Working Memory Network Task Reveals Brain Areas Involved in Goal-Directed Retention
DOI:
https://doi.org/10.17323/1813-8918-2026-3-454-466Keywords:
working memory, working memory network task, central executive, goal, source analysisAbstract
Working Memory (WM) provides temporary storage and processing of information to enable goal-directed behavior. According to the cognits framework, WM arises from the interaction of perceptual and executive neuronal ensembles, with the latest contributing to the maintenance and prioritization of goal-relevant information. In this study, we tested the hypothesis that explicit memorization goals would preferentially engage executive neural mechanisms during information retention. We used a Working Memory Network Task and conducted a source level analysis of oscillatory activity during the retention of the multimodal stimulus under conditions where there was explicit goal to memorize the stimulus and where no such goal was present. The data of twenty-nine healthy adults was used for the analysis. Source reconstruction was performed using Dynamic Imaging of Coherent Sources (DICS), and condition differences were assessed using cluster-based permutation statistics across theta (4–8 Hz), alpha (8–14 Hz), beta (14–30 Hz), and gamma (30–80 Hz) frequency bands. We found that goaldirected information retention is accompanied by increased theta activity in frontal cortical regions and beta activity in occipital regions. In contrast, retention without a goal was characterized by increased theta and alpha activity in parietal regions, as well as distributed beta activity in frontal and inferior parietal areas. These results confirm the distinction between executive and perceptual cognits predicted by the theoretical model.
References
Aben, B., Stapert, S., & Blokland, A. (2012). About the distinction between working memory and shortterm memory. Frontiers in Psychology, 3. Article 301. https://doi.org/10.3389/fpsyg.2012.00301
Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8, pp. 47–89. https://doi.org/10.1016/S0079-7421(08)60452-1
Bastos, A. M., Loonis, R., Kornblith, S., Lundqvist, M., & Miller, E. K. (2018). Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory. Proceedings of the National Academy of Sciences, 115(5), 1117–1122. https://doi.org/10.1073/pnas.1710323115
Braver, T. S., & Bongiolatti, S. R. (2002). The role of frontopolar cortex in subgoal processing during working memory. NeuroImage, 15(3), 523–536. https://doi.org/10.1006/nimg.2001.1019
Brookes, M. J., Vrba, J., Robinson, S. E., Stevenson, C. M., Peters, A. M., Barnes, G. R., Hillebrand, A., & Morris, P. G. (2008). Optimising experimental design for MEG beamformer imaging. NeuroImage, 39(4), 1788–1802. https://doi.org/10.1016/j.neuroimage.2007.09.050
Cavanagh, J. F., & Shackman, A. J. (2015). Frontal midline theta reflects anxiety and cognitive control: Meta-analytic evidence. Journal of Physiology-Paris, 109(1–3), 3–15. https://doi.org/10.1016/j.jphysparis.2014.04.003
Cecere, R., Rees, G., & Romei, V. (2015). Individual differences in alpha frequency drive crossmodal illusory perception. Current Biology, 25(2), 231–235. https://doi.org/10.1016/j.cub.2014.11.034
Chaumon, M., Puce, A., & George, N. (2021). Statistical power: Implications for planning MEG studies. NeuroImage, 233, Article 117894. https://doi.org/10.1016/j.neuroimage.2021.117894
Cooper, P. S., Wong, A. S. W., McKewen, M., Michie, P. T., & Karayanidis, F. (2017). Frontoparietal theta oscillations during proactive control are associated with goal-updating and reduced behavioral variability. Biological Psychology, 129, 253–264. https://doi.org/10.1016/j.biopsycho.2017.09.008
Cohen, M. X. (2019). A better way to define and describe Morlet wavelets for time-frequency analysis. NeuroImage, 199, 81–86. https://doi.org/10.1016/j.neuroimage.2019.05.048
Cowan, N. (2008). What are the differences between long-term, short-term, and working memory? In Progress in Brain Research (Vol. 169, pp. 323–338). Elsevier. https://doi.org/10.1016/S0079-6123(07)00020-9
Elekta Neuromag Oy. (2005). Elekta Neuromag system hardware technical manual (Rev. F). Elekta Neuromag Oy.
