Brain-wave recognition of sentences

Electrical and magnetic brain waves of two subjects were recorded for the purpose of recognizing which one of 12 sentences or seven words auditorily presented was processed. The analysis consisted of averaging over trials to create prototypes and test samples, to each of which a Fourier transform was applied, followed by filtering and an inverse transformation to the time domain. The filters used were optimal predictive filters, selected for each subject. A still further improvement was obtained by taking differences between recordings of two electrodes to obtain bipolar pairs that then were used for the same analysis. Recognition rates, based on a least-squares criterion, varied, but the best were above 90%. The first words of prototypes of sentences also were cut and pasted to test, at least partially, the invariance of a word’s brain wave in different sentence contexts. The best result was above 80% correct recognition. Test samples made up only of individual trials also were analyzed. The best result was 134 correct of 288 (47%), which is promising, given that the expected recognition number by chance is just 24 (or 8.3%). The work reported in this paper extends our earlier work on brain-wave recognition of words only. The recognition rates reported here further strengthen the case that recordings of electric brain waves of words or sentences, together with extensive mathematical and statistical analysis, can be the basis of new developments in our understanding of brain processing of language.

Description of microcolumnar ensembles in association cortex and their disruption in Alzheimer and Lewy body dementias

The cortex of the brain is organized into clear horizontal layers, laminae, which subserve much of the connectional anatomy of the brain. We hypothesize that there is also a vertical anatomical organization that might subserve local interactions of neuronal functional units, in accord with longstanding electrophysiological observations. We develop and apply a general quantitative method, inspired by analogous methods in condensed matter physics, to examine the anatomical organization of the cortex in human brain. We find, in addition to obvious laminae, anatomical evidence for tightly packed microcolumnar ensembles containing approximately 11 neurons, with a periodicity of about 80 μm. We examine the structural integrity of this new architectural feature in two common dementing illnesses, Alzheimer disease and dementia with Lewy bodies. In Alzheimer disease, there is a dramatic, nearly complete loss of microcolumnar ensemble organization. The relative degree of loss of microcolumnar ensembles is directly proportional to the number of neurofibrillary tangles, but not related to the amount of amyloid-β deposition. In dementia with Lewy bodies, a similar disruption of microcolumnar ensemble architecture occurs despite minimal neuronal loss. These observations show that quantitative analysis of complex cortical architecture can be applied to analyze the anatomical basis of brain disorders.