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Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions

Nature Human Behaviour volume 8, pages 758–770 (2024)Cite this article

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Abstract

Neural representations of perceptual decision formation that are abstracted from specific motor requirements have previously been identified in humans using non-invasive electrophysiology; however, it is currently unclear where these originate in the brain. Here we capitalized on the high spatiotemporal precision of intracranial EEG to localize such abstract decision signals. Participants undergoing invasive electrophysiological monitoring for epilepsy were asked to judge the direction of random-dot stimuli and respond either with a speeded button press (N = 24), or vocally, after a randomized delay (N = 12). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual buildup that was modulated by the strength of the sensory evidence, and an amplitude that predicted participants’ choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision-making.

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Fig. 1: Experimental approach.
Fig. 2: Overview of coverage and signal profiles for task-responsive contacts.
Fig. 3: Mapping signal profiles of interest.
Fig. 4: Relationship of HFA with decision-related behaviour.
Fig. 5: Validating effector independence at ‘abstract’ candidate sites.

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Data availability

Data have been made available on OSF at https://osf.io/9bzx8/?view_only=ed6f1eba830840cb9921458490b3c362.

Code availability

Code has been made available on OSF at https://osf.io/9bzx8/?view_only=ed6f1eba830840cb9921458490b3c362.

References

  1. Hanes, D. P. & Schall, J. D. Neural control of voluntary movement initiation. Science 274, 427–430 (1996).

    CAS  PubMed  Google Scholar 

  2. Kim, J. N. & Shadlen, M. N. Neural correlates of a decision in the dorsolateral prefrontal cortex of the macaque. Nat. Neurosci. 2, 176–185 (1999).

    PubMed  Google Scholar 

  3. Shadlen, M. N. & Newsome, W. T. Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J. Neurophysiol. 86, 1916–1936 (2001).

    CAS  PubMed  Google Scholar 

  4. Ding, L. & Gold, J. I. Caudate encodes multiple computations for perceptual decisions. J. Neurosci. 30, 15747–15759 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Gold, J. I. & Shadlen, M. N. The neural basis of decision making. Annu. Rev. Neurosci. 30, 535–574 (2007).

    CAS  PubMed  Google Scholar 

  6. de Lafuente, V., Jazayeri, M. & Shadlen, M. N. Representation of accumulating evidence for a decision in two parietal areas. J. Neurosci. 35, 4306–4318 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Freedman, D. J. & Assad, J. A. Experience-dependent representation of visual categories in parietal cortex. Nature 443, 85–88 (2006).

    CAS  PubMed  Google Scholar 

  8. Bennur, S. & Gold, J. I. Distinct representations of a perceptual decision and the associated oculomotor plan in the monkey lateral intraparietal area. J. Neurosci. 31, 913–921 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Zhou, Y. & Freedman, D. J. Posterior parietal cortex plays a causal role in perceptual and categorical decisions. Science 365, 180–185 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Zhou, Y. et al. Distributed functions of prefrontal and parietal cortices during sequential categorical decisions. eLife 10, e58782 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Horwitz, G. D., Batista, A. P. & Newsome, W. T. Representation of an abstract perceptual decision in macaque superior colliculus. J. Neurophysiol. 91, 2281–2296 (2004).

    PubMed  Google Scholar 

  12. Heekeren, H. R., Marrett, S., Ruff, D. A., Bandettini, P. A. & Ungerleider, L. G. Involvement of human left dorsolateral prefrontal cortex in perceptual decision making is independent of response modality. Proc. Natl Acad. Sci. USA 103, 10023–10028 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Ho, T. C., Brown, S. & Serences, J. T. Domain general mechanisms of perceptual decision making in human cortex. J. Neurosci. 29, 8675–8687 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Liu, T. & Pleskac, T. J. Neural correlates of evidence accumulation in a perceptual decision task. J. Neurophysiol. 106, 2383–2398 (2011).

    PubMed  Google Scholar 

  15. Hebart, M. N., Donner, T. H. & Haynes, J.-D. Human visual and parietal cortex encode visual choices independent of motor plans. NeuroImage 63, 1393–1403 (2012).

    PubMed  Google Scholar 

  16. Morito, Y. & Murata, T. Accumulation system: distributed neural substrates of perceptual decision making revealed by fMRI deconvolution. J. Neurosci. 42, 4891–4912 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Sandhaeger, F., Omejc, N., Pape, A.-A. & Siegel, M. Abstract perceptual choice signals during action-linked decisions in the human brain. PLoS Biol. 21, e3002324 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Wilming, N., Murphy, P. R., Meyniel, F. & Donner, T. H. Large-scale dynamics of perceptual decision information across human cortex. Nat. Commun. 11, 5109 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Peters, M. A. K. et al. Perceptual confidence neglects decision-incongruent evidence in the brain. Nat. Hum. Behav. 1, 0139 (2017).

