Theta-burst TMS of lateral occipital cortex reduces BOLD responses across category-selective areas in ventral temporal cortex

AbstractHuman visual cortex contains three scene-selective regions in the lateral, medial and ventral cortex, termed the occipital place area (OPA), medial place area (MPA) and parahippocampal place area (PPA). Using functional magnetic resonance imaging (fMRI), all three regions respond more strongly when viewing visual scenes compared with isolated objects or faces. To determine how these regions are functionally and causally connected, we applied transcranial magnetic stimulation to OPA and measured fMRI responses before and after stimulation, using a theta-burst paradigm (TBS). To test for stimulus category-selectivity, we presented a range of visual categories (scenes, buildings, objects, faces). To test for specificity of any effects to TBS of OPA we employed two control conditions: Sham, with no TBS stimulation, and an active TBS-control with TBS to a proximal face-selective cortical region (occipital face area, or OFA). We predicted that TBS to OPA (but not OFA) would lead to decreased responses to scenes and buildings (but not other categories) in other scene-selective cortical regions. Across both ROI and whole-volume analyses, we observed decreased responses to scenes in PPA as a result of TBS. However, these effects were neither category specific, with decreased responses to all stimulus categories, nor limited to scene-selective regions, with decreases also observed in face-selective fusiform face area (FFA). Furthermore, similar effects were observed with TBS to OFA, thus effects were not specific to the stimulation site in the lateral occipital cortex. Whilst these data are suggestive of a causal, but non-specific relationship between lateral occipital and ventral temporal cortex, we discuss several factors that could have underpinned this result, such as the differences between TBS and online TMS, the role of anatomical distance between stimulated regions and how TMS effects are operationalised. Furthermore, our findings highlight the importance of active control conditions in brain stimulation experiments to accurately assess functional and causal connectivity between specific brain regions.

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Equal Degrees of Object Selectivity for Upper and Lower Visual Field Stimuli

Journal of Neurophysiology ◽

10.1152/jn.00462.2010 ◽

2010 ◽

Vol 104 (4) ◽

pp. 2075-2081 ◽

Cited By ~ 16

Author(s):

Lars Strother ◽

Adrian Aldcroft ◽

Cheryl Lavell ◽

Tutis Vilis

Keyword(s):

Visual Field ◽

Occipital Cortex ◽

Recognition System ◽

Blood Oxygen Level Dependent ◽

Lower Visual Field ◽

Blood Oxygen Level ◽

Visual Areas ◽

Bold Responses ◽

Cortical Regions ◽

Lateral Occipital Cortex

Functional MRI (fMRI) studies of the human object recognition system commonly identify object-selective cortical regions by comparing blood oxygen level–dependent (BOLD) responses to objects versus those to scrambled objects. Object selectivity distinguishes human lateral occipital cortex (LO) from earlier visual areas. Recent studies suggest that, in addition to being object selective, LO is retinotopically organized; LO represents both object and location information. Although LO responses to objects have been shown to depend on location, it is not known whether responses to scrambled objects vary similarly. This is important because it would suggest that the degree of object selectivity in LO does not vary with retinal stimulus position. We used a conventional functional localizer to identify human visual area LO by comparing BOLD responses to objects versus scrambled objects presented to either the upper (UVF) or lower (LVF) visual field. In agreement with recent findings, we found evidence of position-dependent responses to objects. However, we observed the same degree of position dependence for scrambled objects and thus object selectivity did not differ for UVF and LVF stimuli. We conclude that, in terms of BOLD response, LO discriminates objects from non-objects equally well in either visual field location, despite stronger responses to objects in the LVF.

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Changes in structural network topology correlate with severity of hallucinatory behavior in Parkinson’s disease

Network Neuroscience ◽

10.1162/netn_a_00078 ◽

2019 ◽

Vol 3 (2) ◽

pp. 521-538 ◽

Cited By ~ 4

Author(s):

Julie M. Hall ◽

Claire O’Callaghan ◽

Alana J. Muller ◽

Kaylena A. Ehgoetz Martens ◽

Joseph R. Phillips ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Network Topology ◽

