes to the discrimination of useful dimensions and subtypes, different psychiatric disorders, and prediction of treatment success across studies and sites.

Medial temporal lobe function during emotional memory in early Alzheimer's disease, mild cognitive impairment and healthy ageing: an fMRI study.

PubMed

Parra, Mario A; Pattan, Vivek; Wong, Dichelle; Beaglehole, Anna; Lonie, Jane; Wan, Hong I; Honey, Garry; Hall, Jeremy; Whalley, Heather C; Lawrie, Stephen M

2013-03-06

Relative to intentional memory encoding, which quickly declines in Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD), incidental memory for emotional stimuli appears to deteriorate more slowly. We hypothesised that tests of incidental emotional memory may inform on different aspects of cognitive decline in MCI and AD. Patients with MCI, AD and Healthy Controls (HC) were asked to attend to emotional pictures (i.e., positive and neutral) sequentially presented during an fMRI session. Attention was monitored behaviourally. A surprise post-scan recognition test was then administered. The groups remained attentive within the scanner. The post-scan recognition pattern was in the form of (HC = MCI) > AD, with only the former group showing a clear benefit from emotional pictures. fMRI analysis of incidental encoding demonstrated clusters of activation in para-hippocampal regions and in the hippocampus in HC and MCI patients but not in AD patients. The pattern of activation observed in MCI patients tended to be greater than that found in HC. The results suggest that incidental emotional memory might offer a suitable platform to investigate, using behavioural and fMRI measures, subtle changes in the process of developing AD. These changes seem to differ from those found using standard episodic memory tests. The underpinnings of such differences and the potential clinical use of this methodology are discussed in depth.

A bacterial tyrosine phosphatase inhibits plant pattern recognition receptor activation

USDA-ARS?s Scientific Manuscript database

Perception of pathogen-associated molecular patterns (PAMPs) by surface-localised pattern-recognition receptors (PRRs) is a key component of plant innate immunity. Most known plant PRRs are receptor kinases and initiation of PAMP-triggered immunity (PTI) signalling requires phosphorylation of the PR...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2011 CFR

2011-07-01

... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (xi...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2010 CFR

2010-07-01

... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (xi...

Infrared face recognition based on LBP histogram and KW feature selection

NASA Astrophysics Data System (ADS)

Xie, Zhihua

2014-07-01

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

The structural neuroanatomy of music emotion recognition: Evidence from frontotemporal lobar degeneration

PubMed Central

Omar, Rohani; Henley, Susie M.D.; Bartlett, Jonathan W.; Hailstone, Julia C.; Gordon, Elizabeth; Sauter, Disa A.; Frost, Chris; Scott, Sophie K.; Warren, Jason D.

2011-01-01

Despite growing clinical and neurobiological interest in the brain mechanisms that process emotion in music, these mechanisms remain incompletely understood. Patients with frontotemporal lobar degeneration (FTLD) frequently exhibit clinical syndromes that illustrate the effects of breakdown in emotional and social functioning. Here we investigated the neuroanatomical substrate for recognition of musical emotion in a cohort of 26 patients with FTLD (16 with behavioural variant frontotemporal dementia, bvFTD, 10 with semantic dementia, SemD) using voxel-based morphometry. On neuropsychological evaluation, patients with FTLD showed deficient recognition of canonical emotions (happiness, sadness, anger and fear) from music as well as faces and voices compared with healthy control subjects. Impaired recognition of emotions from music was specifically associated with grey matter loss in a distributed cerebral network including insula, orbitofrontal cortex, anterior cingulate and medial prefrontal cortex, anterior temporal and more posterior temporal and parietal cortices, amygdala and the subcortical mesolimbic system. This network constitutes an essential brain substrate for recognition of musical emotion that overlaps with brain regions previously implicated in coding emotional value, behavioural context, conceptual knowledge and theory of mind. Musical emotion recognition may probe the interface of these processes, delineating a profile of brain damage that is essential for the abstraction of complex social emotions. PMID:21385617

The structural neuroanatomy of music emotion recognition: evidence from frontotemporal lobar degeneration.

PubMed

Omar, Rohani; Henley, Susie M D; Bartlett, Jonathan W; Hailstone, Julia C; Gordon, Elizabeth; Sauter, Disa A; Frost, Chris; Scott, Sophie K; Warren, Jason D

2011-06-01

Despite growing clinical and neurobiological interest in the brain mechanisms that process emotion in music, these mechanisms remain incompletely understood. Patients with frontotemporal lobar degeneration (FTLD) frequently exhibit clinical syndromes that illustrate the effects of breakdown in emotional and social functioning. Here we investigated the neuroanatomical substrate for recognition of musical emotion in a cohort of 26 patients with FTLD (16 with behavioural variant frontotemporal dementia, bvFTD, 10 with semantic dementia, SemD) using voxel-based morphometry. On neuropsychological evaluation, patients with FTLD showed deficient recognition of canonical emotions (happiness, sadness, anger and fear) from music as well as faces and voices compared with healthy control subjects. Impaired recognition of emotions from music was specifically associated with grey matter loss in a distributed cerebral network including insula, orbitofrontal cortex, anterior cingulate and medial prefrontal cortex, anterior temporal and more posterior temporal and parietal cortices, amygdala and the subcortical mesolimbic system. This network constitutes an essential brain substrate for recognition of musical emotion that overlaps with brain regions previously implicated in coding emotional value, behavioural context, conceptual knowledge and theory of mind. Musical emotion recognition may probe the interface of these processes, delineating a profile of brain damage that is essential for the abstraction of complex social emotions. Copyright © 2011 Elsevier Inc. All rights reserved.

An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data

PubMed Central

Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800

Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers

USGS Publications Warehouse

Lottig, Noah R.; Tan, Pang-Ning; Wagner, Tyler; Cheruvelil, Kendra Spence; Soranno, Patricia A.; Stanley, Emily H.; Scott, Caren E.; Stow, Craig A.; Yuan, Shuai

2017-01-01

Ecology has a rich history of studying ecosystem dynamics across time and space that has been motivated by both practical management needs and the need to develop basic ideas about pattern and process in nature. In situations in which both spatial and temporal observations are available, similarities in temporal behavior among sites (i.e., synchrony) provide a means of understanding underlying processes that create patterns over space and time. We used pattern analysis algorithms and data spanning 22–25 yr from 601 lakes to ask three questions: What are the temporal patterns of lake water clarity at sub‐continental scales? What are the spatial patterns (i.e., geography) of synchrony for lake water clarity? And, what are the drivers of spatial and temporal patterns in lake water clarity? We found that the synchrony of water clarity among lakes is not spatially structured at sub‐continental scales. Our results also provide strong evidence that the drivers related to spatial patterns in water clarity are not related to the temporal patterns of water clarity. This analysis of long‐term patterns of water clarity and possible drivers contributes to understanding of broad‐scale spatial patterns in the geography of synchrony and complex relationships between spatial and temporal patterns across ecosystems.

2D DOST based local phase pattern for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.

Voice, Schooling, Inequality, and Scale

ERIC Educational Resources Information Center

Collins, James

2013-01-01

The rich studies in this collection show that the investigation of voice requires analysis of "recognition" across layered spatial-temporal and sociolinguistic scales. I argue that the concepts of voice, recognition, and scale provide insight into contemporary educational inequality and that their study benefits, in turn, from paying attention to…

Mining Recent Temporal Patterns for Event Detection in Multivariate Time Series Data

PubMed Central

Batal, Iyad; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

Improving the performance of classifiers using pattern mining techniques has been an active topic of data mining research. In this work we introduce the recent temporal pattern mining framework for finding predictive patterns for monitoring and event detection problems in complex multivariate time series data. This framework first converts time series into time-interval sequences of temporal abstractions. It then constructs more complex temporal patterns backwards in time using temporal operators. We apply our framework to health care data of 13,558 diabetic patients and show its benefits by efficiently finding useful patterns for detecting and diagnosing adverse medical conditions that are associated with diabetes. PMID:25937993

Neural basis for recognition confidence in younger and older adults.

PubMed

Chua, Elizabeth F; Schacter, Daniel L; Sperling, Reisa A

2009-03-01

Although several studies have examined the neural basis for age-related changes in objective memory performance, less is known about how the process of memory monitoring changes with aging. The authors used functional magnetic resonance imaging to examine retrospective confidence in memory performance in aging. During low confidence, both younger and older adults showed behavioral evidence that they were guessing during recognition and that they were aware they were guessing when making confidence judgments. Similarly, both younger and older adults showed increased neural activity during low- compared to high-confidence responses in the lateral prefrontal cortex, anterior cingulate cortex, and left intraparietal sulcus. In contrast, older adults showed more high-confidence errors than younger adults. Younger adults showed greater activity for high compared to low confidence in medial temporal lobe structures, but older adults did not show this pattern. Taken together, these findings may suggest that impairments in the confidence-accuracy relationship for memory in older adults, which are often driven by high-confidence errors, may be primarily related to altered neural signals associated with greater activity for high-confidence responses.

Neural basis for recognition confidence in younger and older adults

PubMed Central

Chua, Elizabeth F.; Schacter, Daniel L.; Sperling, Reisa A.

2008-01-01

Although several studies have examined the neural basis for age-related changes in objective memory performance, less is known about how the process of memory monitoring changes with aging. We used fMRI to examine retrospective confidence in memory performance in aging. During low confidence, both younger and older adults showed behavioral evidence that they were guessing during recognition, and that they were aware they were guessing when making confidence judgments. Similarly, both younger and older adults showed increased neural activity during low compared to high confidence responses in lateral prefrontal cortex, anterior cingulate cortex, and left intraparietal sulcus. In contrast, older adults showed more high confidence errors than younger adults. Younger adults showed greater activity for high compared to low confidence in medial temporal lobe structures, but older adults did not show this pattern. Taken together, these findings may suggest that impairments in the confidence-accuracy relationship for memory in older adults, which are often driven by high confidence errors, may be primarily related to altered neural signals associated with greater activity for high confidence responses. PMID:19290745

The effects of gender and COMT Val158Met polymorphism on fearful facial affect recognition: a fMRI study.

PubMed

Kempton, Matthew J; Haldane, Morgan; Jogia, Jigar; Christodoulou, Tessa; Powell, John; Collier, David; Williams, Steven C R; Frangou, Sophia

2009-04-01

The functional catechol-O-methyltransferase (COMT Val108/158Met) polymorphism has been shown to have an impact on tasks of executive function, memory and attention and recently, tasks with an affective component. As oestrogen reduces COMT activity, we focused on the interaction between gender and COMT genotype on brain activations during an affective processing task. We used functional MRI (fMRI) to record brain activations from 74 healthy subjects who engaged in a facial affect recognition task; subjects viewed and identified fearful compared to neutral faces. There was no main effect of the COMT polymorphism, gender or genotypexgender interaction on task performance. We found a significant effect of gender on brain activations in the left amygdala and right temporal pole, where females demonstrated increased activations over males. Within these regions, Val/Val carriers showed greater signal magnitude compared to Met/Met carriers, particularly in females. The COMT Val108/158Met polymorphism impacts on gender-related patterns of activation in limbic and paralimbic regions but the functional significance of any oestrogen-related COMT inhibition appears modest.

Effective connectivity of visual word recognition and homophone orthographic errors

PubMed Central

Guàrdia-Olmos, Joan; Peró-Cebollero, Maribel; Zarabozo-Hurtado, Daniel; González-Garrido, Andrés A.; Gudayol-Ferré, Esteve

2015-01-01

The study of orthographic errors in a transparent language like Spanish is an important topic in relation to writing acquisition. The development of neuroimaging techniques, particularly functional magnetic resonance imaging (fMRI), has enabled the study of such relationships between brain areas. The main objective of the present study was to explore the patterns of effective connectivity by processing pseudohomophone orthographic errors among subjects with high and low spelling skills. Two groups of 12 Mexican subjects each, matched by age, were formed based on their results in a series of ad hoc spelling-related out-scanner tests: a high spelling skills (HSSs) group and a low spelling skills (LSSs) group. During the f MRI session, two experimental tasks were applied (spelling recognition task and visuoperceptual recognition task). Regions of Interest and their signal values were obtained for both tasks. Based on these values, structural equation models (SEMs) were obtained for each group of spelling competence (HSS and LSS) and task through maximum likelihood estimation, and the model with the best fit was chosen in each case. Likewise, dynamic causal models (DCMs) were estimated for all the conditions across tasks and groups. The HSS group’s SEM results suggest that, in the spelling recognition task, the right middle temporal gyrus, and, to a lesser extent, the left parahippocampal gyrus receive most of the significant effects, whereas the DCM results in the visuoperceptual recognition task show less complex effects, but still congruent with the previous results, with an important role in several areas. In general, these results are consistent with the major findings in partial studies about linguistic activities but they are the first analyses of statistical effective brain connectivity in transparent languages. PMID:26042070

How landmark suitability shapes recognition memory signals for objects in the medial temporal lobes.

PubMed

Martin, Chris B; Sullivan, Jacqueline A; Wright, Jessey; Köhler, Stefan

2018-02-01

A role of perirhinal cortex (PrC) in recognition memory for objects has been well established. Contributions of parahippocampal cortex (PhC) to this function, while documented, remain less well understood. Here, we used fMRI to examine whether the organization of item-based recognition memory signals across these two structures is shaped by object category, independent of any difference in representing episodic context. Guided by research suggesting that PhC plays a critical role in processing landmarks, we focused on three categories of objects that differ from each other in their landmark suitability as confirmed with behavioral ratings (buildings > trees > aircraft). Participants made item-based recognition-memory decisions for novel and previously studied objects from these categories, which were matched in accuracy. Multi-voxel pattern classification revealed category-specific item-recognition memory signals along the long axis of PrC and PhC, with no sharp functional boundaries between these structures. Memory signals for buildings were observed in the mid to posterior extent of PhC, signals for trees in anterior to posterior segments of PhC, and signals for aircraft in mid to posterior aspects of PrC and the anterior extent of PhC. Notably, item-based memory signals for the category with highest landmark suitability ratings were observed only in those posterior segments of PhC that also allowed for classification of landmark suitability of objects when memory status was held constant. These findings provide new evidence in support of the notion that item-based memory signals for objects are not limited to PrC, and that the organization of these signals along the longitudinal axis that crosses PrC and PhC can be captured with reference to landmark suitability. Copyright © 2017 Elsevier Inc. All rights reserved.

Optical Pattern Recognition for Missile Guidance.

DTIC Science & Technology

1982-11-15

directed to novel pattern recognition algo- rithms (that allow pattern recognition and object classification in the face of various geometrical and...I wats EF5 = 50) p.j/t’ni 2 (for btith image pat tern recognitio itas a preproicessing oiperatiton. Ini devices). TIhe rt’ad light intensity (0.33t mW...electrodes on its large faces . This Priz light modulator and the motivation for its devel- SLM is known as the Prom (Pockels real-time optical opment. In Sec

Brief Report: The Role of Task Support in the Spatial and Temporal Source Memory of Adults with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Bowler, Dermot M.; Gaigg, Sebastian B.; Gardiner, John M.

2015-01-01

Adults with autism spectrum disorder (ASD) show intact recognition (supported procedure) but impaired recall (unsupported procedure) of incidentally-encoded context. Because this has not been demonstrated for temporal source, we compared the temporal and spatial source memory of adults with ASD and verbally matched typical adults. Because of…

Recognition as Support for Reasoning about Horizontal Motion: A Further Resource for School Science?

ERIC Educational Resources Information Center

Howe, Christine; Taylor Tavares, Joana; Devine, Amy

2016-01-01

Background: Even infants can recognize whether patterns of motion are or are not natural, yet an acknowledged challenge for science education is to promote adequate reasoning about such patterns. Since research indicates linkage between the conceptual bases of recognition and reasoning, it seems possible that recognition can be engaged to support…

What pharmacological interventions indicate concerning the role of the perirhinal cortex in recognition memory

PubMed Central

Brown, M.W.; Barker, G.R.I.; Aggleton, J.P.; Warburton, E.C.

2012-01-01

Findings of pharmacological studies that have investigated the involvement of specific regions of the brain in recognition memory are reviewed. The particular emphasis of the review concerns what such studies indicate concerning the role of the perirhinal cortex in recognition memory. Most of the studies involve rats and most have investigated recognition memory for objects. Pharmacological studies provide a large body of evidence supporting the essential role of the perirhinal cortex in the acquisition, consolidation and retrieval of object recognition memory. Such studies provide increasingly detailed evidence concerning both the neurotransmitter systems and the underlying intracellular mechanisms involved in recognition memory processes. They have provided evidence in support of synaptic weakening as a major synaptic plastic process within perirhinal cortex underlying object recognition memory. They have also supplied confirmatory evidence that that there is more than one synaptic plastic process involved. The demonstrated necessity to long-term recognition memory of intracellular signalling mechanisms related to synaptic modification within perirhinal cortex establishes a central role for the region in the information storage underlying such memory. Perirhinal cortex is thereby established as an information storage site rather than solely a processing station. Pharmacological studies have also supplied new evidence concerning the detailed roles of other regions, including the hippocampus and the medial prefrontal cortex in different types of recognition memory tasks that include a spatial or temporal component. In so doing, they have also further defined the contribution of perirhinal cortex to such tasks. To date it appears that the contribution of perirhinal cortex to associative and temporal order memory reflects that in simple object recognition memory, namely that perirhinal cortex provides information concerning objects and their prior occurrence (novelty/familiarity). PMID:22841990

Recollection of episodic memory within the medial temporal lobe: behavioural dissociations from other types of memory.

