scholarly journals Dorsomedial striatal activity tracks completion of behavioral sequences

2021 ◽  
Author(s):  
Youna Vandaele ◽  
David J Ottenheimer ◽  
Patricia H Janak
Keyword(s):  
Neural Activity ◽  
Population Level ◽  
General Representation ◽  
Related Activity ◽  
Self Monitoring ◽  
Action Sequences ◽  
Directed Action ◽  
Ongoing Behavior ◽  
Behavioral Sequences ◽  
Dorsomedial Striatum

For proper execution of goal-directed behaviors, individuals require both a general representation of the goal and an ability to monitor their own progress toward that goal. Here, we examine how dorsomedial striatum (DMS), a region pivotal for forming associations among stimuli, actions, and outcomes, encodes the execution of goal-directed action sequences that require self-monitoring of behavior. We trained rats to complete a sequence of at least 5 consecutive lever presses (without visiting the reward port) to obtain a reward and recorded the activity of individual cells in DMS while rats performed the task. We found that the pattern of DMS activity gradually changed during the execution of the sequence, permitting accurate decoding of sequence progress from neural activity at a population level. Moreover, this sequence-related activity was blunted on trials where rats did not complete a sufficient number of presses. Overall, these data suggest a link between DMS activity and the execution of behavioral sequences that require monitoring of ongoing behavior.

scholarly journals Distinct recruitment of dorsomedial and dorsolateral striatum erodes with extended training

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Youna Vandaele ◽  
Nagaraj R Mahajan ◽  
David J Ottenheimer ◽  
Jocelyn M Richard ◽  
Shreesh P Mysore ◽  
...  
Keyword(s):  
Neural Activity ◽  
Activity Patterns ◽  
Dorsolateral Striatum ◽  
Skilled Performance ◽  
Extended Training ◽  
Initial Acquisition ◽  
Lever Pressing ◽  
Behavioral Sequences ◽  
Early Training ◽  
Dorsomedial Striatum

Hypotheses of striatal orchestration of behavior ascribe distinct functions to striatal subregions, with the dorsolateral striatum (DLS) especially implicated in habitual and skilled performance. Thus neural activity patterns recorded from the DLS, but not the dorsomedial striatum (DMS), should be correlated with habitual and automatized performance. Here, we recorded DMS and DLS neural activity in rats during training in a task promoting habitual lever pressing. Despite improving performance across sessions, clear changes in corresponding neural activity patterns were not evident in DMS or DLS during early training. Although DMS and DLS activity patterns were distinct during early training, their activity was similar following extended training. Finally, performance after extended training was not associated with DMS disengagement, as would be predicted from prior work. These results suggest that behavioral sequences may continue to engage both striatal regions long after initial acquisition, when skilled performance is consolidated.

scholarly journals Enhancing GABAergic Tone in the Rostral Nucleus of the Solitary Tract Reconfigures Sensorimotor Neural Activity

2020 ◽  
Author(s):  
Joshua D. Sammons ◽  
Caroline E. Bass ◽  
Jonathan D. Victor ◽  
Patricia M. Di Lorenzo
Keyword(s):  
Neural Activity ◽  
Inhibitory Activity ◽  
Nucleus Tractus Solitarius ◽  
Artificial Saliva ◽  
Experimental Chamber ◽  
Response Patterns ◽  
Related Activity ◽  
Electrophysiological Recordings ◽  
Rostral Nucleus ◽  
The Relationship