Visual Processing ◽

Temporal Cortex ◽

Occipital Cortex ◽

Structural Network ◽

Visual Cortices ◽

Transfer Of Information ◽

Lateral Occipital Cortex

Inefficient integration between bottom-up visual input and higher order visual processing regions is implicated in visual hallucinations in Parkinson’s disease (PD). Here, we investigated white matter contributions to this perceptual imbalance hypothesis. Twenty-nine PD patients were assessed for hallucinatory behavior. Hallucination severity was correlated to connectivity strength of the network using the network-based statistic approach. The results showed that hallucination severity was associated with reduced connectivity within a subnetwork that included the majority of the diverse club. This network showed overall greater between-module scores compared with nodes not associated with hallucination severity. Reduced between-module connectivity in the lateral occipital cortex, insula, and pars orbitalis and decreased within-module connectivity in the prefrontal, somatosensory, and primary visual cortices were associated with hallucination severity. Conversely, hallucination severity was associated with increased between- and within-module connectivity in the orbitofrontal and temporal cortex, as well as regions comprising the dorsal attentional and default mode network. These results suggest that hallucination severity is associated with marked alterations in structural network topology with changes in participation along the perceptual hierarchy. This may result in the inefficient transfer of information that gives rise to hallucinations in PD.

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Direct comparison of contralateral bias and face/scene selectivity in human occipitotemporal cortex

Brain Structure and Function ◽

10.1007/s00429-021-02411-8 ◽

2021 ◽

Author(s):

Edward H. Silson ◽

Iris I. A. Groen ◽

Chris I. Baker

Keyword(s):

Visual Cortex ◽

Visual Field ◽

Visual Information ◽

Large Scale ◽

Temporal Cortex ◽

Spatial Location ◽

Occipital Cortex ◽

Ventral Surface ◽

Right Visual Field ◽

Ventral Temporal Cortex

AbstractHuman visual cortex is organised broadly according to two major principles: retinotopy (the spatial mapping of the retina in cortex) and category-selectivity (preferential responses to specific categories of stimuli). Historically, these principles were considered anatomically separate, with retinotopy restricted to the occipital cortex and category-selectivity emerging in the lateral-occipital and ventral-temporal cortex. However, recent studies show that category-selective regions exhibit systematic retinotopic biases, for example exhibiting stronger activation for stimuli presented in the contra- compared to the ipsilateral visual field. It is unclear, however, whether responses within category-selective regions are more strongly driven by retinotopic location or by category preference, and if there are systematic differences between category-selective regions in the relative strengths of these preferences. Here, we directly compare contralateral and category preferences by measuring fMRI responses to scene and face stimuli presented in the left or right visual field and computing two bias indices: a contralateral bias (response to the contralateral minus ipsilateral visual field) and a face/scene bias (preferred response to scenes compared to faces, or vice versa). We compare these biases within and between scene- and face-selective regions and across the lateral and ventral surfaces of the visual cortex more broadly. We find an interaction between surface and bias: lateral surface regions show a stronger contralateral than face/scene bias, whilst ventral surface regions show the opposite. These effects are robust across and within subjects, and appear to reflect large-scale, smoothly varying gradients. Together, these findings support distinct functional roles for the lateral and ventral visual cortex in terms of the relative importance of the spatial location of stimuli during visual information processing.

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Direct comparison of category and spatial selectivity in human occipitotemporal cortex

10.1101/2021.05.06.442603 ◽

2021 ◽

Author(s):

Edward H Silson ◽

Iris Isabelle Anna Groen ◽

Chris I Baker

Keyword(s):

