The DOI matches its Crossref record; 107 of the 107 references it cites were found in a registry or an index.
Touch is a team effort: interplay of submodalities in cutaneous sensibility
Abstract
Traditionally, different classes of cutaneous mechanoreceptive afferents are ascribed different and largely non-overlapping functional roles (for example texture or motion) stemming from their different response properties. This functional segregation is thought to be reflected in cortex, where each neuron receives input from a single submodality. We summarize work that challenges this notion. First, while it is possible to design artificial stimuli that preferentially excite a single afferent class, most natural stimuli excite all afferents and most tactile percepts are shaped by multiple submodalities. Second, closer inspection of cortical responses reveals that most neurons receive convergent input from multiple afferent classes. We argue that cortical neurons should be grouped based on their function rather than on their submodality composition.
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In the citing paper
“Different populations of afferents can be activated through these individual electrodes, which can have distinct receptive field locations (Saal and Bensmaia, 2014) and different sub-modality compositions of sensory afferents (mix of slowly adapting (SA), rapidly adapting (RA), and pacinian corpuscles (PC) afferents).”
From Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review. (2017) · cites this paper as Saal and Bensmaia, 2014
In the citing paper
“During natural contact with objects, all afferent types are activated and convey information about the objects' shape, size, texture and motion with respect to the skin (Saal and Bensmaia, 2014).”
From Biomimetic approaches to bionic touch through a peripheral nerve interface (2015) · cites this paper as Saal and Bensmaia, 2014
In the citing paper
“Indeed, while different afferent types were traditionally assumed to encode a single tactile feature, such as surface texture or tactile motion, recent reinterpretation of extant data suggests that information about most tactile features is encoded synergistically by all afferent classes (see Saal and Bensmaia, 2014 for a review).”
From Biomimetic approaches to bionic touch through a peripheral nerve interface (2015) · cites this paper as Saal and Bensmaia, 2014
In the citing paper
“Importantly, signals from multiple afferent types converge at the earliest stages of processing in somatosensory cortex (and perhaps even before) (Carter et al., 2014;Pei et al., 2009;Saal and Bensmaia, 2014), allowing for the possibility that mimicking naturalistic patterns of activation over small populations of afferents of mixed type will result in naturalistic patterns of cortical activation,”
From Biomimetic approaches to bionic touch through a peripheral nerve interface (2015) · cites this paper as Saal and Bensmaia, 2014
Citations
Cites
MODALITY AND TOPOGRAPHIC PROPERTIES OF SINGLE NEURONS OF CAT'S SOMATIC SENSORY CORTEX
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Coding and use of tactile signals from the fingertips in object manipulation tasks
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The roles and functions of cutaneous mechanoreceptors.
Johnson, K. (2001) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(00)00234-8 · Cited by 1,063
Four channels mediate the mechanical aspects of touch
Bolanowski, S. J., Gescheider, G. A., Verrillo, R. T., & Checkosky, C. M. (1988) · The Journal of the Acoustical Society of America · doi:10.1121/1.397184 · Cited by 937
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First spikes in ensembles of human tactile afferents code complex spatial fingertip events
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Sorted by citations
Tactile innervation densities across the whole body
Corniani, G., & Saal, H. P. (2020) · Journal of Neurophysiology · doi:10.1152/jn.00313.2020 · Cited by 396
Self-citationGeorge, J. A., Kluger, D. T., Davis, T. S., Wendelken, S. M., Okorokova, E. V., He, Q., Duncan, C. C., Hutchinson, D. T., Thumser, Z. C., Beckler, D. T., et al. (2019) · Science Robotics · doi:10.1126/scirobotics.aax2352 · Cited by 388
Simulating tactile signals from the whole hand with millisecond precision
Saal, H. P., Delhaye, B. P., Rayhaun, B. C., & Bensmaı̈a, S. J. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1704856114 · Cited by 274
Self-citationThe neural mechanisms of manual dexterity
Sobinov, A. R., & Bensmaia, S. J. (2021) · Nature Reviews Neuroscience · doi:10.1038/s41583-021-00528-7 · Cited by 248
Chen, W., Khamis, H., Birznieks, I., Lepora, N. F., & Redmond, S. J. (2018) · IEEE Sensors Journal · doi:10.1109/jsen.2018.2868340 · Cited by 234
Metadata
- Authors
- Saal, H. P., & Bensmaia, S. J.
- Affiliations
- University of Chicago (US)
- ORCID
- Saal, Hannes P.
- Venue
- Trends in Neurosciences
- Publisher
- Elsevier BV
- Published
- 2014-12
- Volume
- 37
- Issue
- 12
- Pages
- 689-697
- ISSN
- 0166-2236 (ISSN-L)
- OpenAlex
- W2094721746
- Cited by
- 280
- References
- 107
- Citations by year
- 2026: 33 · 2025: 23 · 2024: 23 · 2023: 24 · 2022: 31 · 2021: 27 · 2020: 21 · 2019: 22 · 2018: 26 · 2017: 16 · 2016: 18 · 2015: 15 · 2014: 1
- FWCI
- 1.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Trends in Neurosciences (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- cutaneous mechanoreceptors, tactile perception, afferent convergence, cortical neurons, functional segregation, texture perception, naturalistic stimuli, multisensory integration, somatosensory cortex
- MeSH terms
- Afferent Pathways, Brain Mapping, Humans, Mechanoreceptors, Neurons, Somatosensory Cortex, Touch
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