Globus pallidus dynamics reveal covert strategies for behavioral inhibition

Gu, Bon-Mi; Schmidt, Robert; Berke, Joshua D.

doi:10.1101/2020.03.03.975540

Cited by 7 publications

(12 citation statements)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…SNr is a basal ganglia output nucleus, receiving converging inputs from multiple basal ganglia structures including GPe. The finding that SNr decodes behavioral output more selectively and accurately compared to GPe is consistent with the idea that SNr is closer to post-decision behavioral outputs, whereas GPe represent internal preparatory states [72].…”

Section: Decoding Behavioral Condition From Neural Activity With a Smsupporting

confidence: 84%

“…We used the spike count in the first 100 ms after the rat exited the center port to predict the behavioral condition (left or right). Further details on the surgical, experimental, and preprocessing steps can be found in [72].…”

Section: Recordings From Basal Gangliamentioning

confidence: 99%

“…For this analysis we examined 54 single units in the rat basal ganglia (18 units from globus pallidus pars externa, GPe, and 36 from the substantia nigra pars reticulata, SNr) that were recorded simultaneously during performance of a behavioral task involving rapid leftward or rightward head movements in response to cues. Details of the task are given in [72]; the analysis was restricted to trials in which a correct head movement was made. Thus, the decoding model consisted of binary logistic regression predicting trial outcome (left or right) using the single-unit spike counts as features.…”

Section: Decoding Behavioral Condition From Neural Activity With a Smmentioning

confidence: 99%

See 2 more Smart Citations

Accurate inference in parametric models reshapes neuroscientific interpretation and improves data-driven discovery

Sachdeva

Livezey

Dougherty

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

A central goal of systems neuroscience is to understand the relationships amongst constituent units in neural populations and their modulation by external factors using high-dimensional and stochastic neural recordings. Statistical models, particularly parametric models, play an instrumental role in accomplishing this goal, because their fitted parameters can provide insight into the underlying biological processes that generated the data. However, extracting conclusions from a parametric model requires that it is fit using an inference procedure capable of selecting the correct parameters and properly estimating their values. Traditional approaches to parameter inference have been shown to suffer from failures in both selection and estimation. Recent development of algorithms that ameliorate these deficiencies raises the question of whether past work relying on such inference procedures have produced inaccurate systems neuroscience models, thereby impairing their interpretation. Here, we used the Union of Intersections, a statistical inference framework capable of state-of-the-art selection and estimation performance, to fit functional coupling, encoding, and decoding models across a battery of neural datasets. We found that, compared to baseline procedures, UoI inferred models with increased sparsity, improved stability, and qualitatively different parameter distributions, while maintaining predictive performance across recording modality, brain region, and task. Specifically, we obtained highly sparse functional coupling networks with substantially different community structure, more parsimonious encoding models, and decoding models that rely on fewer single-units. Together, these results demonstrate that accurate parameter inference reshapes interpretation in diverse neuroscience contexts. The ubiquity of model-based data-driven discovery in biology suggests that analogous results would be seen in other fields.

show abstract

Section: Decoding Behavioral Condition From Neural Activity With a Smsupporting

confidence: 84%

Section: Recordings From Basal Gangliamentioning

confidence: 99%

Section: Decoding Behavioral Condition From Neural Activity With a Smmentioning

confidence: 99%

See 1 more Smart Citation

Accurate inference in parametric models reshapes neuroscientific interpretation and improves data-driven discovery

Sachdeva

Livezey

Dougherty

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Lesioning or inactivation studies were largely inconclusive, as these manipulations did not result in a consistent motor phenotype (Norton, 1976;Ossowska et al, 1983;Schneider and Olazabal, 1984;Hauber et al, 1998;Joel et al, 1998;Konitsiotis et al, 1998;Soares et al, 2004;Hegeman et al, 2016). A large number of studies showed that GPe neurons change their activity in relation to movement; however, the identity of the recorded neurons was unknown (DeLong, 1971;Anderson, 1978;Anderson and Horak, 1985;DeLong et al, 1985;Mink and Thach, 1987;Mitchell et al, 1987;Filion et al, 1988;Nambu et al, 1990;Mink and Thach, 1991b, a;Mushiake and Strick, 1995;Parent and Hazrati, 1995;Kimura et al, 1996;Arkadir et al, 2004;Shin and Sommer, 2010;Schmidt et al, 2013;Yoshida and Tanaka, 2016;Gu et al, 2020;Mullie et al, 2020). It has been shown that identified GPe neuron subtypes can display diverse changes in their activity during spontaneous body movements (Dodson et al, 2015).…”

