Primitive visual channels have a causal role in cognitive transfer

Saban, William; Raz, Gal; Grabner, Roland H.; Gabay, Shai; Kadosh, Roi Cohen

doi:10.1038/s41598-021-88271-y

Cited by 8 publications

(14 citation statements)

References 45 publications

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“…These results challenge the exclusive role of the cortex in cognitive transfer as was previously assumed. Most pertinent for the current work, this recent finding demonstrates the direct relations between spatial and arithmetic abilities, but also converge with the notion that the subcortex functionally supports arithmetic 13 .…”

Section: Discussionsupporting

confidence: 83%

“…To conclude, in contrast to most literature, research conducted in recent years has taught us that many of the high-level functions, which were traditionally associated with neocortical regions, can functionally involve lower subcortical regions 10 , 13 , 14 , 22 , 37 . The current findings demonstrate that a uniquely human cultural product, such as solving arithmetic equations, does not solely involve neocortical regions, and they suggest a primitive mechanism for arithmetic abilities that might be shared by different species.…”

Section: Discussionmentioning

confidence: 72%

“…Recently, using the stereoscopic manipulation, it was demonstrated that the subcortex has a causal role in cognitive transfer of complex cognitive skills in humans 13 . Such cognitive transfer was found for both novel figural-spatial problems (near transfer) and novel subtraction problems (far transfer).…”

Section: Discussionmentioning

confidence: 99%

“…This conceptual notion predicts that: 1) SNS are involved in the evolution and development of cognition, and 2) SNS are involved in cognition in species that do not have fully developed cortex (e.g., fish), and 3) SNS are involved in cognitive abilities in the mature human brain even in what is considered “higher-order” cognition, such as arithmetic. We term this conceptual framework the “ SNS hypothesis .” We propose that SNS, which are ubiquitous across the animal kingdom, enable cognitive operations essential for the emergence of complex cognition (see also 13 ). SNS can be reused and manipulated by neocortical mechanisms, and jointly, novel skills can be developed during evolution.…”

Section: Discussionmentioning

confidence: 99%

“…For each participant, the stereoscope apparatus was calibrated to ensure perceptual fusion of the images presented in all the conditions 12 , 13 , 37 , 60 . Before the experiment began, we conducted two tests to preclude any confounding effect of perceptual differences between the eye-of-origin conditions and to determine whether participants experienced a well-fused percept in all the conditions 12 , 13 , 37 , 60 . Two rectangles were presented throughout the task, one to each eye, and all stimuli were presented inside those rectangles 12 , 13 , 37 , 60 .…”

Section: Methodsmentioning

confidence: 99%

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Ancient visual channels have a causal role in arithmetic calculations

Saban

Sklar

Hassin

et al. 2021

Sci Rep

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Humans exhibit complex arithmetic skills, often attributed to our exceptionally large neocortex. However, the past decade has provided ample evidence that the functional domain of the subcortex extends well beyond basic functions. Using a sensitive behavioral method, for the first time, we explored the contributions of lower-order visual monocular channels to symbolic arithmetic operations, addition and subtraction. The pattern of results from 4 different experiments provides converging evidence for a causal relation between mental arithmetic and primitive subcortical regions. The results have major implications for our understanding of the neuroevolutionary development of general numerical abilities–subcortical regions, which are shared across different species, are essential to complex numerical operations. In a bigger conceptual framework, these findings and others call for a shift from the modal view of the exclusive role of the neocortex in high-level cognition to a view that emphasizes the interplay between subcortical and cortical brain networks.

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Section: Discussionsupporting

confidence: 83%

Section: Discussionmentioning

confidence: 72%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Ancient visual channels have a causal role in arithmetic calculations

Saban

Sklar

Hassin

et al. 2021

Sci Rep

Self Cite

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Decomposing neural circuit function into information processing primitives

Voges

Hausmann²,

Brovelli

et al. 2022

Preprint

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Cognitive functions arise from the coordinated activity of neural populations distributed over large-scale brain networks. However, it is challenging to understand and measure how specific aspects of neural dynamics translate into operations of information processing, and, ultimately, cognitive functions. An obstacle is that simple circuit mechanisms–such as self-sustained or propagating activity and nonlinear summation of inputs–do not directly give rise to high-level functions. Nevertheless, they already implement simple transformations of the information carried by neural activity.Here, we propose that distinct neural circuit functions, such as stimulus representation, working memory, or selective attention stem from different combinations and types of low-level manipulations of information, or information processing primitives. To test this hypothesis, we combine approaches from information theory with computational simulations of canonical neural circuits involving one or more interacting brain regions that emulate well-defined cognitive functions. More specifically, we track the dynamics of information emergent from dynamic patterns of neural activity, using suitable quantitative metrics to detect where and when information is actively buffered (“active information storage”), transferred (“information transfer”) or non-linearly merged (“information modification”), as possible modes of low-level processing. We find that neuronal subsets maintaining representations in working memory or performing attention-related gain modulation are signaled by their boosted involvement in operations of active information storage or information modification, respectively.Thus, information dynamics metrics, beyond detecting which network units participate in cognitive processing, also promise to specify how and when they do it, i.e., through which type of primitive computation, a capability that may be exploited for the parsing of actual experimental recordings.

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Decomposing Neural Circuit Function into Information Processing Primitives

Voges,

Lima,

Hausmann

et al. 2023

J. Neurosci.

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Cognitive functions arise from the coordinated activity of many neural populations. It is challenging to measure how specific aspects of neural dynamics translate into operations of information processing, and, ultimately, cognitive functions. An obstacle is that simple circuit mechanisms -such as self-sustained or propagating activity and nonlinear summation of inputs- do not directly give rise to high-level functions. Nevertheless, they already implement simple transformations of the information carried by neural activity. Here, we propose that distinct neural circuit functions, such as stimulus representation, working memory or selective attention stem from different combinations and types of low-level manipulations of information, or information processing primitives. To test this hypothesis, we combine approaches from information theory with computational simulations of neural circuits involving interacting brain regions that emulate well-defined cognitive functions (canonic ring models and a large-scale connectome-based model). Specifically, we track the dynamics of information emergent from dynamic patterns of neural activity, using suitable quantitative metrics to detect where and when information is actively buffered ("active information storage"), transferred ("information transfer") or non-linearly merged ("information modification"), as possible modes of low-level processing. We find that neuronal subsets maintaining representations in working memory or performing attention-related gain modulation are signaled by their involvement in operations of information storage or modification, respectively. Thus, information dynamics metrics, beyond detectingwhichnetwork units participate in cognitive processing, also promise to specifyhow and whenthey do it, i.e., through which type of primitive computation, a capability that may be exploited for the analysis of experimental recordings.Significance StatementWe can easily name brain functions and we are well informed about brain structure. However, it is not easy to bridge the gap between the two. Part of the problem is that simple circuit mechanisms do not directly give rise to high-level functions. Yet, they already implement simpler forms of information processing, a sort of "neural assembly language". Here we track such primitive operations of processing using metrics from information theory and benchmarking them on functional simulations. We thus prove that these metrics can reveal the different flavors of information processing involved in different well-defined functions (working memory, selective attention...). We thus transform descriptions of neuronal dynamics into descriptions of how these dynamics specifically propagate and modify information.

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Primitive visual channels have a causal role in cognitive transfer

Cited by 8 publications

References 45 publications

Ancient visual channels have a causal role in arithmetic calculations

Ancient visual channels have a causal role in arithmetic calculations

Decomposing neural circuit function into information processing primitives

Decomposing Neural Circuit Function into Information Processing Primitives

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