Thalamocortical contributions to cognitive task activity

Abstract

Thalamocortical interaction is a ubiquitous functional motif in the mammalian brain. Previously (Hwang et al., 2021), we reported that lesions to network hubs in the human thalamus are associated with multi-domain behavioral impairments in language, memory, and executive functions. Here we show how task-evoked thalamic activity are organized to support these broad cognitive abilities. We analyzed functional MRI data from human subjects that performed 127 tasks encompassing a broad range of cognitive representations. We first investigated the spatial organization of task-evoked activity and found a basis set of activity patterns evoked to support processing needs of each task. Specifically, the anterior, medial, and posterior-medial thalamus exhibit hub-like activity profiles that are suggestive of broad functional participation. These thalamic task hubs overlapped with network hubs interlinking cortical systems. To further determine the cognitive relevance of thalamic activity and thalamocortical functional connectivity, we built a data-driven thalamocortical model to test whether thalamic activity can be used to predict cortical task activity. The thalamocortical model predicted task-specific cortical activity patterns, and outperformed comparison models built on cortical, hippocampal, and striatal regions. Simulated lesions to low-dimensional, multi-task thalamic hub regions impaired task activity prediction. This simulation result was further supported by profiles of neuropsychological impairments in human patients with focal thalamic lesions. In summary, our results suggest a general organizational principle of how the human thalamocortical system supports cognitive task activity.

Thalamocortical contributions to hierarchical cognitive control

“…Through this converging input, thalamic neurons extract a summary signal from multiple converging cortical inputs, encoding a low-dimensional, compressed representation abstracted from the high-dimensional inputs. This observation is further consistent with our prior fMRI studies, where we found that relative to the cortex, the thalamus encodes low-dimensional structures of cognitive activity (Hwang et al, 2022), and that thalamic subregions showing the strongest context coding also exhibit converging connectivity (hub-like connectivity) with multiple frontoparietal structures (Hwang et al, 2017, 2021).…”

“…Specifically, the anterior, medial, and posterior thalamus exhibit strong converging connectivity with multiple frontal-parietal systems that have been implicated in control-related functions (Hwang et al, 2017). The behavioral significance of this thalamocortical connectivity profile is further affirmed by recent functional neuroimaging studies (Chen et al, 2023;Hwang et al, 2022) and lesion evidence (Hwang et al, 2021(Hwang et al, , 2022. However, it remains unclear how thalamocortical connectivity supports hierarchical cognitive control.…”

A detailed spatio-temporal atlas of the white matter tracts for the fetal brain

“…The thalamocortical radiations are essential for transmitting information and help regulate cortical arousal and consciousness. Moreover, through their connections with different cortical regions, they are involved in higher-order cognitive functions [82]. Our work reconstructed thalamic radiations using the whole thalamus as a starting region and the cortical targets as the end regions.…”

Cerebellar-driven cortical dynamics enable task acquisition, switching and consolidation

“…In future work it would be of interest to compare different mechanisms by which the cerebellum may realise context-dependent processing; for example, a recent study has suggested that dendritic gating via cerebellar interneurons may perform this role 72 . Moreover, recent observations suggest that the cerebellar-driven thalamus enables context-dependent responses in the cortex for movement initiation 51,56 and cognitive tasks 73 . Indeed, our work suggests that fast context-switching is easier to incorporate in the relatively simple, divergent and rapidly learnable feedforward architecture of the cerebellum compared to the highly intricate cortical RNNs with weak plasticity.…”