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The mediodorsal nucleus of the thalamus amplifies the functional connectivity of the prefrontal cortex, thereby sustaining cortical representations of rule sets without relaying categorical information. Attention, larger role for thalamus The thalamus has long been associated with relay functions, transferring information to and from cortical processing regions. But recent data suggest there is a large diversity of connectivity between the thalamus and cortex, perhaps also reflecting more functional diversity. Here, Michael Halassa and colleagues find evidence that the thalamus can maintain rule representations and amplify local connectivity to guide attention, but does so without relaying categorical information. This modulation of cortical connectivity suggests that the thalamus may play a larger role in cognitive processes than previously thought. Elsewhere in this issue, Karel Svoboda and colleagues investigate persistent neural activity maintenance for motor planning and show that, in mice, neurons in parts of the thalamus connected to the anterior lateral motor cortex show persistent delay activity that predicted their direction of movement. Although interactions between the thalamus and cortex are critical for cognitive function 1 , 2 , 3 , the exact contribution of the thalamus to these interactions remains unclear. Recent studies have shown diverse connectivity patterns across the thalamus 4 , 5 , but whether this diversity translates to thalamic functions beyond relaying information to or between cortical regions 6 is unknown. Here we show, by investigating the representation of two rules used to guide attention in the mouse prefrontal cortex (PFC), that the mediodorsal thalamus sustains these representations without relaying categorical information. Specifically, mediodorsal input amplifies local PFC connectivity, enabling rule-specific neural sequences to emerge and thereby maintain rule representations. Consistent with this notion, broadly enhancing PFC excitability diminishes rule specificity and behavioural performance, whereas enhancing mediodorsal excitability improves both. Overall, our results define a previously unknown principle in neuroscience; thalamic control of functional cortical connectivity. This function, which is dissociable from categorical information relay, indicates that the thalamus has a much broader role in cognition than previously thought.

Interactions between the mediodorsal thalamus and the prefrontal cortex are critical for cognition. Studies in humans indicate that these interactions may resolve uncertainty in decision-making 1 , but the precise mechanisms are unknown. Here we identify two distinct mediodorsal projections to the prefrontal cortex that have complementary mechanistic roles in decision-making under uncertainty. Specifically, we found that a dopamine receptor (D2)-expressing projection amplifies prefrontal signals when task inputs are sparse and a kainate receptor (GRIK4) expressing-projection suppresses prefrontal noise when task inputs are dense but conflicting. Collectively, our data suggest that there are distinct brain mechanisms for handling uncertainty due to low signals versus uncertainty due to high noise, and provide a mechanistic entry point for correcting decision-making abnormalities in disorders that have a prominent prefrontal component 2 – 6 . Two different cell types in the mediodorsal thalamus have complementary roles in decision-making, with one type of mediodorsal projection amplifying prefrontal activity under low signal levels and one type suppressing it under high noise levels.

The authors trained mice to attend to or suppress vision based on behavioral context and show, through novel and established techniques, that changes in visual gain rely on tunable feedforward inhibition of visual thalamus via innervating thalamic reticular neurons; these findings introduce a subcortical model of attention in which modality-specific thalamic reticular subnetworks mediate top-down and context-dependent control of sensory selection. Subcortical sensory selection The prefrontal cortex is thought to regulate attention to sensory stimuli through top-down control of sensory cortical areas. Here, Michael Halassa and colleagues trained mice to attend to the appropriate stimulus by selecting between two competing auditory and visual stimuli. Performance on this task required the prelimbic cortex, but not the anterior cingulate cortex (ACC) or the lateral orbitofrontal cortex (OFC), and involved prelimbic cortex interactions with the visual thalamic reticular nucleus (visTRN) rather than with sensory cortex. They provide evidence that the visTRN controls visual thalamic gain through feedforward inhibition of the lateral geniculate nucleus, thereby selecting the appropriate input for further processing. These findings support a subcortical model of sensory selection in which modality-specific thalamic reticular subnetworks mediate top-down control of sensory thalamic gain. How the brain selects appropriate sensory inputs and suppresses distractors is unknown. Given the well-established role of the prefrontal cortex (PFC) in executive function 1 , its interactions with sensory cortical areas during attention have been hypothesized to control sensory selection 2 , 3 , 4 , 5 . To test this idea and, more generally, dissect the circuits underlying sensory selection, we developed a cross-modal divided-attention task in mice that allowed genetic access to this cognitive process. By optogenetically perturbing PFC function in a temporally precise window, the ability of mice to select appropriately between conflicting visual and auditory stimuli was diminished. Equivalent sensory thalamocortical manipulations showed that behaviour was causally dependent on PFC interactions with the sensory thalamus, not sensory cortex. Consistent with this notion, we found neurons of the visual thalamic reticular nucleus (visTRN) to exhibit PFC-dependent changes in firing rate predictive of the modality selected. visTRN activity was causal to performance as confirmed by bidirectional optogenetic manipulations of this subnetwork. Using a combination of electrophysiology and intracellular chloride photometry, we demonstrated that visTRN dynamically controls visual thalamic gain through feedforward inhibition. Our experiments introduce a new subcortical model of sensory selection, in which the PFC biases thalamic reticular subnetworks to control thalamic sensory gain, selecting appropriate inputs for further processing.

