Electrocorticography Evidence of Tactile Responses in Visual Cortices

Gaglianese, Anna; Branco, Mariana P.; Groen, Iris; Benson, Noah C.; Vansteensel, Mariska J.; Murray, Micah M.; Petridou, Natalia; Ramsey, Nick

doi:10.1007/s10548-020-00783-4

Cited by 10 publications

(5 citation statements)

References 70 publications

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“…Moreover, the fact that hMT+ exhibited the same properties as the primary visual cortex V1 in encoding basic features of a visual stimuli, such as the spatial and temporal frequency components, is consistent with previous studies in both humans and primates showing that area MT receives, and is able to process, fundamental properties of the visual input directly from the thalamus, bypassing the role of the primary visual cortex (ffytche et al, 1995; Gaglianese et al, 2012; Sincich et al, 2004) and could explain the absence of deficit in biological motion perception in patients affected by congenital visual deprivation (Bottari et al, 2015). This fundamental low level mechanism of the MT complex in processing visual motion features could explain the multisensory role of this area in encoding motion via other sensory modalities such touch and hearing (Avanzini et al, 2016; Gaglianese et al, 2020; Poirier et al, 2005; Van Kemenade et al, 2014). Indeed, asensory specific areas rely on the process of task information (e.g.…”

Section: Discussionmentioning

confidence: 96%

Mechanisms of speed encoding in the human middle temporal cortex measured by 7T fMRI

Gaglianese

Fracasso

et al. 2021

Preprint

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Perception of environmental dynamic scenes results from the evaluation of visual features such as the fundamental spatial and temporal frequencies components of a moving object. The ratio between these two components represents its speed of motion. The human middle temporal cortex hMT+ has a crucial biological role in the direct encoding of object speed. However, the link between hMT+ speed encoding and the spatiotemporal frequency components of a moving object may be more complex than we thought. Both animal studies and recent human electrocorticography data showed that recorded neuronal populations within MT+/V5 change their speed preferences in accordance with the stimulus fundamental spatial frequency. We disentangle whether such mechanism holds for the entire human MT+. We recorded high resolution 7T blood oxygen level-dependent BOLD responses to different visual motion stimuli as a function of their fundamental spatial and temporal frequency components. We fitted each hMT+ BOLD response with a 2D Gaussian model allowing for distinct and independent selectivity for spatial and temporal frequencies of the visual stimuli or tuning for the speed of motion. We show that: 1) hMT+ encodes the speed of motion via independent tuning of the fundamental spatial frequency component of the visual stimuli, 2) the optimal spatial frequency selectivity of hMT+ is tuned for the low spatial frequency of the visual stimuli and is highly reproducible within subjects. Our results show that hMT+ speed preference changes according to the fundamental spatial frequency presented, demonstrating a primary role of the entire hMT+ in the evaluation of the spatial features of the moving visual input. These findings confirm a more complex mechanism involved in the direct perception of speed than initially thought.

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Section: Discussionmentioning

confidence: 96%

Mechanisms of speed encoding in the human middle temporal cortex measured by 7T fMRI

Gaglianese

Fracasso

et al. 2021

Preprint

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“…This finding is in line with previous research assigning a multimodal role to occipital cortex ( Lacey et al, 2007 ; Murray et al, 2016 ) and suggesting that multisensory enhancements originate from the sensory cortices ( Kayser and Logothetis, 2007 ; Lakatos et al, 2007 ; Lewis and Noppeney, 2010 ). Specifically, recent research involved the visual cortex in audiovisual interactions ( Mishra et al, 2007 ; Cao et al, 2019 ; Rohe et al, 2019 ) as well as tactile perception and visuo-haptic interactions ( Lucan et al, 2010 ; Sathian, 2016 ; Gaglianese et al, 2020 ). In agreement with the above, here we also found unique H information in parieto-occipital electrodes.…”

