Sensory Systems/Somato System Whiskers

Rodents: Somatosensory Perception of Whiskers

edit

Introduction

edit
Figure 1A. Overview of the whisker system in rats
Figure 1B. System level description of the ascending pathways from whiskers to barrel cortex.

The barrel Cortex is a specialized region in somatosensory cortex responsible for processing the tactile information from whiskers. As every other cortical region, the barrel cortex also preserves the columnar organization which plays a crucial role in information processing. Information from each whisker is represented in separate, discrete columns analogous to “barrels”, hence the name barrel cortex. Rodents use whiskers constantly to acquire sensory information from the environment. Given their nocturnal nature, tactile information carried by whisker forms the primary sensory signals to build a perceptual map of the environment. The whiskers on the snouts of mice and rats serve as arrays of highly sensitive detectors for acquiring tactile information as shown in Figure 1 A and B. By using their whiskers, rodents can build spatial representations of their environment, locate objects, and perform fine-grain texture discrimination. Somatosensory whisker-related processing is highly organized into stereotypical maps, which occupy a large portion of the rodent brain. During exploration and palpation of objects, the whiskers are under motor control, often executing rapid large-amplitude rhythmic sweeping movements, and this sensory system is therefore an attractive model for investigating active sensory processing and sensory-motor integration. In these animals, a large part of the neocortex is dedicated to the processing of information from the whiskers. Since rodents are nocturnal, visual information is relatively poor and they rely heavily on the tactile information from whiskers. Perhaps the most remarkable specialization of this sensory system is the primary somatosensory ‘‘barrel’’ cortex, where each whisker is represented by a discrete and well-defined structure in layer 4.

These layer 4 barrels are somatotopically arranged in an almost identical fashion to the layout of the whiskers on the snout i.e. bordering whiskers are represented in adjacent cortical areas [1]. Sensorimotor integration of whisker related activity leads to pattern discrimination and enables rodents to have a reliable map of the environment. This is an interesting model to study because rodents use whisker to “see” and this cross modality sensory information processing could help us to improve the life of humans, who are deprived of one sensory modality. Specifically, blind people can be trained to use somatosensory information to build a spatial map of the environment [2].


Pathways carrying whisker information to Barrel Cortex

edit
Pathways carrying whisker information to Barrel Cortex
 
Figure 2. Schematic demonstrating the ascending pathway of rodent whisker-related sensorimotor system.



The tactile information from the whiskers on the snouts is carried through the trigeminal nerves, which terminate at the trigeminal nucleus as shown in Figure 2. The ascending pathway starts with the primary afferents in the trigeminal ganglion (TG) transducing whisker vibrations into neuronal signals, and projecting to the trigeminal brainstem complex (TN). The TN consists of the principal nucleus (PrV), and the spinal sub-nuclei (interpolarisSpVi; caudalisSpVc; the detailed connectivity of the oralis sub-nucleus is unknown and is omitted in the figure). The SpVi falls into a caudal and rostral part (SpVic and SpVir). The classical mono-whisker lemniscal pathway (lemniscal 1) originates in PrV barrelettes, and projects via VPM barreloid cores to primary somatosensory cortex (S1) barrel columns. A second lemniscal pathway originating from PrV has been recently discovered which carries multi-whisker signals via barreloid heads to septa (and dysgranular zone) of S1. The extra-lemniscal pathway originates in SPVic and carries multi-whisker signals via barreloid tails in VPM to the secondary somatosensory area. Finally, the parelemniscal pathway originates in SpVir and carries multi-whisker signals via POm to S1, S2, and primary motor area (M1). The different colours of connections indicate three principal pathways through which associative coupling between the sensorimotor cortical areas may be realized. Black indicates direct cortico-cotical connections. Blue shows cortico-thalamic cascades. Brown represents cortico-sub-cortical loops. Projections of S1 and S2 may open or close the lemniscal gate (i.e. gate signal flow through PrV) by modulating intrinsic TN circuitry.


 
Figure 3.Processing of whisker-related sensory information in barrel cortex. System level description of the pathways involved in the propagation of information from whiskers to cortex & columnar organization of the barrel cortex which receives information from single whisker.



