Neural coding of 3D features of objects for hand action in the parietal cortex of the monkey

Sakata, Hideo; Taira, Masato; Kusunoki, Makoto; Murata, Akira; Tanaka, Yuji; Tsutsui, Ken

doi:10.1098/rstb.1998.0290

Cited by 145 publications

(90 citation statements)

References 41 publications

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“…In the macaque, previous electrophysiological reports have described face-(or shape-) related activity, in specific sites in parietal cortex (e.g., in LIP and AIP) (36)(37)(38) and ventrolateral prefrontal cortex (the inferior prefrontal convexity) (39)(40)(41). These electrophysiological areas appear to coincide with the fMRI-based, face-responsive patches shown here in monkey.…”

Section: Discussionmentioning

confidence: 58%

An anterior temporal face patch in human cortex, predicted by macaque maps

Rajimehr

Young

Tootell

2009

Proc. Natl. Acad. Sci. U.S.A.

264

235

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Increasing evidence suggests that primate visual cortex has a specialized architecture for processing discrete object categories such as faces. Human fMRI studies have described a localized region in the fusiform gyrus [the fusiform face area (FFA)] that responds selectively to faces. In contrast, in nonhuman primates, electrophysiological and fMRI studies have instead revealed 2 apparently analogous regions of face representation: the posterior temporal face patch (PTFP) and the anterior temporal face patch (ATFP). An earlier study suggested that human FFA is homologous to the PTFP in macaque. However, in humans, no obvious homologue of the macaque ATFP has been demonstrated. Here, we used fMRI to map face-selective sites in both humans and macaques, based on equivalent stimuli in a quantitative topographic comparison. This fMRI evidence suggests that such a face-selective area exists in human anterior inferotemporal cortex, comprising the apparent homologue of the fMRI-defined ATFP in macaques.face processing ͉ fMRI ͉ inferotemporal cortex ͉ macaque-human homology T he fusiform face area (FFA) is one of the most distinctive regions in the human ventral temporal cortex. A wide range of noninvasive techniques, including PET, fMRI, ERP, and MEG have shown that FFA responds selectively to images of faces, relative to a wide variety of control objects (1-7). Such approaches have revealed an enormous amount about face selectivity in this distinctive region of human cerebral cortex.Such noninvasive techniques cannot furnish the kind of incisive information that is available from classical neurobiological techniques (e.g., single-unit recording) in nonhuman primates. These 2 realms have begun to be bridged by recent fMRI studies in awake monkeys, which demonstrated that apparently homologous face-selective regions also exist in macaque inferotemporal (IT) cortex (8,9). Subsequent experiments reported that Ϸ97% of the single units in the largest face-selective region (the so-called posterior temporal face patch, located in caudal TE) respond strongly and selectively to images of faces, compared with images of control objects (10). This fMRI and physiological evidence supports the idea that this region of monkey cortex is indeed selective for faces.A computational transformation concluded that this posterior temporal face patch (PTFP) in macaques is located in a cortical region that corresponds topographically to area FFA in human subjects (8). This analysis assumes that neighborhood relations between specific cortical areas are evolutionarily conserved across the sheet of cortical gray matter, as validated in many previous human-monkey comparisons (11-14).However, this conclusion raises a significant issue. In macaques, an additional face-selective region is consistently found further anterior in the temporal lobe, in rostral TE (8-10, 15, 16); here, this is termed the anterior temporal face patch (ATFP). However, in humans, no such area (i.e., anterior to FFA) has been reported by conventional fMRI mapping of face rep...

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Section: Discussionmentioning

confidence: 58%

An anterior temporal face patch in human cortex, predicted by macaque maps

Rajimehr

Young

Tootell

2009

Proc. Natl. Acad. Sci. U.S.A.

264

235

View full text Add to dashboard Cite

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“…For instance, there are many neuroimaging reports that implicate dorsal stream structures in the preparation and comprehension of tool manipulation (Boronat et al, 2005;Johnson-Frey et al, 2005;Kellenbach et al, 2003) . Moreover, research on apraxia has shown that some of these dorsal stream structures are causally implicated in the manipulation of objects (Buxbaum et al, 2007;Haaland et al, 2000;Goldenberg & Spatt 2009;Sirigu et al, 1991 Sakata et al, 1998; see also Shikata et al, 2001), who found that that the firing rate of a population of neurons in caudal intraparietal sulcus increases monotonically with increasing length of the stimulus, and decreases with increasing thickness of the elongated stimuli. Finally, these more posterior parietal regions seem to be involved in the processing of other visuomotor dimensions, such as object orientation and perhaps size, in support of object grasping (e.g., James et al, 2002).…”