Fellrath, J., Mottaz, A., Schnider, A., Guggisberg, A. G., & Ptak, R. (2016). Theta-band functional connectivity in the dorsal fronto-parietal network predicts goal-directed attention. Neuropsychologia, 92, 20–30. https://doi.org/10.1016/j.neuropsychologia.2016.07.012
Fuster, J. M. (2006). The cognit: A network model of cortical representation. International Journal of Psychophysiology, 60(2), 125–132. https://doi.org/10.1016/j.ijpsycho.2005.12.015
Fuster, J. M., & Bressler, S. L. (2012). Cognit activation: A mechanism enabling temporal integration in working memory. Trends in Cognitive Sciences, 16(4), 207–218. https://doi.org/10.1016/j.tics.2012.03.005
Gelastopoulos, A., Whittington, M. A., & Kopell, N. J. (2019). Parietal low beta rhythm provides a dynamical substrate for a working memory buffer. Proceedings of the National Academy of Sciences, 116(33), 16613–16620. https://doi.org/10.1073/pnas.1902305116
Gross, J., Kujala, J., Hämäläinen, M., Timmermann, L., Schnitzler, A., & Salmelin, R. (2001). Dynamic imaging of coherent sources: Studying neural interactions in the human brain. Proceedings of the National Academy of Sciences, 98(2), 694–699. https://doi.org/10.1073/pnas.98.2.694
Gulbinaite, R., van Rijn, H., & Cohen, M. X. (2014). Fronto-parietal network oscillations reveal relationship between working memory capacity and cognitive control. Frontiers in Human Neuroscience, 8, Article 761. https://doi.org/10.3389/fnhum.2014.00761
Jones, K. T., Johnson, E. L., & Berryhill, M. E. (2020). Frontoparietal theta-gamma interactions track working memory enhancement with training and tDCS. NeuroImage, 211, Article 116615. https://doi.org/10.1016/j.neuroimage.2020.116615
Koechlin, E., & Summerfield, C. (2007). An information theoretical approach to prefrontal executive
function. Trends in Cognitive Sciences, 11(6), 229–235. https://doi.org/10.1016/j.tics.2007.04.005
Köster, M., Finger, H., Graetz, S., Kater, M., & Gruber, T. (2018). Theta-gamma coupling binds visual perceptual features in an associative memory task. Scientific Reports, 8(1), Article 17688. https://doi.org/10.1038/s41598-018-35812-7
Kottlow, M., Schlaepfer, A., Baenninger, A., Michels, L., Brandeis, D., & Koenig, T. (2015). Pre-stimulus BOLD-network activation modulates EEG spectral activity during working memory retention. Frontiers in Behavioral Neuroscience, 9, Article 111. https://doi.org/10.3389/fnbeh.2015.00111
Mantini, D., Franciotti, R., Romani, G. L., & Pizzella, V. (2008). Improving MEG source localizations: An automated method for complete artifact removal based on independent component analysis. NeuroImage, 40(1), 160–173. https://doi.org/10.1016/j.neuroimage.2007.11.022
Maris, E., & Oostenveld, R. (2007). Nonparametric statistical testing of EEG- and MEG-data. Journal of Neuroscience Methods, 164(1), 177–190. https://doi.org/10.1016/j.jneumeth.2007.03.024
Maurer, U., Brem, S., Liechti, M., Maurizio, S., Michels, L., & Brandeis, D. (2015). Frontal midline theta reflects individual task performance in a working memory task. Brain Topography, 28(1), 127–134. https://doi.org/10.1007/s10548-014-0361-y
Meltzer, J. A., Negishi, M., Mayes, L. C., & Constable, R. T. (2007). Individual differences in EEG theta and alpha dynamics during working memory correlate with fMRI responses across subjects. Clinical Neurophysiology, 118(11), 2419–2436. https://doi.org/10.1016/j.clinph.2007.07.023