PubMed

Easton, Alexander; Eacott, Madeline J

2010-12-31

In recent years there has been significant debate about whether there is a single medial temporal lobe memory system or dissociable systems for episodic and other types of declarative memory. In addition there has been a similar debate over the dissociability of recollection and familiarity based processes in recognition memory. Here we present evidence from recent work using episodic memory tasks in animals that allows us to explore these issues in more depth. We review studies that demonstrate triple dissociations within the medial temporal lobe, with only the hippocampal system being necessary for episodic memory. Similarly we review behavioural evidence for a dissociation in a task of episodic memory in rats where animals with lesions of the fornix are only impaired at recollection of the episodic memory, not recognition within the same trial. This work, then, supports recent models of dissociable neural systems within the medial temporal lobe but also raises questions for future investigation about the interactions of these medial temporal lobe memory systems with other structures. Copyright © 2009 Elsevier B.V. All rights reserved.

33 CFR 105.210 - Facility personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

...: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely...

33 CFR 105.210 - Facility personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

...: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely...

Memory for temporally dynamic scenes.

PubMed

Ferguson, Ryan; Homa, Donald; Ellis, Derek

2017-07-01

Recognition memory was investigated for individual frames extracted from temporally continuous, visually rich film segments of 5-15 min. Participants viewed a short clip from a film in either a coherent or a jumbled order, followed by a recognition test of studied frames. Foils came either from an earlier or a later part of the film (Experiment 1) or from deleted segments selected from random cuts of varying duration (0.5 to 30 s) within the film itself (Experiment 2). When the foils came from an earlier or later part of the film (Experiment 1), recognition was excellent, with the hit rate far exceeding the false-alarm rate (.78 vs. 18). In Experiment 2, recognition was far worse, with the hit rate (.76) exceeding the false-alarm rate only for foils drawn from the longest cuts (15 and 30 s) and matching the false-alarm rate for the 5 s segments. When the foils were drawn from the briefest cuts (0.5 and 1.0 s), the false-alarm rate exceeded the hit rate. Unexpectedly, jumbling had no effect on recognition in either experiment. These results are consistent with the view that memory for complex visually temporal events is excellent, with the integrity unperturbed by disruption of the global structure of the visual stream. Disruption of memory was observed only when foils were drawn from embedded segments of duration less than 5 s, an outcome consistent with the view that memory at these shortest durations are consolidated with expectations drawn from the previous stream.

From The Cover: Induction of antiviral immunity requires Toll-like receptor signaling in both stromal and dendritic cell compartments

NASA Astrophysics Data System (ADS)

Sato, Ayuko; Iwasaki, Akiko

2004-11-01

Pattern recognition by Toll-like receptors (TLRs) is known to be important for the induction of dendritic cell (DC) maturation. DCs, in turn, are critically important in the initiation of T cell responses. However, most viruses do not infect DCs. This recognition system poses a biological problem in ensuring that most viral infections be detected by pattern recognition receptors. Furthermore, it is unknown what, if any, is the contribution of TLRs expressed by cells that are infected by a virus, versus TLRs expressed by DCs, in the initiation of antiviral adaptive immunity. Here we address these issues using a physiologically relevant model of mucosal infection with herpes simplex virus type 2. We demonstrate that innate immune recognition of viral infection occurs in two distinct stages, one at the level of the infected epithelial cells and the other at the level of the noninfected DCs. Importantly, both TLR-mediated recognition events are required for the induction of effector T cells. Our results demonstrate that virally infected tissues instruct DCs to initiate the appropriate class of effector T cell responses and reveal the critical importance of the stromal cells in detecting infectious agents through their own pattern recognition receptors. mucosal immunity | pattern recognition | viral infection

Time fluctuation analysis of forest fire sequences

NASA Astrophysics Data System (ADS)

Vega Orozco, Carmen D.; Kanevski, Mikhaïl; Tonini, Marj; Golay, Jean; Pereira, Mário J. G.

2013-04-01

Forest fires are complex events involving both space and time fluctuations. Understanding of their dynamics and pattern distribution is of great importance in order to improve the resource allocation and support fire management actions at local and global levels. This study aims at characterizing the temporal fluctuations of forest fire sequences observed in Portugal, which is the country that holds the largest wildfire land dataset in Europe. This research applies several exploratory data analysis measures to 302,000 forest fires occurred from 1980 to 2007. The applied clustering measures are: Morisita clustering index, fractal and multifractal dimensions (box-counting), Ripley's K-function, Allan Factor, and variography. These algorithms enable a global time structural analysis describing the degree of clustering of a point pattern and defining whether the observed events occur randomly, in clusters or in a regular pattern. The considered methods are of general importance and can be used for other spatio-temporal events (i.e. crime, epidemiology, biodiversity, geomarketing, etc.). An important contribution of this research deals with the analysis and estimation of local measures of clustering that helps understanding their temporal structure. Each measure is described and executed for the raw data (forest fires geo-database) and results are compared to reference patterns generated under the null hypothesis of randomness (Poisson processes) embedded in the same time period of the raw data. This comparison enables estimating the degree of the deviation of the real data from a Poisson process. Generalizations to functional measures of these clustering methods, taking into account the phenomena, were also applied and adapted to detect time dependences in a measured variable (i.e. burned area). The time clustering of the raw data is compared several times with the Poisson processes at different thresholds of the measured function. Then, the clustering measure value depends on the threshold which helps to understand the time pattern of the studied events. Our findings detected the presence of overdensity of events in particular time periods and showed that the forest fire sequences in Portugal can be considered as a multifractal process with a degree of time-clustering of the events. Key words: time sequences, Morisita index, fractals, multifractals, box-counting, Ripley's K-function, Allan Factor, variography, forest fires, point process. Acknowledgements This work was partly supported by the SNFS Project No. 200021-140658, "Analysis and Modelling of Space-Time Patterns in Complex Regions". References - Kanevski M. (Editor). 2008. Advanced Mapping of Environmental Data: Geostatistics, Machine Learning and Bayesian Maximum Entropy. London / Hoboken: iSTE / Wiley. - Telesca L. and Pereira M.G. 2010. Time-clustering investigation of fire temporal fluctuations in Portugal, Nat. Hazards Earth Syst. Sci., vol. 10(4): 661-666. - Vega Orozco C., Tonini M., Conedera M., Kanevski M. (2012) Cluster recognition in spatial-temporal sequences: the case of forest fires, Geoinformatica, vol. 16(4): 653-673.

Decision making and preferences for acoustic signals in choice situations by female crickets.

PubMed

Gabel, Eileen; Kuntze, Janine; Hennig, R Matthias

2015-08-01

Multiple attributes usually have to be assessed when choosing a mate. Efficient choice of the best mate is complicated if the available cues are not positively correlated, as is often the case during acoustic communication. Because of varying distances of signalers, a female may be confronted with signals of diverse quality at different intensities. Here, we examined how available cues are weighted for a decision by female crickets. Two songs with different temporal patterns and/or sound intensities were presented in a choice paradigm and compared with female responses from a no-choice test. When both patterns were presented at equal intensity, preference functions became wider in choice situations compared with a no-choice paradigm. When the stimuli in two-choice tests were presented at different intensities, this effect was counteracted as preference functions became narrower compared with choice tests using stimuli of equal intensity. The weighting of intensity differences depended on pattern quality and was therefore non-linear. A simple computational model based on pattern and intensity cues reliably predicted female decisions. A comparison of processing schemes suggested that the computations for pattern recognition and directionality are performed in a network with parallel topology. However, the computational flow of information corresponded to serial processing. © 2015. Published by The Company of Biologists Ltd.

Rate and onset cues can improve cochlear implant synthetic vowel recognition in noise

PubMed Central

Mc Laughlin, Myles; Reilly, Richard B.; Zeng, Fan-Gang

2013-01-01

Understanding speech-in-noise is difficult for most cochlear implant (CI) users. Speech-in-noise segregation cues are well understood for acoustic hearing but not for electric hearing. This study investigated the effects of stimulation rate and onset delay on synthetic vowel-in-noise recognition in CI subjects. In experiment I, synthetic vowels were presented at 50, 145, or 795 pulse/s and noise at the same three rates, yielding nine combinations. Recognition improved significantly if the noise had a lower rate than the vowel, suggesting that listeners can use temporal gaps in the noise to detect a synthetic vowel. This hypothesis is supported by accurate prediction of synthetic vowel recognition using a temporal integration window model. Using lower rates a similar trend was observed in normal hearing subjects. Experiment II found that for CI subjects, a vowel onset delay improved performance if the noise had a lower or higher rate than the synthetic vowel. These results show that differing rates or onset times can improve synthetic vowel-in-noise recognition, indicating a need to develop speech processing strategies that encode or emphasize these cues. PMID:23464025

Neural Correlates of Music Recognition in Down Syndrome

ERIC Educational Resources Information Center

Virji-Babul, N.; Moiseev, A.; Sun, W.; Feng, T.; Moiseeva, N.; Watt, K. J.; Huotilainen, M.

2013-01-01

The brain mechanisms that subserve music recognition remain unclear despite increasing interest in this process. Here we report the results of a magnetoencephalography experiment to determine the temporal dynamics and spatial distribution of brain regions activated during listening to a familiar and unfamiliar instrumental melody in control adults…

Delayed Self-Recognition in Children with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Lind, Sophie E.; Bowler, Dermot M.

2009-01-01

This study aimed to investigate temporally extended self-awareness (awareness of one's place in and continued existence through time) in autism spectrum disorder (ASD), using the delayed self-recognition (DSR) paradigm (Povinelli et al., Child Development 67:1540-1554, 1996). Relative to age and verbal ability matched comparison children, children…

Repetition and lag effects in movement recognition.

PubMed

Hall, C R; Buckolz, E

1982-03-01

Whether repetition and lag improve the recognition of movement patterns was investigated. Recognition memory was tested for one repetition, two-repetitions massed, and two-repetitions distributed with movement patterns at lags of 3, 5, 7, and 13. Recognition performance was examined both immediately afterwards and following a 48 hour delay. Both repetition and lag effects failed to be demonstrated, providing some support for the claim that memory is unaffected by repetition at a constant level of processing (Craik & Lockhart, 1972). There was, as expected, a significant decrease in recognition memory following the retention interval, but this appeared unrelated to repetition or lag.

Dentate gyrus supports slope recognition memory, shades of grey-context pattern separation and recognition memory, and CA3 supports pattern completion for object memory.

PubMed

Kesner, Raymond P; Kirk, Ryan A; Yu, Zhenghui; Polansky, Caitlin; Musso, Nick D

2016-03-01

In order to examine the role of the dorsal dentate gyrus (dDG) in slope (vertical space) recognition and possible pattern separation, various slope (vertical space) degrees were used in a novel exploratory paradigm to measure novelty detection for changes in slope (vertical space) recognition memory and slope memory pattern separation in Experiment 1. The results of the experiment indicate that control rats displayed a slope recognition memory function with a pattern separation process for slope memory that is dependent upon the magnitude of change in slope between study and test phases. In contrast, the dDG lesioned rats displayed an impairment in slope recognition memory, though because there was no significant interaction between the two groups and slope memory, a reliable pattern separation impairment for slope could not be firmly established in the DG lesioned rats. In Experiment 2, in order to determine whether, the dDG plays a role in shades of grey spatial context recognition and possible pattern separation, shades of grey were used in a novel exploratory paradigm to measure novelty detection for changes in the shades of grey context environment. The results of the experiment indicate that control rats displayed a shades of grey-context pattern separation effect across levels of separation of context (shades of grey). In contrast, the DG lesioned rats displayed a significant interaction between the two groups and levels of shades of grey suggesting impairment in a pattern separation function for levels of shades of grey. In Experiment 3 in order to determine whether the dorsal CA3 (dCA3) plays a role in object pattern completion, a new task requiring less training and using a choice that was based on choosing the correct set of objects on a two-choice discrimination task was used. The results indicated that control rats displayed a pattern completion function based on the availability of one, two, three or four cues. In contrast, the dCA3 lesioned rats displayed a significant interaction between the two groups and the number of available objects suggesting impairment in a pattern completion function for object cues. Copyright © 2015 Elsevier Inc. All rights reserved.

Digital video steganalysis exploiting collusion sensitivity

NASA Astrophysics Data System (ADS)

Budhia, Udit; Kundur, Deepa

2004-09-01

In this paper we present an effective steganalyis technique for digital video sequences based on the collusion attack. Steganalysis is the process of detecting with a high probability and low complexity the presence of covert data in multimedia. Existing algorithms for steganalysis target detecting covert information in still images. When applied directly to video sequences these approaches are suboptimal. In this paper, we present a method that overcomes this limitation by using redundant information present in the temporal domain to detect covert messages in the form of Gaussian watermarks. Our gains are achieved by exploiting the collusion attack that has recently been studied in the field of digital video watermarking, and more sophisticated pattern recognition tools. Applications of our scheme include cybersecurity and cyberforensics.

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed Central

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-01-01

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. PMID:29172273

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-11-26

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. Creative Commons Attribution License

Solution NMR studies provide structural basis for endotoxin pattern recognition by the innate immune receptor CD14

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

Albright, Seth; Chen Bin; Holbrook, Kristen

CD14 functions as a key pattern recognition receptor for a diverse array of Gram-negative and Gram-positive cell-wall components in the host innate immune response by binding to pathogen-associated molecular patterns (PAMPs) at partially overlapping binding site(s). To determine the potential contribution of CD14 residues in this pattern recognition, we have examined using solution NMR spectroscopy, the binding of three different endotoxin ligands, lipopolysaccharide, lipoteichoic acid, and a PGN-derived compound, muramyl dipeptide to a {sup 15}N isotopically labeled 152-residue N-terminal fragment of sCD14 expressed in Pichia pastoris. Mapping of NMR spectral changes upon addition of ligands revealed that the pattern ofmore » residues affected by binding of each ligand is partially similar and partially different. This first direct structural observation of the ability of specific residue combinations of CD14 to differentially affect endotoxin binding may help explain the broad specificity of CD14 in ligand recognition and provide a structural basis for pattern recognition. Another interesting finding from the observed spectral changes is that the mode of binding may be dynamically modulated and could provide a mechanism for binding endotoxins with structural diversity through a common binding site.« less

Contrasting visual working memory for verbal and non-verbal material with multivariate analysis of fMRI

PubMed Central

Habeck, Christian; Rakitin, Brian; Steffener, Jason; Stern, Yaakov

2012-01-01

We performed a delayed-item-recognition task to investigate the neural substrates of non-verbal visual working memory with event-related fMRI (‘Shape task’). 25 young subjects (mean age: 24.0 years; STD=3.8 years) were instructed to study a list of either 1,2 or 3 unnamable nonsense line drawings for 3 seconds (‘stimulus phase’ or STIM). Subsequently, the screen went blank for 7 seconds (‘retention phase’ or RET), and then displayed a probe stimulus for 3 seconds in which subject indicated with a differential button press whether the probe was contained in the studied shape-array or not (‘probe phase’ or PROBE). Ordinal Trend Canonical Variates Analysis (Habeck et al., 2005a) was performed to identify spatial covariance patterns that showed a monotonic increase in expression with memory load during all task phases. Reliable load-related patterns were identified in the stimulus and retention phase (p<0.01), while no significant pattern could be discerned during the probe phase. Spatial covariance patterns that were obtained from an earlier version of this task (Habeck et al., 2005b) using 1, 3, or 6 letters (‘Letter task’) were also prospectively applied to their corresponding task phases in the current non-verbal task version. Interestingly, subject expression of covariance patterns from both verbal and non-verbal retention phases correlated positively in the non-verbal task for all memory loads (p<0.0001). Both patterns also involved similar frontoparietal brain regions that were increasing in activity with memory load, and mediofrontal and temporal regions that were decreasing. Mean subject expression of both patterns across memory load during retention also correlated positively with recognition accuracy (dL) in the Shape task (p<0.005). These findings point to similarities in the neural substrates of verbal and non-verbal rehearsal processes. Encoding processes, on the other hand, are critically dependent on the to-be-remembered material, and seem to necessitate material-specific neural substrates. PMID:22652306

The influence of lexical statistics on temporal lobe cortical dynamics during spoken word listening

PubMed Central

Cibelli, Emily S.; Leonard, Matthew K.; Johnson, Keith; Chang, Edward F.

