Texture coarseness responsive neurons and their mapping in layer 2–3 of the rat barrel cortex in vivo

Garion, Liora; Dubin, Uri; Rubin, Yoav; Khateb, Mohamed; Schiller, Yitzhak; Azouz, Rony; Schiller, Jackie

doi:10.7554/elife.03405

Cited by 37 publications

(48 citation statements)

References 51 publications

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“…Voigts These heterogeneous responses observed in L2/3 could represent tuning for specific patterns of deviations relative to baseline stimuli. However, the higher firing rates we observed for smaller amplitude stimuli are also consistent with individual cells tuned to static stimulus amplitude ranges 47 . To disambiguate these possibilities and test whether L2/3 encoded a true history dependent deviant signal, we analyzed trials where deviant stimulus amplitudes were matched, but deviants were preceded by higher or lower amplitude baseline stimuli (55 sessions, Extended Data Figures 13).…”

Section: Layers 2/3 Neurons Explicitly Encoded Stimulus Amplitude Devsupporting

confidence: 88%

Layer 6 ensembles can selectively regulate the behavioral impact and layer-specific representation of sensory deviants

Voigts

Deister

Moore

2019

Preprint

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Predictive models can enhance the salience of unanticipated input, and the neocortical laminar architecture is believed to be central to this computation. Here, we examined the role of a key potential node in model formation, layer (L) 6, using behavioral, electrophysiological and imaging methods in mouse somatosensory cortex. To test the contribution of L6, we applied weak optogenetic drive that changed which L6 neurons were sensory-responsive, without affecting overall firing rates in L6 or L2/3. This stimulation suppressed L2/3 deviance encoding, but maintained other stimulus encoding. The stimulation also selectively suppressed behavioral sensitivity to deviant stimuli without impacting baseline performance. In contrast, stronger L6 drive inhibited firing and suppressed overall sensory function. These findings indicate that, despite their sparse activity, specific ensembles of stimulus-driven L6 neurons are required to form neocortical predictions, and for their behavioral benefit. 45 50 55 60 65 70 75 2-Photon Imaging. A two-photon microscope (Bruker/Prairie Technologies) using an 8 kHz resonant galvanometer (CRS) for fast x-axis scanning, and a non-resonant galvanometer (Cambridge 6215) for y-axis increments was used. In Voigts, Deister and Moore Page 16/23 590 595 600 605 610 615 620 625 630 635 Code Availability. All custom software used in this study is freely available: Behavioral experiments were controlled using a custom state machine (www.github.com/open-ephys/behavioral_state_machine) written in Matlab via PCI DIO boards (National Instruments). Vibrissae were tracked using an automated tracker (Extended Data Figure 2, www.github.com/jvoigts/whisker_tracking). Spike sorting was performed using a custom manual sorting tool (www.github.com/open-ephys/simpleclust). Voigts, Deister and Moore Page 17/23 645 650 655 660 665 670 675 680 685 690

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Section: Layers 2/3 Neurons Explicitly Encoded Stimulus Amplitude Devsupporting

confidence: 88%

Layer 6 ensembles can selectively regulate the behavioral impact and layer-specific representation of sensory deviants

Voigts

Deister

Moore

2019

Preprint

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“…5). These stick-slip events occur at each feature element and it is hypothesized that neural encoding of stick-slip events (Wolfe et al 2008;Jadhav et al 2009;Jadhav & Feldman, 2010) allows fine texture discrimination (Neimark et al 2003;Ritt et al 2008;Wolfe et al 2008;Lottem & Azouz, 2009;Bosman et al 2011;Morita et al 2011;Garion et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Laminar‐specific encoding of texture elements in rat barrel cortex