Mening, S., Fedele, T., & Otstavnov, N. (2025). Working memory: MEG study of the oscillatory mechanisms for working memory components. 2025 Seventh International Conference Neurotechnologies and Neurointerfaces (CNN), 62–65. https://doi.org/10.1109/CNN67635.2025.11177471
Miller, E. K., Lundqvist, M., & Bastos, A. M. (2018). Working memory 2.0. Neuron, 100(2), 463–475. https://doi.org/10.1016/j.neuron.2018.09.023
Oberauer, K. (2002). Access to information in working memory: Exploring the focus of attention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28(3), 411–421. https://doi.org/10.1037/0278-7393.28.3.411
Oberauer, K. (2013). The focus of attention in working memory—from metaphors to mechanisms. Frontiers in Human Neuroscience, 7, Article 673. https://doi.org/10.3389/fnhum.2013.00673
Otstavnov, N., Voevodina, E., Mening, S., Urazaeva, R., & Fedele, T. (2024). New working memory paradigm for neuroimaging testing of visual and verbal modality under different attentional involvement. Psychology. Journal of the Higher School of Economics, 21(3), 456–471. https://doi.org/10.17323/1813-8918-2024-3-456-471 (in Russian)
Pavlov, Y. G., & Kotchoubey, B. (2017). EEG correlates of working memory performance in females. BMC Neuroscience, 18(1), Article 26. https://doi.org/10.1186/s12868-017-0344-5
Pavlov, Y. G., & Kotchoubey, B. (2022). Oscillatory brain activity and maintenance of verbal and visual working memory: A systematic review. Psychophysiology, 59(5), Article 13735. https://doi.org/10.1111/psyp.13735
Pitchford, B., & Arnell, K. M. (2019). Resting EEG in alpha and beta bands predicts individual differences in attentional breadth. Consciousness and Cognition, 75, Article 102803. https://doi.org/10.1016/j.concog.2019.102803
Ravizza, S. M., & Carter, C. S. (2008). Shifting set about task switching: Behavioral and neural evidence for distinct forms of cognitive flexibility. Neuropsychologia, 46(12), 2924–2935. https://doi.org/10.1016/j.neuropsychologia.2008.06.006
Riddle, J., Scimeca, J. M., Cellier, D., Dhanani, S., & D’Esposito, M. (2020). Causal evidence for a role of theta and alpha oscillations in the control of working memory. Current Biology, 30(9), 1748–1754.e4. https://doi.org/10.1016/j.cub.2020.02.065
Sauseng, P., Klimesch, W., Schabus, M., & Doppelmayr, M. (2005). Fronto-parietal EEG coherence in theta and upper alpha reflect central executive functions of working memory. International Journal of Psychophysiology, 57(2), 97–103. https://doi.org/10.1016/j.ijpsycho.2005.03.018
Taulu, S., & Kajola, M. (2005). Presentation of electromagnetic multichannel data: The signal space separation method. Journal of Applied Physics, 97(12), Article 124905. https://doi.org/10.1063/1.1935742
Toscani, M., Marzi, T., Righi, S., Viggiano, M. P., & Baldassi, S. (2010). Alpha waves: A neural signature of visual suppression. Experimental Brain Research, 207(3–4), 213–219. https://doi.org/10.1007/s00221-010-2444-7
Ursino, M., & Pirazzini, G. (2024). Theta–gamma coupling as a ubiquitous brain mechanism: Implications for memory, attention, dreaming, imagination, and consciousness. Current Opinion in Behavioral Sciences, 59, Article 101433. https://doi.org/10.1016/j.cobeha.2024.101433
Wendiggensen, P., Prochnow, A., Pscherer, C., Münchau, A., Frings, C., & Beste, C. (2023). Interplay between alpha and theta band activity enables management of perception-action representations for goal-directed behavior. Communications Biology, 6(1), Article 494. https://doi.org/10.1038/s42003-023-04878-z
