LEARNING AND MEMORY PROCESSES AND THE MODULARITY OF THE BRAIN

We will consider recent evidence for spatial and temporal modularity, as well as structured connectivity in the cortex. These modularities have consequences concerning the “code” of cortical function, i.e., the internal language of the cortex - “how it talks to itself”. In order to understand learning and memory processes in the cortex, we must also investigate this code and suggest that they are crucially dependent. We discuss several spatial and several temporal scales in the cortex, concentrating here on their role in learning and memory. For example, we have proposed that the concept of selective versus instructional learning depends strongly on these modularities, as does the memory storage of large sequential quantities of information as in music. Short-term plasticity in the cortex is discussed: we suggest a key method to induce these effects involves the presentation of spatially and temporally patterned stimuli. We will base much of our remarks on recent results and generalizations of the trion model which is a highly structured mathematical realization of the Mountcastle organizational principle in which the cortical column is the basic neural network of cortex and is comprised of subunit minicolumns, our idealized trions. A columnar network of trions has a large repertoire of quasistable, periodic spatial-temporal firing patterns, MPs, which can be excited. These MPs can be readily enhanced (as well as inherent categories of MPs) by only a small change in connection strengths via a Hebb learning rule. The MPs evolve in natural sequences (related by certain symmetries) from one to another in Monte Carlo probabilistic evolutions. As the synaptic (neurotransmitter) fluctuation parameter B is varied, there exist a series of specific values B(n) giving new repertoires of MPs. The learning properties of the MPs are especially enhanced at these B(n) and the nature of the Monte Carlo evolutions are qualitatively different at the B(n). Learning properties between coupled columnar networks are discussed. A recent testable prediction that an epileptic focus might be eliminated by spatially and temporally patterned electrical stimulation depends crucially on both the modularity of the cortex and the details of the Hebb learning rule.