A subset of children with autism spectrum disorder appear to show an improvement in their behavioural symptoms during the course of a fever, a sign of systemic inflammation 1 , 2 . Here we elucidate the molecular and neural mechanisms that underlie the beneficial effects of inflammation on social behaviour deficits in mice. We compared an environmental model of neurodevelopmental disorders in which mice were exposed to maternal immune activation (MIA) during embryogenesis 3 , 4 with mouse models that are genetically deficient for contactin-associated protein-like 2 ( Cntnap2 ) 5 , fragile X mental retardation-1 ( Fmr1 ) 6 or Sh3 and multiple ankyrin repeat domains 3 ( Shank3 ) 7 . We establish that the social behaviour deficits in offspring exposed to MIA can be temporarily rescued by the inflammatory response elicited by the administration of lipopolysaccharide (LPS). This behavioural rescue was accompanied by a reduction in neuronal activity in the primary somatosensory cortex dysgranular zone (S1DZ), the hyperactivity of which was previously implicated in the manifestation of behavioural phenotypes associated with offspring exposed to MIA 8 . By contrast, we did not observe an LPS-induced rescue of social deficits in the monogenic models. We demonstrate that the differences in responsiveness to the LPS treatment between the MIA and the monogenic models emerge from differences in the levels of cytokine production. LPS treatment in monogenic mutant mice did not induce amounts of interleukin-17a (IL-17a) comparable to those induced in MIA offspring; bypassing this difference by directly delivering IL-17a into S1DZ was sufficient to promote sociability in monogenic mutant mice as well as in MIA offspring. Conversely, abrogating the expression of IL-17 receptor subunit a (IL-17Ra) in the neurons of the S1DZ eliminated the ability of LPS to reverse the sociability phenotypes in MIA offspring. Our data support a neuroimmune mechanism that underlies neurodevelopmental disorders in which the production of IL-17a during inflammation can ameliorate the expression of social behaviour deficits by directly affecting neuronal activity in the central nervous system. IL-17a induced by immune activation affects cortical neural activity and promotes social interaction in a mouse model of neurodevelopmental disorders.

Developmental disabilities, including attention-deficit hyperactivity disorder (ADHD), intellectual disability (ID), and autism spectrum disorders (ASD), affect one in six children in the USA. Recently, gene mutations in patched domain containing 1 (PTCHD1) have been found in ~1% of patients with ID and ASD. Individuals with PTCHD1 deletion show symptoms of ADHD, sleep disruption, hypotonia, aggression, ASD, and ID. Although PTCHD1 is probably critical for normal development, the connection between its deletion and the ensuing behavioural defects is poorly understood. Here we report that during early post-natal development, mouse Ptchd1 is selectively expressed in the thalamic reticular nucleus (TRN), a group of GABAergic neurons that regulate thalamocortical transmission, sleep rhythms, and attention. Ptchd1 deletion attenuates TRN activity through mechanisms involving small conductance calcium-dependent potassium currents (SK). TRN-restricted deletion of Ptchd1 leads to attention deficits and hyperactivity, both of which are rescued by pharmacological augmentation of SK channel activity. Global Ptchd1 deletion recapitulates learning impairment, hyper-aggression, and motor defects, all of which are insensitive to SK pharmacological targeting and not found in the TRN-restricted deletion mouse. This study maps clinically relevant behavioural phenotypes onto TRN dysfunction in a human disease model, while also identifying molecular and circuit targets for intervention.

The thalamic reticular nucleus (TRN), the major source of thalamic inhibition, regulates thalamocortical interactions that are critical for sensory processing, attention and cognition 1 – 5 . TRN dysfunction has been linked to sensory abnormality, attention deficit and sleep disturbance across multiple neurodevelopmental disorders 6 – 9 . However, little is known about the organizational principles that underlie its divergent functions. Here we performed an integrative study linking single-cell molecular and electrophysiological features of the mouse TRN to connectivity and systems-level function. We found that cellular heterogeneity in the TRN is characterized by a transcriptomic gradient of two negatively correlated gene-expression profiles, each containing hundreds of genes. Neurons in the extremes of this transcriptomic gradient express mutually exclusive markers, exhibit core or shell-like anatomical structure and have distinct electrophysiological properties. The two TRN subpopulations make differential connections with the functionally distinct first-order and higher-order thalamic nuclei to form molecularly defined TRN–thalamus subnetworks. Selective perturbation of the two subnetworks in vivo revealed their differential role in regulating sleep. In sum, our study provides a comprehensive atlas of TRN neurons at single-cell resolution and links molecularly defined subnetworks to the functional organization of thalamocortical circuits. A study integrating single-cell RNA-sequencing and electrophysiology data shows that in mouse, the cellular repertoire of the thalamic reticular nucleus is characterized by a transcriptomic gradient defined at its extremes by mutually exclusive expression of Spp1 and Ecel1 , providing insights into the organizational principles underlying the divergent functions of this brain region.

