Publications by authors named "Emily D Grossman"

The superior temporal sulcus (STS) has a functional topography that has been difficult to characterize through traditional approaches. Automated atlas parcellations may be one solution while also being beneficial for both dimensional reduction and standardizing regions of interest, but they yield very different boundary definitions along the STS. Here we evaluate how well machine learning classifiers can correctly identify six social cognitive tasks from STS activation patterns dimensionally reduced using four popular atlases (Glasser et al.

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Observing the actions of others engages a core action observation network (AON) that includes the bilateral inferior frontal cortex (IFC), posterior superior temporal sulcus (pSTS) and inferior parietal lobule (IPL) (Caspers et al., 2010). Each region in the AON has functional properties that are heterogeneous and include representing the perceptual properties of action, predicting action outcomes and making inferences as to the goals of the actor.

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Among a variety of entities in their environment, what do humans consider alive or animate and how does this attribution of animacy promote development of more abstract levels of mentalizing? By decontextualizing the environment of bodily features, we review how physical movements give rise to perceived animacy in Heider-Simmel style animations. We discuss the developmental course of how perceived animacy shapes our interpretation of the social world, and specifically discuss when and how children transition from perceiving actions as goal-directed to attributing behaviors to unobservable mental states. This transition from a teleological stance, asserting a goal-oriented interpretation to an agent's actions, to a mentalistic stance allows older children to reason about more complex actions guided by hidden beliefs.

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With the advent of multivariate pattern analysis (MVPA) as an important analytic approach to fMRI, new insights into the functional organization of the brain have emerged. Several software packages have been developed to perform MVPA analysis, but deploying them comes with the cost of adjusting data to individual idiosyncrasies associated with each package. Here we describe PyMVPA BIDS-App, a fast and robust pipeline based on the data organization of the BIDS standard that performs multivariate analyses using powerful functionality of PyMVPA.

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Background: Multivariate pattern analysis (MVPA or pattern decoding) has attracted considerable attention as a sensitive analytic tool for investigations using functional magnetic resonance imaging (fMRI) data. With the introduction of MVPA, however, has come a proliferation of methodological choices confronting the researcher, with few studies to date offering guidance from the vantage point of controlled datasets detached from specific experimental hypotheses.

New Method: We investigated the impact of four data processing steps on support vector machine (SVM) classification performance aimed at maximizing information capture in the presence of common noise sources.

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Blind individuals commonly use verbal encoding (i.e. text-to-speech) and memory-based strategies (i.

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Robust gender differences exist in the acoustic correlates of clearly articulated speech, with females, on average, producing speech that is acoustically and phonetically more distinct than that of males. This study investigates the relationship between several acoustic correlates of clear speech and subjective ratings of vocal attractiveness. Talkers were recorded producing vowels in /bVd/ context and sentences containing the four corner vowels.

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The posterior superior temporal sulcus (pSTS) is a brain region characterized by perceptual representations of human body actions that promote the understanding of observed behavior. Increasingly, action observation is recognized as being strongly shaped by the expectations of the observer (Kilner 2011; Koster-Hale and Saxe 2013; Patel et al. 2019).

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Visual attentive tracking requires a balance of excitation and inhibition across large-scale frontoparietal cortical networks. Using methods borrowed from network science, we characterize the induced changes in network dynamics following low frequency (1 Hz) repetitive transcranial magnetic stimulation (rTMS) as an inhibitory noninvasive brain stimulation protocol delivered over the intraparietal sulcus. When participants engaged in visual tracking, we observed a highly stable network configuration of six distinct communities, each with characteristic properties in node dynamics.

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Visual processing of human movements is critical for adaptive social behavior. Cerebellar activations have been observed during biological motion discrimination in prior neuroimaging studies, and cerebellar lesions may be detrimental for this task. However, whether the cerebellum plays a causal role in biological motion discrimination has never been tested.

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Non-invasive brain stimulation safely induces persistent large-scale neural modulation in functionally connected brain circuits. Interruption models of repetitive transcranial magnetic stimulation (rTMS) capitalize on the acute impact of brain stimulation, which decays over minutes. However, rTMS also induces longer-lasting impact on cortical functions, evident by the use of multi-session rTMS in clinical population for therapeutic purposes.

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Autism Spectrum Disorder (ASD) is a developmental disorder characterized by impaired social communication, including attending to and interpreting social cues, initiating and responding to joint attention, and engaging in abstract social cognitive reasoning. Current studies emphasize a underconnectivity in ASD, particularly for brain systems that support abstract social reasoning and introspective thought. Here, we evaluate intrinsic connectivity in children with ASD, targeting brain systems that support the developmental precursors to social reasoning, namely perception of social cues and joint attention.

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The posterior extent of the human superior temporal sulcus (pSTS) is an important cortical region for detecting animacy, attributing agency to others, and decoding goal-directed behavior. Theoretical accounts attribute these cognitive skills to unique neural populations that have been difficult to identify empirically (Hein and Knight, 2008). The aim of this study is to evaluate the multivariate statistical structure of pSTS activation patterns when viewing different social cues.

