Mechanisms underlying a thalamocortical transformation during active tactile sensation

During active somatosensation, neural signals expected from movement of the sensors are suppressed in the cortex, whereas information related to touch is enhanced. This tactile suppression underlies low-noise encoding of relevant tactile features and the brain’s ability to make fine tactile discriminations. Layer (L) 4 excitatory neurons in the barrel cortex, the major target of the somatosensory thalamus (VPM), respond to touch, but have low spike rates and low sensitivity to the movement of whiskers. Most neurons in VPM respond to touch and also show an increase in spike rate with whisker movement. Therefore, signals related to self-movement are suppressed in L4. Fast-spiking (FS) interneurons in L4 show similar dynamics to VPM neurons. Stimulation of halorhodopsin in FS interneurons causes a reduction in FS neuron activity and an increase in L4 excitatory neuron activity. This decrease of activity of L4 FS neurons contradicts the "paradoxical effect" predicted in networks stabilized by inhibition and in strongly-coupled networks. To explain these observations, we constructed a model of the L4 circuit, with connectivity constrained by in vitro measurements. The model explores the various synaptic conductance strengths for which L4 FS neurons actively suppress baseline and movement-related activity in layer 4 excitatory neurons. Feedforward inhibition, in concert with recurrent intracortical circuitry, produces tactile suppression. Synaptic delays in feedforward inhibition allow transmission of temporally brief volleys of activity associated with touch. Our model provides a mechanistic explanation of a behavior-related computation implemented by the thalamocortical circuit

Dynamic population coding in primary visual cortex

More than a century ago Ramon y Cajal pioneered the description of neural circuits. Currently, new techniques are being developed to streamline the characterization of entire neural circuits. Even if this \u27connectome\u27 approach is successful, it will represent only a static description of neural circuits. Thus, a fundamental question in neuroscience is to understand how information is dynamically represented by neural populations. In this thesis, I studied two main aspects of dynamical population codes. First, I studied how the exposure or adaptation, for a fraction of a second to oriented gratings dynamically changes the population response of primary visual cortex neurons. The effects of adaptation to oriented gratings have been extensively explored in psychophysical and electrophysiological experiments. However, whether rapid adaptation might induce a change in the primary visual cortex\u27s functional connectivity to dynamically impact the population coding accuracy is currently unknown. To address this issue, we performed multi-electrode recordings in primary visual cortex, where adaptation has been previously shown to induce changes in the selectivity and response amplitude of individual neurons. We found that adaptation improves the population coding accuracy. The improvement was more prominent for iso- and orthogonal orientation adaptation, consistent with previously reported psychophysical experiments. We propose that selective decorrelation is a metabolically inexpensive mechanism that the visual system employs to dynamically adapt the neural responses to the statistics of the input stimuli to improve coding efficiency. Second, I investigated how ongoing activity modulates orientation coding in single neurons, neural populations and behavior. Cortical networks are never silent even in the absence of external stimulation. The ongoing activity can account for up to 80% of the metabolic energy consumed by the brain. Thus, a fundamental question is to understand the functional role of ongoing activity and its impact on neural computations. I studied how the orientation coding by individual neurons and cell populations in primary visual cortex depend on the spontaneous activity before stimulus presentation. We hypothesized that since the ongoing activity of nearby neurons is strongly correlated, it would influence the ability of the entire population of orientation-selective cells to process orientation depending on the prestimulus spontaneous state. Our findings demonstrate that ongoing activity dynamically filters incoming stimuli to shape the accuracy of orientation coding by individual neurons and cell populations and this interaction affects behavioral performance. In summary, this thesis is a contribution to the study of how dynamic internal states such as rapid adaptation and ongoing activity modulate the population code accuracy

Endogenous fluctuations in cortical state selectively enhance different modes of sensory processing in human temporal lobe