ABSTRACTRecent work has shown that most cells in the rostral, gustatory portion of the nucleus tractus solitarius (rNTS) in awake, freely licking rats show lick-related firing. However, the relationship between taste-related and lick-related activity in rNTS remains unclear. Here, we tested if GABA-derived inhibitory activity regulates the balance of lick- and taste-driven neuronal activity. Combinatorial viral tools were used to restrict expression of ChR2-EYFP to GAD1+ GABAergic neurons. Viral infusions were bilateral in rNTS. 2-4wks later, an optical fiber attached to 8-16 drivable microwires was implanted into the rNTS. After recovery, water-deprived rats were presented with taste stimuli in an experimental chamber. Trials were 5 consecutive taste licks [NaCl, KCl, NH4Cl, sucrose, MSG/IMP, citric acid, quinine, or artificial saliva (AS)] separated by 5 AS licks on a VR5 schedule. Each taste lick triggered a 1s train of laser light (25Hz; 473nm; 8-10mW) in a random half of the trials. In all, 113 cells were recorded in the rNTS, 50 responded to one or more taste stimuli without GABA enhancement. Selective changes in response magnitude (spike count) within cells shifted across unit patterns but preserved inter-stimulus relationships. Cells where enhanced GABAergic tone increased lick coherence conveyed more information distinguishing basic taste qualities and different salts than other cells. In addition, GABA activation significantly amplified the amount of information that discriminated palatable vs. unpalatable tastants. By dynamically regulating lick coherence and remodeling the across-unit response patterns to taste, enhancing GABAergic tone in rNTS reconfigures the neural activity reflecting sensation and movement.Significance StatementThe rostral nucleus tractus solitarius (rNTS) is the first structure in the central gustatory pathway. Electrophysiological recordings from the rNTS in awake, freely-licking animals show that cells in this area have lick- as well as taste-related activity, but the relationship between these characteristics is not well understood. Here, we showed evidence that GABA activation can dynamically regulate both of these two properties in rNTS cells to enhance the information conveyed, especially about palatable vs. unpalatable tastants. These data provide insights into the role of inhibitory activity in the rNTS.

scholarly journals Structure in Neural Activity during Observed and Executed Movements Is Shared at the Neural Population Level, Not in Single Neurons

Cell Reports ◽  
2020 ◽  
Vol 32 (6) ◽  
pp. 108006 ◽  
Author(s):  
Xiyuan Jiang ◽  
Hemant Saggar ◽  
Stephen I. Ryu ◽  
Krishna V. Shenoy ◽  
Jonathan C. Kao
Keyword(s):  
Neural Activity ◽  
Population Level ◽  
Neural Population ◽  
Single Neurons

scholarly journals Stimulus Feature-Specific Information Flow Along the Columnar Cortical Microcircuit Revealed by Multivariate Laminar Spiking Analysis

2020 ◽  
Vol 14 ◽  
Author(s):  
David A. Tovar ◽  
Jacob A. Westerberg ◽  
Michele A. Cox ◽  
Kacie Dougherty ◽  
Thomas A. Carlson ◽  
...  
Keyword(s):  
Neural Activity ◽  
Visual Stimulation ◽  
Brain Activity ◽  
Contextual Information ◽  
Univariate Analysis ◽  
Stimulus Presentation ◽  
Population Level ◽  
Granular Cell ◽  
Stimulus Orientation ◽  
Specific Information

Most of the mammalian neocortex is comprised of a highly similar anatomical structure, consisting of a granular cell layer between superficial and deep layers. Even so, different cortical areas process different information. Taken together, this suggests that cortex features a canonical functional microcircuit that supports region-specific information processing. For example, the primate primary visual cortex (V1) combines the two eyes' signals, extracts stimulus orientation, and integrates contextual information such as visual stimulation history. These processes co-occur during the same laminar stimulation sequence that is triggered by the onset of visual stimuli. Yet, we still know little regarding the laminar processing differences that are specific to each of these types of stimulus information. Univariate analysis techniques have provided great insight by examining one electrode at a time or by studying average responses across multiple electrodes. Here we focus on multivariate statistics to examine response patterns across electrodes instead. Specifically, we applied multivariate pattern analysis (MVPA) to linear multielectrode array recordings of laminar spiking responses to decode information regarding the eye-of-origin, stimulus orientation, and stimulus repetition. MVPA differs from conventional univariate approaches in that it examines patterns of neural activity across simultaneously recorded electrode sites. We were curious whether this added dimensionality could reveal neural processes on the population level that are challenging to detect when measuring brain activity without the context of neighboring recording sites. We found that eye-of-origin information was decodable for the entire duration of stimulus presentation, but diminished in the deepest layers of V1. Conversely, orientation information was transient and equally pronounced along all layers. More importantly, using time-resolved MVPA, we were able to evaluate laminar response properties beyond those yielded by univariate analyses. Specifically, we performed a time generalization analysis by training a classifier at one point of the neural response and testing its performance throughout the remaining period of stimulation. Using this technique, we demonstrate repeating (reverberating) patterns of neural activity that have not previously been observed using standard univariate approaches.

scholarly journals Habits as action sequences: hierarchical action control and changes in outcome value