Visual Cortex ◽

Visual Field ◽

Visual Information ◽

Large Scale ◽

Spatial Information ◽

Temporal Cortex ◽

Occipital Cortex ◽

Right Visual Field ◽

Ventral Temporal Cortex ◽

Category Bias

Human visual cortex is organised broadly according to two major principles: retinotopy (the spatial mapping of the retina in cortex) and category-selectivity (preferential responses to specific categories of stimuli). Historically, these principles were considered anatomically separate, with retinotopy restricted to the occipital cortex and category-selectivity emerging in lateral-occipital and ventral-temporal cortex. Contrary to this assumption, recent studies show that category-selective regions exhibit systematic retinotopic biases. It is unclear, however, whether responses within these regions are more strongly driven by retinotopic location or by category preference, and if there are systematic differences between category-selective regions in the relative strengths of these preferences. Here, we directly compare spatial and category preferences by measuring fMRI responses to scene and face stimuli presented in the left or right visual field and computing two bias indices: a spatial bias (response to the contralateral minus ipsilateral visual field) and a category bias (response to the preferred minus non-preferred category). We compare these biases within and between scene- and face-selective regions across the lateral and ventral surfaces of visual cortex. We find an interaction between surface and bias: lateral regions show a stronger spatial than category bias, whilst ventral regions show the opposite. These effects are robust across and within subjects, and reflect large-scale, smoothly varying gradients across both surfaces. Together, these findings support distinct functional roles for lateral and ventral category-selective regions in visual information processing in terms of the relative importance of spatial information.

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The Representation of Objects in the Human Occipital and Temporal Cortex

Journal of Cognitive Neuroscience ◽

10.1162/089892900564055 ◽

2000 ◽

Vol 12 (supplement 2) ◽

pp. 35-51 ◽

Cited By ~ 209

Author(s):

Alumit Ishai ◽

Leslie G. Ungerleider ◽

Alex Martin ◽

James V. Haxby

Keyword(s):

Temporal Cortex ◽

Occipital Cortex ◽

Visual Pathway ◽

Distributed Representation ◽

National Academy Of Sciences ◽

Line Drawings ◽

Ventral Visual Pathway ◽

Presentation Formats ◽

Ventral Temporal Cortex ◽

Object Form

Recently, we identified, using fMRI, three bilateral regions in the ventral temporal cortex that responded preferentially to faces, houses, and chairs [Ishai, A., Ungerleider, L. G., Martin, A., Schouten, J. L., & Haxby, J. Y. (1999). Distributed representation of objects in the human ventral visual pathway. Proceedings of the National Academy of Sciences, U.S.A., 96, 9379-9384]. Here, we report differential patterns of activation, similar to those seen in the ventral temporal cortex, in bilateral regions of the ventral occipital cortex. We also found category-related responses in the dorsal occipital cortex and in the superior temporal sulcus. Moreover, rather than activating discrete, segregated areas, each category was associated with its own differential pattern of response across a broad expanse of cortex. The distributed patterns of response were similar across tasks (passive viewing, delayed matching) and presentation formats (photographs, line drawings). We propose that the representation of objects in the ventral visual pathway, including both occipital and temporal regions, is not restricted to small, highly selective patches of cortex but, instead, is a distributed representation of information about object form. Within this distributed system, the representation of faces appears to be less extensive as compared to the representations of nonface objects.

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Neural Evidence of Statistical Learning: Efficient Detection of Visual Regularities Without Awareness

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2009.21131 ◽

2009 ◽

Vol 21 (10) ◽

pp. 1934-1945 ◽

Cited By ~ 248

Author(s):

Nicholas B. Turk-Browne ◽

Brian J. Scholl ◽

Marvin M. Chun ◽

Marcia K. Johnson

Keyword(s):

Statistical Learning ◽

Medial Temporal Lobe ◽

Temporal Cortex ◽

Occipital Cortex ◽

Relational Memory ◽

Neural Responses ◽

Statistical Structure ◽

Efficient Detection ◽

Statistical Regularities ◽

Lateral Occipital Cortex

Our environment contains regularities distributed in space and time that can be detected by way of statistical learning. This unsupervised learning occurs without intent or awareness, but little is known about how it relates to other types of learning, how it affects perceptual processing, and how quickly it can occur. Here we use fMRI during statistical learning to explore these questions. Participants viewed statistically structured versus unstructured sequences of shapes while performing a task unrelated to the structure. Robust neural responses to statistical structure were observed, and these responses were notable in four ways: First, responses to structure were observed in the striatum and medial temporal lobe, suggesting that statistical learning may be related to other forms of associative learning and relational memory. Second, statistical regularities yielded greater activation in category-specific visual regions (object-selective lateral occipital cortex and word-selective ventral occipito-temporal cortex), demonstrating that these regions are sensitive to information distributed in time. Third, evidence of learning emerged early during familiarization, showing that statistical learning can operate very quickly and with little exposure. Finally, neural signatures of learning were dissociable from subsequent explicit familiarity, suggesting that learning can occur in the absence of awareness. Overall, our findings help elucidate the underlying nature of statistical learning.

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