Age-related differences in the intrinsic connectivity of the hippocampus and ventral temporal lobe in autistic individuals

Introduction

Although memory challenges in autistic individuals have been characterized recently, the functional connectivity of the hippocampus and ventral temporal lobe, two structures important for episodic and semantic memory functions, are poorly understood in autistic individuals. Moreover, age-related differences in the functional connectivity associated with these two memory networks are unrevealed.

Methods

The current study investigated age-related differences in intrinsic connectivity of the hippocampal and ventral temporal lobe (vTL) memory networks in well-matched ASD (n = 73; age range: 10.23-55.40 years old) and Non-ASD groups (n = 74; age range: 10.46-56.20 years old) from the open dataset ABIDE-I. Both theory-driven ROI-to-ROI approach and exploratory seed-based whole-brain approach were used.

Results and discussion

Our findings revealed reduced connectivity in ASD compared to Non-ASD peers, as well as an age-related reduction in the connectivity of hippocampal and vTL networks with triple networks, namely, the default mode network (DMN), the central executive network (CEN), and the salience network (SN), potentially underpinning their challenges in memory, language, and social functions. However, we did not observe reliable differences in age-related effects between the ASD and Non-ASD groups. Our study underscores the importance of understanding memory network dysfunctions in ASD across the lifespan to inform educational and clinical practices.

Decoding semantic representations in mind and brain

A key goal for cognitive neuroscience is to understand the neurocognitive systems that support semantic memory. Recent multivariate analyses of neuroimaging data have contributed greatly to this effort, but the rapid development of these novel approaches has made it difficult to track the diversity of findings and to understand how and why they sometimes lead to contradictory conclusions. We address this challenge by reviewing cognitive theories of semantic representation and their neural instantiation. We then consider contemporary approaches to neural decoding and assess which types of representation each can possibly detect. The analysis suggests why the results are heterogeneous and identifies crucial links between cognitive theory, data collection, and analysis that can help to better connect neuroimaging to mechanistic theories of semantic cognition.

Domain-specific connectivity drives the organization of object knowledge in the brain

The goal of this chapter is to review neuropsychological and functional MRI findings that inform a theory of the causes of functional specialization for semantic categories within occipito-temporal cortex-the ventral visual processing pathway. The occipito-temporal pathway supports visual object processing and recognition. The theoretical framework that drives this review considers visual object recognition through the lens of how "downstream" systems interact with the outputs of visual recognition processes. Those downstream processes include conceptual interpretation, grasping and object use, navigating and orienting in an environment, physical reasoning about the world, and inferring future actions and the inner mental states of agents. The core argument of this chapter is that innately constrained connectivity between occipito-temporal areas and other regions of the brain is the basis for the emergence of neural specificity for a limited number of semantic domains in the brain.

Category-specific activations depend on imaging mode, task demand, and stimuli modality: An ALE meta-analysis

The cortical organization of the semantic network has been examined extensively in neuropsychological and neuroimaging studies; however, after decades of research, several issues remain controversial. A comprehensive and systematic investigation is needed to characterize the consistent patterns of category-specific activations as well as to examine factors that contribute to the varying findings across numerous neuroimaging studies. In this study, we reviewed 113 published papers that reported category-specific activations for living or nonliving concepts from the past two decades. Using the Activation Likelihood Estimate (ALE) method, we characterized the brain regions associated with living and nonliving concepts and revealed how the observed patterns were heavily influenced by methodological factors including imaging mode, task demand, and stimuli modality. Our findings provided the most comprehensive summary of category-specific activations for living and nonliving concepts and critically revealed that these activation patterns are highly contextually dependent. This work advanced our knowledge about the organization of the cortical semantic network and provided important insights into theoretical accounts and future research directions.

From shape to meaning: Evidence for multiple fast feedforward hierarchies of concept processing in the human brain

A number of fMRI studies have provided support for the existence of multiple concept representations in areas of the brain such as the anterior temporal lobe (ATL) and inferior parietal lobule (IPL). However, the interaction among different conceptual representations remains unclear. To better understand the dynamics of how the brain extracts meaning from sensory stimuli, we conducted a human high-density electroencephalography (EEG) study in which we first trained participants to associate pseudowords with various animal and tool concepts. After training, multivariate pattern classification of EEG signals in sensor and source space revealed the representation of both animal and tool concepts in the left ATL and tool concepts within the left IPL within 250 ​ms. Finally, we used Granger Causality analyses to show that orthography-selective sensors directly modulated activity in the parietal-tool selective cluster. Together, our results provide evidence for distinct but parallel "perceptual-to-conceptual" feedforward hierarchies in the brain.

Domain-Specific Diaschisis: Lesions to Parietal Action Areas Modulate Neural Responses to Tools in the Ventral Stream

Neural responses to small manipulable objects ("tools") in high-level visual areas in ventral temporal cortex (VTC) provide an opportunity to test how anatomically remote regions modulate ventral stream processing in a domain-specific manner. Prior patient studies indicate that grasp-relevant information can be computed about objects by dorsal stream structures independently of processing in VTC. Prior functional neuroimaging studies indicate privileged functional connectivity between regions of VTC exhibiting tool preferences and regions of parietal cortex supporting object-directed action. Here we test whether lesions to parietal cortex modulate tool preferences within ventral and lateral temporal cortex. We found that lesions to the left anterior intraparietal sulcus, a region that supports hand-shaping during object grasping and manipulation, modulate tool preferences in left VTC and in the left posterior middle temporal gyrus. Control analyses demonstrated that neural responses to "place" stimuli in left VTC were unaffected by lesions to parietal cortex, indicating domain-specific consequences for ventral stream neural responses in the setting of parietal lesions. These findings provide causal evidence that neural specificity for "tools" in ventral and lateral temporal lobe areas may arise, in part, from online inputs to VTC from parietal areas that receive inputs via the dorsal visual pathway.

