Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models.

The brain has a never-ending internal activity, whose spatiotemporal evolution interacts with external inputs to constrain their impact on brain activity and thereby how we perceive them. We used reproducible touch-related spatiotemporal sensory inputs and recorded intracellularly from rat (Sprague-Dawley, male) neocortical neurons to characterize this interaction. The synaptic responses, or the summed input of the networks connected to the neuron, varied greatly to repeated presentations of the same tactile input pattern delivered to the tip of digit 2. Surprisingly, however, these responses tended to sort into a set of specific time-evolving response types, unique for each neuron. Further, using a set of eight such tactile input patterns, we found each neuron to exhibit a set of specific response types for each input provided. Response types were not determined by the global cortical state, but instead likely depended on the time-varying state of the specific subnetworks connected to each neuron. The fact that some types of responses recurred indicates that the cortical network had a non-continuous landscape of solutions for these tactile inputs. Therefore, our data suggest that sensory inputs combine with the internal dynamics of the brain networks, thereby causing them to fall into one of the multiple possible perceptual attractor states. The neuron-specific instantiations of response types we observed suggest that the subnetworks connected to each neuron represent different components of those attractor states. Our results indicate that the impact of cortical internal states on external inputs is substantially more richly resolvable than previously shown.

The brain has a never-ending internal activity, whose spatiotemporal evolution impacts how we perceive external inputs and generate illusions. The spatiotemporal evolution depends on the 10 neuronal network structure, which forms such a rich dynamic system that the internal interaction with external inputs has remained poorly understood. We used reproducible touch-related spatiotemporal inputs and recorded intracellularly from rat neocortical neurons to characterize this interaction at the circuitry level. Although repeated presentations of the same input generated variable responses, they tended to sort into a set of preferred response states, unique for each 15 neuron. This suggests that sensory inputs combine with internal brain network dynamics to cause it to fall into one out of many possible local minima solutions with disparate instantiations in the subnetworks connected to each neuron.One Sentence Summary: Responses to identical sensory inputs provide detailed indications on the structure of internal cortical network processing. 20 Short title: Cortical state structure to fixed input

Neuroanatomy suggests that adjacent neocortical neurons share a similar set of afferent synaptic inputs, as opposed to neurons localized to different areas of the neocortex. In the present study, we made simultaneous single-electrode patch clamp recordings from two or three adjacent neurons in the primary somatosensory cortex (S1) of the ketamine-xylazine anesthetized rat in vivo to study the correlation patterns in their spike firing during both spontaneous and sensory-evoked activity. One difference with previous studies of pairwise neuronal spike firing correlations was that here we identified several different quantifiable parameters in the correlation patterns by which different pairs could be compared. The questions asked were if the correlation patterns between adjacent pairs were similar and if there was a relationship between the degree of similarity and the layer location of the pairs. In contrast, our results show that for putative pyramidal neurons within layer III and within layer V, each pair of neurons is to some extent unique in terms of their spiking correlation patterns. Interestingly, our results also indicated that these correlation patterns did not substantially alter between spontaneous and evoked activity. Our findings are compatible with the view that the synaptic input connectivity to each neocortical neuron is at least in some aspects unique. A possible interpretation is that plasticity mechanisms, which could either be initiating or be supported by transcriptomic differences, tend to differentiate rather than harmonize the synaptic weight distributions between adjacent neurons of the same type.

The existence of input plasticity in the deep cerebellar nuclear (DCN) cells of the adult cerebellum could have profound implications for our understanding of cerebellar function. Whereas the existence of plastic changes in mossy fiber (mf) synaptic responses in DCN neurons has been demonstrated in juvenile slices, there has so far been no direct demonstration of this form of plasticity in the adult cerebellum in vivo. In the present paper, we recorded from neurons in the anterior interposed nucleus (AIN) and stimulated the spinocerebellar tracts (SCT) directly or via the skin to obtain mf activation and the inferior olive to activate climbing fibers (cfs) in the nonanesthetized, adult, decerebrated cat. We used three different types of protocols that theoretically could be expected to induce plasticity, each of which involved episodically intense afferent activation lasting for 10 min. These were conjunctive mf-cf activation, which effectively induces plasticity in cortical neurons; mf and cf activation in a pattern resembling the protocol for inducing classical conditioning; and conjunctive activation of two excitatory mf inputs. None of these protocols had any statistically significant effect on the evoked responses in the AIN neurons. We conclude that the input plasticity for excitatory mfs in the AIN cells of the adult cerebellum in vivo is likely to be less effective than that of parallel fiber synaptic inputs in cerebellar cortical cells, at least in the timespan of 1 h.