2015-01-01

Neural representations of words are thought to have a complex spatio-temporal cortical basis. It has been suggested that spoken word recognition is not a process of feed-forward computations from phonetic to lexical forms, but rather involves the online integration of bottom-up input with stored lexical knowledge. Using direct neural recordings from the temporal lobe, we examined cortical responses to words and pseudowords. We found that neural populations were not only sensitive to lexical status (real vs. pseudo), but also to cohort size (number of words matching the phonetic input at each time point) and cohort frequency (lexical frequency of those words). These lexical variables modulated neural activity from the posterior to anterior temporal lobe, and also dynamically as the stimuli unfolded on a millisecond time scale. Our findings indicate that word recognition is not purely modular, but relies on rapid and online integration of multiple sources of lexical knowledge. PMID:26072003

Social cognition dysfunctions in patients with epilepsy: Evidence from patients with temporal lobe and idiopathic generalized epilepsies.

PubMed

Realmuto, Sabrina; Zummo, Leila; Cerami, Chiara; Agrò, Luigi; Dodich, Alessandra; Canessa, Nicola; Zizzo, Andrea; Fierro, Brigida; Daniele, Ornella

2015-06-01

Despite an extensive literature on cognitive impairments in focal and generalized epilepsy, only a few number of studies specifically explored social cognition disorders in epilepsy syndromes. The aim of our study was to investigate social cognition abilities in patients with temporal lobe epilepsy (TLE) and in patients with idiopathic generalized epilepsy (IGE). Thirty-nine patients (21 patients with TLE and 18 patients with IGE) and 21 matched healthy controls (HCs) were recruited. All subjects underwent a basic neuropsychological battery plus two experimental tasks evaluating emotion recognition from facial expression (Ekman-60-Faces test, Ek-60F) and mental state attribution (Story-based Empathy Task, SET). In particular, the latter is a newly developed task that assesses the ability to infer others' intentions (i.e., intention attribution - IA) and emotions (i.e., emotion attribution - EA) compared with a control condition of physical causality (i.e., causal inferences - CI). Compared with HCs, patients with TLE showed significantly lower performances on both social cognition tasks. In particular, all SET subconditions as well as the recognition of negative emotions were significantly impaired in patients with TLE vs. HCs. On the contrary, patients with IGE showed impairments on anger recognition only without any deficit at the SET task. Emotion recognition deficits occur in patients with epilepsy, possibly because of a global disruption of a pathway involving frontal, temporal, and limbic regions. Impairments of mental state attribution specifically characterize the neuropsychological profile of patients with TLE in the context of the in-depth temporal dysfunction typical of such patients. Impairments of socioemotional processing have to be considered as part of the neuropsychological assessment in both TLE and IGE in view of a correct management and for future therapeutic interventions. Copyright © 2015 Elsevier Inc. All rights reserved.

The impact of left and right intracranial tumors on picture and word recognition memory.

PubMed

Goldstein, Bram; Armstrong, Carol L; Modestino, Edward; Ledakis, George; John, Cameron; Hunter, Jill V

2004-02-01

This study investigated the effects of left and right intracranial tumors on picture and word recognition memory. We hypothesized that left hemispheric (LH) patients would exhibit greater word recognition memory impairment than right hemispheric (RH) patients, with no significant hemispheric group picture recognition memory differences. The LH patient group obtained a significantly slower mean picture recognition reaction time than the RH group. The LH group had a higher proportion of tumors extending into the temporal lobes, possibly accounting for their greater pictorial processing impairments. Dual coding and enhanced visual imagery may have contributed to the patient groups' similar performance on the remainder of the measures.

Forecasting of hourly load by pattern recognition in a small area power system

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

Dehdashti-Shahrokh, A.

1982-01-01

An intuitive, logical, simple and efficient method of forecasting hourly load in a small area power system is presented. A pattern recognition approach is used in developing the forecasting model. Pattern recognition techniques are powerful tools in the field of artificial intelligence (cybernetics) and simulate the way the human brain operates to make decisions. Pattern recognition is generally used in analysis of processes where the total physical nature behind the process variation is unkown but specific kinds of measurements explain their behavior. In this research basic multivariate analyses, in conjunction with pattern recognition techniques, are used to develop a linearmore » deterministic model to forecast hourly load. This method assumes that load patterns in the same geographical area are direct results of climatological changes (weather sensitive load), and have occurred in the past as a result of similar climatic conditions. The algorithm described in here searches for the best possible pattern from a seasonal library of load and weather data in forecasting hourly load. To accommodate the unpredictability of weather and the resulting load, the basic twenty-four load pattern was divided into eight three-hour intervals. This division was made to make the model adaptive to sudden climatic changes. The proposed method offers flexible lead times of one to twenty-four hours. The results of actual data testing had indicated that this proposed method is computationally efficient, highly adaptive, with acceptable data storage size and accuracy that is comparable to many other existing methods.« less

Optical character recognition based on nonredundant correlation measurements.

PubMed

Braunecker, B; Hauck, R; Lohmann, A W

1979-08-15

The essence of character recognition is a comparison between the unknown character and a set of reference patterns. Usually, these reference patterns are all possible characters themselves, the whole alphabet in the case of letter characters. Obviously, N analog measurements are highly redundant, since only K = log(2)N binary decisions are enough to identify one out of N characters. Therefore, we devised K reference patterns accordingly. These patterns, called principal components, are found by digital image processing, but used in an optical analog computer. We will explain the concept of principal components, and we will describe experiments with several optical character recognition systems, based on this concept.

Self-organizing neural network models for visual pattern recognition.

PubMed

Fukushima, K

1987-01-01

Two neural network models for visual pattern recognition are discussed. The first model, called a "neocognitron", is a hierarchical multilayered network which has only afferent synaptic connections. It can acquire the ability to recognize patterns by "learning-without-a-teacher": the repeated presentation of a set of training patterns is sufficient, and no information about the categories of the patterns is necessary. The cells of the highest stage eventually become "gnostic cells", whose response shows the final result of the pattern-recognition of the network. Pattern recognition is performed on the basis of similarity in shape between patterns, and is not affected by deformation, nor by changes in size, nor by shifts in the position of the stimulus pattern. The second model has not only afferent but also efferent synaptic connections, and is endowed with the function of selective attention. The afferent and the efferent signals interact with each other in the hierarchical network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent signals, and at the same time, the afferent signals gate efferent signal flow. When a complex figure, consisting of two patterns or more, is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the models is paying selective attention is affected by noise or defects, the model can "recall" the complete pattern from which the noise has been eliminated and the defects corrected.

Effect of physical workload and modality of information presentation on pattern recognition and navigation task performance by high-fit young males.

PubMed

Zahabi, Maryam; Zhang, Wenjuan; Pankok, Carl; Lau, Mei Ying; Shirley, James; Kaber, David

2017-11-01

Many occupations require both physical exertion and cognitive task performance. Knowledge of any interaction between physical demands and modalities of cognitive task information presentation can provide a basis for optimising performance. This study examined the effect of physical exertion and modality of information presentation on pattern recognition and navigation-related information processing. Results indicated males of equivalent high fitness, between the ages of 18 and 34, rely more on visual cues vs auditory or haptic for pattern recognition when exertion level is high. We found that navigation response time was shorter under low and medium exertion levels as compared to high intensity. Navigation accuracy was lower under high level exertion compared to medium and low levels. In general, findings indicated that use of the haptic modality for cognitive task cueing decreased accuracy in pattern recognition responses. Practitioner Summary: An examination was conducted on the effect of physical exertion and information presentation modality in pattern recognition and navigation. In occupations requiring information presentation to workers, who are simultaneously performing a physical task, the visual modality appears most effective under high level exertion while haptic cueing degrades performance.

A strip chart recorder pattern recognition tool kit for Shuttle operations

NASA Technical Reports Server (NTRS)

Hammen, David G.; Moebes, Travis A.; Shelton, Robert O.; Savely, Robert T.

1993-01-01

During Space Shuttle operations, Mission Control personnel monitor numerous mission-critical systems such as electrical power; guidance, navigation, and control; and propulsion by means of paper strip chart recorders. For example, electrical power controllers monitor strip chart recorder pen traces to identify onboard electrical equipment activations and deactivations. Recent developments in pattern recognition technologies coupled with new capabilities that distribute real-time Shuttle telemetry data to engineering workstations make it possible to develop computer applications that perform some of the low-level monitoring now performed by controllers. The number of opportunities for such applications suggests a need to build a pattern recognition tool kit to reduce software development effort through software reuse. We are building pattern recognition applications while keeping such a tool kit in mind. We demonstrated the initial prototype application, which identifies electrical equipment activations, during three recent Shuttle flights. This prototype was developed to test the viability of the basic system architecture, to evaluate the performance of several pattern recognition techniques including those based on cross-correlation, neural networks, and statistical methods, to understand the interplay between an advanced automation application and human controllers to enhance utility, and to identify capabilities needed in a more general-purpose tool kit.

Neural Correlates of Verbal Episodic Memory and Lexical Retrieval in Logopenic Variant Primary Progressive Aphasia.

PubMed

Win, Khaing T; Pluta, John; Yushkevich, Paul; Irwin, David J; McMillan, Corey T; Rascovsky, Katya; Wolk, David; Grossman, Murray

2017-01-01

Objective: Logopenic variant primary progressive aphasia (lvPPA) is commonly associated with Alzheimer's disease (AD) pathology. But lvPPA patients display different cognitive and anatomical profile from the common clinical AD patients, whose verbal episodic memory is primarily affected. Reports of verbal episodic memory difficulty in lvPPA are inconsistent, and we hypothesized that their lexical retrieval impairment contributes to verbal episodic memory performance and is associated with left middle temporal gyrus atrophy. Methods: We evaluated patients with lvPPA ( n = 12) displaying prominent word-finding and repetition difficulties, and a demographically-matched cohort of clinical Alzheimer's disease (AD, n = 26), and healthy seniors ( n = 16). We assessed lexical retrieval with confrontation naming and verbal episodic memory with delayed free recall. Whole-brain regressions related naming and delayed free recall to gray matter atrophy. Medial temporal lobe (MTL) subfields were examined using high in-plane resolution imaging. Results: lvPPA patients had naming and delayed free recall impairments, but intact recognition memory. In lvPPA, delayed free recall was related to naming; both were associated with left middle temporal gyrus atrophy but not MTL atrophy. Despite cerebrospinal fluid evidence consistent with AD pathology, examination of MTL subfields revealed no atrophy in lvPPA. While AD patients displayed impaired delayed free recall, this deficit did not correlate with naming. Regression analyses related delayed free recall deficits in clinical AD patients to MTL subfield atrophy, and naming to left middle temporal gyrus atrophy. Conclusion: Unlike amnestic AD patients, MTL subfields were not affected in lvPPA patients. Verbal episodic memory deficit observed in lvPPA was unlikely to be due to a hippocampal-mediated mechanism but appeared to be due to poor lexical retrieval. Relative sparing of MTL volume and intact recognition memory are consistent with previous reports of hippocampal-sparing variant cases of AD pathology, where neurofibrillary tangles are disproportionately distributed in cortical areas with relative sparing of the hippocampus. This suggests that AD neuropathology in lvPPA may originate in neuronal networks outside of the MTL, which deviates from the typical Braak staging pattern of spreading pathology in clinical AD.

On the right side? A longitudinal study of left- versus right-lateralized semantic dementia.

PubMed

Kumfor, Fiona; Landin-Romero, Ramon; Devenney, Emma; Hutchings, Rosalind; Grasso, Roberto; Hodges, John R; Piguet, Olivier

2016-03-01

The typical presentation of semantic dementia is associated with marked, left predominant anterior temporal lobe atrophy and with changes in language. About 30% of individuals, however, present with predominant right anterior temporal lobe atrophy, usually accompanied by behavioural changes and prosopagnosia. Here, we aimed to establish whether these initially distinct clinical presentations evolve into a similar syndrome at the neural and behavioural level. Thirty-one patients who presented with predominant anterior temporal lobe atrophy were included. Based on imaging, patients were categorized as either predominant left (n = 22) or right (n = 9) semantic dementia. Thirty-three Alzheimer's disease patients and 25 healthy controls were included for comparison. Participants completed the Addenbrooke's Cognitive Examination, a Face and Emotion Processing Battery and the Cambridge Behavioural Inventory, and underwent magnetic resonance imaging annually. Longitudinal neuroimaging analyses showed greater right temporal pole atrophy in left semantic dementia than Alzheimer's disease, whereas right semantic dementia showed greater orbitofrontal and left temporal lobe atrophy than Alzheimer's disease. Importantly, direct comparisons between semantic dementia groups revealed that over time, left semantic dementia showed progressive thinning in the right temporal pole, whereas right semantic dementia showed thinning in the orbitofrontal cortex and anterior cingulate. Behaviourally, longitudinal analyses revealed that general cognition declined in all patients. In contrast, patients with left and right semantic dementia showed greater emotion recognition decline than Alzheimer's disease. In addition, left semantic dementia showed greater motivation loss than Alzheimer's disease. Correlational analyses revealed that emotion recognition was associated with right temporal pole, right medial orbitofrontal and right fusiform integrity, while changes in motivation were associated with right temporal pole cortical thinning. While left and right semantic dementia show distinct profiles at presentation, both phenotypes develop deficits in emotion recognition and behaviour. These findings highlight the pervasive socio-emotional deficits in frontotemporal dementia, even in patients with an initial language presentation. These changes reflect right anterior temporal and orbitofrontal cortex degeneration, underscoring the role of these regions in social cognition and behaviour. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Visual cluster analysis and pattern recognition methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

2001-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1984-01-01

Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

Proceedings of the NASA/MPRIA Workshop: Pattern Recognition

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

Outlines of talks presented at the workshop conducted at Texas A & M University on February 3 and 4, 1983 are presented. Emphasis was given to the application of Mathematics to image processing and pattern recognition.

Multi-dimension feature fusion for action recognition

NASA Astrophysics Data System (ADS)

Dong, Pei; Li, Jie; Dong, Junyu; Qi, Lin

2018-04-01

Typical human actions last several seconds and exhibit characteristic spatio-temporal structure. The challenge for action recognition is to capture and fuse the multi-dimension information in video data. In order to take into account these characteristics simultaneously, we present a novel method that fuses multiple dimensional features, such as chromatic images, depth and optical flow fields. We built our model based on the multi-stream deep convolutional networks with the help of temporal segment networks and extract discriminative spatial and temporal features by fusing ConvNets towers multi-dimension, in which different feature weights are assigned in order to take full advantage of this multi-dimension information. Our architecture is trained and evaluated on the currently largest and most challenging benchmark NTU RGB-D dataset. The experiments demonstrate that the performance of our method outperforms the state-of-the-art methods.

Temporal patterns of the use of non-prescribed drugs.

PubMed

Sinnett, E R; Morris, J B

1977-12-01

Licit and illicit non-prescribed drugs, regardless of their classification, are used in a common temporal pattern with the possible exceptions of caffeine and cocaine. The temporal patterns of drug use are highly correlated with the nationwide temporal pattern of TV watching, suggesting a pleasure-oriented, recreational use. The peak times for substance use and abuse may have implications for the delivery of professional or paraprofessional services.

Temporal motifs reveal homophily, gender-specific patterns, and group talk in call sequences.

PubMed

Kovanen, Lauri; Kaski, Kimmo; Kertész, János; Saramäki, Jari

2013-11-05

Recent studies on electronic communication records have shown that human communication has complex temporal structure. We study how communication patterns that involve multiple individuals are affected by attributes such as sex and age. To this end, we represent the communication records as a colored temporal network where node color is used to represent individuals' attributes, and identify patterns known as temporal motifs. We then construct a null model for the occurrence of temporal motifs that takes into account the interaction frequencies and connectivity between nodes of different colors. This null model allows us to detect significant patterns in call sequences that cannot be observed in a static network that uses interaction frequencies as link weights. We find sex-related differences in communication patterns in a large dataset of mobile phone records and show the existence of temporal homophily, the tendency of similar individuals to participate in communication patterns beyond what would be expected on the basis of their average interaction frequencies. We also show that temporal patterns differ between dense and sparse neighborhoods in the network. Because also this result is independent of interaction frequencies, it can be seen as an extension of Granovetter's hypothesis to temporal networks.