Section: Discussionmentioning

confidence: 99%

Neural Encoding of Active Multi-Sensing Enhances Perceptual Decision-Making via a Synergistic Cross-Modal Interaction

et al. 2022

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Most perceptual decisions rely on the active acquisition of evidence from the environment involving stimulation from multiple senses. However, our understanding of the neural mechanisms underlying this process is limited. Crucially, it remains elusive how different sensory representations interact in the formation of perceptual decisions. To answer these questions, we used an active sensing paradigm coupled with neuroimaging, multivariate analysis, and computational modeling to probe how the human brain processes multisensory information to make perceptual judgments. Participants of both sexes actively sensed to discriminate two texture stimuli using visual (V) or haptic (H) information or the two sensory cues together (VH). Crucially, information acquisition was under the participants' control, who could choose where to sample information from and for how long on each trial. To understand the neural underpinnings of this process, we first characterized where and when active sensory experience (movement patterns) is encoded in human brain activity (EEG) in the three sensory conditions. Then, to offer a neurocomputational account of active multisensory decision formation, we used these neural representations of active sensing to inform a drift diffusion model of decision-making behavior. This revealed a multisensory enhancement of the neural representation of active sensing, which led to faster and more accurate multisensory decisions. We then dissected the interactions between the V, H, and VH representations using a novel information-theoretic methodology. Ultimately, we identified a synergistic neural interaction between the two unisensory (V, H) representations over contralateral somatosensory and motor locations that predicted multisensory (VH) decision-making performance. SIGNIFICANCE STATEMENT In real-world settings, perceptual decisions are made during active behaviors, such as crossing the road on a rainy night, and include information from different senses (e.g., car lights, slippery ground). Critically, it remains largely unknown how sensory evidence is combined and translated into perceptual decisions in such active scenarios. Here we address this knowledge gap. First, we show that the simultaneous exploration of information across senses (multi-sensing) enhances the neural encoding of active sensing movements. Second, the neural representation of active sensing modulates the evidence available for decision; and importantly, multi-sensing yields faster evidence accumulation. Finally, we identify a cross-modal interaction in the human brain that correlates with multisensory performance, constituting a putative neural mechanism for forging active multisensory perception.

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“…showing that area MT receives, and is able to process, fundamental properties of the visual input directly from the thalamus, bypassing the V1 (Ffytche et al, 1995;Gaglianese et al, 2012;Sincich et al, 2004) and could explain the absence of deficit in biological motion perception in patients affected by congenital visual deprivation (Bottari et al, 2015). This fundamental low level mechanism of the hMT complex in processing visual motion features could explain the multisensory role of this area in encoding motion via other sensory modalities such touch and hearing (Avanzini et al, 2016;Gaglianese et al, 2020;Poirier et al, 2005;van Kemenade et al, 2014). Indeed, asensory specific areas rely on the process of task information (e.g.…”

Section: Hmt+ Bold Response Amplitudes Were Mainly Characterized By I...mentioning

confidence: 99%

Mechanisms of speed encoding in the human middle temporal cortex measured by 7T fMRI

Gaglianese

Fracasso

Fernandes

et al. 2023

Human Brain Mapping

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Perception of dynamic scenes in our environment results from the evaluation of visual features such as the fundamental spatial and temporal frequency components of a moving object. The ratio between these two components represents the object's speed of motion. The human middle temporal cortex hMT+ has a crucial biological role in the direct encoding of object speed. However, the link between hMT+ speed encoding and the spatiotemporal frequency components of a moving object is still under explored. Here, we recorded high resolution 7T blood oxygen level-dependent BOLD responses to different visual motion stimuli as a function of their fundamental spatial and temporal frequency components. We fitted each hMT+ BOLD response with a 2D Gaussian model allowing for two different speed encoding mechanisms:(1) distinct and independent selectivity for the spatial and temporal frequencies of the visual motion stimuli; (2) pure tuning for the speed of motion. We show that both mechanisms occur but in different neuronal groups within hMT+, with the largest subregion of the complex showing separable tuning for the spatial and temporal frequency of the visual stimuli. Both mechanisms were highly reproducible within participants, reconciling single cell recordings from MT in animals that have showed both encoding mechanisms. Our findings confirm that a more complex process is involved in the perception of speed than initially thought and suggest that hMT+ plays a primary role in the evaluation of the spatial features of the moving visual input.

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Electrocorticography Evidence of Tactile Responses in Visual Cortices

Cited by 10 publications

References 70 publications

Mechanisms of speed encoding in the human middle temporal cortex measured by 7T fMRI

Mechanisms of speed encoding in the human middle temporal cortex measured by 7T fMRI

Neural Encoding of Active Multi-Sensing Enhances Perceptual Decision-Making via a Synergistic Cross-Modal Interaction

Mechanisms of speed encoding in the human middle temporal cortex measured by 7T fMRI

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