I.P. Pavlov Journal of Higher Nervous ActivityI.P. Pavlov Journal of Higher Nervous ActivityЖурнал высшей нервной деятельности им. И.П. Павлова0044-46773034-5316The Russian Academy of Sciences69256610.31857/S0044467725050064ФИЗИОЛОГИЯ ВЫСШЕЙ НЕРВНОЙ (КОГНИТИВНОЙ) ДЕЯТЕЛЬНОСТИ ЧЕЛОВЕКАФИЗИОЛОГИЯ ВЫСШЕЙ НЕРВНОЙ (КОГНИТИВНОЙ) ДЕЯТЕЛЬНОСТИ ЧЕЛОВЕКАResearch ArticleCategorization and Attentional Templates in Working Memory: An Event-Related Potential (ERP) StudyКатегоризация и внутренние шаблоны в рабочей памяти: исследование с помощью электрической активности мероприятий (ERP)KlimenkovN. V.КлименковН. В.gorbunovaes@gmail.comKovalenkoS. D.КоваленкоС. Д.gorbunovaes@gmail.comGorbunovaE. S.ГорбуноваЕ. С.gorbunovaes@gmail.comLaboratory for Cognitive Psychology of Digital Interfaces User, HSE University, Moscow, RussiaЛаборатория когнитивной психологии пользователя цифровых интерфейсов, НИУ ВШЭ, Москва, Россия15102025755VOL 75, NO5 (2025)ТОМ 75, №5 (2025)57258508102025Copyright ©; 2025, Russian Academy of SciencesCopyright ©; 2025, Российская академия наук2025Russian Academy of SciencesРоссийская академия наукhttps://innoscience.ru/0044-4677/article/view/692566

This study is devoted to the investigation of neural correlates of attentional template formation in categorical search. The categorization process plays a crucial role in optimizing information processing and storage in working memory. Categories are divided into subordinate, basic and superordinate levels, which determine the degree of specificity and clarity of representation. Attentional templates contain attributes that define the target, such as color, shape, or size, and are activated in preparation for retrieval. The aim of the study was to examine the difference in the neurophysiological mechanisms of attentional template formation under the influence of verbally given categories of basic and superordinate levels. The category level (basic or superordinate) was manipulated, possible changes in N2pc (N2-posterior-contralateral component) and CDA (contralateral delay activity) amplitudes were recorded as well as behavioral measures. Behavioral results were consistent with other studies of visual search and categorization. The CDA component related to visual working memory load showed no statistically significant differences, whereas the N2pc component showed classic results for visual search paradigm – it changed with lateralization and with the number of stimuli, but no effect of category level was revealed. This study showed that there are differences at the behavioral level in a categorical visual search task, but they are absent for the CDA and N2pc components amplitudes – the effect may be manifested in oscillations; a block design is probably not suitable for assessing changes in CDA amplitude, verbal presentation of categories does not lead to differences in amplitude.

Данное исследование посвящено изучению нейронных коррелятов формирования шаблонов внимания при категориальном поиске. Процесс категоризации играет ключевую роль в оптимизации обработки и хранения информации в рабочей памяти. Категории подразделяются на субординатные, базовые и суперординатные уровни, которые определяют степень специфичности и четкости представления. Шаблоны внимания содержат атрибуты, определяющие цель, такие как цвет, форма или размер, и активируются при подготовке к извлечению. Целью исследования было изучение различий в нейрофизиологических механизмах формирования шаблонов внимания под воздействием вербально заданных категорий базового и суперординатного уровней. Уровень категории (базовый или суперординатный) варьировался, регистрировались возможные изменения амплитуд N2pc (N2-задне-контралатеральный компонент) и CDA (контралатеральная задержка активности), а также поведенческие показатели. Поведенческие результаты согласуются с результатами других исследований зрительного поиска и категоризации. Компонент CDA, связанный с нагрузкой на зрительную рабочую память, не показал статистически значимых различий, тогда как компонент N2pc продемонстрировал классические результаты для парадигмы зрительного поиска – он менялся в зависимости от латерализации и количества стимулов, однако не был выявлен эффект уровня категории. Данное исследование показало, что на поведенческом уровне в задаче категориального зрительного поиска существуют различия, но они отсутствуют для амплитуд компонентов CDA и N2pc – эффект может проявляться в изменении осцилляций; блочный дизайн, вероятно, не подходит для оценки изменений амплитуды CDA, вербальное предъявление категорий не приводит к различиям в амплитуде.