Temporal motifs reveal homophily, gender-specific patterns, and group talk in call sequences

PubMed Central

Kovanen, Lauri; Kaski, Kimmo; Kertész, János; Saramäki, Jari

2013-01-01

Recent studies on electronic communication records have shown that human communication has complex temporal structure. We study how communication patterns that involve multiple individuals are affected by attributes such as sex and age. To this end, we represent the communication records as a colored temporal network where node color is used to represent individuals’ attributes, and identify patterns known as temporal motifs. We then construct a null model for the occurrence of temporal motifs that takes into account the interaction frequencies and connectivity between nodes of different colors. This null model allows us to detect significant patterns in call sequences that cannot be observed in a static network that uses interaction frequencies as link weights. We find sex-related differences in communication patterns in a large dataset of mobile phone records and show the existence of temporal homophily, the tendency of similar individuals to participate in communication patterns beyond what would be expected on the basis of their average interaction frequencies. We also show that temporal patterns differ between dense and sparse neighborhoods in the network. Because also this result is independent of interaction frequencies, it can be seen as an extension of Granovetter’s hypothesis to temporal networks. PMID:24145424

Using pattern recognition as a method for predicting extreme events in natural and socio-economic systems

NASA Astrophysics Data System (ADS)

Intriligator, M.

2011-12-01

Vladimir (Volodya) Keilis-Borok has pioneered the use of pattern recognition as a technique for analyzing and forecasting developments in natural as well as socio-economic systems. Keilis-Borok's work on predicting earthquakes and landslides using this technique as a leading geophysicist has been recognized around the world. Keilis-Borok has also been a world leader in the application of pattern recognition techniques to the analysis and prediction of socio-economic systems. He worked with Allan Lichtman of American University in using such techniques to predict presidential elections in the U.S. Keilis-Borok and I have worked together with others on the use of pattern recognition techniques to analyze and to predict socio-economic systems. We have used this technique to study the pattern of macroeconomic indicators that would predict the end of an economic recession in the U.S. We have also worked with officers in the Los Angeles Police Department to use this technique to predict surges of homicides in Los Angeles.

Authorship attribution based on Life-Like Network Automata.

PubMed

Machicao, Jeaneth; Corrêa, Edilson A; Miranda, Gisele H B; Amancio, Diego R; Bruno, Odemir M

2018-01-01

The authorship attribution is a problem of considerable practical and technical interest. Several methods have been designed to infer the authorship of disputed documents in multiple contexts. While traditional statistical methods based solely on word counts and related measurements have provided a simple, yet effective solution in particular cases; they are prone to manipulation. Recently, texts have been successfully modeled as networks, where words are represented by nodes linked according to textual similarity measurements. Such models are useful to identify informative topological patterns for the authorship recognition task. However, there is no consensus on which measurements should be used. Thus, we proposed a novel method to characterize text networks, by considering both topological and dynamical aspects of networks. Using concepts and methods from cellular automata theory, we devised a strategy to grasp informative spatio-temporal patterns from this model. Our experiments revealed an outperformance over structural analysis relying only on topological measurements, such as clustering coefficient, betweenness and shortest paths. The optimized results obtained here pave the way for a better characterization of textual networks.

Temporal masking of multidimensional tactual stimuli

NASA Astrophysics Data System (ADS)

Tan, Hong Z.; Reed, Charlotte M.; Delhorne, Lorraine A.; Durlach, Nathaniel I.; Wan, Natasha

2003-12-01

Experiments were performed to examine the temporal masking properties of multidimensional tactual stimulation patterns delivered to the left index finger. The stimuli consisted of fixed-frequency sinusoidal motions in the kinesthetic (2 or 4 Hz), midfrequency (30 Hz), and cutaneous (300 Hz) frequency ranges. Seven stimuli composed of one, two, or three spectral components were constructed at each of two signal durations (125 or 250 ms). Subjects identified target signals under three different masking paradigms: forward masking, backward masking, and sandwiched masking (in which the target is presented between two maskers). Target identification was studied as a function of interstimulus interval (ISI) in the range 0 to 640 ms. For both signal durations, percent-correct scores increased with ISI for each of the three masking paradigms. Scores with forward and backward masking were similar and significantly higher than scores obtained with sandwiched masking. Analyses of error trials revealed that subjects showed a tendency to respond, more often than chance, with the masker, the composite of the masker and target, or the combination of the target and a component of the masker. The current results are compared to those obtained in previous studies of tactual recognition masking with brief cutaneous spatial patterns. The results are also discussed in terms of estimates of information transfer (IT) and IT rate, are compared to previous studies with multidimensional tactual signals, and are related to research on the development of tactual aids for the deaf.

A Compact Prototype of an Optical Pattern Recognition System

NASA Technical Reports Server (NTRS)

Jin, Y.; Liu, H. K.; Marzwell, N. I.

1996-01-01

In the Technology 2006 Case Studies/Success Stories presentation, we will describe and demonstrate a prototype of a compact optical pattern recognition system as an example of a successful technology transfer and continuuing development of state-of-the-art know-how by the close collaboration among government, academia, and small business via the NASA SBIR program. The prototype consists of a complete set of optical pattern recognition hardware with multi-channel storage and retrieval capability that is compactly configured inside a portable 1'X 2'X 3' aluminum case.

Disambiguating past events: Accurate source memory for time and context depends on different retrieval processes.

PubMed

Persson, Bjorn M; Ainge, James A; O'Connor, Akira R

2016-07-01

Current animal models of episodic memory are usually based on demonstrating integrated memory for what happened, where it happened, and when an event took place. These models aim to capture the testable features of the definition of human episodic memory which stresses the temporal component of the memory as a unique piece of source information that allows us to disambiguate one memory from another. Recently though, it has been suggested that a more accurate model of human episodic memory would include contextual rather than temporal source information, as humans' memory for time is relatively poor. Here, two experiments were carried out investigating human memory for temporal and contextual source information, along with the underlying dual process retrieval processes, using an immersive virtual environment paired with a 'Remember-Know' memory task. Experiment 1 (n=28) showed that contextual information could only be retrieved accurately using recollection, while temporal information could be retrieved using either recollection or familiarity. Experiment 2 (n=24), which used a more difficult task, resulting in reduced item recognition rates and therefore less potential for contamination by ceiling effects, replicated the pattern of results from Experiment 1. Dual process theory predicts that it should only be possible to retrieve source context from an event using recollection, and our results are consistent with this prediction. That temporal information can be retrieved using familiarity alone suggests that it may be incorrect to view temporal context as analogous to other typically used source contexts. This latter finding supports the alternative proposal that time since presentation may simply be reflected in the strength of memory trace at retrieval - a measure ideally suited to trace strength interrogation using familiarity, as is typically conceptualised within the dual process framework. Copyright © 2016 Elsevier Inc. All rights reserved.

Signal recognition by green treefrogs (Hyla cinerea) and Cope's gray treefrogs (Hyla chrysoscelis) in naturally fluctuating noise.

PubMed

Vélez, Alejandro; Bee, Mark A

2013-05-01

This study tested three hypotheses about the ability of female frogs to exploit temporal fluctuations in the level of background noise to overcome the problem of recognizing male advertisement calls in noisy breeding choruses. Phonotaxis tests with green treefrogs (Hyla cinerea) and Cope's gray treefrogs (Hyla chrysoscelis) were used to measure thresholds for recognizing calls in the presence of noise maskers with (a) no level fluctuations, (b) random fluctuations, or level fluctuations characteristic of (c) conspecific choruses and (d) heterospecific choruses. The dip-listening hypothesis predicted lower signal recognition thresholds in the presence of fluctuating maskers compared with nonfluctuating maskers. Support for the dip-listening hypothesis was weak; only Cope's gray treefrogs experienced dip listening and only in the presence of randomly fluctuating maskers. The natural soundscapes advantage hypothesis predicted lower recognition thresholds when level fluctuations resembled those of natural soundscapes compared with artificial fluctuations. This hypothesis was rejected. In noise backgrounds with natural fluctuations, the species-specific advantage hypothesis predicted lower recognition thresholds when fluctuations resembled species-specific patterns of conspecific soundscapes. No evidence was found to support this hypothesis. These results corroborate previous findings showing that Cope's gray treefrogs, but not green treefrogs, experience dip listening under some noise conditions. Together, the results suggest level fluctuations in the soundscape of natural breeding choruses may present few dip-listening opportunities. The findings of this study provide little support for the hypothesis that receivers are adapted to exploit level fluctuations of natural soundscapes in recognizing communication signals.

Signal Recognition by Green Treefrogs (Hyla cinerea) and Cope’s Gray Treefrogs (Hyla chrysoscelis) in Naturally Fluctuating Noise

PubMed Central

Vélez, Alejandro; Bee, Mark A.

2013-01-01

This study tested three hypotheses about the ability of female frogs to exploit temporal fluctuations in the level of background noise to overcome the problem of recognizing male advertisement calls in noisy breeding choruses. Phonotaxis tests with green treefrogs (Hyla cinerea) and Cope’s gray treefrogs (Hyla chrysoscelis) were used to measure thresholds for recognizing calls in the presence of noise maskers with (i) no level fluctuations, (ii) random fluctuations, or level fluctuations characteristic of (iii) conspecific choruses and (iv) heterospecific choruses. The dip-listening hypothesis predicted lower signal recognition thresholds in the presence of fluctuating maskers compared with non-fluctuating maskers. Support for the dip listening hypothesis was weak; only Cope’s gray treefrogs experienced dip listening and only in the presence of randomly fluctuating maskers. The natural soundscapes advantage hypothesis predicted lower recognition thresholds when level fluctuations resembled those of natural soundscapes compared with artificial fluctuations. This hypothesis was rejected. In noise backgrounds with natural fluctuations, the species-specific advantage hypothesis predicted lower recognition thresholds when fluctuations resembled species-specific patterns of conspecific soundscapes. No evidence was found to support this hypothesis. These results corroborate previous findings showing that Cope’s gray treefrogs, but not green treefrogs, experience dip listening under some noise conditions. Together, the results suggest level fluctuations in the soundscape of natural breeding choruses may present few dip-listening opportunities. The findings of this study provide little support for the hypothesis that receivers are adapted to exploit level fluctuations of natural soundscapes in recognizing communication signals. PMID:23106802

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

1999-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Photonic correlator pattern recognition: Application to autonomous docking

NASA Technical Reports Server (NTRS)

Sjolander, Gary W.

1991-01-01

Optical correlators for real-time automatic pattern recognition applications have recently become feasible due to advances in high speed devices and filter formulation concepts. The devices are discussed in the context of their use in autonomous docking.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

Construction of sediment budgets for drainage basins

Treesearch

William E. Dietrich; Thomas Dunne; Neil F. Humphrey; Leslie M. Reid

1982-01-01

Abstract - A sediment budget for a drainage basin is a quantitative statement of the rates of production, transport, and discharge of detritus. To construct a sediment budget for a drainage basin, one must integrate the temporal and spatial variations of transport and storage processes. This requires: recognition and quantification of transport processes, recognition...

Semantic Memory Recognition Is Supported by Intrinsic Recollection-Like Processes: "The Butcher on the Bus" Revisited

ERIC Educational Resources Information Center

Waidergoren, Shani; Segalowicz, Judith; Gilboa, Asaf

2012-01-01

Dual-process models suggest that recognition memory is independently supported by recollection and familiarity. Current theories attribute recollection solely to hippocampally mediated episodic memory (EM), and familiarity to both episodic and semantic memory (SM) supported by medial temporal lobe cortex (MTLC) and prefrontal cortex. We tested…

Hippocampal contributions to recollection in retrograde and anterograde amnesia.

PubMed

Gilboa, Asaf; Winocur, Gordon; Rosenbaum, R Shayna; Poreh, Amir; Gao, Fuqiang; Black, Sandra E; Westmacott, Robyn; Moscovitch, Morris

2006-01-01

Lesions restricted to the hippocampal formation and/or extended hippocampal system (hippocampal formation, fornix, mammillary bodies, and anterior thalamic nuclei) can disrupt conscious recollection in anterograde amnesia, while leaving familiarity-based memory relatively intact. Familiarity may be supported by extra-hippocampal medial temporal lobe (MTL) structures. Within-task dissociations in recognition memory best exemplify this distinction in anterograde amnesia. The authors report for the first time comparable dissociations within recognition memory in retrograde amnesia. An amnesic patient (A.D.) with bilateral fornix and septal nuclei lesions failed to recognize details pertaining to personal past events only when recollection was required, during recognition of episodic details. His intact recognition of generic and semantic details pertaining to the same events was ascribed to intact familiarity processes. Recollective processes in the controls were reflected by asymmetrical Receiver's Operating Characteristic curves, whereas the patient's Receiver's Operating Characteristic was symmetrical, suggesting that his inferior recognition performance on episodic details was reliant on familiarity processes. Anterograde and retrograde memories were equally affected, with no temporal gradient for retrograde memories. By comparison, another amnesic person (K.C.) with extensive MTL damage (involving extra-hippocampal MTL structures in addition to hippocampal and fornix lesions) had very poor recognition and no recollection of either episodic or generic/semantic details. These data suggest that the extended hippocampal system is required to support recollection for both anterograde and retrograde memories, regardless of their age.

Brain correlates of musical and facial emotion recognition: evidence from the dementias.

PubMed

Hsieh, S; Hornberger, M; Piguet, O; Hodges, J R

2012-07-01

The recognition of facial expressions of emotion is impaired in semantic dementia (SD) and is associated with right-sided brain atrophy in areas known to be involved in emotion processing, notably the amygdala. Whether patients with SD also experience difficulty recognizing emotions conveyed by other media, such as music, is unclear. Prior studies have used excerpts of known music from classical or film repertoire but not unfamiliar melodies designed to convey distinct emotions. Patients with SD (n = 11), Alzheimer's disease (n = 12) and healthy control participants (n = 20) underwent tests of emotion recognition in two modalities: unfamiliar musical tunes and unknown faces as well as volumetric MRI. Patients with SD were most impaired with the recognition of facial and musical emotions, particularly for negative emotions. Voxel-based morphometry showed that the labelling of emotions, regardless of modality, correlated with the degree of atrophy in the right temporal pole, amygdala and insula. The recognition of musical (but not facial) emotions was also associated with atrophy of the left anterior and inferior temporal lobe, which overlapped with regions correlating with standardized measures of verbal semantic memory. These findings highlight the common neural substrates supporting the processing of emotions by facial and musical stimuli but also indicate that the recognition of emotions from music draws upon brain regions that are associated with semantics in language. Copyright © 2012 Elsevier Ltd. All rights reserved.

Unconstrained handwritten numeral recognition based on radial basis competitive and cooperative networks with spatio-temporal feature representation.

PubMed

Lee, S; Pan, J J

1996-01-01

This paper presents a new approach to representation and recognition of handwritten numerals. The approach first transforms a two-dimensional (2-D) spatial representation of a numeral into a three-dimensional (3-D) spatio-temporal representation by identifying the tracing sequence based on a set of heuristic rules acting as transformation operators. A multiresolution critical-point segmentation method is then proposed to extract local feature points, at varying degrees of scale and coarseness. A new neural network architecture, referred to as radial-basis competitive and cooperative network (RCCN), is presented especially for handwritten numeral recognition. RCCN is a globally competitive and locally cooperative network with the capability of self-organizing hidden units to progressively achieve desired network performance, and functions as a universal approximator of arbitrary input-output mappings. Three types of RCCNs are explored: input-space RCCN (IRCCN), output-space RCCN (ORCCN), and bidirectional RCCN (BRCCN). Experiments against handwritten zip code numerals acquired by the U.S. Postal Service indicated that the proposed method is robust in terms of variations, deformations, transformations, and corruption, achieving about 97% recognition rate.

Voice gender discrimination provides a measure of more than pitch-related perception in cochlear implant users.

PubMed

Li, Tianhao; Fu, Qian-Jie

2011-08-01

(1) To investigate whether voice gender discrimination (VGD) could be a useful indicator of the spectral and temporal processing abilities of individual cochlear implant (CI) users; (2) To examine the relationship between VGD and speech recognition with CI when comparable acoustic cues are used for both perception processes. VGD was measured using two talker sets with different inter-gender fundamental frequencies (F(0)), as well as different acoustic CI simulations. Vowel and consonant recognition in quiet and noise were also measured and compared with VGD performance. Eleven postlingually deaf CI users. The results showed that (1) mean VGD performance differed for different stimulus sets, (2) VGD and speech recognition performance varied among individual CI users, and (3) individual VGD performance was significantly correlated with speech recognition performance under certain conditions. VGD measured with selected stimulus sets might be useful for assessing not only pitch-related perception, but also spectral and temporal processing by individual CI users. In addition to improvements in spectral resolution and modulation detection, the improvement in higher modulation frequency discrimination might be particularly important for CI users in noisy environments.

Finger Vein Recognition Based on a Personalized Best Bit Map

PubMed Central

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition. PMID:22438735

Finger vein recognition based on a personalized best bit map.

PubMed

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition.

Large-memory real-time multichannel multiplexed pattern recognition

NASA Technical Reports Server (NTRS)

Gregory, D. A.; Liu, H. K.

