The Role of Motor Activity in Insight Problem Solving (the Case of the Nine-Dot Problem).

Attempts to estimate the contribution made by motor activity to insight problem solving is hindered by a lack of detailed description of motor behavior. The goal of this study was to develop and put to the test a novel method for studying the dynamics of insight problem solving based on a quantitative analysis of ongoing motor activity. As a proper problem model, we chose the nine-dot problem (Maier, 1930), in which solvers had to draw a sequence of connected line segments. Instead of using the traditional pen-and-paper way of solving the nine-dot problem we asked participants to use their index finger to draw line segments on the surface of a tablet computer. We are arguing that successful studying of the role of motor activity during problem solving requires the distinction between its instrumental and functional role. We considered the functional role on the motor activity as closely related to the on-line mode of motor planning. The goal of Experiment 1 was to explore the potential power of the method and, at the same time, to assay the patterns of motor activity related to on-line and off-line modes of motor planning. Experiments 2 and 3 were designed to uncover the potential impact of preliminary motor training on the motor output of successful and unsuccessful problem solvers. In these experiments, we tested hypotheses on how preliminary motor training, which presumably played a functional role in Experiment 2 and an instrumental role in Experiment 3, affects the motor activity of a problem solver and hence their effectiveness in solving the problem. The three experiments showed consistent results. They suggest that successful solving of the nine-dot problem relies upon the functional role of motor activity and requires both off-line and on-line modes of motor planning, with the latter helping to overcome the perceptual constraints imposed by a spatial arrangement of the nine dots. The method that we applied allows for systematic comparison between successful and unsuccessful problem solvers based on the quantitative parameters of their motor activity. Through it, we found new specific patterns of motor activity that differentiate successful and unsuccessful solvers.

Neurons in cat V1 show significant clustering by degree of tuning.

Neighboring neurons in cat primary visual cortex (V1) have similar preferred orientation, direction, and spatial frequency. How diverse is their degree of tuning for these properties? To address this, we used single-tetrode recordings to simultaneously isolate multiple cells at single recording sites and record their responses to flashed and drifting gratings of multiple orientations, spatial frequencies, and, for drifting gratings, directions. Orientation tuning width, spatial frequency tuning width, and direction selectivity index (DSI) all showed significant clustering: pairs of neurons recorded at a single site were significantly more similar in each of these properties than pairs of neurons from different recording sites. The strength of the clustering was generally modest. The percent decrease in the median difference between pairs from the same site, relative to pairs from different sites, was as follows: for different measures of orientation tuning width, 29-35% (drifting gratings) or 15-25% (flashed gratings); for DSI, 24%; and for spatial frequency tuning width measured in octaves, 8% (drifting gratings). The clusterings of all of these measures were much weaker than for preferred orientation (68% decrease) but comparable to that seen for preferred spatial frequency in response to drifting gratings (26%). For the above properties, little difference in clustering was seen between simple and complex cells. In studies of spatial frequency tuning to flashed gratings, strong clustering was seen among simple-cell pairs for tuning width (70% decrease) and preferred frequency (71% decrease), whereas no clustering was seen for simple-complex or complex-complex cell pairs.

Adaptive filtering enhances information transmission in visual cortex.

Sensory neuroscience seeks to understand how the brain encodes natural environments. However, neural coding has largely been studied using simplified stimuli. In order to assess whether the brain's coding strategy depends on the stimulus ensemble, we apply a new information-theoretic method that allows unbiased calculation of neural filters (receptive fields) from responses to natural scenes or other complex signals with strong multipoint correlations. In the cat primary visual cortex we compare responses to natural inputs with those to noise inputs matched for luminance and contrast. We find that neural filters adaptively change with the input ensemble so as to increase the information carried by the neural response about the filtered stimulus. Adaptation affects the spatial frequency composition of the filter, enhancing sensitivity to under-represented frequencies in agreement with optimal encoding arguments. Adaptation occurs over 40 s to many minutes, longer than most previously reported forms of adaptation.