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Performance in detection tasks can be improved by directing attention to task-relevant features. In this study, we evaluate the direction tuning of selective attention to motion features when observers detect point-light biological motion in noise. Feature-based attention strategy is assessed by capitalizing on the sensitivity of unattended steady-state visual-evoked potential (SSVEP) to the spreading of feature-based attention to unattended regions of space.

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The posterior STS (pSTS) is an important brain region for perceptual analysis of social cognitive cues. This study seeks to characterize the pattern of network connectivity emerging from the pSTS in three core social perception localizers: biological motion perception, gaze recognition, and the interpretation of moving geometric shapes as animate. We identified brain regions associated with all three of these localizers and computed the functional connectivity pattern between them and the pSTS using a partial correlations metric that characterizes network connectivity.

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Background: The interhemispheric competition hypothesis attributes the distribution of selective attention to a balance of mutual inhibition between homotopic, interhemispheric connections in parietal cortex (Kinsbourne 1977; Battelli et al., 2009). In support of this hypothesis, repetitive inhibitory TMS over right parietal cortex in healthy individuals rapidly induces interhemispheric imbalance in cortical activity that spreads beyond the site of stimulation (Plow et al.

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Perception of natural experiences requires allocation of attention towards features, objects, and events that are moving and changing over time. This allocation of attention is controlled by large-scale brain networks that, when damaged, cause widespread cognitive deficits. In particular, damage to ventral parietal cortex (right lateralized TPJ, STS, supramarginal and angular gyri) is associated with failures to selectively attend to and isolate features embedded within rapidly changing visual sequences (Battelli, Pascual-Leone, & Cavanagh, 2007; Husain, Shapiro, Martin, & Kennard, 1997).

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The brain systems that support motion perception are some of the most studied in the primate visual system, with apparent specialization in the middle temporal area (hMT+ in humans, MT or V5 in monkeys). Even with this specialization, it is safe to assume that the hMT+ interacts with other brain systems as visual tasks demand. Here we have measured those interactions using a specialized case of structure-from-motion, point-light biological motion.

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Motion perception is important for visually segregating and identifying objects from their surroundings, but in some cases extracting motion cues can be taxing to the human attention system. We measured the strength of feature salience required for individuals to correctly judge three types of moving events: biological motion, coherent motion, and multiple object tracking. The motion animations were embedded within a larger Gabor grid and constructed such that motion was conveyed by a salient single-feature dimension (second order) or by alternating across equisalient feature dimensions (third order).

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Single pulses of transcranial magnetic stimulation (TMS) result in distal and long-lasting oscillations, a finding directly challenging the virtual lesion hypothesis. Previous research supporting this finding has primarily come from stimulation of the motor cortex. We have used single-pulse TMS with simultaneous EEG to target seven brain regions, six of which belong to the visual system [left and right primary visual area V1, motion-sensitive human middle temporal cortex, and a ventral temporal region], as determined with functional MRI-guided neuronavigation, and a vertex "control" site to measure the network effects of the TMS pulse.

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Humans extract visual information from the world through spatial frequency (SF) channels that are sensitive to different scales of light-dark fluctuations across visual space. Using two methods, we measured human SF tuning for discriminating videos of human actions (walking, running, skipping and jumping). The first, more traditional, approach measured signal-to-noise ratio (s/n) thresholds for videos filtered by one of six Gaussian band-pass filters ranging from 4 to 128 cycles/image.

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Among the most common events in our daily lives is seeing people in action. Scientists have accumulated evidence suggesting humans may have developed specialized mechanisms for recognizing these visual events. In the current experiments, we apply the "bubbles" technique to construct space-time classification movies that reveal the key features human observers use to discriminate biological motion stimuli (point-light and stick figure walkers).

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Neuroimaging studies of biological motion perception have found a network of coordinated brain areas, the hub of which appears to be the human posterior superior temporal sulcus (STSp). Understanding the functional role of the STSp requires characterizing the response tuning of neuronal populations underlying the BOLD response. Thus far our understanding of these response properties comes from single-unit studies of the monkey anterior STS, which has individual neurons tuned to body actions, with a small population invariant to changes in viewpoint, position and size of the action being viewed.

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Motion transparency is the perception of multiple, moving surfaces within the same retinal location (for example, a ripple on the surface of a drifting stream), and is an interesting challenge to motion models because multiple velocities must be represented within the same region of space. When these motion vectors are in opposite directions, brief in duration and spatially constrained within a very local region, the result is little or no perceived motion (motion opponency). Both motion transparency and motion opponency inhibit the firing rate of single middle temporal area (MT) neurons as compared with the preferred direction alone, but neither generally influences the firing rate of primary visual cortex neurons.

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Human observers readily identify objects with moving parts, and recognize their underlying structure even when the component parts undergo complex movement. This suggests the existence of neural representations that are invariant to motion and state of articulation, which together allow our visual system to maintain 'object constancy'. Ventral temporal cortex has previously been implicated in object perception and in coding object identity, but it is unclear where this is achieved when objects undergo motion-driven shape changes.

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