The direction of frequency-modulated (FM) sweeps is an important temporal cue in animal and human communication. FM direction-selective neurons are found in the primary auditory cortex (A1), but their topography and the mechanisms underlying their selectivity remain largely unknown. Here we report that in the rat A1, direction selectivity is topographically ordered in parallel with characteristic frequency (CF): low CF neurons preferred upward sweeps, whereas high CF neurons preferred downward sweeps. The asymmetry of 'inhibitory sidebands', suppressive regions flanking the tonal receptive field (TRF) of the spike response, also co-varied with CF. In vivo whole-cell recordings showed that the direction selectivity already present in the synaptic inputs was enhanced by cortical synaptic inhibition, which suppressed the synaptic excitation of the non-preferred direction more than that of the preferred. The excitatory and inhibitory synaptic TRFs had identical spectral tuning, but with inhibition delayed relative to excitation. The spectral asymmetry of the synaptic TRFs co-varied with CF, as had direction selectivity and sideband asymmetry, and thus suggested a synaptic mechanism for the shaping of FM direction selectivity and its topographic ordering.

In primary auditory cortex (AI) neurons, tones typically evoke a brief depolarization, which can lead to spiking, followed by a long-lasting hyperpolarization. The extent to which the hyperpolarization is due to synaptic inhibition has remained unclear. Here we report in vivo whole cell voltage-clamp measurements of tone-evoked excitatory and inhibitory synaptic conductances of AI neurons of the pentobarbital-anesthetized rat. Tones evoke an increase of excitatory synaptic conductance, followed by an increase of inhibitory synaptic conductance. The synaptic conductances can account for the gross time course of the typical membrane potential response. Synaptic excitation and inhibition have the same frequency tuning. As tone intensity increases, the amplitudes of synaptic excitation and inhibition increase, and the latency of synaptic excitation decreases. Our data indicate that the interaction of synaptic excitation and inhibition shapes the time course and frequency tuning of the spike responses of AI neurons.

In the mammalian cerebral cortex, neural responses are highly variable during spontaneous activity and sensory stimulation. To explain this variability, the cortex of alert animals has been hypothesized to be in an asynchronous high conductance state in which irregular spiking arises from the convergence of large numbers of uncorrelated excitatory and inhibitory inputs onto individual neurons [1][2][3][4] . Signatures of this state are that a neuron's membrane potential (Vm) hovers just below spike threshold, and its aggregate synaptic input is nearly Gaussian, arising from many uncorrelated inputs [1][2][3][4] . Alternatively, irregular spiking could arise from infrequent correlated input events that elicit large Vm fluctuations 5,6 . To distinguish these hypotheses, we developed a technique to carry out whole-cell Vm measurements from the cortex of behaving monkeys, focusing on primary visual cortex (V1) of monkeys performing a visual fixation task. Contrary to the predictions of an asynchronous state, mean Vm during fixation was far from threshold (14 mV) and spiking was triggered by occasional large spontaneous fluctuations. Distributions of Vm values were skewed beyond that expected for a range of Gaussian input 6,7 , but were consistent with synaptic input arising from infrequent correlated events 5,6 . Furthermore, spontaneous Vm fluctuations were correlated with the surrounding network activity, as reflected in simultaneously recorded nearby local field potential (LFP). Visual stimulation, however, led to responses more consistent with an asynchronous state: mean Vm approached threshold, fluctuations became more Gaussian, and correlations between single neurons and the surrounding network were disrupted. These observations demonstrate that sensory drive can shift a common cortical circuitry from a synchronous to an asynchronous state.Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms Correspondence to: Andrew Y. Y. Tan (atyy@alum.mit.edu) and Nicholas J. Priebe (nico@austin.utexas.edu). * These authors contributed equally to this work. † These authors contributed equally to this work. Author Contributions Competing financial interestsThe authors declare no competing financial interests. HHS Public Access Author Manuscript Author ManuscriptAuthor Manuscript Author ManuscriptCortical neurons exhibit variable activity even after efforts are taken to fix temporal variations in sensory stimuli and attentional state 8 . This ongoing activity affects stimulus encoding and synaptic plasticity 9 , but its neural basis is not well understood. One hypothesis is that the variable activity in alert animals arises from connections between numerous uncorrelated excitatory and inhibitory inputs [1][2][3][4] . Such a network is consistent with studies of neural architecture 10 , and exhibits spiking statistics similar to ...