categorizationN2pcCDAguidanceERPvisual searchattentional templateкатегоризацияN2pcCDAгайденсвызванные потенциалызрительный поискшаблон вниманияThis work was supported by RSCF grant № 20-78-10055-P.Psihologiya. Zhurnal Vysshej Shkoly Ekonomiki. 2024. 21 (4): 634–654.Asp I.E., Störmer V.S., Brady T.F. Greater Visual Working Memory Capacity for Visually Matched Stimuli When They Are Perceived as Meaningful. Journal of Cognitive Neuroscience. 2021. 33 (5): 902–918.Bae G.-Y. Neural evidence for categorical biases in location and orientation representations in a working memory task. NeuroImage. 2021. 240: 118366.Beck A.-K., Czernochowski D., Lachmann T., Berti S. Do categorical representations modulate early perceptual or later cognitive visual processing? An ERP study. Brain and Cognition. 2021. 150: 105724.Berggren N., Eimer M. Does Contralateral Delay Activity Reflect Working Memory Storage or the Current Focus of Spatial Attention within Visual Working Memory? Journal of Cognitive Neuroscience. 2016. 28 (12): 2003–2020.Brady T.F., Robinson M.M., Williams J.R., Wixted J.T. Measuring memory is harder than you think: How to avoid problematic measurement practices in memory research. Psychonomic Bulletin, Review. 2023. 30 (2): 421–449.Brady T.F., Störmer V.S., Alvarez G.A. Working memory is not fixed-capacity: More active storage capacity for real-world objects than for simple stimuli. Proceedings of the National Academy of Sciences. 2016. 113 (27): 7459–7464.Carlei C., Kerzel D. Stronger interference from distractors in the right hemifield during visual search. Laterality: Asymmetries of Body, Brain and Cognition. 2018. 23 (2): 152–165.Chow J.K., Palmeri T.J., Mack M.L. Revealing a competitive dynamic in rapid categorization with object substitution masking. Attention, Perception, Psychophysics. 2022. 84 (3): 638–646.Corbett J.E., Munneke J. Statistical stability and set size exert distinct influences on visual search. Attention, Perception, Psychophysics. 2020. 82 (2): 832–839.Corbetta M., Miezin F., Shulman G., Petersen S. A PET study of visuospatial attention. The Journal of Neuroscience. 1993. 13 (3): 1202–1226.De Schotten M.T., Dell’Acqua F., Forkel S.J., Simmons A., Vergani F., Murphy D.G.M., Catani M. A lateralized brain network for visuospatial attention. Nature Neuroscience. 2011. 14 (10): 1245–1246.Emrich S.M., Al-Aidroos N., Pratt J., Ferber S. Visual Search Elicits the Electrophysiological Marker of Visual Working Memory. PLoS ONE. 2009. 4 (11): e8042.Evans K.K., Horowitz T.S., Howe P., Pedersini R., Reijnen E., Pinto Y. et al. Visual attention. WIREs Cognitive Science. 2011. 2 (5): 503–514.Geng J.J., DiQuattro N.E., Helm J. Distractor probability changes the shape of the attentional template. Journal of Experimental Psychology: Human Perception and Performance. 2017. 43 (12): 1993–2007.Gunseli E., Olivers C.N.L., Meeter M. Effects of Search Difficulty on the Selection, Maintenance, and Learning of Attentional Templates. Journal of Cognitive Neuroscience. 2014. 26 (9): 2042–2054.Heilman K.M., Abell T.V.D. Right hemisphere dominance for attention: The mechanism underlying hemispheric asymmetries of inattention (neglect). Neurology. 1980. 30 (3): 327–327.Itthipuripat S., Sprague T.C., Serences J.T. Functional MRI and EEG Index Complementary Attentional Modulations. The Journal of Neuroscience. 2019. 39 (31): 6162–6179.Jacob G., Arun S. Visual search asymmetries are explained by visual homogeneity. Journal of Vision. 2022. 