The sensory neurons make excitatory glutamatergic synapses in the trigeminal nuclei of the brain stem. Trigemino-thalamic neurons in the principal trigeminal nucleus are organized into somatotopically arranged ‘‘barrelettes,’’ each receiving strong input from a single whisker as shown in (Figure 3). The principal trigeminal neurons project to the ventral posterior medial (VPM) nucleus of the thalamus, which is also somatotopically laid out into anatomical units termed ‘‘barreloids’’ VPM neurons respond rapidly and precisely to whisker deflection, with one ‘‘principal’’ whisker evoking stronger responses than all others. The axons of VPM neurons within individual barreloids project to the primary somatosensory neocortex forming discrete clusters in layer 4, which form the basis of the ‘‘barrel’’ map as shown in Figure 3.



Whisker information processing in Barrel Cortex with specialized local microcircuit

edit

The deflection of a whisker is thought to open mechano-gated ion channels in nerve endings of sensory neurons innervating the hair follicle (although the molecular signalling machinery remains to be identified). The resulting depolarization evokes action potential firing in the sensory neurons of the infraorbital branch of the trigeminal nerve. The transduction through mechanical deformation is similar to the hair cells in the inner ear; in this case the contact of whiskers with the objects causes the mechano-gated ion channels to open. Cation-permeable ion channels let positively charged ions into the cells and causes depolarization, eventually leading to generation of action potentials. A single sensory neuron only fires action potentials to deflection of one specific whisker. The innervation of the hair follicle shows a diversity of nerve endings, which may be specialized for detecting different types of sensory input [3].

The layer 4 barrel map is arranged almost identically to the layout of the whiskers on the snout of the rodent. There are several recurrent connections in layer 4 and it sends axons to layer 2/3 neurons, which integrates information from other cortical regions like primary motor cortex. These intra-cortical and inter-cortical connections enable the rodents to achieve stimulus discrimination capabilities and to extract optimal information from the incoming tactile stimulus. Also, these projections play a crucial role in integrating somatosensory information with motor output. Information from whiskers is processed in the barrel cortex with specialized local microcircuits formed to extract optimal information about the environment. These cortical microcircuits are composed of excitatory and inhibitory neurons as shown in Figure 4.

 
Figure 4.Local Microcircuit in Barrel cortex. Left: schematic representation of the cortical layers (barrels within L4 in cyan ) with examples of typical dendritic morphologies of excitatory cortical neurons (in red , an L2 neuron; in violet , a spiny stellate L4 cell; in green , an L5B pyramidal neuron). Right: schematic representation of the main excitatory connections between cortical layers within a barrel column (black).


Learning whisker based object discrimination & texture differentiation

edit

Rodents move their sensors to collect information, and these movements are guided by sensory input. When action sequences are required to achieve success in novel tasks, interactions between movement and sensation underlie motor control [4] and complex learned behaviours [5]. The motor cortex has important roles in learning motor skills [6-9], but its function in learning sensorimotor associations is unknown. The neural circuits underlying sensorimotor integration are beginning to be mapped. Different motor cortex layers harbour excitatory neurons with distinct inputs and projections [10-12]. Outputs to motor centres in the brain stem and spinal cord arise from pyramidal tract-type neurons in layer 5B (L5B). Within motor cortex, excitation descends from L2/3 to L5 [13, 14]. Input from somatosensory cortex impinges preferentially onto L2/3 neurons. L2/3 neurons [10] therefore directly link somatosensation and control of movements. In one of the recent studies [15], mice were trained head fixed in a vibrissa-based object-detection task while imaging populations of neurons [16]. Following a sound, a pole was moved to one of several target positions within reach of the whiskers (the ‘go’ stimulus) or to an out-of-reach position (the ‘no-go’ stimulus). Target and out-of-reach locations were arranged along the anterior–posterior axis; the out-of reach position was most anterior. Mice searched for the pole with one whisker row, the C row, and reported the pole as ‘present’ by licking, or ‘not present’ by withholding licking. Licking on go trials (hit) was rewarded with water, whereas licking on no-go trials (false alarm) was punished with a time-out during which the trial was stopped for 2 seconds. Trials without licking (no-go, correct rejection, go, and miss) were not rewarded or punished. All mice showed learning within the first two or three sessions. Performance reached expert levels after three to six training sessions. Learning the behavioural task was directly dependent on the motor related behaviour. Naive mice whisked occasionally in a manner unrelated to trail structure. Thus, object detection relies on a sequence of actions, linked by sensory cues. An auditory cue triggers whisking during the sampling period. Contact between whisker and object causes licking for a water reward during a response period. Silencing vM1 indicates that this task requires the motor cortex; with vM1 silenced, task-dependent whisking persisted, but was reduced in amplitude and repeatability, and task performance dropped.