2014 ◽  
Vol 369 (1655) ◽  
pp. 20130482 ◽  
Author(s):  
Amir Dezfouli ◽  
Nura W. Lingawi ◽  
Bernard W. Balleine
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Neural Structure ◽  
Action Sequence ◽  
Action Sequences ◽  
Directed Action ◽  
Sequence Boundaries ◽  
High Level ◽  
Step Over ◽  
Two Sides

Goal-directed action involves making high-level choices that are implemented using previously acquired action sequences to attain desired goals. Such a hierarchical schema is necessary for goal-directed actions to be scalable to real-life situations, but results in decision-making that is less flexible than when action sequences are unfolded and the decision-maker deliberates step-by-step over the outcome of each individual action. In particular, from this perspective, the offline revaluation of any outcomes that fall within action sequence boundaries will be invisible to the high-level planner resulting in decisions that are insensitive to such changes. Here, within the context of a two-stage decision-making task, we demonstrate that this property can explain the emergence of habits. Next, we show how this hierarchical account explains the insensitivity of over-trained actions to changes in outcome value. Finally, we provide new data that show that, under extended extinction conditions, habitual behaviour can revert to goal-directed control, presumably as a consequence of decomposing action sequences into single actions. This hierarchical view suggests that the development of action sequences and the insensitivity of actions to changes in outcome value are essentially two sides of the same coin, explaining why these two aspects of automatic behaviour involve a shared neural structure.

scholarly journals Reward prediction error does not explain movement selectivity in DMS-projecting dopamine neurons

2018 ◽  
Author(s):  
Rachel S. Lee ◽  
Marcelo G. Mattar ◽  
Nathan F. Parker ◽  
Ilana B. Witten ◽  
Nathaniel D. Daw
Keyword(s):  
Prediction Error ◽  
Dopamine Neurons ◽  
Movement Direction ◽  
Related Activity ◽  
Reward Prediction Error ◽  
Reward Prediction ◽  
Trial Basis ◽  
Midbrain Dopamine ◽  
Shed Light ◽  
Dorsomedial Striatum

AbstractAlthough midbrain dopamine (DA) neurons have been thought to primarily encode reward prediction error (RPE), recent studies have also found movement-related DAergic signals. For example, we recently reported that DA neurons in mice projecting to dorsomedial striatum are modulated by choices contralateral to the recording side. Here, we introduce, and ultimately reject, a candidate resolution for the puzzling RPE vs movement dichotomy, by showing how seemingly movement-related activity might be explained by an action-specific RPE. By considering both choice and RPE on a trial-by-trial basis, we find that DA signals are modulated by contralateral choice in a manner that is distinct from RPE, implying that choice encoding is better explained by movement direction. This fundamental separation between RPE and movement encoding may help shed light on the diversity of functions and dysfunctions of the DA system.

scholarly journals Cortical activity at different time scales: high-pass filtering separates motor planning and execution

2019 ◽  
Author(s):  
David Eriksson ◽  
Mona Heiland ◽  
Artur Schneider ◽  
Ilka Diester
Keyword(s):  
Neuronal Activity ◽  
Motor Planning ◽  
Population Level ◽  
Motor Execution ◽  
Related Activity ◽  
Pass Filter ◽  
Planning Processes ◽  
Filter Approach ◽  
High Pass ◽  
Forelimb Movements

AbstractThe smooth conduction of movements requires simultaneous motor planning and execution according to internal goals. So far it is not known how such movement plans can be modified without being distorted by ongoing movements. Previous studies have isolated planning and execution related neuronal activity by separating behavioral planning and movement periods in time by sensory cues1–7. Here, we introduced two novel tasks in which motor planning developed intrinsically. We separated this continuous self-paced motor planning statistically from motor execution by experimentally minimizing the repetitiveness of the movements. Thereby, we found that in the rat sensorimotor cortex, neuronal motor planning processes evolved with slower dynamics than movement related responses both on a sorted unit and population level. The fast evolving neuronal activity preceded skilled forelimb movements while it coincided with movements in a locomotor task. We captured this fast evolving movement related activity via a high-pass filter approach and confirmed the results with optogenetic stimulations. As biological mechanism underlying such a high pass filtering we suggest neuronal adaption. The differences in dynamics combined with a high pass filtering mechanism represents a simple principle for concurrent motor planning and execution in which planning will result in relatively slow dynamics that will not produce movements.

scholarly journals Encoding time in neural dynamic regimes with distinct computational tradeoffs

