Event related potentials during object recognition tasks

Zhang, Xiao Lei; Begleiter, Henri; Porjesz, Bernice; Wang, Wenyu; Litke, Ann

doi:10.1016/0361-9230(95)02023-5

Cited by 244 publications

(147 citation statements)

References 43 publications

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“…First, our delayed matching-to-sample task required participants to hold an object in memory while responding to several test objects. To our knowledge, prior studies that used a matching task only required one comparison to each object held in mind (e.g., Talsma et al, 2001;Zhang et al, 1995). This within trial difference could account for discrepancies between past studies and the present findings, since our task required the object to be held in mind longer and allowed for within-trial interference, neither of which have been adequately studied in relation to old-new effects.…”

Section: Discussioncontrasting

confidence: 61%

“…Psychophysiological studies have localized several neural structures critical to WM including the prefrontal cortex implicated in coordination processes characteristic of the central executive (D'Esposito, 2001;Goldman-Rakic, 1996;Petrides, 1994;Postle 2006;Ranganath 2006;Wagner, 1999), posterior parietal cortex which participates in phonological coding and storage (Awh et al, 1996;Jonides et al, 1998;Postle & D'Esposito, 1999), thalamo-cortical activity which is implicated in allocating attentional resources towards a specific cortical region (Birbaumer, 1990;LaBerge, 1997), inferior temporal (IT) cortex that is involved in comparing current visual images with internal representations (Miller & Desimone, 1994;Vogels & Orban, 1994;Zhang et al, 1995), and the premotor areas that are Correspondence should be addressed to: Yang Jiang (yjiang@uky.edu), Department of Behavioral Science College of Medicine, University of Kentucky, Lexington, KY 40536-0086; Tel: 859-2572122, Fax: 859-3235350, or …”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Brain potentials distinguish new and studied objects during working memory

Guo

Lawson

Zhang

et al. 2007

Human Brain Mapping

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We investigated brain responses to matching versus nonmatching objects in working memory with a modified delayed match-to-sample task using event-related potentials (ERPs). In addition, ERP correlates of new items (new matches/new nonmatches) and previously studied items (studied matches/studied nonmatches) were examined in the working memory task. Half of the common visual objects were initially studied until 95% accuracy was attained and half were new. Each memory trial began with the presentation of a sample object followed by nine test objects. Participants indicated whether each test item was the same as the object held in mind (i.e., match) or a nonmatch. Compared to studied matches, new matches evoked activity that was 50 msec earlier and largest at frontal sites. In contrast, P3 activity associated with studied nonmatches was larger than for new nonmatches at mostly posterior sites, which parallels previously reported oldnew ERP effects. The ERP source analysis further confirms that the cortical mechanisms underlying matching objects and rejecting irrelevant objects during the task are both temporally and spatially distinct. Moreover, our current findings suggest that prior learning affects brain responses to matching visual items during a working memory task. KeywordsERPs; visual memory; matching; delayed match-to-sample; stimulus evaluation; common objects; LORETA Intentionally holding an item in mind for current use is an important function of working memory (WM), an active, short-term memory mechanism (Baddeley, 1986;Baddeley & Hitch, 1974). Psychophysiological studies have localized several neural structures critical to WM including the prefrontal cortex implicated in coordination processes characteristic of the central executive (D'Esposito, 2001;Goldman-Rakic, 1996;Petrides, 1994;Postle 2006;Ranganath 2006;Wagner, 1999), posterior parietal cortex which participates in phonological coding and storage (Awh et al., 1996;Jonides et al., 1998;Postle & D'Esposito, 1999), thalamo-cortical activity which is implicated in allocating attentional resources towards a specific cortical region (Birbaumer, 1990;LaBerge, 1997), inferior temporal (IT) cortex that is involved in comparing current visual images with internal representations (Miller & Desimone, 1994;Vogels & Orban, 1994;Zhang et al., 1995), and the premotor areas that are Correspondence should be addressed to: Yang Jiang (yjiang@uky.edu), Department of Behavioral Science College of Medicine, University of Kentucky, Lexington, KY 40536-0086; Tel: 859-2572122, Fax: 859-3235350, or NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript involved in the preparation of motor responses based on information held in mind (Petit et al., 1998).Many psychophysiological studies of working memory in primates and humans have used delayed match-to-sample tasks (Levy & Goldman-Rakic, 2000; Bichot, Rossi, & Desimone, 2005;Desimone 1996;Jiang et al., 2000). Typically, a sample item is presented at the beginning of the trial and after a de...

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Section: Discussioncontrasting

confidence: 61%

Section: Introductionmentioning

confidence: 99%

Brain potentials distinguish new and studied objects during working memory

Guo

Lawson

Zhang

et al. 2007

Human Brain Mapping

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“…In order to evaluate our approach, we used the publicly available EEG dataset 4 from the UCI machine learning repository [28]. This collection contains in total 11028 EEG signals recorded from 122 persons.…”

Section: Datamentioning

confidence: 99%

“…Therefore, each EEG signal is a 64-dimensional time series of length 256 in this collection. For more information about data collection and selection of patients we refer to [28]. In order to filter noise, as a simple preprocessing step, we reduced the length of the signals from 256 to 64 by binning with a window size of four, i.e., we averaged four consecutive values of the signal.…”

Section: Datamentioning

confidence: 99%

PROCESS: Projection-Based Classification of Electroencephalograph Signals

Búza

Koller

Marussy

2015

Artificial Intelligence and Soft Computing

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Abstract. Classification of electroencephalograph (EEG) signals is the common denominator in EEG-based recognition systems that are relevant to many applications ranging from medical diagnosis to EEGcontrolled devices such as web browsers or typing tools for paralyzed patients. Here, we propose a new method for the classification of EEG signals. One of its core components projects EEG signals into a vector space. We demonstrate that this projection may allow visual inspection and therefore exploratory analysis of large EEG datasets. Subsequently, we use logistic regression with our novel vector representation in order to classify EEG signals. Our experiments on a large, publicly available real-world dataset containing 11028 EEG signals show that our approach is robust and accurate, i.e., it outperforms state-of-the-art classifiers in various classification tasks, such as classification according to disease or stimulus. Furthermore, we point out that our approach requires only the calculation of a few DTW distances, therefore, our approach is fast compared to other DTW-based classifiers.

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“…For gesture recognition and video sequence matching using computer vision, several features are extracted from each image continuously, which renders them MTSs [6,1,28]. In medicine, Electro Encephalogram (EEG) from 64 electrodes placed on the scalp are measured to examine the correlation of genetic predisposition to alcoholism [36]. Functional Magnetic Resonance Imaging (fMRI) from 696 voxels out of 4391 has been used to detect similarities in activation between voxels in [13].…”

Section: Introductionmentioning

confidence: 99%