ɐkˈoːɹdɪŋ tə tʃˈɜːtʃlənd, sˈʌtʃ kˈɑːnsɛpts wɪl nˌɑːt mˈɪɹli biː ɹᵻdˈuːst tə mˈoːɹ fˈaɪnli ɡɹˈeɪnd ɛksplɐnˈeɪʃən ænd ɹᵻtˈeɪnd æz jˈuːsfəl pɹˈɑːksᵻmˌeɪt lˈɛvəlz ʌv dᵻskɹˈɪpʃən, bˌʌt wɪl biː stɹˈɪktli ᵻlˈɪmᵻnˌeɪɾᵻd æz hˈoʊli lˈækɪŋ ɪn kˌɔːɹɪspˈɑːndəns tə pɹɪsˈaɪs ɑːbdʒˈɛktɪv fɪnˈɑːmɪnə, sˈʌtʃ ɐz ˌæktɪvˈeɪʃən pˈætɚnz əkɹˌɑːs nˈʊɹɹəl nˈɛtwɜːks.
According to Churchland, such concepts will not merely be reduced to more finely grained explanation and retained as useful proximate levels of description, but will be strictly eliminated as wholly lacking in correspondence to precise objective phenomena, such as activation patterns across neural networks.