Transformation of the neural code for tactile detection from thalamus to cortex

Abstract

To understand how sensory-driven neural activity gives rise to perception, it is essential to characterize how various relay stations in the brain encode stimulus presence. Neurons in the ventral posterior lateral (VPL) nucleus of the somatosensory thalamus and in primary somatosensory cortex (S1) respond to vibrotactile stimulation with relatively slow modulations (∼100 ms) of their firing rate. In addition, faster modulations (∼10 ms) time-locked to the stimulus waveform are observed in both areas, but their contribution to stimulus detection is unknown. Furthermore, it is unclear whether VPL and S1 neurons encode stimulus presence with similar accuracy and via the same response features. To address these questions, we recorded single neurons while trained monkeys judged the presence or absence of a vibrotactile stimulus of variable amplitude, and their activity was analyzed with a unique decoding method that is sensitive to the time scale of the firing rate fluctuations. We found that the maximum detection accuracy of single neurons is similar in VPL and S1. However, VPL relies more heavily on fast rate modulations than S1, and as a consequence, the neural code in S1 is more tolerant: its performance degrades less when the readout method or the time scale of integration is suboptimal. Therefore, S1 neurons implement a more robust code, one less sensitive to the temporal integration window used to infer stimulus presence downstream. The differences between VPL and S1 responses signaling the appearance of a stimulus suggest a transformation of the neural code from thalamus to cortex. (1-4), and as the signal is relayed from one layer to the next, its representation in spatiotemporal patterns of activity may change (1). Previous studies have shown that, when a tactile vibratory stimulus is presented, neurons in the ventral posterior lateral (VPL) nucleus in the somatosensory thalamus and primary somatosensory cortex (S1, areas 3b and 1) respond by modulating their firing rates computed over a time scale of hundreds of milliseconds (5-9). Because these slow firing rate modulations occurring within relatively long time windows depend on amplitude and vibration frequency, they encode these key stimulus features. In addition, to varying degrees, evoked spikes in both areas also tend to be synchronized to the waveform of the applied mechanical stimulus, which, for frequencies <40 Hz, varies on a time scale of tens of milliseconds. This entrainment, which corresponds to fast firing rate modulations, also depends on stimulus amplitude (9), and so it too carries information about stimulus presence. However, it is unknown whether both the slow (∼100 ms) and fast (∼10 ms) modulations in firing rate contribute to perceptual performance during stimulus detection. Moreover, it is not clear whether the two time scales are equally important in VPL and S1, nor whether the capacity to signal stimulus presence changes from one area to the next.To investigate these issues, we recorded activity from single neurons in the VPL nucle...

Thalamocortical rhythms during a vibrotactile detection task

“…In a previous report on the same dataset, we observed an amplitude modulation for spike rate and periodicity similar to the one reported here for 20-Hz LFP power, with stronger firing rate modulation in S1 than VPL (16). It is possible that both the LFP response and the changes in spike activity are driven directly by the stimulus; another possibility is that the LFP power modulation at 20 Hz is caused by the modulations in spiking activity.…”

“…This amplitude modulation was stronger in S1 than in VPL, which is in line with previous spike-firing rate results (16). This difference may be a result of the considerably smaller receptive field size in VPL than in S1 or of a gain amplification component, because S1 neurons receive converging input from several VPL neurons (27,28).…”

“…With only a few studies in awake, behaving animals (14,15), the thalamic contribution to somatosensory detection performance remained largely unknown. We recently conducted an experiment in which we recorded the simultaneous neuronal activity across the ventral posterolateral nucleus (VPL) and S1 in two monkeys (Macaca mulatta) performing a vibrotactile detection task (6,16). These recordings of single-unit activity in VPL of awake, behaving monkeys showed that neural activity in these nuclei reflects stimulus properties but not the animal's percept (6).…”

“…Several studies in humans (using EEG/magnetoencephalography) showed that cortical oscillatory dynamics influence somatosensory detection performance by setting the state of the brain networks involved (20,21). Importantly, these studies showed that fluctuations in (anticipatory) prestimulus activity in early sensory areas, predominantly in the alpha (8-14 Hz) and beta bands (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), modulate the likelihood of subsequent stimulus detection (2)(3)(4)(22)(23)(24)(25)(26).…”

“…We studied LFPs that were recorded concurrently in the aforementioned detection experiments (6,16) and asked how oscillatory activity contributes to perceptual decision making. To assess the context dependency of stimulus processing, we compared active stimulus detection with a passive control condition.…”