scholarly journals Large-scale Functional Integration, Rather than Functional Dissociation along Dorsal and Ventral Streams, Underlies Visual Perception and Action

2020 ◽  
Vol 32 (5) ◽  
pp. 847-861 ◽  
Author(s):  
Dipanjan Ray ◽  
Nilambari Hajare ◽  
Dipanjan Roy ◽  
Arpan Banerjee

Visual dual-stream theory posits that two distinct neural pathways of specific functional significance originate from primary visual areas and reach the inferior temporal (ventral) and posterior parietal areas (dorsal). However, there are several unresolved questions concerning the fundamental aspects of this theory. For example, is the functional dissociation between ventral and dorsal stream driven by features in input stimuli or is it driven by categorical differences between visuoperceptual and visuomotor functions? Is the dual stream rigid or flexible? What is the nature of the interactions between the two streams? We addressed these questions using fMRI recordings on healthy human volunteers and employing stimuli and tasks that can tease out the divergence between visuoperceptual and visuomotor variants of dual-stream theory. fMRI scans were repeated after seven practice sessions that were conducted in a non-MRI environment to investigate the effects of neuroplasticity. Brain activation analysis supports an input-based functional dissociation and existence of context-dependent neuroplasticity in dual-stream areas. Intriguingly, premotor cortex activation was observed in the position perception task and distributed deactivated regions were observed in all perception tasks, thus warranting a network-level analysis. Dynamic causal modeling analysis incorporating activated and deactivated brain areas during perception tasks indicates that the brain dynamics during visual perception and actions could be interpreted within the framework of predictive coding. Effectively, the network-level findings point toward the existence of more intricate context-driven functional networks selective of “what” and “where” information rather than segregated streams of processing along ventral and dorsal brain regions.

2019 ◽  
Author(s):  
Dipanjan Ray ◽  
Nilambari Hajare ◽  
Dipanjan Roy ◽  
Arpan Banerjee

AbstractVisual dual stream theory posits that two distinct neural pathways of specific functional significance originate from primary visual areas and reach the inferior temporal (ventral) and posterior parietal areas (dorsal). However, there are several unresolved questions concerning the fundamental aspects of this theory. For example, is the functional dissociation between ventral and dorsal stream driven by features in input stimuli or is it driven by categorical differences between visuo-perceptual and visuo-motor functions? Is the dual stream rigid or flexible? What is the nature of the interactions between two streams? We addressed these questions using fMRI recordings on healthy human volunteers and employing stimuli and tasks that can tease out the divergence between visuo-perceptual and visuo-motor models of dual stream theory. fMRI scans were repeated after seven practice sessions that were conducted in a non-MRI environment to investigate the effects of neuroplasticity. Brain activation analysis supports an input-based functional dissociation and existence of context-dependent neuroplasticity in dual stream areas. Intriguingly, premotor cortex activation was observed in the position perception task and distributed deactivated regions were observed in all perception tasks thus, warranting a network level analysis. Dynamic causal modelling (DCM) analysis incorporating activated and deactivated brain areas during perception tasks indicates that the brain dynamics during visual perception and actions could be interpreted within the framework of predictive coding. Effectively, the network level findings point towards the existence of more intricate context-driven functional networks selective of “what” and “where” information rather than segregated streams of processing along ventral and dorsal brain regions.


2017 ◽  
Author(s):  
Cameron Parro ◽  
Matthew L Dixon ◽  
Kalina Christoff

AbstractCognitive control mechanisms support the deliberate regulation of thought and behavior based on current goals. Recent work suggests that motivational incentives improve cognitive control, and has begun to elucidate the brain regions that may support this effect. Here, we conducted a quantitative meta-analysis of neuroimaging studies of motivated cognitive control using activation likelihood estimation (ALE) and Neurosynth in order to delineate the brain regions that are consistently activated across studies. The analysis included functional neuroimaging studies that investigated changes in brain activation during cognitive control tasks when reward incentives were present versus absent. The ALE analysis revealed consistent recruitment in regions associated with the frontoparietal control network including the inferior frontal sulcus (IFS) and intraparietal sulcus (IPS), as well as consistent recruitment in regions associated with the salience network including the anterior insula and anterior mid-cingulate cortex (aMCC). A large-scale exploratory meta-analysis using Neurosynth replicated the ALE results, and also identified the caudate nucleus, nucleus accumbens, medial thalamus, inferior frontal junction/premotor cortex (IFJ/PMC), and hippocampus. Finally, we conducted separate ALE analyses to compare recruitment during cue and target periods, which tap into proactive engagement of rule-outcome associations, and the mobilization of appropriate viscero-motor states to execute a response, respectively. We found that largely distinct sets of brain regions are recruited during cue and target periods. Altogether, these findings suggest that flexible interactions between frontoparietal, salience, and dopaminergic midbrain-striatal networks may allow control demands to be precisely tailored based on expected value.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ni Shu ◽  
Yaou Liu ◽  
Yunyun Duan ◽  
Kuncheng Li

The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. However, few studies have investigated the hemispheric asymmetries of the human brain from the perspective of the network model, and little is known about the asymmetries of the connection patterns of brain regions, which may reflect the functional integration and interaction between different regions. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 72 right-handed healthy adult subjects. We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography. To investigate the hemispheric asymmetries of the brain, statistical analyses were performed to reveal the brain regions with significant differences between bilateral topological properties, such as degree of connectivity, characteristic path length, and betweenness centrality. Furthermore, local structural connections were also investigated to examine the local asymmetries of some specific white matter tracts. From the perspective of both the global and local connection patterns, we identified the brain regions with hemispheric asymmetries. Combined with the previous studies, we suggested that the topological asymmetries in the anatomical network may reflect the functional lateralization of the human brain.


