Biomedical subjects

T Lelekov

Publications and source records attributed to T Lelekov.

3 recordsLinked to original sources

PubMed2000

Cognitive sequence processing and syntactic comprehension in schizophrenia.

It has been repeatedly demonstrated that schizophrenic patients are impaired in the comprehension of sentences with complex syntax. We investigated the hypothesis that this syntactic comprehension impairment in schizophrenia is not a purely linguistic dysfunction, but rather the reflection of a cognitive sequence processing impairment that is revealed as task complexity increases. We tested 10 schizophrenic patients using a standard measure of syntactic comprehension, and a non-linguistic sequence processing task, both of which required simple and complex transformation processing. Patients' performance impairment on the two tasks was highly correlated (r2 = 0.84), and there was a significant effect for complexity, independent of the task. These results are quite similar to those of aphasic patients with left hemisphere lesions. This suggests that syntactic comprehension deficits in schizophrenia reveal the dysfunction of cognitive sequence processing mechanisms that can be expressed both in linguistic and non-linguistic sequence tasks.

Adult↗

PubMed2000

Dissociable ERP profiles for processing rules vs instances in a cognitive sequencing task.

A hotly debated question in cognitive neuroscience is whether individual instances of perceptual sequences, and the rules that describe them, are processed by the same brain mechanisms. We tested the hypothesis that such rules and instances are processed by dissociable brain mechanisms. We analyzed event-related brain potentials (ERPs) evoked during cognitive sequencing tasks that assessed surface (instance) vs abstract (rule) structure learning. Sequence instances ABCBAC and DEFEDF have different serial order or surface structure, but share the same rule or abstract structure, 123213. Nine healthy subjects were first trained to learn a set of surface and abstract structures in sequences of visually presented stimuli. During the subsequent ERP recording, for surface and abstract structures, they then discriminated between acceptable and unacceptable sequences, based on the pre-learned regularities. Abstract structure processing evoked a late positivity around 500 ms, which was not seen in the surface structure processing, supporting our hypothesis of dissociable processes. We discuss implications for the rule vs instance debate, and similarities between this late positivity and the P600 observed in previous studies of syntactic processing.

Adult↗

PubMed1998

Dissociable processes for learning the surface structure and abstract structure of sensorimotor sequences.

A sensorimotor sequence may contain information structure at several different levels. In this study, we investigated the hypothesis that two dissociable processes are required for the learning of surface structure and abstract structure, respectively, of sensorimotor sequences. Surface structure is the simple serial order of the sequence elements, whereas abstract structure is defined by relationships between repeating sequence elements. Thus, sequences ABCBAC and DEFEDF have different surface structures but share a common abstract structure, 123213, and are therefore isomorphic. Our simulations of sequence learning performance in serial reaction time (SRT) tasks demonstrated that (1) an existing model of the primate fronto-striatal system is capable of learning surface structure but fails to learn abstract structure, which requires an additional capability, (2) surface and abstract structure can be learned independently by these independent processes, and (3) only abstract structure transfers to isomorphic sequences. We tested these predictions in human subjects. For a sequence with predictable surface and abstract structure, subjects in either explicit or implicit conditions learn the surface structure, but only explicit subjects learn and transfer the abstract structure. For sequences with only abstract structure, learning and transfer of this structure occurs only in the explicit group. These results are parallel to those from the simulations and support our dissociable process hypothesis. Based on the synthesis of the current simulation and empirical results with our previous neuropsychological findings, we propose a neuro-physiological basis for these dissociable processes: Surface structure can be learned by processes that operate under implicit conditions and rely on the fronto-striatal system, whereas learning abstract structure requires a more explicit activation of dissociable processes that rely on a distributed network that includes the left anterior cortex.

Computer Simulation↗