Section: Gpe Neuron Subtypes Have Opposing Roles In Motor Controlmentioning

confidence: 99%

Parvalbumin⁺and Npas1⁺Pallidal Neurons Have Distinct Circuit Topology and Function

et al. 2020

View full text Add to dashboard Cite

Author contributionsAP conceived the study. AP and QC designed and conducted the electrophysiological measurements. AP and QC designed and conducted the behavioral experiments. EA performed pilot behavioral experiments. HSX performed pilot experiments on the anatomical properties of the STN-GPe input. AP wrote the analysis scripts for in vivo and ex vivo experiments. AP, BLB, IF, and SC performed histological analysis. AWH, TNL, and SMB offered specialized reagents and technical expertise. AP and CSC wrote the manuscript with input from all co-authors. CSC designed, directed, and supervised the project. All authors reviewed and edited the manuscript.

show abstract

“…Although the importance of the GPe has long been recognized, our understanding of its cell types, their organization, and their functional properties is limited. While prior studies argue GPe neurons are involved in movement control (Dodson et al, 2015; Zimnik et al, 2015; Glajch et al, 2016; Mastro et al, 2017; Aristieta et al, 2020; Gu et al, 2020; Pamukcu et al, 2020), precisely how they are involved in motor function and dysfunction remains poorly defined. A major hurdle has been imposed by the complexity of the cellular makeup of the GPe.…”

Section: Introductionmentioning

confidence: 99%

Dissociable Roles of Pallidal Neuron Subtypes in Regulating Motor Patterns

Cherian

Cui

Pamukcu

et al. 2020

Preprint

View full text Add to dashboard Cite

We have previously established that PV+ neurons and Npas1+ neurons are distinct neuron classes in the GPe: they have different topographical, electrophysiological, circuit, and functional properties. Aside from Foxp2+ neurons, which are a unique subclass within the Npas1+ class, we lack driver lines that effectively capture other GPe neuron subclasses. In this study, we examined the utility of Kcng4-Cre, Npr3-Cre, and Npy2r-Cre mouse lines (both males and females) for the delineation of GPe neuron subtypes. By using these novel driver lines, we have provided the most exhaustive investigation of electrophysiological studies of GPe neuron subtypes to date. Corroborating our prior studies, GPe neurons can be divided into two statistically distinct clusters that map onto PV+ and Npas1+ classes. By combining optogenetics,, and machine learning-based tracking, we showed that optogenetic perturbation of GPe neuron subtypes generated unique behavioral structures. Our findings further highlighted the dissociable roles of GPe neurons in regulating movement and anxiety. We concluded that Npr3+ neurons and Kcng4+ neurons are distinct subclasses of Npas1+ neurons and PV+ neurons, respectively. Finally, by examining local collateral connectivity, we inferred the circuit mechanisms involved in the motor patterns observed with optogenetic perturbations. In summary, by identifying mouse lines that allow for manipulations of GPe neuron subtypes, we created new opportunities for interrogations of cellular and circuit substrates that can be important for motor function and dysfunction.

show abstract

Globus pallidus dynamics reveal covert strategies for behavioral inhibition

Cited by 7 publications

References 69 publications

Accurate inference in parametric models reshapes neuroscientific interpretation and improves data-driven discovery

Accurate inference in parametric models reshapes neuroscientific interpretation and improves data-driven discovery

Parvalbumin⁺and Npas1⁺Pallidal Neurons Have Distinct Circuit Topology and Function

Dissociable Roles of Pallidal Neuron Subtypes in Regulating Motor Patterns

Contact Info

Product

Resources

About

Globus pallidus dynamics reveal covert strategies for behavioral inhibition

Cited by 7 publications

References 69 publications

Accurate inference in parametric models reshapes neuroscientific interpretation and improves data-driven discovery

Accurate inference in parametric models reshapes neuroscientific interpretation and improves data-driven discovery

Parvalbumin+and Npas1+Pallidal Neurons Have Distinct Circuit Topology and Function

Dissociable Roles of Pallidal Neuron Subtypes in Regulating Motor Patterns

Contact Info

Product

Resources

About

Parvalbumin⁺and Npas1⁺Pallidal Neurons Have Distinct Circuit Topology and Function