Neuronal Activity in the Primary Somatosensory Thalamocortical Loop Is Modulated by Reward Contingency during Tactile Discrimination

Pantoja, Janaina; Ribeiro, Sidarta; Wiest, Michael; Soares, Ernesto S.; Gervasoni, Damien; Lemos, Nelson A. M.; Nicolelis, Miguel A. L.

doi:10.1523/jneurosci.5279-06.2007

Cited by 57 publications

(54 citation statements)

References 45 publications

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“…For this, we used a classifier and tested the amount of information above chance level that was present in sessions with neural activity recorded from supragranular, granular, or infragranular layers. As previously reported (Krupa et al 2004;Pantoja et al 2007;Wiest et al 2010), neural activity in all different layers contained sufficient information to decode the aperture width significantly above chance (see Fig. 15, open bars).…”

Section: S1 Neurons Reflect Vpm or Pom Dynamicssupporting

confidence: 83%

“…Indeed, the behavior of supragranular, granular, and infragranular layer neurons varied according to the distinct epochs that defined a tactile discrimination task trial. In previous studies, we have shown that, during the anticipatory period, the firing modulations of S1 infragranular layer neurons were fundamentally different from the ones observed in layers II/III and IV (Krupa et al 2004;Pais-Vieira et al 2013b;Pantoja et al 2007;Wiest et al 2010). We have also shown that M1 was partially responsible for these specific infragranular neuron-firing patterns (Pais-Vieira et al 2013b).…”

Section: Discussionmentioning

confidence: 80%

“…We have grouped S1 layers as supragranular, granular, and infragranular layers, as in previous studies of the same task (Krupa et al 2004;Pais-Vieira et al 2013a, 2013bPantoja et al 2007;Shuler et al 2001;Wiest et al 2005). However, it should be noted that physiological differences in our set of data could occur attributable to the existence of further anatomical subdivisions currently not surveyed in the present study.…”

Section: Discussionmentioning

confidence: 99%

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Cortical and thalamic contributions to response dynamics across layers of the primary somatosensory cortex during tactile discrimination

Pais-Vieira

Kunicki²,

Tseng

et al. 2015

Journal of Neurophysiology

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Pais-Vieira M, Kunicki C, Tseng PH, Martin J, Lebedev M, Nicolelis MA. Cortical and thalamic contributions to response dynamics across layers of the primary somatosensory cortex during tactile discrimination. J Neurophysiol 114: 1652-1676, 2015. First published July 15, 2015 doi:10.1152/jn.00108.2015.-Tactile information processing in the rodent primary somatosensory cortex (S1) is layer specific and involves modulations from both thalamocortical and cortico-cortical loops. However, the extent to which these loops influence the dynamics of the primary somatosensory cortex while animals execute tactile discrimination remains largely unknown. Here, we describe neural dynamics of S1 layers across the multiple epochs defining a tactile discrimination task. We observed that neuronal ensembles within different layers of the S1 cortex exhibited significantly distinct neurophysiological properties, which constantly changed across the behavioral states that defined a tactile discrimination. Neural dynamics present in supragranular and granular layers generally matched the patterns observed in the ventral posterior medial nucleus of the thalamus (VPM), whereas the neural dynamics recorded from infragranular layers generally matched the patterns from the posterior nucleus of the thalamus (POM). Selective inactivation of contralateral S1 specifically switched infragranular neural dynamics from POM-like to those resembling VPM neurons. Meanwhile, ipsilateral M1 inactivation profoundly modulated the firing suppression observed in infragranular layers. This latter effect was counterbalanced by contralateral S1 block. Tactile stimulus encoding was layer specific and selectively affected by M1 or contralateral S1 inactivation. Lastly, causal information transfer occurred between all neurons in all S1 layers but was maximal from infragranular to the granular layer. These results suggest that tactile information processing in the S1 of awake behaving rodents is layer specific and state dependent and that its dynamics depend on the asynchronous convergence of modulations originating from ipsilateral M1 and contralateral S1.

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Section: S1 Neurons Reflect Vpm or Pom Dynamicssupporting

confidence: 83%

Section: Discussionmentioning

confidence: 80%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Cortical and thalamic contributions to response dynamics across layers of the primary somatosensory cortex during tactile discrimination

Pais-Vieira

Kunicki²,

Tseng

et al. 2015

Journal of Neurophysiology

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“…Demonstrations of reward dependent sustained activity in somatosensory cortex (11) and sustained responses in auditory cortex (8) might indicate that temporal and reward processing occur in lower order areas of the brain than previously thought. Additionally, because local neural populations throughout the cortex meet our model's minimal requirements, the fundamental concept of using an external signal to modulate plasticity (23,24) could be the basis of elementary mechanisms used throughout the brain to process time.…”

Section: Discussionmentioning

confidence: 99%

Learning reward timing in cortex through reward dependent expression of synaptic plasticity

