Koji Ikezoe

Fast activation of feedforward inhibitory neurons from thalamic input and its relevance to the regulation of spike sequences in the barrel cortex

Thalamocortical afferents innervate both excitatory and inhibitory cells, the latter in turn producing disynaptic feedforward inhibition, thus creating fast excitation–inhibition sequences in the cortical cells. Since this inhibition is disynaptic, the time lag of the excitation–inhibition sequence could be ∼2–3 ms, while it is often as short as only slightly above 1 ms; the mechanism and function of such fast IPSPs are not fully understood. Here we show that thalamic activation of inhibitory neurons precedes that of excitatory neurons, due to increased conduction velocity of thalamic axons innervating inhibitory cells. Developmentally, such latency differences were seen only after the end of the second postnatal week, prior to the completion of myelination of the thalamocortical afferent. Furthermore, destroying myelination failed to extinguish the latency difference. Instead, axons innervating inhibitory cells had consistently lower threshold, indicating they had larger diameter, which is likely to underlie the differential conduction velocity. Since faster activation of GABAergic neurons from the thalamus can not only curtail monosynaptic EPSPs but also make disynaptic ISPSs precede disynaptic EPSPs, such suppression theoretically enables a temporal separation of thalamically driven mono‐ and disynaptic EPSPs, resulting in spike sequences of ‘L4 leading L2/3’. By recording L4 and L2/3 cells simultaneously, we found that suppression of IPSPs could lead to deterioration of spike sequences. Thus, from the end of the second postnatal week, by activating GABAergic neurons prior to excitatory neurons from the thalamus, fast feedforward disynaptic suppression on postsynaptic cells may play a role in establishing the spike sequences of ‘L4 leading L2/3 cells’.

Relationship between the Local Structure of Orientation Map and the Strength of Orientation Tuning of Neurons in Monkey V1: A 2-Photon Calcium Imaging Study

A majority of neurons in the monkey primary visual cortex (V1) are tuned to stimulus orientations. Preferred orientations and tuning strengths vary among V1 neurons. The preferred orientation of neurons gradually changes across the cortex with occasional failures of this organization. How V1 neurons are arranged by the strength of orientation tuning and whether neuronal arrangement for tuning strength relates to orientation preference maps remains controversial. In this study, we performed in vivo two-photon calcium imaging in macaque V1 to examine the local spatial organization of orientation tuning at the level of single cells. We recorded fluorescence signals from individual neurons loaded with a calcium-sensitive dye in layer 2 and the uppermost tier of layer 3. The strength of orientation tuning was shared by nearby neurons, and changed across the cortex. The neurons with similar tuning strength were distributed across at least the entire thickness of layer 2. The tuning strength was weaker in regions where neurons exhibited heterogeneous preferred orientations, as compared with regions where neurons shared similar orientation preferences. Nearby direction-selective neurons often shared their preferred directions, although only a few neurons were direction selective in the layers examined. Thus, the orientation tuning strength of V1 neurons is partially predictable from the local structure of orientation map. The weaker orientation tuning we found in regions with heterogeneous orientation preferences suggests that orientation-independent interactions among local populations of V1 neurons play a critical role in determining their orientation tuning.

Decorrelation of sensory-evoked neuronal responses in rat barrel cortex during postnatal development

The ability to detect and discriminate sensory stimuli greatly improves with age. To better understand the neural basis of perceptual development, we studied the postnatal development of sensory responses in cortical neurons. Specifically, we analyzed neuronal responses to single-whisker deflections in the posteromedial barrel subfield (PMBSF) of the rat primary somatosensory cortex. Responses of PMBSF neurons showed a long onset latency and duration in the first postnatal week, but became fast and transient over the next few weeks. Trial-by-trial variations of single neuron responses did not change systematically with age, whereas the covariation of responses across trials between neurons (noise correlation) was high on postnatal day 5-6 (P5-6), and gradually decreased with age to near zero by P30-31. Computational analyses showed that pooled responses of multiple neurons became more reliable across stimulus trials with age. The period over which these changes occurred corresponds to the period when rats develop a full set of exploratory whisking behavior. We suggest that reduced noise correlation across a population of neurons, in addition to sharpening the temporal characteristics of single neuron responses, may help improve behavioral performance.

Mapping stimulus feature selectivity in macaque V1 by two-photon Ca 2+ imaging: Encoding-model analysis of fluorescence responses to natural movies

ABSTRACT In vivo calcium (Ca2+) imaging using two‐photon microscopy allows activity to be monitored simultaneously from hundreds of individual neurons within a local population. While this allows us to gain important insights into how cortical neurons represent sensory information, factors such as photo‐bleaching of the Ca2+ indicator limit imaging duration (and thus the numbers of stimuli that can be tested), which in turn hampers the full characterization of neuronal response properties. Here, we demonstrate that using an encoding model combined with presentation of natural movies results in detailed characterization of receptive field (RF) properties despite the relatively short time for data collection. During presentation of natural movie clips to macaque monkeys, we recorded fluorescence signals from primary visual cortex (V1) neurons that had been loaded with a Ca2+ indicator. For each recorded neuron, we constructed an encoding model that comprised an array of motion‐energy filters that tiled over the RFs. We optimized the weight of each filters output so that the linear sum of the outputs across the filters mimicked the neurons Ca2+‐signal responses. These models were able to predict the neural responses to a different set of natural movies with a significant degree of accuracy. Moreover, the orientation tunings of neurons simulated by the model were highly correlated with those experimentally obtained when grating stimuli were presented to the monkeys. The model predictions were also consistent with what is known about spatial frequency tunings, the structure of excitatory subfields of RFs (i.e., classical RFs), and functional maps for these RF properties in V1. Further analysis revealed a new aspect of V1 functional architecture; the extent and distribution of suppressive RF subfields varied among nearby neurons, while those for excitatory subfields were shared. Thus, applying our encoding‐model analysis to two‐photon Ca2+ imaging of neuronal responses to natural movies provides a reliable and efficient means of analyzing a wide range of RF properties in multiple neurons imaged in a local region.

Detailed analysis of orientation preference map in visual cortex

Mammalian primary visual cortex (V1) contains a functional map of orientation preference. Within the orientation preference map, neurons aggregate in two different local patterns. Neurons with similar orientation preferences gather within orientation domains, whereas neurons with all different orientation preferences converge at the center of pinwheel-like arrangements of orientation domains. The differences in local organization of domains and pinwheels have been the subject of considerable controversy. Here, we focus on the differences in global organizations of domains and pinwheels. We analyzed the spatial distribution of orientation preferences in wide regions around domains and pinwheels in monkey V1. A particular distribution pattern of orientation preferences was found more clearly in the regions around domains than in the regions around pinwheels. This suggests that neuronal responses to large stimuli outside of a neurons receptive field can vary between domains and pinwheels.