Human decision-making involves model-free and model-based reinforcement learning (RL) strategies, largely implemented by prefrontal-striatal circuits. Combining human brain imaging with neural network modelling in a probabilistic reversal learning task, we identify a unique role for the mediodorsal thalamus (MD) in arbitrating between RL strategies. While both dorsal PFC and the striatum support rule switching, the former does so when subjects predominantly adopt model-based strategy, and the latter model-free. The lateral and medial subdivisions of MD likewise engage these modes, each with distinct PFC connectivity. Notably, prefrontal transthalamic processing increases during the shift from stable rule use to model-based updating, with model-free updates at intermediate levels. Our CogLinks model shows that model-free strategies emerge when prefrontal-thalamic mechanisms for context inference fail, resulting in a slower overwriting of prefrontal strategy representations - a phenomenon we empirically validate with fMRI decoding analysis. These findings reveal how prefrontal transthalamic pathways implement flexible RL-based cognition. The mediodorsal thalamus (MD) is central to flexible decision-making. Here, the authors identify MD’s unique roles in arbitrating between different reinforcement learning strategies through prefrontal-striatal brain circuits.

Low-threshold (T-type) Ca(2+) channels encoded by the Ca(V)3 genes endow neurons with oscillatory properties that underlie slow waves characteristic of the non-rapid eye movement (NREM) sleep EEG. Three Ca(V)3 channel subtypes are expressed in the thalamocortical (TC) system, but their respective roles for the sleep EEG are unclear. Ca(V)3.3 protein is expressed abundantly in the nucleus reticularis thalami (nRt), an essential oscillatory burst generator. We report the characterization of a transgenic Ca(V)3.3(-/-) mouse line and demonstrate that Ca(V)3.3 channels are indispensable for nRt function and for sleep spindles, a hallmark of natural sleep. The absence of Ca(V)3.3 channels prevented oscillatory bursting in the low-frequency (4-10 Hz) range in nRt cells but spared tonic discharge. In contrast, adjacent TC neurons expressing Ca(V)3.1 channels retained low-threshold bursts. Nevertheless, the generation of synchronized thalamic network oscillations underlying sleep-spindle waves was weakened markedly because of the reduced inhibition of TC neurons via nRt cells. T currents in Ca(V)3.3(-/-) mice were <30% compared with those in WT mice, and the remaining current, carried by Ca(V)3.2 channels, generated dendritic [Ca(2+)](i) signals insufficient to provoke oscillatory bursting that arises from interplay with Ca(2+)-dependent small conductance-type 2 K(+) channels. Finally, naturally sleeping Ca(V)3.3(-/-) mice showed a selective reduction in the power density of the σ frequency band (10-12 Hz) at transitions from NREM to REM sleep, with other EEG waves remaining unaltered. Together, these data identify a central role for Ca(V)3.3 channels in the rhythmogenic properties of the sleep-spindle generator and provide a molecular target to elucidate the roles of sleep spindles for brain function and development.

The correlation between sleep integrity and attentional performance is normally interpreted as poor sleep causing impaired attention. Here, we provide an alternative explanation for this correlation: common thalamic circuits regulate sensory processing across sleep and attention, and their disruption may lead to correlated dysfunction. Using multi-electrode recordings in mice, we find that rate and rhythmicity of thalamic reticular nucleus (TRN) neurons are predictive of their functional organization in sleep and suggestive of their participation in sensory processing across states. Surprisingly, TRN neurons associated with spindles in sleep are also associated with alpha oscillations during attention. As such, we propose that common thalamic circuit principles regulate sensory processing in a state-invariant manner and that in certain disorders, targeting these circuits may be a more viable therapeutic strategy than considering individual states in isolation.

Prefrontal cortical neurons play essential roles in performing rule-dependent tasks and working memory-based decision making. Motivated by PFC recordings of task-performing mice, we developed an excitatory–inhibitory spiking recurrent neural network (SRNN) to perform a rule-dependent two-alternative forced choice (2AFC) task. We imposed several important biological constraints onto the SRNN and adapted spike frequency adaptation (SFA) and SuperSpike gradient methods to train the SRNN efficiently. The trained SRNN produced emergent rule-specific tunings in single-unit representations, showing rule-dependent population dynamics that resembled experimentally observed data. Under various test conditions, we manipulated the SRNN parameters or configuration in computer simulations, and we investigated the impacts of rule-coding error, delay duration, recurrent weight connectivity and sparsity, and excitation/inhibition (E/I) balance on both task performance and neural representations. Overall, our modeling study provides a computational framework to understand neuronal representations at a fine timescale during working memory and cognitive control and provides new experimentally testable hypotheses in future experiments.