22 (14): 4110.James W. The principles of psychology, Vol. I. Henry Holt and Co. 1890.Kermani M., Verghese A., Vidyasagar T.R. Attentional asymmetry between visual hemifields is related to habitual direction of reading and its implications for debate on cause and effects of dyslexia. Dyslexia. 2018. 24 (1): 33–43.Kerzel D., Huynh Cong S. Attentional guidance by irrelevant features depends on their successful encoding into working memory. Journal of Experimental Psychology: Human Perception and Performance. 2021. 47 (9): 1182–1191.Luck S.J., Ford M.A. On the role of selective attention in visual perception. Proceedings of the National Academy of Sciences. 1998. 95 (3): 825–830.Machizawa M., Goh C., Driver J., Husain M. Hemispheric differences in visual working memory maintenance indexed by contralateral delay activity. Journal of Vision. 2012. 12 (9): 180–180.Mangun G.R., Luck S.J., Plager R., Loftus W., Hillyard S.A., Handy T. et al. Monitoring the Visual World: Hemispheric Asymmetries and Subcortical Processes in Attention. Journal of Cognitive Neuroscience. 1994. 6 (3): 267–275.Maxfield J.T., Stalder W.D., Zelinsky G.J. Effects of target typicality on categorical search. Journal of Vision. 2014. 14 (12): 1–1.Maxfield J.T., Zelinsky G.J. Searching through the hierarchy: How level of target categorization affects visual search. Visual Cognition. 2012. 20 (10): 1153–1163.Merkel C., Bartsch M.V., Schoenfeld M.A., Vellage A.-K., Müller N.G., Hopf J.-M. A direct neural measure of variable precision representations in visual working memory. Journal of Neurophysiology. 2021. 126 (4): 1430–1439.Moon A., He C., Ditta A.S., Cheung O.S., Wu R. Rapid category selectivity for animals versus man-made objects: An N2pc study. International Journal of Psychophysiology. 2022. 171: 20–28.Nako R., Wu R., Eimer M. Rapid guidance of visual search by object categories. Journal of Experimental Psychology: Human Perception and Performance. 2014. 40 (1): 50–60.Olivers C.N.L., Peters J., Houtkamp R., Roelfsema P.R. Different states in visual working memory: When it guides attention and when it does not. Trends in Cognitive Sciences. 2011. S1364661311000854.Palmer J., Davis E. Visual search and attention: An overview. Spatial Vision. 2004. 17 (4): 249–255.Quirk C., Adam K.C.S., Vogel E.K. No Evidence for an Object Working Memory Capacity Benefit with Extended Viewing Time. Eneuro. 2020. 7 (5): ENEURO.0150–20.2020.Reijnen E., Hoffmann J., Wolfe J. The role of working memory capacity in visual search and search of visual short term memory. Journal of Vision. 2014. 14 (10): 1073–1073.Reinhart R.M.G., Carlisle N.B., Woodman G.F. Visual working memory gives up attentional control early in learning: Ruling out interhemispheric cancellation. Psychophysiology. 2014. 51 (8): 800–804.Robbins A., Hout M.C. Scene priming provides clues about target appearance that improve attentional guidance during categorical search. Journal of Experimental Psychology: Human Perception and Performance. 2020. 46 (2): 220–230.Rosario Rueda M., Pozuelos J., Cómbita L. Cognitive Neuroscience of Attention from brain mechanisms to individual differences in efficiency. AIMS Neuroscience. 2015. 2 (4): 183–202.Roy Y., Faubert J. Is the Contralateral Delay Activity (CDA) a robust neural correlate for Visual Working Memory (VWM) tasks? A reproducibility study. Psychophysiology. 2023. 60 (2): e14180.Serences J. EEG and fMRI provide different insights into the link between attention and behavior in human visual cortex. Journal of Vision. 2015. 15 (12): 1413.Shulman G.L., Pope D.L.W., Astafiev S.V., McAvoy M.P., Snyder A.Z., Corbetta M. Right Hemisphere Dominance during Spatial Selective Attention and Target Detection Occurs Outside the Dorsal Frontoparietal Network. The Journal of Neuroscience. 