2015 ◽  
Vol 112 (28) ◽  
pp. E3719-E3728 ◽  
Author(s):  
Paul Hoffman ◽  
Matthew A. Lambon Ralph ◽  
Anna M. Woollams

The goal of cognitive neuroscience is to integrate cognitive models with knowledge about underlying neural machinery. This significant challenge was explored in relation to word reading, where sophisticated computational-cognitive models exist but have made limited contact with neural data. Using distortion-corrected functional MRI and dynamic causal modeling, we investigated the interactions between brain regions dedicated to orthographic, semantic, and phonological processing while participants read words aloud. We found that the lateral anterior temporal lobe exhibited increased activation when participants read words with irregular spellings. This area is implicated in semantic processing but has not previously been considered part of the reading network. We also found meaningful individual differences in the activation of this region: Activity was predicted by an independent measure of the degree to which participants use semantic knowledge to read. These characteristics are predicted by the connectionist Triangle Model of reading and indicate a key role for semantic knowledge in reading aloud. Premotor regions associated with phonological processing displayed the reverse characteristics. Changes in the functional connectivity of the reading network during irregular word reading also were consistent with semantic recruitment. These data support the view that reading aloud is underpinned by the joint operation of two neural pathways. They reveal that (i) the ATL is an important element of the ventral semantic pathway and (ii) the division of labor between the two routes varies according to both the properties of the words being read and individual differences in the degree to which participants rely on each route.


2017 ◽  
Vol 117 (5) ◽  
pp. 1959-1968 ◽  
Author(s):  
Francesca Fardo ◽  
Mikkel C. Vinding ◽  
Micah Allen ◽  
Troels Staehelin Jensen ◽  
Nanna Brix Finnerup

Cold-sensitive and nociceptive neural pathways interact to shape the quality and intensity of thermal and pain perception. Yet the central processing of cold thermosensation in the human brain has not been extensively studied. Here, we used magnetoencephalography and EEG in healthy volunteers to investigate the time course (evoked fields and potentials) and oscillatory activity associated with the perception of cold temperature changes. Nonnoxious cold stimuli consisting of Δ3°C and Δ5°C decrements from an adapting temperature of 35°C were delivered on the dorsum of the left hand via a contact thermode. Cold-evoked fields peaked at around 240 and 500 ms, at peak latencies similar to the N1 and P2 cold-evoked potentials. Importantly, cold-related changes in oscillatory power indicated that innocuous thermosensation is mediated by oscillatory activity in the range of delta (1–4 Hz) and gamma (55–90 Hz) rhythms, originating in operculo-insular cortical regions. We suggest that delta rhythms coordinate functional integration between operculo-insular and frontoparietal regions, while gamma rhythms reflect local sensory processing in operculo-insular areas. NEW & NOTEWORTHY Using magnetoencephalography, we identified spatiotemporal features of central cold processing, with respect to the time course, oscillatory profile, and neural generators of cold-evoked responses in healthy human volunteers. Cold thermosensation was associated with low- and high-frequency oscillatory rhythms, both originating in operculo-insular regions. These results support further investigations of central cold processing using magnetoencephalography or EEG and the clinical utility of cold-evoked potentials for neurophysiological assessment of cold-related small-fiber function and damage.


2019 ◽  
Author(s):  
Burcu A. Urgen ◽  
Ayse P. Saygin

AbstractVisual perception of actions is supported by a network of brain regions in the occipito-temporal, parietal, and premotor cortex in the primate brain, known as the Action Observation Network (AON). Although there is a growing body of research that characterizes the functional properties of each node of this network, the communication and direction of information flow between the nodes is unclear. According to the predictive coding account of action perception, this network is not a purely feedforward system but has feedback connections through which prediction error signals are communicated between the regions of the AON. In the present study, we investigated the effective connectivity of the AON in an experimental setting where the human subjects’ predictions about the observed agent were violated, using fMRI and Dynamical Causal Modeling (DCM). We specifically examined the influence of the lowest and highest nodes in the AON hierarchy, pSTS and ventral premotor cortex, respectively, on the middle node, inferior parietal cortex during prediction violation. Our DCM results suggest that the influence on the inferior parietal node is through a feedback connection from ventral premotor cortex during perception of actions that violate people’s predictions.


