Functioning of Circuits Connecting Thalamus and Cortex

Sherman, S. Murray

doi:10.1002/cphy.c160032

Cited by 131 publications

(119 citation statements)

References 173 publications

(175 reference statements)

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“…Our proposal that working memory is jointly stored between thalamus and cortex owes much to the FROST model (Ashby et al, 2005). Our picture of thalamic relays is inspired by the work of Sherman and Guillery as well as others on the anatomy of thalamo-cortical connections (McFarland and Haber, 2002;Sherman, 2017). Our suggestion that the basal ganglia provides control over thalamo-cortical memory structures via inhibition and disinhibition of the thalamus is similar to that of O'Reilly and Frank (O'Reilly and Frank, 2006), and of (Stocco et al, 2010), as well as (Stewart et al, 2010).…”

Section: Relations With Other Proposalsmentioning

confidence: 94%

“…For example, visual information from the retina is transmitted to the primary visual cortex via relay cells in the lateral geniculate nucleus (LGN) of the thalamus. First order relays like the LGN constitute only a small proportion of the volume of the thalamus in primates (Sherman, 2017). In fact, it seems that every cortical region receives projections from and sends projections to the thalamus.…”

Section: Sherman's "Thalamic Higher Order Relays"mentioning

confidence: 99%

“…As we detail below, the crucial element in each of these circuits will be a model for a set of gateable thalamic higher-order relays. A growing body of anatomical and physiological evidence supports the idea that 'higher order relays' in the thalamus provide a means for relaying information among cortical areas (Mitchell et al, 2014;Sherman, 2017). Furthermore, recent evidence has bolstered the view that the persistent storage of information in working memory is mediated by cortico-thalamo-cortical loops, rather than solely via recurrent activation within the cortex itself (Bolkan et al, 2017;Guo et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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How thalamic relays might orchestrate supervised deep training and symbolic computation in the brain

Marblestone

2018

Preprint

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The thalamus appears to be involved in the flexible routing of information among cortical areas, yet the computational implications of such routing are only beginning to be explored. Here we create a connectionist model of how selectively gated cortico-thalamo-cortical relays could underpin both symbolic and sub-symbolic computations. We first show how gateable relays can be used to create a Dynamically Partitionable Auto-Associative Network (DPAAN) (Hayworth, 2012) consisting of a set of cross-connected cortical memory buffers. All buffers and relays in a DPAAN are trained simultaneously to have a common set of stable attractor states that become the symbol vocabulary of the DPAAN. We show via simulations that such a DPAAN can support operations necessary for syntactic rule-based computation, namely buffer-to-buffer copying and equality detection. We then provide each DPAAN module with a multilayer input network trained to map sensory inputs to the DPAAN's symbol vocabulary, and demonstrate how gateable thalamic relays can provide recall and clamping operations to train this input network by Contrastive Hebbian Learning (CHL) (Xie and Seung, 2003). We suggest that many such DPAAN modules may exist at the highest levels of the brain's sensory hierarchies and show how a joint snapshot of the contents of multiple DPAAN modules can be stored as a declarative memory in a simple model of the hippocampus. We speculate that such an architecture might first have been 'discovered' by evolution as a means to bootstrap learning of more meaningful cortical representations feeding the striatum, eventually leading to a system that could support symbolic computation. Our model serves as a bridging hypothesis for linking controllable thalamo-cortical information routing with computations that could underlie aspects of both learning and symbolic reasoning in the brain.

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Section: Relations With Other Proposalsmentioning

confidence: 94%

Section: Sherman's "Thalamic Higher Order Relays"mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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How thalamic relays might orchestrate supervised deep training and symbolic computation in the brain

Marblestone

2018

Preprint

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“…The thalamus and habenula are glutamatergic regions that derive from a single progenitor domain, prosomere 2 (Watson et al, 2012). The thalamus is a sensory relay centre, and part of the cortico-subcortical loops that process sensorimotor information and produce goal-directed behaviours (Sherman, 2017). The habenula controls reward-and aversion-driven behaviours by connecting cortical and subcortical regions with the monoamine system in the brainstem (Benekareddy et al, 2018;Hikosaka, 2010).…”

Section: Introductionmentioning

confidence: 99%

TCF7L2 regulates postmitotic differentiation programs and excitability patterns in the thalamus