    PubMed  PubMed Central  Google Scholar 

  20. Philiastides, M. G. & Sajda, P. Temporal characterization of the neural correlates of perceptual decision making in the human brain. Cereb. Cortex 16, 509–518 (2006).

    PubMed  Google Scholar 

  21. Diaz, J. A., Queirazza, F. & Philiastides, M. G. Perceptual learning alters post-sensory processing in human decision-making. Nat. Hum. Behav. 1, 0035 (2017).

    Google Scholar 

  22. Meister, M. L. R., Hennig, J. A. & Huk, A. C. Signal multiplexing and single-neuron computations in lateral intraparietal area during decision-making. J. Neurosci. 33, 2254–2267 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. O’Connell, R. G., Dockree, P. M. & Kelly, S. P. A supramodal accumulation-to-bound signal that determines perceptual decisions in humans. Nat. Neurosci. 15, 1729–1735 (2012).

    PubMed  Google Scholar 

  24. Kelly, S. P. & O’Connell, R. G. Internal and external influences on the rate of sensory evidence accumulation in the human brain. J. Neurosci. 33, 19434–19441 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Philiastides, M. G., Heekeren, H. R. & Sajda, P. Human scalp potentials reflect a mixture of decision-related signals during perceptual choices. J. Neurosci. 34, 16877–16889 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. O’Connell, R. G. & Kelly, S. P. Neurophysiology of human perceptual decision-making. Annu. Rev. Neurosci. 44, 495–516 (2021).

    PubMed  Google Scholar 

  27. Kelly, S. P., Corbett, E. A. & O’Connell, R. G. Neurocomputational mechanisms of prior-informed perceptual decision-making in humans. Nat. Hum. Behav. 5, 467–481 (2021).

    PubMed  Google Scholar 

  28. Loughnane, G. M. et al. Target selection signals influence perceptual decisions by modulating the onset and rate of evidence accumulation. Curr. Biol. 26, 496–502 (2016).

    CAS  PubMed  Google Scholar 

  29. Twomey, D. M., Kelly, S. P. & O’Connell, R. G. Abstract and effector-selective decision signals exhibit qualitatively distinct dynamics before delayed perceptual reports. J. Neurosci. 36, 7346–7352 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Steinemann, N. A., O’Connell, R. G. & Kelly, S. P. Decisions are expedited through multiple neural adjustments spanning the sensorimotor hierarchy. Nat. Commun. 9, 3627 (2018).

    PubMed  PubMed Central  Google Scholar 

  31. Parvizi, J. & Kastner, S. Promises and limitations of human intracranial electroencephalography. Nat. Neurosci. 21, 474–483 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Nunez, M. D., Gosai, A., Vandekerckhove, J. & Srinivasan, R. The latency of a visual evoked potential tracks the onset of decision making. NeuroImage 197, 93–108 (2019).

    PubMed  Google Scholar 

  33. Britten, K. H., Shadlen, M. N., Newsome, W. T. & Movshon, J. A. Responses of neurons in macaque MT to stochastic motion signals. Vis. Neurosci. 10, 1157–1169 (1993).

    CAS  PubMed  Google Scholar 

  34. Twomey, D. M., Murphy, P. R., Kelly, S. P. & O’Connell, R. G. The classic P300 encodes a build-to-threshold decision variable. Eur. J. Neurosci. 42, 1636–1643 (2015).

    PubMed  Google Scholar 

  35. Yeo, B. T. T. et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol. 106, 1125–1165 (2011).

    PubMed  Google Scholar 

  36. Fox, M. D., Corbetta, M., Snyder, A. Z., Vincent, J. L. & Raichle, M. E. Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proc. Natl Acad. Sci. USA 103, 10046–10051 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Seeley, W. W. et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci. 27, 2349–2356 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Devine, C. A., Gaffney, C., Loughnane, G. M., Kelly, S. P. & O’Connell, R. G. The role of premature evidence accumulation in making difficult perceptual decisions under temporal uncertainty. eLife 8, e48526 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Sandhaeger, F., Omejc, N., Pape, A.-A. & Siegel, M. Abstract perceptual choice signals during action-linked decisions in the human brain. PLOS Biol. 21, e3002324 (2023).

  40. Tremel, J. J. & Wheeler, M. E. Content-specific evidence accumulation in inferior temporal cortex during perceptual decision-making. NeuroImage 109, 35–49 (2015).