Neural Correlates of Sensorimotor learning mechanism

edit

Coding of touch in the motor cortex is consistent with direct input from vS1 to the imaged neurons. A model based on population coding of individual behavioural features also predicted motor behaviours. Accurate decoding of whisking amplitude, whisking set-point and lick rate suggests that vM1 controls these slowly varying motor parameters, as expected from previous motor cortex and neurophysiological experiments.


References

edit

1 Feldmeyer D, Brecht M, Helmchen F, Petersen CCH, Poulet JFA, Staiger JF, Luhmann HJ, Schwarz C."Barrel cortex function" Progress in Neurobiology 2013, 103 : 3-27.

2 Lahav O, Mioduser D. "Multisensory virtual environment for supporting blind persons' acquisition of spatial cognitive mapping, orientation, and mobility skills." Academia.edu 2002.

3 Alloway KD. "Information processing streams in rodent barrel cortex: The differential functions of barrel and septal circuits." Cereb Cortex 2008, 18(5):979-989.

4 Scott SH. "Inconvenient truths about neural processing in primary motor cortex." The Journal of physiology 2008, 586(5):1217-1224.

5 Wolpert DM, Diedrichsen J, Flanagan JR. "Principles of sensorimotor learning." Nature reviews Neuroscience 2011, 12(12):739-751.

6 Wise SP, Moody SL, Blomstrom KJ, Mitz AR. "Changes in motor cortical activity during visuomotor adaptation." Experimental brain research Experimentelle Hirnforschung Experimentation cerebrale 1998, 121(3):285-299.

7 Rokni U, Richardson AG, Bizzi E, Seung HS. "Motor learning with unstable neural representations." Neuron 2007, 54(4):653-666.

8 Komiyama T, Sato TR, O'Connor DH, Zhang YX, Huber D, Hooks BM, Gabitto M, Svoboda K. "Learning-related fine-scale specificity imaged in motor cortex circuits of behaving mice." Nature 2010, 464(7292):1182-1186.

9 Hosp JA, Pekanovic A, Rioult-Pedotti MS, Luft AR. "Dopaminergic projections from midbrain to primary motor cortex mediate motor skill learning." The Journal of neuroscience : the official journal of the Society for Neuroscience 2011, 31(7):2481-2487.

10 Keller A. "Intrinsic synaptic organization of the motor cortex." Cereb Cortex 1993, 3(5):430-441.

11 Mao T, Kusefoglu D, Hooks BM, Huber D, Petreanu L, Svoboda K. "Long-range neuronal circuits underlying the interaction between sensory and motor cortex." Neuron 2011, 72(1):111-123.

12 Hooks BM, Hires SA, Zhang YX, Huber D, Petreanu L, Svoboda K, Shepherd GM. "Laminar analysis of excitatory local circuits in vibrissal motor and sensory cortical areas." PLoS biology 2011, 9(1):e1000572.

13 Anderson CT, Sheets PL, Kiritani T, Shepherd GM. "Sublayer-specific microcircuits of corticospinal and corticostriatal neurons in motor cortex." Nature neuroscience 2010, 13(6):739-744.

14 Kaneko T, Cho R, Li Y, Nomura S, Mizuno N. "Predominant information transfer from layer III pyramidal neurons to corticospinal neurons." The Journal of comparative neurology 2000, 423(1):52-65.

15 O'Connor DH, Clack NG, Huber D, Komiyama T, Myers EW, Svoboda K. "Vibrissa-based object localization in head-fixed mice." The Journal of neuroscience : the official journal of the Society for Neuroscience 2010, 30(5):1947-1967.

16 O'Connor DH, Peron SP, Huber D, Svoboda K. "Neural activity in barrel cortex underlying vibrissa-based object localization in mice." Neuron 2010, 67(6):1048-1061.

17 Shaner NC, Campbell RE, Steinbach PA, Giepmans BN, Palmer AE, Tsien RY. "Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein." Nature biotechnology 2004, 22(12):1567-1572.

18 Tian L, Hires SA, Mao T, Huber D, Chiappe ME, Chalasani SH, Petreanu L, Akerboom J, McKinney SA, Schreiter ER. "Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators." Nature methods 2009, 6(12):875-881.