2021 ◽  
Author(s):  
Shanglin Zhou ◽  
Sotiris C. Masmanidis ◽  
Dean V. Buonomano
Keyword(s):  
Neural Activity ◽  
Complex Dynamics ◽  
Experimental Studies ◽  
Network Connectivity ◽  
Population Level ◽  
Inhibitory Neurons ◽  
Task Structure ◽  
Neural Dynamic ◽  
Encoding Strategies ◽  
Encode Time

Converging evidence suggests the brain encodes time in time-varying patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Temporal tasks that require producing the same time-dependent output patterns may have distinct computational requirements in regard to the need to exhibit temporal scaling or generalize to novel contexts. It is not known how neural circuits can both encode time and satisfy distinct computational and generalization requirements, it is also not known whether similar patterns of neural activity at the population level can emerge from distinctly different network configurations. To begin to answer these questions, we trained RNNs on two timing tasks based on behavioral studies. The tasks had different input structures but required producing identically timed output patterns. Using a novel framework we quantified whether RNNs encoded two intervals using either of three different timing strategies: scaling, absolute, or stimulus-specific dynamics. We found that similar neural dynamics for single intervals were associated with fundamentally different encoding strategies and network configurations. Critically, some regimes were better suited for generalization, categorical timing, or robustness to noise. Further analysis revealed different connection patterns underlying the different encoding strategies. Our results predict that apparently similar neural dynamic regimes at the population level can be produced through fundamentally different mechanisms—e.g., in regard to network connectivity and the role of excitatory and inhibitory neurons. We also predict that the task structure used in different experimental studies accounts for some of the experimentally observed variability in how networks encode time.

scholarly journals Value signals in orbitofrontal cortex predict economic decisions on a trial-to-trial basis

2021 ◽  
Author(s):  
Vincent B. McGinty ◽  
Shira M. Lupkin
Keyword(s):  
Neural Activity ◽  
Orbitofrontal Cortex ◽  
Population Level ◽  
Weighted Sum ◽  
Decision Behavior ◽  
Economic Decisions ◽  
Trial Basis ◽  
Individual Value ◽  
Value Coding ◽  
First Time

ABSTRACTNeuroeconomics seeks to explain how neural activity contributes to decision behavior. For value-based decisions, the primate orbitofrontal cortex (OFC) is thought to have a key role; however, the mechanism by which single OFC cells contribute to choices is still unclear. Here, we show for the first time a trial-to-trial relationship between choices and population-level value representations in OFC, defined by the weighted sum of activity from many individual value-coding neurons.

scholarly journals Prefrontal Multielectrode Transcranial Direct Current Stimulation Modulates Performance and Neural Activity Serving Visuospatial Processing

2020 ◽  
Vol 30 (9) ◽  
pp. 4847-4857
Author(s):  
Yasra Arif ◽  
Rachel K Spooner ◽  
Alex I Wiesman ◽  
Amy L Proskovec ◽  
Michael T Rezich ◽  
...  
Keyword(s):  
Direct Current ◽  
Neural Activity ◽  
Transcranial Direct Current Stimulation ◽  
Critical Role ◽  
Population Level ◽  
Direct Current Stimulation ◽  
Relative Contribution ◽  
Left Dlpfc ◽  
Dorsolateral Prefrontal ◽  
Visuospatial Processing

Abstract The dorsolateral prefrontal cortex (DLPFC) is known to play a critical role in visuospatial attention and processing, but the relative contribution of the left versus right DLPFC remains poorly understood. We applied multielectrode transcranial direct-current stimulation (ME-tDCS) to the left and right DLPFC to investigate its net impact on behavioral performance and population-level neural activity. The primary hypothesis was that significant laterality effects would be observed in regard to behavior and neural oscillations. Twenty-five healthy adults underwent three visits (left, right, and sham ME-tDCS). Following stimulation, participants completed a visuospatial processing task during magnetoencephalography (MEG). Statistically significant oscillatory events were imaged, and time series were then extracted from the peak voxels of each response. Behavioral findings indicated differences in reaction time and accuracy, with left DLPFC stimulation being associated with slower responses and decreased accuracy compared to right stimulation. Left DLPFC stimulation was also associated with increases in spontaneous theta and decreases in gamma within occipital cortices relative to both right and sham stimulation, while connectivity among DLPFC and visual cortices was generally increased contralateral to stimulation. These data suggest spectrally specific modulation of spontaneous cortical activity at the network-level by ME-tDCS, with distinct outcomes based on the laterality of stimulation.

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