Lipiec

Koziński

Zajkowski

et al. 2019

Preprint

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StatementThe study describes a role of TCF7L2 in neuronal differentiation of thalamic glutamatergic neurons at two developmental stages, highlighting its involvement in the postnatal establishment of critical thalamic electrophysiological features. AbstractNeuronal phenotypes are controlled by terminal selector transcription factors in invertebrates, but few examples of such regulators have been provided in vertebrates. TCF7L2 has been identified as a regulator of efferent outgrowth in the thalamus and habenula. We used a complete and conditional knockout of Tcf7l2 in mice to investigate the hypothesis that TCF7L2 plays a dual role in thalamic neuron differentiation and functions as a terminal selector. Connectivity and cell clustering was disrupted in the thalamo-habenular region in Tcf7l2 -/embryos. The expression of subregional thalamic and habenular transcription factors was lost and region-specific cell migration and axon guidance genes were downregulated. In mice with postnatal Tcf7l2 knockout, the induction of genes that confer terminal electrophysiological features of thalamic neurons was impaired. Many of these genes proved to be TCF7L2 direct targets. The role of TCF7L2 in thalamic terminal selection was functionally confirmed by impaired firing modes in thalamic neurons in the mutant mice.These data corroborate the existence of master regulators in the vertebrate brain that maintain regional transcriptional network, control stage-specific genetic programs and induce terminal selection.of the mice colony, and Kacper Posyniak for assistance with sample staining and acquisition.

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“…Sherman, 2017). To determine the nature of PreS/RSC afferents, we determined paired-pulse 209 ratios (PPRs) of TRN-and ATN+-EPSCs.…”

mentioning

confidence: 99%

A thalamic reticular circuit for head direction cell tuning and spatial navigation

Vantomme

Rovó

Cardis

et al. 2019

Preprint

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A thalamic reticular circuit 1 for head direction cell tuning 2 and spatial navigation 3 4 Summary 11To navigate in space, an animal must reference external sensory landmarks to the spatial 12 orientation of its body and head. Circuit and synaptic mechanisms that integrate external cues 13 with internal head-direction (HD) signals to drive navigational behavior remain, however, poorly 14 described. We identify an excitatory synaptic projection from the presubiculum and retrosplenial 15 cortex to the anterodorsalmost sector of the thalamic reticular nucleus (TRN), so far classically 16 implied in gating sensory information flow. Projections to TRN showed driver characteristics and 17 involved AMPA/NMDA-type glutamate receptors that initiated TRN cell burst discharge and 18 feedforward inhibition of anterior thalamic nuclei, where HD-tuned cells relevant for egocentric 19 navigation reside. Chemogenetic anterodorsal TRN inhibition broadened the tuning of thalamic 20 HD cells and compromised egocentric search strategies in the Morris water maze. Besides 21 sensory gating, TRN-dependent thalamic inhibition is an integral part of limbic navigational circuits 22to recruit HD-cell-dependent search strategies during spatial navigation. 23 P a g e | 3 (RSC) (Clark et al., 2010). Both areas are reciprocally connected (van Groen and Wyss, 1990) 60 and receive afferents from ATN, primary and secondary visual cortex, integrating information 61 relevant for egocentric and allocentric, external cue-guided, navigation (Dumont and Taube, 2015; 62 Clark et al., 2018;Mitchell et al., 2018;Simonnet and Fricker, 2018). Behaviorally, lesion of dPreS 63 compromises rapid orienting behaviors based on landmarks (Yoder et al., 2019), whereas RSC 64 lesions lead to multiple deficits in spatial navigation and memory formation (Clark et al., 2018; 65 Mitchell et al., 2018). Although there is evidence for a topographically organized cortical feedback 66 from RSC to rat and monkey anterodorsal TRN (Cornwall et al., 1990;Lozsádi, 1994; Zikopoulos 67 and Barbas, 2007), the nature of this cortico-thalamic communication has never been 68 characterized. Indeed, current models of HD circuits involving ATN, dPreS and RSC (Dumont 69 and Taube, 2015;Peyrache et al., 2017;Simonnet and Fricker, 2018; Perry and Mitchell, 2019) 70 and of the brain's 'limbic ' navigational system (Bubb et al., 2017) largely disregard a functionally 71 integrated TRN. In spite of this gap of knowledge, the notion of a limbic anterior TRN has been 72 proposed recently (Zikopoulos and Barbas, 2012;Halassa et al., 2014). 73In this study, we combined tracing techniques, in vitro and in vivo electrophysiological recordings 74 together with a spatial navigation task to probe the synaptic integration and the function of TRN 75 in the communication between PreS, RSC and ATN. 76 77 Results 78 RSC and PreS send topographically organized projections to ATN and TRN 79To determine afferent projection to the anterodorsal portion of the TRN, we injected small volumes 80 (5...

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Functioning of Circuits Connecting Thalamus and Cortex

Cited by 131 publications

References 173 publications

How thalamic relays might orchestrate supervised deep training and symbolic computation in the brain

How thalamic relays might orchestrate supervised deep training and symbolic computation in the brain

TCF7L2 regulates postmitotic differentiation programs and excitability patterns in the thalamus

A thalamic reticular circuit for head direction cell tuning and spatial navigation

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