    PubMed  Google Scholar 

  41. Pereira, M. et al. Evidence accumulation relates to perceptual consciousness and monitoring. Nat. Commun. 12, 3261 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Polanía, R., Krajbich, I., Grueschow, M. & Ruff, C. C. Neural oscillations and synchronization differentially support evidence accumulation in perceptual and value-based decision making. Neuron 82, 709–720 (2014).

    PubMed  Google Scholar 

  43. Buzsáki, G., Anastassiou, C. A. & Koch, C. The origin of extracellular fields and currents–EEG, ECoG, LFP and spikes. Nat. Rev. Neurosci. 13, 407–420 (2012).

    PubMed  PubMed Central  Google Scholar 

  44. Leszczyński, M. et al. Dissociation of broadband high-frequency activity and neuronal firing in the neocortex. Sci. Adv. 6, eabb0977 (2020).

    PubMed  PubMed Central  Google Scholar 

  45. Ray, S., Crone, N. E., Niebur, E., Franaszczuk, P. J. & Hsiao, S. S. Neural correlates of high-gamma oscillations (60–200 Hz) in macaque local field potentials and their potential implications in electrocorticography. J. Neurosci. 28, 11526–11536 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Roitman, J. D. & Shadlen, M. N. Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. J. Neurosci. 22, 9475–9489 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Hanks, T., Kiani, R. & Shadlen, M. N. A neural mechanism of speed–accuracy tradeoff in macaque area LIP. eLife 3, e02260 (2014).

    PubMed  PubMed Central  Google Scholar 

  48. Murphy, P. R., Boonstra, E. & Nieuwenhuis, S. Global gain modulation generates time-dependent urgency during perceptual choice in humans. Nat. Commun. 7, 13526 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Thura, D. & Cisek, P. Modulation of premotor and primary motor cortical activity during volitional adjustments of speed–accuracy trade-offs. J. Neurosci. 36, 938–956 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Donner, T. H., Siegel, M., Fries, P. & Engel, A. K. Buildup of choice-predictive activity in human motor cortex during perceptual decision making. Curr. Biol. 19, 1581–1585 (2009).

    CAS  PubMed  Google Scholar 

  51. Selimbeyoglu, A. & Parvizi, J. Electrical stimulation of the human brain: perceptual and behavioral phenomena reported in the old and new literature. Front. Hum. Neurosci. 4, 46 (2010).

    PubMed  PubMed Central  Google Scholar 

  52. Ding, L. & Gold, J. I. The basal ganglia’s contributions to perceptual decision-making. Neuron 79, 640–649 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Yartsev, M. M., Hanks, T. D., Yoon, A. M. & Brody, C. D. Causal contribution and dynamical encoding in the striatum during evidence accumulation. eLife 7, e34929 (2018).

    PubMed  PubMed Central  Google Scholar 

  54. Groppe, D. M. et al. iELVis: an open source MATLAB toolbox for localizing and visualizing human intracranial electrode data. J. Neurosci. Methods 281, 40–48 (2017).

    CAS  PubMed  Google Scholar 

  55. Smith, S. M. Fast robust automated brain extraction. Hum. Brain Mapp. 17, 143–155 (2002).

    PubMed  PubMed Central  Google Scholar 

  56. Jenkinson, M. & Smith, S. A global optimisation method for robust affine registration of brain images. Med. Image Anal. 5, 143–156 (2001).

    CAS  PubMed  Google Scholar 

  57. Jenkinson, M., Bannister, P., Brady, M. & Smith, S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 17, 825–841 (2002).

    PubMed  Google Scholar 

  58. Papademetris, X. et al. BioImage Suite: an integrated medical image analysis suite: an update. Insight J. 2006, 209 (2006).

    PubMed  PubMed Central  Google Scholar 

  59. Fischl, B. FreeSurfer. NeuroImage 62, 774–781 (2012).

    PubMed  Google Scholar 

  60. Mercier, M. R. et al. Evaluation of cortical local field potential diffusion in stereotactic electro-encephalography recordings: a glimpse on white matter signal. NeuroImage 147, 219–232 (2017).

    PubMed  Google Scholar 

  61. Shadlen, M. N. & Kiani, R. Decision making as a window on cognition. Neuron 80, 791–806 (2013).

    CAS  PubMed  Google Scholar 

  62. Aarts, E., Verhage, M., Veenvliet, J. V., Dolan, C. V. & van der Sluis, S. A solution to dependency: using multilevel analysis to accommodate nested data. Nat. Neurosci. 17, 491–496 (2014).

