Extracellular single-unit recordings were made from simple cells in area 17 of anesthetized cats. Cells were tested with drifting gratings under control and adapted conditions. Response amplitude and phase were measured as a function of either contrast or temporal frequency. Adapting not only reduces amplitude, but also retards phase. Adaptation alters the responses of simple cells in a particular way: the onset of the response to each cycle of a sinusoidally modulated stimulus is delayed. Once cells start to respond during each cycle, however, they generally recover to control levels, and the offset of the response is unaffected by adapting. The timing aftereffects are independent of the amplitude aftereffects. Timing aftereffects are tuned around the adapting temporal frequency, with a bias toward lower temporal frequencies. Adaptation thus modifies cortical responses even more specifically then previously thought. Firing rates are depressed primarily at response onset, even after several stimulus cycles have occurred following the end of adapting. Because all cells appear to adapt in this way, the data offer an opportunity to theorize about cortical connectivity. One implication is that inhibition onto a simple cell arises from other simple cells with similar response properties that fire a half-cycle out of phase with the target cell.

On the basis of what is known about the neural circuitry essential or normally involved in eyeblink classical conditioning (EBCC), the pattern of neurodegeneration in Huntington's disease (HD) would not appear to interfere with this type of learning. HD causes severe atrophy of the basal ganglia and thinning and shrinkage of the cerebral cortex. However, the hippocampus and hippocampal cholinergic system remain relatively intact, as does the cerebellum. Because the brain circuitry engaged in EBCC is neither lesioned nor disrupted in HD, it was predicted that HD patients would perform like normal control subjects in the 400-ms delay EBCC paradigm. Performance of seven patients with HD was compared to age-matched normals, with two control subjects matched to each HD patient. There were no differences in production of conditioned responses (CRs) between HD patients and normal control subjects, but the timing of the CR was abnormal in HD. Comparisons of HD patients to patients with other neurodegenerative diseases (probable Alzheimer's disease (PAD) and Down syndrome (DS) over the age of 35 with presumed Alzheimer-like neuropathology) and to patients with cerebellar lesions demonstrated significantly better EBCC performance in HD. Results suggest that the ability to acquire CRs is normal in HD, but the striatum may have some role in optimizing the timing of the CR. (JINS, 1996, 2, 323–334.)

Five lagged cells were recognized by extracellular recording in the lateral geniculate nucleus of an awake, behaving macaque monkey. Previous reports of lagged cells were all in the anesthetized cat. Both parvocellular and magnocellular lagged cells were observed. Response timing was distributed continuously across the population, and both sustained and transient responses were seen in the magnocellular subpopulation. Cortex thus receives signals with a wide range of timing, which can mediate direction selectivity across multiple dimensions.

Simple cells display a specific adaptation aftereffect when tested with drifting gratings. The onset of the response to each cycle of the grating is delayed after adapting, but the offset is unaffected. Testing with stationary bars whose luminance was modulated in time revealed that aftereffects occur only at certain points in both space and time. The aftereffects seen with moving stimuli were predicted from those seen with stationary stimuli. These adaptation experiments suggest a model that consists of mutually inhibitory simple cells that are in spatiotemporal quadrature. The inhibition is appropriately localized in space and time to create the observed aftereffects. In this model, inhibition onto direction-selective simple cells arises from simple cells with the same preferred direction.

Previous studies of cat visual cortex have shown that the spatiotemporal (S-T) structure of simple cell receptive fields correlates with direction selectivity. However, great heterogeneity exists in the relationship and this has implications for models. Here we report a laminar basis for some of the heterogeneity. S-T structure and direction selectivity were measured in 101 cells using stationary counterphasing and drifting gratings, respectively. Two procedures were used to assess S-T structure and its relation to direction selectivity. In the first, the S-T orientations of receptive fields were quantified by fitting response temporal phase versus stimulus spatial phase data. In the second procedure, conventional linear predictions of direction selectivity were computed from the amplitudes and phases of responses to stationary gratings. Extracellular recording locations were reconstructed histologically. Among direction-selective cells, S-T orientation was greatest in layer 4B and it correlated well (r = 0.76) with direction selectivity. In layer 6, S-T orientation was uniformly low, overlapping little with layer 4B, and it was not correlated with directional tuning. Layer 4A was intermediate in S-T orientation and its relation (r = 0.46) to direction selectivity. The same laminar patterns were observed using conventional linear predictions. The patterns do not reflect laminar differences in direction selectivity since the layers were equivalent in directional tuning. We also evaluated a model of linear spatiotemporal summation followed by a static nonlinear amplification (exponent model) to account for direction selectivity. The values of the exponents were estimated from differences between linearly predicted and actual amplitude modulations to counterphasing gratings. Comparing these exponents with another exponent—that required to obtain perfect matches between linearly predicted and measured directional tuning—indicates that an exponent model largely accounts for direction selectivity in most cells in layer 4, particularly layer 4B, but not in layer 6. Dynamic nonlinearities seem essential for cells in layer 6. We suggest that these laminar differences may partly reflect the differential involvement of geniculocortical and intracortical mechanisms.