1984-01-01

The principle and experimental design of a real-time multichannel multiplexed optical pattern recognition system via use of a 25-focus dichromated gelatin holographic lens (hololens) are described. Each of the 25 foci of the hololens may have a storage and matched filtering capability approaching that of a single-lens correlator. If the space-bandwidth product of an input image is limited, as is true in most practical cases, the 25-focus hololens system has 25 times the capability of a single lens. Experimental results have shown that the interfilter noise is not serious. The system has already demonstrated the storage and recognition of over 70 matched filters - which is a larger capacity than any optical pattern recognition system reported to date.

Episodic retrieval involves early and sustained effects of reactivating information from encoding.

PubMed

Johnson, Jeffrey D; Price, Mason H; Leiker, Emily K

2015-02-01

Several fMRI studies have shown a correspondence between the brain regions activated during encoding and retrieval, consistent with the view that memory retrieval involves hippocampally-mediated reinstatement of cortical activity. With the limited temporal resolution of fMRI, the precise timing of such reactivation is unclear, calling into question the functional significance of these effects. Whereas reactivation influencing retrieval should emerge with neural correlates of retrieval success, that signifying post-retrieval monitoring would trail retrieval. The present study employed EEG to provide a temporal landmark of retrieval success from which we could investigate the sub-trial time course of reactivation. Pattern-classification analyses revealed that early-onsetting reactivation differentiated the outcome of recognition-memory judgments and was associated with individual differences in behavioral accuracy, while reactivation was also evident in a sustained form later in the trial. The EEG findings suggest that, whereas prior fMRI findings could be interpreted as reflecting the contribution of reinstatement to retrieval success, they could also indicate the maintenance of episodic information in service of post-retrieval evaluation. Copyright © 2014 Elsevier Inc. All rights reserved.

Face Patch Resting State Networks Link Face Processing to Social Cognition

PubMed Central

Schwiedrzik, Caspar M.; Zarco, Wilbert; Everling, Stefan; Freiwald, Winrich A.

2015-01-01

Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills. PMID:26348613

Hybrid Spintronic-CMOS Spiking Neural Network with On-Chip Learning: Devices, Circuits, and Systems

NASA Astrophysics Data System (ADS)

Sengupta, Abhronil; Banerjee, Aparajita; Roy, Kaushik

2016-12-01

Over the past decade, spiking neural networks (SNNs) have emerged as one of the popular architectures to emulate the brain. In SNNs, information is temporally encoded and communication between neurons is accomplished by means of spikes. In such networks, spike-timing-dependent plasticity mechanisms require the online programing of synapses based on the temporal information of spikes transmitted by spiking neurons. In this work, we propose a spintronic synapse with decoupled spike-transmission and programing-current paths. The spintronic synapse consists of a ferromagnet-heavy-metal heterostructure where the programing current through the heavy metal generates spin-orbit torque to modulate the device conductance. Low programing energy and fast programing times demonstrate the efficacy of the proposed device as a nanoelectronic synapse. We perform a simulation study based on an experimentally benchmarked device-simulation framework to demonstrate the interfacing of such spintronic synapses with CMOS neurons and learning circuits operating in the transistor subthreshold region to form a network of spiking neurons that can be utilized for pattern-recognition problems.

The memory is in the details: relations between memory for the specific features of events and long-term recall during infancy.

PubMed

Bauer, Patricia J; Lukowski, Angela F

2010-09-01

The second year of life is marked by pronounced changes in the length of time over which events are remembered. We tested whether the age-related differences are related to differences in memory for the specific features of events. In our study, 16- and 20-month-olds were tested for immediate and long-term recall of individual actions and temporal order of actions of three-step sequences in an elicited imitation paradigm as well as for forced-choice recognition of the specific feature of the props used to produce the sequences. Memory for the props was related to long-term recall of the events only for the 20-month-olds. It accounted for unique variance above and beyond the variance explained by immediate recall of the individual actions and the temporal order of actions of the sequences. The different pattern of relations in the older and younger infants seemingly reflects a developmental difference in the determinants of long-term recall over the second year of life. Copyright 2010 Elsevier Inc. All rights reserved.

Auditory orientation in crickets: Pattern recognition controls reactive steering

NASA Astrophysics Data System (ADS)

Poulet, James F. A.; Hedwig, Berthold

2005-10-01

Many groups of insects are specialists in exploiting sensory cues to locate food resources or conspecifics. To achieve orientation, bees and ants analyze the polarization pattern of the sky, male moths orient along the females' odor plume, and cicadas, grasshoppers, and crickets use acoustic signals to locate singing conspecifics. In comparison with olfactory and visual orientation, where learning is involved, auditory processing underlying orientation in insects appears to be more hardwired and genetically determined. In each of these examples, however, orientation requires a recognition process identifying the crucial sensory pattern to interact with a localization process directing the animal's locomotor activity. Here, we characterize this interaction. Using a sensitive trackball system, we show that, during cricket auditory behavior, the recognition process that is tuned toward the species-specific song pattern controls the amplitude of auditory evoked steering responses. Females perform small reactive steering movements toward any sound patterns. Hearing the male's calling song increases the gain of auditory steering within 2-5 s, and the animals even steer toward nonattractive sound patterns inserted into the speciesspecific pattern. This gain control mechanism in the auditory-to-motor pathway allows crickets to pursue species-specific sound patterns temporarily corrupted by environmental factors and may reflect the organization of recognition and localization networks in insects. localization | phonotaxis

Precipitation Nowcast using Deep Recurrent Neural Network

NASA Astrophysics Data System (ADS)

Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

2016-12-01

An accurate precipitation nowcast (0-6 hours) with a fine temporal and spatial resolution has always been an important prerequisite for flood warning, streamflow prediction and risk management. Most of the popular approaches used for forecasting precipitation can be categorized into two groups. One type of precipitation forecast relies on numerical modeling of the physical dynamics of atmosphere and another is based on empirical and statistical regression models derived by local hydrologists or meteorologists. Given the recent advances in artificial intelligence, in this study a powerful Deep Recurrent Neural Network, termed as Long Short-Term Memory (LSTM) model, is creatively used to extract the patterns and forecast the spatial and temporal variability of Cloud Top Brightness Temperature (CTBT) observed from GOES satellite. Then, a 0-6 hours precipitation nowcast is produced using a Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN) algorithm, in which the CTBT nowcast is used as the PERSIANN algorithm's raw inputs. Two case studies over the continental U.S. have been conducted that demonstrate the improvement of proposed approach as compared to a classical Feed Forward Neural Network and a couple simple regression models. The advantages and disadvantages of the proposed method are summarized with regard to its capability of pattern recognition through time, handling of vanishing gradient during model learning, and working with sparse data. The studies show that the LSTM model performs better than other methods, and it is able to learn the temporal evolution of the precipitation events through over 1000 time lags. The uniqueness of PERSIANN's algorithm enables an alternative precipitation nowcast approach as demonstrated in this study, in which the CTBT prediction is produced and used as the inputs for generating precipitation nowcast.

Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

PubMed

Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

2016-01-01

To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

Instruction-specific brain activations during episodic encoding. a generalized level of processing effect.

PubMed

Petersson, Karl Magnus; Sandblom, Johan; Elfgren, Christina; Ingvar, Martin

2003-11-01

In a within-subject design we investigated the levels-of-processing (LOP) effect using visual material in a behavioral and a corresponding PET study. In the behavioral study we characterize a generalized LOP effect, using pleasantness and graphical quality judgments in the encoding situation, with two types of visual material, figurative and nonfigurative line drawings. In the PET study we investigate the related pattern of brain activations along these two dimensions. The behavioral results indicate that instruction and material contribute independently to the level of recognition performance. Therefore the LOP effect appears to stem both from the relative relevance of the stimuli (encoding opportunity) and an altered processing of stimuli brought about by the explicit instruction (encoding mode). In the PET study, encoding of visual material under the pleasantness (deep) instruction yielded left lateralized frontoparietal and anterior temporal activations while surface-based perceptually oriented processing (shallow instruction) yielded right lateralized frontoparietal, posterior temporal, and occipitotemporal activations. The result that deep encoding was related to the left prefrontal cortex while shallow encoding was related to the right prefrontal cortex, holding the material constant, is not consistent with the HERA model. In addition, we suggest that the anterior medial superior frontal region is related to aspects of self-referential semantic processing and that the inferior parts of the anterior cingulate as well as the medial orbitofrontal cortex is related to affective processing, in this case pleasantness evaluation of the stimuli regardless of explicit semantic content. Finally, the left medial temporal lobe appears more actively engaged by elaborate meaning-based processing and the complex response pattern observed in different subregions of the MTL lends support to the suggestion that this region is functionally segregated.

Content-Specific Source Encoding in the Human Medial Temporal Lobe

ERIC Educational Resources Information Center

Awipi, T.; Davachi, L.

2008-01-01

Although the medial temporal lobe (MTL) is known to be essential for episodic encoding, the contributions of individual MTL subregions remain unclear. Data from recognition memory studies have provided evidence that the hippocampus supports relational encoding important for later episodic recollection, whereas the perirhinal cortex has been linked…

Behavioural and magnetoencephalographic evidence for the interaction between semantic and episodic memory in healthy elderly subjects.

PubMed

La Corte, Valentina; Dalla Barba, Gianfranco; Lemaréchal, Jean-Didier; Garnero, Line; George, Nathalie

2012-10-01

The relationship between episodic and semantic memory systems has long been debated. Some authors argue that episodic memory is contingent on semantic memory (Tulving 1984), while others postulate that both systems are independent since they can be selectively damaged (Squire 1987). The interaction between these memory systems is particularly important in the elderly, since the dissociation of episodic and semantic memory defects characterize different aging-related pathologies. Here, we investigated the interaction between semantic knowledge and episodic memory processes associated with faces in elderly subjects using an experimental paradigm where the semantic encoding of famous and unknown faces was compared to their episodic recognition. Results showed that the level of semantic awareness of items affected the recognition of those items in the episodic memory task. Event-related magnetic fields confirmed this interaction between episodic and semantic memory: ERFs related to the old/new effect during the episodic task were markedly different for famous and unknown faces. The old/new effect for famous faces involved sustained activities maximal over right temporal sensors, showing a spatio-temporal pattern partly similar to that found for famous versus unknown faces during the semantic task. By contrast, an old/new effect for unknown faces was observed on left parieto-occipital sensors. These findings suggest that the episodic memory for famous faces activated the retrieval of stored semantic information, whereas it was based on items' perceptual features for unknown faces. Overall, our results show that semantic information interfered markedly with episodic memory processes and suggested that the neural substrates of these two memory systems overlap.

Brain substrates of social decision-making in dual diagnosis: cocaine dependence and personality disorders.

PubMed

Verdejo-Garcia, Antonio; Verdejo-Román, Juan; Albein-Urios, Natalia; Martínez-González, José M; Soriano-Mas, Carles

2017-03-01

Cocaine dependence frequently co-occurs with personality disorders, leading to increased interpersonal problems and greater burden of disease. Personality disorders are characterised by patterns of thinking and feeling that divert from social expectations. However, the comorbidity between cocaine dependence and personality disorders has not been substantiated by measures of brain activation during social decision-making. We applied functional magnetic resonance imaging to compare brain activations evoked by a social decision-making task-the Ultimatum Game-in 24 cocaine dependents with personality disorders (CDPD), 19 cocaine dependents without comorbidities and 19 healthy controls. In the Ultimatum Game participants had to accept or reject bids made by another player to split monetary stakes. Offers varied in fairness (in fair offers the proposer shares ~50 percent of the money; in unfair offers the proposer shares <30 percent of the money), and participants were told that if they accept both players get the money, and if they reject both players lose it. We contrasted brain activations during unfair versus fair offers and accept versus reject choices. During evaluation of unfair offers CDPD displayed lower activation in the insula and the anterior cingulate cortex and higher activation in the lateral orbitofrontal cortex and superior frontal and temporal gyri. Frontal activations negatively correlated with emotion recognition. During rejection of offers CDPD displayed lower activation in the anterior cingulate cortex, striatum and midbrain. Dual diagnosis is linked to hypo-activation of the insula and anterior cingulate cortex and hyper-activation of frontal-temporal regions during social decision-making, which associates with poorer emotion recognition. © 2015 Society for the Study of Addiction.

Brain activation for lexical decision and reading aloud: two sides of the same coin?

PubMed

Carreiras, Manuel; Mechelli, Andrea; Estévez, Adelina; Price, Cathy J

2007-03-01

This functional magnetic resonance imaging study compared the neuronal implementation of word and pseudoword processing during two commonly used word recognition tasks: lexical decision and reading aloud. In the lexical decision task, participants made a finger-press response to indicate whether a visually presented letter string is a word or a pseudoword (e.g., "paple"). In the reading-aloud task, participants read aloud visually presented words and pseudowords. The same sets of words and pseudowords were used for both tasks. This enabled us to look for the effects of task (lexical decision vs. reading aloud), lexicality (words vs. nonwords), and the interaction of lexicality with task. We found very similar patterns of activation for lexical decision and reading aloud in areas associated with word recognition and lexical retrieval (e.g., left fusiform gyrus, posterior temporal cortex, pars opercularis, and bilateral insulae), but task differences were observed bilaterally in sensorimotor areas. Lexical decision increased activation in areas associated with decision making and finger tapping (bilateral postcentral gyri, supplementary motor area, and right cerebellum), whereas reading aloud increased activation in areas associated with articulation and hearing the sound of the spoken response (bilateral precentral gyri, superior temporal gyri, and posterior cerebellum). The effect of lexicality (pseudoword vs. words) was also remarkably consistent across tasks. Nevertheless, increased activation for pseudowords relative to words was greater in the left precentral cortex for reading than lexical decision, and greater in the right inferior frontal cortex for lexical decision than reading. We attribute these effects to differences in the demands on speech production and decision-making processes, respectively.

Receptor-like cytoplasmic kinases are pivotal components in pattern recognition receptor-mediated signaling in plant immunity.

PubMed

Yamaguchi, Koji; Yamada, Kenta; Kawasaki, Tsutomu

2013-10-01

Innate immunity is generally initiated with recognition of conserved pathogen-associated molecular patterns (PAMPs). PAMPs are perceived by pattern recognition receptors (PRRs), leading to activation of a series of immune responses, including the expression of defense genes, ROS production and activation of MAP kinase. Recent progress has indicated that receptor-like cytoplasmic kinases (RLCKs) are directly activated by ligand-activated PRRs and initiate pattern-triggered immunity (PTI) in both Arabidopsis and rice. To suppress PTI, pathogens inhibit the RLCKs by many types of effectors, including AvrAC, AvrPphB and Xoo1488. In this review, we summarize recent advances in RLCK-mediated PTI in plants.

Proceedings of the NASA Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

The application of mathematical and statistical analyses techniques to imagery obtained by remote sensors is described by Principal Investigators. Scene-to-map registration, geometric rectification, and image matching are among the pattern recognition aspects discussed.

Students' Dichotomous Experiences of the Illuminating and Illusionary Nature of Pattern Recognition in Mathematics

ERIC Educational Resources Information Center

Mhlolo, Michael Kainose

2016-01-01

The concept of pattern recognition lies at the heart of numerous deliberations concerned with new mathematics curricula, because it is strongly linked to improved generalised thinking. However none of these discussions has made the deceptive nature of patterns an object of exploration and understanding. Yet there is evidence showing that pattern…

Better Object Recognition and Naming Outcome With MRI-Guided Stereotactic Laser Amygdalohippocampotomy for Temporal Lobe Epilepsy

PubMed Central

Drane, Daniel L.; Loring, David W.; Voets, Natalie L.; Price, Michele; Ojemann, Jeffrey G.; Willie, Jon T.; Saindane, Amit M.; Phatak, Vaishali; Ivanisevic, Mirjana; Millis, Scott; Helmers, Sandra L.; Miller, John W.; Meador, Kimford J.; Gross, Robert E.

2015-01-01

SUMMARY OBJECTIVES Temporal lobe epilepsy (TLE) patients experience significant deficits in category-related object recognition and naming following standard surgical approaches. These deficits may result from a decoupling of core processing modules (e.g., language, visual processing, semantic memory), due to “collateral damage” to temporal regions outside the hippocampus following open surgical approaches. We predicted stereotactic laser amygdalohippocampotomy (SLAH) would minimize such deficits because it preserves white matter pathways and neocortical regions critical for these cognitive processes. METHODS Tests of naming and recognition of common nouns (Boston Naming Test) and famous persons were compared with nonparametric analyses using exact tests between a group of nineteen patients with medically-intractable mesial TLE undergoing SLAH (10 dominant, 9 nondominant), and a comparable series of TLE patients undergoing standard surgical approaches (n=39) using a prospective, non-randomized, non-blinded, parallel group design. RESULTS Performance declines were significantly greater for the dominant TLE patients undergoing open resection versus SLAH for naming famous faces and common nouns (F=24.3, p<.0001, η2=.57, & F=11.2, p<.001, η2=.39, respectively), and for the nondominant TLE patients undergoing open resection versus SLAH for recognizing famous faces (F=3.9, p<.02, η2=.19). When examined on an individual subject basis, no SLAH patients experienced any performance declines on these measures. In contrast, 32 of the 39 undergoing standard surgical approaches declined on one or more measures for both object types (p<.001, Fisher’s exact test). Twenty-one of 22 left (dominant) TLE patients declined on one or both naming tasks after open resection, while 11 of 17 right (non-dominant) TLE patients declined on face recognition. SIGNIFICANCE Preliminary results suggest 1) naming and recognition functions can be spared in TLE patients undergoing SLAH, and 2) the hippocampus does not appear to be an essential component of neural networks underlying name retrieval or recognition of common objects or famous faces. PMID:25489630

Separability of Abstract-Category and Specific-Exemplar Visual Object Subsystems: Evidence from fMRI Pattern Analysis

PubMed Central

McMenamin, Brenton W.; Deason, Rebecca G.; Steele, Vaughn R.; Koutstaal, Wilma; Marsolek, Chad J.