    CAS  PubMed  Google Scholar 

  63. Desikan, R. S. et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31, 968–980 (2006).

    PubMed  Google Scholar 

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Acknowledgements

This work was funded by an NIH research grant to S.B., R.G.O’C. and S.P.K. (R01MH122513). We thank the neurology, neurosurgery and technician teams at North Shore University and Lenox Hill hospitals for support throughout the conduct of the study, and the patients who kindly volunteered their time to participate in the research. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA

    Sabina Gherman, Noah Markowitz, Gelana Tostaeva, Elizabeth Espinal, Ashesh D. Mehta & Stephan Bickel

  2. Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, USA

    Elizabeth Espinal

  3. Departments of Neurology and Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA

    Ashesh D. Mehta & Stephan Bickel

  4. Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland

    Redmond G. O’Connell

  5. School of Psychology, Trinity College Dublin, Dublin, Ireland

    Redmond G. O’Connell

  6. School of Electrical and Electronic Engineering and UCD Centre for Biomedical Engineering, University College Dublin, Dublin, Ireland

    Simon P. Kelly

  7. Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA

    Stephan Bickel

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Contributions

S.G., R.G.O’C., S.P.K. and S.B. designed the experiment and wrote the manuscript. S.G. recorded the neural data and performed the formal analysis. N.M., G.T. and E.E. contributed to data acquisition, preprocessing and visualization. All authors provided feedback on data analysis and reviewed the manuscript.

Corresponding authors

Correspondence to Sabina Gherman or Stephan Bickel.

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Extended data

Extended Data Fig. 1 Spatiotemporal profile of HFA consistent with transient low-level spatially-selective processes.

Top: Spatial distribution of electrodes in this category (black dots: all sites included in the analysis). Bottom: Temporal profile of activity, separated by strength of sensory evidence (High vs. Low motion coherence) and spatial location of the evidence (Contralateral vs. Ipsilateral side), averaged across contacts. Shaded areas represent standard error of the mean across contacts.

Extended Data Fig. 2 Spatial distribution and temporal variability of sites categorized as abstract accumulator candidates.

a. Proportion of sites categorized as “abstract” across anatomical regions (calculated relative to the total number of recorded sites in a given region). b. Average time of peak HFA amplitude relative to motor response, by anatomical region. Gray symbols reflect values at individual contacts. Colored brain areas in a and b represent gyral based parcellations63. Only parcels with coverage of at least 5 contacts are displayed.

Extended Data Fig. 3 Time of peak amplitude in response-aligned HFA at individual electrodes.

a. Abstract (that is, effector-independent) accumulator candidate sites b. Effector-selective sites.

Extended Data Fig. 4 Spatial distribution of electrodes categorized as effector-selective under an alternative set of criteria.

To isolate this category of contacts (blue dots), we included two additional requirements in the selection criteria which were used for the selection of Abstract accumulator candidates, namely modulation of HFA by Evidence Strength, and the absence of Evidence Location effect. Black dots mark all sites considered for this analysis.

Extended Data Fig. 5 Coverage of sites of interest during the vocal response task.

a. Electrodes categorized as potential abstract (that is, effector-independent) accumulators based on analysis of signals recorded during the manual response task. Small dots mark sites that were recorded from only during the Manual task. Large dots mark the subset of these electrodes which were also recorded from during the vocal response task. b. Electrodes categorized as effector-selective. Conventions are the same as in (a).

Extended Data Fig. 6 Effect of task order on activity during the vocal response task.

Temporal profile of average HFA during the delayed vocal response task, in sites categorized previously (that is based on the manual response task) as abstract (that is, effector independent) (a) vs. effector selective (b). Results are shown for two subject groups based on the order in which they performed the two versions of the task (left panels: subjects performed the manual response task first; right panel: subjects performed the vocal response first). All color conventions are the same as in Fig. 5.

Extended Data Fig. 7 Modulation of HFA by evidence strength in contacts common between the two behavioral tasks.

Displayed here are only the task-responsive contacts showing a significant effect of evidence strength (High>Low) in the evidence-aligned signal in at least one of the tasks (thresholded at p < .05, uncorrected; see ANOVA in Methods). a. Effect sizes (partial eta squared, ηp2) reflecting the magnitude of the modulation by evidence strength during the vocal (x axis) and manual (y axis) response tasks. Data points represent individual contacts. b. Spatial distribution of evidence strength modulation (large dots: contacts categorized as abstract accumulator candidates during the manual-response task).

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Gherman, S., Markowitz, N., Tostaeva, G. et al. Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions. Nat Hum Behav 8, 758–770 (2024). https://doi.org/10.1038/s41562-024-01824-9

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