Gavornik

Shuler

Loewenstein

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

124

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The ability to represent time is an essential component of cognition but its neural basis is unknown. Although extensively studied both behaviorally and electrophysiologically, a general theoretical framework describing the elementary neural mechanisms used by the brain to learn temporal representations is lacking. It is commonly believed that the underlying cellular mechanisms reside in high order cortical regions but recent studies show sustained neural activity in primary sensory cortices that can represent the timing of expected reward. Here, we show that local cortical networks can learn temporal representations through a simple framework predicated on reward dependent expression of synaptic plasticity. We assert that temporal representations are stored in the lateral synaptic connections between neurons and demonstrate that reward-modulated plasticity is sufficient to learn these representations. We implement our model numerically to explain reward-time learning in the primary visual cortex (V1), demonstrate experimental support, and suggest additional experimentally verifiable predictions. reinforcment learning ͉ visual cortex O ur brains process time with such instinctual ease that the difficulty of defining what time is, in a neural sense, seems paradoxical. There is a rich literature in experimental neuroscience describing the temporal dynamics of both cellular and system-level neuronal processes and many insightful psychophysical studies have revealed perceptual correlates of time. Despite this, and the clear importance of accurate temporal processing at all levels of behavior, we still know little about how time is represented or used by the brain (1). Temporal processing is classically understood as a higher order function, and although there is some disagreement (2, 3), it is often argued that dedicated structures or regions in the brain are responsible for representing time (4). Because different mechanisms are likely responsible for computing timing at different time scales (1,5,6), and because there is evidence for modality specific temporal mechanisms (7), an alternative possibility is that timing processes develop locally within different brain regions.Recent evidence indicates that temporal representations are expressed in primary sensory cortices (8-10) and that rewardbased reinforcement can affect the form of stimulus driven activity in the primary somatosensory cortex (11-13). In particular, Shuler and Bear (9) showed that neurons in rat primary visual cortex can develop persistent activity, evoked by brief visual stimuli, that robustly represents the temporal interval between a visual stimulus and paired reward (Fig. 1). A mechanistic framework capable of describing how a neural substrate can learn the observed temporal representations does not exist.Here, we explain how these temporal signals can be encoded in recurrent excitatory synaptic connections and how a local network can learn specific temporal instantiations through reward modulated plasticity. Although our model is potentially ...

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“…Most research has focused on the role of learned value in biasing the neural mechanisms that are involved in planning and executing eye movements, suggesting an influence of value on decision making at a relatively late stage of information processing (Dorris and Glimcher 2004;Platt and Glimcher 1999;Seo and Lee 2008;Seo et al 2009;Sugrue et al 2004Sugrue et al , 2005. However, several recent studies have shown that value also modulates neural gain in early sensory areas that are thought to encode low-level stimulus features, such as primary visual and somatosensory cortex (V1 and S1, respectively; Pantoja et al 2007;Pleger et al 2008Pleger et al , 2009Serences 2008;Shuler and Bear 2006). These later results imply that value biases decision making not only by differentially weighting motor responses, but also by biasing the quality of relevant sensory inputs (but see Liston and Stone 2008).…”

Section: Introductionmentioning

confidence: 99%

Population Response Profiles in Early Visual Cortex Are Biased in Favor of More Valuable Stimuli

Serences

Saproo

2010

Journal of Neurophysiology

104

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Serences JT, Saproo S. Population response profiles in early visual cortex are biased in favor of more valuable stimuli. J Neurophysiol 104: 76 -87, 2010. First published April 21, 2010 doi:10.1152/jn.01090.2009. Voluntary and stimulus-driven shifts of attention can modulate the representation of behaviorally relevant stimuli in early areas of visual cortex. In turn, attended items are processed faster and more accurately, facilitating the selection of appropriate behavioral responses. Information processing is also strongly influenced by past experience and recent studies indicate that the learned value of a stimulus can influence relatively late stages of decision making such as the process of selecting a motor response. However, the learned value of a stimulus can also influence the magnitude of cortical responses in early sensory areas such as V1 and S1. These early effects of stimulus value are presumed to improve the quality of sensory representations; however, the nature of these modulations is not clear. They could reflect nonspecific changes in response amplitude associated with changes in general arousal or they could reflect a bias in population responses so that high-value features are represented more robustly. To examine this issue, subjects performed a two-alternative forced choice paradigm with a variableinterval payoff schedule to dynamically manipulate the relative value of two stimuli defined by their orientation (one was rotated clockwise from vertical, the other counterclockwise). Activation levels in visual cortex were monitored using functional MRI and feature-selective voxel tuning functions while subjects performed the behavioral task. The results suggest that value not only modulates the relative amplitude of responses in early areas of human visual cortex, but also sharpens the response profile across the populations of feature-selective neurons that encode the critical stimulus feature (orientation). Moreover, changes in space-or feature-based attention cannot easily explain the results because representations of both the selected and the unselected stimuli underwent a similar feature-selective modulation. This sharpening in the population response profile could theoretically improve the probability of correctly discriminating high-value stimuli from low-value alternatives.

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Neuronal Activity in the Primary Somatosensory Thalamocortical Loop Is Modulated by Reward Contingency during Tactile Discrimination

Cited by 57 publications

References 45 publications

Cortical and thalamic contributions to response dynamics across layers of the primary somatosensory cortex during tactile discrimination

Cortical and thalamic contributions to response dynamics across layers of the primary somatosensory cortex during tactile discrimination

Learning reward timing in cortex through reward dependent expression of synaptic plasticity

Population Response Profiles in Early Visual Cortex Are Biased in Favor of More Valuable Stimuli

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