2014-01-01

Previous research indicates that dissociable neural subsystems underlie abstract-category (AC) recognition and priming of objects (e.g., cat, piano) and specific-exemplar (SE) recognition and priming of objects (e.g., a calico cat, a different calico cat, a grand piano, etc.). However, the degree of separability between these subsystems is not known, despite the importance of this issue for assessing relevant theories. Visual object representations are widely distributed in visual cortex, thus a multivariate pattern analysis (MVPA) approach to analyzing functional magnetic resonance imaging (fMRI) data may be critical for assessing the separability of different kinds of visual object processing. Here we examined the neural representations of visual object categories and visual object exemplars using multi-voxel pattern analyses of brain activity elicited in visual object processing areas during a repetition-priming task. In the encoding phase, participants viewed visual objects and the printed names of other objects. In the subsequent test phase, participants identified objects that were either same-exemplar primed, different-exemplar primed, word-primed, or unprimed. In visual object processing areas, classifiers were trained to distinguish same-exemplar primed objects from word-primed objects. Then, the abilities of these classifiers to discriminate different-exemplar primed objects and word-primed objects (reflecting AC priming) and to discriminate same-exemplar primed objects and different-exemplar primed objects (reflecting SE priming) was assessed. Results indicated that (a) repetition priming in occipital-temporal regions is organized asymmetrically, such that AC priming is more prevalent in the left hemisphere and SE priming is more prevalent in the right hemisphere, and (b) AC and SE subsystems are weakly modular, not strongly modular or unified. PMID:25528436

Separability of abstract-category and specific-exemplar visual object subsystems: evidence from fMRI pattern analysis.

PubMed

McMenamin, Brenton W; Deason, Rebecca G; Steele, Vaughn R; Koutstaal, Wilma; Marsolek, Chad J

2015-02-01

Previous research indicates that dissociable neural subsystems underlie abstract-category (AC) recognition and priming of objects (e.g., cat, piano) and specific-exemplar (SE) recognition and priming of objects (e.g., a calico cat, a different calico cat, a grand piano, etc.). However, the degree of separability between these subsystems is not known, despite the importance of this issue for assessing relevant theories. Visual object representations are widely distributed in visual cortex, thus a multivariate pattern analysis (MVPA) approach to analyzing functional magnetic resonance imaging (fMRI) data may be critical for assessing the separability of different kinds of visual object processing. Here we examined the neural representations of visual object categories and visual object exemplars using multi-voxel pattern analyses of brain activity elicited in visual object processing areas during a repetition-priming task. In the encoding phase, participants viewed visual objects and the printed names of other objects. In the subsequent test phase, participants identified objects that were either same-exemplar primed, different-exemplar primed, word-primed, or unprimed. In visual object processing areas, classifiers were trained to distinguish same-exemplar primed objects from word-primed objects. Then, the abilities of these classifiers to discriminate different-exemplar primed objects and word-primed objects (reflecting AC priming) and to discriminate same-exemplar primed objects and different-exemplar primed objects (reflecting SE priming) was assessed. Results indicated that (a) repetition priming in occipital-temporal regions is organized asymmetrically, such that AC priming is more prevalent in the left hemisphere and SE priming is more prevalent in the right hemisphere, and (b) AC and SE subsystems are weakly modular, not strongly modular or unified. Copyright © 2014 Elsevier Inc. All rights reserved.

Cross-Cultural Patterns in Dynamic Ratings of Positive and Negative Natural Emotional Behaviour

PubMed Central

Sneddon, Ian; McKeown, Gary; McRorie, Margaret; Vukicevic, Tijana

2011-01-01

Background Studies of cross-cultural variations in the perception of emotion have typically compared rates of recognition of static posed stimulus photographs. That research has provided evidence for universality in the recognition of a range of emotions but also for some systematic cross-cultural variation in the interpretation of emotional expression. However, questions remain about how widely such findings can be generalised to real life emotional situations. The present study provides the first evidence that the previously reported interplay between universal and cultural influences extends to ratings of natural, dynamic emotional stimuli. Methodology/Principal Findings Participants from Northern Ireland, Serbia, Guatemala and Peru used a computer based tool to continuously rate the strength of positive and negative emotion being displayed in twelve short video sequences by people from the United Kingdom engaged in emotional conversations. Generalized additive mixed models were developed to assess the differences in perception of emotion between countries and sexes. Our results indicate that the temporal pattern of ratings is similar across cultures for a range of emotions and social contexts. However, there are systematic differences in intensity ratings between the countries, with participants from Northern Ireland making the most extreme ratings in the majority of the clips. Conclusions/Significance The results indicate that there is strong agreement across cultures in the valence and patterns of ratings of natural emotional situations but that participants from different cultures show systematic variation in the intensity with which they rate emotion. Results are discussed in terms of both ‘in-group advantage’ and ‘display rules’ approaches. This study indicates that examples of natural spontaneous emotional behaviour can be used to study cross-cultural variations in the perception of emotion. PMID:21364739

Cross-cultural patterns in dynamic ratings of positive and negative natural emotional behaviour.

PubMed

Sneddon, Ian; McKeown, Gary; McRorie, Margaret; Vukicevic, Tijana

2011-02-18

Studies of cross-cultural variations in the perception of emotion have typically compared rates of recognition of static posed stimulus photographs. That research has provided evidence for universality in the recognition of a range of emotions but also for some systematic cross-cultural variation in the interpretation of emotional expression. However, questions remain about how widely such findings can be generalised to real life emotional situations. The present study provides the first evidence that the previously reported interplay between universal and cultural influences extends to ratings of natural, dynamic emotional stimuli. Participants from Northern Ireland, Serbia, Guatemala and Peru used a computer based tool to continuously rate the strength of positive and negative emotion being displayed in twelve short video sequences by people from the United Kingdom engaged in emotional conversations. Generalized additive mixed models were developed to assess the differences in perception of emotion between countries and sexes. Our results indicate that the temporal pattern of ratings is similar across cultures for a range of emotions and social contexts. However, there are systematic differences in intensity ratings between the countries, with participants from Northern Ireland making the most extreme ratings in the majority of the clips. The results indicate that there is strong agreement across cultures in the valence and patterns of ratings of natural emotional situations but that participants from different cultures show systematic variation in the intensity with which they rate emotion. Results are discussed in terms of both 'in-group advantage' and 'display rules' approaches. This study indicates that examples of natural spontaneous emotional behaviour can be used to study cross-cultural variations in the perception of emotion.

Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity

PubMed Central

Yeh, Hsiang J.; Guindani, Michele; Vannucci, Marina; Haneef, Zulfi; Stern, John M.

2018-01-01

Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work illuminates many previously unexplored facets of the dynamic properties of functional connectivity between resting-state networks, and provides a platform for dynamic functional connectivity analysis that facilitates its usage as an investigative measure for healthy as well as abnormal brain function. PMID:29320526

Studies of recognition with multitemporal remote sensor data

NASA Technical Reports Server (NTRS)

Malila, W. A.; Hieber, R. H.; Cicone, R. C.

1975-01-01

Characteristics of multitemporal data and their use in recognition processing were investigated. Principal emphasis was on satellite data collected by the LANDSAT multispectral scanner and on temporal changes throughout a growing season. The effects of spatial misregistration on recognition performance with multitemporal data were examined. A capability to compute probabilities of detection and false alarm was developed and used with simulated distributions for misregistered pixels. Wheat detection was found to be degraded and false alarms increased by misregistration effects. Multitemporal signature characteristics and multitemporal recognition processing were studied to gain insights into problems associated with this approach and possible improvements. Recognition performance with one multitemporal data set displayed marked improvements over results from single-time data.

Methods and means of diagnostics of oncological diseases on the basis of pattern recognition: intelligent morphological systems - problems and solutions

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.

2017-01-01

The development of methods of pattern recognition in modern intelligent systems of clinical cancer diagnosis are discussed. The histological (morphological) diagnosis - primary diagnosis for medical setting with cancer are investigated. There are proposed: interactive methods of recognition and structure of intellectual morphological complexes based on expert training-diagnostic and telemedicine systems. The proposed approach successfully implemented in clinical practice.

Monkey’s short-term auditory memory nearly abolished by combined removal of the rostral superior temporal gyrus and rhinal cortices

PubMed Central

Fritz, Jonathan B.; Malloy, Megan; Mishkin, Mortimer; Saunders, Richard C.

2016-01-01

While monkeys easily acquire the rules for performing visual and tactile delayed matching-to-sample, a method for testing recognition memory, they have extraordinary difficulty acquiring a similar rule in audition. Another striking difference between the modalities is that whereas bilateral ablation of the rhinal cortex (RhC) leads to profound impairment in visual and tactile recognition, the same lesion has no detectable effect on auditory recognition memory (Fritz et al., 2005). In our previous study, a mild impairment in auditory memory was obtained following bilateral ablation of the entire medial temporal lobe (MTL), including the RhC, and an equally mild effect was observed after bilateral ablation of the auditory cortical areas in the rostral superior temporal gyrus (rSTG). In order to test the hypothesis that each of these mild impairments was due to partial disconnection of acoustic input to a common target (e.g., the ventromedial prefrontal cortex), in the current study we examined the effects of a more complete auditory disconnection of this common target by combining the removals of both the rSTG and the MTL. We found that the combined lesion led to forgetting thresholds (performance at 75% accuracy) that fell precipitously from the normal retention duration of ~30–40 seconds to a duration of ~1–2 seconds, thus nearly abolishing auditory recognition memory, and leaving behind only a residual echoic memory. PMID:26707975

Early visual experience and the recognition of basic facial expressions: involvement of the middle temporal and inferior frontal gyri during haptic identification by the early blind

PubMed Central

Kitada, Ryo; Okamoto, Yuko; Sasaki, Akihiro T.; Kochiyama, Takanori; Miyahara, Motohide; Lederman, Susan J.; Sadato, Norihiro

2012-01-01

Face perception is critical for social communication. Given its fundamental importance in the course of evolution, the innate neural mechanisms can anticipate the computations necessary for representing faces. However, the effect of visual deprivation on the formation of neural mechanisms that underlie face perception is largely unknown. We previously showed that sighted individuals can recognize basic facial expressions by haptics surprisingly well. Moreover, the inferior frontal gyrus (IFG) and posterior superior temporal sulcus (pSTS) in the sighted subjects are involved in haptic and visual recognition of facial expressions. Here, we conducted both psychophysical and functional magnetic-resonance imaging (fMRI) experiments to determine the nature of the neural representation that subserves the recognition of basic facial expressions in early blind individuals. In a psychophysical experiment, both early blind and sighted subjects haptically identified basic facial expressions at levels well above chance. In the subsequent fMRI experiment, both groups haptically identified facial expressions and shoe types (control). The sighted subjects then completed the same task visually. Within brain regions activated by the visual and haptic identification of facial expressions (relative to that of shoes) in the sighted group, corresponding haptic identification in the early blind activated regions in the inferior frontal and middle temporal gyri. These results suggest that the neural system that underlies the recognition of basic facial expressions develops supramodally even in the absence of early visual experience. PMID:23372547

Early visual experience and the recognition of basic facial expressions: involvement of the middle temporal and inferior frontal gyri during haptic identification by the early blind.

PubMed

Kitada, Ryo; Okamoto, Yuko; Sasaki, Akihiro T; Kochiyama, Takanori; Miyahara, Motohide; Lederman, Susan J; Sadato, Norihiro

2013-01-01

Face perception is critical for social communication. Given its fundamental importance in the course of evolution, the innate neural mechanisms can anticipate the computations necessary for representing faces. However, the effect of visual deprivation on the formation of neural mechanisms that underlie face perception is largely unknown. We previously showed that sighted individuals can recognize basic facial expressions by haptics surprisingly well. Moreover, the inferior frontal gyrus (IFG) and posterior superior temporal sulcus (pSTS) in the sighted subjects are involved in haptic and visual recognition of facial expressions. Here, we conducted both psychophysical and functional magnetic-resonance imaging (fMRI) experiments to determine the nature of the neural representation that subserves the recognition of basic facial expressions in early blind individuals. In a psychophysical experiment, both early blind and sighted subjects haptically identified basic facial expressions at levels well above chance. In the subsequent fMRI experiment, both groups haptically identified facial expressions and shoe types (control). The sighted subjects then completed the same task visually. Within brain regions activated by the visual and haptic identification of facial expressions (relative to that of shoes) in the sighted group, corresponding haptic identification in the early blind activated regions in the inferior frontal and middle temporal gyri. These results suggest that the neural system that underlies the recognition of basic facial expressions develops supramodally even in the absence of early visual experience.

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models

PubMed Central

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner’s faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals. PMID:27191162

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models.

PubMed

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner's faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals.

Postprocessing for character recognition using pattern features and linguistic information

NASA Astrophysics Data System (ADS)

Yoshikawa, Takatoshi; Okamoto, Masayosi; Horii, Hiroshi

1993-04-01

We propose a new method of post-processing for character recognition using pattern features and linguistic information. This method corrects errors in the recognition of handwritten Japanese sentences containing Kanji characters. This post-process method is characterized by having two types of character recognition. Improving the accuracy of the character recognition rate of Japanese characters is made difficult by the large number of characters, and the existence of characters with similar patterns. Therefore, it is not practical for a character recognition system to recognize all characters in detail. First, this post-processing method generates a candidate character table by recognizing the simplest features of characters. Then, it selects words corresponding to the character from the candidate character table by referring to a word and grammar dictionary before selecting suitable words. If the correct character is included in the candidate character table, this process can correct an error, however, if the character is not included, it cannot correct an error. Therefore, if this method can presume a character does not exist in a candidate character table by using linguistic information (word and grammar dictionary). It then can verify a presumed character by character recognition using complex features. When this method is applied to an online character recognition system, the accuracy of character recognition improves 93.5% to 94.7%. This proved to be the case when it was used for the editorials of a Japanese newspaper (Asahi Shinbun).

Deep Recurrent Neural Networks for Human Activity Recognition

PubMed Central

Murad, Abdulmajid

2017-01-01

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs. PMID:29113103

Deep Recurrent Neural Networks for Human Activity Recognition.

PubMed

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

Contributions of Low and High Spatial Frequency Processing to Impaired Object Recognition Circuitry in Schizophrenia

PubMed Central

Calderone, Daniel J.; Hoptman, Matthew J.; Martínez, Antígona; Nair-Collins, Sangeeta; Mauro, Cristina J.; Bar, Moshe; Javitt, Daniel C.; Butler, Pamela D.