2010. 30 (10): 3640–3651.Summerfield C., Egner T. Feature-Based Attention and Feature-Based Expectation. Trends in Cognitive Sciences. 2016. 20 (6): 401–404.Taniguchi K., Kuraguchi K., Takano Y., Itakura S. Object Categorization Processing Differs According to Category Level: Comparing Visual Information Between the Basic and Superordinate Levels. Frontiers in Psychology. 2020. 11: 501.Thibeault A.M.L., Stojanoski B., Emrich S.M. Investigating the effects of perceptual complexity versus conceptual meaning on the object benefit in visual working memory. Cognitive, Affective, Behavioral Neuroscience. 2024. 24 (3): 453–468.Tsotsos J., Rothenstein A. Computational models of visual attention. Scholarpedia. 2011. 6 (1): 6201.Ueda Y., Kurosu S., Saiki J. Intensity of Visual Search Asymmetry Depends on Physical Property in Target-Present Trials and Search Type in Target-Absent Trials. Journal of Vision. 2015. 15 (12): 1368.Unsworth N., Fukuda K., Awh E., Vogel E.K. Working memory delay activity predicts individual differences in cognitive abilities. Journal of Cognitive Neuroscience. 2015. 27 (5): 853–865.Verleger R., Śmigasiewicz K. Consciousness wanted, attention found: Reasons for the advantage of the left visual field in identifying T2 among rapidly presented series. Consciousness and Cognition. 2015. 35: 260–273.Walz J.M., Goldman R.I., Carapezza M., Muraskin J., Brown T.R., Sajda P. Simultaneous EEG–fMRI reveals a temporal cascade of task-related and default-mode activations during a simple target detection task. NeuroImage. 2014. 102: 229–239.Wang Y., Luo Z., Zhao S., Xie L., Xu M., Ming D., Yin E. Spatial localization in target detection based on decoding N2pc component. Journal of Neuroscience Methods. 2022. 369: 109440.Whitehead R. Right Hemisphere Processing Superiority During Sustained Visual Attention. Journal of Cognitive Neuroscience. 1991. 3 (4): 329–334.Wilschut A., Theeuwes J., Olivers C.N.L. Priming and the guidance by visual and categorical templates in visual search. Frontiers in Psychology. 2014: 5.Wojciulik E., Kanwisher N. The Generality of Parietal Involvement in Visual Attention. Neuron. 1999. 23(4): 747–764.Woodman G.F., Arita J.T. Direct Electrophysiological Measurement of Attentional Templates in Visual Working Memory. Psychological Science. 2011. 22 (2): 212–215.Woodman G.F., Luck S.J. Electrophysiological measurement of rapid shifts of attention during visual search. Nature. 1999. 400 (6747): 867–869.Wu R., Pruitt Z., Runkle M., Scerif G., Aslin R.N. A neural signature of rapid category-based target selection as a function of intra-item perceptual similarity, despite inter-item dissimilarity. Attention, Perception, Psychophysics. 2016. 78 (3): 749–760.Wu R., Scerif G., Aslin R.N., Smith T.J., Nako R., Eimer M. Searching for Something Familiar or Novel: Top–Down Attentional Selection of Specific Items or Object Categories. Journal of Cognitive Neuroscience. 2013. 25 (5): 719–729.Yu C.-P., Maxfield J.T., Zelinsky G.J. Searching for Category-Consistent Features: A Computational Approach to Understanding Visual Category Representation. Psychological Science. 2016. 27 (6): 870–884.Zelinsky G.J., Chen Y., Ahn S., Adeli H. Changing perspectives on goal-directed attention control: The past, present, and future of modeling fixations during visual search. In Psychology of Learning and Motivation. Elsevier. 2020. 73: 231–286.Zhou C., Lorist M.M., Mathôt S. Categorical bias as a crucial parameter in visual working memory: The effect of memory load and retention interval. Cortex. 2022. 154: 311–321.