Section: Discussionmentioning

confidence: 99%

Grasping with the eyes: The role of elongation in visual recognition of manipulable objects

Almeida

Mahon

Zapater-Raberov

et al. 2013

Cogn Affect Behav Neurosci

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Processing within the dorsal visual stream subserves object-directed action, whereas visual object recognition is mediated by the ventral visual stream. Recent findings suggest that the computations performed by the dorsal stream can nevertheless influence object recognition.Little is known, however, about the type of dorsal stream information that is available to assist in object recognition. Here we present a series of experiments that explored different psychophysical manipulations known to bias the processing of a stimulus toward the dorsal visual stream in order to isolate its contribution to object recognition. We show that elongatedshaped stimuli, regardless of their semantic category and familiarity, when processed by the dorsal stream, elicit visuomotor grasp-related information that affects how we categorize manipulable objects. Elongated-shaped stimuli may reduce ambiguity during grasp preparation by providing a coarse cue to hand shaping and orientation that is sufficient to support action planning. We propose that this dorsal-stream based analysis of elongation along a principal axis is the basis for how the dorsal visual object processing stream can affect categorization of manipulable objects.

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“…The middle portion of the IPS, in contrast, has been more thoroughly characterized in nonhuman primates of which a prominent feature is its poorly defined functional properties; neurons in the area can encode either reaches or saccades. For instance, reachrelated neurons can be found not only in both V6A and MIP but also within aspects of cIPS and LIP, areas proximally positioned on the lateral bank of the IPS (Calton et al, 2002;Chang and Snyder, 2010) more prominently implicated in coding action-relevant 3D visual object features (Sakata et al, 1998) and the targets for saccades (Andersen et al, 1985), respectively. A few human studies to date have attempted to describe the homologous functional locations of these regions, and the pIPS and midIPS decoding results provided here also offer good approximations; L-pIPS, L-midIPS, and R-midIPS all predict the direction of both eye and arm movements and, interestingly, this spatial selectivity is similar enough across both effectors to allow for accurate cross-classification.…”

Section: Posterior Parietal Cortex Decodingmentioning

confidence: 99%

“…The posterior IPS or pIPS is defined by selecting activity at the caudal end of the IPS (Sakata et al, 1998;Beurze et al, 2009).…”

Section: Roi Selectionmentioning

confidence: 99%

Decoding Effector-Dependent and Effector-Independent Movement Intentions from Human Parieto-Frontal Brain Activity

Gallivan

McLean

Smith³

et al. 2011

J. Neurosci.

155

171

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Our present understanding of the neural mechanisms and sensorimotor transformations that govern the planning of arm and eye movements predominantly come from invasive parieto-frontal neural recordings in nonhuman primates. While functional MRI (fMRI) has motivated investigations on much of these same issues in humans, the highly distributed and multiplexed organization of parietofrontal neurons necessarily constrain the types of intention-related signals that can be detected with traditional fMRI analysis techniques. Here we employed multivoxel pattern analysis (MVPA), a multivariate technique sensitive to spatially distributed fMRI patterns, to provide a more detailed understanding of how hand and eye movement plans are coded in human parieto-frontal cortex. Subjects performed an event-related delayed movement task requiring that a reach or saccade be planned and executed toward one of two spatial target positions. We show with MVPA that, even in the absence of signal amplitude differences, the fMRI spatial activity patterns preceding movement onset are predictive of upcoming reaches and saccades and their intended directions. Within certain parieto-frontal regions we show that these predictive activity patterns reflect a similar spatial target representation for the hand and eye. Within some of the same regions, we further demonstrate that these preparatory spatial signals can be discriminated from nonspatial, effector-specific signals. In contrast to the largely graded effector-and direction-related planning responses found with fMRI subtraction methods, these results reveal considerable consensus with the parieto-frontal network organization suggested from primate neurophysiology and specifically show how predictive spatial and nonspatial movement information coexists within single human parieto-frontal areas.

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Neural coding of 3D features of objects for hand action in the parietal cortex of the monkey

Cited by 145 publications

References 41 publications

An anterior temporal face patch in human cortex, predicted by macaque maps

An anterior temporal face patch in human cortex, predicted by macaque maps

Grasping with the eyes: The role of elongation in visual recognition of manipulable objects

Decoding Effector-Dependent and Effector-Independent Movement Intentions from Human Parieto-Frontal Brain Activity

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