2013-01-01

Patients with schizophrenia exhibit cognitive and sensory impairment, and object recognition deficits have been linked to sensory deficits. The “frame and fill” model of object recognition posits that low spatial frequency (LSF) information rapidly reaches the prefrontal cortex (PFC) and creates a general shape of an object that feeds back to the ventral temporal cortex to assist object recognition. Visual dysfunction findings in schizophrenia suggest a preferential loss of LSF information. This study used functional magnetic resonance imaging (fMRI) and resting state functional connectivity (RSFC) to investigate the contribution of visual deficits to impaired object “framing” circuitry in schizophrenia. Participants were shown object stimuli that were intact or contained only LSF or high spatial frequency (HSF) information. For controls, fMRI revealed preferential activation to LSF information in precuneus, superior temporal, and medial and dorsolateral PFC areas, whereas patients showed a preference for HSF information or no preference. RSFC revealed a lack of connectivity between early visual areas and PFC for patients. These results demonstrate impaired processing of LSF information during object recognition in schizophrenia, with patients instead displaying increased processing of HSF information. This is consistent with findings of a preference for local over global visual information in schizophrenia. PMID:22735157

Temporal voice areas exist in autism spectrum disorder but are dysfunctional for voice identity recognition

PubMed Central

Borowiak, Kamila; von Kriegstein, Katharina

2016-01-01

The ability to recognise the identity of others is a key requirement for successful communication. Brain regions that respond selectively to voices exist in humans from early infancy on. Currently, it is unclear whether dysfunction of these voice-sensitive regions can explain voice identity recognition impairments. Here, we used two independent functional magnetic resonance imaging studies to investigate voice processing in a population that has been reported to have no voice-sensitive regions: autism spectrum disorder (ASD). Our results refute the earlier report that individuals with ASD have no responses in voice-sensitive regions: Passive listening to vocal, compared to non-vocal, sounds elicited typical responses in voice-sensitive regions in the high-functioning ASD group and controls. In contrast, the ASD group had a dysfunction in voice-sensitive regions during voice identity but not speech recognition in the right posterior superior temporal sulcus/gyrus (STS/STG)—a region implicated in processing complex spectrotemporal voice features and unfamiliar voices. The right anterior STS/STG correlated with voice identity recognition performance in controls but not in the ASD group. The findings suggest that right STS/STG dysfunction is critical for explaining voice recognition impairments in high-functioning ASD and show that ASD is not characterised by a general lack of voice-sensitive responses. PMID:27369067

Trajectory Recognition as the Basis for Object Individuation: A Functional Model of Object File Instantiation and Object-Token Encoding

PubMed Central

Fields, Chris

2011-01-01

The perception of persisting visual objects is mediated by transient intermediate representations, object files, that are instantiated in response to some, but not all, visual trajectories. The standard object file concept does not, however, provide a mechanism sufficient to account for all experimental data on visual object persistence, object tracking, and the ability to perceive spatially disconnected stimuli as continuously existing objects. Based on relevant anatomical, functional, and developmental data, a functional model is constructed that bases visual object individuation on the recognition of temporal sequences of apparent center-of-mass positions that are specifically identified as trajectories by dedicated “trajectory recognition networks” downstream of the medial–temporal motion-detection area. This model is shown to account for a wide range of data, and to generate a variety of testable predictions. Individual differences in the recognition, abstraction, and encoding of trajectory information are expected to generate distinct object persistence judgments and object recognition abilities. Dominance of trajectory information over feature information in stored object tokens during early infancy, in particular, is expected to disrupt the ability to re-identify human and other individuals across perceptual episodes, and lead to developmental outcomes with characteristics of autism spectrum disorders. PMID:21716599

Neural Mechanism for Mirrored Self-face Recognition.

PubMed

Sugiura, Motoaki; Miyauchi, Carlos Makoto; Kotozaki, Yuka; Akimoto, Yoritaka; Nozawa, Takayuki; Yomogida, Yukihito; Hanawa, Sugiko; Yamamoto, Yuki; Sakuma, Atsushi; Nakagawa, Seishu; Kawashima, Ryuta

2015-09-01

Self-face recognition in the mirror is considered to involve multiple processes that integrate 2 perceptual cues: temporal contingency of the visual feedback on one's action (contingency cue) and matching with self-face representation in long-term memory (figurative cue). The aim of this study was to examine the neural bases of these processes by manipulating 2 perceptual cues using a "virtual mirror" system. This system allowed online dynamic presentations of real-time and delayed self- or other facial actions. Perception-level processes were identified as responses to only a single perceptual cue. The effect of the contingency cue was identified in the cuneus. The regions sensitive to the figurative cue were subdivided by the response to a static self-face, which was identified in the right temporal, parietal, and frontal regions, but not in the bilateral occipitoparietal regions. Semantic- or integration-level processes, including amodal self-representation and belief validation, which allow modality-independent self-recognition and the resolution of potential conflicts between perceptual cues, respectively, were identified in distinct regions in the right frontal and insular cortices. The results are supportive of the multicomponent notion of self-recognition and suggest a critical role for contingency detection in the co-emergence of self-recognition and empathy in infants. © The Author 2014. Published by Oxford University Press.

Neural Mechanism for Mirrored Self-face Recognition

PubMed Central

Sugiura, Motoaki; Miyauchi, Carlos Makoto; Kotozaki, Yuka; Akimoto, Yoritaka; Nozawa, Takayuki; Yomogida, Yukihito; Hanawa, Sugiko; Yamamoto, Yuki; Sakuma, Atsushi; Nakagawa, Seishu; Kawashima, Ryuta

2015-01-01

Self-face recognition in the mirror is considered to involve multiple processes that integrate 2 perceptual cues: temporal contingency of the visual feedback on one's action (contingency cue) and matching with self-face representation in long-term memory (figurative cue). The aim of this study was to examine the neural bases of these processes by manipulating 2 perceptual cues using a “virtual mirror” system. This system allowed online dynamic presentations of real-time and delayed self- or other facial actions. Perception-level processes were identified as responses to only a single perceptual cue. The effect of the contingency cue was identified in the cuneus. The regions sensitive to the figurative cue were subdivided by the response to a static self-face, which was identified in the right temporal, parietal, and frontal regions, but not in the bilateral occipitoparietal regions. Semantic- or integration-level processes, including amodal self-representation and belief validation, which allow modality-independent self-recognition and the resolution of potential conflicts between perceptual cues, respectively, were identified in distinct regions in the right frontal and insular cortices. The results are supportive of the multicomponent notion of self-recognition and suggest a critical role for contingency detection in the co-emergence of self-recognition and empathy in infants. PMID:24770712

Facial emotion recognition in patients with focal and diffuse axonal injury.

PubMed

Yassin, Walid; Callahan, Brandy L; Ubukata, Shiho; Sugihara, Genichi; Murai, Toshiya; Ueda, Keita

2017-01-01

Facial emotion recognition impairment has been well documented in patients with traumatic brain injury. Studies exploring the neural substrates involved in such deficits have implicated specific grey matter structures (e.g. orbitofrontal regions), as well as diffuse white matter damage. Our study aims to clarify whether different types of injuries (i.e. focal vs. diffuse) will lead to different types of impairments on facial emotion recognition tasks, as no study has directly compared these patients. The present study examined performance and response patterns on a facial emotion recognition task in 14 participants with diffuse axonal injury (DAI), 14 with focal injury (FI) and 22 healthy controls. We found that, overall, participants with FI and DAI performed more poorly than controls on the facial emotion recognition task. Further, we observed comparable emotion recognition performance in participants with FI and DAI, despite differences in the nature and distribution of their lesions. However, the rating response pattern between the patient groups was different. This is the first study to show that pure DAI, without gross focal lesions, can independently lead to facial emotion recognition deficits and that rating patterns differ depending on the type and location of trauma.

Medial temporal lobe function during emotional memory in early Alzheimer’s disease, mild cognitive impairment and healthy ageing: an fMRI study

PubMed Central

2013-01-01

Background Relative to intentional memory encoding, which quickly declines in Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD), incidental memory for emotional stimuli appears to deteriorate more slowly. We hypothesised that tests of incidental emotional memory may inform on different aspects of cognitive decline in MCI and AD. Methods Patients with MCI, AD and Healthy Controls (HC) were asked to attend to emotional pictures (i.e., positive and neutral) sequentially presented during an fMRI session. Attention was monitored behaviourally. A surprise post-scan recognition test was then administered. Results The groups remained attentive within the scanner. The post-scan recognition pattern was in the form of (HC = MCI) > AD, with only the former group showing a clear benefit from emotional pictures. fMRI analysis of incidental encoding demonstrated clusters of activation in para-hippocampal regions and in the hippocampus in HC and MCI patients but not in AD patients. The pattern of activation observed in MCI patients tended to be greater than that found in HC. Conclusions The results suggest that incidental emotional memory might offer a suitable platform to investigate, using behavioural and fMRI measures, subtle changes in the process of developing AD. These changes seem to differ from those found using standard episodic memory tests. The underpinnings of such differences and the potential clinical use of this methodology are discussed in depth. PMID:23497150

Non-accidental properties, metric invariance, and encoding by neurons in a model of ventral stream visual object recognition, VisNet.

PubMed

Rolls, Edmund T; Mills, W Patrick C

2018-05-01

When objects transform into different views, some properties are maintained, such as whether the edges are convex or concave, and these non-accidental properties are likely to be important in view-invariant object recognition. The metric properties, such as the degree of curvature, may change with different views, and are less likely to be useful in object recognition. It is shown that in a model of invariant visual object recognition in the ventral visual stream, VisNet, non-accidental properties are encoded much more than metric properties by neurons. Moreover, it is shown how with the temporal trace rule training in VisNet, non-accidental properties of objects become encoded by neurons, and how metric properties are treated invariantly. We also show how VisNet can generalize between different objects if they have the same non-accidental property, because the metric properties are likely to overlap. VisNet is a 4-layer unsupervised model of visual object recognition trained by competitive learning that utilizes a temporal trace learning rule to implement the learning of invariance using views that occur close together in time. A second crucial property of this model of object recognition is, when neurons in the level corresponding to the inferior temporal visual cortex respond selectively to objects, whether neurons in the intermediate layers can respond to combinations of features that may be parts of two or more objects. In an investigation using the four sides of a square presented in every possible combination, it was shown that even though different layer 4 neurons are tuned to encode each feature or feature combination orthogonally, neurons in the intermediate layers can respond to features or feature combinations present is several objects. This property is an important part of the way in which high capacity can be achieved in the four-layer ventral visual cortical pathway. These findings concerning non-accidental properties and the use of neurons in intermediate layers of the hierarchy help to emphasise fundamental underlying principles of the computations that may be implemented in the ventral cortical visual stream used in object recognition. Copyright © 2018 Elsevier Inc. All rights reserved.

33 CFR 106.205 - Company Security Officer (CSO).

Code of Federal Regulations, 2011 CFR

2011-07-01

... security related communications; (7) Knowledge of current security threats and patterns; (8) Recognition and detection of dangerous substances and devices; (9) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (10) Techniques used to circumvent security...

33 CFR 106.205 - Company Security Officer (CSO).

Code of Federal Regulations, 2010 CFR

2010-07-01

... security related communications; (7) Knowledge of current security threats and patterns; (8) Recognition and detection of dangerous substances and devices; (9) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (10) Techniques used to circumvent security...

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, G.C.; Martinez, R.F.

1999-05-04

A method of clustering using a novel template to define a region of influence is disclosed. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques. 30 figs.

Multiple degree of freedom optical pattern recognition

NASA Technical Reports Server (NTRS)

Casasent, D.

1987-01-01

Three general optical approaches to multiple degree of freedom object pattern recognition (where no stable object rest position exists) are advanced. These techniques include: feature extraction, correlation, and artificial intelligence. The details of the various processors are advanced together with initial results.

Ultrasonography of ovarian masses using a pattern recognition approach

PubMed Central

Jung, Sung Il

2015-01-01

As a primary imaging modality, ultrasonography (US) can provide diagnostic information for evaluating ovarian masses. Using a pattern recognition approach through gray-scale transvaginal US, ovarian masses can be diagnosed with high specificity and sensitivity. Doppler US may allow ovarian masses to be diagnosed as benign or malignant with even greater confidence. In order to differentiate benign and malignant ovarian masses, it is necessary to categorize ovarian masses into unilocular cyst, unilocular solid cyst, multilocular cyst, multilocular solid cyst, and solid tumor, and then to detect typical US features that demonstrate malignancy based on pattern recognition approach. PMID:25797108

Application of pattern recognition techniques to crime analysis

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

Bender, C.F.; Cox, L.A. Jr.; Chappell, G.A.

1976-08-15

The initial goal was to evaluate the capabilities of current pattern recognition techniques when applied to existing computerized crime data. Performance was to be evaluated both in terms of the system's capability to predict crimes and to optimize police manpower allocation. A relation was sought to predict the crime's susceptibility to solution, based on knowledge of the crime type, location, time, etc. The preliminary results of this work are discussed. They indicate that automatic crime analysis involving pattern recognition techniques is feasible, and that efforts to determine optimum variables and techniques are warranted. 47 figures (RWR)

DESIGN OF A PATTERN RECOGNITION DIGITAL COMPUTER WITH APPLICATION TO THE AUTOMATIC SCANNING OF BUBBLE CHAMBER NEGATIVES

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

McCormick, B.H.; Narasimhan, R.

1963-01-01

The overall computer system contains three main parts: an input device, a pattern recognition unit (PRU), and a control computer. The bubble chamber picture is divided into a grid of st run. Concent 1-mm squares on the film. It is then processed in parallel in a two-dimensional array of 1024 identical processing modules (stalactites) of the PRU. The array can function as a two- dimensional shift register in which results of successive shifting operations can be accumulated. The pattern recognition process is generally controlled by a conventional arithmetic computer. (A.G.W.)

Directing an appropriate immune response: the role of defense collagens and other soluble pattern recognition molecules.

PubMed

Fraser, D A; Tenner, A J

2008-02-01

Defense collagens and other soluble pattern recognition receptors contain the ability to recognize and bind molecular patterns associated with pathogens (PAMPs) or apoptotic cells (ACAMPs) and signal appropriate effector-function responses. PAMP recognition by defense collagens C1q, MBL and ficolins leads to rapid containment of infection via complement activation. However, in the absence of danger, such as during the clearance of apoptotic cells, defense collagens such as C1q, MBL, ficolins, SP-A, SP-D and even adiponectin have all been shown to facilitate enhanced phagocytosis and modulate induction of cytokines towards an anti-inflammatory profile. In this way, cellular debris can be removed without provoking an inflammatory immune response which may be important in the prevention of autoimmunity and/or resolving inflammation. Indeed, deficiencies and/or knock-out mouse studies have highlighted critical roles for soluble pattern recognition receptors in the clearance of apoptotic bodies and protection from autoimmune diseases along with mediating protection from specific infections. Understanding the mechanisms involved in defense collagen and other soluble pattern recognition receptor modulation of the immune response may provide important novel insights into therapeutic targets for infectious and/or autoimmune diseases and additionally may identify avenues for more effective vaccine design.

Visual scanning behavior is related to recognition performance for own- and other-age faces

PubMed Central

Proietti, Valentina; Macchi Cassia, Viola; dell’Amore, Francesca; Conte, Stefania; Bricolo, Emanuela

2015-01-01

It is well-established that our recognition ability is enhanced for faces belonging to familiar categories, such as own-race faces and own-age faces. Recent evidence suggests that, for race, the recognition bias is also accompanied by different visual scanning strategies for own- compared to other-race faces. Here, we tested the hypothesis that these differences in visual scanning patterns extend also to the comparison between own and other-age faces and contribute to the own-age recognition advantage. Participants (young adults with limited experience with infants) were tested in an old/new recognition memory task where they encoded and subsequently recognized a series of adult and infant faces while their eye movements were recorded. Consistent with findings on the other-race bias, we found evidence of an own-age bias in recognition which was accompanied by differential scanning patterns, and consequently differential encoding strategies, for own-compared to other-age faces. Gaze patterns for own-age faces involved a more dynamic sampling of the internal features and longer viewing time on the eye region compared to the other regions of the face. This latter strategy was extensively employed during learning (vs. recognition) and was positively correlated to discriminability. These results suggest that deeply encoding the eye region is functional for recognition and that the own-age bias is evident not only in differential recognition performance, but also in the employment of different sampling strategies found to be effective for accurate recognition. PMID:26579056

Temporal Patterns of Behavior from the Scheduling of Psychology Quizzes

ERIC Educational Resources Information Center

Jarmolowicz, David P.; Hayashi, Yusuke; St. Peter Pipkin, Claire

2010-01-01

Temporal patterns of behavior have been observed in real-life performances such as bill passing in the U.S. Congress, in-class studying, and quiz taking. However, the practical utility of understanding these patterns has not been evaluated. The current study demonstrated the presence of temporal patterns of quiz taking in a university-level…

CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern

NASA Astrophysics Data System (ADS)

Gong, Qian; Qu, Zhiyi; Hao, Kun

2017-07-01

Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

Emotional Faces in Context: Age Differences in Recognition Accuracy and Scanning Patterns

PubMed Central

Noh, Soo Rim; Isaacowitz, Derek M.

2014-01-01

While age-related declines in facial expression recognition are well documented, previous research relied mostly on isolated faces devoid of context. We investigated the effects of context on age differences in recognition of facial emotions and in visual scanning patterns of emotional faces. While their eye movements were monitored, younger and older participants viewed facial expressions (i.e., anger, disgust) in contexts that were emotionally congruent, incongruent, or neutral to the facial expression to be identified. Both age groups had highest recognition rates of facial expressions in the congruent context, followed by the neutral context, and recognition rates in the incongruent context were worst. These context effects were more pronounced for older adults. Compared to younger adults, older adults exhibited a greater benefit from congruent contextual information, regardless of facial expression. Context also influenced the pattern of visual scanning characteristics of emotional faces in a similar manner across age groups. In addition, older adults initially attended more to context overall. Our data highlight the importance of considering the role of context in understanding emotion recognition in adulthood. PMID:23163713

Comparing the visual spans for faces and letters

PubMed Central

He, Yingchen; Scholz, Jennifer M.; Gage, Rachel; Kallie, Christopher S.; Liu, Tingting; Legge, Gordon E.

