Biomedical subjects

David A Crowe

Publications and source records attributed to David A Crowe.

9 recordsLinked to original sources

PubMed2005

Dynamics of parietal neural activity during spatial cognitive processing.

Dynamic neural processing unrelated to changes in sensory input or motor output is likely to be a hallmark of cognitive operations. Here we show that neural representations of space in parietal cortex are dynamic while monkeys perform a spatial cognitive operation on a static visual stimulus. We recorded neural activity in area 7a during a visual maze task in which monkeys mentally followed a path without moving their eyes. We found that the direction of the followed path could be recovered from neuronal population activity. When the monkeys covertly processed a path that turned, the population representation of path direction shifted in the direction of the turn. This neural population dynamic took place during a period of unchanging visual input and showed characteristics of both serial and parallel processing. The data suggest that the dynamic evolution of parietal neuronal activity is associated with the progression of spatial cognitive operations.

Action Potentials↗

PubMed2005

Mental maze solving: directional fMRI tuning and population coding in the superior parietal lobule.

The superior parietal lobule (SPL) of six human subjects was imaged at 4 T during mental traversing of a directed maze path. Here we demonstrate the orderly involvement of the SPL in this function, as follows. Forty-two percent of the voxels were tuned with respect to the direction of the maze path. This suggests a coherent tuning of local neuronal populations contributing to the change of the single-voxel BOLD signal. Preferred directions ranged throughout the directional continuum of 360 degrees. Voxels with similar preferred directions tended to cluster together: on average there were seven same-direction clusters per slice, with an average cluster membership of five voxels/cluster and an average nearest-neighbor same-direction intercluster distance of 13.1 mm. On the other hand, the average nearest-neighbor intercluster distance between a given direction and all other directions was 3.1 mm. This suggests a patchy arrangement such that patches of directionally tuned voxels, containing voxels with different preferred directions, alternate with patches of non-tuned voxels. Finally, the population vector predicted accurately the direction of the maze path (with an error of 12.7 degrees), and provided good estimates (with an error of 29 degrees) when calculated within parts of the SPL. Altogether, these findings document a new, orderly functional organization of the SPL with respect to mental tracing.

Adult↗

PubMed2005

Neural correlates of spatial judgement during object construction in parietal cortex.

We recorded the activity of parietal area 7a neurons in monkeys performing an object construction task. In each trial, a model object consisting of a variable arrangement of squares was presented, followed after a delay by a copy of the model object that was missing a single square. Monkeys replaced the missing square to reconstruct the model configuration. Activity of many 7a neurons varied systematically with the position of the missing square and predicted where monkeys were going to add parts to the object they were building. The location of the missing square was a computed spatial datum important to object construction which did not correlate with the retinal location of a visual stimulus or the direction of the required motor response. The population of cells coding this coordinate was generally inactive when the same spatial locations were made relevant by visual targets to which monkeys either planned saccades or directed attention in other behavioral contexts. The data suggest that some parietal neurons participate in neural representations of space that reflect spatial cognitive as opposed to sensorimotor processing, coding the results of spatial computations performed on visual stimuli to meet cognitive objectives.

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PubMed2004

Parietal representation of hand velocity in a copy task.

We recorded neural activity from ensembles of neurons in areas 5 and 2 of parietal cortex, while two monkeys copied triangles, squares, trapezoids, and inverted triangles and used both linear and nonlinear models to predict the hand velocity from the neural activity of the ensembles. The linear model generally outperformed the nonlinear model, suggesting a reasonably linear relation between the neural activity and the hand velocity. We also found that the average transfer function of the linear model fit to individual cells was a low-pass filter because the neural response had considerable high-frequency power, whereas the hand velocity only had power at frequencies below approximately 5 Hz. Increasing the width of the transfer function, up to a width of 700-800 ms, improved the fit of the model. Furthermore, the Rsqr of the linear model improved monotonically with the number of cells in the ensemble, saturating at 60-80% for a filter width of 700 ms. Finally, it was found that including an interaction term, which allowed the transfer function to shift with the eye position, did not improve the fit of the model. Thus ensemble neural responses in superior parietal cortex provide a high-fidelity, linear representation of hand kinematics within our task.

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PubMed2004

Participation of primary motor cortical neurons in a distributed network during maze solution: representation of spatial parameters and time-course comparison with parietal area 7a.

Traditionally, primary motor cortex (M1) has been thought to be involved solely in planning and generating movements. Recent evidence suggests that the arm area of M1 plays a role in other functions, such as the representation of serial order (Pellizzer et al. 1995, Science 269:702-705; Carpenter et al. 1999, Science 283:1752-1757) and spatial processing (Georgopoulos et al. 1989, Science 243:234-236). Previous studies of such cognitive processes have used tasks in which a directed arm movement was required, raising a question as to whether this brain area is involved in cognitive processing per se, or whether such cognitive signals may be gated into the arm area of M1 only when arm movements are required. To study this question, we developed a task that required a spatial analysis of a complex visual stimulus, but required no arm movement as a response. In this task, monkeys were shown an octagonal maze. After an imposed delay of 2 to 2.5 s, they indicated whether a path that emanated from the center of the maze exited at the perimeter (exit maze) or terminated within the maze (no-exit maze) by pressing a pedal with their left or right foot, respectively. We recorded from 785 cells from the arm area of M1 from two monkeys during the delay period of the maze task. We found that cell activity was influenced by both the exit status and the direction of the path, beginning soon after the maze was displayed. This activity was not related to the activation of arm muscles, suggesting that the directional signals observed represented abstract spatial aspects of maze processing. Finally, we compared maze-related activity of M1 neurons with those recorded from posterior parietal area 7a, reported previously (Crowe et al. 2004). Interestingly, cells from each area exhibited similar properties. Both the exit status and path direction were encoded by cells in M1 and 7a, although to different extents. An analysis of the time-course of the neural representation of these factors revealed that area 7a and M1 begin to encode these factors at the same time, suggesting these brain areas are part of a distributed system performing the spatial computations involved in maze solution.

