Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain

Manea, Ana M.G.; Zilverstand, Anna; Uğurbil, Kâmil; Heilbronner, Sarah R.; Zimmermann, Jan

doi:10.7554/elife.75540

Cited by 26 publications

(40 citation statements)

References 71 publications

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“…The present data shows changes in human lPFC with extensive learning that may parallel changes in activity patterns and representations observed in NHP electrophysiology studies after WM training (Qi et al, 2019;Riley et al, 2018). However, it is difficult to fully bridge across discrepancies in measurement techniques and species: While BOLD fMRI signals can correlate with representations detected via multi-unit activity and high-gamma LFP (Klink et al, 2021;Manea et al, 2022), there is a complicated relationship between spiking activity, LFP signals, and BOLD measurements (Mukamel et al, 2005;Nir et al, 2007;Shi et al, 2017). Ultimately, paradigms using identical tasks, training timelines, and stimuli will be needed to compare the effects of learning on WM neural data between NHP and humans.…”

Section: Plasticity Of the Pfcsupporting

confidence: 50%

Long-term learning transforms prefrontal cortex representations during working memory

Miller

Tambini

Kiyonaga

et al. 2022

Preprint

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The lateral prefrontal cortex (lPFC) is reliably active during working memory (WM) across human and animal models, but the role of lPFC in successful WM is under debate. For instance, non-human primate (NHP) electrophysiology research finds that lPFC circuitry stores WM representations. Human neuroimaging instead suggests that lPFC plays a control function over WM content that is stored in sensory cortices. These seemingly incompatible WM accounts are often confounded by differences in the amount of task training and stimulus exposure across studies (i.e., NHPs tend to be trained extensively). Here, we test the possibility that such long-term training may alter the role of lPFC in WM maintenance. We densely sampled WM-related activity across learning, in three human participants, using a longitudinal functional MRI (fMRI) protocol. Over three months, participants trained on (1) a serial reaction time (SRT) task, wherein complex fractal stimuli were embedded within probabilistic sequences, and (2) a delayed recognition task probing WM for trained or novel stimuli. Participants were scanned frequently throughout training, to track how WM activity patterns change with repeated stimulus exposure and long-term associative learning. WM task performance improved for trained (but not novel) fractals and, neurally, delay activity significantly increased in distributed lPFC voxels across learning. Pattern similarity analyses also found that item-level WM representations emerged within lPFC, but not in sensory cortices, and lPFC delay activity increasingly reflected sequence relationships from the SRT task, even though that information was task-irrelevant for WM. These findings demonstrate that human lPFC develops stimulus-selective WM responses with learning and WM representations are shaped by long-term experience. Influences from training and long-term memory may reconcile competing accounts of lPFC function during WM.

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Section: Plasticity Of the Pfcsupporting

confidence: 50%

Long-term learning transforms prefrontal cortex representations during working memory

Miller

Tambini

Kiyonaga

et al. 2022

Preprint

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“…A robust functional hierarchy has been described that situates different cortical brain regions along a sensorimotor-association axis (Bernhardt et al, 2022;Burt et al, 2018;Harris et al, 2019;Margulies et al, 2016;Sydnor et al, 2021). Besides discriminating functional roles of different cortical territories, variation in other physiological properties of the cortex occur along a similar topography to the functional hierarchy (Burt et al, 2018;Fulcher et al, 2019;Gao et al, 2020;Wang, 2020), and it may serve as a principal avenue for directional functional signals (Manea et al, 2022;Pines et al, 2022;Siegle et al, 2021;Vézquez-Rodríguez et al, 2020). Cortical peaks in the functional hierarchy are distributed nearly maximally distant from one another (Margulies et al, 2016;Oligschläger et al, 2019), suggesting that the functional hierarchy may arise due to interacting underlying transcriptomic gradients (Wagstyl et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Conserved whole-brain spatiomolecular gradients shape adult brain functional organization

Vogel

Alexander-Bloch

Wagstyl

et al. 2022

Preprint

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Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression of morphogens and transcription factors. However, how these gradients relate to adult brain function, and whether they are maintained in the adult brain, remains unknown. Here we uncover three axes of topographic variation in gene expression in the adult human brain that specifically capture previously identified rostral-caudal, dorsal-ventral and medial-lateral axes of early developmental patterning. The interaction of these spatiomolecular gradients i) accurately predicts the location of unseen brain tissue samples, ii) delineates known functional territories, and iii) explains the topographical variation of diverse cortical features. The spatiomolecular gradients are distinct from canonical cortical functional hierarchies differentiating primary sensory cortex from association cortex, but radiate in parallel with the axes traversed by local field potentials along the cortex. We replicate all three molecular gradients in three independent human datasets as well as two non-human primate datasets, and find that each gradient shows a distinct developmental trajectory across the lifespan. The gradients are composed of several well known morphogens (e.g., PAX6 and SIX3), and a small set of genes shared across gradients are strongly enriched for multiple diseases. Together, these results provide insight into the developmental sculpting of functionally distinct brain regions, governed by three robust transcriptomic axes embedded within brain parenchyma.

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“…Such a hypothesis would imply that it would predict variability in integration time-constants in other domains (for example, auditory evidence integration (Brunton et al, 2013; Keung et al, 2019; McWalter and McDermott, 2018) or more broadly cognitive tasks that involve continuous maintenance and manipulation of information across time in working memory). If so, it may also be possible to relate variabilty in behavioural time constants to underlying neurobiological causes by measuring the resting autocorrelation structure of neural activity, for example in MEG or fMRI data (Cavanagh et al, 2020; Manea et al, 2022; Raut et al, 2020). On the other hand, the individual variability we observe may be a consequence of the prior expectations that our participants have about the overall task structure, combined with learning over the course of training.…”

Section: Discussionmentioning

confidence: 99%

Quantifying decision-making in dynamic, continuously evolving environments

Ruesseler

Weber

Marshall

et al. 2022

Preprint

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During perceptual decision-making tasks, centroparietal EEG potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. Confronted with time-varying stimuli, humans can appropriately adapt their weighting of recent evidence according to the statistics of the environment. The neural mechanisms supporting this adaptation currently remain unclear. Here, we show that humans' ability to adapt evidence weighting to different sensory environments is reflected in changes in centroparietal EEG potentials. We use a novel continuous task design to show that the Centroparietal Positivity (CPP) becomes more sensitive to fluctuations in sensory evidence when large shifts in evidence are less frequent, and is primarily sensitive to fluctuations in decision-relevant (not decision-irrelevant) sensory input. A complementary triphasic component over parietal cortex encodes the sum of recently accumulated sensory evidence, and its magnitude covaries with the duration over which different individuals integrate sensory evidence. Our findings reveal how adaptations in centroparietal responses reflect flexibility in evidence accumulation to the statistics of dynamic sensory environments.

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Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain

Cited by 26 publications

References 71 publications

Long-term learning transforms prefrontal cortex representations during working memory

Long-term learning transforms prefrontal cortex representations during working memory

Conserved whole-brain spatiomolecular gradients shape adult brain functional organization

Quantifying decision-making in dynamic, continuously evolving environments

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