2015-01-01

The visual span—the number of adjacent text letters that can be reliably recognized on one fixation—has been proposed as a sensory bottleneck that limits reading speed (Legge, Mansfield, & Chung, 2001). Like reading, searching for a face is an important daily task that involves pattern recognition. Is there a similar limitation on the number of faces that can be recognized in a single fixation? Here we report on a study in which we measured and compared the visual-span profiles for letter and face recognition. A serial two-stage model for pattern recognition was developed to interpret the data. The first stage is characterized by factors limiting recognition of isolated letters or faces, and the second stage represents the interfering effect of nearby stimuli on recognition. Our findings show that the visual span for faces is smaller than that for letters. Surprisingly, however, when differences in first-stage processing for letters and faces are accounted for, the two visual spans become nearly identical. These results suggest that the concept of visual span may describe a common sensory bottleneck that underlies different types of pattern recognition. PMID:26129858

Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies

NASA Astrophysics Data System (ADS)

Fournier-Viger, Philippe; Nkambou, Roger; Faghihi, Usef; Nguifo, Engelbert Mephu

We propose two mechanisms for agent learning based on the idea of mining temporal patterns from agent behavior. The first one consists of extracting temporal patterns from the perceived behavior of other agents accomplishing a task, to learn the task. The second learning mechanism consists in extracting temporal patterns from an agent's own behavior. In this case, the agent then reuses patterns that brought self-satisfaction. In both cases, no assumption is made on how the observed agents' behavior is internally generated. A case study with a real application is presented to illustrate each learning mechanism.

Recognition of Time-Compressed and Natural Speech with Selective Temporal Enhancements by Young and Elderly Listeners

ERIC Educational Resources Information Center

Gordon-Salant, Sandra; Fitzgibbons, Peter J.; Friedman, Sarah A.

2007-01-01

Purpose: The goal of this experiment was to determine whether selective slowing of speech segments improves recognition performance by young and elderly listeners. The hypotheses were (a) the benefits of time expansion occur for rapid speech but not for natural-rate speech, (b) selective time expansion of consonants produces greater score…

Remembering versus Knowing during Face Recognition in Unilateral Temporal Lobe Epilepsy Patients with or without Hippocampal Sclerosis

ERIC Educational Resources Information Center

Bengner, Thomas; Malina, Thomas

2008-01-01

Recognition memory involves knowing an item was learned (familiarity) and remembering contextual details about the prior learning episode (recollection). We tested three competing hypotheses about the role of the hippocampus in recollection and familiarity. It mediates either recollection or familiarity, or serves both processes. We further tested…

Training Strategies for Mitigating the Effect of Proportional Control on Classification in Pattern Recognition Based Myoelectric Control

PubMed Central

Scheme, Erik; Englehart, Kevin

2013-01-01

The performance of pattern recognition based myoelectric control has seen significant interest in the research community for many years. Due to a recent surge in the development of dexterous prosthetic devices, determining the clinical viability of multifunction myoelectric control has become paramount. Several factors contribute to differences between offline classification accuracy and clinical usability, but the overriding theme is that the variability of the elicited patterns increases greatly during functional use. Proportional control has been shown to greatly improve the usability of conventional myoelectric control systems. Typically, a measure of the amplitude of the electromyogram (a rectified and smoothed version) is used to dictate the velocity of control of a device. The discriminatory power of myoelectric pattern classifiers, however, is also largely based on amplitude features of the electromyogram. This work presents an introductory look at the effect of contraction strength and proportional control on pattern recognition based control. These effects are investigated using typical pattern recognition data collection methods as well as a real-time position tracking test. Training with dynamically force varying contractions and appropriate gain selection is shown to significantly improve (p<0.001) the classifier’s performance and tolerance to proportional control. PMID:23894224

Addressing the issue of insufficient information in data-based bridge health monitoring : final report.

DOT National Transportation Integrated Search

2015-11-01

One of the most efficient ways to solve the damage detection problem using the statistical pattern recognition : approach is that of exploiting the methods of outlier analysis. Cast within the pattern recognition framework, : damage detection assesse...

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

PubMed

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-19

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

PubMed Central

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-01

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed. PMID:25608217

Human brain activity with functional NIR optical imager

NASA Astrophysics Data System (ADS)

Luo, Qingming

2001-08-01

In this paper we reviewed the applications of functional near infrared optical imager in human brain activity. Optical imaging results of brain activity, including memory for new association, emotional thinking, mental arithmetic, pattern recognition ' where's Waldo?, occipital cortex in visual stimulation, and motor cortex in finger tapping, are demonstrated. It is shown that the NIR optical method opens up new fields of study of the human population, in adults under conditions of simulated or real stress that may have important effects upon functional performance. It makes practical and affordable for large populations the complex technology of measuring brain function. It is portable and low cost. In cognitive tasks subjects could report orally. The temporal resolution could be millisecond or less in theory. NIR method will have good prospects in exploring human brain secret.

Feature extraction inspired by V1 in visual cortex

NASA Astrophysics Data System (ADS)

Lv, Chao; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Xin, Peng; Zhu, Mingning; Ma, Hongqiang

2018-04-01

Target feature extraction plays an important role in pattern recognition. It is the most complicated activity in the brain mechanism of biological vision. Inspired by high properties of primary visual cortex (V1) in extracting dynamic and static features, a visual perception model was raised. Firstly, 28 spatial-temporal filters with different orientations, half-squaring operation and divisive normalization were adopted to obtain the responses of V1 simple cells; then, an adjustable parameter was added to the output weight so that the response of complex cells was got. Experimental results indicate that the proposed V1 model can perceive motion information well. Besides, it has a good edge detection capability. The model inspired by V1 has good performance in feature extraction and effectively combines brain-inspired intelligence with computer vision.

Temporal identity in axonal target layer recognition.

PubMed

Petrovic, Milan; Hummel, Thomas

2008-12-11

The segregation of axon and dendrite projections into distinct synaptic layers is a fundamental principle of nervous system organization and the structural basis for information processing in the brain. Layer-specific recognition molecules that allow projecting neurons to stabilize transient contacts and initiate synaptogenesis have been identified. However, most of the neuronal cell-surface molecules critical for layer organization are expressed broadly in the developing nervous system, raising the question of how these so-called permissive adhesion molecules support synaptic specificity. Here we show that the temporal expression dynamics of the zinc-finger protein sequoia is the major determinant of Drosophila photoreceptor connectivity into distinct synaptic layers. Neighbouring R8 and R7 photoreceptors show consecutive peaks of elevated sequoia expression, which correspond to their sequential target-layer innervation. Loss of sequoia in R7 leads to a projection switch into the R8 recipient layer, whereas a prolonged expression in R8 induces a redirection of their axons into the R7 layer. The sequoia-induced axon targeting is mediated through the ubiquitously expressed Cadherin-N cell adhesion molecule. Our data support a model in which recognition specificity during synaptic layer formation is generated through a temporally restricted axonal competence to respond to broadly expressed adhesion molecules. Because developing neurons innervating the same target area often project in a distinct, birth-order-dependent sequence, temporal identity seems to contain crucial information in generating not only cell type diversity during neuronal division but also connection diversity of projecting neurons.

Impaired familiarity with preserved recollection after anterior temporal-lobe resection that spares the hippocampus.

PubMed

Bowles, Ben; Crupi, Carina; Mirsattari, Seyed M; Pigott, Susan E; Parrent, Andrew G; Pruessner, Jens C; Yonelinas, Andrew P; Köhler, Stefan

2007-10-09

It is well established that the medial-temporal lobe (MTL) is critical for recognition memory. The MTL is known to be composed of distinct structures that are organized in a hierarchical manner. At present, it remains controversial whether lower structures in this hierarchy, such as perirhinal cortex, support memory functions that are distinct from those of higher structures, in particular the hippocampus. Perirhinal cortex has been proposed to play a specific role in the assessment of familiarity during recognition, which can be distinguished from the selective contributions of the hippocampus to the recollection of episodic detail. Some researchers have argued, however, that the distinction between familiarity and recollection cannot capture functional specialization within the MTL and have proposed single-process accounts. Evidence supporting the dual-process view comes from demonstrations that selective hippocampal damage can produce isolated recollection impairments. It is unclear, however, whether temporal-lobe lesions that spare the hippocampus can produce selective familiarity impairments. Without this demonstration, single-process accounts cannot be ruled out. We examined recognition memory in NB, an individual who underwent surgical resection of left anterior temporal-lobe structures for treatment of intractable epilepsy. Her resection included a large portion of perirhinal cortex but spared the hippocampus. The results of four experiments based on three different experimental procedures (remember-know paradigm, receiver operating characteristics, and response-deadline procedure) indicate that NB exhibits impaired familiarity with preserved recollection. The present findings thus provide a crucial missing piece of support for functional specialization in the MTL.

Episodic Memory and Regional Atrophy in Frontotemporal Lobar Degeneration

PubMed Central

Söderlund, Hedvig; Black, Sandra E.; Miller, Bruce L.; Freedman, Morris; Levine, Brian

2008-01-01

It has been unclear to what extent memory is affected in frontotemporal lobar degeneration (FTLD). Since patients usually have atrophy in regions implicated in memory function, the frontal and/or temporal lobes, one would expect some memory impairment, and that the degree of atrophy in these regions would be inversely related to memory function. The purposes of this study were 1) to assess episodic memory function in FTLD, and more specifically patients' ability to episodically re-experience an event, and determine its source; 2) to examine whether memory performance is related to quantified regional brain atrophy. FTLD patients (n=18) and healthy comparison subjects (n=14) were assessed with cued recall, recognition, “remember/know” (self-reported re-experiencing) and source recall, at 30 min and 24 hr after encoding. Regional gray matter volumes were assessed with high resolution structural MRI concurrently to testing. Patients performed worse than comparison subjects on all memory measures. Gray matter volume in the left medial temporal lobe was positively correlated with recognition, re-experiencing, and source recall. Gray matter volume in the left posterior temporal lobe correlated significantly with recognition, at 30 min and 24 hr, and with source recall at 30 min. Estimated familiarity at 30 min was positively correlated with gray matter volume in the left inferior parietal lobe. In summary, episodic memory deficits in FTLD may be more common than previously thought, particularly in patients with left medial and posterior temporal atrophy. PMID:17888461

A Novel Fiber Optic Based Surveillance System for Prevention of Pipeline Integrity Threats.

PubMed

Tejedor, Javier; Macias-Guarasa, Javier; Martins, Hugo F; Piote, Daniel; Pastor-Graells, Juan; Martin-Lopez, Sonia; Corredera, Pedro; Gonzalez-Herraez, Miguel

2017-02-12

This paper presents a novel surveillance system aimed at the detection and classification of threats in the vicinity of a long gas pipeline. The sensing system is based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) technology for signal acquisition and pattern recognition strategies for threat identification. The proposal incorporates contextual information at the feature level and applies a system combination strategy for pattern classification. The contextual information at the feature level is based on the tandem approach (using feature representations produced by discriminatively-trained multi-layer perceptrons) by employing feature vectors that spread different temporal contexts. The system combination strategy is based on a posterior combination of likelihoods computed from different pattern classification processes. The system operates in two different modes: (1) machine + activity identification, which recognizes the activity being carried out by a certain machine, and (2) threat detection, aimed at detecting threats no matter what the real activity being conducted is. In comparison with a previous system based on the same rigorous experimental setup, the results show that the system combination from the contextual feature information improves the results for each individual class in both operational modes, as well as the overall classification accuracy, with statistically-significant improvements.

Adaptive Classification of Landscape Process and Function: An Integration of Geoinformatics and Self-Organizing Maps

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

Coleman, Andre M.

2009-07-17

The advanced geospatial information extraction and analysis capabilities of a Geographic Information System (GISs) and Artificial Neural Networks (ANNs), particularly Self-Organizing Maps (SOMs), provide a topology-preserving means for reducing and understanding complex data relationships in the landscape. The Adaptive Landscape Classification Procedure (ALCP) is presented as an adaptive and evolutionary capability where varying types of data can be assimilated to address different management needs such as hydrologic response, erosion potential, habitat structure, instrumentation placement, and various forecast or what-if scenarios. This paper defines how the evaluation and analysis of spatial and/or temporal patterns in the landscape can provide insight intomore » complex ecological, hydrological, climatic, and other natural and anthropogenic-influenced processes. Establishing relationships among high-dimensional datasets through neurocomputing based pattern recognition methods can help 1) resolve large volumes of data into a structured and meaningful form; 2) provide an approach for inferring landscape processes in areas that have limited data available but exhibit similar landscape characteristics; and 3) discover the value of individual variables or groups of variables that contribute to specific processes in the landscape. Classification of hydrologic patterns in the landscape is demonstrated.« less

Spatio-temporal Analysis for New York State SPARCS Data

PubMed Central

Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng

2017-01-01

Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148

Iris recognition based on key image feature extraction.

PubMed

Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

2008-01-01

In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

The Development of Invariant Object Recognition Requires Visual Experience with Temporally Smooth Objects

ERIC Educational Resources Information Center

Wood, Justin N.; Wood, Samantha M. W.

2018-01-01

How do newborns learn to recognize objects? According to temporal learning models in computational neuroscience, the brain constructs object representations by extracting smoothly changing features from the environment. To date, however, it is unknown whether newborns depend on smoothly changing features to build invariant object representations.…

Quantum pattern recognition with multi-neuron interactions

NASA Astrophysics Data System (ADS)

Fard, E. Rezaei; Aghayar, K.; Amniat-Talab, M.

2018-03-01

We present a quantum neural network with multi-neuron interactions for pattern recognition tasks by a combination of extended classic Hopfield network and adiabatic quantum computation. This scheme can be used as an associative memory to retrieve partial patterns with any number of unknown bits. Also, we propose a preprocessing approach to classifying the pattern space S to suppress spurious patterns. The results of pattern clustering show that for pattern association, the number of weights (η ) should equal the numbers of unknown bits in the input pattern ( d). It is also remarkable that associative memory function depends on the location of unknown bits apart from the d and load parameter α.

Tree invasion of a montane meadow complex: temporal trends, spatial patterns, and biotic interactions

Treesearch

Charles B. Halpern; Joseph A. Antos; Janine M. Rice; Ryan D. Haugo; Nicole L. Lang

2010-01-01

We combined spatial point pattern analysis, population age structures, and a time-series of stem maps to quantify spatial and temporal patterns of conifer invasion over a 200-yr period in three plots totaling 4 ha. In combination, spatial and temporal patterns of establishment suggest an invasion process shaped by biotic interactions, with facilitation promoting...

Local but not long-range microstructural differences of the ventral temporal cortex in developmental prosopagnosia

PubMed Central

Song, Sunbin; Garrido, Lúcia; Nagy, Zoltan; Mohammadi, Siawoosh; Steel, Adam; Driver, Jon; Dolan, Ray J.; Duchaine, Bradley; Furl, Nicholas

2015-01-01

Individuals with developmental prosopagnosia (DP) experience face recognition impairments despite normal intellect and low-level vision and no history of brain damage. Prior studies using diffusion tensor imaging in small samples of subjects with DP (n=6 or n=8) offer conflicting views on the neurobiological bases for DP, with one suggesting white matter differences in two major long-range tracts running through the temporal cortex, and another suggesting white matter differences confined to fibers local to ventral temporal face-specific functional regions of interest (fROIs) in the fusiform gyrus. Here, we address these inconsistent findings using a comprehensive set of analyzes in a sample of DP subjects larger than both prior studies combined (n=16). While we found no microstructural differences in long-range tracts between DP and age-matched control participants, we found differences local to face-specific fROIs, and relationships between these microstructural measures with face recognition ability. We conclude that subtle differences in local rather than long-range tracts in the ventral temporal lobe are more likely associated with developmental prosopagnosia. PMID:26456436

Comparison of auditory temporal resolution between monolingual Persian and bilingual Turkish-Persian individuals.

PubMed

Omidvar, Shaghayegh; Jafari, Zahra; Tahaei, Ali Akbar; Salehi, Masoud

2013-04-01

The aims of this study were to prepare a Persian version of the temporal resolution test using the method of Phillips et al (1994) and Stuart and Phillips (1996), and to compare the word-recognition performance in the presence of continuous and interrupted noise as well as the temporal resolution abilities between monolingual (ML) Persian and bilingual (BL) Turkish-Persian young adults. Word-recognition scores (WRSs) were obtained in quiet and in the presence of background competing continuous and interrupted noise at signal-to-noise ratios (SNRs) of -20, -10, 0, and 10 dB. Two groups of 33 ML Persian and 36 BL Turkish-Persian volunteers participated. WRSs significantly differed between ML and BL subjects at four sensation levels in the presence of continuous and interrupted noise. However, the difference in the release from masking between ML and BL subjects was not significant at the studied SNRs. BL Turkish-Persian listeners seem to show poorer performance when responding to Persian words in continuous and interrupted noise. However, bilingualism may not affect auditory temporal resolution ability.