The Cognitive Neuroscience of Stable and Flexible Semantic Typicality

Typicality effects are among the most well-studied phenomena in the study of concepts. The classical notion of typicality is that typical concepts share many features with category co-members and few features with members of contrast categories. However, this notion was challenged by evidence that typicality is highly context dependent and not always dependent on central tendency. Dieciuc and Folstein (2019) argued that there is strong evidence for both views and that the two types of typicality effects might depend on different mechanisms. A recent theoretical framework, the controlled semantic cognition framework (Lamdon Ralph et al., 2017) strongly emphasizes the classical view, but includes mechanisms that could potentially account for both kinds of typicality. In contrast, the situated cognition framework (Barsalou, 2009b) articulates the context-dependent view. Here, we review evidence from cognitive neuroscience supporting the two frameworks. We also briefly evaluate the ability of computational models associated with the CSC to account for phenomena supporting SitCog (Rogers and McClelland, 2004). Many predictions of both frameworks are borne out by recent cognitive neuroscience evidence. While the CSC framework can at least potentially account for many of the typicality phenomena reviewed, challenges remain, especially with regard to ad hoc categories.

A unified model of human semantic knowledge and its disorders

How is knowledge about the meanings of words and objects represented in the human brain? Current theories embrace two radically different proposals: either distinct cortical systems have evolved to represent different kinds of things, or knowledge for all kinds is encoded within a single domain-general network. Neither view explains the full scope of relevant evidence from neuroimaging and neuropsychology. Here we propose that graded category-specificity emerges in some components of the semantic network through joint effects of learning and network connectivity. We test the proposal by measuring connectivity amongst cortical regions implicated in semantic representation, then simulating healthy and disordered semantic processing in a deep neural network whose architecture mirrors this structure. The resulting neuro-computational model explains the full complement of neuroimaging and patient evidence adduced in support of both domain-specific and domain-general approaches, reconciling long-standing disputes about the nature and origins of this uniquely human cognitive faculty.

Oscillatory Dynamics Supporting Semantic Cognition: MEG Evidence for the Contribution of the Anterior Temporal Lobe Hub and Modality-Specific Spokes

The "hub and spoke model" of semantic representation suggests that the multimodal features of objects are drawn together by an anterior temporal lobe (ATL) "hub", while modality-specific "spokes" capture perceptual/action features. However, relatively little is known about how these components are recruited through time to support object identification. We used magnetoencephalography to measure neural oscillations within left ATL, lateral fusiform cortex (FC) and central sulcus (CS) during word-picture matching at different levels of specificity (employing superordinate vs. specific labels) for different categories (manmade vs. animal). This allowed us to determine (i) when each site was sensitive to semantic category and (ii) whether this was modulated by task demands. In ATL, there were two phases of response: from around 100 ms post-stimulus there were phasic bursts of low gamma activity resulting in reductions in oscillatory power, relative to a baseline period, that were modulated by both category and specificity; this was followed by more sustained power decreases across frequency bands from 250 ms onwards. In the spokes, initial power increases were not stronger for specific identification, while later power decreases were stronger for specific-level identification in FC for animals and in CS for manmade objects (from around 150 ms and 200 ms, respectively). These data are inconsistent with a temporal sequence in which early sensory-motor activity is followed by later retrieval in ATL. Instead, knowledge emerges from the rapid recruitment of both hub and spokes, with early specificity and category effects in the ATL hub. The balance between these components depends on semantic category and task, with visual cortex playing a greater role in the fine-grained identification of animals and motor cortex contributing to the identification of tools.

The neural network for tool-related cognition: An activation likelihood estimation meta-analysis of 70 neuroimaging contrasts

The ability to recognize and use a variety of tools is an intriguing human cognitive function. Multiple neuroimaging studies have investigated neural activations with various types of tool-related tasks. In the present paper, we reviewed tool-related neural activations reported in 70 contrasts from 56 neuroimaging studies and performed a series of activation likelihood estimation (ALE) meta-analyses to identify tool-related cortical circuits dedicated either to general tool knowledge or to task-specific processes. The results indicate the following: (a) Common, task-general processing regions for tools are located in the left inferior parietal lobule (IPL) and ventral premotor cortex; and (b) task-specific regions are located in superior parietal lobule (SPL) and dorsal premotor area for imagining/executing actions with tools and in bilateral occipito-temporal cortex for recognizing/naming tools. The roles of these regions in task-general and task-specific activities are discussed with reference to evidence from neuropsychology, experimental psychology and other neuroimaging studies.

Development of Tool Representations in the Dorsal and Ventral Visual Object Processing Pathways

Tools represent a special class of objects, because they are processed across both the dorsal and ventral visual object processing pathways. Three core regions are known to be involved in tool processing: the left posterior middle temporal gyrus, the medial fusiform gyrus (bilaterally), and the left inferior parietal lobule. A critical and relatively unexplored issue concerns whether, in development, tool preferences emerge at the same time and to a similar degree across all regions of the tool-processing network. To test this issue, we used functional magnetic resonance imaging to measure the neural amplitude, peak location, and the dispersion of tool-related neural responses in the youngest sample of children tested to date in this domain (ages 4-8 years). We show that children recruit overlapping regions of the adult tool-processing network and also exhibit similar patterns of co-activation across the network to adults. The amplitude and co-activation data show that the core components of the tool-processing network are established by age 4. Our findings on the distributions of peak location and dispersion of activation indicate that the tool network undergoes refinement between ages 4 and 8 years.