2018 ◽  
Author(s):  
Corbett Bennett ◽  
Samuel D. Gale ◽  
Marina E. Garrett ◽  
Melissa L. Newton ◽  
Edward M. Callaway ◽  
...  

SummaryHigher-order thalamic nuclei, such as the visual pulvinar, play essential roles in cortical function by connecting functionally-related cortical and subcortical brain regions. Yet a coherent framework describing pulvinar function remains elusive due to its anatomical complexity and involvement in diverse cognitive processes. Here we combined large-scale anatomical circuit mapping with high-density electrophysiological recordings to dissect a homolog of pulvinar in mice, the lateral posterior nucleus (LP). We define three broad LP subregions based on correspondence between input/output connectivity and functional properties. These subregions form corticothalamic loops biased towards ventral or dorsal stream cortical areas and contain separate representations of visual space. To reveal which input sources drive LP activity, we silenced visual cortex or superior colliculus and found they drive visual tuning properties in separate LP subregions. Thus, by specifying the driving input sources, functional properties, and downstream targets of LP circuits, our data provide a roadmap for understanding the mechanisms of higher-order thalamic function in vision.


2016 ◽  
Vol 113 (52) ◽  
pp. 15108-15113 ◽  
Author(s):  
Julius Fridriksson ◽  
Grigori Yourganov ◽  
Leonardo Bonilha ◽  
Alexandra Basilakos ◽  
Dirk-Bart Den Ouden ◽  
...  

Several dual route models of human speech processing have been proposed suggesting a large-scale anatomical division between cortical regions that support motor–phonological aspects vs. lexical–semantic aspects of speech processing. However, to date, there is no complete agreement on what areas subserve each route or the nature of interactions across these routes that enables human speech processing. Relying on an extensive behavioral and neuroimaging assessment of a large sample of stroke survivors, we used a data-driven approach using principal components analysis of lesion-symptom mapping to identify brain regions crucial for performance on clusters of behavioral tasks without a priori separation into task types. Distinct anatomical boundaries were revealed between a dorsal frontoparietal stream and a ventral temporal–frontal stream associated with separate components. Collapsing over the tasks primarily supported by these streams, we characterize the dorsal stream as a form-to-articulation pathway and the ventral stream as a form-to-meaning pathway. This characterization of the division in the data reflects both the overlap between tasks supported by the two streams as well as the observation that there is a bias for phonological production tasks supported by the dorsal stream and lexical–semantic comprehension tasks supported by the ventral stream. As such, our findings show a division between two processing routes that underlie human speech processing and provide an empirical foundation for studying potential computational differences that distinguish between the two routes.


2014 ◽  
Vol 11 (04) ◽  
pp. 245-253
Author(s):  
S. B. Eickhoff ◽  
D. Bzdok

SummaryThe links between symptomatic phenomenology of psychiatric disorders and their neurobiological pathophysiology are still understood only in fragments. While functional and structural neuroimaging methods have leveraged our knowledge of regional dysfunction in psychiatric disorders, emerging novel approaches more focused on brain networks or neural patterns promise additional forward progress. Activation likelihood estimation (ALE) performs quantitative large-scale aggregation of neuroimaging findings. Resting-state (RS) correlation captures networks of functional relationships between regions in the idling, non-goal-focused brain. In contrast, meta-analytic connectivity modeling (MACM) captures functional coupling between brain regions in the context of experimental paradigms. These methods may furthermore be exploited to provide data-driven parcellations (CBP, connectivity-based parcellation) of larger brain regions into distinct functional modules. Dynamic causal modeling (DCM), in turn, allows for the automatic selection among a set of connectional network models to delineate effective connectivity dynamics during experimental paradigms. Finally, machine learning (ML) allows for the automatic detection and prediction of diagnosis/treatment-response patterns in massive datasets. Capitalizing on this toolbox of computational modeling methods might considerably further psychiatry and thus benefit patients with mental disorders.


2020 ◽  
Vol 6 (5) ◽  
pp. eaay2739 ◽  
Author(s):  
Gabriel Castrillon ◽  
Nico Sollmann ◽  
Katarzyna Kurcyus ◽  
Adeel Razi ◽  
Sandro M. Krieg ◽  
...  

Transcranial magnetic stimulation (TMS) is a noninvasive method to modulate brain activity and behavior in humans. Still, stimulation effects substantially vary across studies and individuals, thereby restricting the large-scale application of TMS in research or clinical settings. We revealed that low-frequency stimulation had opposite impact on the functional connectivity of sensory and cognitive brain regions. Biophysical modeling then identified a neuronal mechanism underlying these region-specific effects. Stimulation of the frontal cortex decreased local inhibition and disrupted feedforward and feedback connections. Conversely, identical stimulation increased local inhibition and enhanced forward signaling in the occipital cortex. Last, we identified functional integration as a macroscale network parameter to predict the region-specific effect of stimulation in individual subjects. In summary, we revealed how TMS modulation critically depends on the connectivity profile of target regions and propose an imaging marker to improve sensitivity of noninvasive brain stimulation for research and clinical applications.


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