Abstract The degree of synchronized fluctuations in neocortical network activity can vary widely during alertness. One influential idea that has emerged over the past few decades is that perceptual decisions are more accurate when the state of population activity is desynchronized. This suggests that optimal task performance may occur during a particular cortical state – the desynchronized state. Here we show that, contrary to this view, cortical state can both facilitate and suppress perceptual performance in a task-dependent manner. We performed electrical recordings from surface-implanted grid electrodes in the temporal lobe while human subjects completed two perceptual tasks. We found that when local population activity is in a synchronized state, network and perceptual performance are enhanced in a detection task and impaired in a discrimination task, but these modulatory effects are reversed when population activity is desynchronized. These findings indicate that the brain has adapted to take advantage of endogenous fluctuations in the state of neural populations in temporal cortex to selectively enhance different modes of sensory processing during perception in a state-dependent manner

Low-noise encoding of active touch by layer 4 in the somatosensory cortex

Abstract Cortical spike trains often appear noisy, with the timing and number of spikes varying across repetitions of stimuli. Spiking variability can arise from internal (behavioral state, unreliable neurons, or chaotic dynamics in neural circuits) and external (uncontrolled behavior or sensory stimuli) sources. The amount of irreducible internal noise in spike trains, an important constraint on models of cortical networks, has been difficult to estimate, since behavior and brain state must be precisely controlled or tracked. We recorded from excitatory barrel cortex neurons in layer 4 during active behavior, where mice control tactile input through learned whisker movements. Touch was the dominant sensorimotor feature, with >70% spikes occurring in millisecond timescale epochs after touch onset. The variance of touch responses was smaller than expected from Poisson processes, often reaching the theoretical minimum. Layer 4 spike trains thus reflect the millisecond-timescale structure of tactile input with little noise

Flow of Cortical Activity Underlying a Tactile Decision in Mice

Perceptual decisions involve distributed cortical activity. Does information flow sequentially from one cortical area to another, or do networks of interconnected areas contribute at the same time? Here we delineate when and how activity in specific areas drives a whisker-based decision in mice. A short-term memory component temporally separated tactile “sensation” and “action” (licking). Using optogenetic inhibition (spatial resolution, 2 mm; temporal resolution, 100 ms), we surveyed the neocortex for regions driving behavior during specific behavioral epochs. Barrel cortex was critical for sensation. During the short-term memory, unilateral inhibition of anterior lateral motor cortex biased responses to the ipsilateral side. Consistently, barrel cortex showed stimulus-specific activity during sensation, whereas motor cortex showed choice-specific preparatory activity and movement-related activity, consistent with roles in motor planning and movement. These results suggest serial information flow from sensory to motor areas during perceptual decision making.Howard Hughes Medical Institut

Activity in motor–sensory projections reveals distributed coding in somatosensation

Cortical feed-back projections to primary sensory areas terminate most heavily in layer (L) 1(1,2), where they make synapses with tuft dendrites of pyramidal neurons. L1 input is thought to provide ‘contextual’ information(3), but the signals transmitted by L1 feedback remain uncharacterized. In the rodent somatosensory system, the spatially diffuse(4) vibrissal motor cortex (vM1)→ vibrissal somatosensory cortex (barrel cortex, vS1) feedback projection may allow whisker touch to be interpreted in the context of whisker position to compute object location(5,6). When mice palpate objects with their whiskers to localize object features(7,8), whisker touch excites vibrissal somatosensory cortex (barrel cortex, vS1)(9) and later vibrissal motor cortex (vM1) in a somatotopic manner(10,11,12,13). Here we used axonal calcium imaging to track activity in vM1→ vS1 afferents in L1 of barrel cortex, while mice performed whisker-dependent object localization. Spatially intermingled individual axons represented whisker movements, touch, and other behavioral features. In a subpopulation of axons, activity depended on object location and persisted for seconds after touch. Neurons in the barrel cortex thus have information to integrate movements and touches of multiple whiskers over time, key components of object identification and navigation by active touch