Allitt

Alwis

Rajan

2017

The Journal of Physiology

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Texture discrimination by rats is exquisitely guided by fine-grain mechanical stick-slip motions of the face whiskers as they encounter, stick to and slip past successive texture-defining surface features such as bumps and grooves. Neural encoding of successive stick-slip texture events will be shaped by adaptation, common to all sensory systems, whereby receptor and neural responses to a stimulus are affected by responses to preceding stimuli, allowing resetting to signal novel information. Additionally, when a whisker is actively moved to contact and brush over surfaces, that motion itself generates neural responses that could cause adaptation of responses to subsequent stick-slip events. Nothing is known about encoding in the rat whisker system of stick-slip events defining textures of different grain or the influence of adaptation from whisker protraction or successive texture-defining stick-slip events. Here we recorded responses from halothane-anaesthetized rats in response to texture-defining stimuli applied to passive whiskers. We demonstrate that: across the columnar network of the whisker-recipient barrel cortex, adaptation in response to repetitive stick-slip events is strongest in uppermost layers and equally lower thereafter; neither whisker protraction speed nor stick-slip frequency impede encoding of stick-slip events at rates up to 34.08 Hz; and layer 2 normalizes responses to whisker protraction to resist effects on texture signalling. Thus, within laminar-specific response patterns, barrel cortex reliably encodes texture-defining elements even to high frequencies.

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“…The electrophysiological and imaging traces were synchronized by driving the electrophysiological software with transistor–transistor logic pulses generated by the imaging software via a PCI‐6110 board (National Instruments, Austin, Texas). In addition, the electrophysiological software recorded frame triggers from the 2‐photon microscope to monitor the imaging frame acquisition, and the same computer was used to acquire both imaging and electrophysiological data. To simultaneously record the electrophysiological activity from multiple neocortical depths, we used a single‐shaft 16‐contact silicon probe electrode (A16 probe) as previously described …”

Section: Methodsmentioning

confidence: 99%

“…To simultaneously record the electrophysiological activity from multiple neocortical depths, we used a singleshaft 16-contact silicon probe electrode (A16 probe) as previously described. 24…”

Section: Electrophysiologymentioning

confidence: 99%

Layer‐ and Cell‐Specific Recruitment Dynamics during Epileptic Seizures In Vivo

Aeed

Shnitzer

Talmon

et al. 2019

Annals of Neurology

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Objective To investigate the network dynamics mechanisms underlying differential initiation of epileptic interictal spikes and seizures. Methods We performed combined in vivo 2‐photon calcium imaging from different targeted neuronal subpopulations and extracellular electrophysiological recordings during 4‐aminopyridine–induced neocortical spikes and seizures. Results Both spikes and seizures were associated with intense synchronized activation of excitatory layer 2/3 pyramidal neurons (PNs) and to a lesser degree layer 4 neurons, as well as inhibitory parvalbumin‐expressing interneurons (INs). In sharp contrast, layer 5 PNs and somatostatin‐expressing INs were gradually and asynchronously recruited into the ictal activity during the course of seizures. Within layer 2/3, the main difference between onset of spikes and seizures lay in the relative recruitment dynamics of excitatory PNs compared to parvalbumin‐ and somatostatin‐expressing inhibitory INs. Whereas spikes exhibited balanced recruitment of PNs and parvalbumin‐expressing INs, during seizures IN responses were reduced and less synchronized than in layer 2/3 PNs. Similar imbalance was not observed in layers 4 or 5 of the neocortex. Machine learning–based algorithms we developed were able to distinguish spikes from seizures based solely on activation dynamics of layer 2/3 PNs at discharge onset. Interpretation During onset of seizures, the recruitment dynamics markedly differed between neuronal subpopulations, with rapid synchronous recruitment of layer 2/3 PNs, layer 4 neurons, and parvalbumin‐expressing INs and gradual asynchronous recruitment of layer 5 PNs and somatostatin‐expressing INs. Seizures initiated in layer 2/3 due to a dynamic mismatch between local PNs and inhibitory INs, and only later spread to layer 5 by gradually and asynchronously recruiting PNs in this layer. ANN NEUROL 2020;87:97–115

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Texture coarseness responsive neurons and their mapping in layer 2–3 of the rat barrel cortex in vivo

Cited by 37 publications

References 51 publications

Layer 6 ensembles can selectively regulate the behavioral impact and layer-specific representation of sensory deviants

Layer 6 ensembles can selectively regulate the behavioral impact and layer-specific representation of sensory deviants

Laminar‐specific encoding of texture elements in rat barrel cortex

Layer‐ and Cell‐Specific Recruitment Dynamics during Epileptic Seizures In Vivo

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