Action Potentials↗

PubMed2004

Neural activity in primate parietal area 7a related to spatial analysis of visual mazes.

Cognitive psychological studies of humans and monkeys solving visual mazes have provided evidence that a covert analysis of the maze takes place during periods of eye fixation interspersed between saccades, or when mazes are solved without eye movements. We investigated the neural basis of this process in posterior parietal cortex by recording the activity of single neurons in area 7a during maze solution. Monkeys were required to determine from a single point of fixation whether a critical path through the maze reached an exit or a blind ending. We found that during this process the activity of approximately one in four neurons in area 7a was spatially tuned to maze path direction. We obtained evidence that path tuning did not reflect a covert saccade plan insofar as the majority of neurons active during maze solution were not active on a delayed-saccade control task, and the minority that were active on both tasks did not exhibit congruent spatial tuning in the two conditions. We also obtained evidence that path tuning during maze solution was not due to the locations of visual receptive fields mapped outside the behavioral context of maze solution, in that receptive field centers and preferred path directions were not spatially aligned. Finally, neurons tuned to path direction were not present in area 7a when a naïve animal viewed the same visual maze stimuli but did not solve them. These data support the hypothesis that path tuning in parietal cortex is not due to the lower level visual features of the maze stimulus, but rather is associated with maze solution, and as such, reflects a cognitive process applied to a complex visual stimulus.

Animals↗

PubMed2003

Neural activity in prefrontal cortex during copying geometrical shapes. I. Single cells encode shape, sequence, and metric parameters.

In drawing a copy of a geometrical shape, a sequence of movements must be produced to represent the sides of the object in the proper spatial relationship. We investigated neural mechanisms of this process by training monkeys to draw (using a joystick) copies of geometrical shapes (triangles, squares, trapezoids and inverted triangles) presented on a video monitor while recording single cell activity in prefrontal cortex. The drawing trajectories monkeys produced were divided into a series of discrete segments, varying in direction and length. We performed a stepwise multiple linear regression analysis to identify those copy parameters significantly influencing cell activity. The copied shape (e.g., triangle, square) and the serial position of the segment within each trajectory were the most prevalent effects (in 46% and 43% of cells, respectively), followed by segment direction (32%) and length (16%). Effects of temporal factors (maximum segment speed and time to maximum segment speed) were less frequent. These results demonstrate that prefrontal neurons encode several spatial and sequence variables that define copy trajectories. We also found that specific groupings of significant effects tended to occur together in single neurons. Specifically, single neurons simultaneously processed the serial position of a segment within each trajectory along with the corresponding spatial (but not temporal) attributes of that segment (i.e., direction and length), as well as with the overall shape to which the segments belong. Finally, we discovered that relationships between neural activity and segment serial position were systematic in many instances, described by monotonically increasing and decreasing functions, as well as parabolic functions. These findings indicate that, within the copying task, the serial segment position is a key factor for neural activity in the periprincipalis area of the prefrontal cortex.

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PubMed2003

Neural activity in prefrontal cortex during copying geometrical shapes. II. Decoding shape segments from neural ensembles.

We trained two monkeys to draw copies of geometrical shapes (e.g. squares, triangles) using a joystick, and found that several variables describing the arm trajectories were encoded in the activity of individual prefrontal neurons (Averbeck et al. 2003). Copy trajectories were drawn as sequences of segments, identified by the serial order in which they were drawn and the shape that they together produced. Here we use linear discriminant analysis to test how well the segments of copied shapes could be decoded from the neural activity patterns of small ensembles (3-22 neurons) of simultaneously recorded cells in prefrontal cortex. Using this analysis, the proper segment (drawn by the monkey) was correctly decoded from the ensemble activity pattern during the drawing of that segment in 60-80% of the cases when the largest ensembles were considered. The information transmitted by these ensembles, as well as by single neurons, was also calculated. We found that the information transmitted by the ensembles increased on average with the number of neurons they contained. Each neuron conveyed information about multiple segments within the drawing trajectory, suggesting that neurons were 'broadly tuned' across segments and that the neural code of segment was distributed.

Action Potentials↗

PubMed2002

Parallel processing of serial movements in prefrontal cortex.

A key idea in Lashley's formulation of the problem of serial order in behavior is the postulated neural representation of all serial elements before the action begins. We studied this question by recording the activity of individual neurons simultaneously in small ensembles in prefrontal cortex while monkeys copied geometrical shapes shown on a screen. Monkeys drew the shapes as sequences of movement segments, and these segments were associated with distinct patterns of neuronal ensemble activity. Here we show that these patterns were present during the time preceding the actual drawing. The rank of the strength of representation of a segment in the neuronal population during this time, as assessed by discriminant analysis, predicted the serial position of the segment in the motor sequence. An analysis of errors in copying and their neural correlates supplied additional evidence for this code and provided a neural basis for Lashley's hypothesis that errors in motor sequences would be most likely to occur when executing elements that had prior representations of nearly equal strength.

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